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\
LIBRARY (ET

Mn higan State
University

k

 
 
 
  

THES'S

 

This is to certify that the

thesis entitled
A SIMULATION MODEL OF THE

PHYSICIAN SERVICES MARKET

presented by

Karen Windau Tyson

has been accepted towards fulfillment
of the requirements for

Ph. D . Economics

degree in

 

 

Major professor

Date May 6, 1980

0-7639

 

 

OVERDUE FINES:
25¢ per day per item
RETURNING LIBRARY MATERIALS:

Place in book return to remove
charge fron circulation records

 

 

 

,ii‘l“!

A SIMULATION MODEL OF THE
PHYSICIAN SERVICES MARKET

By

Karen Nindau Tyson

A DISSERTATION

Submitted to
Michigan State University
in partial fulfillment of the requirements

for the degree of

DOCTOR OF PHILOSOPHY

Department of Economics

1980

'/J 1’

ABSTRACT
A SIMULATION MODEL OF THE PHYSICIAN SERVICES MARKET
By

Karen Windau Tyson

The model developed in this study links the market fOr physician
services to the supply of trained physicians in the United States. The
price of physician services is determined by a combination of supply
and demand forces, including the physician-population ratio, the coin-
surance rate, prices of related products, family income, and technology.
Physician income is related to physician prices, population, family in-
come, and the number of physicians. The change in number of doctors
is related to lagged values of physician income, family income, and
population.

High rates of return to investment in medical education have
been cited as evidence that entry into the medical profession has been
limited in order to allow physicians to exercise market power. This
study tests the limited entry hypothesis by comparing equilibrium in-
come and equilibrium number of physicians from the empirical model with
estimates from a competitive optimum. Results of the test Show that the
stock of physicians over the period 1960-1977 has been lower than the
stock of physicians consistent with a competitive, free-entry optimum.
Incomes of physicians were considerably higher than optimal levels.
There are two possible reasons for this observed shortage of physicians--

a lag in the adjustment of prices to equilibrium or barriers to entry

into the profession. In this case, observed prices and equilibrium

 

prices are roughly equal. Therefbre, the evidence suggests that the
observed differences in physician income and number of physicians are
due to barriers to entry.

The model can be used to forecast future numbers of physicians,
physician earnings, and physician prices. Such forecasts are sensitive
to the assumptions made about future patterns of the exogenous variables,
so three alternative scenarios were simulated. -The forecasts imply
slower rates of growth in future physician stock than government-
sponsored forecasts using non-economic methods. The model used here
has the advantage that income, number of physicians, and prices are fore-
cast in a unified way, and the response of potential U.S. physicians to
income incentives is included.

The simulation model can also be used to determine the future
pattern of physicians, prices, and incomes if the medical education
sector were to expand to meet more of the demand for medical education.
In such a case, the number of doctors would be higher, while physician
incomes would be about the same or lower. The added supply of physi-

cians would, however, result in higher prices.

 

ACKNOWLEDGMENTS

I am indebted to several individuals for comments and criticism
throughout the development of this study: Daniel Suits, Mark Freeland,
Kenneth Boyer, and Ronald Fisher. Their help has contributed much to
the finished product.

I would like thank Thomas Hall for providing information on his
research, Daniel Suits for developing the solution method described in
Appendix A, and Eugene Moyer, Barry Greengart, and Myron Katzoff for
technical assistance and support.

Thanks to Robert Rasche, Daniel Hamermesh, the late Herbert
Kisch, Ruth Monroe, Pam Japinga, and Marie Connolly for their encourage-
ment and assistance during my years at MSU.

I thank my parents, Bob and Lola Windau, for helping me through
school and for always expecting the best from me. Finally, I thank
Herb Tyson, who encouraged me in this effort as in all my other endea-

vors and who has made our partnership a joyous one.

ii

TABLE OF CONTENTS

List of Tables ....................................................

List of Figures ...................................................

Chapter I.
Chapter 11.
Chapter III.
Chapter IV.
Chapter V.
Chapter VI.

Introduction ......................................
Controversy Over High Medical Care Prices ........
Trends in the Supply of Health Manpower ...........

The Medical Education System and Freedom
of Entry ..........................................

Conclusion ........................................
Theoretical Structure .............................
The Market for Physician Services .................
The Supply of Physician Manpower ..................
The Simulation Model ..............................
The Price Equation ................................
The Income Equation ...............................
The Change in Number of Doctors Equation ..........
Conclusion.............. ..................... i .....
Results of Forecast Simulation ....................

Simulation of Equilibrium Positions of . .
the Model .........................................

Has There Been a Shortage of Physicians? ..........

Comparison with Results on "Optimal" Physician
Stock .............................................

Freedom of Entry ..................................
Conclusions and Recommendations ...................

Conclusions of the Research .......................

iii

vii

13
19
22
22
25
27
30
34
36
38
41

52
53

55
62
69
69

Implications for Policy .........................

Limitations of the Model and Recommendations-
for Further Research ............................

Appendix A. Solution Method for Equilibrium Values of
Physician Population, Prices, and Income ........

Appendix B. Data Sources ....................................

Bibliography ....................................................

iv

70

71

73
76
77

Table
Table

Table

Table

Table

Table

Table

Table

Table

Table

Table

Table
Table
Table

Table
Table

10.

11.

12.
13.
14.

15.
16.

LIST OF TABLES

Annual Changes in Consumer Price Index ..................

Comparison of Medical Care Spending to Personal
Consumption Expenditures ................................

Supply of Active Physicians (M.D. and 0.0.) by
Country of Medical Education ............................

U.S.-trained Medical Graduates (M.D. and 0.0.)
1960-61 through 1974-75 .................................

First-Year Enrollments in Medical and Osteopathic
Schools; 1960-61 through 1975-76 ........................

Foreign Medical Graduates as Percent of Total Active
M.0.s and New Entrants Compared with U.S. Graduates
Selected Years 1963-1976 ................................
Foreign Physicians and Surgeons Admitted to the

United States as Immigrants, by Region of Last
Permanent Residence: Selected Years 1965-1974 ..........

Trend in Number of Active M.D.s by Specialty:
United States and Possessions, 1963-76 ..................

First-Year Students in Medical and Basic Science
Schools and Applicant/Acceptance Ratio, 1931-1978 .......

Attrition Rates in U.S. Medical Schools, Academic
Years 1963-64 through 1976-77 ...........................

First-Year Residency Positions Offered and Percent
Filled 1960-1976 Selected Years ........................

Regression Results for the Price Equation ...............
Regression Results--The Physician Income Equation .......

Regression Results--Change in Number of Doctors
Equation ................................................

Regression Results--Number of Applicants Equation .......

Growth Assumptions for Exogenous Variables-~Baseline
Forecast ................................................

V

3

4

6

8

9

10

11

12

15

18

20
33
35

37
39

42

 

Table

Table
Table

Table

Table

Table

Table

Table

17.

18.
19.

20.

21.

22.

23.

24.

Forecast of Physician Income, Physician Prices,
and Number of Physicians Using Basic Economic
Assumptions .............................................

Results of Two Alternative Forecasts .............. _ ......

Comparison of Simulation Model Forecast of Number
of Physicians with Three Other Forecasts ................

Equilibrium and Actual Levels of Physician Stock,
Nominal Physician Income, and Nominal Physician
Prices ..................................................

Comparison of Equilibrium, Optimal, and Actual
Physician Earnings Patterns .............................

Comparison of Optimal, Actual, and Equilibrium
Physician Stock .........................................

Comparison of Physician Shortages in Simulation
Model and under Hall's Method with 4-Percent
Discount Rate ...........................................

Results of Two Freedom-of-Entry Alternative
Forecasts ...............................................

vi

44
45

49

54

58

59

61

64

- Figure 1.

Figure 2.

Figure 3.

Figure 4.

Figure 5.

Figure 6.

Figure 7.

LIST OF FIGURES

Number of Physicians, 1979-1995--Baseline
Forecast and Two Alternatives ........................... 46

Nominal Physician Income, 1979-1995--Baseline
Forecast and Two Alternatives ........................... 47

Physician Prices, 1979-1995--Baseline and Two
Alternative Forecasts ................................... 48

Relationship of Physician Stock to Earnings and
Returns to Medical Training ............................. 57

Millions of Physicians, 1979-1995--Baseline and
Two Freer-Entry Alternatives ............................ 65

Nominal Physician Income, l979-1995--Baseline and
Two Freer-Entry Alternatives ............................ 66

Physician Prices, 1979-1995--Baseline and Two
Freer-Entry Alternatives ................................ 67

vii

 

CHAPTER I
INTRODUCTION
This dissertation tests the hypotheses that the observed number of
physicians has been lower than the number which would have occurred in a

competitive optimum and that observed physician incomes have been higher

than incomes in a competitive optimum. These hypotheses were developed
from observations about the potential for noncompetitive behavior in
health care markets, particularly with respect to freedom of entry.

The hypotheses were tested using a model of the physician stock which
responds to market forces. It was assumed that physician prices are de-
termined through a combination of supply and demand for services. Physi-
cian income, in turn, was related to physician prices. Finally, the
change in the number of physicians was related to physician income.

The model has some useful applications, including forecasting and
calculation of equilibrium values. The questions to be examined in this
study are:

1) What will be the pattern of physician stock, earnings, and
prices in the future?

2) What has been the relationship between optimal physician stock
and equilibrium physician stock? Have there been surpluses or shortages?

3) What would be the impact of greater freedom of entry into the
medical profession?

Using assumptions based on past experience, the model forecasted
a growth in physician prices from 1980 to 1995 averaging 17.2 percent
per year. Physician income is expected to grow 17.9 percent per year over
the same period, while the physician stock will increase at a rate of only

2 percent per year. The model showed that the stock of physicians over

1

2

the period 1960 to 1977 has been lower and the income of physicians
higher than the levels consistent with a competitive, free-entry op-
timum. Finally, the results indicated that greater freedom of entry
would result in a higher number of physicians with lower average in-
comes than in the baseline forecast.

The remainder of this chapter describes the setting out of which

concerns over freedom of entry to the medical profession have arisen.

Controversy Over High Medical Care Prices

Persistently high medical care prices have led to questions about
the degree of competition in the health care sector. Prices of medical
care services have been rising at a rate faster than the overall Consumer
Price Index for some time. Table 1 shows the rate of increase of the
overall Consumer Price Index as compared with the prices of medical care
goods and services. Since 1955, the pattern has been that the physician
fee index has increased faster than the general price index. This has
been the case in every year since 1965, with the exception of price con-
trol years when medical care was singled out for controls stricter than
those imposed in other sectors. Hospital prices have been increasing
at an even faster rate than physician fees, possibly due to better in-
surance coverage for hospital charges than for physician fees. The
pattern of high prices in the medical care field has been noted by
economists, who look toward lack of competition as one possible explana-
tion.

A second feature of medical care markets which has led to concern
is the rise in real consumption of medical care services (see Table 2).

Personal consumption expenditures for medical care were nearly $116

3
Table 1

Annual Changes in Consumer Price Index*

Opto-
metric
All exami-
medical Physi- nation Prescrip-
Calendar All care cians' Dentists' and eye- Hospital tions
year Items Items fees fees glasses room and drugs

 

1955 -
1960

1965

1966

1967

1968

1969

1970

1971

1972

1973

1974 l
1975

1976

1977

1978

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** Because of revisions to the Consumer Price Index, indices for these
categories are not comparable to prior years.

SOURCE: Health Insurance Institute, Source Book of Health Insurance
Data 1978-79 (Washington: Health Insurance Institute, 1979): 54.

