Hiroyuki Kasahara

This study examines the identification of household preference from a micro-panel dataset andthe effects of the stock market collapse and the Zero-Lower Bound monetary policy on householdconsumption decisions during the 2007-2008 global financial crisis (GFC).In the first chapter, I propose a procedure for estimating the household utility function from amicro-panel dataset using the intertemporal Euler equation. Here, I demonstrate that the household utility function can be estimated accurately from a micro-panel dataset using the intertemporal Euler equation by taking into account the differences in the portfolio compositions of household savings across households. In addition, I construct a new household dynamic model in which the household stock-holding behavior is modeled by explicitly taking into account the hidden stock market participation cost pointed out in recent empirical studies as a potential explanation for the low stock market participation rate among households in the United States.In the second chapter, I explore the effects of the stock market collapse and the Zero-LowerBound monetary policy on household consumption decisions during the GFC. The huge drop in the stock market return and the decline in the risk-free rate due to the Zero-Lower Bound monetarypolicy triggered a large percentage decrease in the consumption of wealthy households in this period in the United States. Meanwhile, the consumption of households at the bottom part of the wealth distribution, which generally do not participate in the stock market, increased slightly in percentage due to the decline in the risk-free rate during the GFC in the United States. As a result, the stock market collapse and the Zero-Lower Bound monetary policy generated a substantial decrease in consumption inequality among households.In the third chapter, I estimate the heterogeneity in household preference by employing a combination of the extremum and nonparametric estimation methods and find significant heterogeneity in the preferences across households in the United States and Italy. This estimated heterogeneity in household preference can be used to explain the observed wealth distribution and the differences in career and investment choices across households in future research.

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Chapter 2 provides a tractable model that separates firms’ incentive problems and coordinationproblems during the initiation of collusion. In the Chilean pharmaceutical industry, firms colludethrough price leadership. Collusion gradually diffuses among markets: firms collusively raiseprices in a couple of markets per week. We propose a model of price leadership under the dynamic pricing game framework to incorporate the coordination problems by allowing firms’ beliefs about competitors’ conduct to be biased towards a competitive equilibrium. As firms observe supracompetitive prices, they adaptively learn that competitors are willing to collude. We show that gradualism is explained by the heterogeneous market characteristics as well as firms’ learning to coordinate.Chapter 3 develops the likelihood-ratio based test of the null hypothesis of a m₀-componentmodel against an alternative of (m₀+1)-component model in the normal mixture panel regression.I show that the normal mixture panel regression does not suffer from the Fisher Information matrixdegeneracy under the reparameterization proposed in Kasahara and Shimotsu [89]. As a result, the likelihood ratio test statistic can be approximated by a local quadratic expansion of squares and products of the reparameterized parameters. Moreover, I obtain the data-driven penalty function via computational experiments to attend to the unbounded likelihood ratio. In addition, I apply the test to random coefficient Cobb-Douglas production function estimation following the framework of Gandhi et al. [63] and Kasahara and Shimotsu [90]. The empirical findings suggest evidence of heterogeneous production technology beyond the Hicks-neutral technology factor.Chapter 4 develops a modified expectation-maximization(EM) algorithm to incorporate unobservedheterogeneity for the dynamic discrete choice model that does not require the finite dependenceproperty. Following the Euler Equation(EE) representation of dynamic discrete decision problems, we provide an alternative conditional choice probability (CCP) value function representationthat relies only on the CCP of one action. We illustrate the computational gains with MonteCarlo simulations.

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This dissertation combines three empirical papers in International Trade and Labor Economics.The first chapter uses Ukrainian firm-level data to examine whether firms induced to import from the European Union by trade liberalizationupgrade the quality of goods that they export. I use the instrumental variable regression to address the endogeneity of firms' import status.Obtained results confirm that new importers substantially improved the quality of products sold abroad.After splitting the sample into heterogeneous and homogeneous good producers, I found that the effect of importing is strong and statistically significant for the former and insignificant for the latter. The obtained results indicate that trade liberalization can lead to considerable quality improvement in industries with the large scope for quality differentiation.In the second chapter, I analyze patterns of employment adjustment using a rich panel ofUkrainian manufacturing firms. The data suggest that manufacturing plants operate under considerable firing costs imposed by the employment protection legislation.Moreover, I find that privatized enterprises, similarly to public firms, are more constraint in making their employment adjustment decisions than new private firms. I estimate a model of dynamic labor demand with a flexible adjustment cost function.Obtained results indicate the presence of substantial firing costs in Ukrainian manufacturing.These costs are considerably larger for public and privatized enterprises.The third chapter uses data from the Census, ACS and CPS to document that a large part of the long-run reallocation of labor from the goods to the service sector in the U.S. took place within narrowly defined groups of workers. In particular, sectoral reallocation reflects a labor market trend that is distinct from the automatization of the goods sector and the increase in female labor force participation. We use this result to empirically evaluate the central prediction of job-search theory with on-the-job search: that there is an intrinsic link between the earnings structure and the rates at which employed workers change jobs.We find robust evidence that the earnings distribution in the service sector became more dispersed relative to the goods sector when the rate at which workers flew into the service sector rose.

