Estimation in Partially Linear Single-Index Panel Data Models with Fixed Effects

In this paper, we consider semiparametric estimation in a partially linear single-index panel data model with fixed effects. Without taking the difference explicitly, we propose using a semiparametric minimum average variance estimation (SMAVE) based on a dummy-variable method to remove the fixed effects and obtain consistent estimators for both the parameters and the unknown link function. As both the cross section size and the time series length tend to infinity, we not only establish an asymptotically normal distribution for the estimators of the parameters in the single index and the linear component of the model, but also obtain an asymptotically normal distribution for the nonparametric local linear estimator of the unknown link function. The asymptotically normal distributions of the proposed estimators are similar to those obtained in the random effects case. In addition, we study several partially linear single-index dynamic panel data models. The methods and results are augmented by simulation studies and illustrated by an application to a cigarette-demand data set in the US from 1963-1992Fixed effects, local linear smoothing, panel data, semiparametric estimation, single-index models

Estimating distributions of potential outcomes using local instrumental variables with an application to changes in college enrollment and wage inequality

This paper extends the method of local instrumental variables developed by Heckman and Vytlacil (1999, 2001, 2005) to the estimation of not only means, but also distributions of potential outcomes. The newly developed method is illustrated by applying it to changes in college enrollment and wage inequality using data from the National Longitudinal Survey of Youth of 1979. Increases in college enrollment cause changes in the distribution of ability among college and high school graduates. This paper estimates a semiparametric selection model of schooling and wages to show that, for fixed skill prices, a 14% increase in college participation (analogous to the increase observed in the 1980s), reduces the college premium by 12% and increases the 90-10 percentile ratio among college graduates by 2%.

Estimating distributions of potential outcomes using local instrumental variables with an application to changes in college enrollment and wage inequality

This paper extends the method of local instrumental variables developed by Heckman and Vyt- lacil (1999, 2001, 2005) to the estimation of not only means, but also distributions of potential outcomes. The newly developed method is illustrated by applying it to changes in college enroll- ment and wage inequality using data from the National Longitudinal Survey of Youth of 1979. Increases in college enrollment cause changes in the distribution of ability among college and high school graduates. This paper estimates a semiparametric selection model of schooling and wages to show that, for fixed skill prices, a 14% increase in college participation (analogous to the increase observed in the 1980s), reduces the college premium by 12% and increases the 90-10 percentile ratio among college graduates by 2

Semi-Parametric Hedonic Models, and Empirical Comparison

Hedonic models have been widely used in the literature for valuation of non- market goods such as air quality. While the inclusion of air quality variables in hedonic models is common in applied work, there is not theoretical basis for defining the functional relation between air quality and house prices. Estimation of semiparametric models that allow the data to determine the functional form may provide more insight on the real relationships suggested by the data rather than imposing the constraints of fully parametric models. Using an instrumental variable estimator, I explore the advantages of using semiparametric models in the estimation of spatial hedonic models by comparing the economic estimates from a parametric spatial lag model with those of a semiparametric specification, where the environmental variable is introduced nonparametrically.air quality valuation, endogeneity, hedonic models, real estate markets., semi-parametric, spatial econometrics

Approximate Bayesian inference in semiparametric copula models

We describe a simple method for making inference on a functional of a multivariate distribution. The method is based on a copula representation of the multivariate distribution and it is based on the properties of an Approximate Bayesian Monte Carlo algorithm, where the proposed values of the functional of interest are weighed in terms of their empirical likelihood. This method is particularly useful when the "true" likelihood function associated with the working model is too costly to evaluate or when the working model is only partially specified.Comment: 27 pages, 18 figure

Modelling bilateral intra-industry trade indexes with panel data: a semiparametric approach

This paper focuses on the modelling of bilateral intra-industry trade indexes with panel data, applying a semiparametric approach. This extends the work of Papke and Wooldridge (J Econom 145: 121–133, 2008) for fractional responses, by introducing a nonparametric component to control for unobserved heterogeneity associated with the regressors. The proposed approach is based on the semi-mixed effects gen eralised linear model of Lombardía and Sperlich (Comput Stat Data Anal 56:2903– 2917, 2012), introduced in the context of small area statistics, and the semiparametric gravity model of Proença et al. (Empir Econ doi:10.1007/s00181-014-0891-x, 2014). The resulting nonlinear semiparametric model serves to explain the bilateral intra industry trade indexes between Portugal and the European Union, the BRIC emerging economies, and the five Portuguese-speaking African countries.info:eu-repo/semantics/publishedVersio

Explaining trends in UK household spending

In this paper we model the changing distribution of household spending in the UK over the period 1978 to 1999 and explore the interpretation of remaining time trends in spending once changes in other observed covariates have been accounted for