INDUSTRIAL RESTRUCTURING AND SPATIAL DEVELOPMENT IN THE KOREAN MANUFACTURING INDUSTRY, 1983-1993 BY Won Sup Lee A DISSERTATION Submitted to Michigan State University in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY Department of Geography 1998 ABSTRACT INDUSTRIAL RESTRUCTURING AND SPATIAL DEVELOPMENT IN THE KOREAN MANUFACTURING INDUSTRY, 1983-1993 BY Won Sup Lee This study examines the spatial aspects of industrial restructuring in Korea during the period of 1983 to 1993. Changes in industrial location, regional productivity, and spatial inequalities in location and productivity are analyzed using both descriptive and statistical methods. Analysis of changes in industrial location reveals a new trend of decentralization toward formerly less developed regions. Regional productivity shows a strong association with regional hierarchies. A trade-off relationship between industrialization and regional productivity indicates the importance of improvement of productive efficiencies in new industrializing areas. Analysis of spatial inequality supports the convergence hypotheses, both in terms of location and productivity. Thus, industrial restructuring provides an opportunity for more balanced territorial development in Korea. To my parents for their dedication to my education To beloved Daiok, my wife, Hosuk and Helen iii ACKNOWLEDGEMENTS First of all, I would like to express my appreciation to my advisor, Dr. Bruce Wm. Pigozzi, for his invaluable comments and criticism of the research proposal, as well as the dissertation, and my guidance committee, Dr. Mehretu, Dr. Manson, and Dean Corey for their friendship and encouragement. I also would like to thank Dr. Randall Schaetzl for arranging financial assistance, and Ms. Sharon Ruggles for her kind assistance. I give special thanks to Dr. Judy Olson who taught me a lot of basic techniques on graduate level study through the research design class. I especially appreciate Jim Biles for his excellent editorial help in the preparation of this dissertation. Last, I thank Mr. Changhyun Kim, my colleague at the KRIHS, for his help in data collection. iv TABLE OF CONTENTS LIST OF TABLES LIST OF FIGURES CHAPTER 1 INTRODUCTION ...................................................................... -- Problem Statement ...................................................... - Research Purposes mmmmmmmmmmmmmmmmmmmmmmm" ..... Significance of the Research ................................ CHAPTER 2 INDUSTRIAL RESTRUCTURING AND LOCATION CHANGE ................... Industrial Restructuring and Space mm. ...................................... Explanations of Location Change ...................................................... Factors of Industrial Location Change H. u“--.-- Hypotheses ..................................................................................................................... Methods of Research ........................................... - Location Quotient ................................... . ........ Regression Analysis ................................................ CHAPTER 3 INDUSTRIAL RESTRUCTURING AND REGIONAL PRODUCTIVITY mmmm Industrial Restructuring and Productivity ........................ Spatial Variation of Productivity ................................................ Determinants of Regional Productivity .................................... Productivity as a Source of Industrial Growth mmmm Hypotheses ..................................................................................................................... Methods of Research .......................................................................................... Indices of Productivity mmmmmmmm; ...................................... Growth Accounting Model ............................................................... Regression Analysis ........................................................................... CHAPTER 4 INDUSTRIAL RESTRUCTURING AND SPATIAL INEQUALITY ..................... Industrial Restructuring and Inequalities in Location ........................................................................................................................... Spatial Convergence and/or Divergence .................................... cybuare 9 12 20 25 3O 30 31 35 35 37 42 47 50 53 53 55 56 58 6O Polarization Reversal .................................................................................... 64 Inequalities in Regional Productivity .................................... 68 Hypotheses ..................................................................................................................... 73 Methods of Research mmmmmmmmmmmmmmmmm. ...................................... 74 Inequality Measures ........................................................................... 74 Regression Analysis ........................................................................... 77 CHAPTER 5 RESEARCH DATA ........................................................................................................................ 79 CHAPTER 6 RESULTS OF ANALYSIS ......................................................................................................... 84 Industrial Restructuring and Location .................................... 84 Industrial Location ..................................... .u .. 84 Results of Regression Analysis ............................................. 109 Regional Productivity -mmmm. ." H. 118 Growth of Output and Input Factors .............................. 118 Spatial Pattern of Productivity ....................................... 125 Sources of Regional Manufacturing Growth ............ 135 Sources of Labor Productivity Growth ........................ 139 Determinants of Regional Productivity ..................... 142 Spatial Inequality .................................................. -z .................. 147 Inequalities in Industrial Location ........................... 148 Inequalities in Regional Productivity ..................... 153 CHAPTER 7 CONCLUSION .uu-". ............................................................... 157 Conclusions .................................................................................................................. 157 Future Research Areas ............................................ .u--"m- 165 APPENDICES .................................................................................................................................... 169 BIBLIOGRAPHY .............................................................................................................................. 174 vi Table Table Table Table Table Table Table Table Table Table Table Table Table Table 10 11 12 13 14 LIST OF TABLES Major Indices of Manufacturing Industry ............... 85 Industrial Location Change by Urban and Rural Region mmmmmmmmmmmmmmmmmmmmmmmmm. ...................................... 88 Industrial Location Change by Industrialization and Core-Periphery .............................................................................. 95 Regional Types and Patterns of Industrialization (1983—88) 102 ooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooo Regional Types and Patterns of Industrialization (1988-93) ..................................................... 103 Test of Regional Effect on Location Change ...... 111 Test of the Factors of Employment Change ............ 114 Growth of Manufacturing Output and Input (Percent Per Annum) ...................................................................................................... 120 Indices of Regional Productivity .................................... 127 Sources of Manufacturing Output Growth (Percent Per Annum) ................................................................................................... 136 Sources of Labor Productivity Growth (Percent Per Annum) ................................................................................................... 141 Test of the Determinants of Regional Productivity ............................................................................................. 143 Change in Regional Inequality .......................................... 149 Test of Spatial Convergence ................................................ 152 vii Table 15 - Summary of Results ........................................................................... 156 viii Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure 10 ll 12 13 14 15 16 17 18 19 LIST OF FIGURES Research Area .......................................................................................... 80 Change in Employment (1983-1988) ................................. 89 Change in Employment (1988-1993) 89 Change in Location Quotient (1983-1988) ............ 91 Change in Location Quotient (1988-1993) ............ 91 Growth of Employment (1983-1988) ................................. 104 Growth of Employment (1988-1993) ................................. 104 Location Quotient (1983) ......................................................... 108 Location Quotient (1993) ......................................................... 108 Growth of Output (1983-1988) .......................................... 121 Growth of Output (1988-1993) .......................................... 121 Growth of Capital Stock (1983-1988) ..................... 124 Growth of Capital Stock (1988-1993) . 124 Labor Productivity (1983) . 128 Labor Productivity (1993) ................................................... 128 Capital Productivity (1983) ............................................. 130 Capital Productivity (1993) ............................................. 130 Nominal Total Factor Productivity (1983) ...... 134 Nominal Total Factor Productivity (1993) ...... 134 ix Figure 20 - Growth of TFP Figure 21 - Growth of TFP (1983-1988) (1988-1993) Chapter 1 INTRODUCTION Problem Statement Korean manufacturing, once considered the locomotive for the unprecedented rapid economic development of the country, has been undergoing significant structural changes since the late 19805. Traditionally, the competitive advantage of Korean manufacturing industry has centered on labor, both quantitatively and qualitatively. Industrial development strategy relying on labor cost advantages is no longer considered a viable means for sustained economic development during this period of fierce international competition. The size of manufacturing employment has decreased since 1988 following three decades of expansion. Political democratization after the late 19803, coupled with the widespread shortage of labor, has been followed by rapid wage increases. In a very short period, Korean manufacturing has witnessed the rapid erosion of one of its major sources of international competitiveness. Therefore, recent industrial restructuring could be understood as an effort to search for new sources of development. Expanded investment in research and development, introduction of advanced l production systems and business organizations, and new locational trends exemplify such efforts (Kim, 1995; Park, 1995, Webber, 1995). Industrial location has been an important determinant of spatial development in Korea. Industrial location has configured the geography of economic well-being of the country for the past three decades. Unfortunately, Korean industrialization has exhibited a classic example of polarized development, corresponding to a general pattern in most developing economies' spatial economy (Meyer and Min, 1987; Nam, 1990). Existing major urban centers, as well as selective growth poles, have been major beneficiaries of economic development. Most rural areas and cities in depressed regions have been the source of labor for the growing regions. Thus, regional economic disparities, with few exceptions, can be viewed as synonymous with disparities in industrial location. Lack of an industrial base has been considered a primary indicator of depressed areas when primary or tertiary activities cannot provide propulsive impetus for regional economies. With limited resources available for national economic development, industrial location became selective in utilizing locational advantages of certain regions. Thus, significant regional disparities have emerged since the initiation of industrial development in the early 19605. It is also argued that spatial inequality will exist in regional productivity. The basis of this statement is that insufficient socioeconomic infrastructure in less developed regions will affect those regions’ capacities for technological development. In addition, spatial concentration of research and development facilities, institutions of higher education, and advanced business services is greater than that of industrial location (KRIHS, 1993). Some conditions necessary for reducing spatial disparities, at least in terms of industrial location, have been developed since the late 19805. Most importantly, a number of urban diseconomies have significantly reduced the attractiveness of urban areas as the locus of industrial activities. Rapidly rising land prices and land shortages, housing problems, high wages, severe traffic congestion, and environment regulations have forced urban industries to move beyond city limits, or even to foreign countries. In contrast, rural regions, with improved transportation and communication accessibility and abundant cheap land, have begun to attract industrial investment. Regional policies provided additional motivation for the dispersion of manufacturing industries by providing assistance and subsidies in various forms. There is an urgent need to investigate how industrial restructuring has affected spatial patterns and processes of industrial location, manufacturing productivity, and inequalities in location and productivity. Rnsoarch Purposes This research will investigate the nature and processes of industrial restructuring in Korea, from a spatial perspective, during the span of 1983 to 1993. The research will focus on three aspects of spatial restructuring of manufacturing industry: location, productivity, and inequality. First, the research examines the changes in industrial location. Emphasis will be placed on the examination of the premise that recent restructuring has brought about deconcentration of industrial location. Locational decentralization has been considered characteristic of developed countries. The regional shift of industrial location from advanced regions toward less developed areas will be examined using the location quotient and regression analysis. Differential performance by different types of regions will be identified. A set of factors will be introduced and tested to explain locational changes. Second, this study examines the effect of industrial restructuring on changes in regional productivity. If industrial restructuring has brought about the redistribution of production factors over space, regional productivity should have changed. Some regions might have lost employment but managed to compensate for this loss by capital investment as an alternative source of industrial growth, while others may have experienced growth in both employment and capital stock. Regional labor and capital productivity will be directly affected by theSe locational changes. In recent years, the importance of technological advances has been emphasized as a means to improve the quality of products and competitiveness. A growth accounting model will be employed to measure the technical improvement of production and explain the sources of growth in manufacturing output. Again, factors that are related to changes in regional productivity will be tested. The analysis of regional productivity will provide some answers about how Korean manufacturing industries have adjusted to a rapidly changing industrial environment. Finally, this research addresses disparities in manufacturing location and regional productivity. The magnitude of spatial reallocation of production factors and resulting changes in regional productivity determine the extent of regional inequality. This study tests, in Korean context, the basic principles of two alternative approaches to spatial disparities. Neoclassical regional development theories, assuming free factor mobility within a capitalist market mechanism, predict the emergence of interregional convergence, whereas structural approaches, based on the principles of cumulative causation, argue that spatial disparities increase as a result of capitalist restructuring. Two indices of inequality and a simple regression model will be employed to test the theme of inter-regional convergence or divergence. Significance of the Research A dominant paradigm in the research of industrial location in developing economies, including Korea, has focused on spatial disparities. Spatial concentration or polarization, rather than decentralization or polarization reversal, characterizes the pattern of spatial development in developing economies. Although few scholars have proposed polarization reversal of population and industries in the context of developing countries’, their evidence has largely been confined to areas in, or around, primary cities rather than whole nation (Storper, 1984; Townroe and Keen, 1984). It is no surprise that Korea was noted as an exemplary case of polarization reversal as early as in the 19705, when Seoul, the capital city of the country, began to lose its national share of manufacturing employment (Richardson, 1980). However, if polarization reversal had really occurred, there would have been no need to implement strong industrial decentralization policies during the 19805 and 19905. On the contrary, regional development plans or national industrial location policies have assumed that manufacturing is far from evenly distributed over space (Kim and Mills, 1990). A series of government guided industrial location policies has been very effective in developing a group of industrial growth centers away from the Seoul metropolitan region. However, decentralization of industrial location, an important goal of the development of growth centers, for the most part, has been limited to urban areas and their surrounding rural counties (Lee and Choe, 1990). This research focuses on the most recent spatial process of industrial location, specifically when the nation is losing manufacturing employment. The effect of industrial restructuring on industrial location, as well as regional productivity, is virtually unknown in Korea. In western developed countries, restructuring has brought about significant changes in industrial location and regional development. Such dramatic reconfiguration of industrial location might have not occurred in Korea, considering differences in the history of industrialization, industrial structure, labor market conditions, and technology. However, the rapidly changing international competitiveness of Korean industries will have impacts on communities where manufacturing is the primary source of regional development. In addition, changing regional factor market conditions for land, labor and capital inevitably alter regional potential for the locus of manufacturing industries. New patterns of industrial location affect regional productivity through the distribution of production inputs and output between urban and rural areas, and between the center and the periphery. Productivity is considered one of the best measures of competitiveness. Thus, the productivity performance of regional industries is an important determinant of regional wealth and development. Literature focusing on regional productivity in Korea is hard to find. Most existing productivity studies examine national and sectoral level data, accounting for the performance of Korean industry during the period of rapid growth between the 19605 and 19805. The lack of regional studies is not limited to Korea, but is also true for other developing countries. The current study will contribute to the geographic literature by conceptualizing the relationship between changes in industrial location and productivity, especially in the context of developing economies. In addition, the incorporation of productivity into traditional geographic research agendas, such as location and inequality, will expand our understanding of spatial processes of industrial restructuring and their consequences for national industrial development. The following three chapters review the theoretical background and empirical studies on the three key subjects of this research: industrial location (Chapter 2), regional productivity (Chapter 3), and spatial inequality (Chapter 4). Based on the review of literature, research hypotheses are developed and the methods of analysis are presented. Chapter 5 explains the spatial scope of the research and discusses data availability, problems, and procedures involved in addressing problems. Chapter 6 presents the results of the analysis. The last chapter provides a conclusion and proposes future directions of research. Chapter 2 INDUSTRIAL RESTRUCTURING AND LOCATION CHANGE Industrial Restructuring and Space The history of capitalism has shown a sequence of development patterns based on different modes of production, which is often called the regime of accumulation. Industrial restructuring, from this viewpoint, can be understood as a response to structural crisis in capitalist development, whether it was caused by the fluctuation of business cycles or the fundamental limit of capitalism (Bradburry, 1985; Castells, 1985). Capitalist restructuring aims to restore profitability through a reorganization of the production process (Soja et. al., 1983). The shift toward a new production system results in a break in the secular trend of accumulation, although it is arguable whether the transition can be clearly distinguished in chronological order, or the shift occurs through the process of gradual adjustment (Beauregard, 1989). In general, industrial restructuring is characterized by rationalization of production process, reduction of employment, and a rise in productivity and profit rate (Vazquez-Barguero, 1990). 10 Each production system has its own geographical character. The spatial structure of the Fordist accumulation system (or Fordism) is associated with a series of great industrial agglomeration in core industrial regions. The main reason for this spatial concentration is to utilize economies of scale and scope, both internally and externally (Rodriguez-Pose, 1994; Scott, 1988b). The traditional spatial production system has dissolved into a new spatial system since the Fordist system entered into crisis during the late 19605 and early 19705 (Scott, 1988a; 1988b). A series of new industrial spaces has emerged away from traditional industrial complexes, reshaping the spatial system of production. Literature from advanced economies reveals significant changes in spatial development during industrial restructuring (Noyelle, 1983; Scott and Storper, 1992). Recent locational change in manufacturing industry can be characterized by single word decentralization. New manufacturing locations include suburban areas of metropolitan centers, smaller cities and peripheral rural regions. In contrast, traditional industrial centers have experienced a significant loss of production employment (Keeble, 1976). The driving force for these locational tendencies was to reduce factor costs through lower labor and land costs in new industrial spaces. Thus, space is used as an instrument in the process of restructuring. 