 

 

4
Table 2
Comparison of Medical Care Spending to

Personal Consumption Expenditures

 

Personal

Consumption Total

Expenditures Disposable Personal Ratio of Ratio of
Calendar for Medical Personal Consumption Col. (2) to Col. (2) to
year Care* Income Expenditures Col. (3) Col. (4)
(1) (2) (3) (4 (5) (6)
1950 s 8.8 $ 205.5 3: 192.0 4.3% 4.5%
1960 19.5 349.4 324.9 5.6 6.0
1965 29.4 472.2 430.2 6.2 6.8
1966 31.8 510.4 464.8 6.2 6.8
1967 34.2 544.5 490.4 6.3 7.0
1968 37.8 588.1 535.9 6.4 7.1
1969 43.4 630.4 579.7 6.9 7.5
1970 48.7 685.9 618.8 7.1 7.9
1971 53.4 742.8 668.2 ‘ 7.2 8.0
1972 59.6 801.3 733.0 7.4 8.1
1973 66.6 901.7 809.9 7.4 8.2
1974 75.2 984.6 889.6 7.6 8.5
1975 87.0 1,086.7 979.1 8.0 8.9
1976 101.9 1,184.4 1,090.2 8.6 9.3 '
1977 115.6 1.303.0 ,1,206.5 9.1 9.6

 

* Includes all expenses for health insurance (except loss of income
type .

SOURCE: Health Insurance Institute, op. cit., p. 56

5

billion for calendar year 1977, more than three times the amount spent
ten years earlier. Personal consumption expenditures for medical care
were 9.6 percent of total personal conSumption expenditures in 1977, up
from 7.0 percent ten years earlier. Increases in the price of services
accounted for 54.6 percent of the increase in personal health care ex-
penditures between 1950 and 1976, while increases in the quantity and
quality of services accounted for 34.9 percent of the expenditure in-
crease.17 Thus, medical care expenditures have been growing substan-
tially even when the faster growth in prices.is taken into account.

Trends in the Supply of Health Manpower

 

The supply of health manpower is an important dimension of the
problem of health care delivery. This section examines trends in the
supply of physicians.

The nation's supply of active physicians, including medical doctors
(M.D.s) and osteopaths (0.0.5) rose from 251,900 in 1960 to 390,800 in
1976 (see Table 3.) The growth rate of number of physicians has out-
paced p0pulation growth, so that the ratio of physicians to population
is increasing. In 1950, the ratio as 135 physicians per 100,000 popu-
lation, and the ratio increased by 1976 to 181.5. There was a substan-
tial increase in the proportion of physicians who provide care in the
United States but who have foreign training. The proportion rose from

16.8 percent in 1970 to 20.4 percent in 1976.

 

1 0.5. Congressional Budget Office. "Expenditures for Health Care:
Federal Programs and their Effects" August 1977, cited in Health Insur-
ance Institute, Source Book of Health Insurance Data, 1978-1979 (Washing-
ton: Health Insurance Institute, 1979), p. 47.

Table 3

Supply of Active Physicians (M.D. and 0.0.)
by Country of Medical Education

 

 

 

 

 

Category
1960 1970 1974 1976
Number of Active Physicians
All active
physicians ............ 251,900 323,200 362,500 390,800
U.S. trained ............. NA 263,200 286,000 305,600
M.D. ................. NA 251,200 272,400 290,900
0.0. ................. 12,200 12,000 13,600 14,700
Canadian-trained M. D.‘ s.. NA 5,500 5,600 5,500
Foreign-trained M. D.‘ s. .. NA 54,400 70,900 79,700
Rate per 100,000 Population
All active
physicians ............ 136.0 156.8 171.1 181.5
U.S. trained ............. NA 127.7 135.0 141.9
M.D. ................. NA 121.9 128. 6 135.1
0.0. ................. 6.6 5.8 6. 4 6.8
Canadian-trained ......... NA 2.7 2. 6 2.6
Foreign- -trained .......... NA 26.4 33.5 37.0
Percent Distribution
All active ‘
physicians ............ 100.0 100.0 100.0 100.0
U.S. trained ............. NA 81.4 78.9 78.2
M. D. ................. NA 77. 8 75.1 74.4
0.0. ................. 4.8 3. 7 3.8 3.8
Canadian-trained ......... NA 1. 7 1.5 1.4
Foreign-trained .......... NA 16. 8 19.6 20.4

 

SOURCE: U.S. Department of Health, Education and Welfare. "The
Current and Future Supply of Physicians and Physician Specialists"
Division of Manpower Analysis Report No. 79-13. (Washington: Health
Resources Administration, 1979): Table 4.

7

The growth in overall physician supply also reflects the growth in
number of graduates of U.S. medical and osteopathic schools. Gradua-
tions from medical and osteopathic schools have increased from 7421 in
1951 to 13.415 in 1975 (see Table 4). There has also been an increase
in medical school enrollment, mostly since the mid-1960's. First-year
enrollments increased by 84 percent between the 1960-61 and 1975-76
academic years, while first-year enrollments in schools of osteopathy
increased by 108 percent over the same period (see Table 5).

A substantial part of the overall increase is accounted for by
the entry of foreign-trained physicians. Foreign medical graduates
(FMGs) were about 11 percent of the U.S. physician supply in 1963, but
their numbers have increased so that they were about 21 percent of the
supply in 1976 (see Table 6).

FMGs may enter the U.S. for one of two purposes--training (in which
case they are here on a temporary visa) or permanent residence (perma-
nent resident visa). A shift in donor countries from more developed to
lesser developed and developing countries is evident from the figures in
Table 7. Over time, the proportioh of physicians and surgeons admitted
from Asian countries has increased, while the proportion from Europe
and the Americas has declined. As of 1974, Asian physicians dominated.

The specialty distribution has also gone through changes over time.
Data from 1963 to 1976 from Table 8 show minor changes among most
specialties but great changes in the proportion of general and family
practitioners. The proportion of general practitioners has been de-
clining, but in more recent years the decline has leveled off as demand
for general care has increased and a new specialty, family practice, has

been introduced.

Table 4

U.S.-trained Medical Graduates
(M.D. and 0.0.) 1960-61 through 1974-75

 

 

Total
Graduates M.0. Graduates 0.0. Graduates
1960-61 .... 7,421 6,994 427
1961-62 .... 7,674 7,168 506
1962-63 .... 7,626 7,264 362
1963-64 .... 7,690 7,336 354
1964-65 .... 7,804 7,409 395
1965-66 .... 7,934 7,574 360
1966-67 .... 8,148 7,743 405
1967-68 .... 8,400 7,973 427
1968-69 .... 8,486 8,059 427
1969-70 .... 8,799 8,367 432
1970-71 .... 9,446 8,974 472
1971-72 .... 10,036 9,551 485
1972-73 .... 11,040 10,391 649
1973-74 .... 12,200 11,613 587
1974-75 .... 13,416 12,714 702

 

SOURCE: U.S. Department of Health, Education and Welfare. “The
Current and Future Supply of Physicians and Physician Specialists.“
Division of Manpower Analysis Report No. 79-13. (Washington: Health
Resources Administration, 1979): Table 2.

Table 5

First-Year Enrollments in Medical and Osteopathic Schools;
1960-61 through 1975-76

 

 

 

Academic Total M.D. and 0.0. M.D. First-year 0.0. First-year
Year x First-year Enrollments Enrollments Enrollments
1960-61 .... 8,794 8,298 496
1961-62 .... 9,013 8,484 530
1962-63 .... 9,075 8,642 433
1963-64 .... 9,213 8,772 441
1964-65 .... 9,328 8,856 472
1965-66 .... 9,223 8,759 464
1966-67 .... 9,444 8,964 480
1967-68 .... 9,988 9,479 509
1968-69 .... 10,384 9,863 521
1969-70 .... 10,978 10,401 577
1970-71 .... 11,971 11,348 623
1971-72 .... 13,031 12,361 670
1972-73 .... 14,536 13,726 810
1973-74 .... 15,069 14,185 884
1974-75 .... 15,928 14,963 965
1975-76 .... 16,329 15,295 1,034
SOURCE: U.S. Department of Health, Education and Welfare, op. cit.,

Table 3.

Table 6

10

Foreign Medical Graduates as Percent of Total Active
M.D.s and New Entrants Compared with U.S. Graduates

Selected Years 1963-1976

 

 

 

 

Active FMG Supply Total
New U.S.
Number Percent of Total Active M.D.S‘ Entries Graduates
1963 30,925 11.2 6730 7264
1967 45,816 14.8 8115 7743
1969 53,552 16.5 (6939 8059
1971 59,499 18.5 7879 8974
1973 67,141 19.9 8123 10,391
1974 70,940 20.3 8352 11,588
1975 76,205 20.9 7316 12,714
1976 79,722 21.2 NA 13,561
SOURCE: U.S. Department of Health, Education and Welfare, op. cit.,

Table 6.

11

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12

Table 8

Trend in Number of Active M10.s by Specialty:
United States and Possessions, 1963-76

 

Total . Primary Care Other Medical

, Surgical Other
Active M.0.s Specialties Specialties

Specialties Specialties

 

1963 261,728 110,071 12,291 67,745 71,621
1964 269,552 111,573 12,753 70,515 74,811
1965 277,575 113,090 13,288 73,185 78,012
1966 285,857 114,157 14,045 76,178 81,477
1967 294,072 115,581 14,770 79,025 84,696
1968 296,312 116,760 15,762 81,820 81,970
1969 302,966 114,275 16,530 82,912 89,249
1970 310,845 117,761 17,401 86,042 89,641
1971 318,699 121,599 16,685 89,779 90,636
1972 320,903 122,952 16,549 91,058 90,344
1973 324,367 123,776 17,094 91,549 91,348
1974 330,266 126,431 17,485 93,386 92,964
1975 340,280 130,634 19,010 96,015 94,621
1976 348,443 135,881 18,955 98,667 94,040

 

SOURCE: U.S. Department of Health, Education and Welfare, op. cit.,

Table 8.

13

The Medical Education System and Freedom of Entry

 

One of the key characteristics of a perfectly competitive market
is freedom of entry. Freedom of entry means that resources can flow
unimpeded to the uses for which they can earn the greatest returns.
Firms move into areas where they can earn the greatest profits. When
firms in an industry earn more than normal profit, new firms are induced
to enter the industry. When profits are less than normal, firms leave
the industry. Thus, free entry and exit implies that any profit above
the level of normal profit will be competed away.

In the case of medicine, a substantial investment in human capital
is required for entry into the profession. The requirements that a po-
tential physician attend medical school and be licensed are costly, and
the potential doctor must decide whether the future earnings are likely
to allow a reasonable return on the investment. Some risk is also in-
volved, since the student typically decides on a pre-med curriculum
early in college. The student must appraise the likelihood of being ad-
mitted to medical school, of graduating, and of being licensed.

Potential departures from freedom of entry have been noted at the
various stages of the medical education process. It is important to
examine the process of additions to the stock of physicians and the
charges of economists who believe that freedom of entry is restricted.
We shall also consider the influence of the American Medical Association
on the process, since the AMA is the organization most frequently cited
.as having an interest in restricting the supply of physicians.

The capacity of medical schools to accept new students is a very
important variable. Kessel argues that the capacity of medical schools

was sharply limited by the standards in the Flexner report, a report on

14

medical education assembled for the Carnegie Foundation.1 The result
of the implementation of Flexner's recommendations was reduced output
of physicians by making the graduates of some medical schools (those
which were not "Class A" medical schools as defined by Flexner) ineli-
gible to be examined for licensure and by reducing the output of schools
that continued to produce eligible graduates. Flexner believed that the
best way to educate physicians was the very expensive method then used
at Johns Hopkins University. According to Kessel, Flexner implicitly
ruled out all production functions for physicians other than the one at
Johns Hopkins. Kessel's thesis is that Flexner and the Carnegie Foun-
dation were "dupes of the interests"--i.e., they unwittingly served the
financial interests of the medical profession. Only very sketchy figures
are available to indicate pre-Flexner and post-Flexner physician stock.
In 1900, before the publication of the Flexner report, the Census found
132,000 physicians or 173 per 100,000 population. By 1930, twenty years
after the Flexner report, there were 153,800 physicians or 125 per
100,000 population. More dramatically, the number of medical schools
declined from 160 in 1900 to 76 in 1930. From 1930 to about 1948, the
basic capacity of medical schools remained relatively constant and then
began a general secular increase, as seen in Table 9.

