IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/106098.html
   My bibliography  Save this paper

Modeling of Big Chili Supply Response Using Bayesian Method

Author

Listed:
  • Fajar, Muhammad
  • Winarti, Yuyun Guna

Abstract

This study aims to estimate the response model of Big Chili offerings with the Bayesian method so that information elasticity of price (production) derived from posterior hyperparameter can be obtained. The method used in this study is a supply response model that adopts the Nerlove model and it is estimated with the Bayesian method. The data used in this study are Big Chili production (kg), harvested area (hectares), and Big Chili prices of producer level (IDR/kg) with the period 2008 - 2018 monthly sourced from Statistics Indonesia. The Bayesian method can be applied in the estimation of the Nerlove Model of The Big Chili supply. However, the resulting coefficient of determination is low by 21.05%. The reason is thought to be the use of prior that have a bias effect on posterior distribution and/or there is a nonlinear relationship to the variables in the model. However, only two variables were not significant from the five predictor variables, namely the price of producer level of Big Chili at time t-1 and the production of Big Chili at time t-2. The estimation results of price elasticity in the short and long-term were 8.49% and 2.50%, respectively, which are the inelastic category. It shows that farmers are not responsive to prices. Because the costs of cultivation are high, so it causes the profits obtained by farmers not so much , even though the farm-level prices increase. It becomes insignificant for income farmers.

Suggested Citation

  • Fajar, Muhammad & Winarti, Yuyun Guna, 2020. "Modeling of Big Chili Supply Response Using Bayesian Method," MPRA Paper 106098, University Library of Munich, Germany, revised 21 Dec 2020.
    • Handle: RePEc:pra:mprapa:106098
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/106098/1/MPRA_paper_106098.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Leaver, Rosemary, 2003. "Measuring The Supply Response Function Of Tobacco In Zimbabwe," 2003 Annual Conference, October 2-3, 2003, Pretoria, South Africa 19079, Agricultural Economics Association of South Africa (AEASA).
    2. Braulke, Michael, 1982. "A Note on the Nerlove Model of Agricultural Supply Response," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 23(1), pages 241-244, February.
    3. Marc Nerlove & William Addison, 1958. "Statistical Estimation of Long-Run Elasticities of Supply and Demand," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 40(4), pages 861-880.
    4. Askari, Hossein & Cummings, John Thomas, 1977. "Estimating Agricultural Supply Response with the Nerlove Model: A Survey," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 257-292, June.
    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. Diebold, Francis X. & Lamb, Russell L., 1997. "Why are estimates of agricultural supply response so variable?," Journal of Econometrics, Elsevier, vol. 76(1-2), pages 357-373.
    2. Anbes Tenaye, 2020. "New Evidence Using a Dynamic Panel Data Approach: Cereal Supply Response in Smallholder Agriculture in Ethiopia," Economies, MDPI, vol. 8(3), pages 1-24, July.
    3. Torok, Steven John, 1982. "International trade in commodities and labor: the case of the importation of Mexican agricultural labor and fresh market winter tomatoes into the US, 1964-1979," ISU General Staff Papers 198201010800008550, Iowa State University, Department of Economics.
    4. Md Zabid Iqbal & Bruce A. Babcock, 2018. "Global growing‐area elasticities of key agricultural crops estimated using dynamic heterogeneous panel methods," Agricultural Economics, International Association of Agricultural Economists, vol. 49(6), pages 681-690, November.
    5. Leaver, Rosemary, 2003. "Measuring The Supply Response Function Of Tobacco In Zimbabwe," 2003 Annual Conference, October 2-3, 2003, Pretoria, South Africa 19079, Agricultural Economics Association of South Africa (AEASA).
    6. Leaver, Rosemary, 2004. "Measuring the supply response function of tobacco in Zimbabwe," Agrekon, Agricultural Economics Association of South Africa (AEASA), vol. 43(1), pages 1-19, March.
    7. Magrini, Emiliano & Morales-Opazo, Cristian & Balie, Jean, 2014. "Supply response along the value chain in selected SSA countries: the case of grains," 2014: Food, Resources and Conflict, December 7-9, 2014. San Diego, California 197193, International Agricultural Trade Research Consortium.
    8. Shengying Zhai & Qihui Chen & Wenxin Wang, 2019. "What Drives Green Fodder Supply in China?—A Nerlovian Analysis with LASSO Variable Selection," Sustainability, MDPI, vol. 11(23), pages 1-17, November.
    9. Shoko, R.R. & Chaminuka, P. & Belete, A., 2016. "Estimating the Supply Response of Maize in South Africa: A Nerlovian Partial Adjustment Model Approach," Agrekon, Agricultural Economics Association of South Africa (AEASA), vol. 55(3), September.
    10. Lamb, Russell L., 2000. "Food crops, exports, and the short-run policy response of agriculture in Africa," Agricultural Economics, Blackwell, vol. 22(3), pages 271-298, April.
    11. Rickard, Bradley J. & Gonsalves, Jana L., 2008. "How would compliance with dietary recommendations affect revenues for agricultural producers?," Food Policy, Elsevier, vol. 33(5), pages 422-433, October.
    12. Rickard, Bradley J. & Lei, Lei, 2010. "How important are sanitary and phytosanitary barriers in international markets for fresh fruit?," Working Papers 126974, Cornell University, Department of Applied Economics and Management.
    13. Xie, Lunyu & MacDonald, Sarah L. & Auffhammer, Maximilian & Jaiswal, Deepak & Berck, Peter, 2019. "Environment or food: Modeling future land use patterns of miscanthus for bioenergy using fine scale data," Ecological Economics, Elsevier, vol. 161(C), pages 225-236.
    14. Shumway, C. Richard, 1986. "Supply Relationships In The South - What Have We Learned?," Southern Journal of Agricultural Economics, Southern Agricultural Economics Association, vol. 18(1), pages 1-9, July.
    15. Antony, Nyerere, 2016. "Determinants Of Rice Supply In Tanzania," Research Theses 276426, Collaborative Masters Program in Agricultural and Applied Economics.
    16. Stigler, Matthieu M., 2018. "Supply response at the field-level: disentangling area and yield effects," 2018 Annual Meeting, August 5-7, Washington, D.C. 274343, Agricultural and Applied Economics Association.
    17. Lunyu Xie & Sarah M. Lewis & Maximilian Auffhammer & Peter Berck, 2019. "Heat in the Heartland: Crop Yield and Coverage Response to Climate Change Along the Mississippi River," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 73(2), pages 485-513, June.
    18. Jean-Paul Chavas & Matthew T. Holt, 1990. "Acreage Decisions Under Risk: The Case of Corn and Soybeans," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 72(3), pages 529-538.
    19. Barker, Abigail R. & Mazzucca, Stephanie, 2020. "The differential impact of SSB taxation over time and by income: Evidence from Nielsen Homescan and Retail Data," 2020 Annual Meeting, July 26-28, Kansas City, Missouri 304511, Agricultural and Applied Economics Association.
    20. Burton, Diana M. & Love, H. Alan, 1996. "A Review of Alternative Expectations Regimes in Commodity Markets: Specification, Estimation, and Hypothesis Testing Using Structural Models," Agricultural and Resource Economics Review, Cambridge University Press, vol. 25(2), pages 213-231, October.

    More about this item

    Keywords

    Big Chili; Supply; Nerlove Model; Price Elasticity; Bayesian; Prior;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • Q11 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Aggregate Supply and Demand Analysis; Prices
    • Q21 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Demand and Supply; Prices

    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:pra:mprapa:106098. 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: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.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.