11 The geographical dispersion of manufacturing industry has been associated with increased capital mobility, plant closure and relocation, and the development of subcontracting networks (Soja, et. al., 1983). Increasingly footloose capital can be free from traditional locational constraints due to technological innovations in transport, communications, and production (Fainstein and Fainstein, 1989). Thus, flexible production sectors found in new industrial spaces are relatively independent of the agglomeration economies of old Fordist industrial centers, such as linkages to mass production complexes and labor skills (Storper, 1990). This locational independence has been the result of the new sectors' changed skill requirement of the labor force (Massey and Meagan, 1978). Not all localities have benefited from the new locational tendencies. The impact of economic restructuring has been uneven as capital tended to accumulate in some sites at the expense of others. To some scholars, unequal spatial development is a necessary condition for the accumulation of capital and is the logical outcome of capitalist restructuring (Beauregard, 1989; Bradburry, 1985; Harvey, 1982). Recent empirical studies indicate that deindustrialization theories based on the post-Fordist framework oversimplified industrial transition in older manufacturing regions. Pollard and Storper (1996), in their research on US metropolitan areas, pointed out that the 12 pathway to regional development is multiple; neither the European-style post-Fordist manufacturing sector nor highly specialized urban information economies explains American metropolitan growth in the 19905. Fielding (1994) found that the overall spatial structure of employment and population distribution in Europe did not show any significant shift in spite of fundamental changes in the production system. In addition, older Fordist manufacturing regions are undergoing a fundamental economic transformation by adopting new production systems to existing industries. Florida (1996) recognized these processes as regional creative destruction. The strenuous effort to preserve long-standing comparative advantage has contributed to regenerate industries in new localities within the old industrial regions (Brown et. al., 1996). Explanations of Location Change A variety of concepts have been proposed to explain emerging patterns of industrial location, including nonmetropolitan industrialization, urban-rural shift, Snowbelt-Sunbelt shift, filtering down, spill-over, and so on. These relatively new (compared to two centuries of industrialization) locational tendencies revealed a significant departure from the classic pattern of urban concentration. There has been a realignment of the core- periphery relationship in production as industrial heartlands lost competitive advantage to the newly growing 13 industrial spaces in formerly peripheral regions. The decentralization of manufacturing location, in turn, has contributed to reverse the long-lasting population out- migration from smaller settlement systems (Lonsdale, 1979). As a result, the classic center-periphery model of industrial development no longer accurately depicts recent trends. These patterns of spatial restructuring in advanced industrialized countries have been observed in recently industrialized nations in the Southern part of Europe as well (Vazquez-Barquero, 1990). In these countries also, spatial diffusion of manufacturing industry, from core areas toward less industrialized regions, is transforming a long- lasting territorial hierarchy. One widely held belief is that nonmetropolitan industrialization or industrial decentralization is a normal process of industrial development in advanced economies (Lonsdale, 1979). Product-cycle theory, assuming a close relationship between industrial location and the stage of economic development, explains locational decentralization using the filtering down process (Erickson, 1976; Erickson and Leinbach, 1979; Rees, 1979). Three distinct phases in the development of production processes and resulting locational patterns were identified. In the first phase, when an industrial product is introduced, location is highly concentrated in high technology regions or large urban areas in order to utilize the pool of skilled labor and a variety of external l4 economies in these areas. During the following phase, when the demand for the product increases rapidly, production is transformed into a mass production method. The new locational requirement for these growing industries is low costs sites, typically smaller urban areas. During the final stage of the product-cycle, the production process becomes standardized and routinized, with less reliance on technology as well as agglomeration economies or economies of scope. Production can be most effectively done by branch plants located in different nonmetropolitan areas that provide advantages in assembly costs. Therefore, the spatial filtering down process reflects firms’ locational strategy to reduce production costs, thus enhancing competitiveness. It was noted that differential settlement size offers different competitive advantage. Thus, the spatial division of labor in manufacturing activities is manifested through regional hierarchies (Moriarty, 1991). Regions at lower levels of the hierarchy have advantages in standardized production whereas those at upper levels have competitive edges in newly growing high technology industries (Norton and Rees, 1979). In addition, there is an order in the spatial filtering process. Within rural regions, areas that are adjacent to metropolitan centers tend to grow faster than non-adjacent rural areas (Haynes and Machunda, 1987). External economies can emerge in peripheries as industrial agglomeration stimulates the creation of local linkages and social infrastructure. They promote further industrial 15 accumulation in these areas (Rees, 1979). One negative aspect of nonmetropolitan or rural industrialization is that slow growing industries attracted to smaller communities contribute little to the improvement of skills and wages, even if they provide jobs for unemployed labor during periods of slow growth (Thomas and Leinbach, 1981). A recent study (Wojan and Pulver, 1995) raised questions about the general accountability of location theories based on the product cycle and filtering down process. They concluded that there is no linear relationship between regional hierarchies and locational potentials. In many cases, more remote areas had a wider range of business services than those adjacent to larger urban areas. Thus, existing theories are unduly pessimistic about the prospect of economic development of nonmetropolitan areas. On the contrary, high technology industries can do well in smaller communities. They also tend to decentralize toward peripheries as they mature and production processes are standardized. This occurs when access to urbanization economies such as specialized inputs, research facilities and skilled labor market are no longer the primary conditions for the location of high technology industries (Barkley, 1988). Following Keeble, et. al. (1983), there are three major explanatory frameworks for the decentralization of industrial location. The first approach, the production cost explanation, highlights cost difference as the mechanism for 16 locational shifts from urban to rural regions. In general, urban locations have higher operating costs, including wages and salaries, and factory rents. High production costs in urban areas reduce competitiveness, resulting in lower profitability. This decentralizes urban industries to rural settlements. The cost advantage explanation of new industrial space is not limited to urban to rural shift, but can be applied at different regional scales. Chinitz (1986) cites the cost pull of the Southern US states as the main force for the locational shift of US manufacturing. The South has lower labor costs, lower operating costs, lower local taxes, and a higher level of subsidies for capital investment, physical facilities and worker training, compared to the North. Carlino and Mills (1987) also emphasize the importance of the spatial variation of production costs for the regional shift of manufacturing employment. Urban disadvantages in production costs are represented by agglomeration diseconomies. Agglomeration of manufacturing firms and employment in urban areas has a positive impact on productivity, but after a certain level, deglomerative forces come into being due to diseconomies from congestion, rising land costs, lack of space, high wages, labor conflicts, etc (Hakanson and Danielsson, 1985; Haynes and Machunda, 1987). Therefore, larger metropolitan centers are more prone to losing manufacturing industries. A decline in the strength of relationship between urban l7 hierarchies and manufacturing employment density might reflect the diseconomies of large cities (Moriarty, 1991). The second approach, constrained location theory, focuses on the physical constraints of urban location. Urban place has limited space available for factory expansion, which acts as a ceiling on industrial growth. Thus, for further extension of production capacity, firms need to move out to suburban or rural areas or to displace labor for machinery. In either case, urban manufacturing employment decreases. Tulpule (1969) proposed a series of hypotheses based on physical constraints of urban location. Growing firms need larger factory site to accommodate new machinery to increase output. Thus, industries requiring more space tend to locate in rural areas where land is readily available at lower costs. Two basic conditions need to be met for this dispersion to occur. First, urban areas have to be saturated, thus land supply is short and rent is high. Second, the accessibility of rural areas has to be improved by such means as the development of modern transportation and communication system including information technology. Accepting the basic principles of constrained location theory, the following causal relationships can be expected: 1) A negative relationship between land price and manufacturing employment growth; 2) A negative relationship between the initial density of manufacturing employment and following growth rates; and 18 3) A positive relationship between the capital-output ratio and the tendency toward rural location. Fothergill et al. (1987) examined the relationship between employment change and space availability. They found that regions with higher proportions of old buildings and heavily built-up sites with little room for expansion were associated with larger employment losses. Scott (1982) also considered the lack of space in central cities an important motivation for the industrial dispersion to peripheral areas. Thus, capital intensive firms tend to locate at peripheral areas where cheap land is available for horizontal plant layouts, while labor intensive (and competitive) firms concentrate at the center of metropolitan labor markets. The decentralization tendency is stronger when new investment strategies attempt to replace labor with machinery. The last approach, capitalist restructuring theory, emphasizes capital mobility and flexible production system as the explanation of spatial shift of industrial location. The spatial restructuring is an attempt to recover profitability by reducing factor costs. Especially, the existence of exploitable, unskilled and low cost labor is one of primary locational factors at international scale. Capital employs a variety of strategies to reorganize the production system over space due to its increased mobility and technical innovation. As a result, the range and scope of spatial forms of production organization have greatly 19 increased (Hudson, 1988). An increasingly footloose capital freed from locational constraints more easily makes use of spatial decentralization as an instrument to secure profit. Interregional and international shifts of production facilities are dominated by branch plants,.which are specialized for standardized mass production supported by automated technology. In contrast, strategic and control functions such as planning, R&D, administrative and bureaucratic activities are highly centralized in core regions. Therefore, there is a clear spatial division of labor between centers and peripheries, depending on the comparative advantage of respective regions (Capello, 1994; Fainstein and Fainstein, 1989; Spooner, 1995). The rise of a series of new industrial spaces based on flexible production systems has caught recent attention. Relying on the principle of flexible specialization, firms in new industrial agglomerations are interconnected through dense networks of horizontal and vertical linkages (Graham and Spence, 1995). These new industrial ensembles can arise out of nowhere (such as the Silicon Valley), but more often are found in pre-existing localities with skills and resources for new production system. They include the Third Italy, Los Angeles, New England, the M4 Corridor, etc. (Harvey, 1988). In the latter case in which development is based on endogenous resources, new industrial space does not generate totally new urbanization. This might be the main reason for the relatively stable spatial structure of 20 settlement systems, in spite of considerable changes in production systems (Fielding, 1994). To some scholars (Brown et al, 1996; Camagni, 1991; Florida, 1996), theories based on flexible accumulation are overly pessimistic about the prospect of revitalization of old industrial regions. According to their view, restructuring of traditional industrial centers does not mean monotonic decline of old centers or acceleration toward post-Fordist accumulation system. Rather, there is a simultaneous process of regeneration of some old industries in new localities and decline in other traditional sectors. This regional creative destruction occurs as innovations in new production systems and technologies are adopted by existing industries. Factors of Industrial Location Change There are many variables affecting the location of industrial activities across space. The selection of variables largely depends on the theory and method upon which research is based, and the availability of data. In addition, it might be possible that a set of variables performing well in one region do not do well in another region. The same notion could be extended to temporal sequence, industrial sectors, and spatial scale. In this section, some locational factors considered important for industrial and spatial restructuring in Korea are discussed. It must be noted that these factors are not comprehensive. For example, various social, behavioral, and political 21 variables are not considered because no such data are readily available at micro-regional level. Instead, the focus is on economic and geographical factors. Economic variables have been considered the most important factors for the location of manufacturing industries because they are directly related to the costs of production. Three economic factors are considered in this study. First, the availability of low wage labor is one of primary factors for both regional and global shifts of industrial location (Dicken, 1992; Graham and Spencer, 1995; Haynes and Machunda, 1987; Keeble, 1976; Taylor, 1993). Low regional wage levels are often accompanied by sizable labor reserves, often the result of underemployment i.e., employment in part-time jobs or in occupations in which the worker’s skill and ability are not fully used. Thus, even if the unemployment rate is low in a region, the existence of low wage workers means a potential labor supply for high paying firms (Kale and Lonsdale, 1979). However, low average wages do not necessary mean that new firms will pay low labor costs because the wage level can reflect systematic disparities in the structure of regional industries (Smith, 1971). Industrial wage rates tend to increase as city size increases and this, according to Scott (1982), is the outcome of increased transportation costs for the journey- to-work. Second, the price and availability of industrial land have been central elements in the constrained location model 22 (Fothergill and Gudgin, 1982; Fothergill et al, 1987; Tulpule, 1969). According to Fothergill and Gudgin (1982), over one half of the difference in employment change between urban and rural areas is due to the employment expansion of existing plants. They claim that the shift of manufacturing out of large cities is because urban firms have great difficulties in undertaking physical expansion. Nonmetropolitan industrialization and the concurrent decrease in urban manufacturing employment reflect the effort to obtain cheap and abundant space (Haynes and Machunda, 1987; Graham and Spence, 1995; Hakanson and Danielsson, 1985). The importance of low cost industrial land in uncongested areas has been increased by the development of transportation networks and the increased use of the automobile by workers (Fuchs, 1973); Scott (1982) noted the importance of the price of land, arguing that high industrial land prices at the urban center will repel manufacturing industry, while low land prices at the periphery of the city will attract industries. The significance of land price (as well as availability) as a factor of industrial location will be greater in countries with smaller territory and higher density such as UK and Korea. The last economic factor is industrial structure. The demand for labor is strongly affected by the mix of industries. Regions with favorable (thus growth oriented) industrial structures will require a larger labor force than 23 those with unfavorable sectoral composition (Hakanson and Danielson, 1985). Keeble (1976) showed that regional industrial structure, measured by the share of regional employment in rapidly growing industries at the national level, was closely associated with manufacturing employment change. In a study of the location of Japanese investment in Britain, Taylor (1993) found that industry mix of recipient areas was a strong explanatory factor. Another important measure of industrial structure, with respect to the demand for employment, is labor intensity (or labor-output ratio). It was noted that capital intensive industries have different locational tendencies from labor intensive industries (Fothergill et al, 1987; Scott, 1982). Therefore, in developing economies such as Korea that exhibit a strong tendency to transform industrial structures from labor intensive toward capital intensive, the structural factor will be strongly associated with employment change. According to classic location theory, under isotropic assumptions, distance (thus transportation cost) is the single most important factor in determining the optimal location of manufacturing industries. The importance of distance (to market, raw materials, and suppliers) has declined significantly as a result of the development of modern transportation and tele-communication networks. However, accessibility is still considered the primary reason for the geographical agglomeration of vertically and 24 horizontally interrelated industries in the new flexible production system. One major difference between classic and modern location theory is that the former is focused on the minimization of transportation cost, whereas the latter emphasizes linkages and transactions among manufacturing firms and between manufacturing and business service firms (Scott, 1988a). Thus, the existence of major transportation axes offers a good opportunity for the location of traditional industrial complexes as well as the formation of new industrial spaces based on the flexible production system. Highly developed highway systems have been a major contributing factor for nonmetropolitan industrialization in the US. The construction of Korea’s modern highway system also has played a key role in the location of industry away from the largest cities to newly formed industrial growth centers and adjacent rural areas. Agglomeration economies have been recognized as a geographical source of cost reduction. Agglomeration economies (including urbanization and localization economies) can be defined as the savings in costs occurring from the accumulation of industries in a particular region, which enables firms to share external expenses with others (Keeble, 1976). In Korea, the existence of agglomeration economies has been considered one of the most important reasons for polarized industrial development (Kwon, 1981). However, there is a limit to the scale of agglomeration economies, with decreases after a certain point (Smith, 25 1971). During the periods of locational decentralization, various types of negative agglomeration economies have been noted as major causes for the decay of industrial centers. These factors include high land and housing prices, traffic congestion, pollution, high labor costs, and high incidence of crime. These agglomeration diseconomies raise production costs directly and indirectly, thus reducing the economic efficiency of manufacturing firms. This, in turn, encourages the migration of existing industries to other locations. In addition, more and more newly established firms will seek to locate in less congested areas. These areas do not offer greater external economies compared to established centers, but location in these localities can be more profitable due to technological advances in production, transportation, telecommunication, and information processing. Hypotheses It is expected that characteristic differences in the pattern of industrial location will be revealed through the comparison of industrializing and restructuring periods. During the industrializing period (1983-88), manufacturing employment will grow more rapidly in traditional industrial centers. During restructuring period (1988-93), established industrial centers will not continue to add industrial employment due to the growing diseconomies from overconcentration and resulting physical constraints. On the other hand, less industrialized regions, such as smaller 26 cities and rural areas, will experience a net growth of employment due to improved competitive advantages. Therefore, the classic center-periphery model will not explain emerging trends of industrial location in Korea; The following hypotheses can be stated with regard to the spatial patterns of industrial location especially during the restructuring period: I—1: Rural counties will perform better than urban cities. I-2: Smaller cities will perform better than larger cities. I-3: Less industrialized areas will perform better than industrialized areas. I-4: Peripheral regions will perform better than core areas. Changes in regional manufacturing employment, as an index of ongoing restructuring of Korean industry, can be associated with a variety of regional factors. The expected causal relationship between the growth of regional employment and a set of explanatory factors is hypothesized as follows. First, rapid wage increases in recent years have been one of the most important reasons for the diminished international competitiveness of Korean industries. High wage levels directly increase production costs, accelerating the rationalization of industries. Thus, it can be hypothesized that: 27 II-l: Regional wage ratio (to gross output) will be negatively associated with the growth of employment. The shortage of labor and high wages will promote the adoption of alternative strategies with less reliance on labor. New strategies of industrial development will heavily depend on the use of capital equipment. In the short term, when output remains the same level, the substitution of capital for labor tends to save labor inputs. However, in the context of rapid output growth, a high rate of new capital investment is more likely to generate new employment. Therefore, the second hypothesis states that: II-2: The growth of the capital-labor ratio will be positively related to manufacturing employment growth. Industrial restructuring is a process of structural transformation by which firms seek an improvement in productive efficiency and competitiveness. For several decades, low cost labor was one of the most important sources of competitiveness of Korean industry. However, the advantage deteriorated as quickly as the rise in wages. As a result, those regions with industries relying heavily on labor will be more adversely affected by changes in labor markets. Thus, the third hypothesis states that: II-3: There will be a negative relationship between labor intensity and the growth of regional employment. In addition, the significance of this association will be higher during the restructuring period than the industrializing period. 28 Industrial location requires open space with such attributes as relatively large, continuous and flat sites located away from residential areas. In most large urban areas of Korea, the supply of industrial land is severely limited due to various constraints. In addition, the price of land has increased rapidly, forcing manufacturing firms to spend large amount of capital for the acquisition of land. It is expected that regions with a higher ratio of factory site value to gross output will be less likely to attract new industrial activities than those with lower land prices. Therefore, the fourth hypothesis states that: II-4: There will be a negative association between the growth of the ratio of land assets to output and manufacturing employment change. The relationship between the size of settlement and the growth rate of industrial employment will decline significantly during restructuring period. First, a high growth rate of manufacturing employment in large cities is difficult to maintain because of the large size of base employment. Second, there are strong indications that a variety of urban diseconomies have undermined the competitiveness of heavily populated areas. Thus, the fifth hypothesis states that: II-5: A negative relationship will prevail between population density and the growth of manufacturing employment. The impact of urbanization diseconomies will be 29 larger during the period of restructuring than the rapidly industrializing years. During the period of rapid industrialization, major industrial growth poles, including metropolitan centers, accounted for a large part of the growth of manufacturing employment. In recent years, these traditional industrial centers have struggled to continue rapid growth. This suggests that the spatial concentration of manufacturing activities has declined as industry spreads out toward wider geographical areas. Thus, the following hypothesis states that: II-6: There will be a positive association between the level of industrialization (location quotient) and manufacturing employment growth during the period of industrialization. However, a negative relationship will prevail during the period of restructuring. Modern highway networks can reduce time and monetary costs significantly, thus improving the potential of industrial location for regions adjacent to the highway system. The positive effect of the highway system on the location of manufacturing industry will spread out toward more distant areas as road system sub-connections are further developed. Thus, the last hypothesis states that: II-7: There will be a positive association between access to the expressway network and the growth of manufacturing employment. The importance of expressway accessibility will increase over time. 30 Methods of Research Location Quotient The location quotient (LQ) measures the ‘relative’ concentration of manufacturing employment in a region with regard to the nation as the benchmark region. Formally, the LQ is the numerical equivalent of a fraction whose numerator is the share of employment of manufacturing industry relative to total population in a region, and whose denominator is the share of manufacturing employment relative to total population in the nation. A LQ of larger than unity indicates relative concentration (or specialization) in a region compared to the nation as a whole; less than unity signifies less relative concentration of manufacturing employment (North, 1973). In addition, an increase in the LQ of a region can be considered as an indication of the increasing importance of the region as a locus of manufacturing activities. It must be remembered that the LQ is affected not only by changes in the growth rate of employment, but also by changes in population. Considering unequal population growth among different regions of Korea, the LQ may not be an ideal measure of location change. Thus, the absolute figures of regional employment change will also be presented to compensate the conceptual weakness of the index. 