Using the ECI methodology, Hartmann et al.  recently introduced a measure that associates products with income inequality and showed how the development of sophisticated products is associated with changes in income inequality. Here, we introduce a measure that links a product to the average environmental performance and air pollution level of the countries that export it. In this way, we illustrate how environmental performance is being affected by the level of sophistication of exported products and we quantify the influence of countries’ level of economic complexity on their environmental performance.
Following the methodology in Hartmann et al. , we define the Product Environmental Per-formance Index (PEPI) and the Product Air Pollution Index (PAPI) as the average EPI and the average level of CO2 emissions, respectively, of the countries that export the focal product, normalized by the importance of this product to the total exports of the countries that export it. More precisely, we decompose the relationship between the ECI and both the EPI and CO2 emissions into individual economic sectors by creating product-level estimators of these measures for the countries exporting a given product.
5.1 Product environmental indexes
Assuming that we have trade data for l countries and k products, we can fill the (l × k) matrix M so that its matrix element Mcp= 1 if country c has a RCA for product p, and zero otherwise
−3 −2 −1 0 1
Figure 1: PEPI and PAPI against PCI. The solid lines represent the fit of a linear model and the dashed lines a 95% prediction interval based on the fitted linear model.
(see the Appendix A). Dataset 2 (see Section 2) contains information for the 88 developed and developing countries used in the above analysis and for 772 products from 2002 to 2012, classified according to the Standard International Trade Classification (SITC) at the 4-digit level.
Every product p generates some value for the country c that exports it. Therefore, for every product p, we can calculate the fraction scp:
where Xcp is the total export value of product p when exported by country c, whileP
p0Xcp0 is the value of all exports of country c. If EP Ic (resp. CO2c) is the EP I (resp. CO2 emissions) of country c, we can calculate the PEPIp and the PAPIp for every product as:
cMcpscp is a normalization factor.
Table 6: List of the five products with the highest and lowest P EP I and P AP I values during the period of 2002-2012
SITC4 Product name Product section PEPI PAPI PCI
8851 Watches and clocks Miscellaneous manufactured articles 77.2 0.16 0.45
5415 Medicinal and pharmaceutical products Chemicals and related products, n.e.s. 76.9 0.19 1.20 7259 Paper mill and pulp mill machinery, paper-cutting machines Machinery and transport equipment 76.2 0.26 1.23 5416 Glycosides, glands, antisera, vaccines Chemicals and related products, n.e.s. 75.9 0.21 1.18
7913 Railway vehicles Machinery and transport equipment 75.3 0.23 1.01
2654 Vegetable textile fibres, waste of these fibres Crude materials, inedible, except fuels 32.0 0.08 -0.96 2923 Vegetable materials of a kind used primarily for plaiting Crude materials, inedible, except fuels 30.9 0.12 -0.78 2631 Cotton (other than linters), not carded or combed Crude materials, inedible, except fuels 30.8 0.18 -2.82 2683 Fine animal hair, not carded or combed Crude materials, inedible, except fuels 29.4 0.16 -0.47 2922 Lac, natural gums, resins, gum resins, and balsams Crude materials, inedible, except fuels 26.0 0.11 -2.01
6812 Platinum metals Manufactured goods classified chiefly by material 54.0 0.60 0.73
7915 Railway vehicles Machinery and transport equipment 56.0 0.60 0.49
3353 Pitch and pitch coke Mineral fuels, lubricants 59.1 0.57 0.36
2814 Roasted iron pyrites Crude materials, inedible, except fuels 55.2 0.54 0.04
6712 Pig-iron and spiegeleisen Manufactured goods classified chiefly by material 49.7 0.53 0.07
2922 Lac, natural gums, resins, gum resins, and balsams Crude materials, inedible, except fuels 26.0 0.11 -2.01
2225 Sesame seeds Crude materials, inedible, except fuels 34.0 0.10 -2.58
4314 Vegetable waxes Animal and vegetable oils, fats and waxes 39.7 0.10 -1.29
2876 Tin ores and concentrates Crude materials, inedible, except fuels 36.5 0.09 -1.44
2654 Vegetable textile fibres, waste of these fibres Crude materials, inedible, except fuels 32.0 0.08 -0.96
Notes: PEPI: Product Environmental Performance Index; PAPI: Product Air-Pollution Index. Average values for 2002-2012
For every year in the period of 2002-2012, we utilize the EPI and CO2 emissions for the 88 developed and developing countries in our sample and calculate the mean value of all the product-related indexes (PCI, PEPI and PAPI) for each product.
