Wang, Yu2020-08-252020-08-252020-05https://hdl.handle.net/11299/215109University of Minnesota Ph.D. dissertation.May 2020. Major: Applied Economics. Advisor: Marc Bellemare. 1 computer file (PDF); vii, 137 pages.This dissertation consists of three essays regarding political economy and the theoretical discussion of two empirical methods. Chapter 2 (Essay 1) discusses how the introduction of local direct elections, by providing local information, facilitates the fulfillment of the meritocratic selection of local leaders. Using the Bayesian framework, this paper finds that because local residents, the voters, communicate with the local leader candidates of more times than upper officials do, local residents infer each local leader candidate’s virtue or capacity more accurately and precisely. This paper then shows that due to the higher accuracy, the expectation of the competence (a weighted average of virtue and capacity) of the elected local leader is higher than that of the appointed leader; due to the higher precision, the variance of the competence of the elected local leader is lower than that of the appointed leader. Chapter 3 (Essay 2) discusses the lagged IV method, namely using the lagged endogenous explanatory variable as its instrumental variable (IV). This paper starts with a conceptual framework, and then conducts the numerical analysis. It shows that when the lagged IV only violates the independence assumption, the lagged IV estimate is consistent, and has lower bias than the OLS estimate; however, when the lagged IV violates both the independence assumption and the exclusion restriction, the lagged IV estimate is inconsistent, and has much higher bias than the OLS estimate. The simulation results support the numerical analysis. Chapter 4 (Essay 3) discusses the spatially lagged IV method, namely using the spatially lagged endogenous explanatory variable, namely the spatial weighting matrix, as its instrumental variable (IV). This paper introduces the spatially local average treatment effect (SLATE) theorem, which consists of two key properties: the spatial independence assumption and the spatial exclusion restriction. This paper demonstrates that when the spatially lagged IV satisfies the spatial independence assumption and the spatial exclusion restriction, its estimate is unbiased and consistent. Even if the treatment has multiple waves of implementation, the spatially lagged IV is still valid.enElectionEndogeneityLagged IVPolitical SelectionSpatially Lagged IVThesis or Dissertation