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Clean Technological Change in Developing-Country Industrial Clusters: Mexican Leather Tanning

  • Blackman, Allen

    ()

    (Resources for the Future)

  • Kildegaard, Arne

In many cities in developing countries, clusters of small and medium enterprises create severe pollution problems. Because conventional regulatory approaches are typically ineffective in such situations, policy responses have increasingly focused on promoting voluntary clean technological change. Yet the data and analysis needed to guide such efforts are scarce. This paper uses original firmlevel survey data on a cluster of small- and medium-scale leather tanneries in León, Guanajuato— Mexico’s leather capital—to econometrically identify the factors that drive the adoption of three clean tanning technologies. Using a multivariate probit model to estimate a system of seemingly unrelated regressions, we find—in contrast to conventional wisdom—that neither firm size nor regulatory pressure is correlated with adoption. Rather, the drivers of adoption are the firm’s human capital and stock of technical information, the same factors that explain conventional productivity-enhancing technological change. We also find that private-sector trade associations and input suppliers are important sources of technical information about clean technologies.

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Paper provided by Resources For the Future in its series Discussion Papers with number dp-03-12-rev.

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Date of creation: 01 Apr 2003
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Handle: RePEc:rff:dpaper:dp-03-12-rev
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  1. Stavins, Robert & Jaffe, Adam & Newell, Richard, 2000. "Technological Change and the Environment," Working Paper Series rwp00-002, Harvard University, John F. Kennedy School of Government.
  2. Blackman, Allen & Shih, Jhih-Shyang & Evans, David & Batz, Michael & Newbold, Stephen & Cook, Joseph, 2006. "The benefits and costs of informal sector pollution control: Mexican brick kilns," Environment and Development Economics, Cambridge University Press, vol. 11(05), pages 603-627, October.
  3. JunJie Wu & Bruce A. Babcock, 1998. "The Choice of Tillage, Rotation, and Soil Testing Practices: Economic and Environmental Implications," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 80(3), pages 494-511.
  4. Feder, Gershon & Lau, Lawrence J. & Lin, Justin Y. & Xiaopeng Luo, 1991. "Credit's effect on productivity in Chinese agriculture : a microeconomic model of disequilibrium," Policy Research Working Paper Series 571, The World Bank.
  5. Ramirez, Octavio A. & Schultz, Steven D., 2000. "Poisson Count Models To Explain The Adoption Of Agricultural And Natural Resource Management Technologies By Small Farmers In Central American Countries," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 32(01), April.
  6. Suzi Kerr & Richard G. Newell, 2003. "Policy-Induced Technology Adoption: Evidence from the U.S. Lead Phasedown," Journal of Industrial Economics, Wiley Blackwell, vol. 51(3), pages 317-343, 09.
  7. Wozniak, Gregory D, 1984. "The Adoption of Interrelated Innovations: A Human Capital Approach," The Review of Economics and Statistics, MIT Press, vol. 66(1), pages 70-79, February.
  8. JunJie Wu & Bruce A. Babcock & P. G. Lakshminarayan, 1996. "Choice of Tillage, Rotation, and Soil Testing Practices: Economic and Environmental Implications, The," Center for Agricultural and Rural Development (CARD) Publications 96-wp161, Center for Agricultural and Rural Development (CARD) at Iowa State University.
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