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Essays on Impact Evaluation in Labor and Development Economics
[Thesis]
Christensen, Garret Smyth
Miguel, Edward
UC Berkeley
2011
UC Berkeley
2011
This dissertation studies examples of applied econometrics for causal inference in labor and development economics. One of the fundamental problems in applied fields of economics is causal inference. Merely observing that event B occurred after event A is not enough to claim that A caused B. The field of economics, and the social sciences in general, are limited by ethics and practicality in their ability to conduct randomized field experiments, the gold standard for causality in other fields. Several statistical methods have been devised to obtain causal estimates from "natural" or "quasi" experimental settings--settings where plausibly exogenous variation in a treatment effect of interest can be found and exploited to produce an unbiased estimate of causal effects. Some of these methods include panel data with fixed effects, nearest-neighbor matching, and regression discontinuity. This dissertation explores applications of these econometric methods, as well as an actual randomized controlled trial, in issues of labor and development economics.The first chapter uses panel data, and causal estimates are identified using a series of fixed effects to control for unmeasurable characteristics that could be correlated with both dependent and independent variables. The subject matter is the recruiting task of the United States military, which is the largest employer in the nation and spends over
Christensen, Garret Smyth
Miguel, Edward
UC Berkeley
مطالعه متن کتاب p
[Thesis]
276903
a
Y
