IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v11y2019i23p6692-d291164.html
   My bibliography  Save this article

What Drives Green Fodder Supply in China?—A Nerlovian Analysis with LASSO Variable Selection

Author

Listed:
  • Shengying Zhai

    (College of Economics and Management, China Agricultural University, Beijing 100083, China)

  • Qihui Chen

    (College of Economics and Management, China Agricultural University, Beijing 100083, China)

  • Wenxin Wang

    (College of Economics and Management, China Agricultural University, Beijing 100083, China)

Abstract

To understand key factors that drive China’s green fodder supply, this study estimates a Nerlovian partial-adjustment model, using provincial-level panel data spanning two decades (1997–2016). Based on a set of explanatory variables selected by the LASSO (Least Absolute Shrinkage and Selection Operator) method, estimation of the Nerlovian model by the system-GMM (Generalized Method of Moments) method yields three key findings. First, while farmers’ previous cultivation decisions on green fodder supply strongly predict their current decisions, without the influence of other drivers, China’s green fodder supply tends to decline over time. Second, among the identified drivers, government policy plays the most significant role—the availability of subsidies for cultivation of green fodder crops raises the sown area of green fodder crops by more than 30 percent. In contrast, farmer’s sown-area decision is only modestly responsive to price incentives. Finally, while the stock of fixed capital inputs (e.g., number of combine harvesters) and natural disasters (e.g., floods) both affect green fodder supply, their impacts are small.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:23:p:6692-:d:291164
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/11/23/6692/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/11/23/6692/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Cheng, Leilei & Yin, Changbin & Chien, Hsiaoping, 2015. "Demand for milk quantity and safety in urban China: evidence from Beijing and Harbin," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 59(2), April.
    2. van Buuren, Stef & Groothuis-Oudshoorn, Karin, 2011. "mice: Multivariate Imputation by Chained Equations in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 45(i03).
    3. Marc Nerlove, 1979. "The Dynamics of Supply: Retrospect and Prospect," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 61(5), pages 874-888.
    4. Qihui Chen & Gaoshuai Liu & Yumei Liu, 2017. "Can product-information disclosure increase Chinese consumer’s willingness to pay for GM foods? The case of Fad-3 GM lamb," China Agricultural Economic Review, Emerald Group Publishing Limited, vol. 9(3), pages 415-437, September.
    5. Marc Nerlove, 1956. "Estimates of the Elasticities of Supply of Selected Agricultural Commodities," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 38(2), pages 496-509.
    6. Krause, Mark A. & Lee, Jung-Hee & Koo, Won W., 1995. "Program And Nonprogram Wheat Acreage Responses To Prices And Risk," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 20(1), pages 1-12, July.
    7. Ortega, David L. & Wang, H. Holly & Wu, Laping & Hong, Soo Jeong, 2015. "Retail channel and consumer demand for food quality in China," China Economic Review, Elsevier, vol. 36(C), pages 359-366.
    8. Kazim Konyar & Keith Knapp, 1988. "Market analysis of alfalfa hay: California case," Agribusiness, John Wiley & Sons, Ltd., vol. 4(3), pages 271-284.
    9. Hausman, Jerry, 2015. "Specification tests in econometrics," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 38(2), pages 112-134.
    10. Tao Yang, Dennis, 2004. "Education and allocative efficiency: household income growth during rural reforms in China," Journal of Development Economics, Elsevier, vol. 74(1), pages 137-162, June.
    11. Marc Nerlove, 1958. "Distributed lags and Estimation of Long-Run Supply and Demand Elasticities: Theoretical Considerations," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 40(2), pages 301-310.
    12. Leilei Cheng & Changbin Yin & Hsiaoping Chien, 2015. "Demand for milk quantity and safety in urban China: evidence from Beijing and Harbin," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 59(2), pages 275-287, April.
    13. Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2014. "High-Dimensional Methods and Inference on Structural and Treatment Effects," Journal of Economic Perspectives, American Economic Association, vol. 28(2), pages 29-50, Spring.
    14. Yi, Fujin & Sun, Dingqiang & Zhou, Yingheng, 2015. "Grain subsidy, liquidity constraints and food security—Impact of the grain subsidy program on the grain-sown areas in China," Food Policy, Elsevier, vol. 50(C), pages 114-124.
    15. 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.
    16. Hal R. Varian, 2014. "Big Data: New Tricks for Econometrics," Journal of Economic Perspectives, American Economic Association, vol. 28(2), pages 3-28, Spring.
    17. Russell Lidman & D. Lee Bawden, 1974. "The Impact of Government Programs on Wheat Acreage," Land Economics, University of Wisconsin Press, vol. 50(4), pages 327-335.
    18. Dikshit, A.K. & Birthal, Pratap Singh, 2010. "India’s Livestock Feed Demand: Estimates and Projections," Agricultural Economics Research Review, Agricultural Economics Research Association (India), vol. 23(1), January.
    19. Arellano, Manuel & Bover, Olympia, 1995. "Another look at the instrumental variable estimation of error-components models," Journal of Econometrics, Elsevier, vol. 68(1), pages 29-51, July.
    20. Haile, Mekbib G & Kalkuhl, Matthias & Usman, Muhammed A, 2015. "Market information and smallholder farmer price expectations," African Journal of Agricultural and Resource Economics, African Association of Agricultural Economists, vol. 10(4), pages 1-15, December.
    21. B. J. Morzuch & R. D. Weaver & P. G. Helmberger, 1980. "Wheat Acreage Supply Response under Changing Farm Programs," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 62(1), pages 29-37.
    22. Mordecai Ezekiel, 1938. "The Cobweb Theorem," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 52(2), pages 255-280.
    23. Garst, Gail D. & Miller, Thomas A., 1975. "Impact of the Set-Aside Program on the U.S. Wheat Acreages," Journal of Agricultural Economics Research, United States Department of Agriculture, Economic Research Service, vol. 27(2), pages 1-8, April.
    24. Shonkwiler, John Scott & Hinckley, Suzanne, 1985. "A Generalized Supply Response/Factor Demand Model And Its Application To The Feeder Cattle Market," Western Journal of Agricultural Economics, Western Agricultural Economics Association, vol. 10(2), pages 1-9, December.
    25. Sendhil Mullainathan & Jann Spiess, 2017. "Machine Learning: An Applied Econometric Approach," Journal of Economic Perspectives, American Economic Association, vol. 31(2), pages 87-106, Spring.
    26. Bazen, Ernest F. & Roberts, Roland K. & Travis, John & Larson, James A., 2008. "Factors Affecting Hay Supply and Demand in Tennessee," 2008 Annual Meeting, February 2-6, 2008, Dallas, Texas 6889, Southern Agricultural Economics Association.
    27. Wickens, M R & Greenfield, J N, 1973. "The Econometrics of Agricultural Supply: An Application to the World Coffee Market," The Review of Economics and Statistics, MIT Press, vol. 55(4), pages 433-440, November.
    28. 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.
    29. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(2), pages 277-297.
    30. 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.
    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. 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.

