IDEAS home Printed from https://ideas.repec.org/p/ags/aaea02/19589.html

Climate Change And Crop Yield Distribution: Some New Evidence From Panel Data Models And Implications For Crop Insurance

Author

Listed:
  • Chang, Ching-Cheng
  • Chen, Chi-Chung

Abstract

This study examines the impact of climate on yield for seven major crops in Taiwan based on a pooled panel data of 15 counties over the period 1977-1996. Unit-root tests and maximum likelihood methods are explored to obtain reliable estimates. Results suggest that climate has diversified impacts on crop yields and their variability. A simple crop insurance model by Ahsan, Ali, and Kurian (1982) is shown how crop yield distribution can be the base to calculate the premium and indemnity.

Suggested Citation

  • Chang, Ching-Cheng & Chen, Chi-Chung, 2002. "Climate Change And Crop Yield Distribution: Some New Evidence From Panel Data Models And Implications For Crop Insurance," 2002 Annual meeting, July 28-31, Long Beach, CA 19589, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    • Handle: RePEc:ags:aaea02:19589
    DOI: 10.22004/ag.econ.19589
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/19589/files/sp02ch01.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.19589?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. Baltagi, Badi H. & Li, Qi, 1995. "Testing AR(1) against MA(1) disturbances in an error component model," Journal of Econometrics, Elsevier, vol. 68(1), pages 133-151, July.
    2. Chang, Ching-Cheng, 2002. "The potential impact of climate change on Taiwan's agriculture," Agricultural Economics, Blackwell, vol. 27(1), pages 51-64, May.
    3. Mendelsohn, Robert & Nordhaus, William D & Shaw, Daigee, 1994. "The Impact of Global Warming on Agriculture: A Ricardian Analysis," American Economic Review, American Economic Association, vol. 84(4), pages 753-771, September.
    4. Richard E. Just & Quinn Weninger, 1999. "Are Crop Yields Normally Distributed?," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 81(2), pages 287-304.
    5. Atanu Saha & Arthur Havenner & Hovav Talpaz, 1997. "Stochastic production function estimation: small sample properties of ML versus FGLS," Applied Economics, Taylor & Francis Journals, vol. 29(4), pages 459-469.
    6. Robert K. Kaufmann & Seth E. Snell, 1997. "A Biophysical Model of Corn Yield: Integrating Climatic and Social Determinants," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 79(1), pages 178-190.
    7. Dickey, David A & Fuller, Wayne A, 1981. "Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root," Econometrica, Econometric Society, vol. 49(4), pages 1057-1072, June.
    8. Arellano, Manuel, 1993. "On the testing of correlated effects with panel data," Journal of Econometrics, Elsevier, vol. 59(1-2), pages 87-97, September.
    9. Wayne I. Park & Thomas R. Sinclair, 1993. "Consequences of Climate and Crop Yield Limits on the Distribution of Corn Yields," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 15(3), pages 483-493.
    10. Levin, Andrew & Lin, Chien-Fu & James Chu, Chia-Shang, 2002. "Unit root tests in panel data: asymptotic and finite-sample properties," Journal of Econometrics, Elsevier, vol. 108(1), pages 1-24, May.
    11. Quah, Danny, 1994. "Exploiting cross-section variation for unit root inference in dynamic data," Economics Letters, Elsevier, vol. 44(1-2), pages 9-19.
    Full references (including those not matched with items on IDEAS)

