Bayesian learning, growth, and pollution
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- Kolstad, Charles D., 1996. "Learning and Stock Effects in Environmental Regulation: The Case of Greenhouse Gas Emissions," Journal of Environmental Economics and Management, Elsevier, vol. 31(1), pages 1-18, July.
- Taylor, John B & Uhlig, Harald, 1990.
"Solving Nonlinear Stochastic Growth Models: A Comparison of Alternative Solution Methods,"
Journal of Business & Economic Statistics, American Statistical Association, vol. 8(1), pages 1-17, January.
- John B. Taylor & Harald Uhlig, 1989. "Solving Nonlinear Stochastic Growth Models: A Comparison of Alternative Solution Methods," NBER Working Papers 3117, National Bureau of Economic Research, Inc.
- Tauchen, George, 1990. "Solving the Stochastic Growth Model by Using Quadrature Methods and Value-Function Iterations," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(1), pages 49-51, January.
- Kelly, David L. & Kolstad, Charles D., 2001.
"Malthus and Climate Change: Betting on a Stable Population,"
Journal of Environmental Economics and Management, Elsevier, vol. 41(2), pages 135-161, March.
- Kelly, David L. & Kolstad, Charles D., 1999. "Malthus and Climate Change: Betting on a Stable Population," University of California at Santa Barbara, Economics Working Paper Series qt9ks625sk, Department of Economics, UC Santa Barbara.
- Evans, George W & Ramey, Garey, 1992. "Expectation Calculation and Macroeconomic Dynamics," American Economic Review, American Economic Association, vol. 82(1), pages 207-224, March.
- Edmonds Jae & Reilly John, 1983.
"Global Energy and C02 to the Year 2050,"
The Energy Journal, , vol. 4(3), pages 21-48, July.
- Joe Edmonds & John Reilly, 1983. "Global Energy and CO2 to the Year 2050," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 21-48.
- Judd, Kenneth L., 1992. "Projection methods for solving aggregate growth models," Journal of Economic Theory, Elsevier, vol. 58(2), pages 410-452, December.
- Yaakov Bar-Shalom & Edison Tse, 1976. "Caution, Probing, and the Value of Information in the Control of Uncertain Systems," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 5, number 3, pages 323-337, National Bureau of Economic Research, Inc.
- Balvers, Ronald J & Cosimano, Thomas F, 1990. "Actively Learning about Demand and the Dynamics of Price Adjustment," Economic Journal, Royal Economic Society, vol. 100(402), pages 882-898, September.
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