Based on a substantially larger data set (in both regional and temporal coverage) than the existing literature, we investigate the theoretically ambiguous link between income inequality and per capita emissions using cross-country panel data. We nd that the relationship depends on the level of income. Using an arguably superior group-xed eects estimator, we show that for low and middle-income economies, higher income inequality is associated with lower carbon emissions while in upper middle-income and high-income economies, higher income inequality increases per capita emissions. The result is robust to the inclusion of plausible transmission variables as well as dierent data sources or aggregations.JEL codes: Q0, Q1, Q3

This paper investigates to what extent international migration can be explained by climatic variations. A gravity model of migration augmented with average temperature and precipitation in the country of origin is estimated using a panel data set of 142 sending countries for the period 1995 to 2006. We find two primary results. First, temperature is positively correlated with migration. Second, stronger changes in precipitation are also associated with aligned, but small changes in migration. Both effects are robust to various model modifications. Furthermore, we present initial explorations into the channels relating climate changes with migration via agriculture and internal conflict.JEL Codes: F22, Q54

This paper introduces a new estimator for the fixed-effects ordered logit model. The proposed method has two advantages over existing estimators. First, it estimates the differences in the cut points along with the regression coefficient, leading to provide bounds on partial effects. Second, the proposed estimator for the regression coefficient is more efficient. I use the fact that the ordered logit model with J outcomes and T observations can be converted to a binary choice logit model in (J − 1) T ways. As an empirical illustration, I examine the income-health gradient for children using the Medical Expenditure Panel Survey.

Two effects largely determine global warming: the well-known greenhouse effect and the less well-known solar radiation effect. An increase in concentrations of carbon dioxide and other greenhouse gases contributes to global warming: the greenhouse effect. In addition, small particles, called aerosols, reflect and absorb sunlight in the atmosphere. More pollution causes an increase in aerosols, so that less sunlight reaches the Earth (global dimming). Despite its name, global dimming is primarily a local (or regional) effect. Because of the dimming the Earth becomes cooler: the solar radiation effect. Global warming thus consists of two components: the (global) greenhouse effect and the (local) solar radiation effect, which work in opposite directions. Only the sum of the greenhouse effect and the solar radiation effect is observed, not the two effects separately. Our purpose is to identify the two effects. This is important, because the existence of the solar radiation effect obscures the magnitude of the greenhouse effect. We propose a simple climate model with a small number of parameters. We gather data from a large number of weather stations around the world for the period 1959-2002. We then estimate the parameters using dynamic panel data methods, and quantify the parameter uncertainty. Next, we decompose the estimated temperature change of 0.73 • C (averaged over the weather stations) into a greenhouse effect of 1.87 • C, a solar radiation effect of −1.09 • C, and a small remainder term. Finally, we subject our findings to extensive sensitivity analyses.

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in EconStor may AbstractWe document a U-shaped relationship between income inequality and carbon dioxide emissions per capita, using a newly available panel data set on income inequality (GINI) with observations for 138 countries over the period 1960-2008. Our findings suggest that, for high-income countries with high income inequality, pro-poor growth and reduced per capita emissions levels go hand in hand.