This article investigates the causal links between health and employment status. To disentangle correlation from causality effects, the authors leverage a French panel survey to estimate a bivariate dynamic probit model that can account for the persistence effect, initial conditions, and...

In a multilingual context, this study investigates the role of language skills on mathematics achievement. It compares characteristics of 5048 Grade-6 learners in 275 Namibian schools. The outcome variable is the standardized SACMEQ mathematics score collected in year 2000. Hierarchical linear...

The diagonal GARCH(1,1) model is shown to support identification of the triangular system and is argued as a second moment analog to traditional exclusion restrictions. Estimators for this result include QML and GMM. The GMM estimator contains many (potential weak) moment conditions that can be...

The diagonal GARCH(1,1) model is shown to support identification of the triangular system and is argued as a second moment analog to traditional exclusion restrictions. Estimators for this result include QML and GMM. The GMM estimator contains many (potential weak) moment conditions that can be...

A new method is proposed for estimating linear triangular models, where identification results from the structural errors following a bivariate and diagonal GARCH(1,1) process. The associated estimator is a GMM estimator shown to have the usual √T-asymptotics. A Monte Carlo study of the...

Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA) is the largest and most ambitious public works program for poverty alleviation, adopted by Government of India since independence. It was implemented in year 2006, starting with the first phase of 200 most backward districts in...

Grandmont (1985) found that the parameter space of the most classical dynamic models are stratified into an infinite number of subsets supporting an infinite number of different kinds of dynamics, from monotonic stability at one extreme to chaos at the other extreme, and with all forms of...

I introduce a technique to estimate parameters in regressions with reduced rank parameters in a general setting. The framework can handle a general class of parameter restrictions and allows for specifications with heteroskedastic and autocorrelated regression errors. Applications of this...

A correlation between regressors and disturbances presents challenging problems in linear regression. Issues like omitted variables, measurement error and simultaneity render ordinary least squares (OLS) biased and inconsistent. In the context of heteroscedastic linear regression, this note...

A particularly useful approach for analyzing pooled cross sectional and time series data is Swamy's random coefficient panel data (RCPD) model. This paper examines the performance of Swamy's estimators and tests associated with this model by using Monte Carlo simulation. The Monte Carlo study...