IDEAS home Printed from https://ideas.repec.org/a/spr/endesu/v24y2022i7d10.1007_s10668-021-01821-2.html
   My bibliography  Save this article

An evaluation of subsidy policy impacts, transient and persistent technical efficiency: A case of Mongolia

Author

Listed:
  • Narangerel Ganbold

    (Northwest A&F University)

  • Shah Fahad

    (Leshan Normal University)

  • Hua Li

    (Northwest A&F University)

  • Tumendemberel Gungaa

    (Mongolian University of Life Sciences)

Abstract

Agricultural sector is the backbone of economy in an developing country. Farm households living in rural areas are particularly small-scale farmers and mainly rely on agriculture. Agriculture sector is the highly supported sector by governmental agencies in Mongolia. Although the subsidy–efficiency relationship has been extensively studied in other country contexts, limited studies have discussed that how farm efficiency and productivity are influenced by subsidies; in all studies subsidies are treated as exogenous. In order to fulfill the research gap, this paper specifically analyzes the subsidy payment effects on technical efficiency (TE) of wheat farmers in Mongolia. An unbalanced farm-level data of central arable region farmers from 2013 to 2018 were utilized in this study. We use a four-component stochastic frontier analysis approach that specifically separates the persistent and transient components, by controlling the heterogeneity. The findings of production frontier results indicate that wheat sown area, seed and labor were the main driving inputs for production growth. The investment in machinery has no impact on the output with insignificant technical changes. The overall estimated mean TE was 60% and mean persistent and transient TE were 0.778 and 0.765 respectively, that implies the possible growth in production without increasing the inputs under current technology. Our results further reveal that cash incentives and soft loans for the purchase of inputs have positive affect on overall TE and its transient components. The farm households technical skills toward efficient use of inputs and farming practices need to be improved. The government should take necessary measures related to technology innovations and disaster risk management and further promote the current subsidy policy, efficiency and technical up-gradation in wheat farming.

