There is policy interest in factoring productivity growth into technical progress and returns to scale components. Our approach uses exact index number methods to reduce the parameters that must be estimated, and allows us to exploit the cross-sectional dimension of plant-level panel data. We...

Much of the public concern about the growing labor force participation of women centers on feared, or hoped for, effects of the market work of mothers on the well-being of their children. On the one side, there are those who fear that the children of working mothers will not receive the care...

Women's Careers explores contexts and strategies that advance or hinder women's career development. It brings readers up-to-date on the intersection of the fields of women's studies, career development, and human resources. The applied focus and broad range of topics covered will appeal to both...

A Markov chain model is applied to analyze changes in real annual state and local police expenditures in the United States, where transition probabilities are functions of crime, demographic and economic variables. Of these variables, the inflation rate for state and local government...

The way in which economist try to learn about economics responses, such as the effects of children on female labor supply, can be broken down into three steps: the consideration of information already available called a priori information, including inferences based on what economist believe...

When a regression model is estimated using a censored subset of observations, coefficient estimates may be biased. Censored regression models have a long history in biometrics, engineering and other areas of applied statistics. The interest of economists in these models was stimulated by...

Pure cross-sectional model cannot capture the observed continuity over time in the work behavior of wives. Proposed alternative models generally require panel data not available in most countries. We present simulation results for models incorporating more limited information about previous...

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