Over the period 193141968, the growth of the medical school sector

was very slow compared with the growth of graduate education as a whole.

 

1 Reuben A. Kessel, "The A.M.A. and the Supply of Physicians," Law and
Contemporary Problems 35 (Spring 1970); Abraham Flexner, Medica
EdUcation in the United States and Canada. (New York: Carnegie Foun-
dation for the Advancement of Teaching, 1910).

 

 

15
Table 9

First-Year Students in Medical and Basic Science Schools
and Applicant/Acceptance Ratio, 1931-1978

 

 

 

Academic Year Total Acceptance Ratio
1931 6,456

1948 6.487 2.9
1949 6,688 3.5
1950 7.041 3.4
1951 7,182 3.1
1952 7,441 2.6
1953 7,425 2.2
1954 7,399 1.9
1955 7,525 1.8
1956 7,688 1.9
1957 7,962 1.9
1958 7,977 1.9
1959 8,145 1.8
1960 8,202 1.8
1961 8,322 1.7
1962 8,510 1.7
1963 8,668 1.8
1964 8,794 1.9
1965 8,800 2.1
1966 8,698 2.1
1967 8,901 2.0
1968 9,403 1.9
1969 9,769 2.1
1970 10,310 2.3
1971 11,348 2.2
1972 12,361 . 2.4
1973 13,726 2.6
1974 14,185 2.8
1975 14,963 2.8
1976 15,351 2.8
1977 15,667 2.7
1978 16,134 2.5
SOURCE: Journal of the American Medical Association, Annual

Education Issues.

 

16

While medical school enrollments were growing about 56 percent, overall
graduate enrollments increased elevenfold. According to Stevens,1 the
aggregate capacity of the medical school sector results from many de-
centralized decisions.

What is the role of the AMA in determining medical school capacity?
According to Stevens, there was direct AMA influence on medical school
capacity after the Great Depression. As a result of the almost 40 percent
delcine in physician incomes between 1929 and 1932, the AMA concluded
that there was a great surplus of physicians and encouraged medical schools
to limit enrollment. Applicantiacceptance ratios increased from an
average of 1.7 during the depression to 3.0 during the late Thirties.
During the war years, accelerated programs were adopted by medical
schools without AMA opposition. Selection of medical students during
the war was made by military officers in conjunction with medical school
admission officers. Beginning in 1949, bills were introduced in Cong-
ress to provide aid to medical education and incentives to increase med-
ical school enrollments. The AMA renewed its efforts in opposing this
legislation, and it maintained a large lobbying force in Washington to
make its views known. The AMA did not enjoy a general stamp of approval
from the medical community, however. During the 19505, other medical
groups, such as the American Academy of Medical Colleges, expressed con-
cern over a shortage of applicants and took Steps to recruit more and

better qualified applicants.

 

1 Carl M. Stevens, "Medical Schools and the Market for Physicians'
Services," in M.S. Gordon, ed., Higher Education and the Labor Market
(New York: McGraw-Hill, 1974).

 

17

Around 1959, the AMA stand changed slightly. AMA committees spoke
out in favor of expanded medical education facilities, but they opposed
federal interference or assistance. There were Several efforts in the
19605, particularly from the private sector, to increase the financial
incentives for applying, entering, and remaining in medical school. In
the late 19605, increased financing from the federal government in the
form of student scholarships and capitation grants helped encourage the

expansion of medical manpower.

During the 19605 and 19705, the number of applicants increased
rapidly, and medical school capacity did not increase quickly enough
to keep up with them. As seen in Table 9, the applicant/acceptance
ratio has been 2.5 or higher since 1972. Federal initiatives to in-
crease medical school admissions have been expanded. The Seventies
saw an increase in the number of American students, unable to get into
crowded U.S. schools, seeking medical training abroad. Data on their
numbers are spotty, but the importance of the phenomenon is illustrated
by a government program which mandates gradual transfers of U.S. medical
students in foreign schools back into U.S. schools.

In the late 19705, there were signs of policy changes. Concern
about a physician oversupply appeared and aid to medical education be-
came less abundant. While the applicant/acceptance ratio remained high,
federal support declined.

Along with the applicant/acceptance ratio, another indicator of
a tight market for medical education is the attrition rate.. As can be
seen from Table 10. attrition rates have declined considerably. Total
four-year attrition from the first-year class was estiamted at 12.2 per-
cent for the academic year 1963-1964 as opposed to 5.4 percent for the

academic year 1976-77. This would tend to indicate that medical students

18

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19

are generally well-qualified and well-motivated. More applicants could
be admitted without a great decline in quality.

Specialty training is one area of medical education where there
is an oversupply of places. According to Table 11, there are actually
vacancies in first-year residency programs. The vacancy rates are
themselves deceptively low, because foreign medical graduates fill many
of the residency slots. The Graduate Medical Education National Ad-
visory Committee estimated that in 1976 there were enough residencies
available to accommodate 128 percent of U.S. medical graduates.1 One
reason for the relative abundance of postgraduate training opportunities
is that financial benefits to the medical profession result from the
existence of hospital interns and residents. Low-paid hospital staff
can free private practice doctors from long hours and night duty.
Doctors who are attached to hospitals with large intern and residency
programs have a competitive advantage stemming from their lower patient
care costs. Thus, once students have graduated from medical school,
the bottleneck in medical education opens up and training becomes
readily available.

Conclusion

 

This section has presented some of the descriptive trends in
medical education and the stock of physicians. The capacity of medical
schools has not expanded as quickly the number of applicants seeking
admission.

Descriptive evidence strongly suggests that there are barriers to

entry into the medical profession. This study will develop a model of

 

1 Graduate Medical Education National Advisory Committee, Interim Report
to the Secretary of Health, Education and Welfare (Washington: Public
Health Service, 1979).

20

Table 11

First-Year Residency Positions Offered and Percent Filled
1960-1976

Selected Years

 

 

First-Year
Resigegcies Offered Percent Filled
1960 713,085 . 87
1968 15,365 ”83
1971 17,693 86
1974 20,405 92
1976 21,145 94

 

SOURCE: American Medical Association, Directory of Accredited
Residencies.

21-

the market for physicians in order to determine whether barriers to
entry do in fact exist. By examining the market for physician services
and responses of potential doctors to income incentives, the study

can determine whether the market for physicians has reached equilibrium

or whether there are surpluses or shortages of physicians.

 

CHAPTER II
THEORETICAL STRUCTURE

The model to be developed in Chapter III examines the supply of
physician manpower by relating changes in the number of doctors to in-
comes of physicians. Physician incomes, in turn, are related to con-
ditions in the product market, the market for physician services.

This chapter discusses the background of the model in terms of
the work of other researchers. First, it is important to understand the
controversies which have arisen over the structure of the market for
services and how supply and demand are uniquely intertwined. Second, it
is important to examine the way in which others have explored the supply

of physician manpower, particularly the question of freedom of entry.

The Market for Physician Services

 

The literature on the market for physician services has exhibited
persistent problems in separating demand and supply factors. Both will
be discussed here.

The theory of the demand for physician services is derived from the
general neoclassical theory of demand, with some additions to allow for
distinctive institutions in medical care markets. The typical demand
curve relates quantity to price of the good or service, holding prices
of other goods, tastes, technology, and income constant. Studies of
the demand for medical care (such as Feldstein, Fuchs and Kramer, and

Newhouse and Phelps)1 have generally included these factors except for

 

1 Martin S. Feldstein, "Econometric Studies in Health Economics," in
Frontiers in Quantitative Economics II ed. Michael Intrilligator and John
Kendrick (New York: North-Holland, 1974); Victor R. Fuchs and Marcia

J. Kramer, Determinants of Expenditures for Physicians' Services in the
United States 1948-68 (Washington: National Center for Health Services
Résearch and Development, 1972); Joseph Newhouse and Charles Phelps,

22

 

23
tastes, which are difficult to measure) in estimating demand.

Insurance has an important influence on all health care markets,
including the physician services market. When insurance coverage is
comprehensive, the consumer does not pay the full cost of care directly.
Since much insurance coverage is provided by employers or government, the
consumer is often unaware even of the cost of the insurance which pays
the bills. Feldstein1 included insurance coverage in his demand model
by using net price, that is, the price of service net of insurance re-
imbursements. By this reasoning, the individual decides how'much care
to consume by looking, not at total price, but at out-of-pocket price.

Determinants of the supply of services have included the price of
services, the price of other factors of production, and the number of
suppliers. It is in examining the impact of number of suppliers on
the quantity and price of services that difficulties arise. Typically,
one would expect that, given constant demand, an increase in the number
of suppliers would increase equilibrium quantity and decrease equilibri-
um price. The increased number of suppliers is seen as a factor which
shifts the supply curve upward. In the case of physician services,
however, it is possible that the number of suppliers has considerable
influence on demand. The potential exists for more influence on demand
than what we would expect just because an increased number of suppliers
means that it will be more convenient to find care.

This potential for "supplier-induced demand" stems from the fact

that physicians both provide care directly and prescribe care to be

 

"New Estimates of Price and Income Elasticities of Medical Care Services"
in The Role of Health Insurance in the Health Services Sector, ed. R.
Rosett New or : ationa ureau o conom1c esearc ,

1 Martin J. Feldstein, op. cit.

24

provided by others. Feldstein classified patient care into three
types: 1) care initiated by the patient himself, 2) care prescribed
by one physician but provided by another, 3) care prescribed and provided
by the same physician. Theories of demand for these three types of
care have varying degrees of similarity to the familiar theory of house-
hold demand. Demand for the first type of care is most similar to the
traditional theories. The patient makes up his own mind whether or not
to seek care and where to seek it. In the second case, the patient may
have less technical knowledge of the care required, but (barring some
sort of fee-splitting arrangement) the physician has little incentive to
maximize the amount of care prescribed. In the third case, where care
is prescribed and provided by the same physician, the doctor does have
an incentive to prescribe additional care. According to Feldstein, it
is only meaningful to study this third type of demand as autonomous
demand if the physician acts completely as the patient's agent--that
is, if the physician makes the same choices as the patient would make if
. the patient had complete information. If the third type of demand is
a significant portion of total demand and if the physician does not act
completely as the patient's agent, then structural models will be un-
successful in disentangling supply and demand.

In contrast to Feldstein, other analysts such as Sloan and Feldman1
have argued that demand generation is not significant enough to worry

about. They cite other industries, such as auto repair, plumbing, and

 

1Frank A. Sloan andRoger Feldman, "Monopolistic Elements in the Market
for Physicians' Services," paper presented at a conference on Competition
in the Health Care Sector, Washington, D.C., 1 June 1977.

25

legal services, where the performance of services requires special
technical expertise.

The controversy over whether suppliers can shift the demand curve
has made structural modeling of the physician services market very
difficult.

The Supply of Physician Manpower

 

The idea that professional associations of physicians conspire to
limit the supply of practitioners is one which has long been advanced,
particularly in Friedman and Kuznets and Kessel.1 A class of studies
in the economics literature has debated whether the pattern or physician
earnings illustrates that the medical profession has the power to limit
the supply of doctors.

Friedman and Kuznets and Fein and Weber2 report high physician
earnings which they think constitute economic rent--that is, a return
to investment in medical education above the amount necessary to keep
physicians in practice. Returns to physician education were reported
to be higher than returns to investment in education for other professions
such as law and dentistry.