31 The location quotient for manufacturing employment in region ‘r’ is calculated with the following formula: L9, = [E,/P.1/[E./P..] ( 2-1, where: E = manufacturing employment; P = population; r = region; and n = nation. The LQ will be measured at three points in time: the initial year (1983); the mid-point (1988); and the final year (1993). Comparisons of LQ and employment changes will be made among various regional types (urban and rural areas, industrialized and less industrialized areas, and core and peripheral areas) to identify spatial shifts in manufacturing locations. Regression Analysis A multiple regression model is used to explain regional variation in the growth rate of manufacturing employment, an important indicator of restructuring. The growth rate of manufacturing employment reflect the attractiveness of a region as a locus of industrial activity. Independent variables represent regional manufacturing structures and locational characteristics. The generic model assumes an exponential function between the change in regional manufacturing employment and a set of regional variables, EMP = efHumuuchaEU< "Amy 88 mmmfi umm> on» so pmmmn mum mmmum m>HumuuchHEU¢ uAoad8m ucmfluoso COHDMUOA coflmmm amusm ocm Conn: >b mocmnu coflumooq HmfluumsocH I N manna 90 areas. The large absolute increase, though lower growth rate, in urban areas during the first period is due to the law of diminishing returns. A clear pattern is revealed through the settlement system. During the first period, growth rates were much higher in smaller city groups than in larger ones. During the restructuring period, larger city groups experienced negative growth rates, whereas the smallest cities recorded positive growth. In rural areas, nonadjacent counties performed better, followed by counties adjacent to nonmetropolitan cities and metropolitan cities. Therefore, the trend of locational decentralization is true for rural, as well as urban, areas. The accelerated deurbanization and decentralization of manufacturing employment are much more apparent in changes in location quotients (Figures 4 and 5). Urban areas as a whole have witnessed decreases in the location quotients, whereas rural areas have seen increases over the time periods (Table 2). The decrease in urban areas was most evident in the largest cities. The location quotient of these cities was above average initially, about average at the mid-point, then below average in the final year. The opposite trend is seen in the smallest cities. Medium sized cities are more industrialized than other city groups, but tended to lose dominance over time. In rural regions, all types of counties experienced increases in location quotients throughout the research period. The location quotient for rural areas as a whole was only 36 percent that 8372;: 236:0 3383 5 wmcmzo I m 6:6: $22.35: ucofloso c0333 5 6955 I v 3sz \IAl/ 91 92 of urban areas in 1983 but became higher than urban areas in 1993. In fact, rural areas, especially those adjacent to metropolitan cities, became the most highly industrialized in 1993. One point to be kept in mind is that changes in location quotient were affected by regional population shifts. In most cases, an increase in the location quotient was accompanied by an increase in manufacturing employment. In the same manner, a decrease in the location quotient does not always mean the loss of employment. As can be seen in Table 2, the location quotient decreased in urban areas during 1983-1988 in spite of significant increases in total employment. Thus over-dependence on the location quotient as an indicator of spatial restructuring of industrial location can be misleading, especially in a society in which population migration is occurring at a fast rate. However, this concern does not preclude the significance of the index. This is because industrial location has meaning only when it is related to the population residing in a region. An increase in the location quotient, even without a corresponding increase in employment, does indicate that a larger proportion of people are engaged in manufacturing activities that provide an important source of regional income, which is a higher state of industrialization. An additional comparison of industrial location change during industrializing and restructuring periods is carried out by examining the level of industrialization (Table 3). 93 Regional categorization is based on the location quotient. Industrialized regions are those with a location quotient larger than unity, while less industrialized regions are those with less than unity. The breaking point between highly and modestly industrialized regions is a location quotient of 2.0, whereas that for moderately less and the least industrialized regions is set to 0.2. Dramatic changes are revealed in employment growth during the two time periods. During the industrializing period (1983-88), two types of industrialized regions accounted for more than two thirds of total growth. Within industrialized areas, highly industrialized regions gained more than 60 percent of the growth. The vast number of the least industrialized regions, mostly rural counties, accounted for only 4 percent of national growth. These facts suggest that the spatial concentration of industrial location proceeded within established industrial areas during the rapidly industrializing period. Remarkable changes occurred during restructuring period (1988—93). The most highly and the least industrialized regions moved in opposite direction from moderately industrialized and moderately less industrialized regions. Moderately industrialized areas led deindustrialization, accounting for more than 90 percent of the decrease in national manufacturing employment. The loss is equivalent to more than 20 percent of base employment, or about one-third of the gain from the previous period. The least 94 industrialized regions added more than 60 percent of base employment during the restructuring period. The most highly industrialized regions also experienced a net gain, but the size was negligible compared to industrializing years. The differential performance by regions of different levels of industrialization was revealed through changes in the location quotients (Table 3). Two industrialized regions and moderately less industrialized regions experienced a decline in the LQ. Only the least industrialized areas witnessed an increase in the LQ. As a result, there was a general decline in the disparity in the index between industrialized and less industrialized regions. In 1983, the location quotient of the most highly industrialized group was 28 times larger than that of the least industrialized group. The difference diminished to 11 times in 1993. The results strongly suggest that the classic core- periphery model is not a valid analytical framework for the explanation and prediction of locational changes in contemporary Korea. The majority of employment loss has occurred in established areas, while employment has grown in the least favorable regions. It must be emphasized, however, that the most heavily industrialized regions did not lose employment. The decline in the location quotient of this region is due to greater population growth. The ascendance of the least industrialized areas and the status quo of the most highly industrialized areas are somewhat different from advanced economies, in which traditional industrial centers "”8565 £25 EH coBMonBM “5&3. 550 moUCa>oum maonoocoozu pom maaon pom .COnmma toflmcmzx "coammm umsznusom m¢oCa>oum mammmc5>x cam .somme .cmmsm ”COammm ummmlnusom mosa>oum aoocsxx cam .conocH .aoomm "coammm amuadmo Av m.o cmnu mmwa 0a nuaz mmonu mum mcoamwu owuaamauumsoca ummma N.o cmnu Hmmuma 0a spa: wmoru mum mcoammu Umnaamauumsocalmmma mawumumooz o.a cmnu uwouma 0a cuaz mmonu mum mcoammu omnaamauumsch >amumumpoz o.m cmnu Hmmuma 0a spa: mmonu mum mCOHOmH omNaamanumsoca >acmam mmma pom mmma Ga Ga one so owmmn ma COaDmNaamauumSUCH Am oo.a ".mmma pom mmma "Lav .AUV mm mmma emu» map so comma mum mmoum m>aumuumacaeo¢ "Ame mmma umm> one so Ummmb mum mmmum o>aumuumHCaEp¢ ”Adv Ia "wuoz 95 omcmnu ucmE>0adEm Damauoso coaumooa mm.a am.a mam.m amm.m mm.o om.o om.o ma.o mumano ma.a as.a mmm.sm mma.maa mm.o as.o av.o mv.o ummza850m Ga.a mv.a mom.me mmm.sma No.0 v5.0 vv.o mm.o sumgaaumm sm.o am.a www.mma- mom.mmm mm.a om.a om.a Gm.a ummmnusom om.o mv.a Nmo.amaI www.mmv Go.a aa.a aa.a em.a amuaamo am.o as.a vam.mom- oma.mss sa.a mm.a mm.a am.a muoo >umcdauwdlmnou mo.a Hm.a smm.om mmm.wm sm.o aa.o Ga.o oa.o smmmq mm.o mm.a mam.sw- oma.msm mo.o «6.0 mm.o as.o samumumnoz Gm.o mm.a mos.om- aaa.smm sm.o mm.o vm.o mm.o umwaamauumsnca mama as.o am.a mos.mamI mmm.mmm ma.a ov.a ss.a sw.a samumumuoz No.a mm.a mmo.ma smm.smm mm.m as.m av.m om.m sagas: oa.o as.a www.maa- osm.amm so.a sm.a sm.a Go.m vowaamausmsncH COflUflNHHMHHumDUCH—H Na.o as.a ave.GmNI mme.mom oo.a oo.a oo.a oo.a coanmz locmamalovmmma maummaa mmImmma mama lmvmmmalavwmma mama >HmndaummImHou ocm coaDMNaamauumsocH xn mmcmco coaumooa amauumzocH I m manme 96 are losing competitiveness and the most peripheral areas have remained largely underdeveloped. These characteristics are also quite different from developing nations in which acute spatial disparities are persistent between a limited number of core areas and the vast majority of peripheral areas. A third comparison of industrial location change during the two periods focuses on core and peripheral areas (Table 3). The purpose of the core—periphery comparison is not to emphasize the disparities between the two regions, but to provide a new dimension with regard to recent industrial location changes in Korea. The spatial scale of core and periphery is relatively large, namely at the metropolitan city and provincial level. As of 1993, there were six metropolitan cities with more than a million population. The four largest metropolitan cities - Seoul (No.1 in Figure 1), Pusan (2), Taegu (3), and Inchon (4), and three provinces - Kyonggi (cities 7-24, counties 75-91 including 25) and Kyongsang (North and South: cities 53-72, counties 166-207) surrounding these cities are grouped as the core. Thus, geographically, core areas are not contiguous, but are two separate units: the capital region and the Southeast region. In 1983, 87 percent of national manufacturing employment and 67 percent of population were concentrated in the two cores. Peripheral areas include the Southwest region — the metropolitan cities of Kwangjoo (5) and Taejon (6), and the provinces of Choongchong (North and South: cities 33-40, 97 counties 107-131), Cholla (North and South: cities 41-52, counties 132-165), and remaining regions (Kangwon: cities 26-32, counties 92-106, and Cheju: cities 73-74, counties 208-209). It should be noted that the two metropolitan cities and few growth centers in the periphery are by no means peripheries in the rigorous sense. During the industrializing period (1983-88), manufacturing employment change shows a typical core- periphery relationship (Table 3). Core regions accounted for as much as 86 percent of new manufacturing jobs, well above the share of industrialized areas as a whole or that of urban areas. Within core regions, the capital region absorbed more than one half of national employment growth, while the Southeast region accounted for about one third. Peripheral areas attracted only 14 percent of new manufacturing employment in the nation during the period. The Southwest region accounted for most of employment growth of peripheral areas. Other regions attracted less than one percent of the national gains in industrial jobs. In relative terms, however, there was no significant difference between core and peripheral areas. Even the least industrialized peripheral areas performed as well as the heavily industrialized Southeast region in terms of growth. Therefore, the pattern during the first period can be summarized as universal gains in terms of growth rates, but a clear core-periphery relationship in absolute growth. 98 There was a radical breakup in the long—lasting core— periphery pattern of manufacturing employment growth during the restructuring period (1988-93). Core regions lost a considerable number of industrial workers during the restructuring period (Table 3). In fact, employment losses of core regions exceeded total national decreases. The capital region and the Southeast region lost about the same amount of employment, roughly equivalent to 10 percent of base employment. Peripheral areas recorded a net gain, although absolute growth was reduced to one half that of the previous period. Most of the growth occurred in the Southwest region, but other peripheral areas did much better in relative terms. In fact, these areas added more employment during the restructuring period than the previous period. Therefore, the relationship between core and periphery was completely reversed during restructuring, which might be comparable to the Snowbelt-Sunbelt shift in the US, though at a smaller scale. Location quotients mirror the regional shift of manufacturing employment growth, from core regions toward peripheral areas. The indices of industrial concentration decreased in core regions and increased in the peripheral regions (Table 3). In particular, the capital region, which had a solid level of industrial concentration in the early 19805, is not an especially industrialized region when population is considered. The Southeast region has maintained its status as the industrial heartland of Korea. 99 Peripheral areas, while still less industrialized than the nation as a whole, are rapidly catching up to core regions. The difference in the location quotient between the highly industrialized Southeast region and the least industrialized peripheral areas was reduced by about one half during the ten year period. The last part of this section examines the pattern of growth in manufacturing employment by regional types (Table 4 and 5). Each city and county is classified into one of four categories depending on its growth rate in employment for each period. The first category is composed of ‘rapidly industrializing’ (RI) regions that have more than doubled manufacturing employment during the five year period. The next category applies to ‘moderately industrializing’ (MI) regions. They also have gained employment but the growth was less than two times of the initial level. The third category refers to ‘moderately deindustrializing’ (MD) regions that have lost less than one quarter of base employment. The last category includes ‘rapidly deindustrializing’ (RD) regions which have lost more than one quarter of base employment. The number of regions in each category shows that how many regions in that category are industrializing or deindustrializing, whether rapidly or moderately. Of the 51 regions (out of 187) that fall into the first category (RI) during 1983-88, about 90 percent are rural counties (Table 4 and Figure 6). Only five cities more than doubled their manufacturing employment during this period. 100 Of the 46 rural counties in this category, half of them were located around urban areas and another half were distant from urban centers. Rural counties adjacent to metropolitan cities were more likely to experience rapid industrialization than those adjacent to nonmetropolitan cities. Rapidly industrializing regions were fairly evenly distributed between core and peripheral regions (Figure 6). In addition, about the same percentage of core regions and peripheral regions experienced rapid industrialization during the period. Within the core, the capital region had a higher percentage of rapidly industrialized areas than the Southeast region. Within the periphery, the Southwest region had a higher percent of rapidly industrializing areas. Therefore, the distribution of rapidly industrializing regions is not biased toward a specific type of regions, although rural areas adjacent to metropolitan centers and the capital region comprised a slightly higher proportion of this category. During the 1988-93 period, the number of rapidly industrializing regions decreased to 35 (from 51) in spite of the increase in the total number of administrative areas (Table 5). The absolute majority of rapidly industrializing regions is located in rural areas (Figure 7). Only three small cities expanded manufacturing employment more than 100 percent during the restructuring period. Within rural areas, nonadjacent counties had a higher proportion of rapidly industrialized region than adjacent counties. The 101 relationship between core and periphery displayed significant differences from the pervious period. Of the 35 rapidly industrialized regions, 22 were located in peripheral areas. Within the core, only two regions were found in the capital region, a substantial reduction from the 11 during the previous period. Within the periphery, about 20 percent of both the Southwest and other regions were rapidly industrializing regions. Therefore, during the restructuring period, rapidly industrializing areas were much more likely to be found in rural areas, especially distant from the Seoul metropolitan region. This is an apparent indication of the ongoing spatial shift in manufacturing employment from established urban industrial centers toward formerly less industrialized peripheral rural areas. These results also suggest that spatial spread or trickling down of industrial location in Korea began well before the industrial restructuring. The second category (MI) does not display notable changes in the aggregate number during the two periods (Tables 4 and 5). Overall, more than one half of all regions belong to this category during both periods. However, the spatial distribution of this group is quite different during each period especially for urban and rural areas. During the industrializing period (1983-88), 41 of 52 cities, including all metropolitan cities, were classified as modestly industrialized regions. This number declined to 24 (out of 73) during the restructuring period (1988-93). Although all 102 mm LON om m.m 02 meI A wooa v o.vm o.ma m.mm >.mm m.mm m.mm m.mm >.mm m.mm m.>m m.wm «.mm m.av m.vm m.mm N.om 0.0m o.ov v.>m m.mm m.mv a.vm m.mo m.ma 0.0m >.m o.ooa I m.ms m.m m.>m m.>m Amomucmouwmv a2 am Ammlmmmav meI v ucmaaoaQEw mo unsoum .mo v DGmE>0aQEm no nuzouo .wo A ucmaxoadEo mo unsoum .mcanaamauumDUCaoU macadmu "om COCHNHHMHHUMDOCHOO >HOUMHOOOE "DE .oCaNaamauumDUca zamumumooe ”Hz wooa A ucmemoadEm mo unsoum .mCaNaamauumSUCa macadmu "am ”muoz o.ooa a v ma v mm muwnuo o.ooa w v Nv mm vb ummzsusom 0.03 s m mm, mm mm 39328 o.ooa m m mm ea mm ummmnusom 0.03 I a Z 3. am Gimme o.ooa m oa om mm mm muou xumcdauwm w muoo 0.03 m 3 mm mm G ucmomavmcoz 0.00a N v «N ma mv .ouumEcoz o.ooa I I ma oa mm .ouumz 0.03 N v mm mm mm 28mm?“ o.ooa m va mm mm mma amusm o.ooa a a aa m ma aamEm 0.00a a m «N N om Esaowz 0.03 I I G I G cmnaaoaofimz o.ooa N v av m mm amen: amusm w CMQHD o.ooa oa ma moa am nma c0aumz Acoamwm mo umnfiszv amuoe am 02 a2 am amuoe coaumNaamauumsocH mo mcumuumm ocm mmm>e amcoammm I v manna wmmI v ucms>oad8m mo unsoum .mCaNaamauumsocawo aaoaamu "am meI A .wo v ucmE>0adEm mo nuzoum .mcanaamauumSUCaoU >amumuooofi "oz GQOa v .wo A ucmE>0adEm mo nuzouo .mCanaamauumsUCa mamumumooe ”a: 103 mooa A ucwexoaQEm mo nu3oum rosanaamauumsoca >aoadmu “am "wuoz G.aa N.Ga o.OG N.Ga o.ooa m G Ga G Gm mumnno v.s G.Ga G.GG o.am o.ooa G Ha ha ha am ummzsusom G.G G.Ga a.GG G.GN G.GGH G Ga GG mm soa sumaaauma G.G G.am G aG. N.sa G.GGH G Ga. Gm aa «G nmmmcozom G.Ga a.GG G.GG G.G o.ooa a Ga Ga N am amuaamo a.ma s.Gm G.ss G.ma G.GGH Ga am Ga Ga aoa mnoo xumcdanmm G muoo G.G G.aa G.GG G.GN G.GOa G s mm Ga HG Gcmomanmcoz o.m G.G G.G» G.sa o.ooa a G Gm G HG .ounmscoz I s.G G.GG s.am o.ooa I N Ga G Gm .ounmz s.a G.G G.Gs G.Ga G.GGH a s NG Ga es Gamumanm s.m v.0a N.NG s.mm o.ooa G «a VG mm Gma amnsm G.GN G.am 0.0a G.G G.GGH a aa Ga G Gm aamsm G.GN G.GG a.GN I G.GOH G Ga a I mm Esanmz G.GG G.GG s.Ga I o.ooa N m a I G cmsaaooousmz G.GN >.Gm G.mm a.v o.ooa as am Gm m G» amass amusm G omens G.Ga s.om G.aG G.Ga o.ooa mm Ge Goa Gm Gom coaumz Ammmucmoummv ACOHmmm Mo monaszv am o: as am“ amuoe am as as am amooe AGGIGGGHV ceaomwaamauumsGCH Go mcumuumm new mmase amcoammm I G magma 104 IGGGGIGGGHG Gcwe>oaa2m Go nuzou o I s Guzman AGGGaImea. GcmE>0aQEG Go nuxouo I G Guzman 105 six metropolitan cities were found in this category during the first period, the number had been reduced to one during the second period. In addition, only nine medium sized cities were classified as moderately industrializing during the second period, well below the 24 cities identified during the first period. Small-sized cities showed a slight increase. As a result, during the restructuring period, rural areas became the absolute majority of the MI group. The number of moderately industrializing rural areas increased by 17, whereas the number of urban areas decreased by 17. Twelve of these rural counties were located adjacent to nonmetropolitan cities. More than 60 percent of rural counties were classified as MI during the restructuring period, an increase from about 50 percent during the previous period. This figure is much higher than that of urban regions (33 percent). Within rural areas, adjacent counties were much more likely to be found in this group. During the first period, 57 percent of adjacent counties and 42 percent of nonadjacent counties were MI. The figures changed to 70 and 53 percent, respectively, during the second period. However, the relationship between core and periphery did not change as radically as that of urban and rural regions. Both the number and share of MI region did not show significant changes between the two periods. The number of regions categorized as MD more than doubled during the restructuring period (Tables 4, 5 and Figures 6, 7). A clear spatial pattern can be recognized by 106 comparing the two periods. During the industrializing period, there were only four moderately deindustrializing cities. This number increased to 29 cities during the restructuring period, evidence that deindustrialization was not confined to a limited number of urban areas. The category MD became dominant for larger urban areas. Rural areas did not experience a change in their numbers as a whole. There was a slight increase among adjacent counties, but a small decrease among nonadjacent counties. Core and periphery had roughly the same number of moderately deindustrializing regions during the first period. The number of MD regions increased for both types of region though increases were more than two times greater in core areas. Within the core, the rapid increase in the number of modestly deindustrializing regions was mostly attributable to the capital region, which accounted for 12 of 17 additions. Within the periphery, the Southwest region accounted for 7 of 8 increases. The last category (RD) exhibits a spatial pattern similar to that of moderately deindustrializing regions (Tables 4, 5 and Figures 6, 7). Only two rapidly deindustrializing cities were identified during the first period, but the number increased to 17 during the second period. All sizes of urban areas experienced increases, led by medium sized cities accounting for 60 percent of the change. Rural areas, on the contrary, showed a slight decrease. None of the rural counties adjacent to 107 metropolitan cities experienced rapid deindustrialization during either period. The most radical change can be seen in the comparison between the core and periphery. During the first period, three core regions and seven peripheral regions were grouped as rapidly deindustrializing. The number changed to thirteen and nine, respectively, during restructuring. Within the core, no part of the capital region was classified as rapidly deindustrializing in the first period. However, seven regions emerged as rapidly deindustrializing during the second period. The Southeast region also witnessed an increase. The periphery added only two RD regions during the second period. Significant changes also have occurred in the pattern of the growth of manufacturing employment between different types of region. During the industrializing period, urban areas and their adjacent rural areas attracted a majority of new industrial employment. In addition, a greater portion of core areas performed well in gaining manufacturing jobs. Industrial restructuring has had a different impact depending on the geographical location and level of industrialization of a region. Whereas more advanced areas were heavily affected by the national trend of deindustrialization, most disadvantaged areas were not adversely affected. As a result, less developed regions have emerged as newly industrializing spaces. This spatial process is very similar to patterns that have occurred in advanced industrialized countries. Comparing two maps 109 (Figures 8 and 9), it is apparent that industrial location has spread from the two core regions, the capital region in the northeast and the southeastern part of the country, towards wider geographical areas. Results of Regression Analysis A bivariate regression model integrating intercept and slope dummy variables was applied to test the regional effect on industrial location change. The model and hypotheses can be summarized as follows: Model: ALQ = (a + b2) + (b1+ b3)LQtl + e, where: b2 and b3 are intercept and slope dummies. Hypotheses: H1: b2 = 0 H2: b3 = 0 H3: b2 = b3 = 0 Results from the simple regression model confirm overall differences in the pattern of manufacturing employment growth between contrasting regional types (urban/rural, industrialized/less industrialized, and core/periphery). The results of the analysis are presented in Table 6. First, the large F statistic using the Chow test strongly supports structural differences in growth patterns between the three pairs of regions. The null hypothesis of the Chow test (b2= b3= 0) is rejected for both industrializing and restructuring periods. In addition, the F statistic is consistently larger for the second period, llO suggesting a larger structural difference during the later period. With regard to the intercept dummy, the null hypothesis (b2= 0) is rejected only for industrialized versus less industrialized regions. This result can be disregarded because regional categorization is based on the location quotient in the beginning points. However, the null hypothesis assuming an identical initial level of industrial development between rural and urban areas, and core and periphery, cannot be rejected for any period. With regard to the slope dummy, the null hypothesis (b3= 0) is rejected in all cases with the exception for core versus periphery during the first period. This implies significant regional differentials in the growth rate of manufacturing employment between two opposite type of regions. Again, the test statistics are consistently larger for the restructuring period, indicating increasing differentials between the regions. The results demonstrate not only differential growth patterns between contrasting regional types, but also structural changes in the trend of industrial location between the industrializing and restructuring periods. In addition, the regression analysis provides evidence of spatial convergence or catch-up process. The coefficients of intercept dummies are positive in five out of six cases, and those of slope dummies are negative in five out of six cases. The positive intercept and negative slope indicate that benchmark regions (urban, industrialized, and core 111 Table 6 - Test of Regional Effect on Location Change Urban/Rural Industrialized Core/Periphery /Less-indus. 