The aggregate production function approach is one way to forecast future energy demand (a step in forecasting carbon dioxide emissions, for example) and to analyze the aggregate economic effects of measures such as the increase of taxes on energy use. The results of such an approach tend to...

The aggregate production function approach is one way to forecast future energy demand (a step in forecasting carbon dioxide emissions, for example) and to analyze the aggregate economic effects of measures such as the increase of taxes on energy use. The results of such an approach tend to...

The aggregate production function approach is one way to forecast future energy demand (a step in forecasting carbon dioxide emissions, for example) and to analyze the aggregate economic effects of measures such as the increase of taxes on energy use. The results of such an approach tend to...

This paper gives a brief survey of forecasting with panel data. Starting with a simple error component regression and surveying best linear unbiased prediction under various assumptions of the disturbance term. This includes various ARMA models as well as spatial autoregressive models. The paper...

In 1994, Blanchflower and Oswald reported that they have found an empirical law of economics the Wage Curve. According to their empirical results, the elasticity of wages with respect to regional unemployment is -0.1. This holds especially for the Anglo-Saxon countries...

This paper analyzes the relationship between higher education and body weight and smoking behavior among women in Turkey. We exploit the largely exogenous and substantial increase in the openings of universities throughout Turkey. Based on the spatial and temporal variability of university...

This paper studies the impact of urban density, city government efficiency, and medical resources on COVID-19 infection and death outcomes in China. We adopt a simultaneous spatial dynamic panel data model to account for (i) the simultaneity of infection and death outcomes, (ii) the spatial...

This paper extends the Baltagi et al. (2018, 2021) static and dynamic ?-contamination papers to dynamic space-time models. We investigate the robustness of Bayesian panel data models to possible misspecification of the prior distribution. The proposed robust Bayesian approach departs from the...