|dc.description.abstract||In recent years much governmental and public attention has been focused on house foreclosures as they related to the recent recession. Housing spillovers can degrade neighborhood quality and depress property tax revenues, which are an important source of funding of local public goods such as public schools. It is my aim to study these spillover effects and to assess how the timing and number of foreclosures affect surrounding house values, and ultimately erode the tax base in Atlanta, Georgia.
Chapter 2 and Chapter 3 employ the same dataset to study the effects of house foreclosures. Chapter 2 uses cross-sectional data to examine the effect of foreclosures on subsequent home sales prices in 2008 by employing spatial models. Chapter 3 uses panel data (2000-2010) to study the effect of foreclosures on neighborhood property values in the city of Atlanta. The quasi-experiment methods, difference-in-differences (DID) model and propensity score matching (PSM) are employed and compared. A difference-in-differences model not only removes biases from comparisons between the treatment and control groups that could be the result from systematic differences, but also removes biases from comparisons over time in the treatment group that could be the result of trends. Like difference-in-differences method, propensity score matching removes the differences between treatment and control groups by matching treatment and control units based on a set of covariates.
Compared to the cross-sectional data, panel data has an advantage to reduce omitted variable problems by subtracting constant unobserved variables. However, using cross-sectional data, spatial models also help avoid omitted variable problems by controlling spatially correlated housing prices and spatially correlated errors.
Chapter 3 examines the impact of irrigation adoption on farmers’ cropping income, agricultural income and the total profit of agricultural products sold. It also examines income inequality using agriculture products sales value. This paper is the first attempt to use U.S. county level data to examine the 9 Southeast states’ irrigation impacts. Irrigation is often promoted as a technology that can increase crop production, improve agriculture income and alleviate poverty. However, irrigation is a relatively expensive technology for small-scale and poor farmers, which impedes their opportunities to adopt irrigation technology. Income inequality may increase due to adoption barriers. Thus, irrigation is suspected endogenous to farmers’ cropping income.
In this dissertation, addressing endogeneity problem is one interest. The endogeneity problems in Chapter 1 and Chapter 3 are caused by reverse causality. Because neighborhood house values depreciated by foreclosures may lead to more foreclosures, foreclosures may thus be endogenous to the sales price. Previous studies argue that it is hard to find an instrumental variable which is correlated with foreclosures but not correlated with the residuals of the hedonic price equation. The contributions of Chapter 1 include creating an innovative way to examine endogeneity through accounting for foreclosure timing and it also addresses the endogeneity of the spatially lagged dependent variable by using GS2SLS procedures. Chapter 3 deals with endogeneity with 2SLS regression. Because irrigation is a relatively expensive technology for small-scale farmers and poor farmers, it impedes their opportunities to adopt irrigation technology. Thus, irrigation is potentially endogenous to agricultural sales income.||en_US