    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. 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.
    2. 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.
    3. Skold, Karl Durwood, 1989. "The integration of alternative information systems: an application to the Hogs and Pigs report," ISU General Staff Papers 1989010108000010239, 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. Donato, Romano & Carraro, Alessandro, 2015. "Modelling Acreage, Production and Yield Supply Response to Domestic Price Volatility," 2015 Fourth Congress, June 11-12, 2015, Ancona, Italy 207278, Italian Association of Agricultural and Applied Economics (AIEAA).
    6. Amina Al Naabi & Shekar Bose, 2020. "Do Regulatory Measures Necessarily Affect Oman’s Seafood Export-Supply?," SAGE Open, , vol. 10(3), pages 21582440209, August.
    7. Magrini, Emiliano & Balié, Jean & Morales Opazo, Cristian, 2016. "Price signals and supply responses for staple food crops in SSA countries," DARE Discussion Papers 1601, Georg-August University of Göttingen, Department of Agricultural Economics and Rural Development (DARE).
    8. Mundlak, Yair, 1985. "The Aggregate Agricultural Supply," Working Papers 232646, Hebrew University of Jerusalem, Center for Agricultural Economic Research.
    9. Langley, James A., 1983. "Regional acreage response functions for major US field crops: estimation and policy implications," ISU General Staff Papers 198301010800008678, Iowa State University, Department of Economics.
    10. Jessica M. Mc Lay & Roy Lay-Yee & Barry J. Milne & Peter Davis, 2015. "Regression-Style Models for Parameter Estimation in Dynamic Microsimulation: An Empirical Performance Assessment," International Journal of Microsimulation, International Microsimulation Association, vol. 8(2), pages 83-127.
    11. Huy Quang Doan, 2019. "Trade, Institutional Quality and Income: Empirical Evidence for Sub-Saharan Africa," Economies, MDPI, vol. 7(2), pages 1-23, May.
    12. Broich, Tobias, 2017. "Do authoritarian regimes receive more Chinese development finance than democratic ones? Empirical evidence for Africa," China Economic Review, Elsevier, vol. 46(C), pages 180-207.
    13. Abdul Latif Alhassan & Nicholas Biekpe, 2017. "Liberalization Outcomes and Competitive Behaviour in an Emerging Insurance Market," African Development Review, African Development Bank, vol. 29(2), pages 122-138, June.
    14. Neifar, Malika, 2020. "Interest-free versus Conventional banks- A Comparative Study using Linear and Nonlinear Panel Regression: Empirical Evidence from Turky and 6 MENA countries," MPRA Paper 101028, University Library of Munich, Germany.
    15. Vassilis Tselios, 2008. "Income and educational inequalities in the regions of the European Union: Geographical spillovers under welfare state restrictions," Papers in Regional Science, Wiley Blackwell, vol. 87(3), pages 403-430, August.
    16. Stephanos Papadamou & Moïse Sidiropoulos & Eleftherios Spyromitros, 2017. "Is There a Role for Central Bank Independence on Public Debt Dynamics?," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 7(1), pages 1-6.
    17. Mukhopadhyay, Jhuma & Chakraborty, Indrani, 2017. "Foreign institutional investment, business groups and firm performance: Evidence from India," Research in International Business and Finance, Elsevier, vol. 39(PA), pages 454-465.
    18. Croux, Christophe & Jagtiani, Julapa & Korivi, Tarunsai & Vulanovic, Milos, 2020. "Important factors determining Fintech loan default: Evidence from a lendingclub consumer platform," Journal of Economic Behavior & Organization, Elsevier, vol. 173(C), pages 270-296.
    19. Cândida Ferreira, 2021. "Financial development and macroeconomic performance: a panel data approach," Working Papers REM 2021/0173, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.
    20. Liobikienė, Genovaitė & Butkus, Mindaugas, 2017. "Environmental Kuznets Curve of greenhouse gas emissions including technological progress and substitution effects," Energy, Elsevier, vol. 135(C), pages 237-248.

    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:gam:jsusta:v:11:y:2019:i:23:p:6692-:d:291164. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.