Skill distribution and comparative advantage: a comparison of China and India

This paper empirically examines the different comparative advantages of two emerging economic giants, China and India, in relation to the different skill distribution patterns in each country. By utilizing industry export data on China and India from 1983 to 2000, we find that a country with a greater dispersion of skills (i.e., India, especially in the earlier years) has higher exports in industries with shorter production chains, whereas a country with a more equal dispersion of skills (i.e., China, especially in the later years) is found to have higher exports in industries with longer production chains. The causal relationship is fairly robust across different specifications. This empirical evidence supports our assumption that the likely mechanism for these results is the negative impact of low-skilled workers on input quality, which accumulates and becomes larger as the length of production chains and the proportion of low-skilled workers in the economy increase.

Skill sorting, inter-industry skill wage premium, and production chains: evidence from India 1999-2000

This paper proposes a mechanism that links industry’s technological characteristics (i.e. quality of non-labor inputs, which is proxied by the length of industry production chains), industry-specific skill wage premium, and skill sorting across industries. It is hypothesized that high-skilled workers are sorted into industries where they can receive a higher skill wage premium, by working with better quality non-labor input. The quality of non-labor inputs is assumed to be worse in industries with longer production chains due to the increased involvement of low-skilled labor and poor infrastructure over the sequential production. By examining Indian wage and employment data for 1999-2000, empirical evidence to support this mechanism can be obtained: First, the skill wage premium is lower [higher] in industries with longer [shorter] production chains. Second, the skill wage premium is lower [higher] in industries with a higher [lower] proportion of low-skilled workers producing inputs outside their own industry. Third, the proportion of high-skilled workers is larger in industries with shorter production chains and lower ratio of low-skilled labor involved, i.e., a skill sorting trend can be observed.

Skill sorting and production chains : evidence from India

This study proposes a new mechanism that explains skill-sorting patterns and skill wage differentials across industries based on the length of the industry's production chain. A simple simultaneous production model shows that when the quality of intermediate inputs deteriorates rapidly along the production chains, high-skilled individuals choose to work in industries with shorter production chains because of higher returns to skill. I empirically confirm this skill-sorting pattern and these inter-industry skill wage differentials in India, where the quality of intermediate inputs is likely to degrade rapidly because of the high number of unskilled laborers, poor infrastructure, and less-advantaged technology. The results remain robust even when considering selection bias, alternative reasons for inter-industry skill wage differentials, and a different period. The results of this study have important implications when considering countries' industrial development patterns.

Negative skill sorting across production chains

Previous literature generally predicts that individuals with higher skills work in industries with longer production chains. However, the opposite skill-sorting pattern, a "negative skill-sorting" phenomenon, is also observed in reality. This paper proposes a possible mechanism by which both cases can happen and shows that negative skill sorting is more likely to occur when the quality of intermediate inputs degrade rapidly (or improves slowly) along the production chain. We empirically confirm our theoretical prediction by using country-industry panel data. The results are robust regardless of estimation method, control variables, and industry coverage. This study has important implications for understanding countries' comparative advantages and development patterns.

How does firm heterogeneity information impact the estimation of embodied carbon emissions in Chinese exports?

Using an augmented Chinese input–output table in which information about firm ownership and type of traded goods are explicitly reported, we show that ignoring firm heterogeneity causes embodied CO2 emissions in Chinese exports to be overestimated by 20% at the national level, with huge differences at the sector level, for 2007. This is because different types of firm that are allocated to the same sector of the conventional Chinese input–output table vary greatly in terms of market share, production technology and carbon intensity. This overestimation of export-related carbon emissions would be even higher if it were not for the fact that 80% of CO2 emissions embodied in exports of foreign-owned firms are, in fact, emitted by Chinese-owned firms upstream of the supply chain. The main reason is that the largest CO2 emitter, the electricity sector located upstream in Chinese domestic supply chains, is strongly dominated by Chinese-owned firms with very high carbon intensity.