Friedman and Kuznets did not look directly at the rate of return,
but they calculated that a difference of 17 percent in earnings of
doctors and dentists was necessary to make the two careers equally

attractive. The actual earnings differential was 32.5 percent, which

 

1 Milton Friedman and Simon Kuznets, Income from Independent Professional
Practice (New York: National Bureau 6? Economic Research, 1945); Reuben
A, Kessel, "The A.M.A. and the Supply of Physicians," Law and Contemporary
Problems 35 (Spring 1970).

2 Rashi Fein and Gerald I. Weber, FinancinggMedical Education: An Anal-
ysis of Alternative Policies and Mechanisms (New York: McGraw-Hill,
1971).

 

26

Friedman and Kuznets explained by citing greater barriers to entry in
medicine. Later, Fein and Weber calculated internal rates of return
for investment in medical training of at least 15 percent.

Continuing the debate, Lindsay1 challenged the methodology of
these studies. He claimed that, in order to measure the returns to
training, the increased work hours of trained persons must be taken
into account in evaluating increased earnings. According to Lindsay,
the productivity of work increases relative to the productivity of
leisure as education increases, so work is substituted for leisure.
Lindsay reevaluated the results of rate-of-return studies using an ad-
justment for hours of work. When hours were accounted for, rents to
medical training disappeared.

Sloan2 contended that the rate of return is not sufficient evidence
for or against monopoly power, since nonmonetary factors also enter into
the occupational choice. Mennemeyer3 reported additional evidence that
the rate of return to physician training, when adjusted for hours of work,
is equal to the rate of return to training for dentistry and law. The
rates of return in all three of these professions, all of which have
some potential for supplier-induced demand, are clearly superior to

the rates of return in other professions.

 

1 Cotton M. Lindsay, "Real Returns to Medical Education," Journal of
Human Resources 8 (Summer 1973): 331-48.

2 Frank A. Sloan, "Real Returns to Medical Education: A Comment"
Journal of Human Resources 11 (Winter 1976): 118-26.

3.S.T. Mennemeyer, "Really Great Returns to Medical Education?" Journal
of Human Resources 13 (Spring 1978): 75-90.

CHAPTER III
THE SIMULATION MODEL

The model of the physician services market to be developed here
will examine the workings of three related processes which make up a
dynamic model. These three processes, each modeled in an independent
equation, are: 1) the determination of the price of physician services;
2) the determination of physician income, and 3) the determination of
the number of physicians.

The number of practitioners relative to population affects the
price of physician services for the reasons discussed above. The number
of practitioners also affects the incomes of individual physicians if
there is a finite demand elasticity for physician services. In turn,
the number of new physicians depends on lagged physician income, because
potential entrants will examine the return to entering the medical pro-
fession.

Various pieces of the process have been modeled before, but a com-
plete simulation model has not been attempted. In developing the model,
lessons from previous work can be incorporated. Ideally, we would like
to construct a structural model of the supply and demand for services
involving both price and quantity. Total physician income would be
equal to total expenditures on physician services, or price times quan-
tity. Average income would then be total physician income divided by
number of doctors.

This procedure was not used for two reasons. First, the controversy
over physician demand generation leaves doubts whether structural models
of the market for services are appropriate. Second, there are problems

of measurement and data availability. Physician services are heterogenous,
27

28
and no reliable measure of quantity is available. In addition, data

on median incomes, not average incomes, of physicians are available.

The price equation estimated incorporates elements of both supply
and demand for services, without attempting to disentangle structural
relationships. This price equation includes variables to reflect the
rapid growth in insurance coverage and the availability of increasingly
sophisticated technology. The income equation includes price and vari-
ables designed to represent quantity of service, since we have no direct
measure of it. The equation determining number of physicians departs
from such previous work as rate-of-return studies by relating the change
in number of doctors to lagged physician income.

Rather than estimate supply and demand equations, I will estimate
the following three relationships which have no direct interpretation
as representing individual economic relationships.

1) Price = f(number of doctors, coinsurance rate, price of other
medical care services, family incomes, level of technical
sophistication)

2) Physicians income a g(price, population, income, number of doctors)
3) Change in number of doctors = h(physicians income lagged 6 years,

real family income lagged 6 years, population lagged 6
years)

The parameters to be estimated are shown in the following
equations:

1) PHYSt/CPIt = a0 + alMDPOP + azcomst + a3MEDPRt/CPIt

t
+ auFAMINCt/CPIt + asTECHt/CPIt
2) LOQ(MDINCt/cplt) = b0 * blLog(PHYSt/CPIt) + b2L09(POPt)

+ b3Log(FAMINCt/CPIt) + b,Log(N00cst)

29

3) DELNDOCS = c0 + c 1140111Ct_5/C1>1t_6 + c2FAMINCt_6/CPIt_

+ c 3P0Pt-6

6

Equation 1 generates the price of physicians' services (PHYS/CPI)--
as measured by the ratio of the physician fee component of the Consumer
Price Index to the total index--as a function of: the U.S. doctor-
population ratio (MDPOP), the average coinsurance rate (COINS), the real
price of other medical care services (MEDPR/CPI), median real family
income (FAMINC/CPI), and the level of technological sophistication of
available services (TECH/CPI) as measured by the ratio of total non-
labor inputs into hospital services to the CPI.

Equation 2 represents average real income per physician as a
function of: the price of physician services (PHYS/CPI), the total
population (POP), median real family income (FAMINC/CPI), and the total
number of physicians (NDOCS).

Equation 3 represents the change in number of doctors (DELNDOCS)
in a praticular year as a function of: real physician income six years
ago (MDINC/CPI), median family income six years ago (FAMINC/CPI), and
total population six years ago (POP). A detailed description of the
data used to measure each variable is contained in Appendix B.

The system represented above is not estimated as a group of simul-
taneous equations but was fitted as three free-standing relationships.
The simultaneity of the relationships is taken into account in the
simulation exercises in Chapter IV. The model used in this work is de-
signed to use changes in the demand for physician services, as reflected
by prices and incomes, to predict the growth in number of physicians.

The number of physicians then feeds back into the price and income

30
equations. Throughout the model, it is assumed that actors in the

‘ marketplace make decisions based upon real quantities. Therefore, all
variables are expressed in real terms. Below, the structure of each

equation and the estimated coefficients are presented and discussed.

The Price Equation

The physician fee component of the CPI was chosen as the dependent
variable for price because of its comprehensiveness. Subcomponents
such as the index for a follow-up office visit were considered, but
because this is a model of the total physician population, it was de-
cided not to use any such index restricted to office-based physicians.
Another possibility which has been used in several studies is a measure
of price as total expenditures deflated by a quantity index. This has
been shown to be a seriously biased procedure, since any measurement
error in expenditure or quantity is compounded when a price measure is
computed. As previously mentioned, all price and income variables in
the model have been deflated by the overall CPI.

The independent variables were chosen to reflect both supply and
demand. Variables in the equation include:

1) The doctor-population ratio, MDPOP. The doctor-population
ratio can be thought of as either a demand or a supply variable. As a
supply variable, it is a measure of the degree of competitiveness of the
marketplace. In recent work, however, several researchers have used
MDPOP in the demand curve in an attempt to examine the hypothesis that
physician supply creates its own demand or simply to examine the effect
of greater availability and convenience of consuming physician services.

It is difficult to predict the sign of this coefficient. As a supply

31
variable, it would be negative, since a higher number of physicians rel-

ative to population would tend to mean more price competition. As a
demand variable, a positive sign is expected, because a greater supply
of practitioners relative to population means that it is more convenient
to consume medical care.

2) The average coinsurance rate, COINS. This is a demand variable
which represents the degree of insurance coverage, both public and pri-
vate, in the population. The average coinsurance rate is the percentage
of total expenditures on physician services which is paid by the patient
out of pocket. The rate has shown a downward trend as insurance covers
more different types of physician services and protects more people.

The sign of the coefficient of COINS is expected to be negative--as
there is more insurance coverage (i.e., a lower coinsurance rate),

people will tend to increase their demand for services and will be

willing to pay a higher price for services.

3) The prices of other medical goods, MEDPR/CPI. Neoclassical
demand theory suggests that demand for a particular good depends on the
price of substitutes and complements. An expenditure-weighted index
of prescription drug prices and hospital prices is used here as a mea-
sure of prices of related medical goods. A positive sign is expected
for the coefficient of MEDPR/CPI, which would mean that these related
goods are substitutes rather than complements with respect to physician
services. The rise in hospital costs, which make up most of the index,
has received considerable public attention. It seems reasonable that a
rise in the price of these services would increase the demand for office-
based physician services because people wish to remain healthy and avoid

expensive treatments.

32
4) Family income, FAMINC. The demand for physician services de-

pends on the ability of families to pay f0r such care. The traditional
measure of ability to pay is income. We expect a positive sign for the
coefficient, but the magnitude is expected to be fairly small because
medical care is perceived as a necessity.

5) Technology, TECH. The increase in the technological sophis-
tication of services available has increased both demand and supply .
Technology would tend to act on the supply of services by increasing
the number of cases a physician could treat in a given period of time,
but it could act on demand by increasing the scope of remedies which
a physician could give a patient. While both influences can work on
prices, it seems reasonable to expect that the demand influence will
predominate. Most of the technological advances in the years in ques-
tion have been of the type that increase the scope of treatment. Thus,
a positive sign for the coefficient of TECH TS EXPECtEd-

The price equation was estimated for the period 1960 to 1977.
Results are given in Table 12. Signs of the coefficients are as ex-
petted Niall but two cases, the coefficients of COINS and TECH/CPI.

The relationship appears to fit well, however. The coefficient of the
most critical variable, MDPOP, appears reasonable. The elasticity of
real price with respect to physician/population ratio is -.00345. This
may indicate that there are indeed two conflicting pressures on price
when the supply of physicians increases--a positive pressure on price
due to increased availability of services and and a negative pressure
due to increased supply and competition among practitioners. The re-
gression shows that the net result is a statistically insignificant co-
efficient. Thus, the doctor/population ratio does not significantly

affect price.

33

Table 12

Regression Results for the Price Equation

PHYS/CPI = a0 + alMDPOP + aZCOINS + aaMEDPR/CPI + auFAMINC/CPI +
asTECH/CPI

 

COEF VALUE STD. ERROR T-STATISTIC ELASTICITY
a0 -0.13507 0.27117 -0.49809

a1 -0.00204 0.15147 -0.01349 -0.00345
a2 0.44904 0.15767 2.84801 0.226

63 0.71384 0.13497 5.28872 0.77976
an 0.00388 0.00122 3.17567 0.308

as -0.67542 -.32440 -2.08209 0.17474

 

RANGE: 1960 to 1977
R2 = .98 Corrected R2 = .97 F = 117.29

Standard error of the regression = 0.0134

34
The Income Equation

 

The physician income equation explains real physician income in
terms of the prices physicians receive for services, the population
available to receive services, family income, and the number of prac-
titioners.

1) Physician prices, PHYS. Real physician income is expected to
respond positively to real physician prices, other things being equal.

2) Population, POP. Population is a proxy for quantity of ser-
vices, in very rough terms. As population increases, the demand for
services, and thus income per physician, is expected to rise.

3) Family income, FAMINC. Real family income is expected to
have a positive impact on real physician income. Family income is an
indicator of ability to pay for services.

4) Number of doctors, NDOCS. As in the price equation, the in-
fluence of number of doctors on physician income can have both supply
and demand components. As a supply variable, a rise in NDOCS would
tend to depress incomes due to the pressure of competition. On the other
hand, we may also see an ”availability" effect on demand. As NDOCS
increases, medical care becomes more convenient to obtain, increasing
demand and thus physician incomes.

