IDEAS home Printed from https://ideas.repec.org/a/ags/joaaec/43420.html
   My bibliography  Save this article

Issues and Strategies for Aggregate Supply Response Estimation for Policy Analyses

Author

Listed:
  • Ramirez, Octavio A.
  • Mohanty, Samarendu
  • Carpio, Carlos E.
  • Denning, Megan

Abstract

We demonstrate the use of the small-sample econometrics principles and strategies to come up with reliable yield and acreage models for policy analyses. We focus on demonstrating the importance of proper representation of systematic and random components of the model for improving forecasting precision along with more reliable confidence intervals for the forecasts. A probability distribution function modeling approach, which has been shown to provide more reliable confidence intervals for the dependent variable forecasts than the standard models that assume error term normality, is used to estimate cotton supply response in the Southeastern United States.

Suggested Citation

  • Ramirez, Octavio A. & Mohanty, Samarendu & Carpio, Carlos E. & Denning, Megan, 2004. "Issues and Strategies for Aggregate Supply Response Estimation for Policy Analyses," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 36(2), pages 1-17, August.
    • Handle: RePEc:ags:joaaec:43420
    DOI: 10.22004/ag.econ.43420
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/43420/files/Ramirez2%20JAAE%20August%202004.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.43420?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
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Ramirez, Octavio A. & Fadiga, Mohamadou L., 2003. "Forecasting Agricultural Commodity Prices with Asymmetric-Error GARCH Models," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 28(1), pages 1-15, April.
    2. Octavio A. Ramirez & Sukant Misra & James Field, 2003. "Crop-Yield Distributions Revisited," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 85(1), pages 108-120.
    3. Ramirez, Octavio A. & Somarriba, Eduardo, 2000. "Risk And Returns Of Diversified Cropping Systems Under Nonnormal, Cross-, And Autocorrelated Commodity Price Structures," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 25(2), pages 1-16, December.
    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. Capps, Oral, Jr. & Williams, Gary W., 2006. "The Economic Effectiveness of the Cotton Checkoff Program," Reports 90753, Texas A&M University, Agribusiness, Food, and Consumer Economics Research Center.

    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. Gregory Colson & Octavio A. Ramirez & Shengfei Fu, 2014. "Crop Insurance Savings Accounts: A Viable Alternative to Crop Insurance?," Applied Economic Perspectives and Policy, Agricultural and Applied Economics Association, vol. 36(3), pages 527-545.
    2. Ramirez, Octavio A., 2014. "Appendix II to: Crop Insurance Savings Accounts: A Viable Alternative to Crop Insurance?," Applied Economic Perspectives and Policy Appendices 162319, Agricultural and Applied Economics Association.
    3. Jesus Crespo Cuaresma & Ines Fortin & Jaroslava Hlouskova & Michael Obersteiner, 2024. "Regime‐dependent commodity price dynamics: A predictive analysis," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(7), pages 2822-2847, November.
    4. Jesse B. Tack & David Ubilava, 2015. "Climate and agricultural risk: measuring the effect of ENSO on U.S. crop insurance," Agricultural Economics, International Association of Agricultural Economists, vol. 46(2), pages 245-257, March.
    5. Tao XIONG & Chongguang LI & Yukun BAO, 2017. "An improved EEMD-based hybrid approach for the short-term forecasting of hog price in China," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 63(3), pages 136-148.
    6. David A. Hennessy, 2009. "Crop Yield Skewness Under Law of the Minimum Technology," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 91(1), pages 197-208.
    7. Huang, Pei & McCarl, Bruce A., 2014. "Estimating Decadal Climate Variability Effects on Crop Yields: A Bayesian Hierarchical Approach," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 169828, Agricultural and Applied Economics Association.
    8. Chen, Shu-Ling & Miranda, Mario J., 2006. "Modeling Yield Distribution In High Risk Counties: Application To Texas Upland Cotton," 2006 Annual meeting, July 23-26, Long Beach, CA 21392, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    9. Lei Xu & Qiao Zhang & Xi Zhang, 2011. "Evaluating agricultural catastrophic risk," China Agricultural Economic Review, Emerald Group Publishing Limited, vol. 3(4), pages 451-461, November.
    10. Li, Shuang & Ker, Alan P., 2013. "An Assessment of the Canadian Federal-Provincial Crop Production Insurance Program under Future Climate Change Scenarios in Ontario," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 151213, Agricultural and Applied Economics Association.
    11. Vitor A. Ozaki & Sujit K. Ghosh & Barry K. Goodwin & Ricardo Shirota, 2008. "Spatio-Temporal Modeling of Agricultural Yield Data with an Application to Pricing Crop Insurance Contracts," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 90(4), pages 951-961.
    12. Jesse Tack & David Ubilava, 2013. "The effect of El Niño Southern Oscillation on U.S. corn production and downside risk," Climatic Change, Springer, vol. 121(4), pages 689-700, December.
    13. Ramirez, Octavio A. & Carpio, Carlos E. & Collart, Alba J., 2014. "Producer Welfare Implications of the RMA’s “Shrinkage” Crop Insurance Premium Estimator," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 168367, Agricultural and Applied Economics Association.
    14. Jesus Crespo Cuaresma & Jaroslava Hlouskova & Michael Obersteiner, 2021. "Agricultural commodity price dynamics and their determinants: A comprehensive econometric approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(7), pages 1245-1273, November.
    15. Gerlt, Scott & Thompson, Wyatt & Miller, Douglas, 2014. "Exploiting the Relationship between Farm-Level Yields and County-Level Yields for Applied Analysis," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 39(2), pages 1-18.
    16. Duarte, Gislaine Vieira & Ozaki, Vitor Augusto, 2019. "Pricing Crop Revenue Insurance using Parametric Copulas," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 73(3), September.
    17. Jing Wang & Feng Fang & Qiang Zhang & Jinsong Wang & Yubi Yao & Wei Wang, 2016. "Risk evaluation of agricultural disaster impacts on food production in southern China by probability density method," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 83(3), pages 1605-1634, September.
    18. Ramirez, Octavio & Shonkwiler, J. Scott, 2016. "Some Comparative Statics for Evaluating the Performance of the US Crop Insurance Program," SCC-76 Meeting, 2016, March 17-19, Pensacola, Florida 233761, SCC-76: Economics and Management of Risk in Agriculture and Natural Resources.
    19. ARAUJO ENCISO Sergio Rene & PIERALLI SIMONE & PEREZ DOMINGUEZ Ignacio, 2017. "Partial Stochastic Analysis with the Aglink-Cosimo Model: A Methodological Overview," JRC Research Reports JRC108837, Joint Research Centre.
    20. Ozaki, Vitor Augusto & Olinda, Ricardo & Faria, Priscila Neves & Campos, Rogério Costa, 2014. "Estimation of the Agricultural Probability of Loss: evidence for soybean in Paraná State," Revista de Economia e Sociologia Rural (RESR), Sociedade Brasileira de Economia e Sociologia Rural, vol. 52(1), January.

    More about this item

    JEL classification:

    • Q11 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Aggregate Supply and Demand Analysis; Prices
    • Q18 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Policy; Food Policy; Animal Welfare Policy
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

    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:joaaec:43420. 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/saeaaea.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.