Table 6 lists the five products with the highest and lowest PEPI and PAPI values during the period of 2002-2012. It is evident that technologically moderate manufacturing industries and primary sectors such as textile fibres and their wastes (SITC Rev.4 division: 22) and crude animal and vegetable materials (SITC Rev.4 division: 29) appear to be associated with lower environmental performance. Regarding the index of air pollution (PAPI), the reader can easily verify that a country’s RCA in products such as non-ferrous metals (SITC Rev.4 division: 68) and railway vehicles (SITC Rev.4 group: 791) is associated with higher CO2 emissions. In Table 6, the SITC Rev.4 group 2654 of vegetable textile fibres and the waste of these fibres and the
SITC Rev.4 subgroup 2922 of lac, natural gums, resins, gum resins, and balsams appear to be environmentally detrimental but air pollution friendly.
5.2 Product environmental indexes and product complexity
We test the existence of a bivariate relationship between the PCI and the PEPI and PAPI indexes by calculating Pearson’s correlation coefficient for both pairs, PEPI against PCI and PAPI against PCI. If such a relation exists, it should allow us to derive expectations about whether product sophistication can be associated with the quality of the environment and the level of CO2 emissions. For the case of PEPI against PCI, the correlation coefficient is ρ = 0.74 with a p-value < 10−99, while for PAPI against PCI, it is ρ = 0.29 with a p-value < 10−15. In Figure 1, we present the scatter plots of the PEPI and PAPI indexes against the PCI index for all 772 products in our dataset, together with the fitted linear models. The slopes of the linear fits are the corresponding correlation coefficients.
The statistically significant positive correlations between (a) PEPI and PCI and (b) PAPI and PCI, indicate that more sophisticated products are associated with countries that demonstrate relatively better environmental performances as measured by the EPI, but higher air pollution as measured by CO2 emissions. This adds to our previous discussion about economic complexity at the country level, as it allows us to understand which sets of products are leading to a better overall environmental performance and less air pollution, based on their embodied sophistication.
Our analysis illustrates that the environmental performance of a country is highly correlated with the mix of products that it produces and exports. In a panel data setting, we have verified that there is a robust positive (resp. negative) relationship between environmental performance
(resp. air quality) and product sophistication. Moreover, the effect of economic complexity on environmental performance has been verified with fixed-effects instrumental variables estimation techniques. Thus, the evidence presented in the paper suggests that the sophistication of a country’s productive structure predicts its environmental performance.
More specifically, countries that produce more complex products are associated with improved environmental performance but also with inferior air quality (higher exposure to PM2.5 and CO2 emissions). Explicitly, it seems that when an economy accelerates from an agricultural productive structure to a more sophisticated one with industrial and technological sectors, the effect on overall environmental performance is positive but the particular effect on air quality is negative.
We build a Product Environmental Performance Index and a Product Air Pollution Index that associate exported products with the average level of countries’ environmental performance as measured by the EPI and air pollution as measured by CO2 emissions, respectively.
With these indexes, we show how the development of complex products is associated with changes in the environment. Hence, the two indexes could be a valuable tool for evaluating smart special-ization strategies and/or sectoral reallocation policies towards activities/sectors that are associ-ated with better environmental performance and lower air pollution. According to WHO , exposure to air pollution has been found to have both direct and indirect detrimental effects on human health. The direct effects include respiratory irritation, chronic respiratory symptoms, heart diseases, lung cancer, premature mortality and reduced life expectancy [37, 70, 94]. The indirect mechanisms relate to pulmonary oxidative stress and inflammatory responses. Hence, empirical evidence about the effect of economic complexity on air quality should be highly infor-mative for policy makers.
In sum, this study identifies economic complexity as an explanatory variable of the observed differences in environmental footprints across countries. However, we do not attempt to address
the question of why some countries have a higher level of economic complexity than others.
Trying to answer this question is beyond the scope of this paper, but an interesting way forward.
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