This paper documents the convergence of incomes across Indian states over the period 1965 to 1998. It departs from traditional analyses of convergence by tracking the evolution of the entire income distribution, instead of standard regression and time series analyses. The findings reveal...

This paper documents the convergence of incomes across Indian states over the period 1965 to 1998. It departs from traditional analyses of convergence by tracking the evolution of the entire income distribution, instead of standard regression and time series analyses. The findings reveal...

This paper documents the convergence of incomes across Indian states over the period 1965 to 1998. It departs from traditional analyses of convergence by tracking the evolution of the entire income distribution, instead of standard regression and time series analyses. The findings reveal...

This paper documents the convergence of incomes across Indian states over the period 1965 to 1998. It departs from traditional analyses of convergence by tracking the evolution of the entire income distribution, instead of standard regression and time series analyses. The findings reveal...

In a panel data model with fixed effects, possible cross-sectional dependence is investigated in a spatial autoregressive setting. An Edgeworth expansion is developed for the maximum likelihood estimate of the spatial correlation coefficient. The expansion is used to develop more accurate...

Nonparametric regression is developed for data with both a temporal and a cross-sectional dimension. The model includes additive, unknown, individual-specific components and allows also for cross-sectional and temporal dependence and conditional heteroscedasticity. A simple nonparametric...

This paper focuses on the estimation and predictive performance of several estimators for the dynamic and autoregressive spatial lag panel data model with spatially correlated disturbances. In the spirit of Arellano and Bond (1991) and Mutl (2006), a dynamic spatial GMM estimator is proposed...

A dynamic panel data model is considered that contains possibly stochastic individual components and a common fractional stochastic time trend. We propose four different ways of coping with the individual effects so as to estimate the fractional parameter. Like models with autoregressive...

One of the motivations frequently cited by Sen and Nussbaum for moving away from a utility metric towards a capabilities framework is a concern about adaptive preferences or conditioned expectations. If utility is related to the satisfaction of aspirations or expectations, and if these are...

We consider the incidental parameters problem in this paper, i.e. the estimation for a small number of parameters of interest in the presence of a large number of nuisance parameters. By assuming that the observations are taken from a multiple strictly stationary process, the two estimation...