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Author: Olga Voyteshenko Livingston
Publisher:
ISBN:
Category : Econometrics
Languages : en
Pages : 180
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Two essays are focused on semiparametric econometric methods. The first essay investigates applicability of the smooth back tting estimator (SBE) to statistical analysis of residential energy consumption. The second essay attempts to incorporate additivity restrictions into semiparametric stochastic frontier estimation. The procedure described in the first study is used to estimate the directional regressions for each of the additive components. These estimates are used as a pilot for stochastic frontier estimation. The essay contains an empirical study of power generating units in the US.
Author: Olga Voyteshenko Livingston
Publisher:
ISBN:
Category : Econometrics
Languages : en
Pages : 180
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Book Description
Two essays are focused on semiparametric econometric methods. The first essay investigates applicability of the smooth back tting estimator (SBE) to statistical analysis of residential energy consumption. The second essay attempts to incorporate additivity restrictions into semiparametric stochastic frontier estimation. The procedure described in the first study is used to estimate the directional regressions for each of the additive components. These estimates are used as a pilot for stochastic frontier estimation. The essay contains an empirical study of power generating units in the US.
Author: Martin Burda
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Author: Christoph Rothe
Publisher:
ISBN:
Category :
Languages : en
Pages : 102
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Author: Hyungtaik Ahn
Publisher:
ISBN:
Category :
Languages : en
Pages : 402
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Author: Tomás Andrés Rau Binder
Publisher:
ISBN: 9780549168775
Category :
Languages : en
Pages : 162
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This dissertation consists of two essays. In the first essay I propose a new class of flexible microeconometric models that incorporates endogenous regressors and sorting. Existing models, including Garen's (1984) correlated random coefficients model, and Newey, Powell, and Vella's (1999) fully-flexible model with an additive error, can be derived from a structural equation with unobserved heterogeneity by imposing homogeneity and constancy assumptions on the first and second derivatives. I consider a less restrictive model that imposes homogeneity assumptions on the second partial derivative of the structural equation. Assuming the existence of suitable instrumental variables, the model can be estimated using a generalized control function approach. I consider an application to the estimation of the returns to education in Chile, exploiting variation across regions and cohorts in educational infrastructure and compulsory schooling laws. Using penalized spline functions to approximate the components of the average structural response function, I find that the local average returns to schooling are typically under-estimated by flexible models that ignore the endogeneity of schooling. I also find limited evidence of comparative advantage bias in the returns to certain levels of education.
Author: Eduardo García Echeverri
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ISBN:
Category : Social mobility
Languages : en
Pages : 0
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"This dissertation consists of three chapters on nonparametric and semiparametric econometrics. Chapter 1 introduces the estimators used in the empirical applications of Chapter 2 and therefore should be read first. Chapter 3 is independent from the first two. The first chapter introduces a measure of intergenerational social mobility based on [phi]-divergences. The measure can be decomposed to study mobility in population subgroups of interest and can be used to describe mobility of multiple outcome variables across an arbitrary number of generations, unlike most indicators in the literature. The measure also fully controls for marginal distributions, meaning it is not affected by income growth or changes in income inequality. I propose two estimators for the measure: a non-parametric estimator and an estimator based on the mobility matrix. I provide conditions under which these estimators are n-consistent and asymptotically normal. In the second chapter, I use a specific [phi]-divergence (the Hellinger distance) to measure multidimensional social mobility in the USA and Germany. For this purpose, I use the Panel Study of Income Dynamics (PSID), the German Socio-Economic Panel (SOEP), and US administrative tax data. The measure reveals lower income and health mobility in the USA than Germany, but the opposite for educational mobility. It also shows income mobility for both countries is lowest in the tails of the parental income distribution and greatest in the centre. This inverted U-pattern is more pronounced in the USA. Most of these empirical findings for population subgroups are hidden to the existing indicators in the literature. Chapter 3 introduces a Low CPU Cost Semiparametric (LCS) estimator for linear single index models. The LCS estimator significantly reduces estimation time when compared to the standard semiparametric estimator in Ichimura (1993). It does so by more than 90% in medium sample sizes. Moreover, it makes estimation feasible in a regular PC when the sample size exceeds 10,000 observations. We provide conditions for consistency and asymptotic normality of the LCS estimator based on spline function theory. In our empirical application, we study determinants of expenditures in vocational rehabilitation (VR) programs using the RSA-911 data, containing information on more than 900,000 workers with disabilities. We find that minorities such as African Americans, Hispanic or females have lower expenditures in VR programs. On the other hand, expenditure is greater for more educated workers."--Pages viii-ix.