Both linear and logarithmic forms of the income equation were esti-
mated over the period 1955-1977, the longest period compatible with a
reasonable data set. The logarithmic form was tried on the grrunds that
the elasticities of the independent variables with respect to income
might be expected to be constant. The logarithmic form exhibited a
better fit and was retained in the model. The regression results are

presented in Table 13. Signs of the coefficients were in accordance

35
Table 13

Regression Results--The Physician Income Equation

LOG(MDINC/ACPI) - b1 + b2*LOG(PHYS/ACPI) + b3*LOG(POP)
+ ba*LOG(FAMINC/ACPI) + b5*LOG(NDOCS)

 

COEF VALUE STD ERR T-STAT
bl -15.74720 10.50580 -1.19891
b2 0.71290 0.63578 1.12129
b3 3.32902 1.20749 2.75696
bk 1.02337 0.42995 2.38020
05 -1.85644 0.37138 -4.99879

 

RANGE: 1955 to 1977

R2 = .90 Corrected R2 = .88 F = 41.808

Standard error of the regression = .0568

NOTE: Since the regression is in double-log form, coefficients

represent elasticities.

36
with expectations. The NDOCS variable had a negative sign, and the elas-

ticity of real physician income with respect to NDOCS is -1.8.

The Change in Number of Doctors Equation

 

An equation with changes in number of doctors as the dependent
variable was estimated with a six-year lag on the grounds that the de-
cision to become a doctor and policy decisions with respect to health
manpower are made six years before they have an effect on the physician
stock. The independent variables in the equation are:

1) Physician income lagged six years, MDINCt_6. The pattern of
physician income at the time of a person's career decision gives infor-
mation on the potential return to investment in medical education.
Higher physician incomes are expected to lead to a higher number of
doctors.

2) Family income lagged six years, FAMINCt_6. The family income
term is included in the equation as a contrast to physician income. The
absolute level of physician income is important, but so is the position
of physicians relative to the rest of the population. A negative sign
is expected for this variable.

3) Population lagged six years, POPt-G' The population is a mea-
sure of potential doctors and potential demand for services. A positive
sign is expected.

The equation was estimated for the interval 1961-1977, and the re-
sults are presented in Table 14. The fit of the equation is not as good
as that of the other two equations, and none of the coefficients are
statistically significant. An alternative formulation with the two income
variables collapsed into a ratio to minimize collinearity was tried,

but the ratio was still insignificant. This is not too surprising in

37

Table 14

Regression Results--Change in Number of of Doctors Equation
NDOCSt - NDOCSt_1 = C1 + CZ (MDINC/CPI)t_6 + C3 (FAMINC/CPI)t_6

+ C, POPt_

 

6
COEF VALUE STD ERR T-STAT ELASTICITY
c1 -30915.10000 46126.00000 -0.67023
c2 102.29400 177.72000 0.57559 3.08
c3 -520.99700 928.91700 -0.56086 -3.79
cu 0.25220 0.40304 0.62576 4.91

 

RANGE: 1961 to 1977
R2 = .40 Corrected R2 = .27 F = 2.932

Standard error of the regression = 4760

38
view of the limitations on entry into the U.S. medical profession. This

equation and the model as a whole represent the response of potential
doctors to income differentials as permitted by admissions policies to
medical schools and immigration policies toward foreign physicians.

If entry is restricted, the true response of potential physicians is
masked by restrictive admission or immigration policies.

In order to gain further information about responses of potential
physicians, the responses of applicants to medical schools were inves-
tigated using a similar specification (see Table 15). Applicants do
respond significantly to income incentives, and the elasticity of appli-

cants with respect to real physician income is 3.265, slightly higher

than the 3.08 observed in the physician equation. This is, if anything,
an underestimate of the true responsiveness of potential physicians to
physician income. It seems reasonable to assume that there are poten-
tial physicians who do not apply to medical school because entry is so
limited. The formulation also does not take account of foreign physi-
cians seeking admission to this country.

Conclusion

 

The results of the model estimation reveal some interesting charac-
teristics of the market for physician services. An increase in MDPOP
does not have much effect on price, while an increase in NDOCS does in-
crease physician income. This suggests that the adjustment mechanism
to a new number of doctors works mainly through quantity rather than
price. It also suggests that physicians have a strong incentive to
limit their numbers, since an increase in NDOCS affects their incomes

negatively.

39

Table 15

Regression Results -- Number of Applicants Equation

APPLIC = d1 + d2 (MDINC/CPI)t_6 + (13 (FAMINC/CPI)t_6

 

+ dl+ (POP)
COEF VALUE STD ERR T STAT ELASTICITY
d1 30696.7 42904.7 0.72
d2 308.35836 100.44246 3.07 3.265
d3 -777.77578 396.82438 -1.96 -1.990
d“ -O.18937 0.24638 -O.77 -1.393

 

RANGE: 1961 to 1977
R2 = .95 Corrected R2 = .94 F = 90.014

Standard error of the regression = 2560

40

The estimated elasticity of income with respect to NDOCS of -1.8
has implications for physician fixed costs. Assume that, in the short
run, a constant total of fees were divided up among more and more doc-
tors. If this were the only factor at work, the elasticity should be
-1.0. Since the number of doctors has little effect on price, in the
short run the difference must be due to fixed cost per physician. Total
income per doctor net of expenses (y) is total fees per doctor (F,
assumed constant) less fixed cost per doctor (c).

y = (F/n) - c
If total fees are constant, the elasticity of y with respect to n is:
e= (n/y) (dy/dn) = -1/(1-(c-f), where f is average fee per
doctor. If e is -1.8, this implies that c/f’a .45, i.e., 45 percent
of the average physician's fees are absorbed by fixed costs.

Finally, the poor fit of the change in NDOCS equation provides
additional corroboration for the restricted entry hypothesis.

In the following two Chapters, the empirical model is put to prac-
tical use. In Chapter IV, the model is used to forecast the endogenous
variables, and these forecasts are compared with other forecasts which
do not take economic factors into account. In Chapter V, equilibrium
positions of the model are examined to determine whether there has been

a shortage of physicians, and if there has been, to determine the cause.

CHAPTER IV
RESULTS OF FORECAST SIMULATION

The model presented in the last chapter can be used to forecast
number of physicians, their average incomes, and the level of physician
fees under varying economic conditions. Unlike methods which build up
from medical school capacity and other institutional variables, the
model allows us to make f0recasts accounting for the economic deter-
minants of behavior.

In order to forecast, future values of the exogenous variables
were assumed. The assumptions for exogenous variables (Table 16) were
based on recent historical patterns and macroeconomic forecasts. A
baseline forecast and two alternative forecasts were performed to demon-
strate the sensitivity of the model to varying assumptions.

Population was assumed to grow at a rate of 0.7 percent per year,
the approximate growth from 1974-77. This yielded a population estimate
in 1995 within 2 percent of the Census projections. The coinsurance
rate was assumed to decline slightly each year due to improvements in
insurance for physician services. The 0.5 percent per year decline allows
for gradual improvement in health care coverage, but it does not allow
for major government or private expansion of coverage. Other medical
care prices are assumed to grow 14 percent per year, or 8 percentage
points per year faster than the Consumer Price Index, in the baseline
forecast. Since 1967, other medical care prices have grown substantially
faster than the overall CPI. Even a mild hospital cost containment pro-
gram has been voted down. While it appears unlikely that.the inflation
in medical care prices will moderate, Alternative 2 assumes that medical

.Care prices and the CPI will both increase at the same rate. Family
41

42

Table 16

Growth Assumptions for Exogenous Variables

VARIABLE

Population
Coinsurance rate
Other medical prices
Family income
Technology

Consumer price index

Baseline Forecast

SOURCE OF ASSUMPTION

 

1974-77 growth rate

1975-77 growth rate
1974-76 growth rate

Chase Econometrics long-
term forecast

ANNUAL RATE OF GROWTH

 

0.7%
-0.49
14.0

9.0
19.0

6.0

 

ALTERNATIVE 1

CPI -- 10 percent per year

Family income -- 8 percent per year

ALTERNATIVE 2

CPI -- 10 percent per year

Other medical prices -- 10 percent per year

43
income was assumed to grow in the baseline forecast at the rate of 1974-

77, 9 percent. Alternative 1 assumes that family income will not grow

as fast as the CPI but will grow at only 8 percent. Technology change

is difficult to measure, but the most recent growth rate has been 19
percent, and it seems unlikely that this will decline much soon. With
more sophisticated equipment and the growing use of paramedical personnel,
it is unlikely that the production function for services will remain the
same. The CPI was assumed to grow at 6 percent, because this seemed the
most reasonable long-term forecast. The two alternatives do allow for
different patterns of growth in the CPI.

Results of the baseline simulation are shown in Table 17. The
forecast shows a growth in physician prices from 1980-1995 averaging
17.2 percent per year, well over the 6 percent growth assumed in the
overall CPI. Physician income is expected to grow by 17.9 percent per
year over the same period, while the physician stock will grow only about
2.0 percent per year.

Results of the two alternative forecasts are shown on the following
pages. When family income grows more slowly than the CPI (Alternative 1),
the number of physicians starts out lower than the baseline and ends up
higher. Physician income starts out higher and ends up lower, while
prices are slightly higher. When other medical prices and the CPI both
grow at 10 percent per year (Alternative 2), the number of physicians,
physician income, and physician prices are all lower. In this alternative,
the slower growth of other medical prices eventually puts a brake on
demand.

Forecasts from this model can be compared with forecasts of number

of physicians obtained from other models. The results will be compared

44
' Table 17
Forecast of Physician Income, Physician Prices, and Number of

Physicians Using Basic Economic Assumptions

 

NUMBER OF

YEAR PHYSICIANS NOMINAL INCOME PHYSICIAN CPI

 

1979 472605. 61502.7 248.243
1980 478796. 68438.2 274.379
1981 485291. 76042.2 302.993
1982 491788. 84457.4 334.247
1983 198130. 93809.5 368.291
1984 504822. 103996. 405.259
1985 512158. 114931. 445.258
1986 520302. 126541. 488.359
1987 529237. 138809. 534.578
1988 538978. 151676. 583.859
1989 549557. 165072. 636.053
1990 560934. 178921. 690.884
1991 573026. 193166. 747.913
1992 585712. 207749. 806.495
1993 598866. 222573. 865.722
1994 612349. 237536. 924.35

1995 626004. 252457. 980.718

 

45

Table 18

Results of TWo Alternative Forecasts

ALTERNATIVE 1

NUMBER OF DOCTORS NOMINAL INCOME PHYSICIAN PRICES

 

 

 

1979 454969.00000 70745.10000 278.50400
1980 462887.00000 77669.40000 305.66400
1981 471664.00000 85009.20000 335.34700
1982 480752.00000 92951.70000 367.72300
1983 488233.00000 102284.00000 402.95600
1984 499951.00000 110767.00000 441.19600
1985 512453.00000 119648.00000 482.57000
1986 524705.00000 128928.00000 527.17300
1987 539623.00000 138630.00000 575.05300
1888 554192.00000 148734.00000 626.19400
1989 569689.00000 159067.00000 680.49400
1990 585496.00000 169892.00000 737.73600
1991 601511.00000 181224.00000 797.55300
1992 617629.00000 193043.00000 859.39000
1993 633753.00000 205343.00000 922.44800
1994 649782.00000 218022.00000 985.61500
1995 665564.00000 231009.00000 1047.39000
ALTERNATIVE 2
NUMBER OF DOCTORS NOMINAL INCOME PHYSICIAN PRICES
1979 454969.00000 69093.60000 262.39000
1980 462887.00000 74773.80000 278.51800
1981 471664.00000 80508.50000 294.69800
1982 480752.00000 86402.90000 310.65700
1983 488233.00000 93069.10000 326.04200
1984 499156.00000 98644.30000 340.40900
1985 509969.00000 104220.00000 353.19100
1986 520532.00000 109709.00000 363.68000
1987 530642.00000 114990.00000 370.99300
1988 540155.00000 119844.00000 374.03800
1989 549173.00000 123844.00000 371.46700
1990 557074.00000 126709.00000 361.62500
1991 563701.00000 127700.00000 342.48600
1992 568881.00000 125685.00000 311.57400
1993 572421.00000 118834.00000 265.87800
1994 574081.00000 103962.00000 201.73700
1995 573535.00000 74577.60000 114.71200

