Abstract
Using a large plant level data set, this paper carries out an econometric analysis of the environmental performance of multinational firms in the gold mining industry worldwide. The aim of the analysis is to determine if, by looking at the actual environmental performance of firms (as opposed to inferring such behavior from location decisions), we can shed any light on important questions in the literature on firm location decisions: Do pollution havens exist in the gold mining industry? Do foreign controlled gold mines perform environmentally worse or better than their domestic counterparts? We develop different ways of measuring environmental performance within the context of a Bayesian stochastic production frontier approach. In particular, we derive different ways of measuring technical and environmental efficiency. When we implement these methods in our empirical work, we find that results are robust across different models and ways of measuring efficiency. We find that gold mines exhibit a wide range of environmental efficiencies; some are clearly more efficient than others. However, and most importantly for our questions, we find that this variation in efficiencies cannot be systematically related to mine characteristics such as whether they are foreign or domestically controlled or whether they are located in developed versus developing countries.
Original language | English |
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Pages (from-to) | 129-143 |
Number of pages | 15 |
Journal | Journal of Productivity Analysis |
Volume | 30 |
Issue number | 2 |
DOIs | |
Publication status | Published - Oct 2008 |
Keywords
- Bayesian stochastic frontier analysis
- efficiency
- environmental regulations
- plant performance
- pollution havens
- regulatory chill
- gold mining
- econometrics