Chapter 1 analyzes how principals and teachers react when principals are given complete control over teacher retention decisions after a district-level restructuring policy has laid off all untenured teachers. I examine three questions related to increases in principal autonomy: Was there a change in the probability of an untenured teacher returning to the same school the next year? If so, were higher-value-added teachers retained at a higher rate? Lastly, what effect did the restructuring of staffs have on student performance? A conceptual framework based on Bayesian updating employer learning predicts that in the year of the layoffs fewer teachers would be retained in their position with the more-senior, untenured teachers being the least likely to be retained. Using a triple-difference identification strategy on data collected from the Rockford Public School District (RPS) and Illinois State Board of Education, I find that fewer untenured teachers were retained in the year of the restructuring with an inverse relationship between untenured teacher experience and retention rates. Additionally, there is suggestive evidence of an inverse relationship between value-added scores and retention rates. Finally, I find evidence that the policy had a negative impact on student test performance. A 10 percentage point increase in untenured teachers at a school in the year of the layoffs is associated with 0.02 - 0.04 standard deviations lower student test scores in math two years after the policy.Chapter 2 examines whether layoff policies, like the one outlined in Chapter 1, affect teacher effort. I utilize a difference-in-difference identification strategy to estimate the effect of the RPS layoff announcement of this policy on untenured teacher effort. Both ordinary least squares and Poisson quasi-maximum likelihood estimation methods find that the there is little impact on the total teacher absences after the layoff announcement. However, when separated into weeks, I find that untenured teachers took, on average, 0.08 fewer absences in the week immediately following the layoff announcement. Additionally, looking at the daily-level, in the Friday after the layoff announcement teachers took, on average, 0.04 more absences. I hypothesize that this initial negative effect is due to lower teacher morale but the initial shock to morale dissipates and teachers change their behavior to apply more effort to attempt to win their jobs back. These results indicate that teachers are sensitive to policies regarding their job security, but their initial response to the policies fade quickly.Chapter 3 discusses the impact of charter schools on property values. While prior research has found clear impacts of schools and school quality on property values, little is known about whether charter schools have similar effects. Using sale price data for residential properties in Los Angeles County from 2008 to 2011 we estimate the neighborhood level impact of charter schools on housing prices. Using an identification strategy that relies on census block fixed-effects and variation in charter penetration over time, we find little evidence that the availability of a charter school affects housing prices on average. However, we do find that when restricting to districts other than Los Angeles Unified and counting only charter schools located in the same school district as the household, housing prices fall in response to an increase in nearby charter penetration.
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