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Thesis (Ph. D.)--University of Hawaii at Manoa, 1994. / Includes bibliographical references (leaves 135-142). / Microfiche. / vii, 142 leaves, bound ill. 29 cm

Thesis (Ph. D.)--Washington State University, August 2008. / Includes bibliographical references.

Thesis (PhD.)--Beijing hang kong hang tian da xue, 1991. / Includes bibliographical references (p. 192-199)

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Over the past decade there has been a number of innovations in the estimation of input demand equations. In particular, ways of incorporating the hypothesis of rational expectations into empirical models of the firm have been developed and improved upon. This research agenda was perhaps inspired by the Lucas critique of econometric policy evaluation, which suggested that econometric models which did not explicitly take account of how expectations of the future affect current behaviour would give misleading results regarding the possible effects of various government policies. Lucas specifically directed part of his critique at empirical models of business investment, which had been used previously in the assessment of tax policies designed to affect investment. This thesis has a dual purpose. First, two distinct models of input demand are estimated with Canadian manufacturing data. Each of the models incorporates to some degree the hypothesis of rational expectations, but the specifications of technology differ. Neither of these models, to our knowledge, has been estimated with Canadian data. We are interested in whether either model explains well the behaviour of the Canadian manufacturing sector, and in how the results compare with the (few) U.S. applications of this type of model. The second purpose is to use the results of these models in simulations to assess the effect of changes to the after-tax rental rate of capital on investment and employment in manufacturing. While there have been studies in Canada (and elsewhere) that attempt to calculate the effects of various tax policies on investment, most studies were done prior to the innovation of techniques in estimating models with rational expectations. This thesis is able to examine the effects of a particular change while remaining immune to the Lucas critique. If the modelling of expectations is correct, this could not only improve the reliability of the estimates, but also give some indication of the empirical importance of the Lucas critique. The results can be summarized as follows. The two models give very different estimates of price elasticities of demand for capital and labour, even though they are similar in many respects and are estimated with a common data set. It is also the case that their estimates of the effects of temporary and permanent changes to the rental rate are different. Adjusting the reduced form parameters of the input demand equations to account for changes in tax policy regimes alters the results to a significant degree, suggesting that the explicit modelling of expectations matters in an empirically relevant sense. However, these effects are in opposite directions for the two models considered here. All this suggests that more research is required into the relationship between expectations of future policy and investment behaviour. / Arts, Faculty of / Vancouver School of Economics / Graduate

