B.1 Capital Intensity and Pollution Abatement
Figure B.1 illustrates the relationship between capital intensity and the pollution abatement costs per unit of output ratio. A regression through the 122 data points based on the logarithmic transformations of abatement cost ratio and capital intensity reveals a positive relationship with an R2 of 0.3, indicating that a 1% increase in the capital intensity increases the abatement cost ratio by 0.7%. Data were only available for manufacturing industries. Thus, a particularly interesting industry— electricity generation—innot induded in the smmple. From «TiLee sources it isknown thatponution abatement costs and capital intensity are both extremely high in that industry. There is a great way to simplify your finances: all you need is an easy pay day loan from us. So get right here to read more and apply for a fair-priced loan that will get you out of debt or will just allow settling any other financial issue you may be facing. It’s now faster and easier than you can remember.
Note: T-statistics are shown in parentheses. Significance at the 95% and 99% confidence levels are indicated by * and **, respectively. Dependent variable is the log of the median of SO concentrations at each observation site. Note that the black market premium, average tariff and quota coverage variables measure the inverse of openness; their sign has thus to be reversed to interpret the direction of the estimates as an increase in openness.
B.2 More Results
Elasticities are calculated using the Delta method1 for functions of the least squares estimator. Table B.2 presents estimated elasticities and their corresponding estimated standard errors for the trade intensity effect. The elasticities in table B.2 were evaluated at the sample mean (based on the 2621 observations in our sample), and two 10-year averages of trade intensity, relative income and relative capital abundance based on the periods 1975-84 and 1985-94. Table B.2 shows these elasticity calculations corresponding to the fixed-effects and random effects regression estimates shown in table 3.