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This dissertation studies the impact of international trade on the Indonesia labor market. The first chapter investigates how task trading induce workers to change jobs. To understand the link between international trade and workers' occupation choices, I propose a general equilibrium model with heterogeneous workers self-selecting into different tasks according to their skill-specific comparative advantage, individual task-specific abilities and task prices. Task outsourcing from foreign countries acts as a demand shock that influences workers' occupation decisions through changing task prices. The model predicts that occupational employments shifts with foreign task demand. I use Indonesian data to estimate this effect. The main finding is that during the post-opening period (2002-2006), growth in mining goods demanded by foreign countries induced workers to move into manual jobs. The second chapter uses the Indonesia plant level data to examine how importing intermediate goods affects the demand for highly educated workers within and across production and non-production occupations categories. We estimate a model of importing and skill-biased technological change in which selection into importing arises due to unobservable heterogenous returns from importing. Both instrumental variable regression and marginal treatment effect estimates confirm that importing has substantially increased the relative demand for educated workers within each occupation. In contrast, we do not consistently estimate a significant impact of importing on the relative demand for non-production workers. The last chapter examines the relationship between trading dynamics of plants and the aggregate skill demand at different margins (reallocation of workers across plants versus the skill composition changes within plants). We find that plants that switched from domestic to trade grew in employment shares. This growth was skill biased for plants that started importing, but not for plants that started exporting. Consequently, the growth in size and increase in the skill intensities of the plants that switched from non-importing to importing increase in the aggregate demand for skilled workers. Plants that stopped importing or exporting laid off workers, more unskilled workers are involved in this reduction. The plants that continue trading grew in size, and the growth was not bias toward workers of any skill type. Given that always-trading plants are most skill intensive, their growth increase the aggregate skill demand.

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This dissertation consists of three chapters. Chapter 1 investigates how returns to education are related to occupation choices. Specifically, I investigate the returns to attending a two-year college and a four-year college and how these returns to education differ from a blue-collar occupation to a white-collar occupation. To address the endogenous education and occupation choices, I use a finite mixture model. I show how the finite mixture model can be nonparametrically identified by using test scores and variations in wages across occupations over time. Using data taken from the National Longitudinal Survey of Youth (NLSY) 1979, I estimate a parametrically specified model and find that returns to education are occupation specific. Specifically, a two-year college attendance enhances blue-collar wages by 24% and white-collar wages by 17% while a four-year college attendance increases blue-collar wages by 23% and white-collar wages by 30%.Chapter 2 and Chapter 3 study how to perform econometric analysis with complex survey data, which is widely used in large scale surveys. Although it is attractive in terms of sampling costs, it introduces complication in statistical analysis, when compared with the simple random sampling method. In Chapter 2, I study the properties of M-estimators when they are used with complex survey data. To undo the over- and under-representation effects of the complex survey design, it is typically necessary to use the survey weight in M-estimation. I establish the consistency and asymptotic normality of the weighted M-estimators. I also discuss how to estimate the asymptotic covariance matrix of the M-estimators. Further, I demonstrate serious consequences of ignoring the survey design in M-estimation and inference based on it. In Chapter 3, I consider specification testing with complex survey data. Specifically, I modify the standard m-testing framework to propose a new method to test if a given model is correct for a subpopulation. The proposed test has advantages over the standard m-testing, takingaccount of likely heterogeneity of subpopulation distributions. All of the three chapters deal with heterogeneity of subpopulation distributions, whether or not the subpopulation identity is known (Chapter 2 and Chapter 3) and unknown (Chapter 1).

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