IDEAS home Printed from https://ideas.repec.org/p/ags/cudawp/250035.html

The Economic Impacts of Climate Change on Agriculture: Accounting for Time-invariant Unobservables in the Hedonic Approach

Author

Listed:
  • Ortiz-Bobea, Ariel

Abstract

I propose a strategy of measuring the long-run economic impact of climate change on farmland values that tackles the elusive problem of time-invariant spatially-dependent unobservables in the hedonic approach. The strategy exploits that a county’s agricultural productivity is primarily influenced by its own climate, and the fact that climate assignment appears random conditional on average county-neighborhood characteristics. Results suggest that large impacts of climate change on US agriculture seem unlikely. Findings are robust to multiple checks and cannot be attributed to measurement error. Ignoring such confounders considerably overstates long-run climate change impacts on the sector.

Suggested Citation

  • Ortiz-Bobea, Ariel, 2016. "The Economic Impacts of Climate Change on Agriculture: Accounting for Time-invariant Unobservables in the Hedonic Approach," Working Papers 250035, Cornell University, Department of Applied Economics and Management.
    • Handle: RePEc:ags:cudawp:250035
    DOI: 10.22004/ag.econ.250035
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/250035/files/Cornell-Dyson-wp1615.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.250035?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Kelejian, Harry H & Prucha, Ingmar R, 1999. "A Generalized Moments Estimator for the Autoregressive Parameter in a Spatial Model," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 40(2), pages 509-533, May.
    2. Conley, T. G., 1999. "GMM estimation with cross sectional dependence," Journal of Econometrics, Elsevier, vol. 92(1), pages 1-45, September.
    3. Griliches, Zvi & Hausman, Jerry A., 1986. "Errors in variables in panel data," Journal of Econometrics, Elsevier, vol. 31(1), pages 93-118, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. DePaula, Guilherme, 2020. "The distributional effect of climate change on agriculture: Evidence from a Ricardian quantile analysis of Brazilian census data," Journal of Environmental Economics and Management, Elsevier, vol. 104(C).
    2. Arellano Gonzalez, Jesus, "undated". "Estimating climate change damages in data scarce and non-competitive settings: a novel version of the Ricardian approach with an application to Mexico," 2018 Annual Meeting, August 5-7, Washington, D.C. 274010, Agricultural and Applied Economics Association.
    3. Frederick Quaye & Denis Nadolnyak & Valentina Hartarska, 2018. "Climate Change Impacts on Farmland Values in the Southeast United States," Sustainability, MDPI, vol. 10(10), pages 1-16, September.
    4. Ariel Ortiz-Bobea, 2021. "Climate, Agriculture and Food," Papers 2105.12044, arXiv.org.
    5. Guilherme DePaula, 2018. "The Distributional Impact of Climate Change in Brazilian Agriculture: A Ricardian Quantile Analysis with Census Data," Center for Agricultural and Rural Development (CARD) Publications 18-wp583, Center for Agricultural and Rural Development (CARD) at Iowa State University.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. David A. McGranahan & Timothy R. Wojan & Dayton M. Lambert, 2011. "The rural growth trifecta: outdoor amenities, creative class and entrepreneurial context -super-§," Journal of Economic Geography, Oxford University Press, vol. 11(3), pages 529-557, May.
    2. Frank Davenport, 2017. "Estimating standard errors in spatial panel models with time varying spatial correlation," Papers in Regional Science, Wiley Blackwell, vol. 96, pages 155-177, March.
    3. Bhattacharjee, Arnab & Jensen-Butler, Chris, 2013. "Estimation of the spatial weights matrix under structural constraints," Regional Science and Urban Economics, Elsevier, vol. 43(4), pages 617-634.
