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Driving Regional Economic Models with a Statistical Model: Hypothesis Testing for Economic Impact Analysis

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Listed:
  • Weiler, Stephan

    (Colorado State University)

  • Loomis, John

    (Colorado State University)

  • Richardson, Robby

    (Colorado State University)

  • Shwiff, Stephanie

    (Colorado State University)

Abstract

Policy models such as Input-Output (IO) or Computable General Equilibrium (CGE) are deterministic, with exogenous final demand shocks producing point estimates of local impacts. Confidence intervals around these point estimates, while desirable, are not readily available. Using the causal statistical model to form confidence intervals around the input/shock estimates allows for the configuration of confidence intervals around the output/impact results. The method is demonstrated on a sample policy scenario, which tests the relative significance of population versus climate change as a determinant of local economic activity in Rocky Mountain National Park's gateway community.

Suggested Citation

  • Weiler, Stephan & Loomis, John & Richardson, Robby & Shwiff, Stephanie, 2002. "Driving Regional Economic Models with a Statistical Model: Hypothesis Testing for Economic Impact Analysis," The Review of Regional Studies, Southern Regional Science Association, vol. 32(1), pages 97-111, Winter/Sp.
    • Handle: RePEc:rre:publsh:v:32:y:2002:i:1:p:97-111
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    References listed on IDEAS

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    1. Donald B. K. English, 2000. "Calculating Confidence Intervals for Regional Economic Impacts of Recreation by Bootstrapping Visitor Expenditures," Journal of Regional Science, Wiley Blackwell, vol. 40(3), pages 523-539, August.
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    Cited by:

    1. Weiler, Stephan, 2006. "A park by any other name: National Park designation as a natural experiment in signaling," Journal of Urban Economics, Elsevier, vol. 60(1), pages 96-106, July.
    2. Devkota, Nirmala & Fannin, James Matthew & Paudel, Krishna P., 2006. "Economic Impact Estimation Using Bootstrap Samples Obtained From Internet And Intercept Survey Data," 2006 Annual meeting, July 23-26, Long Beach, CA 21150, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    3. Ya-Yen Sun & Kam-Fai Wong & Hsien-Chung Lai, 2010. "Statistical Properties and Survey Design of Visitor Spending Using Segmentation," Tourism Economics, , vol. 16(4), pages 807-832, December.
    4. Todd M. Gabe & Nicholas A. Lisac, 2014. "A Note on the Effects of Popular Music Concerts on Hospitality Sales: The Case of Waterfront Concerts in Bangor, Maine," The Review of Regional Studies, Southern Regional Science Association, vol. 44(1), pages 61-74, Spring.
    5. Chang Seung & Daniel Lew, 2013. "Accounting for variation in exogenous shocks in economic impact modeling," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 51(3), pages 711-730, December.
    6. Philip Watson & Steve Davies & Dawn Thilmany, 2008. "Determining Economic Contributions in a Recreational Industry," Journal of Sports Economics, , vol. 9(6), pages 571-591, December.
    7. Adam Orens & Andrew Seidl, 2009. "Working Lands and Winter Tourists in the Rocky Mountain West: A Travel Cost, Contingent Behaviour and Input–Output Analysis," Tourism Economics, , vol. 15(1), pages 215-242, March.

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