Suggested Citation

  • Narangerel Ganbold & Shah Fahad & Hua Li & Tumendemberel Gungaa, 2022. "An evaluation of subsidy policy impacts, transient and persistent technical efficiency: A case of Mongolia," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(7), pages 9223-9242, July.
    • Handle: RePEc:spr:endesu:v:24:y:2022:i:7:d:10.1007_s10668-021-01821-2
    DOI: 10.1007/s10668-021-01821-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10668-021-01821-2
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10668-021-01821-2?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Adom, Philip Kofi & Adams, Samuel, 2020. "Decomposition of technical efficiency in agricultural production in Africa into transient and persistent technical efficiency under heterogeneous technologies," World Development, Elsevier, vol. 129(C).
    2. Laure Latruffe & Yann Desjeux, 2016. "Common Agricultural Policy support, technical efficiencyand productivity change in French agriculture," Review of Agricultural, Food and Environmental Studies, INRA Department of Economics, vol. 97(1), pages 15-28.
    3. Fahad, Shah & Jing, Wang, 2018. "Evaluation of Pakistani farmers’ willingness to pay for crop insurance using contingent valuation method: The case of Khyber Pakhtunkhwa province," Land Use Policy, Elsevier, vol. 72(C), pages 570-577.
    4. Caudill, Steven B. & Ford, Jon M., 1993. "Biases in frontier estimation due to heteroscedasticity," Economics Letters, Elsevier, vol. 41(1), pages 17-20.
    5. Karagiannis, Giannis & Sarris, Alexander H., 2002. "Direct Subsidies and Technical Efficiency in Greek Agriculture," 2002 International Congress, August 28-31, 2002, Zaragoza, Spain 24868, European Association of Agricultural Economists.
    6. Marian Rizov & Jan Pokrivcak & Pavel Ciaian, 2013. "CAP Subsidies and Productivity of the EU Farms," Journal of Agricultural Economics, Wiley Blackwell, vol. 64(3), pages 537-557, September.
    7. Subal C. Kumbhakar & Almas Heshmati, 1995. "Efficiency Measurement in Swedish Dairy Farms: An Application of Rotating Panel Data, 1976–88," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 77(3), pages 660-674.
    8. Timothy J. Coelli & D.S. Prasada Rao & Christopher J. O’Donnell & George E. Battese, 2005. "An Introduction to Efficiency and Productivity Analysis," Springer Books, Springer, edition 0, number 978-0-387-25895-9, June.
    9. Lai, Hung-pin & Kumbhakar, Subal C., 2018. "Panel data stochastic frontier model with determinants of persistent and transient inefficiency," European Journal of Operational Research, Elsevier, vol. 271(2), pages 746-755.
    10. Kumbhakar,Subal C. & Wang,Hung-Jen & Horncastle,Alan P., 2015. "A Practitioner's Guide to Stochastic Frontier Analysis Using Stata," Cambridge Books, Cambridge University Press, number 9781107029514, January.
    11. Konstantinos Giannakas & Richard Schoney & Vangelis Tzouvelekas, 2001. "Technical Efficiency, Technological Change and Output Growth of Wheat Farms in Saskatchewan," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 49(2), pages 135-152, July.
    12. Hadri, Kaddour, 1999. "Estimation of a Doubly Heteroscedastic Stochastic Frontier Cost Function," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(3), pages 359-363, July.
    13. Kumbhakar, Subal C & Ghosh, Soumendra & McGuckin, J Thomas, 1991. "A Generalized Production Frontier Approach for Estimating Determinants of Inefficiency in U.S. Dairy Farms," Journal of Business & Economic Statistics, American Statistical Association, vol. 9(3), pages 279-286, July.
    14. Meeusen, Wim & van den Broeck, J, 1977. "Technical Efficiency and Dimension of the Firm: Some Results on the Use of Frontier Production Functions," Empirical Economics, Springer, vol. 2(2), pages 109-122.
    15. Tang, Jianjun & Folmer, Henk & Xue, Jianhong, 2015. "Technical and allocative efficiency of irrigation water use in the Guanzhong Plain, China," Food Policy, Elsevier, vol. 50(C), pages 43-52.
    16. Kumbhakar, Subal C. & Sun, Kai, 2013. "Derivation of marginal effects of determinants of technical inefficiency," Economics Letters, Elsevier, vol. 120(2), pages 249-253.
    17. Lai, Hung-pin & Kumbhakar, Subal C., 2018. "Endogeneity in panel data stochastic frontier model with determinants of persistent and transient inefficiency," Economics Letters, Elsevier, vol. 162(C), pages 5-9.
    18. Caudill, Steven B & Ford, Jon M & Gropper, Daniel M, 1995. "Frontier Estimation and Firm-Specific Inefficiency Measures in the Presence of Heteroscedasticity," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(1), pages 105-111, January.
    19. Boris Bravo-Ureta & Daniel Solís & Víctor Moreira López & José Maripani & Abdourahmane Thiam & Teodoro Rivas, 2007. "Technical efficiency in farming: a meta-regression analysis," Journal of Productivity Analysis, Springer, vol. 27(1), pages 57-72, February.
    20. Wilson, Paul & Hadley, David & Asby, Carol, 2001. "The influence of management characteristics on the technical efficiency of wheat farmers in eastern England," Agricultural Economics, Blackwell, vol. 24(3), pages 329-338, March.
    21. Subal Kumbhakar & Efthymios Tsionas & Timo Sipiläinen, 2009. "Joint estimation of technology choice and technical efficiency: an application to organic and conventional dairy farming," Journal of Productivity Analysis, Springer, vol. 31(3), pages 151-161, June.
    22. Hung-Jen Wang, 2002. "Heteroscedasticity and Non-Monotonic Efficiency Effects of a Stochastic Frontier Model," Journal of Productivity Analysis, Springer, vol. 18(3), pages 241-253, November.
    23. Teresa Serra & David Zilberman & Barry K. Goodwin & Allen Featherstone, 2006. "Effects of decoupling on the mean and variability of output," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 33(3), pages 269-288, September.
    24. Hung-jen Wang & Peter Schmidt, 2002. "One-Step and Two-Step Estimation of the Effects of Exogenous Variables on Technical Efficiency Levels," Journal of Productivity Analysis, Springer, vol. 18(2), pages 129-144, September.
    25. Xueqin Zhu & Alfons Oude Lansink, 2010. "Impact of CAP Subsidies on Technical Efficiency of Crop Farms in Germany, the Netherlands and Sweden," Journal of Agricultural Economics, Wiley Blackwell, vol. 61(3), pages 545-564, September.
    26. Lachaal, Lassaad, 1994. "Subsidies, Endogenous Technical Efficiency And The Measurement Of Productivity Growth," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 26(1), pages 1-12, July.
    27. Laure Latruffe & Hervé Guyomard & Chantal Le Mouël, 2009. "The role of public subsidies on farms’ managerial efficiency: An application of a five-stage approach to France," Working Papers SMART 09-05, INRAE UMR SMART.
    28. Battese, G E & Coelli, T J, 1995. "A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data," Empirical Economics, Springer, vol. 20(2), pages 325-332.
    29. Lachaal, Lassaad, 1994. "Subsidies, Endogenous Technical Efficiency and the Measurement of Productivity Growth," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 26(1), pages 299-310, July.
    30. Karagiannis, Giannis & Tzouvelekas, Vangelis, 2009. "Parametric Measurement of Time-Varying Technical Inefficiency: Results from Competing Models," Agricultural Economics Review, Greek Association of Agricultural Economists, vol. 10(1), pages 1-30.
    31. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
    32. Fahad, Shah & Wang, Jianling, 2018. "Farmers’ risk perception, vulnerability, and adaptation to climate change in rural Pakistan," Land Use Policy, Elsevier, vol. 79(C), pages 301-309.
    33. David Hadley, 2006. "Patterns in Technical Efficiency and Technical Change at the Farm‐level in England and Wales, 1982–2002," Journal of Agricultural Economics, Wiley Blackwell, vol. 57(1), pages 81-100, 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. Yungang Tang & Haojie Liao & Ye Wu & Gang Lei, 2024. "Unravelling the bidirectional impact of Chinese agricultural subsidy policy on agricultural efficiency and farmers' income through panel data analysis," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 70(4), pages 165-177.
    2. Bui Xuan Hong & Masaru Ichihashi & Nguyen Thi Bich Ngoc, 2024. "Analysis of Consumer Preferences for Green Tea Products: A Randomized Conjoint Analysis in Thai Nguyen, Vietnam," Sustainability, MDPI, vol. 16(11), pages 1-17, May.

