@mastersthesis {6108,
	title = {Three essays in labor economics and the economics of education},
	volume = {3634483},
	year = {2014},
	note = {Copyright - Copyright ProQuest, UMI Dissertations Publishing 2014 Last updated - 2014-10-25 First page - n/a},
	month = {2014},
	pages = {103},
	school = {Michigan State University},
	type = {Ph.D.},
	address = {East Lansing, MI},
	abstract = {In the first chapter of my dissertation, I examine the robustness of typical teacher quality measures to alternate ranking systems factoring in the dispersion of value-added. The typical measure used by researchers and school administrators to evaluate teachers is based on how the students{\textquoteright} achievement increases after being exposed to the teacher, or based on the teacher{\textquoteright}s {\textquoteleft}{\textquoteleft}value-added{\textquoteright}{\textquoteright}. When teacher value-added is heterogeneous across her students, then the typically used measure reflects differences in the average value-added the teacher provides. However, researchers, administrators, and parents may care not just about the average value-added, but also its variance. Encouragingly, ranking systems factoring in the dispersion produce similar rankings as the ranking system based only on the mean. In the second chapter, I examine the effect of measurement error in the dependent variable on quantile regression, because unlike OLS regression, even classical measurement error can generate bias. I examine the pattern and size of the bias using both simulation and an empirical example. The simulations indicate that classical error can cause bias and that non-classical measurement error, particularly heteroskedastic measurement error, has the potential to produce substantial bias. Using restricted access Health and Retirement Study data containing matched IRS W-2 earnings records, I examine whether estimates of the returns to education statistically differ using a precisely measured and mismeasured earnings variable. I find that returns to education are over-stated by roughly 1 percentage point at the median and 75th percentile using earnings reported by survey respondents. In the third chapter, my coauthors and I investigate how the precision and stability of a teacher{\textquoteright}s value-added estimate relates to student characteristics. We find that the year-to-year stability of teacher value-added estimates can depend on the previous achievement level of a teacher{\textquoteright}s students. The stability level of the estimates are typically 25\% to more than 50\% larger for teachers serving initially higher performing students. We offer a policy simulation demonstrating that teachers who serve low-achieving students may be differentially likely to be the recipient of sanctions in a high stakes policy based on value-added estimates.},
	keywords = {Demographics, Employment and Labor Force, Methodology, Public Policy, Social Security},
	url = {http://proxy.lib.umich.edu/login?url=http://search.proquest.com/docview/1612354970?accountid=14667http://mgetit.lib.umich.edu/?ctx_ver=Z39.88-2004\&ctx_enc=info:ofi/enc:UTF-8\&rfr_id=info:sid/Dissertations+\%26+Theses+\%40+CIC+Institutions\&rft_val_fmt=info:of},
	author = {Stacy, Brian}
}