 

46
FIGURE 1

Number of Physicians, 1979-1995--Baseline Forecast and TWo Alternatives

450000 500000 550000 600000 650000 700000

|=:=======|=====:===|======s==|=:=======I:========|

‘ 75? *2 A I I I I s
I 2 .A I I I I I

I if A I I I I I

l 2 It I I I I I

I 2 A I I I I

84 6 - - - - ZA- — - — I - - - - | — - - - | o - - - o
I I 3 I I I I

I I 28 I I I I

I I 2 13 I I I I

I I 2 It: I I I

89 41" - - - I '- - - - '- B - - I " ' " ' I '- - -'- 0
I I TLA b I I I

I I I C. A B I I

I I I (I A I B I I

I I I C A b I I

94 o - - - - | - - - - | - -C- - | A - - - B , - - - o
I I I C I A I B I
|=========|z===s====I===:=====|=========I====::=:=

650000 500000 550000 600000 650000 700000

LEGEND

Baseline Forecast
Alternative 1
Alternative 2

2 points at same number

)4
II

NOW
ll

47

FIGURE 2

Nominal Physician Income, 1979-1995--Baseline Forecast and Two Alternatives

50000 125000 200000 275000
I:==========:=:|:=======:==:==|=::=====:====2.
'79 <1 A c! I I 0
I .ACB I I I
I AC8 I I I
I 2 E! I I I
I 26 I I I
b4¢----CAB-I ------- I-------*
I (I ABI I I
I (2 A8 I I
I c I 2 I I
I CI 2 I I
59 ‘ .- - up up up up -C- an a BA- «- - I I- c- c- - - - In.
I C 8 A1 I I
I IC 13 Al I
I C BI .A I
I Cl 18 A I
94 0 - - - - -C- -I- - - r - ~ - I - 8 - A - - -¢
I C I I B A I
I=========z==z=|========z=====|======:====::=
50000 125000 200000 275000
LEGEND
A = Baseline Forecast

Alternative 1
Alternative 2
2 points at same number

NOW
II II

48

FIGURE 3

Physician Prices, 1979-1995--Baseline and Two Alternative Forecasts

0 200 400 600 800 1000 1200
I ======= I :===:== I ======= I ======= I ======= I =:===:= I
79 t I 28 I I I I 0
I I 28 I I I I I
I I 28 I I I I I
I I CA til I I I I
I I (3 A8 I I I I
8411' - - - I '- - (IIA B - - I '- - -' I - - - I .- - - 0
I I C: I A8 I I I I
I I CI A8 I I I I
I I CI A BI I I I
I I CI AIB I I I
89 0 - - - I - - -CI ' - - IA-B- - I - - - I - - - 9
I I C I I A B I I I
I I C I I A B I I
I I C I A b I I
I I C I I I A b I I
94 . - - - c - - - I - - - I - - - I - -A-81 - - - .
I C I I I I AI 8 I
I:====:=I:=:====I=======I=======|======3I=======|
0 200 400 500 800 1000 1200

LEGEND

Baseline Forecast
Alternative 1
Alternative 2

2 points at same number

)1
n

NON
II II

49

with a forecast made by the Health Resources Administration in 1974,
with another forecast made by HRA in 1978, and with a 1979 forecast
made by the staff of the Graduate Medical Education National Advisory
Committee (GMENAC).1 It is useful to examine the results of the base-

line forecast and three other forecasts (Table 19). The 1974 HRA fore-

Table'19

Comparison of Simulation Model Forecast of Number of Physicians
with Three Other Forecasts

 

Simulation HRA HRA GMENAC
Year Model 1974 1978 1979
1980 478,796 334,800 444,000 477,800
1985 512,158 381,100 519,000 523,600
1990 560,934 429,800 594,000 596,800
Average rates
of growth:

1980-1985 1.34 2.59 3.12 1.83
1985-1990 1.82 2.41 2.70 2.62
1980-1990 1.58 2.50 2.91 2.20

 

cast is much lower than any of the others. This may be due to the fail-

ure to foresee policy developments such as increased admission of FMGs

or expansion of medical school capacity. In the longer range, the fore-

casts diverge, with the forecast from the simulation model being sub-

 

1 U.S. Department of Health, Education and Welfare, The Supply of Health
Manpower: 1970 Profiles and Projections to 1990 (Washington: Health
Resources AdministratTon, 1974); U.S. Department of Health, Education

and Welfare A Report to the President and Congress on the Status of Health
Professions 1n the United States (Washington: Health ResourceS’Admini-
stration, 1978); Graduate Medical Education National Advisory Committee,
Interim Report to the Secretary of Health, Education and Welfare (Washing-
ton: Health Resources’Administration,1979).

 

50
stantially lower than the HRA 1978 forecast or the GMENAC forecast.
The simulation model and the GMENAC forecast show more rapid growth in
the latter half of the decade. Both the GMENAC and HRA forecasts show
higher rates of growth than the simulation model baseline.

There are two principal reasons for this divergence. First, the
methods used by HRA and GMENAC involve considerably more disaggregation
than the present model. Second, the simulation model forecasts by pro-
jecting that the historical relationships which were estimated empiri-
cally will continue. It does not incorporate, as the other forecasts
do, specific information about medical school capacity.

It is useful to compare the assumptions of the HRA and GMENAC
foecasts with the current forecast. Both of the HRA forecasts build up
from the components of number of physicians, including:

1) the flow of medical school graduates from U.S. medical schools

2) the active stock of physicians in the base year

3) the future supply of FMGs, using trends modified by future

policy prospects

4) deaths and retirements

5) emigration of FMGs who have completed their training.

Except for the FMG components, the components are estimated based on
trends adjusted for expectations of the future. These assumptions are
somewhat different for the 1974 and 1979 HRA forecasts. In 1974, HRA
assumed:

1) The number of first-year places in medical schools mandated
by federal legislation in 1972 would be maintained through 1974.

2) After 1974, a combination of public and private support would be
available to at least maintain the productive capacity of medical schools

at their 1974 level.

51 f
3) The 1970-71 increase in the FMG population is viewed as the

initiation of a continuing, but not accelerating trend throughout the
next two.decades.

4) Projections are made of future profiles of supply, independent
of any considerations of demand.
HRA's 1978 assumptions were somewhat different:

1) There will be enough support to maintain but not expand medical
school enrollments after 1981.

2) Projections are made based on the assumption that demand for
physicians will not affect the short-run supply of graduates.

The model used here has several advantages in forecasting number
of physicians, income, and prices. The forecasting is done in a uni-
fied way, with the three variables relating to one another. The HRA and
GMENAC methods can estimate number of physicians, but they can say nothing
about their incomes or the economic climate in which they operate. The
HRA and GMENAC forecasts are only as good as the judgments made about
government aid to medical schools, licensing regulations, and immigra-
tion policies. Using their methods, trends in medical school enrollments
are assumed to continue, regardless of demand patterns or income incentives
for physicians. The model presented here is a method which has a sensi-
tivity to economic variables which are not used at all in the HRA and

GMENAC forecasts.

CHAPTER V
SIMULATION OF EQUILIBRIUM POSITIONS OF THE MODEL

By observing equilibrium positions of the model and comparing them
with actual values, we can determine whether or not there has been a
shortage of physicians.

The rate-of-return studies cited at the end of Chapter II tried
to examine physician shortages by looking at the return to physician
training. If that return was substantially higher than in other pro-
fessions, this would tend to indicate a shortage due to limited entry.
This study differs from the rate-of-return studies in two important
respects: 1) Physician income is the variable indicating return to
training; explicit rates of return cannot be computed readily given the
data available; 2) Instead of just examining return, we can look ex-
plicitly at equilibrium number of physicians and compare that equili-
brium with the number of physicians which would exist in a no-profit
equilibrium.

There are basically two sets of circumstances in which a shortage
of physicians could persist. The first can be called "shortage due to
limited entry." In this case, limitation of entry to the profession
leads to a population of physicians that is smaller than the equilibrium
level implied by free entry. This could be due to limitation of entry
by a cartel of physicians or by the unwillingness or inability of the
medical education sector to accommodate the demand for training. The
second type of shortage can be called "shortage due to low prices."
When actual price is below equilibrium price, then quantity demanded

exceeds supply and there is a shortage. This may be due either to slow

52

53

adjustment of prices or to persistent willingness of physicians to hold
prices below equilibrium levels.

In this Chapter, the equilibrium positions of the model will be
compared with the actual historical data and with a series on optimal
physician stock developed in Hall.1 Finally, the model will be simula-
ted under conditions of freer entry.

Has There Been a Shortage of Physicians?

In order to determine whether there has been a shortage of physi-
cians, the model relationships can be solved under stationary conditions.
There will be some point at which the stock of physicians just maintains
itself and income and prices are at equilibrium. To obtain these values,
the change in the number of doctors was set to zero, and the resulting
values of physician:, incomes, and prices were examined. The solution
method is examined in more detail in Appendix A. Results of this solution
process for the period 1960-77 are in Table 20. As we can see by com-
paring the equilibrium values with actual values, there has been a sub-
stantial shortage of physicians in this period.

The equilibrium stock of physiCians is substantially higher than the
actual stock in each year. Physician incomes are also substantially
higher than their equilibrium values. These results indicate that phy-
sicians are indeed benefiting from the shortage--their incomes are higher
than they would be in the absence of a shortage.

What is the cause of this shortage? One possibility is that there

is no underlying shortage in the sector, but that speed of adjustment to

 

1 Thomas D. Hall, "The Behavior of Medical Schools as Non-Profit Firms"
(Ph.D. dissertation, UCLA, 1976).

Equilibrium and Actual Levels of Physician Stock.

54

Table 20

Nominal Physician Income, and Nominal Physican Prices

 

Ph sician Stock
EOUI. AC1.

Ph sician Income
E051. 'ACT.

P sician CPI
EEUI. ACT.

 

 

 

 

 

 

1960 350434 274833 13322 22833 78.6 77.2
1961 354983 272484 13965 23567 79.0 79.2
1962 358164 270136 15185 24300 81.2 81.5
1963 378366 289188 15172 25050 83.1 83.3
1964 405019 297089 14913 28380 85.8 85.3
1965 415855 305115 15861 28960 88.5 88.4
1966 446197 313559 15889 32170 i 92.8 94.0
1967 476873 322045 15671 34730 97.9 100.5
1968 506586 330732 16011 37620 104.4 106.1
1969 533592 388942 16748 40550 113.1 112.9
1970 545867 348328 17581' 41500 121.4 121.4
1971 556311 359864 18774 42700 130.5 129.8
1972 560899 371400 20630 40730 135.4 133.8
1973 573800 381600 21622 42140 140.3 138.2
1974 564565 394500 23905 44580 151.3 150.9
1975 566687 409000 26374 47520 161.8 169.4
1976 609070 426000 26665 52430 188.4 188.5
1977 640031 438780 27107 52640 204.8 206.0

 

55
new conditions is slow. There may be a traditional price structure
which does not move rapidly. In the physician market, providers may be
reluctant to raise their prices due to humanitarian motives. If prices
do not rise rapidly enought to clear the market, shortages result. In
order to determine whether the market has been subject to a slow-adjust-
ment type of shortage, it is necessary to look at equilibrium vs. actual
prices. If equilibrium prices are higher than actual prices, this would
support the idea that the shortage is due to slow adjustment. In fact,
examination of the prices in Table 20 does not support this conclusion.
Equilibrium prices are very close to actual prices, slightly above actual
prices in some years and slightly below actual prices in others. There
is no clear pattern of prices failing to adjust in response to demand
pressures.

If the shortage is not due to sticky prices, then the only plausible
cause is restrictions on entry and mobility. The descriptive evidence
of high applicant/acceptance ratios presented in Chapter I has been
corroborated by these findings of a shortage of physicians.

Comparison with Results on "Optimal" Physician Stock

 

Hall1 looks at the problem of freedom of entry from a different per-
spective. He tries to determine the level of physician stock consistent
with a no-profit equilibrium. If this "optimal“ physician stock is near
the actual level, then this would constitute evidence that there is sub-
stantial freedom of entry in the physician services market.

Hall's methodology works from the relationship between the earnings

of physicians and the physician stock. This relationship should be a

 

1 Thomas 0. Hall, op. cit.

56
downward-sloping one, as in Figure 4(a). This relationship can be esti-
mated empirically and is related to the demand curve for services. Then,
in Figure 4(b) earnings of physicians can be related to the degree of
return from physician training. A stock of physicians S0 which has
earnings E0 implies a rate of return no which is a normal profit with
no economic rent. Hall terms the stock of physicians consistent with
zero economic rent the optimal stock of physicians under static demand
conditions. An example of a physician shortage can be seen at physician
stock SA and earnings EA. There, physicians earn a return nA which in-
cludes economic rent.

In order to implement this method, Hall developed a profitability
function which determines the profits of physicians at different levels
of earnings. The profitability function consisted of variables such as
real scholarship dollars per student, tuition for medical school, real
after-tax earnings for college graduates in the same age bracket as the
individual physician, residents' earnings, the percentage of people
drafted multiplied by real military pay, hours worked, the probability
of death by age bracket, and the discount rate. For each year, age-
bracket earnings are compared to median earnings to determine the earnings
consistent with zero-profit equilibrium. These earnings are then sub-
stituted into the earnings-stock relationship to determine optimal phy-
sician stock.

The results from the current model and from Hall's model are compared
in Table 21 (earnings) and Table 22 (physician stock). The two models
have slightly different definitions of earnings and physician stock, so
they cannot be compared directly. The current model forecasts median

earnings of all private, office-based physicians, while Hall's model

57

ea “gamma ea ”“2822
PR om
$3558.. <5 3.85 25333

<m

“

 

 

.
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59
Table 22

Comparison of Optimal, Actual, and Equilibrium Physician Stock

 

 

Equilibrium Actual Optimal Actual
M.D.&D.0. M.D.&D.0. Percent M.D. M.0. Percent
Stock Stock Difference Stock Stock Difference
Year (1) (2) (3) (4) I5) (6)
1960 350434 274833 27.5 265320 255860 3.7
1961 354983 272484 30.3 269330 260150 3.5
1962 358164 270136 32.6 279890 270140 3.6
1963 378366 289188 30.8 291880 276480 5.5
1964 405019 297089 36.3 299450 284220 5.4
1965 415855 305115 36.3 315650 292090 8.1
1966 544197 313559 42.3 325540 300380 8.4
1967 476873 322045 48.1 348690 308630 13.1
1968 506586 330732 49.5 354840 317000 11.9
1969 533592 388942 57.4 360160 324900 19.8
1970 545867 348328 56.7 376060 334000 12.6
1971 556311 359864 54.6 394050 344800 14.3
1972 560899 371400 51.0 392770 355000 10.6
1973 573800 381600 50.4 408930 366380 11.6
SOURCES:
(2) Total U.S. physicians (M.D.‘s plus osteopaths). Historical

 

Statistics of the U.S. and Statistical Abstract.
(4) Optimal stock of M.0.'s, as reported in Lindsay, Hall and
Leffler, op. cit.

(5) Actual stock of M.0.s as reported in Lindsay, Hall and Leffler,
op. cit.

60
looks at median earnings of general practitioners. Hall's model appears

to deal only with M.0.s, and the current model includes both M.0.s and
osteopaths. In order to alleviate these problems of comparability, the
comparisons are made on the basis of percentage differences between
equilibrium or optimal values and actual values. On this basis, the
present model shows consistently higher differences between the equili-
brium earnings and actual earnings than Hall finds between optimal and
actual earnings. Hall finds that earnings are higher than their optimal
levels, but the results are sensitive to the choice of the discount rate.

Using a 12 percent discount rate, the differences between equili-
brium and actual physician stock are smaller. This led Hall to conclude
that the pattern of earnings and physician stock as compared with their
optimal levels did not indicate any artificial limitation of the number
of physicians. However, a 12 percent discount rate seems far too high
for this kind of evaluation. A real discount rate of perhaps two to
four percent would be more appropriate. The lowest discount rate for
which Hall reports results is 8 percent. Rough estimates of optimal
physician stoCk using a 4 percent discount rate indicate larger shortages
(see Table 23).

A second problem with Hall's model is that optimal earnings are com-
puted only for one specialty (and one of the least common Specialties),
general practice. Of course, there is no single optimal earnings level
but different levels depending on specialty. Implicit in Hall's model
is the assumption that one specialty's earnings can be used to represent
a complete set of earnings levels. The current model looks at all
specialties on average. The earnings measures of both models are limited

to office-based practitioners.

61
Table 23

Comparison of Physician Shortages in Simulation Model
and under Hall's Method with 4-Percent Discount Rate

'Percent Physician
Shortage Implied by
Year Simulation Model

Percent Physician
Shortage Using
4-Percent Discount Rate .

 

1950 27.5 28.4
1951 30.3 28.3
1952 32.5 26.8
1963 30.8 27.7
1954 35.3 25.7
1955 35.3 28.0
1955 42.3 27.0
1957 48.1 30.8
1968 49.5 29.5
1959 57.4 _ 27.7
1970 55.7 27.8
1971 54.5 27.5
1972 51.0 23.3
1973 50.4 22.7

 

SOURCE: To estimate the implied shortage at a 4-percent discount rate,
the estimate of optimal physician stock at an 8-percent rate was in-
flated by the ratio of optimal stock at 8 percent and optimal stock
at 12 percent from Lindsay, Hall and Leffler, op. cit.

62

The results from the current model, in sharp contrast to Hall's
results, show actual earnings higher than their equilibrium levels by
a substantial amount. Earnings were highest in comparison to equili-
brium in 1968 and 1969, shortly after the introduction of Medicare and
Medicaid. These two programs greatly expanded patient ability to pay
and may have spurred noncompetitive activity by physicians. The Optimal
vs. actual relationship is slightly more moderate in the early 1970's
as price controls began.

The physician stock comparisons follow the same pattern: Hall's
model shows much smaller physician shortages than the empirical model.
In 1970, Hall's model shows a 12.6 percent shortage, while the present
model shows a 56.7 percent shortage of physicians. According to the
model, equilibrium is not being achieved. As we have seen, this is not
due to slow adjustment of prices but to barriers to entry and mobility.

Freedom of Entry

 

The third application of the model shown is an attempt to determine
the Situation if entry were substantially easier than presently. The
model is an empirically estimated one and thus reflects the entire situa-
tion, including any artificial limitations on physician supply. The ob-
served responsiveness of number of physicians to change in physician
income, family income, and population contains not just autonomous de-
cisions by potential physicians but also reflects the complex policy en-
virnoment in which these decisions were made. This environment includes
the policy toward medical schools, medical school capacity, pressures
by the AMA on capacities or licensing, and policies toward immigration

of foreign medical graduates.

63

In this application of the model, we ask ourselves what would happen
if this pattern of responsiveness were to change. In particular, econo-
mists who believe that the AMA has artificially limited the supply of
physicians believe that the actual responsiveness of potential physicians
to changes in physician income is greater than is manifested.

One way to examine the implications of this view is to perform a
simulation using a different degree of responsiveness. The responsiveness
of applicants to medical school to physician income was estimated. Appli-
cants as a group can be expected to have a higher responsiveness to
changes in physician income, and use of that elasticity is an indicator
of what would happen if the medical education sector were to expand to
reflect the demand for medical education.

The elasticity of change in number of applicants with respect to
physician income Was found to be 3.265 in the equation shown in Table
15, as opposed to a 3.08 elasticity of change in number of doctors
with respect to physician income. As we noted previously, the applicant
elasticity is probably an underestimate of the true responsiveness of
potential physicians to incomes. Therefore, two alternative elasticities
were used. The first alternative was the 3.265 from the applicant
equation. Second, the 3.08 elasticity in the number of doctors equation
was doubled. The same assumptions for the exogenous variables as in the
baseline forecast were used.

The results of the forecasts in Table 24 and the figures following
can be compared with the baseline. Greater responsiveness of the system
to the demands for entry results in a large increase in number of physi-

cians. Nominal physician income is about the same in the first alternative

Results of Two Freedom-of-Entry Alternative Forecasts

64

Table

24

ALTERNATIVE 1

 

NUMBER OF DOCTORS NOMINAL INCOME PHYSICIAN PRICES
1979 458912.00000 71191.20000 279.85300
1980 468485.00000 78473.60000 307.85900
1981 489273.00000 86270.20000 338.52200
1982 490251.00000 94748.90000 372.03100
1983 499513.00000 104771.00000 408.56400
11984 512929.00000 114121.00000 448.29400
1985 526889.00000 124128.00000 491.37200
1986 541369.00000 134832.00000 537.91800
1987 556287.00000 146284.00000 588.00700
1988 571618.00000 158511.00000 641.65600
1989 587672.00000 171354.00000 698.79500
1990 693809.00000 185138.00000 759.24700
1991 619958.00000 199903.00000 822.69000
1992 636045.00000 215668.00000 888.61400
1993 651997.00000 232432.00000 956.27200
1994 667737.00000 250132.00000 1024.61000
1995 683123.00000 268745.00000 1092.20000

 

ALTERNATIVE 2

NUMBER OF DOCTORS NOMINAL INCOME PHYSICIAN PRICES

 

1979 520631.00000 56326.30000 279-35900
1980 559425.00000 56501.70000 297.88400
1981 598357.00000 57133.80000 338.55700
1982 648901.00000 57955.10000 372.07600
1983 676034.00000 59746.20000 408.62000
1984 713258.00000 61885.60000 448.36200
1985 745574.00000 65165.80000 491.45000
1986 773939.00000 69454.10000 538.00400
1987 898890.00000 74720.20000 588.10300
1988 820633.00000 81016.20000 641.75800
1989 839982.00000 88295.40000 698.90400
1990 857151.00000 96621.60000 759.36300
1991 872864.00000 195933.00000 822.81100
1992 887631.00000 116178.00000 888.74100
11993 901840.00000 127288.00000 956.40500
1994 915827.00000 139156.00000 1024.75000
1995 929820.00000 151636.00000 1092.34000

 

65
FIGURE 5
Millions of Physicians, 1979-1995--Baseline and Two Freer-Entry

Alternatives

0.400 0.500 0.600 0.700 0.800 0.900 1.000
I====:::I===:===I=======|=======I=======I=======I

79+ BAIC I I I I .
I bA I C I I I I I
I BAI C I I I I
I HI I C I I I I
I 2 I C I I I I
54 . - - - AB' - - I - - - Ic- - - I - - - I - - - +
I IAB I I C I I I
I I A8 I I C I I I
I I A 8 I I C I I
I I A b I I I C I I
89 0 - - ' I - A -bl - - ' I - - - I -C- - I ' - - t
I I A 8 I I C I I
l I 1A I B I I C I I
I I AI 8 I I CI I
I I A 8 I I C I
94 - - - - I - - - IA- -5- I - - - I - - - Ic- - - .
I | I A BI I I C I
I==:====I===::==I=======Iz======|======:I:==:=:=I
0.400 0.500 0.600 0.700 0.000 0.900 1.000