    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. M.Abimbola OYINLOLA & Luwatosin ADENIYI & Nd Festus O.EGWAIKHIDE*, 2011. "Purchasing Power Parity Hypothesis in the Selected African Countries," Pakistan Journal of Applied Economics, Applied Economics Research Centre, vol. 21, pages 93-110.
    2. Hüseyin Kalyoncu, 2006. "International Intertemporal Solvency in OECD Countries: Evidence from Panel Unit Root," Prague Economic Papers, Prague University of Economics and Business, vol. 2006(1), pages 44-49.
    3. Nieh, Chien-Chung & Ho, Tsung-wu, 2006. "Does the expansionary government spending crowd out the private consumption?: Cointegration analysis in panel data," The Quarterly Review of Economics and Finance, Elsevier, vol. 46(1), pages 133-148, February.
    4. Raju Guntukula & Phanindra Goyari, 2020. "Climate Change Effects on the Crop Yield and Its Variability in Telangana, India," Studies in Microeconomics, , vol. 8(1), pages 119-148, June.
    5. Chang, Yoosoon, 2012. "Taking a new contour: A novel approach to panel unit root tests," Journal of Econometrics, Elsevier, vol. 169(1), pages 15-28.
    6. Eftychia Tsanana & Constantinos Katrakilidis, 2014. "Do Balkan economies catch up with EU? New evidence from panel unit root analysis," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 41(4), pages 641-662, November.
    7. Zhongwen Liang, 2017. "A Unified Approach on the Local Power of Panel Unit Root Tests," Papers 1710.02944, arXiv.org.
    8. Raza, Amar & Ahmad, Munir, 2015. "Analysing the Impact of Climate Change on Cotton Productivity in Punjab and Sindh, Pakistan," MPRA Paper 72867, University Library of Munich, Germany.
    9. Luciano Gutierrez, 2003. "Common and idiosyncratic shocks to labor productivity across sectors and countries: Is climate relevant?," Macroeconomics 0311008, University Library of Munich, Germany.
    10. Shahbaz Bhatti & Sarfraz Hassan & Khalid Mushtaq & Kamran Javed, 2020. "Investigation The Impact Of Climate Change On Productivity Of Cotton: Empirical Evidence From Cotton Zone," Big Data In Agriculture (BDA), Zibeline International Publishing, vol. 2(1), pages 1-4, February.
    11. Mathieu Juliot Mpabe Bodjongo, 2022. "Climate Change, Cotton Prices and Production in Cameroon," The European Journal of Development Research, Palgrave Macmillan;European Association of Development Research and Training Institutes (EADI), vol. 34(1), pages 22-50, February.
    12. Deressa, T. & Hassan, Rashid M. & Poonyth, Daneswar, 2005. "Measuring the impact of climate change on South African agriculture: The case of sugar-cane growing regions," Agrekon, Agricultural Economics Association of South Africa (AEASA), vol. 44(4), pages 1-19, December.
    13. Win Chou & Dominica Lee, 2005. "Panel Cointegration Analysis of Audit Pricing Model," Review of Quantitative Finance and Accounting, Springer, vol. 24(4), pages 423-439, June.
    14. Jacobo Campo Robledo & Henry Antonio Mendoza Tolosa, 2014. "Gasto Público y Crecimiento Económico regional en Colombia (1984 - 2012)," Documentos de Trabajo 12425, Universidad Católica de Colombia.
    15. Cristina Brasili & Luciano Gutierrez, 2004. "Regional convergence across European Union," Development and Comp Systems 0402002, University Library of Munich, Germany.
    16. Chang, Yoosoon, 2004. "Bootstrap unit root tests in panels with cross-sectional dependency," Journal of Econometrics, Elsevier, vol. 120(2), pages 263-293, June.
    17. Wilman-Santiago Ochoa-Moreno & Byron Alejandro Quito & Carlos Andrés Moreno-Hurtado, 2021. "Foreign Direct Investment and Environmental Quality: Revisiting the EKC in Latin American Countries," Sustainability, MDPI, vol. 13(22), pages 1-18, November.
    18. Tsangyao Chang & Wen-Chi Liu & Goodness C. Aye & Rangan Gupta, 2016. "Are there housing bubbles in South Africa? Evidence from SPSM-based panel KSS test with a Fourier function," Global Business and Economics Review, Inderscience Enterprises Ltd, vol. 18(5), pages 517-532.
    19. Ortiz-­Bobea, Ariel, "undated". "Understanding Temperature and Moisture Interactions in the Economics of Climate Change Impacts and Adaptation on Agriculture," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 150435, Agricultural and Applied Economics Association.
    20. Chebli Mongi & Kais Saidi, 2024. "The Impact of Corruption, Government Effectiveness, FDI, and GFC on Economic Growth: New Evidence from Global Panel of 48 Middle-Income Countries," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(3), pages 10696-10721, September.

    More about this item

    Keywords

    ;
    ;
    ;

    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:aaea02:19589. 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/aaeaaea.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.