Author: Paul Schrimpf
Publisher:
ISBN:
Category :
Languages : en
Pages : 146
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This dissertation is a collection of three independent essays in theoretical and applied econometrics. The first chapter analyzes dynamic games with continuous states and controls. There are two main contributions. First, we give conditions under which the payoff function is nonparametrically identified by the observed distribution of states and controls. The identification conditions are fairly general and can be expected to hold in many potential applications. The key identifying restrictions include that one of the partial derivatives of the payoff function is known and that there is some component of the state space that enters the policy function, but not the payoff function directly. The second contribution of the first chapter is to propose a two-step semiparametric estimator for the model. In the first step the transition densities and policy function are estimated nonparametrically. In the second step, the parameters of the payoff function are estimated from the optimality conditions of the model. We give high-level conditions on the first step nonparametric estimates for the parameter estimates to be consistent and parameters to be v/fn-asymptotically normal. Finally, we show that a kernel based estimator satisfies these conditions. The second chapter, which is coauthored with Liran Einav and Amy Finkelstein, analyzes the welfare cost of adverse selection in the U.K. annuity market. We develop a model of annuity contract choice and estimate it using data from the U.K. annuity market. The model allows for private information about mortality risk as well as heterogeneity in preferences over different contract options. We focus on the choice of length of guarantee among individuals who are required to buy annuities. The results suggest that asymmetric information along the guarantee margin reduces welfare relative to a first best symmetric information benchmark by about 2 percent of annuitized wealth. We also find that by requiring that individuals choose the longest guarantee period allowed, mandates could achieve the first-best allocation. The third chapter develops a test for the exogeneity assumptions of classical factor models based on the fixed interactive effects estimator of Bai (2005). The exact form of the test is given for simple linear models. Simulations are used to asses the test's performance. The application of the test to more complicated models is also considered. The test is applied to a model of education as an example.
Author: Sokbae Lee
Publisher:
ISBN:
Category : Econometrics
Languages : en
Pages : 334
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Author: Hongjun Li
Publisher:
ISBN:
Category :
Languages : en
Pages :
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This dissertation aims at investigating the theory and application of semiparametric econometrics. I first inspect the selection of optimal bandwidth using the cross-validation method for the kernel estimation of cumulative distribution/survivor functions. Then, I analyze the determination of the number of factors with the methods of principal component and information criteria. I also show the application of semiparametric methods to "purchasing power parity" puzzle. Firstly, I propose a data-driven least squares cross-validation method to optimally select smoothing parameters for the nonparametric estimation of cumulative distribution/ survivor functions. The general multivariate covariates can be continuous, discrete/ordered categorical or a mix of either. I establish the asymptotic optimality of least squares cross-validation method. Also, I show that the estimators of cumulative distribution/survivor functions using the smoothing parameters selected by the proposed method is asymptotically normally distributed. Monte Carlo simulation verifies the finite-sample properties of the least squares cross-validation method. Secondly, I provide some discussions on the econometric theory for factor models of large dimensions where the number of factors (r) is allowed to increase as the two dimensions, cross-sections (N) and time dimensions (T) increase. I mainly focus on the determination of the number of factors. I extend the existing panel criteria to high dimension case where r may be increasing with N or T. I show that the number of factors can be consistently estimated using the criteria. Also, Monte-Carlo simulation demonstrates the finite sample properties of the proposed estimating method. Lastly, I consider an empirical application of semiparametric econometrics to the problem of purchasing power parity (hereafter PPP) hypothesis test. Traditional linear cointegration tests of PPP hypothesis often lead to rejection of the PPP hypothesis. More recent studies allowing for some sort of nonlinearity in econometric modelings suggest mixed results and leave this problem as an unresolved issue. Therefore, I analyze PPP hypothesis within a semiparametric framework using the varying coefficient model with integrated variables, which can capture the nonlinearity of the economic structures. Applying the semiparametric functional cointegration test method, I conduct the cointegration test of PPP hypothesis between U.S. and Canada, U.S. and Japan, and U.S. and U.K., respectively to test the PPP hypothesis. In contrast to the usual findings based on linear model PPP hypothesis testing, the semiparametric model based tests provide supporting evidence of the PPP hypothesis. The electronic version of this dissertation is accessible from http://hdl.handle.net/1969.1/152605
Author: Matthias Hagmann-von Arx
Publisher:
ISBN:
Category :
Languages : en
Pages : 129
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