    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. Ali M. Oumer & Amin Mugera & Michael Burton & Atakelty Hailu, 2022. "Technical efficiency and firm heterogeneity in stochastic frontier models: application to smallholder maize farms in Ethiopia," Journal of Productivity Analysis, Springer, vol. 57(2), pages 213-241, April.
    2. Subal C. Kumbhakar & Christopher F. Parmeter & Valentin Zelenyuk, 2022. "Stochastic Frontier Analysis: Foundations and Advances I," Springer Books, in: Subhash C. Ray & Robert G. Chambers & Subal C. Kumbhakar (ed.), Handbook of Production Economics, chapter 8, pages 331-370, Springer.
    3. Ajayi, Victor & Weyman-Jones, Tom, 2021. "State-level electricity generation efficiency: Do restructuring and regulatory institutions matter in the US?," Energy Economics, Elsevier, vol. 104(C).
    4. Lien, Gudbrand & Kumbhakar, Subal C. & Alem, Habtamu, 2018. "Endogeneity, heterogeneity, and determinants of inefficiency in Norwegian crop-producing farms," International Journal of Production Economics, Elsevier, vol. 201(C), pages 53-61.
    5. Paul, Satya & Shankar, Sriram, 2018. "Modelling Efficiency Effects in a True Fixed Effects Stochastic Frontier," MPRA Paper 87437, University Library of Munich, Germany.
    6. Dipanwita Sarkar & Trevor C. Collier, 2019. "Does host-country education mitigate immigrant inefficiency? Evidence from earnings of Australian university graduates," Empirical Economics, Springer, vol. 56(1), pages 81-106, January.
    7. Galluzzo Nicola, 2020. "A Technical Efficiency Analysis of Financial Subsidies Allocated by the Cap in Romanian Farms Using Stochastic Frontier Analysis," European Countryside, Sciendo, vol. 12(4), pages 494-505, December.
    8. Subal Kumbhakar & Gudbrand Lien & J. Hardaker, 2014. "Technical efficiency in competing panel data models: a study of Norwegian grain farming," Journal of Productivity Analysis, Springer, vol. 41(2), pages 321-337, April.
    9. Efecan, Volkan & Temiz, İzzettin, 2023. "Assessing the technical efficiency of container ports based on a non-monotonic inefficiency effects model," Utilities Policy, Elsevier, vol. 81(C).
    10. Antti Saastamoinen, 2015. "Heteroscedasticity Or Production Risk? A Synthetic View," Journal of Economic Surveys, Wiley Blackwell, vol. 29(3), pages 459-478, July.
    11. Markose Chekol Zewdie & Michele Moretti & Daregot Berihun Tenessa & Zemen Ayalew Ayele & Jan Nyssen & Enyew Adgo Tsegaye & Amare Sewnet Minale & Steven Van Passel, 2021. "Agricultural Technical Efficiency of Smallholder Farmers in Ethiopia: A Stochastic Frontier Approach," Land, MDPI, vol. 10(3), pages 1-17, March.
    12. Hung-Jen Wang, 2002. "Heteroscedasticity and Non-Monotonic Efficiency Effects of a Stochastic Frontier Model," Journal of Productivity Analysis, Springer, vol. 18(3), pages 241-253, November.
    13. Nicola Galluzzo, 2021. "Estimation of the impact of CAP subsidies as environmental variables on Romanian farms," Economia agro-alimentare, FrancoAngeli Editore, vol. 23(3), pages 1-24.
    14. Jorge Galán & Helena Veiga & Michael Wiper, 2014. "Bayesian estimation of inefficiency heterogeneity in stochastic frontier models," Journal of Productivity Analysis, Springer, vol. 42(1), pages 85-101, August.
    15. Minviel, Jean Joseph & De Witte, Kristof, 2017. "The influence of public subsidies on farm technical efficiency: A robust conditional nonparametric approach," European Journal of Operational Research, Elsevier, vol. 259(3), pages 1112-1120.
    16. Giovanni Marin & Alessandro Palma, 2015. "Technology invention and diffusion in residential energy consumption. A stochastic frontier approach," SEEDS Working Papers 1415, SEEDS, Sustainability Environmental Economics and Dynamics Studies, revised Sep 2015.
    17. Latruffe, Laure & Bravo-Ureta, Boris E. & Moreira, Victor H. & Desjeux, Yann & Dupraz, Pierre, 2011. "Productivity and Subsidies in European Union Countries: An Analysis for Dairy Farms Using Input Distance Frontiers," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 114396, European Association of Agricultural Economists.
    18. Gralka, Sabine, 2018. "Stochastic frontier analysis in higher education: A systematic review," CEPIE Working Papers 05/18, