Limits and possible extension

One could argue that our estimate mirrors the information pollutant intensity ratios already offer and, applying Occam's Razor principle, appears as unnecessarily complicated. Several studies focus on pollution intensities when examining the environment-economy interface (Roberts and Grimes, 1997;

Roberts et al., 2003). Such studies show that CO₂ intensity has improved in highly developed economies while it has remained stable or deteriorated in low and middle income countries. This study offers alternative evidence, since it takes into consideration the amount of resources used by the countries (inputs) and thus offers a more complete and precise image of the efficiency of national production relative to the emissions of CO2. In our sample, there is no significant positive relationship between pollution intensity and GDP per capita²⁶ (figure 3.6). However, the estimated shadow-prices are negatively related to GDP per capita. An interesting development in this direction would consist in analyzing the evolution of the shadow-prices across several years.

26 The estimated equation is: pollution intensity = 1.73E-5 (1.83) * GDP per capita + 0.557 (6,83). T-statistics are in parentheses.

OLS procedure with robust standard errors has been used. R² equals 0.07. Quadratic and logarithmic forms have been tested and did not result in a higher R².

0 0.5 1 1.5 2 2.5 3 3.5

0 5000 10000 15000 20000

GDP per capita

Pollution intensity

Fig. 4.XII Pollution intensity vs. GDP per capita

A second potential development for the estimation of the shadow-prices would be to account in one unique measure for both the marginal macro-economic abatement costs and technical inefficiencies (as captured by the efficiency scores ß). In this paper, the inefficient countries are all projected on the efficient frontier and the shadow-prices are calculated for this projection. The potential zero-cost emission reductions due to the presence of inefficiencies are analyzed separately. We could overcome this limitation by determining shadow-prices of CO₂ emissions where the inefficiencies involved in the process are taken into account. Lee et al. (2002) propose such a framework. Note however that according to our estimates, there is no systematic difference between the degree of technical efficiency attained by the developed and the developing countries. Hence, taking into account the zero-cost CO₂ reduction opportunities would not change our conclusions regarding the relationship between the shadow-prices of CO2 and the countries’ per capita income.

Our results must be considered with caution given the following issues. First, linear programming defines the frontier in terms of the best practices observed in the sample. Hence, our results are relative to the most efficient countries observed and do not rely on a defined optimal technology. For the year 1985, for example, 29 units define the frontier when all four inputs (labor force, capital stock, energy consumption and arable land) are used. Our estimates have however the advantage of being directly comparable across countries.

Second, our estimates are based on cross-country comparisons. Therefore, even if we observe that marginal macro-economic costs of abatement are lower in developed economies, the latter relationship may not hold for one country with varying GDP levels observed over several years. We may again overcome this drawback by analyzing the evolution of the relationship over several years.

Third, the quality of environmental data for poor countries is uncertain (see chapter 1, section 3.2).

Shafik (1994) and Lieb (2002) warn that the usage of environmental pollution data might be problematic for the cross-country comparisons, because these data may be flawed by the differences in the definitions and inaccuracy. This concern has been largely ignored in the empirical literature.

However, as mentioned by Roberts and Grimes (1997), CO₂ data are the best for any measured pollutant when both their coverage and their adequacy are considered. Similarly, data availability also constraint the inputs mix. Taking into consideration additional inputs could better apprehend the specificities of each country. In this regard, including a measure of the human capital stock could be interesting.

Finally, the DEA technique relies on the hypothesis that one unique production frontier pertains to all countries, or, in other words, that countries belong to the same technological regime. This might be erroneous as countries may use different technologies and correspond to different production frontiers (Tyteca, 1995). We postulated the existence of one unique technological regime pertaining for all countries under investigation, because each combustion process generates CO₂ emissions and the inputs take into account the fundamental specificities of each country. Further work on this issue is clearly needed since national conditions such as climate (average temperature), dispersion of economic activities, openness to trade, legislations and state interventions are also part of the story.

Indeed, a valuable direction for further research would consist in examining the influence of exogenous variables on the efficiency scores and macro-economic abatement costs. Such work may more particularly allow to connect differences in preferences across countries (capture by the existence of various policies) to the macro-economic burden of abating pollution.

Conclusion

The implications of our result are twofold. First, income is negatively associated with the macro-economic marginal cost of pollution abatement when all countries are supposed to be perfectly efficient, given their input mix. In other words, reducing carbon dioxide emissions is cheaper (in terms of forgone output) in high-income rather than in low-income countries. It seems therefore that the explanations for ever increasing CO2 emissions lay rather on the demand or willingness to pay for CO2

reduction.

Next, the low-income countries are not found to be systematically less efficient than the high-income countries when inputs used for the production processes are taken into account. Therefore, one should be cautious when asserting that numerous low-cost abatement opportunities are available in the developing countries. The amount of CO2 emissions that could be abated at zero-cost (expressed as a percentage of total national emissions) is higher in countries whose pollution intensities are high.

Further work on the shadow-prices of pollutants is clearly needed. The empirical analysis should be extended to the panel data and to other types of pollutants. Furthermore, the computation of shadow-prices taking into account the degree of a country's inefficiency offers the possibility to combine the two sets of results. Finally, more work is needed in order to explore the link between the characteristics of countries and the macro-economic burden associated with abatement.

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