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Author: Marcia M Schafgans

11 results found.

Econometrics Paper

Multivariate kernel regression in vector and product metric spaces

Marcia M Schafgans and Victoria Zinde-Walsh

Nonparametric kernel regression is widely used in econometrics and has been applied to models with cross-sectional, time series and panel data. As functional data analysis is gaining attention, our analysis extends to th...Read more...

9 May 2024

Econometrics Paper

Inference Without Smoothing for Large Panels with Cross- Sectional and Temporal Dependence

Javier Hidalgo and Marcia M Schafgans

This paper addresses inference in large panel data models in the presence of both cross-sectional and temporal dependence of unknown form. We are interested in making inferences without relying on the choice of any smoo...Read more...

20 February 2018

Econometrics Paper

Inference and Testing Breaks in Large Dynamic Panels with Strong Cross Sectional Dependence

Javier Hidalgo and Marcia M Schafgans

This paper is concerned with various issues related to inference in large dynamic panel data models (where both n and T increase without bound) in the presence of, possibly, strong cross-sectional dependence. Our first a...Read more...

1 April 2015

Economics of Industry Paper

Multiproduct Firms, Income Distribution, and Trade

Marcia M Schafgans and Joachim Stibora

We develop a general equilibrium model of multiproduct fi…rms with quality differentiated goods. Households are characterized by an heterogeneous taste for the differentiated good and their income level. The use of non-h...Read more...

1 July 2014

Econometrics Paper

Adapting Kernel Estimation to Uncertain Smoothness

Yulia Kotlyarova, Marcia M Schafgans and Victoria Zinde-Walsh

For local and average kernel based estimators, smoothness conditions ensure that the kernel order determines the rate at which the bias of the estimator goes to zero and thus allows the econometrician to control the rate...Read more...

April 2011

Econometrics Paper

Smoothness Adaptive Average Derivative Estimation

Marcia M Schafgans and Victoria Zinde-Walsh

Many important models, such as index models widely used in limited dependent variables, partial linear models and nonparametric demand studies utilize estimation of average derivatives (sometimes weighted) of the conditi...Read more...

August 2008

Econometrics Paper

Selectivity and the gender wage gap decomposition in the presence of a joint decision process

Marcia M Schafgans and Morton Stelcnery

In this paper we revisit the gender decomposition of wages in the presence of selection bias. We show that when labor market participation decisions of couples are not independent, the sample selection corrections used i...Read more...

December 2006

Econometrics Paper

A method of moments estimator for semiparametric index models

Bas Donkers and Marcia M Schafgans

We propose an easy to use derivative based two-step estimation procedure for semi-parametric index models. In the first step various functionals involving the derivatives of the unknown function are estimated using nonpa...Read more...

July 2005

Econometrics Paper

On Intercept Estimation in the Sample Selection Model

Marcia M Schafgans

We provide a proof of the consistency and asymptotic normality of the estimator suggested by Heckman (1990) for the intercept of a semiparametrically estimated sample selection model. The estimator is based on 'identific...Read more...

January 2000

Econometrics Paper

Semiparametric Estimation of a Sample Selection Model: A Simulation Study

Marcia M Schafgans

Standard approaches to the estimation of sample selection models are known to be inconsistent under non-normality. In particular, this paper considers the two-step Heckman (1976, 1979) estimator of the interecept of the ...Read more...

March 1997

Econometrics Paper

Gender Wage Differences in Malaysia: Parametric and Semiparametric Estimation

Marcia M Schafgans

This paper is an empirical study on the labor force in (Peninsular) Malaysia. It applies both parametric and semiparametric sample selection methods to the estimation of wage equations. These equations are then used to a...Read more...

March 1997