1983-1988 a 0.080** 0.060 0.111* (2.647) (1.455) (2.541) b1 0.171** 0.081 -O.225* (4.101) (0.715) (-2.548) b; -0.039 0.420“r 0.090 (-0.625) (3.390) (1.406) b3 -0.343** -0.308* 0.098 (-6.877) (-2.537) (1.058) Chow F 36.51** 6.18** 3.21* 1988-1993 a 0.220** 0.127* 0.143* (5.325) (2.195) (2.446) b1 0.185** 0.268 O.313** (4.224) (1.874) (3.042) b2 0.039 0.686** 0.161 (0.517) (4.234) (1.874) b3 —0.503** -0.612** --0.513"“‘r (-8.785) (—3.976) (-4.701) Chow F 55.60** 10.80** 11.55** Note: Base Model: ALQ = a + blLQtl + e (1) Dummy Model: ALQ = a + blLQtl + b2D + b3DLQt1 + e (2) Parentheses are T statistics Chow F = {(SSEl - SSE2)/(K+1)}/{SSE2/(N-2K-2)} ~ Fx+1, N-2K-2 where,SSE1: Residual sum of square from equation (1) SSE2: Residual sum of square from equation (2) K: Number of restriction (=1) N: Number of observations ** significant at .01 * significant at .05 112 regions) tend to have a higher level of industrialization overall, but that growth of the location quotient of these regions tends to fall more rapidly compared to opposing regions. A multiple regression model was also run for the two periods in order to test factors that are related to industrial location change. Identical variables were used for both periods to examine changes in the impact of independent variables on the growth of regional manufacturing employment between industrializing and restructuring periods. The shortcoming of this approach will be a lower overall explanatory power since the identical independent variables are not necessarily the best fits for the different periods. The results found in Table 7 support this argument, with fewer significant variables and a lower coefficient of determination for the first period. The proposed regression model explains only 23 percent of the variations in the growth rates of regional manufacturing employment for the industrializing period and 32 percent for restructuring period. The relatively low coefficients of determination reflect the omission of other variables significant for industrial location change in Korea. They include variables related to industrial and locational policies, labor relations, labor market, infrastructure, government regulations, behavioral factors, business organization, and so on. In addition, the model does not have a serious multicollinearity problem between 113 independent variables. The tolerance values range from 0.693 (LABOR) to 0.902 (ACCESS) (Table 7). The first independent variable (WAGE) tests the effect of the regional wage ratio on manufacturing employment growth. The hypothesis, that a negative association exists between the two variables, can be accepted. For both industrializing and restructuring periods, the coefficient of regional wage ratio is negative and significant. The impact of wage ratio on employment growth was stronger in the period of rapid industrialization than the restructuring period, possibly reflecting the differences in the capacity of labor supply for the two periods. The adjustment of labor inputs to the wage ratio is more flexible when labor supply is abundant. However, in the context of labor shortages and strong labor power, manipulation of employment levels is difficult undertaking. Reduced flexibility in the labor market better represents the period of industrial restructuring than industrialization. The second independent variable (CAPITAL) tests the effect of the growth of the capital-labor ratio. The hypothesis presuming a positive association between capital accumulation and employment growth can be accepted in both periods. The positive relationship between the growth of capital intensity and employment growth suggests that capital investment has been an important source for the creation of new manufacturing jobs. The possibility of a labor shedding effect by new capital investment, as a 114 Table 7 - Test of the Factors of Employment Change Dependent variable: growth rates of manufacturing employment 1983-88 .1988-93 Independent Std. Coeff. t Std. Coeff. t Variables CONSTANT - 5.590** - 6.097** WAGE -0.250 -3.284** —0.157 -2.522* (0.742) (0.874) CAPITAL 0.325 4.238** 0.211 3.086** (0.731) (0.725) LABOR -0.097 -1.229 -0.287 -4.168** (0.693) (0.714) LAND -0.340 -4.786** -0.173 -2.771** (0.852) (0.865) PDEN —0.107 -l.490 -0.250 —3.933** (0.841) (0.837) LQ 0.074 1.045 -0.206 -3.212** (0.864) (0.822) ACCESS 0.126 1.818 0.141 2.300* (0.902) (0.905) R2 0.230 F 7.643** 13.705** Note: parentheses are tolerance values ** significant at .01 * significant at 115 substitute for labor inputs, was insufficient to change the coefficient of the variable to a negative value. This result supports the hypothesis that high rates of capital investment have been a consistent source of industrial development in Korea. The relationship of capital accumulation to employment growth declined during the restructuring period. This reduced effect of new capital investment on the generation of employment might be due to deteriorating labor market conditions during the restructuring period. In addition, a larger portion of new capital investment might have been expended on such areas as quality or productivity enhancement facilities, including research and development activities that demand fewer labor inputs. The third independent variable (LABOR) tests the effect of labor intensity on the growth of manufacturing employment. The hypothesis proposing a negative relationship between the two variables can be accepted only for the restructuring period. The coefficient of labor intensity is also negative for the industrializing period, though not significant. This suggests that regional industry structure has become a more important determinant of regional industrial growth in recent years. It also indicates that regions that depend heavily on labor intensive industries are more likely to lose employment compared to regions with less labor intensive (or capital intensive) structures, especially during industrial restructuring. Thus, the change 116 in the significance of the coefficient explains an ongoing transformation of industrial structure from labor intensive toward capital and technology intensive. The fourth independent variable (LAND) tests the effect of changes in land prices on regional industrial employment. The hypothesis stating a negative effect of growth in the ratio of land assets to gross output can be accepted for both periods. The result suggests that regions that witnessed higher growth in the ratio of land assets would have difficulty in attracting new industrial employment. It is apparent that manufacturing industry has been losing its competitive edge to non-manufacturing activities in those areas with a rapid rise in land prices. An increasing share (value) of land assets to total output will enable existing manufacturing firms to sell (all or part) factory sites and move out of current locations. On the other hand, a higher ratio of land assets means that firms have to expend more for acquisition of land instead of new machinery. In either case, employment will tend to decrease rather than increase. The impact of the variable is stronger during the industrializing period than restructuring, which is not clearly explained. In fact, the variable is most highly associated with employment change in the first period. The fifth and sixth independent variables (PDEN and LQ) test the effect of agglomeration economiesL The hypothesis of negative urbanization economies can be accepted only for the restructuring period. The coefficient of population 117 density (PDEN) is negative for the industrializing period, but not significant. A highly significant and negative coefficient during the second period indicates that diseconomies of urban agglomeration have increasingly deleterious effects on manufacturing industries in densely populated areas. These diseconomies were apparently less serious in the previous period. These results also suggest that the new locational tendency in Korea is similar to that of advanced industrialized countries. The hypothesis regarding the impact of localization economies on the growth of manufacturing employment can be accepted only for the period of industrial restructuring. The coefficient of the location quotient (LQ) has a positive value in the first period, although it is not significant. Industrial location during the industrializing period might take the form of cumulative causation, in which already industrialized areas continued to attract new industrial employment. The highly significant, but negative coefficient for the second period strongly rejects the continuation of the trend of spatial concentration. A negative relationship between the initial level of industrialization and the growth of industrial employment during following years is strong evidence of a new trend of deconcentration of industrial location from industrialized areas toward less industrialized regions. The last independent variable (ACCESS) tests the effect of rural transportation accessibility. The hypothesis of a positive relationship between the variable and the growth of 118 regional manufacturing employment can be accepted only for the restructuring period. The coefficient of rural expressway accessibility is positive in the first period, but less significant (p=0.07). This result implies that the positive effect of a modern expressway system on manufacturing employment in rural areas has increased over time. The result suggests the existence of a moderate time lag between the construction of a new expressway and industrialization in rural areas. Considering the relatively minor changes in the expressway network during the research period, the increased significance of the variable is the result of the effect of the existing highway system. Regional Productivity Growth of Output and Input Factors Korean manufacturing continued rapid output growth throughout industrializing and restructuring periods (Table 8). However, there was a slowdown in the average annual growth rate during the restructuring period, from 15.1 percent to 12.9 percent. One significant change occurred in labor inputs, which declined in absolute terms after 1988. Capital investment grew more rapidly during the restructuring period, from 13.6 percent to 15.6 percent per year. These trends support the argument that there has been a change in the growth pattern of Korean manufacturing industries since the late 19805. 119 Examination of changes in spatial patterns of manufacturing output and input factors is useful starting point for the discussion of regional productivity because regional productivity is determined by the location of inputs and final output. The spatial redistribution of industrial workers and capital investment, along with output from those factors, reconfigures the geography of productivity. The subdivision of national data into smaller regional units based on location and industrial development reveals clear spatial patterns. First, in terms of manufacturing output, the slowdown in growth rates was more evident in urban regions than in rural regions (Table 8 and Figures 10, 11). Rural counties recorded much higher rates of growth throughout the research period. Rural counties, both adjacent and nonadjacent to urban areas, fared equally well, although the former did slightly better during the period of industrialization and the latter performed better during the restructuring period. Within urban areas, medium-sized cities led output growth during the first period, though the smallest cities performed best for the last five years. A similar pattern, not as clear as in urban areas, can be observed among industrialized and less industrialized regions. Industrialized regions displayed better performance during the industrializing period and less industrialized regions grew more rapidly during the restructuring period. 120 Table 8 - Growth of Manufacturing Output and Input (Percent Per Annum) 1983-88 1988-93 Output Input Output Input Labor Capital Labor Capital Nation 15.08 6.18 13.63 12.93 -3.03 15.59 Urban 13.39 4.96 11.09 10.35 -4.95 13.19 Metropolitan 11.52 3.60 13.63 9.02 -6.63 9.55 Medium 15.65 7.31 10.37 10.60 -3.19 13.72 Small 11.41 6.98 3.96 16.06 —0.59 18.46 Rural 22.04 11.28 20.85 19.20 4.23 22.37 Adjacent 22.98 11.25 18.92 18.59 3.82 21.82 Non-adjacent 19.05 11.35 24.54 21.93 5.71 24.32 Industrial 15.71 6.58 11.94 11.98 -3.48 14.06 Less-indust. 13.73 5.45 18.16 13.01 -2.17 19.47 Core 15.32 5.94 12.85 11.33 -3.95 13.04 Seoul Metro. 16.85 7.10 19.23 11.90 -3.73 11.92 Southeast 13.87 4.77 9.07 10.72 -4.18 13.85 Periphery 14.33 7.14 15.73 15.12 0.11 20.84 Southwest 13.70 6.97 17.30 16.88 1.40 24.23 Other 15.35 7.38 13.23 12.03 -1.80 12.95 Note: Output: value added Labor input: number of workers x hours worked Capital input: net fixed asset (total fixed asset — land asset) 121 122 Core and peripheral areas did not show significant differences in the growth rates of output during the first period. Only the Seoul metropolitan region can be singled out as performing better than others. The restructuring period displays a clearer distinction between core and periphery. Overall, the growth rates of peripheral regions were well above those of core areas. Specifically, the Southwest region outperformed all others, both in core and peripheral regions. One of the most important characteristics of regional output growth is the ascendance of a new leader in each category. None of the new leading regions were the best performer during the previous period. In fact, the majority are located in less favored regions. Labor inputs exhibit clear spatial patterns, especially during the most recent period (Table 8). During industrializing years, when national labor inputs were growing, the urban-rural comparison is a better description of the geography of growth in labor inputs. Rural areas, both adjacent and nonadjacent, experienced much higher labor input growth rates than all types of urban areas. Comparisons between industrialized and less industrialized, and core and periphery regions do not reveal significant differentials. One point to be noted is the low growth rate of metropolitan areas. The largest cities were unable to add industrial workers at a higher rates due to an already high volume of workers accumulated through their longer history of industrialization. 123 The spatial pattern of labor input growth shows a radical change during restructuring (Table 8). All types of urban areas witnessed negative growth, with higher rates of decrease in larger cities. Rural regions recorded net gains, with better performance by nonadjacent counties. Regional categorization based on the level of industrialization is not a good explanatory framework for the growth of labor inputs. Core-periphery comparison does not reveal any difference within cores, but does single out the Southwest region in the periphery as a net gainer of labor input. Therefore, the spatial pattern of growth of labor inputs during the period of industrial restructuring is most visible from an urban-rural perspective. The input of capital grew more rapidly during the restructuring period, indicating that recent industrial development has depended heavily on capital investment. The spatial pattern of capital input growth resembles that of output and labor inputs (Table 8 and Figures 12, 13). During the industrializing period, rural areas experienced much higher rates of capital input growth than urban areas. Within urban areas, metropolitan cities recorded the highest growth, possibly due to the substitutive relationship between labor and capital inputs. Because the largest cities had the lowest growth rates of labor inputs, they had to use more capital to maintain a certain level of output growth. The group of smallest cities had the lowest growth rate initially. This pattern was reversed during restructuring, 124 125 with the highest growth in the smallest cities and the lowest growth in metropolitan areas. Rural areas performed much better than urban areas in both periods. In rural areas, nonadjacent counties showed higher growth rates of capital input than adjacent counties. In addition, less industrialized regions performed better than industrialized areas throughout both periods. Higher levels of performance by less favored region are no exception for the core and periphery. Peripheral regions, especially the Southwest region, exhibited the highest growth rates during both periods. The spatial pattern of growth of factor inputs reveals the trend of increasing deconcentration. Higher growth rates of factor inputs and output in rural areas, less industrialized areas, and peripheral areas have shifted the locus of growth away from the former centers. The tendency of spatial decentralization seems to be wider in scope and deeper in extent as the Korean economy entered the phase of restructuring. Spatial Pattern of Productivity Each of the three productivity measures (labor, capital and nominal total factor productivity: NTFP) has its own characteristics. Labor and capital productivity are simply calculated by dividing output by labor or capital inputs, whereas NTFP combines labor and capital using weights as the denominator (See page 54 for details). Therefore, labor and capital productivity estimates the efficiency of labor and 126 capital inputs, while TFP measures the overall technical efficiency or factor use. Table 9 summarizes changes in productivity by regional types using index numbers. It is apparent that the trends in labor productivity are quite different from capital and total factor productivity. Capital productivity seems to be more closely related to NTFP than labor productivity. Labor productivity improved rapidly during both periods and improvement was much greater during the second period (Table 9). The accelerated growth of labor productivity is a combined result of the loss of workers, reduction in working hours, and growth in output. Spatial pattern of labor productivity is quite stable over time (Figures 14 and 15). Urban regions as a whole have similar labor productivity to rural areas. As seen in Table 9, the most prominent differentials exist between different urban sizes. Labor productivity is highest for the smallest city group, followed by medium sized and metropolitan cities. Enormous disparities can be seen between the largest and smallest city groups. In rural areas, counties adjacent to urban areas exhibit higher labor productivity than nonadjacent counties. However the disparity between the two types of rural areas is relatively small. Industrialized regions have advantages over the less industrialized regions. Again, the differentials between the two are not significant compared to those among urban areas of different sizes. Finally, peripheral areas display labor productivity 127 Table 9 - Indices of Regional Productivity. Labor Capital NTFP Productivity Productivity ’83 ’88 ’93 ’83 ’88 ’93 '83 '88 ’93 Nation 100 156 336 100 108 91 100 111 99 Urban 101 154 331 107 113 98 106 117 106 Metropolitan 82 121 265 157 142 138 146 145 154 Medium 132 195 388 85 111 95 84 114 101 Small 206 227 522 48 51 45 46 51 46 Rural 96 165 349 76 9O 77 77 91 80 Adjacent 98 173 362 82 94 80 82 95 83 Non-adjacent 92 136 305 62 74 66 66 76 70 Industrial 104 165 359 89 103 92 90 106 99 Less-indust. 92 137 292 137 124 90 130 126 97 Core 94 150 322 102 115 106 102 119 115 Seoul metro. 90 146 320 151 134 134 142 135 143 Southeast 98 154 324 79 101 86 81 107 96 Periphery 124 178 377 96 90 68 93 90 70 Southwest 134 187 406 103 85 59 97 83 59 Other 111 166 331 87 97 92 88 102 101 Note: 1983 = 100 for nation NTFP: nominal total factor productivity 128 129 well above that of core regions. The two core regions have similar levels of labor productivity. Peripheral areas, whether they are located in the Southwest region or elsewhere, have higher labor productivity than core regions. Every type of region experienced rapid improvement in labor productivity, though gains were stronger during the restructuring period. It is rather unexpected that urban and rural areas have similar levels of labor efficiency. The most striking outcome is the lower labor productivity of the largest cities and core regions compared to smallest cities and peripheries. The great level of capital intensity in the latter regions might explain why this pattern is consistent over time. More importantly, this does suggest that the former types of region will have to shed more industrial workers in order to enhance labor efficiency. Capital productivity exhibits significantly different regional patterns from labor productivity (Table 9 and, Figures 16 and 17). As a nation, the progress of capital productivity does not show the same spectacular trend as labor productivity. There was a minor increase during the 1983 to 1988 period. However, in 1993, capital productivity declined to a level below that of 1983. Urban areas maintained higher efficiency in the utilization of capital assets than rural areas. In urban areas, metropolitan cities have absolute advantages over smaller cities, implying positive external economies that were not revealed in labor productivity. 130 131 Similar effects seem to exist in rural areas, in which adjacent counties have higher capital productivity than nonadjacent counties. Industrialized regions do not display advantages over less industrialized regions. In fact, the latter regions had an obvious advantage in 1983 and 1988 over the former, although it had disappeared by 1993. Core regions have superior capital productivity over peripheral regions. The capital region, especially the Seoul metropolitan area, exhibits much higher efficiency in capital utilization than the Southeast region and two peripheral regions. In general, capital productivity displays regional patterns almost exactly opposite to that of labor productivity (Table 9). These patterns might reflect characteristic differences in industrial development over time and space. Those regions with higher labor productivity but lower capital productivity tend to maintain higher rates of capital investment. They are more rapidly industrializing areas. On the contrary, established regions with a longer history of industrial development tend to depend more on labor inputs. This is presumably because these regions have built industrial structures based on cheap and abundant labor during the earlier period of industrialization. Therefore, they will have a larger portion of labor intensive industries and are more likely to reduce labor inputs during the years of high wages and strong labor power. 