The second essay studies how heterogeneous households respond to the fast rising housing prices through their life-cycle behaviors. Chinese housing market has been undergoing a rapid booming period since 1998, causing the house prices increasing significantly. As a result, households endured severe financial burdens to buy homes at price-to-income ratios of around six. Along with the rising house prices, household savings rate has been increasing consistently since 1998. Can the rising house prices be an important factor to explain the increase in household saving rate? This paper develops a life cycle dynastic model with endogenous choice on housing, coresidence and intergenerational transfer, then quantitatively analyze the effect of housing price on household saving. It shows that housing is an important motive for saving, and it accounts for about 35% of the increase in household savings rate. The housing situation affects households’ saving behavior through three channels. First, households are financially constrained due to the down payment requirement and they choose to limit their consumption in order to buy houses. Second, young adults live in their parents’ houses for a long time and save more intensively, since they get to pay less for the housing expenses under coresidence. Thirdly, older parents make large sum of intergeneration transfer in aid of the children’s housing purchase, indicating the housing affordability issue also has influence on old parents’ saving decisions.
In the second chapter I use administrative data on the ownership, management, and taxes for the universe of all firms in Ecuador to study the role of family management in firm dynamics and its implications for aggregate productivity. A novel finding I document is that family-managed firms grow half as quickly as externally-managed firms. This growth differential implies that family-managed firms account for half of employment, despite comprising 80% of firms. I construct a general equilibrium model of firm dynamics that is consistent with these facts. Entrepreneurs choose whether to utilize family members as managers or hire external managers. External managers allow firms to scale up production, but their efficiency is a affected due to contractual frictions. Changes in the contractual environment that lead to a drop in the presence of family-managed firms by half could increase output on the order of 6%, as firms that abandon family management enjoy rapid growth.
Abstract The first chapter discusses the policies that may have an impact on the long-run innovation capacity of developing economies. The existing literature emphasizes that the backward linkage of foreign-owned firms is a key to determining whether FDI is beneficial or detrimental to a domestic economy. However, little empirical evidence has shown which aspects of FDI policies lead to a strong backward linkage between foreign-owned and domestic firms. This paper focuses on the foreign ownership structure of these foreign-owned firms. I show that joint ventures (i.e, firms with 1%-99% foreign share) have stronger backward linkages than MNC affiliates (i.e, firms with 100% foreign share) with domestic firms. I also find that the differences in backward linkages are strong enough to translate into a positive correlation between domestic innovation and the density of joint ventures and a negative correlation between domestic innovation and the density of MNC affiliates. Finally, I find that the channel through which foreign ownership structure affects domestic innovation raises innovation TFP in domestic firms. My results suggest that policies that affect the foreign ownership structure of foreign-owned firms could have a persistent effect on domestic innovation because they shift the comparative advantage of an developing economy towards the innovation sector in the long run.
Abstract The second chapter provides a unified theory to study what causes the divergence in economic growth of developing economies and how the innovation sector emerges in the developing countries. I show that open developing economies become trapped at the middle-income level because they tend not to specialize in sectors that generate spillover or factor accumulation (the innovation sector). Using a dynamic Heckscher-Ohlin (H-O) model, I show that the fast growth of developing economies tends to end before they can fully catch up with the developed world, and the innovation sector will not operate in the developing countries. However, the successful growth stories of Korea and Taiwan challenge this view. In order to explore the economic miracle that happened in Korea and Taiwan, I generalize a dynamic Heckscher-Ohlin (H-O) model by introducing technology adoption and explore how it generates spillovers to domestic innovation. I show that countries with policies that encourage technology adoption will benefit most from FDI: in addition to the fact that foreign technology raises productivity in the host country, the demand for skilled labor to adopt these technologies raises the education level in equilibrium, which benefits domestic innovation and leads to catch-up in the long run.
Chapter two studies macroeconomic implications of a higher cost of health services faced by the unemployed which arise because 1) workers lose access to ESHI when they leave their jobs and 2) the uninsured face inflated health care prices. First, I provide evidence suggesting that the cost of health services for the privately insured is about 50% lower than for the uninsured. Second, I quantify the effects of higher cost of health services for the unemployed in the Lucas and Prescott (1974) island model extended to allow the workers to pay an extra cost of health services contingent on their employment status. Calibration procedure uses the differences between costs of health services for the privately insured and uninsured inferred from the data as a gap between costs of health services for the employed and unemployed. Quantitative results show that equalizing these costs across workers increases labor productivity by 1.2% and unemployment rate by 1.5 percentage points. The increased unemployment dominates quantitatively leading to a decrease in aggregate output by 0.26%.
The field of behavioral economics explores the ways in which individuals make choices under uncertainty, in part, by examining the role that risk attitudes play in a person’s efforts to maximize their own utility. This thesis aims to contribute to the body of economic literature regarding risk attitudes by first evaluating the traditional economic method for discerning risk coefficients by examining whether students provide reasonable answers to lottery questions. Second, the answers of reasonable respondents are subject to our economic model using the CRRA utility function in which Python code is used to make predictions of the risk coefficients of respondents via a two-step regression procedure. Lastly, the degree to which the economic model provides a good fit for the lottery answers given by reasonable respondents is discerned. The most notable findings of the study are as follows. College students had extreme difficulty in understanding lottery questions of this sort, with Medical and Life Science majors struggling significantly more than both Business and Engineering majors. Additionally, gender was correlated with estimated risk coefficients, with females being more risk-loving relative to males. Lastly, in regards to the model’s goodness of fit when evaluating potential losses, the expected utility model involving choice under uncertainty was consistent with the behavior of progressives and moderates but inconsistent with the behavior of conservatives.
One of the most pressing questions in economics is “why are some countries richer than others?” One methodology designed to help answer the question is known as “Development Accounting,” a framework that organizes the determinants of income into two categories: differences in inputs and differences in efficiency. The objective of our work is to study to what extent differences in the levels of pollution can help explain income differences across countries. To do this, we adjusted a factor-only model to allow us to enter PM2.5, a measure of pollution that tracks the concentration of fine particulate matter in the air and looked to see if the model’s predictive power improved. We ultimately find that we can improve the model’s success in predicting GDP by .5 - 6%. Thus, pollution is unlikely to be a major force in understanding cross-country income differences, but it can be used with other economic factors to potentially magnify its impact with other additions in the future.
Using the Development Accounting methodology specified in Caselli (2004), we investigate the potential of PM2.5, a measure of pollution, as an explanation of cross-country differences in GDP using available Macroeconomic data from the Penn World Table and the WHO. We find that the addition of PM2.5 makes improvements to the model within the expectations of the literature. This adjustment shows promise for use in cooperation with other, more potent economic factors.