Thesis advisor: Arthur Lewbel / In my doctoral research, I developed econometric estimators with strong applications in analysis of heterogeneous consumer demand. The first chapter develops an estimator for grouped patterns of heterogeneity in an approximately sparse setting. This setting is used to estimate demand shocks, competition sets and own-price elasticities for different groups of consumers. The second chapter, which is joint work with Stefan Hoderlein and Alexander Meister, develops a nonparametric estimator of the marginal effects in a panel data even if there are only a small number of time periods. This is used to estimate the heterogeneous marginal effects of increasing income on consumption of junk food. The third chapter, which is joint work with Stefan Hoderlein and Solvejg Wewal, is the first difference-in-differences model for binary choice outcome variables when treatment effects are heterogeneous. We apply this estimator to examine the heterogeneous effects of a soda tax. Chapter 1: ``Approximately Sparse Models and Methods with Grouped Patterns of Heterogeneity with an Application to Consumer Demand" introduces post-Lasso methods to time-varying grouped patterns of heterogeneity in linear panel data models with heterogeneous coefficients. Group membership is left unrestricted and the model is approximately sparse, meaning the conditional expectation of the variables given the covariates can be well-approximated by a subset of the variables whose identities may be unknown. I estimate the parameters of the model using a “grouped fixed-effects” estimator that minimizes a post-Lasso least-squares criterion with respect to all possible groupings of the cross-sectional units. I provide conditions under which the estimator is consistent as both dimensions of the panel tend to infinity and provide inference methods. Under reasonable assumptions, applying this estimator to a consumer demand application allows me to partition consumers into groups, deal with price endogeneity without instrumental variables, estimate demand shocks, and identify compliments and substitutes for each group. I then use this estimator to estimate demand for soda by identifying different groups' competition sets as well as demand shocks using Homescan data. Chapter 2: In ``A Panel Data Estimator for the Distribution and Quantiles of Marginal Effects in Nonlinear Structural Models with an Application to the Demand for Junk Food", we propose a framework to estimate the distribution of marginal effects in a general class of structural models that allow for arbitrary smooth nonlinearities, high dimensional heterogeneity, and unrestricted correlation between the persistent components of this heterogeneity and all covariates. The main idea is to form a derivative dependent variable using two periods of the panel, and use differences in outcome variables of nearby subpopulations to obtain the distribution of marginal effects. We establish constructive nonparametric identification for the population of ``stayers" (Chamberlain 1982), and show generic non-identification for the ``movers". We propose natural semiparametric sample counterparts estimators, and establish that they achieve the optimal (minimax) rate. Moreover, we analyze their behavior through a Monte-Carlo study, and showcase the importance of allowing for nonlinearities and correlated heterogeneity through an application to demand for junk food. In this application, we establish profound differences in marginal income effects between poor and wealthy households, which may partially explain health issues faced by the less privileged population. Chapter 3: In ``A Binary Choice Difference-in-Differences Model with Heterogeneous Treatment Effects and an Application on Soda Taxes", we answer how should Differences-in-Differences be implemented when outcomes are binary and we expect heterogeneous effects. The scope for applications is clearly vast, including labor force participation, product purchase decisions, enrollment in health insurance and much more. However, assumptions necessary to measure heterogeneous effects in classic Difference-in-Difference models break down with a binary dependent variable. We propose a model with a nonparametric random coefficient formulation that allows for heterogeneous treatment effects with a binary dependent variable. We provide identification of the average treatment effect on the treated (ATT) along with identification of the joint distribution of the actual and counterfactual latent outcome variable in the treatment group which allows us to show the heterogenous treatment effects. We suggest an estimator for the treatment effects and evaluate its finite sample properties with the help of Monte Carlo simulations. We further provide extensions that allow for more flexible empirical applications, such as including covariates. We apply our estimator to analyze the effect of a soft drink tax on consumer's likelihood to consume soda and find heterogeneous effects. The tax reduced the likelihood of consumption for the most consumers but not for those who were most likely to be consuming previously. / Thesis (PhD) — Boston College, 2020. / Submitted to: Boston College. Graduate School of Arts and Sciences. / Discipline: Economics.

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The dissertation has three main chapters on product quality innovation. First, we compare innovation effort and social welfare between monopoly, duopoly, and the social planner in a dynamic model with quality dependent on a continuous know-how stock. The technology frontier--the largest reachable know-how socks--does not always positively depend on competitiveness, i.e. a duopoly may technologically surpass the social planner. However, social welfare is always positively tied to competitiveness. Second, with a general equilibrium model, we derive a relative price function expressing productivity and quality effects, and develop a method for inferring relative quality changes. An application to services versus goods of the US from 1946-2006 provides evidence on aggregate quality changes and suggests us to incorporate quality variations when explaining relative prices. Third, we build a two-product model where productivity changes lead to reallocations of labor between quantity production and quality innovation. The correlation between relative productivity and relative quality is negative for low-range substitutability and positive for medium-range substitutability between two products. Looking at services versus goods of the US, the correlation is negative and productivity-driven quality can play a significant role in general quality development.

The objective of this study is to evaluate the changes in import and export demand in China and India on the United States and global agriculture in 2018. A spatial equilibrium model is developed to optimize production and trade in China, India, and other major importing and exporting regions in the world. This research focuses on four primary crops: wheat, com, rice and soybeans. In the model China and India are divided into 31 and 14 producing and consuming regions, respectively. The model also includes five exporting countries and ten importing countries/regions. The results indicate that India will be able to stay largely self-sufficient in 2018 and China will increase its soybean and com imports to meet rising domestic demand. The research also gives perspectives on production and trade in the United States and other major exporting and importing countries.