132 Nominal total factor productivity (NTFP) improved during the first five years, but it declined during the restructuring period in most regional groups (Table 9). The primary reason for the negative growth of total factor productivity should be related to the level of capital inputs and their efficiency. As noted before, a rapid increase in capital inputs during the restructuring period was not followed by comparable growth of output. The combined efficiency of labor and capital reveals distinctive spatial patterns (Figures 18 and 19), which are similar to those of capital productivity (Figures 16 and 17). First, the national trend of improvement during the first five years followed by decreases during the last five years holds true for most regions. The exceptions are found in metropolitan cities in which NTFP tended to increase over time, less industrialized areas and the Southwest region in which NTFP declined throughout the years, and the capital region where NTFP declined initially but increased in following years. Second, enormous disparities exist between the most advanced types of region and remaining regions. The two regional groups that displayed the highest NTFP are metropolitan cities and the capital region in which two largest metropolitan cities are located. In contrast, the two regional types that had the lowest NTFP are the smallest cities and nonadjacent rural areas. Therefore, a clear core- 133 periphery relationship, in a broad sense, is revealed through the regional comparison of NTFP. The highly efficient production system in the capital region and metropolitan cities might be based on the vast amount of social and economic infrastructure. It also suggests that these highly urbanized areas have reacted more successfully to the recent changes in the industrial environment. Therefore, it can be said that these regions continued their role as centers of innovation and the origin of new production methods. The initially high productivity and subsequent decline in less industrialized regions is rather unexpected. Data show that these regions had productivity advantages over industrialized regions until the late 19805. One plausible explanation for the sudden erosion of advantage is that excessive capital accumulation (or overcapacity) had a negative impact on productive efficiency so that they could not produce output up to their capacity. The same explanation could be applied to the relatively low productivity in industrialized regions and the Southeast region, where the majority of industrial growth centers are located. Finally, a consistent pattern exists between urban and rural areas (Table 9). The former displayed superior productivity over the latter, implying the existence of urbanization economies. Within urban regions, metropolitan cities had the highest levels of productivity, 134 135 followed by medium and small sized cities. In rural regions, counties adjacent to urban areas exhibited higher productivity than non—adjacent counties. Sources of Regional Manufacturing Growth The growth accounting model was applied to explain the sources of growth of regional manufacturing output and their change. The model can be restated as: Ln(Q) = Ln(T) + aLn(L) + (l - a)Ln(K) From the model, manufacturing output growth is decomposed into three components: the growth of labor inputs, capital inputs, and TFP or technical efficiency. The results of the growth accounting model verify the overall slowdown in productivity growth and changes in the share of input factors during the restructuring period (Table 10). As a nation, the growth rate of total factor productivity declined during the second period to one half that of the first period. In addition, there has been negative growth in labor inputs and an accelerated growth in capital inputs, demonstrating the distinctive character of recent industrial development in Korea. Subdividing the nation into smaller regions based on location and the level of industrialization does not alter the national pattern greatly. The turnaround in the share of growth of labor inputs, from positive to negative growth, occurred in most regions. Only rural areas, both adjacent and nonadjacent, and the Southwest region did not experience 136 Table 10 - Sources of Manufacturing Output Growth (Percent Per Annum) O Nation 15.08 Urban 13.39 Metropolitan 11.52 Medium 15.65 Small 11.41 Rural 22.04 Adjacent 22.98 Non-adjacent 19.05 Industrial 15.71 Less-indust. 13.73 Core 15.32 Seoul metro. 16.85 Southeast 13.87 Periphery 14.33 Southwest 13.70 Other 15.35 Note: 0: output growth L. K T I—' CONN I—II—IHI—I I—‘I—‘l—‘HNH 1983-88 L K .69 9.91 3. .37 8.03 3. .15 9.26 1. .74 7.90 6. .12 3.33 6. .96 15.39 3. .88 14.08 6. .21 17.61-1. .78 8.71 5 .51 13.13-0. .72 9.13 4. .07 13.61 1. .37 6.47 6. .58 12.24 0. .34 13.97-1. .99 9.67 3. T 48 99 10 01 96 69 02 76 .22 91 47 17 O4 50 61 7O 12. 10. 9. 10. 16. 19 21 11. 13. 11. 11. 10. 15. 16. 12. O 29 35 02 60 O6 .20 18. .93 59 98 01 33 98 72 12 88 03 ' labor input growth weighted by wage share : capital input growth weighted by capital share : total factor productivity growth 1988-93 L .83 .40 .16 .82 .12 .03 .92 .46 .94 .61 .13 .04 .24 .03 .29 .52 11. 10 14 16. 16. 18 K 32 l. .46 2. .44 4. .21 1. .58 1. 93 l. 57 1. .11 2. .29 3. .59 4. .75 2. .95-0. .23-2. .26 3. 80 29 74 21 61 25 O9 37 .68 .39 17 36 21 86 64 28 137 negative growth of labor inputs during the restructuring period. In comparison, the accelerated contribution from the growth of capital inputs have occurred in all types of regions, with exceptions of highly urbanized regions — metropolitan cities and the capital region - and the least urbanized peripheral areas. Regional patterns of the weighted growth rates of labor and capital input should resemble those of unweighted measures (Table 8), as discussed in the previous section. Thus, in this section, emphasis will be placed on TFP. A comparison needs to be made between nominal total factor productivity (NTFP) and total factor productivity (TFP) (See page 53-54 for the detailed explanation). NTFP, as an index measure, is a static concept for a single point in time. TFP more likely portrays change (or improvement) of NTFP between two points in time. Therefore, a higher level of NTFP does not necessarily mean a higher rate of TFP. Rather, the opposite is the norm, with a negative association between the two indices. Figures 20 and 21 show spatial pattern of the growth of TFP. There is evidence that agglomeration economies, such as urbanization and localization effects, play a role in the growth of TFP. Urban regions have higher TFP growth than rural regions, and industrialized regions gained more production efficiency than less industrialized regions (Table 10). The same is true for core and periphery regions with higher rates of growth by the former. Therefore, it can 139 be stated that more advanced regions tend to have a larger proportion of output originating from technological advances, compared to less advanced regions in which direct factor inputs account for the majority of output growth. Therefore, such phrases as ‘growth without productivity’ (Tsao, 1985) or ‘productivity driven economies’ (Page, 1994) should be used with great caution depending on the spatial as well as temporal scale. However, results of the within-group comparison between the two periods tell a slightly different story (Table 10). Metropolitan areas had much lower rates of TFP growth than smaller cities during the first period, but much higher growth rates of productive efficiency during the later period. In rural areas, though adjacent counties had an absolute advantage during the first period, nonadjacent counties displayed higher rates of growth during the second period. Within core areas, the Seoul metropolitan region had much lower growth rates than the Southeast region initially, but the relationship was reversed during the later period. A significant point for the possible explanation of this inconsistent, thus unexpected, within group variations is an apparent strong negative relationship between the growth rates of TFP and that of capital inputs. Sources of Labor Productivity Growth By transforming the growth accounting model, the growth of labor productivity can be decomposed into the share of 140 capital deepening (K/L) and technological advance (T). The equation is restated as follows: Ln(Q/L) = (1— a)Ln(K / L) + Ln(T) As noted before, there was an accelerated improvement of labor productivity during the second period. Regional variation in the growth rates of labor productivity is relatively small (Table 11). The industrializing period exhibited greater regional variation. Less advanced regions, such as the smallest sized cities, nonadjacent rural areas, and peripheral areas, had lower growth rates of labor productivity. The restructuring period does not display a systematic pattern. With regard to the sources of the growth of labor productivity, more significant portion is accounted for by capital accumulation than technological advances. As a nation, the ratio between shares of capital accumulation and technological advances was six to four during the first period, but it widened to about nine to one during the second period. Thus it is apparent that accelerated capital accumulation did not accompany technical advances. The share of capital accumulation is consistently larger in rural regions, less-industrialized regions, and peripheries compared to urban, industrialized, and core regions, respectively. The relationship is reversed in the case of technological advances. Therefore, the more advanced a region is, the more likely it is to rely on technology 141 Table 11 - Sources of Labor Productivity Growth (Percent Per Annum) Nation Urban Metropolitan Medium Small Rural Adjacent Non-adjacent Industrialized Less-indust. Core Seoul metro. Southeast Periphery Southwest Other Note: 8. bmflm 11 OK) \lmd LP 90 .43 .92 .34 .43 .76 .72 .70 .13 .28 .38 .75 .11 .19 .73 .97 1983-88 K/L 5. U) \OU‘Q NNO’XA KO (Db ACDm 42 .44 .82 .33 .54 .06 .70 .46 .91 .19 .91 .59 .06 .69 .34 .27 .48 .99 .10 .01 .96 .69 .02 .76 .22 .91 .47 .17 .04 .50 .61 .70 LP: growth of labor productivity LP 15. 15. 15. .79 .65 13 16 14 14 15. 15. 15 14 15. 15. 13 3.3 3O 65 .97 .77 16. 22 47 19 .27 15. .90 64 01 48 .84 1988-93 K/L 13.52 13.01 10.92 12.58 15.54 13.73 13.67 13.85 12.78 15.58 12.10 11.28 12.69 15.87 18.12 10.56 FJF'DPQ H .80 .29 .74 .21 .61 .25 .09 .37 .68 .39 .17 .36 .21 .86 .64 .28 K/L: growth of capital-labor ratio weighted by capital share T: growth of total factor productivity 142 improvement than the raising of the capital-labor ratio for the growth of labor productivity. It is debatable which of the two sources of labor productivity growth must be promoted to enhance the competitiveness of regional industries. Data analysis shows that the dominance of capital accumulation as a source of labor productivity growth increased significantly. A problem with this pattern of productivity growth is that it requires heavy investment for the improvement of the capital-labor ratio if labor inputs are not reduced radically. The over- dependence on the growth of capital accumulation may not be a cost efficient strategy for industry as a whole. The two major expenses, capital investment and wages, must be covered by a higher growth of output, which apparently has not happened. Therefore, in the long run, more emphasis needs to be placed on the improvement of technology, which demands c00perative effort from various sources. Determinants of Regional Productivity A multiple regression model was applied to test the major determinants of regional productivity (TFP) growth. The results are summarized in Table 12. The proposed model explains the variation in the growth of regional productivity well, with a coefficient of determination 0.791 for the period of 1988-88 and 0.801 for the 1988-93. The model does not have serious multicollinearity problems. Although one independent variable (LAND) has a relatively 143 Table 12 - Test of the Determinants of Regional Productivity Dependent variable: growth rates of 1983-88 Independent Std. Coeff. t Variables CONSTANT - -4.558** LnCL -0.727 -17.787** (0.700) LnOUT -0.336 7.656** (0.608) WAGE 0.343 8.256** (0.678) LAND -0.201 -4.418** (0.567) PDEN 0.023 0.629 (0.851) LQ 0.021 0.556 (0.826) ACCESS 0.019 0.494 (0.794) R2 0.791 F 96.503** Note: parentheses are tolerance values ** significant at .01 * significant at .05 TFP 1988-93 Std. Coeff. - -4 -0 698 -20 (0.836) 0.419 10. (0.666) 0.481 14 (0.856) -0.149 —4 (0.749) 0.076 2 (0.811) 0.101 2 (0.793) —0 025 -0 (0.898) 0.801 115 362** t .295** .261** 847** .122** .093** .169* .866** .763 144 low tolerance value (0.567) during the first period, it does not prohibit the statistical test of the variable. All but one of the seven coefficients of independent variables have identical signs for both periods. The exception is ACCESS (regional dummy for expressway accessibility), which has a positive sign in the first period, and a negative sign in the second period, though it is not significant for any period. Four of seven independent variables are significant (at 0.05 level) for the first period; six are significant for the second period. In addition, variations in the standardized coefficients and significance level of some independent variables for the two periods are relatively large. This indicates that notable changes occurred in the impact of these variables on the growth of regional productivity over time. The first variable (LnCL), the growth rate of capital- labor ratio or capital intensity, is highly significant for both periods. The variable has a negative coefficient, suggesting the detrimental effect of capital accumulation on productivity advances. The strong negative relationship between the two variables is exactly opposite the relationship found in advanced economies. This exceptional result reveals a clear implication: new capital investment, which has been a primary source of industrial development in Korea, has not served to enhance productivity. Therefore, the embodiment or vintage effect from the introduction of new capital has not been realized in the Korean 145 manufacturing sector. A slightly diminished negative coefficient, but a larger t-value of the variable in the second period, implies that an improvement in capital utilization was minimal even during restructuring. The second explanatory variable (LnOUT) is also highly significant and positive. Thus, the cumulative causation effect, or Verdoon’s law, is confirmed. The positive effect of manufacturing output growth on the advance of productivity was significantly larger during the second period. The third variable (WAGE), the average wage ratio in the initial year, is significant and has positive coefficients for both periods. This suggests that firms are responsive (positively) to changes in wage ratio for the improvement of productivity. A higher level of significance for the second period implies that the importance of the wage ratio as a stimulant of productivity has increased over time. The fourth variable (LAND), the growth rate of land assets to the output ratio, has a strong negative association with regional productivity growth, reflecting a side effect of rapid land price increases in Korea. It also suggests that excessive acquisition of land assets for speculative purposes, for example, can do harm to industrial productivity. When land prices are rising rapidly, available resources cannot be allocated optimally for productive purposes, resulting in negative consequences on productivity. The fifth variable (PDEN), population density, 146 has positive coefficients for both periods, but significant only in the second period. In addition, the explanatory power of population variable is less than other variables related to output, investment, and wages. The positive effect of population density suggests that urbanization economies were a more significant source of productivity advance during the restructuring period. The sixth variable (LQ), the location quotient at the initial point, has positive coefficients for both periods, though it is significant only for the second period. Thus the positive effect of localization economies is rather a new phenomenon. This appears to be contradicted by the results of the sources of growth analysis, in which industrialized regions, as a whole, had a higher productivity growth than less industrialized region for both periods. In that case, however, each region was grouped depending on whether its location quotient is greater or less than unity. The last variable (ACCESS), regional dummy for expressway accessibility, is not significant for either period. Thus, in terms of productivity growth, such locational advantages as direct access to modern highway system cannot be verified. The variable has a positive coefficient for the first period, though it is negative during the second. This is presumably because the diffusion of innovative technology and new production systems does not proceed along the transportation network alone, but requires the development of a wide range of social infrastructure. 147 Spatial Inequality The preceding analysis of the changes in spatial patterns of industrial location and regional productivity has shown that formerly less favored regions (rural, less industrialized, and peripheral areas) performed well during the period of industrial restructuring. In contrast, more advanced regions (urban, industrialized, and core areas) did not show such stellar performance during the restructuring period as they did during the rapid industrializing period. The evident differentials between the two types of regions strongly suggest that spatial inequalities in location and productivity have declined over the research period. In this section, more specific evidence of spatial convergence or divergence are provided based on the results from indices of inequality and simple regression analysis. First, two index measures of inequality - the Gini coefficient and the coefficient of variation - are employed to compute the level of regional inequality and to examine its change over time. As discussed before, the Gini coefficients are computed for gross indicators of regional manufacturing activity, whereas the coefficients of variation are calculated for the indices of regional productivity. For both measures of inequality, a weighted formula is employed to account for enormous differences in population size among cities and counties. Second, a series of bivariate regression models are applied to test spatial 148 catch-up or convergence of industrial location and productivity. Inequalities in Industrial Location Eight gross measures of industrial location were used as basic data for the Gini coefficients (Table 13). Overall, the Gini coefficients reveal a trend of diminishing interregional inequalities. Comparing industrializing and restructuring periods, changes in the Gini coefficient are slightly different. The first period shows a strong tendency of diminishing inequality. The Gini coefficients reveal decreases in seven (out of eight) indicators of industrial location. The most significant reduction occurred in the value of fixed assets, followed by employment, gross output, worker remuneration, floor space, value added, and site area. However, inequality increased in the distribution of manufacturing establishments. The second period witnessed a decrease in the inequality in five indicators. Employment exhibited the strongest spatial convergence, followed by worker remuneration, value added, gross output, and fixed assets. It is notable that the spatial distribution of industrial employment is one of the fastest converging areas of manufacturing activity. There were three areas in which spatial disparities increased during the period of restructuring. The number of establishments continued to show spatial concentration. In addition, increasing 149 Table 13 - Change in Regional Inequality 1983 1988(A) 1988(B) 1993 1988(C) 1993(D) GINI EST 0.311 0.323 0.326 0.327 103.8 100.6 WKR 0.458 0.419 0.426 0.392 91.5 92.0 RMN 0.504 0.476 0.484 0.455 94.4 94.0 OPT 0.594 0.551 0.559 0.538 92.7 96.1 VAD 0.545 0.527 0.535 0.509 96.6 95.1 AST 0.648 0.581 0.593 0.590 89.8 99.5 SIT 0.617 0.602 0.611 0.636 97.7 104.0 FLR 0.517 0.495 0.505 0.522 95.8 103.4 C.V. LP 0.764 0.721 0.815 0.710 94.4 87.1 CF 0.630 0.547 0.506 0.674 86.7 133.2 NTFP 0.573 0.506 0.533 0.706 88.2 132.6 Note: 1) (A): Based on 1983 administrative areas (B): Based on 1993 administrative areas 2) (C): 1983:100, (C): 1988(B)=100 3) EST: establishment, WKR: worker, RMN: remuneration OPT: gross output, VAD: value added, AST: fixed asset, SIT: site area, FLR: floor space 4) LP: labor productivity, CP: capital productivity NTFP: nominal factor productivity 150 inequality was newly found in the areas of factory sites and floor space. Increasing inequality in the number of establishments reflects spatial concentration of newly formed small to medium sized businesses in urban areas, whereas increasing disparities in the two site related indices might be due to the shortage of industrial space in urban areas. In the meantime, the absolute level of inequality is quite different from temporal changes. In spite of increasing regional inequality in the number of establishments, the absolute level of inequality in the index is lower than any other indicator. In addition, employment, worker remuneration, and floor space have lower levels of inequality than fixed assets and factory sites. Two measures of output, gross output and value added, occupy an intermediate level. The relationship among the inequalities of the eight indices of industrial location seems to be stable over time. This is supported by the fact that the rank order of the Gini coefficients among those indices remained virtually unchanged, with only one exception. The results of the analysis suggest that the spatial restructuring of industrial location has multiple dimensions. As an example example, the spatial spread of manufacturing employment is not accompanied by a comparable decentralization in the number of firms. Therefore, when implementing an industrial location policy, a specific 151 industrial indicator could be set as the target of the policy. . A series of bivariate regression models were run to test spatial convergence or catch-up processes of industrial location and regional productivity. The model is restated as follows: Ln(Y,2/Y,,)=a+b,LnYn, where: subscripts are years A negative and significant coefficient of the slope (b1) implies spatial convergence or catch-up, and a positive coefficient suggests spatial divergence. In general, results of the regression analysis reveal a strong tendency of spatial convergence of industrial location (Table 14). During the 1983-88 period, seven out of eight gross indices of industrial location have negative coefficients. Of the seven variables with negative coefficients, four are significant and three are not significant (at 0.05 level). Significant variables are gross output, value added, fixed assets, and site area. Insignificant variables are employment, remuneration, and floor space. It must be remembered that all three insignificant variables also exhibited a decline in Gini coefficients. This might be due to conceptual differences between the two techniques. Regression analysis is affected by the growth rate of indices, whereas Gini coefficients are determined by the absolute level of those indicators. It is a matter of choice whether the reduction of regional inequality should be related to faster growth rates in less developed regions or Table 14 - Test of Gross indices Establishment Employment Remuneration Gross Output Value Added Fixed Asset Site Area Floor Space Productivity LP CP NTFP Note: LP: CP: NTFP: Spatial Convergence 152 1983-88 b coeff. 