This paper combines unique experimental and survey data to examine the determinants of self-selection into a training program. Women residing in selected disadvantaged areas in New Delhi, India were invited to apply for a six-month long subsidized training program in stitching and tailoring. A...

This paper derives six different forms of message length functions for general linear regression model. In so doing, two different prior densities and the idea of parameter orthogonality are employed.

In this paper we make a first attempt to explore the relationship between computer use and productivity in French manufacturing and services industries.

In this paper the EM algorithm, which has been used successfully with censored and incomplete data sets, is adapted to the problem of scrambled data. The performance of the method is assayed using an artificially constructed data set. The relevance of the results for a real world labour market...

In this paper, we employ stochastic dominance analysis on Australian unit records to investigate trends in inequality and relative welfare levels in Australia over the period 1983 to 2004. We find that that when the stochastic dominance tests are applied to income and expenditure distributions...

We apply stochastic dominance tests to investigate trends in inequality in Australia over the period 1983 to 1998. Results show significant levels of inequalities in the income and expenditure distributions for the population as a whole as well as within population groups. We further find that...

The main objective of this study is to investigate the rebustness of the popular Durbin-Watson (DW), Langrage multiplier (LM), Box-Pierce (BP) and Ljung-Box (LB) tests and their corrected versions against autoregressive distrurbances in the presence of dynamic heteroscedastic disturbances with...

Theoretical results on the properties of forecasts obtained using singular spectrum analysis are presented in this paper. The mean squared forecast error is derived under broad regularity conditions, and it is shown that the forecasts obtained in practice will converge to their population...

In this paper, we propose a panel data semiparametric varying-coefficient model in which covariates (variables affecting the coefficients) are purely categorical. This model has two features: first, fixed effects are included to allow for correlation between individual unobserved heterogeneity...

In this paper, we consider a partially linear panel data model with cross-sectional dependence and non-stationarity. Meanwhile, we allow fixed effects to be correlated with the regressors to capture unobservable heterogeneity. Under a general spatial error dependence structure, we then...