IDEAS home Printed from https://ideas.repec.org/a/wly/apecpp/v45y2023i3p1356-1373.html
   My bibliography  Save this article

Determinants of downside risk exposure: An analysis of Korean rice farms using partial and quantile moments

Author

Listed:
  • Kedar Kulkarni
  • David Rossi

Abstract

The past decade has seen a resurgence in methods such as the partial and quantile moments model for measuring downside risk exposure and downside risk aversion. However, mixed conclusions are drawn regarding the identification and determinants of downside risk exposure attributable to the methodological differences in the approaches to risk estimation. In this paper, we replicate Kim et al. (2014) who perform a quantile moments‐based analysis of risk exposure. Extending the original study, we address the methodological differences in approaches to measuring downside risk with further robustness checks, including alternative estimation approaches and a comparison to the partial moments model (Antle, 2010). Our results confirm the original finding of Kim et al. (2014) that around 90% of the cost of risk is attributable to downside risk exposure. However, this estimate is highly sensitive to the specification of the estimated mean production as well as the choice of the statistical estimator. Finally, our results suggest that both the quantile moments model and the partial moments model provide similar insights on the determinants of downside risk exposure as well as the cost of risk.

Suggested Citation

  • Kedar Kulkarni & David Rossi, 2023. "Determinants of downside risk exposure: An analysis of Korean rice farms using partial and quantile moments," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 45(3), pages 1356-1373, September.
    • Handle: RePEc:wly:apecpp:v:45:y:2023:i:3:p:1356-1373
    DOI: 10.1002/aepp.13320
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/aepp.13320
    Download Restriction: no
    File URL: https://libkey.io/10.1002/aepp.13320?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. Jean‐Paul Chavas & Salvatore Di Falco, 2012. "On the Role of Risk Versus Economies of Scope in Farm Diversification With an Application to Ethiopian Farms," Journal of Agricultural Economics, Wiley Blackwell, vol. 63(1), pages 25-55, February.
    2. john M. Antle, 2010. "Asymmetry, Partial Moments, and Production Risk," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 92(5), pages 1294-1309.
    3. Jesse Tack & Ardian Harri & Keith Coble, 2012. "More than Mean Effects: Modeling the Effect of Climate on the Higher Order Moments of Crop Yields," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 94(5), pages 1037-1054.
    4. Bruce A. Babcock, 1992. "The Effects of Uncertainty on Optimal Nitrogen Applications," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 14(2), pages 271-280.
    5. Richard E. Just & Rulon D. Pope, 1979. "Production Function Estimation and Related Risk Considerations," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 61(2), pages 276-284.
    6. Wolfram Schlenker & W. Michael Hanemann & Anthony C. Fisher, 2005. "Will U.S. Agriculture Really Benefit from Global Warming? Accounting for Irrigation in the Hedonic Approach," American Economic Review, American Economic Association, vol. 95(1), pages 395-406, March.
    7. Murat Isik & Madhu Khanna, 2003. "Stochastic Technology, Risk Preferences, and Adoption of Site-Specific Technologies," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 85(2), pages 305-317.
    8. Chamberlain, Gary, 1982. "Multivariate regression models for panel data," Journal of Econometrics, Elsevier, vol. 18(1), pages 5-46, January.
    9. J. M. Antle & W. J. Goodger, 1984. "Measuring Stochastic Technology: The Case of Tulare Milk Production," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 66(3), pages 342-350.
    10. Kwansoo Kim & Jean-Paul Chavas & Bradford Barham & Jeremy Foltz, 2014. "Editor's choice Rice, irrigation and downside risk: a quantile analysis of risk exposure and mitigation on Korean farms," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 41(5), pages 775-815.
    11. John M. Antle, 1987. "Econometric Estimation of Producers' Risk Attitudes," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 69(3), pages 509-522.
    12. Kwansoo Kim & Jean-Paul Chavas & Bradford Barham & Jeremy Foltz, 2012. "Specialization, diversification, and productivity: a panel data analysis of rice farms in Korea," Agricultural Economics, International Association of Agricultural Economists, vol. 43(6), pages 687-700, November.
    13. Antle, John M, 1983. "Testing the Stochastic Structure of Production: A Flexible Moment-based Approach," Journal of Business & Economic Statistics, American Statistical Association, vol. 1(3), pages 192-201, July.
    14. Jock R. Anderson, 1973. "Sparse Data, Climatic Variability, and Yield Uncertainty in Response Analysis," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 55(1), pages 77-82.
    15. Edgardo Moscardi & Alain de Janvry, 1977. "Attitudes Toward Risk Among Peasants: An Econometric Approach," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 59(4), pages 710-716.