0.112** 0 —0.018 0 -0.027 0 —0.085** 0 -0.067** 0 -0.107** 0 -0.085** 0 -0.032 0 —0.288** 0 —0.682** 0 -0.603** 0 labor productivity capital productivity nominal total factor productivity ** significant at 0.01 R2 .103 .004 .008 .062 .041 .068 .049 .009 .197 .351 .289 1988-93 b coeff. —0.042 0 -0.132** 0 -0.147** 0 -0.167** 0 -0.152** 0 -0.153** 0 —0.133** O —0.126** 0 -0.355** 0 —0.522** 0 -01444** 0 R2 .017 .215 .248 .255 .228 .169 .098 .125 .323 .325 .228 153 the absolute interregional transfer of industrial activities from developed areas to less developed. In fact, either of these cases can be accepted as the process of spatial convergence. The number of establishments has a significant positive coefficient, implying increasing divergence. This result is same that of the Gini coefficient. During the restructuring period, all of the indices of gross measures of industrial location have negative coefficients. Only the number of establishments is not significant. The two indices that showed an increase in the Gini coefficient (site area and floor space) are also highly significant, although their coefficients of determination are smaller than those significant variables. Two conclusions can be drawn from the regression analysis. First, the proposed regression model is a much better fit for the restructuring period. The coefficients of determination are much higher and larger number of variables are significant. This implies that spatial convergence, in relative terms, was more significant during industrial restructuring. Second, neither the regression analysis nor the Gini score supports the spatial convergence of the aggregate number of manufacturing firms. Inequalities in Regional Productivity Three measures of regional productivity - labor, capital and nominal total factor productivity - are used as basic data for the coefficient of variation and simple 154 regression analysis. The results (Table 13) show that labor productivity is quite different from capital and total factor productivity. Labor productivity has higher levels of inequality than the other two, though it declines consistently over time. On the contrary, inequalities in capital and total factor productivity decreased significantly during the industrializing period, but increased rapidly during the restructuring period. As a result, the coefficients of variation of the three measures of productivity were much more similar to each other in 1993 than previously. The different behavior of labor productivity and the other productivity indices reflects the locational trends exhibited by different indices affecting productivity measures. Results of the regression analysis are more convincing. All coefficients for the three productivity indices are negative and significant for both periods. Thus, the hypothesis of spatial convergence or catch-up can be accepted for labor, capital, and total factor productivity. It must be noted that the negative and significant association between the growth rate of productivity and initial level of productivity seems not to be a sufficient condition for the convergence of regional productivity toward the national average. The coefficients of variation for capital and total factor productivity increased during the second period, while regression analysis revealed the existence of spatial catch-up. Therefore, in spite of the 155 strong performance by regions with lower productivity, the absolute disparities in capital and total factor productivity seemed to persist. The results of various analyses presented in this chapter generally supported research hypotheses, in spite of minor exceptions and unexpected outcomes. In particular, proposed hypotheses better explained more recent changes than changes in the previous industrializing period. The following summaries (Table 15) concisely compare major research hypotheses and results. Table 15 - Summary of Results Topic Industrial location Locational pattern Factors of Location Change Wage ratio Capital accumulation Labor intensity Land asset growth Urbanization effect Localization effect Highway access Regional Productivity Pattern of productivity Sources of growth and regional hierarchy Determinants of productivity Capital deepening Output growth Wage ratio Land asset growth Urbanization effect Localization effect Highway access Regional inequality Industrial location Industrial productivity Regional inequality 156 Hypothesis Deurbanization Rural industrialization Decentralization Regional effect effect effect effect effect effect effect effect Negative Positive Negative Negative Negative Negative Positive Regional hierarchy Industrialization effect Core advantage Declining labor share in high order region High technology share in high order region effect effect effect effect effect effect effect Negative Positive Positive Negative Positive Positive Positive Spatial convergence Spatial convergence Overall decrease Note: C: confirmed C2: confirmed for restructuring period MC: mostly confirmed PC: partly confirmed NC: not confirmed Result MC PC MC MC 2000000 CNN MC MC MC Chapter 7 CONCLUSION Conclusions Industrial restructuring has brought about substantial changes in traditional growth patterns of regional manufacturing employment in Korea, even if it might be premature to conclude these changes were caused by a fundamental shift of the regime of capitalist accumulation. During the industrializing period (1983-88), broadly defined core areas, such as urban areas and their adjacent rural counties, industrialized areas, the capital region and the Southeast region, attracted the majority of new manufacturing employment. During the industrial restructuring period (1988-93), these more advanced regions were heavily affected by a national trend of deindustrialization, whereas less industrialized and peripheral regions including rural areas, and the Southwest and most remote provinces, emerged as newly industrializing spaces. These new patterns of industrial location might be comparable to those that have taken place in western advanced countries (Haynes and Machunda, 1987; Keeble, 1979; 157 158 Scott 1988a). Also, they were observed in recently industrialized countries in southern Europe (Vazquez- Barguero, 1990), as well as newly industrializing countries such as Brazil (Storper, 1991) and Taiwan (Selya, 1993; Todd and Hsueh, 1988). In addition, the spatial spread of industrial location through regional hierarchical system was very similar to the filtering down process suggested by theorists of regional product-cycle (Erickson, 1976; Erickson and Leinbach, 1979; Moriarty, 1991; Rees, 1979). Gross employment change, location quotients, and simple regression analysis provided ample evidence of the emerging process of decentralization of industrial location. Multiple regression analysis identified a significant association between the growth of regional manufacturing employment and economic and geographical factors. Throughout the research period, rapid rises in the regional wage ratio and land prices were negatively associated with the growth of manufacturing employment, whereas capital investment had a strong positive impact. These three factors are some of the most important triggers of industrial restructuring in Korea (Kim, 1993; Park, 1994). Factors that became more important in recent years were agglomeration indicators, such as population density and the location quotient, and the labor intensity of regional industries, all of which had negative (and significant) coefficients only for the restructuring period. Accessibility to modern highway 159 networks had positive impact on the location of manufacturing industries, but with some time lag. Therefore, the emergence of new industrial spaces in former peripheral areas can be explained by cost advantages in these regions (Carlino and Mills, 1987; Chiniz, 1986; Hakanson and Danielsson, 1985), as well as physical constraints in urban location (Fothergill et al, 1987; Fothergill and Gudgin, 1982; Scott, 1982; Tulpule, 1969). However, a large portion of variation remained unexplained, reflecting the omission of socio-political variables. In summary, the overall process of industrial location in Korea revealed similarities to typical developing economies during the industrializing period, but more closely resembled advanced economies during the restructuring period. The examination of regional productivity revealed not only the distinctive characteristics of the growth of Korean manufacturing industry, but also clear spatial patterns. Throughout the research period, the growth of output of Korean manufacturing depended largely on the growth of factor inputs, especially capital investment. The accelerated growth of capital accumulation was universal, leading to the rapid growth of labor productivity, but a decline in capital efficiency. The role of productivity advances was very limited, with decreases over time, suggesting a slowdown in the improvement of technical efficiency of Korean industry. The opposite phenomenon was the case in advanced countries (Mayes, 1996). Thus, it is 160 unlikely that Korean industries have fully accomplished such objectives of restructuring as rationalization of production systems, and improvement of productivity and profit rates (Vazquez-Barguero, 1990). A clear spatial pattern of productivity was exhibited through regional hierarchies. Urban areas, industrialized areas, and core areas had more efficient production systems than rural areas, less industrialized areas, and peripheries, respectively. This spatial pattern corresponds to results from Sweden (Aberg, 1973), the US (Moomaw, 1981; Nicholson, 1978) and Brazil (Hansen, 1990). Metropolitan cities and the capital region, in particular, had absolute advantages over other types of regions. This might be due to the positive agglomeration economies in these regions. There was no evidence that urban productivity advantages are declining as in US metropolitan areas (Blackley, 1986; Carlino, 1985; Moomaw, 1985) or Canadian cities (Soroka, 1990). Regression analysis revealed critical factors that are associated with the technological improvement of production. First, the accumulation of capital, the single most important source for the growth of Korean manufacturing, had a strong negative relationship with productivity growth. The vintage effect from new capital embodying productivity enhancing components was not confirmed in Korea, which is contrary to advanced industrialized economies (Abramobitz, 1986, 1990; Dollar, 1991; Dollar and Wolff, 1993; Wolff, 161 1991; Rigby, 1995). But, as pointed out by Dollar and Sokoloff (1990) and Park (1986), this does not seem to be unusual in Korea. It is rather surprising that industrial restructuring has not brought about any significant improvement of capital efficiencies. However, the growth rate of output or economies of scale was positively associated with the improvement of productivity, corresponding to Casetti (1984). In addition, more efficient resource allocation was also found to be advantageous for productivity, as exemplified by the negative coefficients of the growth of land assets ratio. With regard to the effect of wages, a higher regional wage ratio was shown to be a positive stimulant for productivity, which is comparable to Baily et al (1996). Urbanization and localization economies were also important factors (Beeson, 1987; Watts, 1987), but more so for the period of restructuring. However, the positive impact of highway accessibility was not confirmed, suggesting the need to employ a more comprehensive transportation index (Mas et al, 1996; Moomaw and Williams, 1991). An important interpretation can be drawn from the relationship between new locational trends and spatial patterns of productivity. A clear trade-off relationship exists between the trend of locational decentralization and the improvement of competitive advantage of national industries. The decline of manufacturing employment in more advanced regions is not due to disadvantages in 162 productivity, but because of cost disadvantages compared to less developed areas. Deindustrialization in regions with more efficient production systems and rapid industrialization in less efficient areas might interact to reduce the overall efficiency of Korean manufacturing industry. Thus, two options can be pointed out. First, new industrial location policies should be selective, considering both positive external economies on productivity in established regions, and cost benefits in new industrial spaces in order to maximize locational potentials. Second, further effort should be made to enhance technological advances of industries in newly industrializing areas. The negligible contribution of productivity advances to the growth of industry output poses a challenge for the improvement of the overall efficiency of Korean manufacturing industry. The meager contribution of technological improvements for industrial development does not seem to be unique in Korea. It was found to be true in Singapore (Tsao, 1985) and Taiwan (Choi, 1990) as well. Lower productivity of Korean manufacturing means that capital expenses for investment did not yield enough revenues to recover costs. This can lead firms with lower productivity to seek external sources for new investment, causing financial difficulties during economic downturns. With regard to regional inequality, the impact of industrial restructuring is less conclusive. Different methods of analysis revealed slightly different results. 163 Gini coefficients suggest that the spatial convergence of gross indicators of manufacturing activities was not as strong during the period of restructuring as in the industrializing period. A slight increase in inequality occurred during the restructuring period in site area and floor space, reflecting growing disparities in the availability of industrial land. However, inequality in employment, worker remuneration, and output (both value added and gross output) continued to decline. Inequalities in regional productivity show similar patterns to location change between the two periods. The coefficients of variation indicate that regional disparities decreased in three measures of productivity - labor, capital, and total factor productivity — during the industrializing period. However, during the restructuring period, disparities increased in capital productivity and TFP, but decreased in labor productivity. This might be due to the subpar performance of productivity by newly industrializing regions compared to established regions. On the other hand, the results of regression analysis suggest that the spatial catch-up process was stronger during the later period, especially for gross indicators. The three productivity measures exhibited spatial catch-up in both periods. Therefore, industrial restructuring had not radically altered the existing spatial system of manufacturing activities (Fielding, 1994) and spatial patterns of industrial productivity, in spite of the 164 superior performance of less developed regions. This suggests that ‘regional inversion’ (Suarez-Villa and Cuadrado Roura, 1993) has not taken place in Korea yet. Analysis of regional inequality indicates the importance of interpretation of the outcome with the acknowledgement of their basic principles. In conclusion, industrial restructuring in Korea since the late 19805 has accelerated the process of polarization reversal of manufacturing location, which began in the late 19705 (Richardson, 1980). Locational decentralization is a strong indication that geography is playing an active role for Korean industrial restructuring. The general implication of industrial restructuring on spatial development seems to be more optimistic in Korea compared to advanced countries. An increasing number of regions that were not the locus of previous industrialization are participating in the new phase of development. However, convergence of regional productivity was not as clear as industrial location. The trade-off relationship between industrialization and regional productivity might constrain the pace of spatial convergence of economic well-being. Therefore further effort is needed for the improvement of productive efficiency of industries in less developed areas, in addition to the promotion of decentralization. 165 Future Research Areas The current research has examined spatial aspects of industrial restructuring with an emphasis on location, productivity, and inequality of Korean manufacturing industry. There are several areas that merit additional investigation in order to deepen understanding of the process of industrial and spatial change. There is a need to improve the explanatory power of regression models of change in industrial location. The current research employed a very limited set of explanatory variables, which though significant, accounted for a small part of the variation in the growth of regional manufacturing employment. There are additional variables available from published data sources that could be incorporated into future studies. They include variables related to regional industrial policies, such as the provision of industrial estates and various locational subsidies; indices of social infrastructure comprising various modes of transportation, telecommunication, and basic infrastructure; and variables related to labor relations and human capital. The current research focused on whole cities and counties in Korea to provide an overall picture of industrial and locational changes. A micro scale locality study is needed to examine the effect of industrial restructuring more specifically. One of the traditional industrial centers or new industrial spaces, or a pair of them, could be selected as a study area. Specific strategies 166 of business restructuring in such areas as labor relations, production processes, external linkages, and research and development activities could be surveyed to examine the effect of such strategies on productivity and business profits. In addition, business failure or success can be investigated using the variables related to the extent of restructuring effort, productive efficiency, and geographical location. Another area that demands further investigation is industrial complexes. These are (and will be) the central places of Korean manufacturing industry, and were created by government policies. It is virtually unknown whether firms in these complexes are more efficient and innovative than those in other places. One of the primary objectives of the provision of industrial complexes should be the generation of endogenous external economies from dense networks of inter-firm linkages. The current study identified positive localization economies, but from an aggregated data set. It will be possible to examine the net performance of industrial complexes, both individually and in the aggregate, in a few years when recently published data sets are accumulated. One of the most interesting and significant findings of this study is the strong negative association between capital accumulation and improvement of regional productivity. Although the negative association is not a new phenomenon in Korea (Dollar and Sokoloff, 1990), there is 167 little evidence that the efficiency of capital use improved, even during the restructuring period. How does this happen and why is it so stable over the periods? The answer for the question is crucial because it is widely believed that excessive capital investment with diminishing efficiency led to the financial crisis of Korean industries in the late 19905. How can geographical studies contribute to the understanding of the mechanisms and processes of negative cumulative causation effect of capital investment on the efficiency of the Korean production system? The final list of additional research area involves examining the impact of industrial restructuring on regional development. It has been shown that industrial restructuring has brought about the overall convergence of industrial location and regional productivity. However, it remains unanswered whether restructuring has reduced regional gaps in income and wealth through the decentralization of manufacturing location or aggravated regional disparities by deepening the spatial division of labor with concentration of advanced and profitable activities in a limited number of regions. The economic crisis of the late 19905 not only provides research opportunities, but also demands diagnoses and practical solutions from the academic world. The magnitude and impact of the imminent restructuring of Korean economy in the late 19905 and thereafter will surpass that which occurred since the late 19805. The massive economic 168 restructuring experience of western developed countries can be a starting point for the upcoming spatial reorganization of the Korean production system. How will unprecedented business failures and restructuring affect and be affected by geography? How can geographers contribute to organize advanced production systems over space? Further research effort should be made to extend our limited knowledge of the geographic modus operandi of the capitalist accumulation system. APPENDICES APPENDIX A APPENDIX.A Derivation of Growth Accounting Medal The output of an economic activity depends on the factors of production that are used. The general form of this relationship can be written as: Q=f(K,L,T) (A-l) where, Q is output; K, L, and T are the total inputs for capital, labor, and the level of technology, respectively. Equation (A-l) can be converted to a traditional Cobb- Douglas production function: Q=TLaKfl (A-2) where: a and B are output elasticities of labor and capital. Assuming neutral technical change and constant returns to scale on output, the sum of a and B is equal to unity. In this case, the equation (A-2) becomes: Q = TLaKl—a (A_3) The assumption of constant returns is more reasonable as a longer term explanation, rather than for a single year, since it is based on the long-term equilibrium of factor elasticities in a competitive economy (Park, 1986). Under long-term equilibrium, when factors are paid for their marginal products, the output elasticity of labor input is equal to labor’s distributional share of output. Therefore the share of wages to outputs can be an estimator of a. Taking the logarithm, equation (A-3) can be rewritten to 169 170 show the sources of output growth (Dollar and Wolff, 1993; Jefferson and Xu, 1994; Park, 1986; Wolff, 1991): Ln(Q) = Ln(T) + aLn(L) + (1 — a)Ln(K) (A—4) where: Ln(Q), Ln(L), and Ln(K) are the logarithmic growth rates of value added, labor input, and capital input between two time points, respectively; Ln(T), a residual term, is the growth of total factor productivity; a equals the average wage share to value added over the period. Equation (A—3) can be rewritten to decompose labor productivity growth into the contribution of capital accumulation (capital-labor ratio) and the growth rate of TFP or productive efficiency as a residual (Anderson, 1990; Dollar and Sokoloff, 1990; Wolff, 1991). From equation (A- 3), ' Q/L = TL“"K"“ =TI“”VKF“ =7XK7LYF“ Therefore, taking the logarithm, Ln(Q/L) =(1— a)Ln(K/L) + Ln(T) (A-5) where: Ln(Q/L) and Ln(K/L) are the logarithmic growth rates of labor productivity and capital-labor ratio between two time points, respectively; Ln(T) and a are same as above. APPENDIX B APPENDIX B Study Area NO CITY '83 '88/‘93 NO CITY '83 '88/'93 1 SEOUL / I/ 38 DAECHON / 2 PUSAN / I/ 3 9 ONYANG J 3 TAEGU / / 4 0 SOSAN / 4 INCHON / I 4 1 JONJOO / l 5 KWANGJOO / I 4 2 KOONSAN / l 6 TAEJON / I 4 3 IRI / I/ 7 SOOWON / I 4 4 JONGJOO / I 8 SONGNAM / l 4 5 NAMWON I I 9 ANYANG / I 4 6 KIMJE / 1 0 POOCHON / l 4 7 MOKPO / I/ 11 UIJONGBOO / l 48 YOSOO I J 12 KWANGMYONG / J 4 9 SOONCHON / I/ 13 SONGTAN / I 50 NAJOO I I 14 TONGDOOCHON / l 5 1 YOCHON / l 15 ANSAN / J 52 E-KWANGYANG / 1 6 KWACHON / 53 POHANG / I 17 KOORI / 54 KYONGJOO J I/ 1 8 PYONGTAEK I 55 KIMCHON / I 1 9 MIKUM / 5 6 AN DONG / I 2 0 OSAN / 57 KOOMI I J 2 1 SIHUNG / 58 YONGJOO / I/ 22 KOONPO / 5 9 YONGCHON I I/ 23 UIWANG / 60 SANGJOO / 2 4 HANAM / 61 J OMCHON I 25 KOYANG / I 62 KYONGSAN / 2 6 CHOONCHON / l 63 CHANGWON I l 27 WONJOO / l 64 ULSAN / I 2 8 KANGNUNG / I/ 65 MASAN / I/ 2 9 TONGHAE I I 66 JINJOO / I 30 TAEBAEK I J 67 JINHAE J I 31 SOCKCHO / J 68 CHOONGMOO / I 32 SAMCHOK I 69 SAMCHONPO I I/ 33 CHONGJOO / J 7 0 KIMHAE / I 34 CHOONGJOO / l 7 1 MI LYANG / 35 JECHON / l 72 JANGSUNGPO / 36 CHONAN I J 7 3 JEJOO / / 37 KONGJOO / 7 4 SOGWIPO / l 171 NO 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 COUNTY YANGJOO S-YANGJOO YOJOO PYONGTAEK HWASONG SIHUNG PAJOO KWANGJOO YONCHON POCHON GAPYONG YANGPYONG YICHON YONGIN ANSONG KIMPO KANGHWA CHOONCHON HONGCHON HOENGSONG WONJOO YONGWOL PYONGCHANG JONGSON CHOLWON HWACHON YANGGOO INJE KOSONG YANGYANG MYONGJOO SAMCHOK CHONGWON POEUN OKCHON YONGDONG CHINCHON KOESAN UMSONG CHOONGWON JECHON TANYANG '83 SISISISISI\I\.\.\I\~‘~‘~‘~‘~‘~‘~‘~‘~\~\I\I\.\~\~‘~‘~‘\‘~‘~‘~‘~‘~‘~‘~‘~‘~‘~‘~‘~‘I\.\. '88/'93 ‘\‘\‘\‘\‘\‘\‘\‘\‘\‘\‘\‘\‘\‘\‘\‘\\\‘\‘\‘\‘\‘\‘~‘\‘\‘\‘\‘\‘\‘\‘\‘\‘\‘\‘\‘\ \~\.\.\\\\ 172 NO 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 COUNTY KUMSAN YONKI KONGJOO NONSAN POOYO SOCHON PORYONG CHONGYANG HONGSONG YESAN SOSAN TAEAN TANGJIN ASAN CHONAN WANJOO JINAN MOOJOO JANGSOO IMSIL NAMWON SOONCHANG JONGUP KOCHANG POOAN KIMJE OKKOO IKSAN TAMYANG KOKSONG KOORYE KWANGYANG YOCHON SEUNGJOO KOHEUNG POSONG HWASOON CHANGHEUNG KANGJIN HAENAM YONGAM MOOAN '83 ‘\‘\‘\‘\‘\‘\‘\‘\‘K‘\‘\‘\‘\‘\‘\‘\‘\‘\‘\‘\‘\‘\‘\‘\‘\‘\‘\‘\‘\‘\ ‘~‘~‘~‘~‘~‘~‘~‘~‘~\~‘~ '88/‘93 ‘\‘\‘\‘\‘\‘\‘\‘\‘\‘\‘\‘\‘\‘\‘\‘\‘\‘\‘\‘\‘\‘\\\‘\‘i‘\‘\‘\‘\‘\‘\‘\‘\‘\‘\‘\‘\‘\‘\‘\‘\‘\ 173 NO COUNTY '83 '88/‘93 NO COUNTY '83 '88/‘93 159 NAJOO 160 HAMPYONG 161 YONGKWANG 162 CHANGSONG 185 YECHON 186 YONGPOONG 187 PONGHWA 188 ULCHIN 163 WANDO 189 CHINYANG 164 JINDO 190 UIRYONG 165 SINAN 191 HAMAN 166 TALSONG 192 CHANGNYONG 167 KOONWI 193 MILYANG 168 UISONG 194 YANGSAN 169 ANDONG 195 ULSAN 170 CHONGSONG 171 YONGYANG 172 YONGDOK 173 YONGIL 174 KYONGJOO 175 YONGCHON 176 KYONGSAN 177 CHONGDO 178 KORYONG 179 SONGJOO 180 CHILKOK 181 KUMRUNG 182 SONSAN 183 SANGJOO 184 MOONKYONG 196 KIMHAE 197 CHANGWON 198 TONGYONG 199 KOJE 200 KOSONG 201 SACHON 202 NAMHAE 203 HADONG 204 SANCHONG 205 HAMYANG 206 KOCHANG 207 HAPCHON 208 N-CHEJOO 209 S-CHEJOO \'\\\\\'\\\\\\\\\\\\\\'\\\\\\ \\\\\\\\\\\\\\\\\\\\\\'\'\\\ \\\\\\\\\\\\\\'\\\\\\\\\\'\ \'\\\\'\\\\\'\\\\'\\\\\\'\\\\\ Note: 1) Checked marks reflect administrative areas in respective year. 2) Regional numbers are identical to those in Figure 1 (page 80). BIBLIOGRAPHY BIBLIOGRAPHY Aberg, Yngve, 1973, Regional Productivity Differences in Swedish Manufacturing, Regional and Urban Economics, 3(2): 131-156. Abraham, Filip, and Paul Van Rompuy, 1995, Regional Convergence in the European Monetary Union, Papers in Regional Science, 74(2): 125-142. Abramovitz, Moses, 1986, Catching Up, Forging Ahead, and Falling Behind, The Journal of Economic History, 46(2): 385-406. ' Abramovitz, Moses, 1990, The Catch-Up Factor in Postwar Economic Growth, Economic Inquiry, 28(1): 1-18. Aji, Maria Astrakianaki, 1995, Intra-metropolitan Productivity Variations of Selected Manufacturing and Business Service Sectors: What Can We Learn from Los Angeles? Urban Studies, 32(7): 1081-1096. Alonso, William, 1968, Urban and Regional Imbalances in Economic Development, Economic Development and Cultural Change, 17(1): 1-14. Alonso, William, 1980, Five Bell Shapes in Development, Regional Science Association Papers, 45: 5-16. Amin, Ash and A. Malmberg, 1992, Competing Structural and Institutional Influences on the Geography of Production in Europe, Environment and Planning A, 24(3): 401-416. Amin, Ash, and John Goddard (eds.), 1986, Technological Change, Industrial Restructuring and Regional Development, London: Allen & Unwin. Amos Jr., Orley M., 1988, Unbalanced Regional Growth and Regional Income Inequality in the Latter Stages of Development, Regional Science and Urban Economics, 18(4): 549-566. 174 175 Amstrong, Harvey W., 1995, Convergence Among Regions of the European Union, 1950-1990, Papers in Regional Science, 74(2): 143-152. Anderson, W. P., 1990, Labor Productivity Growth in Canadian Manufacturing: A Regional Analysis, Environment and Planning A, 22(3): 309-320. Andrews, Kim and James Swanson, 1995, Does Public Infrastructure Affect Regional Performance? Growth and Change, 26(2): 204-216. Angel, David P., and Jeffrey Mitchell, 1991, Intermetropolitan Wage Disparities and Industrial Change, Economic Geography, 67(2): 124-135. Ark, Bart van, 1996, Productivity and Competitiveness in Manufacturing: A Comparison of Europe, Japan and the US, In Wagner, Karin and Bart van Ark (eds.), International Productivity Differences: Measurement and Explanation, Amsterdam: ELSEVIER. Asheim, Bjorn, 1992, Flexible specialization, Industrial Districts, and Small Firms: A Critical Appraisal, In Ernste, Huib and Verena Meier (eds.), Regional Development and Contemporary Industrial Response: Extending Flexible Specialization, London: Belhaven Press. Auty, Richard M., 1990, The Impact of Heavy—Industry Growth Poles on South Korean Spatial Structure, Geoforum, 21(1): 23-33. Auty, R. M., 1995, Industrial Policy, Sectoral Maturation, and Postwar Economic Growth in Brazil: The Resource Curse Thesis, Economic Geography, 71(3): 257-272. Bade, Franz-Jasef and Klaus R. Kunzmann, 1991, Deindustrialization and Regional Development in the Federal Republic of Germany, In Rodwin, Lloyd and Hidehiko Sazanami (eds.), Industrial Change and Regional Economic Transformation: The Experience of Western Eurgpe, London: Harper Collins Academic Baily, Martin Neil, Eric J. Bartelsman and John haltiwagner, 1996, Downsizing and Productivity Growth: Myth or Reality? In Mayes, David G. (ed.), Sources of Productivity Growth, Cambridge: Cambridge University Press. 176 Ballance, Robert, 1992, European Economic Restructuring: Retrospect and Prospect, In Cool, Karel, Damien J. Neven and Ingo Walter (eds.), European Economic Restructuring in the 19905, Washington Square: New York University Press. Bar-El, Raphael, 1985, Industrial Dispersion as an Instrument for the Achievement of Development Goals, Economic Geography, 61(3): 205-222. Barkley, David L., 1988, The Decentralization of High- Technology Manufacturing to Nonmetropolitan Areas, Growth and Change, 19(1): 13-30. ’ Barro, Robert J., and Xavier Sala-I-Martin, 1991, Convergence across States and Regions, In Brainard, William C., and George L. Perry (eds.), Brookings Papers on Economic Activity, Washington, D.C.: Brookings Institution. Baumol, William J., 1986, Productivity Growth, Convergence, and Welfare: What the Long-Run Data Show, The American Economic Review, 76(5): 1072-1085. Baumol, William J. and Kenneth Mclennan, 1985, U.S. Productivity Performance and Its Implications, In Baumol, William J. and Kenneth Mclennan, Productivity Growth and U.S. Competitiveness, New York: Oxford University Press. Baumol, William J., Sue Anne Batey Blackman, and Edward N. Wolff, 1989, Productivity and American Leadership: The Long View, Cambridge: The MIT Press. Beauregard, Rebert A., 1989, Space, Time, and Economic Restructuring, In Beauregard, Rebert A. (ed.), Economic Restructuring and Political Response, Newbury Park, CA: Sage Publications. Beeson, Patricia, 1987, Total Factor Productivity Growth and Agglomeration Economies in Manufacturing, Journal of Regional Science, 27(2): 183-199. Begg, Iain, 1991, High Technology Location and the Urban Areas of Great Britain: Development in the 19905, Urban Studies, 28(6): 961-981. 177 Benko, Georges and Mick Dunford, 1991, Structural Change and the Spatial Organization of the Productive System: An Introduction, In Benko, Georges and Mick Dunford (eds.), Industrial Change and Regional Development: The Transformation of New Industrial Spaces, London: Belhaven press. Blackley, Paul R., 1986, Urban-Rural Variations in the Structure of Manufacturing Production, Urban Studies, 23(6): 471—483. Blair, John P., and Robert Premus, 1987, Major Factors in Industrial Location: A Review, Economic Development Quarterly, 1(1): 72-85. Bradbury, J. H., 1985, Regional and Industrial Restructuring Processes in the New International Division of Labor, Progress in Human Geography, 5(1): 38-63. Braun, Denny, 1988, Multiple Measurements of U.S. Income Ineqaulity, The Review of Economics and Statistics, 70(3): 398-405. Braun, Denny, 1991, Income Inequality and Economic Development: Geographical Divergence, Social Science Quarterly, 72(3): 520-536. Brown, Lawrence A., Linda M. Lobao, and Anthony L. Verheyen, 1996, Continuity and Change in an Old Industrial Region, Growth and Change, 27(2): 175-205. Browne, Lynn E., Peter Mieszkowski, and Richard F. Syron, 1980, Regional Investment Patterns, New England Economic Review, July/August: 5-23. Bull, P. J., 1985, Intra-Urban Industrial Geography, In Pacione, Michael (ed.), Progress in Industrial Geography, London: Croom Helm. Camagni, Roberto, 1991, Spatial Implications of Technological Diffusion and Economic Restructuring in Europe - The Italian Case, EKISTICS, 58(350/351): 330- 335. Camagni, Roberto P., 1992, Development Scenarios and Policy Guidelines for the Lagging Regions in the 19905, Regional Studies, 26(4): 361-374. 178 Cameron, Cavin, and John Muellbauer, 1996, Knowledge, Increasing Returns and the UK Production Function, In Mayes, David G. (ed.), Sources of Productivity Growth, Cambridge: Cambridge University Press. Capello, Roberta, 1994, Towards New Industrial and Spatial Systems: The Role of New Technologies, Papers in Regional Science: The Journal of the Regional Science Association International, 73(2): 189-208. Caravaca, Inmaculada and Ricardo Mendez, 1994, Industrial Revitalization of the Metropolitan Areas in Spain, International Journal of Urban and Regional Research, 18(2): 220-233. Carlino, Gerald A., 1985, Declining City Productivity and the Growth of Rural Regions: A Test of Alternative Explanations, Journal of Urban Economics, 18(1): 11-27. Carlino, Gerald A. and Edwin S. Mills, 1987, The Determinants of County Growth, Journal of Regional Science, 27(1): 39-54. Carlton, Dennis W., 1983, The Location and Employment Choices of New Firms: An Econometric Model with Discrete and Continuous Endogenous Variables, The Review of Economics and Statistics, 45(3): 440-449. Casetti, Emilio, 1984, Manufacturing Productivity and Snowbelt-Sunbelt Shifts, Economic Geography, 60(4): 313-324. Casetti, Emilio and John Paul Jones III, 1987, Spatial Aspect of the Productivity Slowdown: An Analysis of U.S. Manufacturing Data, Annals of the Association of American Geographers, 77(1): 76-88. Castells, Manuel, 1988, The New Industrial Space: Information-Technology, Manufacturing and Spatial Structure in the United States, In Sternlieb, George, and James W. Hughes (eds.), America’s New Market Geography: Nation, Region and Metropolis, New Brunswick: Rutgers, The State University of New Jersey. Castells, Manuel, 1989, The Informational City: Information Technology, Economic Restructuring, and the Urban- Regional Process, Oxford: Basil Blackwell. 179 Champion, A. G., and A. R. Townsend, 1990, Contemporary Britain: A Geographical Perspective, London: Edward Arnold. Chatterji, Monojit, 1992, Convergence Clubs and Endogenous Growth, Oxford Review of Economic Policy, 8(4): 57-69. Cheshire, Paul, 1995, A New Phase of Urban Development in Western Europe? The Evidence for 19805, Urban Studies, 32(7): 1045-1063. Chinitz, Benjamin, 1986, The Regional Transformation of the American Economy, Urban Studies, 23(3): 377-385. Choi, Jeong Pyo, 1990, Factor Demand and Production Technology in Korean and Taiwanese Manufacturing, In Kwon, Jene K. (ed.), 1990, Korean Economic Development, Westport, CT: Greenwood Press. Choo, Sungjae, 1994, Production System Changes in the Korean Consumer Electronic Sector, Growth and Change, 25(2): 165-182. Christensen, Laurits R., and Dianne Cummings, 1981, Real Product, Real Factor Input, and Productivity in the Republic of Korea, 1960-1973, Journal of Development Economics, 8(3): 285-302. Clark, Gordon L., 1988, Corporate Restructuring in the Steel Industry: Adjustment Strategies and Local Labor Relations, In Sternlieb, George, and James W. Hughes (eds.), America’s New Market Geography: Nation, Region and Metropolis, New Brunswick: Rutgers, The State University of New Jersey. Clark, Gordon L., 1993, Costs and Prices, Corporate Competitive Strategies and Regions, Environment and Planning A, 25(1): 5-26. Clark, Gordon L., and Won Bae Kim, 1995, Asian NIEs and the Global Economy: Industrial Restructuring and Corporate Strategy in the 19905, Baltimore: The Johns Hopkins University Press. Coffey, William J. and James J. McRae, 1989, Service Industries in Regional Development, Halifax: The Institute for Research on Public Policy. 180 Corbridge, Stuart, 1989, Marxism, Post-Marxism, and the Geography of Development, In Peet, Richard and Nigel Thrift(ed.), New Models in Geography: The Political- Economy Perspective, London: Unwin Hyman Ltd. Cromley, Robert G., and Thomas R. Leinbach, 1981, The Pattern and Impact of the Filter Down Process in Nonmetropolitan Kentucky, Economic Geography, 57(3): 208-224. Davies, Wayne K. D. and Daniel P. Donoghue, 1993, Economic Diversification and Group Stability in an Urban System: The Case of Canada, 1951-86, Urban Studies, 30(7), 1165-1186. Denison, Edward F., 1984, Accounting for Slower Economic Growth: An Update, In Kendrick, John W. (ed.), International Comparisons of Productivity and Causes of the Slowdown, Cmabridge, MA: Ballinger Publishing Company. Dicken, Peter, 1992, Global Shift: The Internationalization of Economic Activity, New York: The Guilford Press. Dicken, Peter and Peter E. Lloyd, 1990, Location in Space: Theoretical Perspectives in Economic Geography, New York: HarperCollinsPulishers. Diniz, Clelio Campolina, 1994, Polygonized Development in Brazil: Neither Decentralization nor Continued Polarization, International Journal of Urban and Regional Research, 18(3): 293-314. Dollar, David, 1991, Convergence of South Korean Productivity on West German Levels, 1966-78, World Development, 19(2/3): 263-273. Dollar, David, and Kenneth Sokoloff, 1990, Patterns of Productivity Growth in South Korean Manufacturing Industries, 1963-1979, Journal of Development Economics, 33(2): 309-327. ' Dollar, David and Edward N. Wolff, 1993, Competitiveness, Convergence, and International Specialization, Cambridge: The MIT Press. 181 Drennan, Mathew P., Emanuel Tobier, and Jonathan Lewis, 1996, The Interruption of Income Convergence and Income Growth in Large Cities in the 19805, Urban Studies, 33(1): 63-82. Driver, Ciaran, and Paul Dunne(eds.), 1992, Structural Change in the UK Economy, Cambridge: Cambridge University Press. Dunford, Mick, 1993, Regional Disparities in the European Community: Evidence from the REGIO Databank, Regional Studies, 27(8): 727-743. Dunford, Michael and Diane Perrons, 1994, Regional Inequality, Regime of Accumulation and Economic Development in Contemporary, Transactions, Institute of British Geographers, 19(2): 163-182. Echeverri-Carroll, Elsie L., 1994, Flexible Linkage and Offshore Assembly Facilities in Developing Countries, International Regional Science Review, 17(1): 49-73. Edgington, David W., 1994, The Geography of Endaka: Industrial Transformation and Regional Employment Changes in Japan, 1986-1991, Regional Studies, 28(5): 521-535. Elmslie, Bruce and William Milberg, 1996, The Productivity Convergence Debate: A Theoretical and Methodological Reconsideration, Cambridge Journal of Economics, 20(2): 153-182. Erickson, Rodney A., 1976, The Filtering-Down Process: Industrial Location in a Nonmetropolitan Area, Professional Geographer, 28(3): 254-260. Erickson, Rodney A., 1994, Technology, Industrial Restructuring, and Regional Development, Growth and Change, 25(3): 353-379. Erickson, Rodney A., and Thomas R. Leinabch, 1979, Characteristics of Branch Plants Attracted to Nonmetropolitan Areas, In Losdale, Richard E., and H. L. Seyler, 1979, Nonmetropolitan Industrialization, Washington D. C.: V. H. Winston & Sons. Ernste, Huib, and Verena Meier, 1992, Regional Development and Contemporary Industrial Response: Extending Flexible Specialization, London: Belhaven Press. 182 Esser, Josef and Joachim Hirsch, 1989, The Crisis of Fordism and the Dimensions of a ‘Post-Fordist’ Regional and Urban Structure, International Journal of Urban and Regional Research, 13(3): 417-437. Ettlinger, Nancy, 1994, The Localization of Development in Comparative Perspective, Economic Geography, 70(2): 144-166. Fabricant, Solomon, 1983, Productivity Measurement and Analysis: An Overview, In Measuring Productivity: Trends and Comparisons from the First International Productivity Symposium, New York: NUIPUB. Fainstein, Susan S., and Norman I. Fainstein, 1989, Technology, the New International Division of Labor, and Location: Continuities and Disjunctures, In Beauregard, Rebert A. (ed.), Economic Restructuring and Political Response, Newbury Park, CA: Sage Publications. Fan, C. Cindy, 1994, The Temporal and Spatial Dynamics of Income and Population Growth in Ohio, 1950-1990, Regional Studies, 28(3): 241-258. Fan, C. Cindy, and Emilio Casetti, 1994, The Spatial and Temporal Dynamics of US Regional Income Inequality, The Annals of Regional Science, 28(2): 177-196. Fielding, A. J., 1994, Industrial Change and Regional Development in Western Europe, Urban Studies, 31(4/5): 679-704. Fingleton, Bernard, 1992, The Location of Employment in High-Technology Manufacturing in Great Britain, Urban Studies, 29(8): 1265-1276. Florida, Richard, 1996, Regional Creative Destruction: Production Organization, Globalization, and the Economic Transformation of the Midwest, Economic Geography, 72(3): 314-334. Fothergill, Steve, and Graham Gudgin, 1982, Unequal Growth: Urban and Regional Employment Change in the UK, London: Heinemann Educational Book. Fothergill, Steve, Michael Kitson, and Sarah Monk, 1987, In Lever, William F. (ed.), Industrial Change in the United Kingdom, Essex: Longman Scientific & Technical. 183 1993, The Shift from Fournier, Stephen F. and Sten Axelsson, Urban Studies, Manufacturing to Services in Sweden, 31(4/5): 679-704. Fuchs, Victor R., 1973, Statistical Explanations of the Relative Shift of Manufacturing among Regions of the United States, In Blunden, John, Christopher Brook, Geoffrey Edge, and Alan Hay (eds.), Regional Analysis and Development, London: Harper and Row. Fuguitt, Glenn V., and Calvin L. Beale, 1996, Recent Trends in Nonmetropolitan Migration: Toward a New Turnaround? Growth and Change, 27(2): 156-174. Kuniko and Richard Hill, 1995, Global Toyotaism and Fujita, International Journal of Urban and Local Development, Regional Research, 19(1): 7-22. Gaile, Gary L., 1977, Effiquity: A Comparison of A Measure of Efficiency with an Entropic Measure of the Equality of Discrete Spatial Distributions, Economic Geography, 53(3): 265-282. Gaile, G. L., 1980, The Spread-Backwash Concept, Regional Studies, 14(1): 15-25. Garofalo, Gasper A., and Devinder M. Malhotra, 1989, Intertemporal and Interspatial Productivity Differentials in U.S. Manufacturing, The Annals of Regional Science, 23(2): 121-136. Gaudemar, Jean-Paul and Remy Prud'Homme, 1991, Spatial Impacts of Deindustrialization in France, In Rodwin, Lloyd and Hidehiko Sazanami (eds.), Industrial Change and Regional Economic Transformation: The Experience of Western Europe, London: Harper Collins Academic. Gersbach, Hans and Martin N. Baily, 1996, Explanations of International Productivity Differences: Lessons from Manufacturing, In Wagner, Karin and Bart van Ark (eds.), International Productivity Differences: Measurement and Explanation, Amsterdam: ELSEVIER. Gerking, Shelby, 1994, Measuring Productivity Growth in U.S. Regions: A Survey, International Regional Science Review, 16(1/2): 155-185. 184 Gertler, Meric S, 1992, Flexibility Revisited: Districts, Nation-States, and The Forces of Production, Transactions, Institute of British Geographers, New Series 17(3): 259-278. Goddard, John B. and Alfred Thwaites, 1987, In Lever, William F. (ed.), Industrial Change in the United Kingdom, Essex: Longman Scientific & Technical. Goe, W. Richard and James L. Shanahan, 1991, Patterns of Economic Restructuring in Industrial-Based Metropolitan Areas, Urban Studies, 28(4): 559-576. Graham, Daniel and Nigel Spence, 1995, Contemporary Deindustrialization and Tertiarization in the London Economy, Urban Studies, 32(6): 885-911. Green, A. E., 1988, The North-South Divide in Great Britain: An Examination of the Evidence, Transactions, Institute of British Geographers, 13(2): 179-198. Green, Francis (ed.), 1989, The Restructuring of the UK Economy, London: Harvester Wheatsheaf. Hage, Jerald, 1979, A Theory of Nonmetropolitan Growth, In Summers, Gene F. and Arne Selvik (eds.), Nonmetropolitan Industrial Growth and Community Change, Lexington, MA: Lexington Books. Hakanson, Lars, and Lars Danielsson, 1985, Structural Adjustment in a Stagnating Economy: Regional Manufacturing Employment in Sweden, 1975-1980, Regional Studies, 19(4): 329-342. Hall, Peter, 1991, Structural Transformation in the Regions of the United Kingdom, In Rodwin, Lloyd and Hidehiko Sazanami (eds.), Industrial Change and Regional Economic Transformation: The Experience of Western Europe, London: Harper Collins Academic. Hammond, Robert and Patrick McCullagh, 1974, Quantitative Techniques in Geography: An Introduction, London: Oxford University Press. Hanink, Dean M., 1994, The International Economy: A Geographical Perspective, New York: John Wiley & Sons, Inc. 185 Hansen, Eric R., 1990, Agglomeration Economies and Industrial Decentralization: The Wage-Productivity Trade-Offs, Journal of Urban Economics, 28(2): 140-159. Hansen, Niles, 1988, Regional Consequences of Structural Changes in the National and International Division of Labor, International Regional Science Review, 11(2): 121-136. Hansen, Niles, 1995, Addressing Regional Disparity and Equity Objectives through Regional Policies: A Skeptical Perspective, Papers in Regional Science, 74(2): 89-104. ' Harrison, Bennett, 1992, Industrial Districts: Old Wine in the New Bottles? Regional Studies, 26(5): 469-483. Harrison, Bennett, and Barry Bluestone, 1988, The Great U- Turn: Corporate Restructuring and the Polarizing of America, New York: Basic Books. Harvey, David, 1982, The Limits to Capital, Oxford: Blackwell. Harvey, David, 1988, The Geographical and Geopolitical Consequences of the Transition from Fordist to Flexible Accumulation, In Sternlieb, George, and James W. Hughes (eds.), America’s New Market Geography: Nation, Region and Metropolis, New Brunswick: Rutgers, The State University of New Jersey. ' Haynes, Kingsley E. and Zachary B. Machunda, 1987, Spatial Restructuring of Manufacturing and Employment Growth in the Rural Midwest: an Analysis for Indiana, Economic Geography, 63(4): 319-333. Haynes, Kingsley E. and Mustafa Dinc, 1997, Productivity Change in Manufacturing Region: A Multifactor/Shift- Share Approach, Growth and Change, 28(2): 201-221. Head, Keith, John Ries, and Deborah Swenson, 1995, Agglomeration Benefits and Location Choice: Evidence from Japanese Manufacturing Investments in the United States, Journal of International Economics, 38(3/4): 223-247. Healey, Michael J. and Brian W. Ilbery, 1990, Location and Change: Perspectives on Economic Geography, New York: Oxford University Press. 186 Henry, Nick, 1992, The New Industrial Spaces: Locational Logic of A New Production Era? International Journal of Urban and Regional Research, 16(3): 375-396. Hicks, Donald A., 1985, Advanced Industrial Development: Restructuring, Relocation, and Renewal, Boston: Oelgeschlager, Gun &;Hain. Hicks, Donald A., 1986, Industrial Renewal through Technology Upgrading in the U.S. Metalworking Industry, In Rees, John (ed.), Technology, Regions, and Policy, Totowa, NJ: Rowman and Littlefield. Hicks, Donald A., 1987, Geo-Industrial Shifts in Advanced Metropolitan Economics, Urban Studies, 24(6): 460-479. Hill, Richard Child and Cynthia Negrey, 1987, Deindustrialization in the Great Lakes, Urban Affairs Quarterly, 22(4): 580-597. Hilpert, Ulrich, 1991, Regional Policy in the Process of Industrial Modernization: The Decentralization of Innovation by the Regionalization of High Tech? In Hilpert, Ulrich (ed.), Regional Innovation and Decentralization: High Tech Industry and Government Policy, London: Routledge. Hirst, Paul, and Jonathan Zeitlin (eds.), 1989, Reversing Industrial Decline? Industrial Structure and Policy in Britain and Her Competitors, Oxford: BERG. Hommel, Hanfred, 1995, Innovation and Restructuring in Old Industrialized Regions in Europe: A Comparative Perspective, In Fluchter, Winfried (ed.), Japan and Central Europe Restructuring: Geographical Aspects of Socio-Economic Urban and Regional Development, Wiesbaden: Harrassoaitz Verlag. Hudson, Ray, 1988, Uneven Development in Capitalist Societies: Changing Spatial Division of Labor, Forms of Spatial Organization of Production and Service Provision, and Their Impacts on Localities, Transactions, Institute of British Geographers, 13(4): 484-496. Hudson, Ray, 1994, New Production Concepts, New Production Geographies? Reflections on Changes in the Automobile Industry, Transactions, Institute of British Geographers, 19(3): 331-345. 187 Hulten, Charles R., and Robert Schwab, 1984, Regional Productivity Growth in U.S. Manufacturing: 1951-78, The American Economic Review, 74(1): 152-162. Humphrys, Graham, 1995, Japanese Industry at Home, Geography, 80(1): 15-22. Jefferson, Gary H. and Wenyi Xu, 1994, Assessing Gains in Efficient Production among China’s Industrial Enterprises, Economic Development and Cultural Change, 42(3): 597-615. Jensen-Butler, Chris, 1992, Rural Industrialization in Denmark and the Role of Public Policy, Urban Studies, 29(6): 881-904. Johnson, Merrill L., 1989, Industrial Transition and the Location of High-Technology Branch Plants in the Nonmetropolitan Southeast, Economic Geography, 65(1): 33-47. Jorgensen, Dale W., 1995, Productivity and Postwar U.S. Economic Growth, In Jorgensen, Dale W., Productivity, Volume 1: Postwar U.S. Economic Growth, Cambridge: The MIT Press. Kale, Steven R., and Richard E. Lonsdale, 1979, Factors Encouraging and Discouraging Plant Location in Nonmetropolitan Areas, In Losdale, Richard E., and H. L. Seyler, 1979, Nonmetropolitan Industrialization, Washington D. C.: V. H. Winston & Sons. Kasarda, John 0., 1988, People and Jobs on the Move: America’s New Spatial Dynamics, In Sternlieb, George, and James W. Hughes (eds.), America’s New Market Geography: Nation, Region and Metropolis, New Brunswick: Rutgers, The State University of New Jersey. Karaska, Gerald J. and David F. Bramhall, 1969, Locational Analysis for Manufacturing: A Selection of Readings, Cambridge: The MIT Press. Ke, Shanzi and Edward M. Bergman, 1995, Regional and Technological Determinants of Company Productivity Growth in the Late 19805, Regional Studies, 29(1): 59- 71. 188 Keeble, David, 1976, Industrial Location and Planning in the United Kingdom, London: Methuen & Co Ltd. Keeble, David, Peter L. Owens, and Chris Thompson, 1983, The Urban-Rural Manufacturing Shift in the Europen Community, Urban Studies, 20(4): 405-418. Keeble, David, 1987, In Lever, William F. (ed.), Industrial Change in the United Kingdom, Essex: Longman Scientific & Technical. Kendrick, John W., 1961, Productivity Trends in the United States, Princeton: Princeton University Press. Kim, Kwang-Doo, 1996, Shifting Strategies: From Cost- Advantage to Superior Value, In Branscomb, Lewis M., and Young-Hwan Choi (eds.), Korea at the Turning Point: Innovation-Based Strategies for Development, Westport: Praeger. Kim, Kyung-Hwan and Edwin S. Mills, 1990, Urbanization and Regional Development in Korea, In Kwon, Jene K. (ed.), 1990, Korean Economic Development, Westport, CT: Greenwood Press. Kim, Won Bae, 1993, Industrial Restructuring and Regional Adjustment in Asian NIEs, Environment and Planning A, 25(1): 27-46. Kim, Won Bae, 1995, Patterns of Industrial Restructuring, in Clark, Gordon. L. and Won Bae Kim (eds.), Asian NIEs and the Global Economy: Industrial Restructuring and Corporate Strategy in the 19905, Baltimore: The Johns Hopkins University Press. Kim, Yong_Woong, 1995, Spatial Changes and Regional Development. In Lee, Gun Young and Hyun Sik Kim (eds.), Cities and Nation: Planning Issues and Policies of Korea, Anyang, Korea: Korea Research Institute for Human Settlemtnts. Kossy, Judith A., 1996, Economic Restructuring and the Restructuring of Economic Development Practice: A New York Perspective, 1985-1995, Economic Development Quarterly, 10(4): 300-314. Kunzmann, Klaus R. and Michael Wegener, 1991, The Pattern of Urbanization in Western Europe, EKISTICS, 58(350/351): 282-291. 