Pollution Abatement and Environmental Equity: A Dynamic Study

We study pollution abatement and environmental equity in a dynamic panel model using data for 236 plants in the US pulp and paper industry observed over the period 1985-1997. We suggest a theoretical model for the plant manager who incorporates regulatory pressures into his calculations of optimal amount of pollution. Assuming actual pollution abatement exhibits a sluggish adjustment process, the theoretical model leads to an empirical AR(1) panel model. We estimate our model using GMM with both ''temporally lagged'' and ''spatially lagged'' instruments. We find that children, people below the poverty line and the smallest minority races are exposed to higher levels of pollution. Our findings show no evidence of environmental inequity against African-Americans or Hispanics, and find that the neighborhoods with a higher percentage of elderly population face signicantly lower levels of pollution from the plants.pollution abatement, environmental equity, dynamic panel, instrumental variable, fixed effects

Small Sample Improvements of the GEL Robust Tests for Linear IV Models and Applications

In order to improve the small sample performance of the Generalized Empirical Likelihood Kleibergen type tests (GELK), we propose to re-weight the variance of moments matrix with GEL probabilities. Our modification improves GELK significantly by cutting the size distortion in half. Using simulations, we compare the performance of our modified tests with Kleibergen's K-test and the original GELK tests in a dynamic panel setting. As an empirical application, we use the Arellano and Bond's dynamic panel data for 140 UK firms to estimate labor demand. We compare our results with the traditionalWald test to illustrate the practical importance of using tests which are robust to weak instruments in a dynamic panel setting.GELK, weak instruments, dynamic panel, empirical likelihood

Does Pollution Affect Crime? Evidence from U.S. Cities

In this paper we study the relationship between air pollution and crime. We construct a city-level, hourly data set with 2.4 million crimes and link each crime to data on pollution and controls, e.g. weather variables. We study the effects of four pollutants (nitrogen dioxide, sulphur dioxide, carbon monoxide, and ozone), as these have different neurotoxic effects. Our identification strategy relies on using high dimensional fixed effects and exploiting hourly variations. We find that carbon monoxide has a positive effect on violent crimes and ozone has a negative effect on property crimes. These relationships are linear and we only find heterogeneity in the effect of ozone on property crimes across cities

Pollution abatement and environmental equity: A dynamic study

We study pollution abatement and environmental equity in a dynamic panel model using data for 234 plants in the US pulp and paper industry observed over the period 1985-1997. We suggest a theoretical model for the plant manager who incorporates regulatory pressure into his calculations of optimal amounts of pollution. Assuming actual pollution abatement exhibits a sluggish adjustment process, the theoretical model leads to an empirical AR(1) panel model. We estimate our model using GMM with both "temporally lagged" and "spatially lagged" instruments and find significant evidence supporting the partial adjustment model for both particulate matters less than 10 [mu]m and sulfur dioxide. We find some environmental inequity with respect to the children (under 6 years) and adults with no high school diploma. Our findings show no evidence of environmental inequity against African-Americans, Hispanics, other minority races, or the poor.Pollution abatement Environmental equity Demographic composition Dynamic panel Instrumental variable

Does Pollution Affect Crime? Evidence from U.S. Cities

In this paper we study the relationship between air pollution and crime. We construct a city-level, hourly data set with 2.4 million crimes and link each crime to data on pollution and controls, e.g. weather variables. We study the effects of four pollutants (nitrogen dioxide, sulphur dioxide, carbon monoxide, and ozone), as these have different neurotoxic effects. Our identification strategy relies on using high dimensional fixed effects and exploiting hourly variations. We find that carbon monoxide has a positive effect on violent crimes and ozone has a negative effect on property crimes. These relationships are linear and we only find heterogeneity in the effect of ozone on property crimes across cities

Pollution abatement and environmental equity: A dynamic study

We study pollution abatement and environmental equity in a dynamic panel model using data for 234 plants in the US pulp and paper industry observed over the period 1985-1997. We suggest a theoretical model for the plant manager who incorporates regulatory pressure into his calculations of optimal amounts of pollution. Assuming actual pollution abatement exhibits a sluggish adjustment process, the theoretical model leads to an empirical AR(1) panel model. We estimate our model using GMM with both " temporally lagged" and " spatially lagged" instruments and find significant evidence supporting the partial adjustment model for both particulate matters less than 10μm and sulfur dioxide. We find some environmental inequity with respect to the children (under 6. years) and adults with no high school diploma. Our findings show no evidence of environmental inequity against African-Americans, Hispanics, other minority races, or the poor. © 2010 Elsevier Inc.Nadezhda V. Baryshnikov