    4. Arnab Bhattacharjee & Sean Holly, 2011. "Structural interactions in spatial panels," Empirical Economics, Springer, vol. 40(1), pages 69-94, February.
    5. Lee, Jungyoon & Robinson, Peter M., 2016. "Series estimation under cross-sectional dependence," Journal of Econometrics, Elsevier, vol. 190(1), pages 1-17.
    6. Heder Oliveira & Rafael Costa e Sousa & Edson Paulo Domingues, 2007. "Regional Development and Brazilian Constitutional Funds," EcoMod2007 23900061, EcoMod.
    7. Jungyoon Lee & Peter Robinson, 2016. "Series estimation under cross-sectional dependence," LSE Research Online Documents on Economics 63380, London School of Economics and Political Science, LSE Library.
    8. Matias Mayor Fernandez & Esteban Fernandez Vazquez & Jorge Rodriguez Valez, 2006. "Spatial Structures and Spatial Spillovers: A GME Approach," ERSA conference papers ersa06p777, European Regional Science Association.
    9. Bester, C. Alan & Conley, Timothy G. & Hansen, Christian B., 2011. "Inference with dependent data using cluster covariance estimators," Journal of Econometrics, Elsevier, vol. 165(2), pages 137-151.
    10. Harald Badinger & Peter Egger, 2015. "Fixed Effects and Random Effects Estimation of Higher-order Spatial Autoregressive Models with Spatial Autoregressive and Heteroscedastic Disturbances," Spatial Economic Analysis, Taylor & Francis Journals, vol. 10(1), pages 11-35, March.
    11. Holly, Sean & Hashem Pesaran, M. & Yamagata, Takashi, 2011. "The spatial and temporal diffusion of house prices in the UK," Journal of Urban Economics, Elsevier, vol. 69(1), pages 2-23, January.
    12. López, Fernando & Matilla-García, Mariano & Mur, Jesús & Marín, Manuel Ruiz, 2010. "A non-parametric spatial independence test using symbolic entropy," Regional Science and Urban Economics, Elsevier, vol. 40(2-3), pages 106-115, May.
    13. repec:ebl:ecbull:v:3:y:2005:i:29:p:1-10 is not listed on IDEAS
    14. Harald Badinger & Peter Egger, 2009. "Estimation of Higher-Order Spatial Autoregressive Panel Data Error Component Models," CESifo Working Paper Series 2556, CESifo.
    15. Peter M Robinson, 2009. "Developments in the Analysis of Spatial Data," STICERD - Econometrics Paper Series 531, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    16. Lambert, Dayton M. & Florax, Raymond J.G.M. & Cho, Seong-Hoon, 2008. "Bandwidth Selection For Spatial Hac And Other Robust Covariance Estimators," Working papers 44258, Purdue University, Department of Agricultural Economics.
    17. Wang, Honglin & Iglesias, Emma M. & Wooldridge, Jeffrey M., 2013. "Partial maximum likelihood estimation of spatial probit models," Journal of Econometrics, Elsevier, vol. 172(1), pages 77-89.
    18. Sebastian Hauptmeier & Ferdinand Mittermaier & Johannes Rincke, 2008. "Fiscal Competition over Taxes and Public Inputs: Theory and Evidence," CESifo Working Paper Series 2499, CESifo.
    19. Bai, Jushan & Li, Kunpeng, 2013. "Spatial panel data models with common shocks," MPRA Paper 52786, University Library of Munich, Germany, revised 09 Mar 2014.
    20. repec:asg:wpaper:1045 is not listed on IDEAS
    21. Natalia Bailey & Sean Holly & M. Hashem Pesaran, 2016. "A Two‐Stage Approach to Spatio‐Temporal Analysis with Strong and Weak Cross‐Sectional Dependence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(1), pages 249-280, January.
    22. William C. Horrace & Kurt E. Schnier, 2010. "Fixed-Effect Estimation of Highly Mobile Production Technologies," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 92(5), pages 1432-1445.

    More about this item

    Keywords

    ;
    ;

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ags:cudawp:250035. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/dacorus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.