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Country-specific demand elasticities for forest products: Estimation method and consequences for long term projections

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  • Buongiorno, Joseph

Abstract

Long-term projections for the global forest sector are particularly sensitive to the parameters of the demand equations for the end products. To get more precise estimators, and test statistics with more power than with pure time-series, the elasticities of demand are typically estimated from panel data, pooling time-series across countries, and thus assuming that the elasticities are the same in all countries. The objective of this study was to recognize potential differences between countries, while using the prior information obtained by pooling. The proposed method estimated with quadratic programming country-specific elasticities that minimized the sum of squares of the errors across countries and over time, while keeping the country elasticities within the confidence intervals of the pooled elasticities. The method was applied to international data for seven product groups from 1992 to 2016. Compared with pooling, country-specific elasticities reduced the root mean square error of in-sample predictions by 7% to 43% depending on the product. The country-specific elasticities had smaller standard errors than the pooled elasticities, and they tended to cluster near the bounds of the confidence intervals of the pooled elasticities. With country-specific elasticities in a global sector model the projected world prices in 2065 were 3% to 13% higher, depending on the product, than with pooled elasticities. World consumption in 2065 with country-specific elasticities was from 2% lower to 42% higher depending on the product, with large differences across countries and product groups.

Suggested Citation

  • Buongiorno, Joseph, 2019. "Country-specific demand elasticities for forest products: Estimation method and consequences for long term projections," Forest Policy and Economics, Elsevier, vol. 106(C), pages 1-1.
  • Handle: RePEc:eee:forpol:v:106:y:2019:i:c:16
    DOI: 10.1016/j.forpol.2019.101967
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    References listed on IDEAS

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    1. Michinaka, Tetsuya & Tachibana, Satoshi & Turner, James A., 2011. "Estimating price and income elasticities of demand for forest products: Cluster analysis used as a tool in grouping," Forest Policy and Economics, Elsevier, vol. 13(6), pages 435-445, July.
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    3. Leamer, Edward E, 1983. "Let's Take the Con Out of Econometrics," American Economic Review, American Economic Association, vol. 73(1), pages 31-43, March.
    4. Leamer, Edward E, 1985. "Sensitivity Analyses Would Help," American Economic Review, American Economic Association, vol. 75(3), pages 308-313, June.
    5. McCloskey, Donald N, 1985. "The Loss Function Has Been Mislaid: The Rhetoric of Significance Tests," American Economic Review, American Economic Association, vol. 75(2), pages 201-205, May.
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    Cited by:

    1. Schier, Franziska & Morland, Christian & Dieter, Matthias & Weimar, Holger, 2021. "Estimating supply and demand elasticities of dissolving pulp, lignocellulose-based chemical derivatives and textile fibres in an emerging forest-based bioeconomy," Forest Policy and Economics, Elsevier, vol. 126(C).
    2. A. I. Pyzhev, 2022. "The Forest Industry of the Regions of Siberia and the Far East: Prospects for the Development of the Forest-Climate Sector," Studies on Russian Economic Development, Springer, vol. 33(4), pages 402-408, August.
    3. Joseph Buongiorno, 2021. "GFPMX: A Cobweb Model of the Global Forest Sector, with an Application to the Impact of the COVID-19 Pandemic," Sustainability, MDPI, vol. 13(10), pages 1-18, May.

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