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Our estimate for industry variation is also highly consistent with Wang and Cui's (2010) 13%.
In our analysis, we are not able to use regional variations but rather rely on the industry shutdown rate as a proxy for industry variation.
As the empirical specifications includes industry dummy variables as controls, the analysis focuses on the within industry variation in shutdown rates.
Nonetheless, our results differ substantially from those of Wang and Wang (2005), whose estimates based on a decomposition of the Theil index suggest that the impact of regional variation on income inequality is much more important than that of industry variation.
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This suggests that at least some of the region and industry variations in income are due to different population compositions and human capital stock across regions and industries.
Environmental and social performances account for only a fractional share of the index's total weighting about 25% to 35%, depending on industry variations.
Several interviewees noted industry variations in the desktop valuation methods, "Telecommunications and service industries tend to prefer multiples (e.g., economic value and/or EBITDA), while the financial sector prefers discounted cash flow".
As a result, the relative contribution of inter-industry variation to the total variation in income has also increased dramatically (Chen et al. 2010).
Using appropriate statistical techniques, it examines the interactions between policy regime, economic environment and the determinants of inter-industry variation in technology imports in Indian manufacturing.
We find that cross-industry variation in input reallocation explains more than 30% of differences in the 5-year productivity growth rates of industries utilizing similar levels of IT.
In the latter, it was considered the key innovation of their paper, which "by absorbing country-specific variation in country indicators, and exploiting only the within-country across-industry variation, we go some way in addressing the specification problem that plague standard cross-country regressions".
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