LEGEND

Baseline Forecast
Alternative 1
Alternative 2

2 points at same number

)-
0

NOW
II II

66
FIGURE 6

Nominal Physician Income, 1979-1995--Baseline and Two Freer-Entry

Alternatives
50000 100000 150000 200000 250000 300000
I===:==:==I=:==::===I:===::===I=========I=========I
79 «CA 8 I I I I 0
IC, IA 8 I I I I I
IC A IS I I I I I
I c A BI I I I I
I C .AIb I I I I
84 . C I- - O 'A-B- - I- 1 '- IP - C I III - - - I a D - O .
I C I A I: I I I I
I C I A B I I I I
I C I ABI I I I
I C I A B I I I
59 . - - - c I - - - - I -AB - - I — - - - I - - - - .
I CI I A8 I I I
I IC I A8 I I
I I C I I A8 I I
I I C I I A8 I I
I I C I A B I
I=========I======:::I==::=====I==:=====:I:=:======I
50000 100000 150000 200000 250000 300000
LEGEND
A = Baseline Forecast
B = Alternative 1
C = Alternative 2

67
FIGURE 7

Physician Prices, 1979-1995--Baseline and Two Freer-Entry Alternatives

0
0 o
l 2 = 1

= u u c .-

= =

= u - u .-

= 2 .-

= u u u .-

.. .-
0 = ' P c = o
0 = 2 = 0
o ................. 0
1 = A = 1

= n u 2 u =

: =

= u . A =

= =

= . . 2 u .-

= A =

= g . - =
0 = a = 0
0 """"""""""" A H a. H H o
8 = = 8

= c o 2 u .-

= A .—

= - o c =

= 2 A .—

.. c c - .-

.. =

= c “C A - .-
u. = = U.
0 ||||||||||||||||||| 0
6 = 2 A = 6

= u u c =

= 2 A =

= c o - =

= 2 =

= u A a u z

= =

= 2 A - u .-
0 = = 0
0 ''''' 2 A '''''''''' O
4 = d 3 .0.

= A c c n .-

.. 2 A =

= — u . =

= a A .-

= 2 A . - . .—

.. =

= A u u a =
o 8 = 0
2 2

9 4 9 4
7 d 5 9

nu

LEGEND

A = Baseline Forecast

Alternative 1
C = Alternative 2

2

B:

2 points at same number

68
forecast, but much lower in the second. The physician fee component

is higher, however, by around 10 percent.

CHAPTER VI
CONCLUSIONS AND RECOMMENDATIONS
In this chapter, the conclusions of the work are summarized. Some
limitations of the model are pointed out, and recommendations are made
for further research.

Conclusions of the Research

 

In the introduction, three key questions were identified. This
work has sought answers to these questions by use of a three-equation
simulation model of the physician services market.

First, the pattern of future physician stock, earnings, and prices
has been described by the use of a simple model. The forecast is, of
course, sensititve to the economic assumptions in the simulated version
of the model. With assumptions based mainly on past experience, the
forecast shows a growth in physician prices from 1980-1995 averaging
17.2 percent per year, well over the six percent growth in the overall
Consumer Price Index. Physician income is expected to grow by 17.9'
percent per year over the same period, while the physician stock will
grow only about 2.0 percent per year. The model results show that
escalation in medical care prices will continue.

Second, the patterns of equilibrium physician stock and earnings
in the model were examined to determine whether a physician shortage
has existed in the past. Over the period 1960-1977, it was determined
that equilibrium physician stock has in fact not been attained. The
stock of physicians has been consistently much lower and physician
earnings consistently much higher than the equilibrium levels. There
are two possible reasons for the observed Shortage: 1) lag in price

response, 2) barriers to entry. In this case, observed prices were

69

70
were roughly equal to equilibrium prices. Therefore, the evidence

suggests that the lack of equilibrium in the market is due to barriers
to entry. These findings contrast with those of Hall, who found much
smaller gaps between optimal and actual physician stocks.

Third, given that there has been a physician shortage, what would
be the effect of greater freedom of entry? The simulation model was used
to reflect what would happen if the medical education sector expanded
to meet more of the demand for medical education. Results showed that
the number of doctors would be higher than in a baseline forecast.
Physician incomes would be the same or lower, although the added supply
of physicians comes at the expense of higher prices.

Implications for Policy

 

The question of what should be the policy toward medical education
involves several issues which cannot be addressed by the results of this
study. Nevertheless, the clear presence of barriers to entry into the
medical profession indicates the need for change.

While there has been considerable resistance to lowering standards
for admission to medical school on the part of the profession, it is
important to consider who has the right to set quality. The nation
might be better served by more physicians of lower average quality than
by a smaller number of "Cadillac model" doctors. One possiblity might
be a movement away from education-based standards for licensure for
medical practice and toward performance-based standards. The time re-
quired to obtain a medical education could be decreased. In Canada, less

than a third of students entering medical school have bachelor's degrees,

71
and considerable time is saved for specialized training.1 The need for

long internship and residency programs could be reappraised. Finally,
there is a need for more experimentation with different forms of medical
education.

Limitations of the Model and Recommendations for Further Research

 

The model of the physician services market presented here is a very
simple one, yet it has provided some useful results. Nevertheless, it
has several limitations which need to be remedied by further research.

One problem is that the whole area of policy toward medical edu-
cation has not been modeled except in the sense that policy is taken as
given. Policies toward medical schools have differed over the period of
the model, from substantial federal funding of construction and capita-
tion payments to lesser support in the present. In order to model policy
adequately, better data on governmental support (including state and
local support) of medical education are needed. The cost of supporting
a student in medical school is another variable for which data are not
available. With data on costs and a better way of quantifying policy,
better models of physician manpower could be constructed.

Second, more work needs to be done on the issue of foreign medical
graduates in this country. A survey of physician earnings in the donor
countries vs. physician earnings in the U.S., the specialty distribution
of the FMGs, and their average length of stay in this country would be

helpful. The number of foreign medical graduates permitted to immigrate

 

1 U.S. Department of Health, Education and Welfare, Health Manpower
Policy under National Health Insurance: The Canadian Experience
(thhington: HeaTthCRESOurces Administration, 1977.)

 

72
to the U.S. is, of course, a policy variable, and forecasts using the

model presented here cannot take this into account.

The results of this work show that, over the period 1960-1977,
there has been a shortage of physicians. The medical school sector,
even with substantial governmental aid, did not respond to demand
pressures. Strong barriers to entry exist for potential physicians,
and policies to break down those barriers will result in a greater

supply of health care.

APPENDICES

 

APPENDIX A

SOLUTION METHOD FOR EQUILIBRIUM VALUES 0F PHYSICIAN POPULATION. PRICES,
AND INCOME

As discussed in Chapter III, the market for physicians' services
was described by a three-equation model:
(1) PHYS/CPI = a0 + a IMDPOP + aZCOINS + afiEDPR/CPI + aeFAMINC/CPI
+ aSTECH/CPI

(2) Log(MDINC/CPI) = b0 + blLog(PHYS/CPI) + b2Log(POP)
+ b 3Log(NDOCS)

(3) DELNDOCS = co + c lMDINC/CPIt_6 + c2FAMINC/CPIt_6 + C3DOPt-6

In order to obtain equilibrium values of the endogenous variables--
PHYS, the physician CPI; NDOCS, the number of physicians; and MDINC,
median physician income--it was necessary to do a stationary simulation
of the model. Values of the exogenous variables in a given year had to
be held constant, and the equilibrium values of the other variables found.
This turned out to be a difficult problem and was not possible on the
computer equipment available. Therefore, a method was devised to do
a stationary simulation by hand. This method had five steps:

1) Set the rate of change in number of doctors in equation 3 to
zero and solve for the equilibrium value of MDINC, physician income.

2) Substitute the value of physician income into equation 2.
After collecting terms, this yields an expression for PHYS and NDOCS.

3) Substitute the expression for PHYS in equation 1 into the
result of step 2 above.

4) NDOCS appears in two places in this equation. The value of
NDOCS can, however, be found by iteration. Assume an initial value for

73

74
NDOCS and substitute into one expression for NDOCS. Solve the resulting
expression for NDOCS. Substitute the result into one expression and
solve again. Continue the iteration until it converges.
5) Use the equilibrium value of NDOCS to solve for PHYS. An
example of the procedure is given below.
The complete model is: ,
1) PHYS/CPI = -.13507 + (-.00204) MDPOP + .44904 COINS + .71384 MEDPR/CPI
+ .00388*FAMINC/CPI + (-.67542)* TECH/CPI
2) Log(MDINC/CPI) = -15.7472 + .7129 Log(PHYS/CPI) + 3.32902* Log(POP)
+ 1.02337 Log(FAMINC/CPI) -1.85644*Log(NDOCS)

3) NDOCSt - NDOCSt_1 = -30915.1 + 102.294 (MDINC/CPI)t_6 -520.997*

(FAMINC/CPI)t_6 + .2522* POPt_6

4) MDPOP = NDOCS/POP
To illustrate, let us solve the model for 1960. Values for the exo-
genous variables are:

Faminc = 5620

Cpi = 88.6

Medpr = 71.086

Tech = 11.09

Coins = .650

Pop = 180880

Faminc (-6) = 4167

Cpi (-6) = 80.5

P0p (-6) = 162391

Step 1: Assume NDOCSt - NDOCSt_1 = 0 in equilibrium.
Solve for MDINC.
0 = -30951.1 + 102.294 (MDINC/80.5)
-520.997 (4167/80.5) + .2522* 162391

16964.96 = 102.294 (MDINC/80.5)
Mdinc = 13322

75

Step 2: Substitute the value of MDINC into equation 2.
Log(13322/88.6) = -15.7472 + .7129 Log(PHYS/88.6)
+ 3.32902*Log(180880) + 1.02337*Log(5620/88.6)
-1.85644*Log(NDOCS)
(a) -23.7864 = .7129*Log(PHYS/88.6) - 1.85644Log(NDOCS)

Step 3: Substitute PHYS in equation 1 into the result of Step 2
Eq. 1 (PHYS/88.6) = .8911 - .00204(NDOCS/180880)
Substituting,

-23.7864 = .7129*Log(.8911 - .00204(NDOCS/180880))
-1.85644Log(NDOCS)

Step 4: Assume an initial value for NDOCS and iterate to a solution
NDOCS = 350434

Step 5: Use equilibrium NDOCS to solve for PHYS using expression (a)
above:
-23.7864 = .7129*Log(PHYS/88.6) - 1.85644*Log(350434)
PHYS = 78.6

APPENDIX B
DATA SOURCES

PHYS. Physician fee component of the Consumer Price Index,
Bureau of Labor Statistics

CPI. Consumer Price Index, Bureau of Labor Statistics.

COINS. Average coinsurance rate, percentage of total physician
services expenditures paid by the consumer out of pocket (and not by
private insurance or government programs). Computed by taking the
ratio of consumer direct physician expenditures and total physician
expenditures by consumers. Data supplied by Social Security Admini-
stration.

MEDPR. Expenditure-weighted index of hospital and drug prices.
CPI for drugs and prescriptions and CPI for hospital service Charges,
semiprivate room, weighted by expenditures in each category, supplied
by Social Security Administration.

FAMINC. Median family income. Current Population Survey.

TECH. Technology index. Non-labor hospital cost per adjusted
patient day. American Hospital Association.

MDINC. Median physician income, nonsalaried physicians. Medical
Economics annual surveys.

POP. Population, U.S. including armed forces overseas.

NDOCS. Total number of physicians in the U.S. Historical Statistics

of the U.S. and Statistical Abstraci, annual issues.

 

 

APPLIC. Number of applicants to medical schools. Journal of the

 

American Medical Association, annual education issues.

76

 

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BIBLIOGRAPHY

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Feldstein, Martin S. "Econometric Studies in Health Economics" in
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------- . "The Rising Price of Physicians' Services." Review of
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Flexner, Abraham. Medical Education in the United States and Canada.
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