    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. Luigi Biagini & Simone Severini, 2022. "How Does the Farmer Strike a Balance between Income and Risk across Inputs? An Application in Italian Field Crop Farms," Sustainability, MDPI, vol. 14(23), pages 1-15, December.
    2. Hongliang Zhang & John M. Antle, 2018. "Weather, Climate and Production Risk," IRENE Working Papers 18-01, IRENE Institute of Economic Research.
    3. Mukasa Adamon N., 2016. "Working Paper 233 - Technology Adoption and Risk Exposure among Smallholder Farmers: Panel Data Evidence from Tanzania and Uganda," Working Paper Series 2328, African Development Bank.
    4. Antti Saastamoinen, 2015. "Heteroscedasticity Or Production Risk? A Synthetic View," Journal of Economic Surveys, Wiley Blackwell, vol. 29(3), pages 459-478, July.
    5. Nolan, Elizabeth & Santos, Paulo, 2012. "Insurance premiums and GM traits," 2012 Conference, August 18-24, 2012, Foz do Iguacu, Brazil 125942, International Association of Agricultural Economists.
    6. Ayenew, Habtamu Yesigat & Sauer, Johannes & Abate-Kassa, Getachew, 2016. "Cost of Risk Exposure, Farm Disinvestment and Adaptation to Climate Uncertainties: The Case of Arable Farms in the EU," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235595, Agricultural and Applied Economics Association.
    7. Bozzola, Martina & DiFalco, Salvatore & Finger, Robert, 2017. "Time variant risk preferences in agriculture: evidences from Italy," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258365, Agricultural and Applied Economics Association.
    8. Mukasa, Adamon N., 2018. "Technology adoption and risk exposure among smallholder farmers: Panel data evidence from Tanzania and Uganda," World Development, Elsevier, vol. 105(C), pages 299-309.
    9. Zhang, Hongliang & Antle, John, 2016. "Assessing Climate Vulnerability of Agricultural Systems Using High-order moments: A Case Study in the U.S. Pacific Northwest," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 236233, Agricultural and Applied Economics Association.
    10. Kim, Kwansoo & Chavas, Jean-Paul, 2003. "Technological change and risk management: an application to the economics of corn production," Agricultural Economics, Blackwell, vol. 29(2), pages 125-142, October.
    11. Phoebe Koundouri, 2004. "Current Issues in the Economics of Groundwater Resource Management," Journal of Economic Surveys, Wiley Blackwell, vol. 18(5), pages 703-740, December.
    12. Xavier Vollenweider & Salvatore Di Falco & Cathal O�Donoghue, 2011. "Risk preferences and voluntary agrienvironmental schemes: does risk aversion explain the uptake of the Rural Environment Protection Scheme?," GRI Working Papers 48, Grantham Research Institute on Climate Change and the Environment.
    13. Antle, John, 1987. "Technology and Uncertainty: Evidence from Egypt," 1987 Occasional Paper Series No. 4 197406, International Association of Agricultural Economists.
    14. Mintewab Bezabih & Remidius Ruhinduka & Mare Sarr, 2016. "Climate change perception and system of rice intensification (SRI) impact on dispersion and downside risk: a moment approximation approach," GRI Working Papers 256, Grantham Research Institute on Climate Change and the Environment.
    15. Rosegrant, Mark W. & Roumasset, James A., 1985. "The Effect Of Fertiliser On Risk: A Heteroscedastic Production Function With Measurable Stochastic Inputs," Australian Journal of Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 29(2), pages 1-15, August.
    16. Celine Nauges & Phoebe Koundouri & Vangelis Tzouvelekas, 2004. "Endogenous Technology Adoption Under Production Risk: Theory and Application to Irrigation Technology," Working Papers 0411, University of Crete, Department of Economics.
    17. Siameh, Celestine & Tack, Jesse & Barnett, Barry J. & Harri, Ardian, 2016. "Cotton Premium Rate Heterogeneities and Implications under Climate Change," 2016 Annual Meeting, February 6-9, 2016, San Antonio, Texas 230089, Southern Agricultural Economics Association.
    18. Agarwal, Sandip Kumar, 2017. "Subjective beliefs and decision making under uncertainty in the field," ISU General Staff Papers 201701010800006248, Iowa State University, Department of Economics.
    19. Kassie, Menale & Yesuf, Mahmud & Köhlin, Gunnar, 2008. "The Role of Production Risk in Sustainable Land-Management Technology Adoption in the Ethiopian Highlands," RFF Working Paper Series dp-08-15-efd, Resources for the Future.
    20. Li, Zheng & Rejesus, Roderick M. & Zheng, Xiaoyong, 2018. "Nonparametric Estimation and Inference of Production Risk with Categorical Variables," 2018 Annual Meeting, August 5-7, Washington, D.C. 274400, Agricultural and Applied Economics Association.

    More about this item

    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:wly:apecpp:v:45:y:2023:i:3:p:1356-1373. 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: Wiley Content Delivery (email available below). General contact details of provider: https://doi.org/10.1002/(ISSN)2040-5804 .

    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.