189 Kuznets, Simon, 1955, Economic Growth and Income Inequality, The American Economic Review, 45(1): 1-28. Kwon, Jene K., 1986, Capital Utilization, Economies of Scale and Technical Change in the Growth of Total Factor Productivity: An Explanation of South Korean Manufacturing Growth, Journal of Development Economics, 24(1): 75-89. Kwon, Jene K. (ed.), 1990, Korean Economic Development, Westport, CT: Greenwood Press. Kwon, Jene, 1994, The East Asia Challenge to Neoclassical Orthodoxy, World Development, 22(4): 635-644. Kwon, Jene K., and Martin Williams, 1982, The Structure of Production in South Korea’s Manufacturing Sector, Journal of Development Economics, 11(2): 215-226. Kwon, Jene K., and Kyhyang Yuhn, 1990, Analysis of Factor Substitution and Productivity Growth in Korean Manufacturing, 1961-1981, In Kwon, Jene K. (ed.), 1990, Korean Economic Development, Westport, CT: Greenwood Press. Kwon, Won-Yong, 1981, A Study of the Economic Impact of Industrial Relocation: The Case of Seoul, Urban Studies, 18(1): 73-90. Lansbury, Melanie, and David Mayes, 1996, Productivity Growth in the 19805, In Mayes, David G. (ed.), Sources of Productivity Growth, Cambridge: Cambridge University Press. Lee, Gun Young and Hyun Sik Kim (eds.), 1995, Cities and Nation: Planning Issues and Policies of Korea, Anyang, Korea: Korea Research Institute for Human Settlemtnts. Lee, Hee-Yeon, 1989, Growth Determinants in the Core- Periphery of Korea, International Regional Science Review, 12(2): 147-163. Lee,Hyung-Koo, 1996, The Korean Economy: Perspectives for the Twenty-First Century, Albany: State University of New York Press. Lee, Kyu Sik, 1985, Decentralization Trends of Employment Location and Spatial Policies in LDC Cities, Urban Studies, 22(2): 151-162. 190 Lee, Kyu Sik and Sang-Chuel Choe, 1990, Changing Location Patterns of Industries and Urban Decentralization Policies in Korea, In Kwon, Jene K. (ed.), 1990, Korean Economic Development, Westport, CT: Greenwood Press. Leven, Charles L., 1988, Post-Industrialism, Regional Change and the New Urban Geography, In Sternlieb, George, and James W. Hughes (eds.), America’s New Market Geography: Nation, Region and Metropolis, New Brunswick: Rutgers, The State University of New Jersey. Lever, W. F., 1985, Theory and Methodology in Industrial Geography, In Pacione, Michael (ed.), Progress in Industrial Geography, London: Croom Helm. Lever, William F., 1987, In Lever, William F. (ed.), Industrial Change in the United Kingdom, Essex: Longman Scientific & Technical. Lim, David, 1994, Explaining the Growth Performance of Asian Developing Economies, Economic Development and Cultural Change, 42(4): 829-844. Lim, J. D., 1994, Restructuring of the Footwear Industry and the Industrial Adjustment of the Pusan Economy, Environment and Planning A, 26(4): 567-581. Lipietz, Alain, 1992, The Regulation Approach and Capitalist Crisis: An Alternative Compromise for the 19905, In Dunford, Mick and Grigoris Kafkalas, Cities and Regions in the New Europe: The Global-Local Interplay and Spatial Development Strategies, London: Belhaven Press. Lo, Fu-Chen, and Kamal Salih, 1981, Growth Poles, Agropolitan Development, and Polarization Reversal: The Debate and Search for Alternatives, In Stohr, W. B., and D. R. Fraser Taylor (eds.), Development from Above or Below? New York: John Wiley & Sons Ltd. Logan, John R. and Todd Swanstrom, 1990, Urban Restructuring: A Critical Review, In Logan, John R. and Todd Swanstrom(eds.), Beyond the City Limits: Urban Policy and Economic Restructuring in Comparative Perspective, Philadelphia: Temple University Press. Losdale, Richard E., and H. L. Seyler, 1979, Nonmetropolitan Industrialization, Washington D. C.: V. H. Winston & Sons. 191 Lovering, John, 1989, The Restructuring Debate, In Peet, Richard and Nigel Thrift (ed.), New Models in Geography: The Political-Economy Perspective (Volume one), London: Unwin Hyman Ltd. Lovering, John, 1990, Fordism's Unknown Successor: A Comment on Scott's Theory of Flexible Accumulation and the Re- emergence of Regional Economies, International Journal of Urban and Regional Research, 14(1): 159-174. Lovering, John, 1991, Southbound Again: The Peripheralization of Britain, In Day, Graham and Gareth Ress (eds.), Regions, Nations and European Integration: Remaking the Celtic Periphery, Cardiff: University of Wales Press. Mair, Andrew, 1993, New Growth Poles? Just-In-Time Manufacturing and Local Economic Development Strategy, Regional Studies, 27(3): 207-221. Magatti, Mauro, 1993, The Market and Social Forces: A Comparative Analysis of Industrial Change, International Journal of Urban and Regional Research, 17(2): 213-231. Malecki, Edward J., 1991, Technology and Economic Development: the Dynamics of Local, Regional and National Change, Essex: Longman Scientific & Technical. Malecki, Edward J. and F. Todtling, 1995, The New Flexible Economy: Shaping Regional and Local Institutions for Global Competition, In Bertuglia, Cristoforo S., Fischer, Manfred M. and Giorgio Preto (eds.), Technological Change, Economic Development and Space, Berlin: Springer. Malmberg, Anders, 1996, Industrial Geography: Agglomeration and Local Milieu, Progress in Human Geography, 20(3): 392-403. Markusen, Ann, and Sam Ock Park, 1993, The State as Industrial Locator and District Builder: The Case of Changwon, South Korea, Economic Geography, 69(2): 157- 181. Martin, Ron, 1988, The Political Economy of Britain’s North- South Divide, Transactions, Institute of British Geographers, 13(4): 389-418. 192 Martin, Ron, 1989(a), The Reorganization of Regional Theory: Alternative Perspectives on The Changing Capitalist Space Economy, Geoforum, 29(2): 187-201. Martin, Ron, 1989(b), Regional Imbalance as Consequence and Constraint in National Economic Renewal, In Green, Francis (ed.), The Restructuring of the UK Economy, London: Harvester Wheatsheaf. Martin, Ron and Peter Townroe, 1992, Changing Trends and Pressures in Regional Development, In Martin, Ron and Peter Townroe(eds.), Regional Development in the !9905: The British Isles in Transition, London: Jessica Kingsley Publishers Ltd. Martin, Ron, and Peter Sunley, 1996, Paul Krugman’s Geographical Economics and Its Implications for Regional Development Theory: A Critical Assessment, Economic Geography, 72(3): 259-292. Martin, S. A., Richard Mchugh, and S. R. Johnson, 1993, The Influence of Location on Productivity: Manufacturing Technology in Rural and Urban Areas, Growth and Change, 24(4): 459-486. Mas, Matilde, Joaquin Maudos, Fransisco Perez, and Ezequiel Uriel, 1996, Infrastructure and Productivity in the Spanish Regions, Regional Studies, 30(7): 641-649. Massey, Doreen, 1995, Spatial Division of Labor: Social Structure and the Geography of Production, New York: Routledge. Massey, Doreen B., and Richard A. Meegan, 1978, Industrial Restructuring versus the Cities, Urban Studies, 15(3): 273-288. Maxwell, Philip, 1994, Trends in Regional Income Disparities: An Australian Perspective on the Canadian Experience, Canadian Journal of Regional Science, 17(2): 189-215. Mayes, David G., 1996, Introduction, In Mayes, David G. (ed.), Sources of Productivitngrowth, Cambridge: Cambridge University Press. McArthur, R., 1990, Replacing the Concept of High Technology: Towards a Diffusion-Based Approach, Environment and Planning A, 22(6): 811-828. 193 Mcquaid, Ronald W., Scott Leitham, and John D. Nelson, 1996, Accessibility and Location Decisions in a Peripheral Region of Europe: A Logit Analysis, Regional Studies, 30(6): 579-588. Mehretu, Assefa, and Lawrence M. Sommers, 1994, Patterns of Macrogeographic and Microgeogaphic Marginality in Michigan, The Great Lakes Geographer, 1(2): 67-80. Meyer, David R. and Kyonghee Min, 1987, City Employment Change in the Republic of Korea, 1960-1970, Urban Affairs Quarterly, 22(4): 598-616. Molle, Willem, and Sjaak Boeckhout, 1995, Economic Disparity Under Conditions of Integration - A Long Term View of the European Case, Papers in Regional Science, 74(2): 105-123. Moomaw, Ronald L., 1981, Productive Efficiency and Region, Southern Economic Journal, 48(2): 344-357. Moomaw, Ronald L., 1983, Spatial Productivity Variations in Manufacturing: A Critical Survey of Cross-Sectional Analyses, International Regional Science Review, 8(1): 1-22. Moomaw, Ronald L., 1985, Firm Location and City Size: Reduced Productivity Advantages as a Factor in the Decline of Manufacturing in Urban Areas, Journal of Urban Economics, 17(1): 73-89. Moomaw, Ronald L., and Martin Williams , 1991, Total Factor Productivity Growth in Manufacturing: Further Evidence from the States, Journal of Regional Science, 31(1): 17-34. Morales, Rebecca, 1994, Flexible Production: Restructuring of the International Automobile Industry, Cambridge: Polity Press. Morgan, James, 1962, The Anatomy of Income Distribution, The Review of Economics and Statistics, 44(3): 270-283. Morgan, Kevin, and Andrew Sayer, 1988, Macrocircuits of Capital: Sunrise Industry and Uneven Development, Boulder: Westview Press. 194 Moriarty, Barry M., 1986, Productivity, Industrial Restructuring, and the Deglomeration of American Manufacturing, In Rees, John (ed.), Technolggy, Regions, and Policy, Totowa, NJ: Rowman and Littlefield. Moriarty, Barry M., 1991, Urban System, Industrial Restructuring, and the Spatial-Temporal Diffusion of Manufacturing Employment, Environment and Planning_A, 23(11): 1571-1588. Moriarty, B. M., and L. R. Moriarty, 1989, Capital Restructuring, Government Policy and the Decentralization of US Manufacturing, In Gibbs, David (ed.), Government Policy and Industrial Change, London: Routledge. Morrill, Richard L., 1992, Population Redistribution within Metropolitan Regions in the 19805: Core, Satellite, and Exurban Growth, Growth and Change, 23(3): 277-302. Morris, Arthur S. and Stella Lowder, 1992, Flexible Specialization: the Application of Theory in A Poor- Country: Leon, Mexico, International Journal of Urban and Regional Research, 16(2): 190-201. Moses, Leon, 1967, The Location of Economic Activity in Cities, The American Economic Review, 57(2): 211-222. Moulaert, Frank and Erik Swyngedouw, 1991,-Regional Development and the Geography of the Flexible production: Theoretical Arguments and Empirical Evidence, In Hilpert, Ulrich (ed.), Regional Innovation and Decentralization: High Tech Industry and Government Policy, London: Routledge. Nam, Sunghee, 1990, Recent Urban Decentralization in South Korea: Implications for Regional Disparity, In Lim, Gill-Chin and Gi-Beom Lee (eds.), Dynamic Transformation: Korea, NICs and Beyond, Urbana: Consortium on Development Studies. National Research Council, 1979, Measurement and Interpretation of Productivity, Washington D.C.: National Academy of Science. National Statistical Office of Republic of Korea, 1993, Major Statistics of Korean Economy, Seoul: Munsung Publiching Co. 195 National Statistical Office of Republic of Korea, Report on Mining and Manufacturing Survey (Several Years), Seoul: Moonsung Publishing Co. Nelson, Richard R., 1981, Research on Productivity Growth and Productivity Differences: Dead Ends and New Departures, Journal of Economic Literature, 19(3): 1929-1064. Nicholson, Norman, 1978, Differences in Industrial Production Efficiency between Urban and Rural Markets, Urban Studies, 15(1): 91-95. Nishimizu, Meiko, and Sherman Robinson, 1984, Trade Policies and Productivity Change in Semi-Industrialized Countries, Journal of Development Economics, 16(1/2): 177-206. Nissan, Edward and George Carter, 1993, Income Inequality Across Regions Over Time, Growth and Change, 24(3): 303-319. Norsworthy, J. R. and S. L. Jang, 1992, Empirical Measurement and Analysis of Productivity and Technological Change: Applications in High-Technology and Service Industries, Amsterdam: North-Holland. North, Douglas C., 1973, Location Theory and Regional Economic Growth, In Blunden, John, Christopher Brook, Geoffrey Edge, and Alan Hay (eds.), Regional Analysis and Development, London: Harper and Row. Norton, R. D., 1992, Agglomeration and Competitiveness: From Marshall to Chiniz, Urban Studies, 29(2): 155-170. Norton, R. D., and J. Rees, 1979, The Product Cycle and the Spatial Decentralization of American Manufacturing, Regional Studies, 13(2): 141-151. Noyelle, Thierry J., 1983, The Implication of Industry Restructuring for Spatial Organization in the United States, In Moulaert, Frank and Patricia Wilson Salinas (eds.), Regional Analysis and the New International Division of Labor: Application of a Political Economy Approach, Boston: Kluwer Nijhoff Publishing. Oberhauser, Ann, M., 1990, Social and Spatial Patterns under Fordism and Flexible Accumulation, Antipode, 22(3): 211-232. 196 Oh, D. S. and I. Masser, 1995, High-tech Centers and Regional Innovation: Some Case Studies in the UK, Germany, Japan and Korea, In Bertuglia, Cristoforo S., Fischer, Manfred M. and Giorgio Preto (eds.), Technological Change, Economic Development and Space, Berlin: Springer. Pacione, Michael (ed.), 1985, Progress in Industrial Geography, London: Croom Helm. Page, John M., 1994, The East Asian Miracle: An Introduction, World Development, 22(4): 615-625. Park, S. 0., 1991, High-Technology Industries in Korea: Spatial Linkages and Policy Implications, Geoforum, 22(4): 421-431. Park, S. O., 1993, Industrial Restructuring and the Spatial Division of Labor: the Case of the Seoul Metropolitan Region, the Republic of Korea, Environment and Planning 5, 25(1): 81-93. Park, S. O., 1994, Industrial Restructuring in the Seoul Metropolitan Region: Major Trigger and Consequences, Environment and Planning A, 26(4): 527-541. Park, Sam Ock, 1995, Seoul, Korea: City and Suburbs, in Clark, Gordon. L. and Won Bae Kim (eds.), Asian NIEs and the Global Economy: Industrial Restructuring and Corporate Strategy in the 19905, Baltimore: The Johns Hopkins University Press. Park, Sam Ock, 1996, Networks and Embededness in the Dynamic Types of New Industrial Districts, Progress in Human Geography, 20(3): 476-493. Park, Sam-Ock and Won-Bae Kim, 1995, Industrial Restructuring and the Role of the Asian NIES in the Pacific Rim Area, In Lee, Gun Young and Hyun Sik Kim (eds.), Cities and Nation: Planning Issues and Policies of Korea, Anyang, Korea: Korea Research Institute for Human Settlements. Park, Yangho, 1986, Manufacturing Decentralization and Regional Productivity Change: The Case of Korea, Unpublished Ph.D. Dissertation, Berkeley: University of California at Berkeley. 197 Pattie, Charles I., and R. J. Johnston, 1990, One Nation or Two? The Changing Geography of Unemployment in Great Britain, 1983-1988, Professional Geography, 42(3): 288- 298. Peck, Jamie, 1992, Labor and Agglomeration: Control and Flexibility in Local Labor Market, Economic Geography, 68(4): 325-347. Phelps, Nicholas A., 1992, External Economies, Agglomeration and Flexible Accumulation, Transactions, Institute of British Geographers, 17(1): 35-46. Pilat, Dirk, 1995, Comparative Productivity of Korean Manufacturing, 1967-1987, Journal of Development Economics, 46(1): 123-144. Pinch, S, Mason, C, and S. Watt, 1991, Flexible Employment Strategies in British Industry: Evidence from the UK 'Sunbelt', Regional Studies, 25(3): 207-218. Pollard, Jane, and Michael Storper, 1996, A Tale of Twelve Cities: Metropolitan Employment Change in Dynamic Industries in the 19805, Economic Geography, 72(1): 1- 22. Pugel Thomas A., 1992, A Comparative Analysis of Industrial Restructuring in Europe, the US and Japan, In Cool, Karel, Damien J. Neven and Ingo Walter (eds.), European Economic Restructuring in the 19905, Washington Square: New York University Press. Pugh, Cedric, 1995, International Structural Adjustment and its Sectoral and Spatial Impacts, Urban Studies, 32(2): 261-285. Rees, John, 1979, Technological Change and Regional Shifts in American Manufacturing, Professional Geographer, 31(1): 45-54. Richardson, Harry W., 1980, Polarization Reversal in Developing Countries, Regional Science Association Papers, 45: 67-85. Rigby, David L., 1995, Investment, Capital Stocks and the Age of Capital in U.S. Regions, Growth and Change, 26(4): 524-552. 198 Rodriguez-Pose, Andres, 1994, Socioeconomic Restructuring and Regional Change: Rethinking Growth in the European Community, Economic Geography, 70(4): 325-343. Rogerson, Christian M., 1994, Flexible Production in the Developing World: the Case of South Africa, Geoforum, 25(1): 1-17. Rodwin, Lloyd, 1989, Deindustrialization and Regional Economic Transformation, In Rodwin, Lloyd and Hidehiko Sazanami(eds.), Deindustrialization and Regional Economic Transformation: The Experience of the United States, Winchester: Unwin Hyman, Inc. Sadler, David, 1992, The Global Region: Production, State Policies and Uneven Development, Oxford: Pergamon Press. Sayer, Andrew, 1989, Postfordism in Question, International Journal of Urban and Regional Research, 13(4): 666-695. Schoenberger, Erica, 1989, New Models of Regional Change, In Peet, Richard and Nigel Thrift (ed.), New Models in Geography: The Political-Economy Perspective (Volume one), London: Unwin Hyman Ltd. V Scott, Allen J., 1982, Locational Patterns and Dynamics of Industrial Activity in the Modern Metropolis, Urban Studies, 19(2): 111-142. Scott, Allen J., 1988a, New Industrial Spaces: Flexible Production Organization and Regional Development in North America and Western Europe, London: Pion. Scott, Allen J., 1988b, Flexible Production Systems and Regional Development: The Rise of New Industrial Spaces in North America and Western Europe, International Journal of Urban and Regional Research, 12(2): 171-185. Scott, Allen J., 1992, The Role of Large Producers in Industrial Districts: A Case Study of High Technology Systems Houses in Southern California, Regional Studies, 26(3): 265-275. Scott, Allen J., 1993a, The Collective Order of Flexible Production Agglomeration: Lessons for Local Economic Development Policy and Strategic Choice, Economic Geography, 68(3): 219-233. 199 Scott, Allen J., 1993b, Technopolis: High-Technology Industry and Regional Development in Southern California, Berkeley: University of California Press. Scott, Allen J., and Michael Storper(eds.), 1986, Production, Work, Territory: The Geographical Anatomy of Industrial Capitalism, London: Allen & Unwin. Scott, Allen J., and Michael Storper(eds.), 1992, Pathways to Industrialization and Regional Development, New York: Routledge. Scott, Allen J. and Michael Storper, 1992, Regional Development Reconsidered, In Ernste, Huib and Verena Meier (eds.), Regional Development and Contemporary Industrial Response: Extending Flexible Specialization, London: Belhaven Press. Selya, Roger Mark, 1993, Economic Restructuring and Spatial Changes in Manufacturing in Taiwan, 1971-1986, Geoforum, 24(2): 115-126. Seyler, H. L., 1979, Contemporary Research Emphases in the United States, In Summers, Gene F. and Arne Selvik (eds.), Nonmetropolitan Industrial Growth and Community Change, Lexington, MA: Lexington Books. Smith, David M., 1971, Industrial Location: An Economic Geographical Analysis, New York: John Wiley & Sons, Inc. Smith, Neil, 1989, Uneven Development and Locational Theory: Towards A Synthesis, In Peet, Richard and Nigel Thrift (ed.), New Models in Geography: The Political-Economy Perspective (Volume one), London: Unwin Hyman Ltd. Soja, Edward, Morales, Rebecca, and Goetz Wolff, 1983, Urban Restructuring: An Analysis of Social and Spatial Change in Los Angels, Economic Geogrephy, 59(2): 195-230. Solow, Robert M., 1957, Technical Change and the Aggregate Production Function, The Review of Economics and Statistics, 39: 312-320. Soroka, Lewis, 1994, Manufacturing Productivity and City Size in Canada, 1975 and 1985: Does Population Matter? Urban Studies, 31(6): 895-911. 200 Spooner, Derek, 1995, Regional Development in the UK: Part I, Geography, 80(1): 72-80. Sternberg, Rolf, 1996, Regional Growth Theories and High- Tech Regions, International Journal of Urban and Regional Research, 20(3): 518-538. Sternlieb, George, and James W. Hughes, 1975, Post- Industrial America: Metropolitan Decline & Inter- Regional Job Shifts, New Brunswick: Rutgers University. Storper, Michael, 1984, Who Benefits from Industrial Decentralization? Social Power in the Labor Market, Income Distribution and Spatial Policy in Brazil, Regional Studies, 18(2): 143-164. Storper, Michael, 1990, Industrialization and regional Question in the Third World: Lessons of Postimperialism; Prospects of Post-fordism, International Journal of Urban and Regional Research, 14(3): 423-444. Storper, Michael, 1991, Industrialization, Economic Development and the Regional Question in the Third World: From Import Substitution to Flexible Production, London: Pion. Storper, Michael, 1993, Regional 'Worlds' of Production: Learning and Innovation in the Technology Districts of France, Italy, and the USA, Regional Studies, 27(5): 433-455. ' Suarez-Villa, Luis, 1989, Policentric Restructuring, Metropolitan Evolution, and the Decentralization of Manufacturing, T.E.S.G., 80(4): 194-205. Suarez-Villa, Luis, and Juan R. Cuadrado Roura, 1993, Regional Economic Integration and the Evolution of Disparities, Papers in Regional Science: The Journal of the Regional Science Association International, 72(4): 369-387. Suer, Banu, 1995, Total Factor Productivity Growth and Characteristics of the Production Technology in the UK Chemicals and Allied Industries, Applied Economics, 27(3): 277-285. 201 Summers, Anita A., Paul C. Cheshire, and Lanfranco Senn (eds.), 1993, Urban Change in the United States and Western Europe: Comparative Analysis and Policy, Washington D.C.: The Urban Institute Press. Summers, Gene F. and Arne Selvik, 1979, Nonmetropolitan Industrial Growth and Community Change, Lexington, MA: Lexington Books. Taylor, Jim, 1993, An Analysis of the Factors Determining the Geographical Distribution of Japanese Manufacturing Investment in the UK, 1984-91, Urban Studies, 30(7): 1209-1224. Thomas, Morgan D., 1975, Growth Pole Theory, Technological Change, and Regional Economic Growth, Papers of the Regional Science Association, 134: 3-25. Tickell, Adam and Jamie A. Peck, 1992, Accumulation, Regulation and the Geographies of Post-Fordism: Missing Links in Regulationist Research, Progress in Human Geography, 16(2): 190-218. Todd, Daniel and Yi-Chung Hsueh, 1988, Taiwan: Some Spatial Implications of Rapid Economic Growth, Geoforum, 19(2): 133-145. Tomkins, J. and J. Twomey, 1990, The Changing Spatial Structure of Manufacturing Plant in Great Britain, 1976 to 1987, Environment and Planning A, 22(3): 385-398. Townroe, Peter M., and David Keen, 1984, Polarization Reversal in the State of Sao Paulo, Brazil, Regional Studies, 18(1): 45-54. Townsend, Alan R., 1993, Uneven Regional Change in Britain, Cambridge: Cambridge University Press. Tsao, Yuan, 1985, Growth without Productivity: Singapore Manufacturing in the 19705, Journal of Development Economics, 19(1/2): 25-38. Tulpule, A. H., 1969, Dispersion of Industrial Employment in the Greater London Area, Regional Studies, 3(1): 25-40. Vazquez-Barquero, A., 1990, Conceptualizing Regional Dynamics in Recently Industrialized Countries, Environment and Planning A, 22(4): 477-491. 202 Vyver, Frank T. De, 1969, Labor Factors in the Industrial Development of the South, In Karaska, Gerald J. and David F. Bramhall (eds.), Locational Analysis for Manufacturing: A Selection of Readings, Cambridge: The MIT Press. Wagner, Karin and Bart van Ark (eds.), 1996, International Productivity Differences: Measurement and Explanation, Amsterdam: ELSEVIER. Warf, Barney, 1995, Telecommunications and the Changing Geographies of Knowledge Transmission in the Late 20th Century, Urban Studies, 32(2): 361-378. Watts, H. D., 1987, Industrial Geography, Essex: Longman Scientific & Technical. Weber, Michael, 1995, Changing Places in East Asia, In Clark, Gordon L. and Won Bae Kim (eds.), Asian NIEs and the Global Economy: Industrial Restructuring and Corporate Strategy in the 19905, Baltimore: The Johns Hopkins University Press. Williams, Colin C. and Jan Windebank, 1995, Social Polarization of Households in Contemporary Britain: A ‘Whole Economy' Perspective, Regional Studies, 29(8): 723-728. Williams, Martin and Ronald L. Moomaw, 1989, Capital and Labor Efficiencies: A Regional Analysis, Urban Studies, 26(6): 573-585. Williamson, Jeffrey G., 1965, Regional Inequality and the Process of National Development, Economic Development and Cultural Change, 13(4): 3-84. Wojan, Timothy R., and Glen C. Pulver, 1995, Location Patterns of High Growth Industries in Rural Counties, Growth and Change, 26(1): 3-22. Wolff, Edward N., 1991, Capital Formation and Productivity Convergence, The American Economic Review, 81(3): 565- 579. Woodward, Rachel, 1995, Approaches toward the Study of Social Polarization in the UK, Progress in Human Geography, 19(1): 75-89 203 World Bank, 1991, World Development Report, 1991, New York: Oxford University Press. World Bank, 1993, The East Asian Miracle: Economic Growth and Public Policy, New York: Oxford University Press. MICHIGAN STATE UNIV. LIBRARIES (MIMI) WI“) “l (“N W l) 1|) (”I (1) l“)! (W WI 31293016838959