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Title: Essays in Local Labor Economics
Citation Type: Dissertation/Thesis
Publication Year: 2014
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Abstract: This dissertation consists of three independent chapters. Chapter 1 examines the determinants and welfare implications of the increased geographic of workers by skill from 1980 to 2000. I estimate a structural spatial equilibrium model of local labor demand, housing supply, labor supply, and amenity levels. The estimates indicate that cross-city changes in Örmsídemands for high and low skill labor were the underlying forces driving the increase in geographic skill sorting. I Önd that the combined e§ects of changes in citiesíwages, rents, and endogenous amenities increased well-being in- equality between high school and college graduates by a signiÖcantly larger amount than would be suggested by the increase in the college wage gap alone. Chapter 2 examines the abilities of state and local governments to extract rent from private sector workers by charging high tax rates and paying government workers high wages. Using a spatial equilibrium model where private sector workers are free to migrate across government jurisdictions, I show that variation in areasíhousing supply elasticities di§erentially restrains governmentsíabilities to extract rent from private sector workers. Governments in less housing elastic areas can charge higher taxes without worry of shrinking their tax bases. I test the modelís predictions by using worker wage data from the CPS-MORG. I Önd the public-private sector wage gap is higher in areas with less elastic housing supplies. Chapter 3 studies the standard practice in regression analyses to allow for clustering in the error covariance matrix when an explanatory variable varies at a more aggregate level than the units of observation. However, the structure of the error covariance matrix may be more complex, with correlations not vanishing for units in di§erent clusters. I show that with equal-sized clusters, if the covariate of interest is randomly assigned at the cluster level, only accounting for non-zero covariances at the cluster level, and ignoring correlations between clusters as well as di§erences in within-cluster correlations, leads to valid conÖdence intervals. However, in the absence of random assignment of the covariates, ignoring general correlation structures may lead to biases in standard errors.
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Authors: Diamond, Rebecca, R
Institution: Harvard University
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Degree: Doctor of Philosophy in the subject of Economics
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Pages: 218
Data Collections: IPUMS USA
Topics: Labor Force and Occupational Structure, Other
Countries: United States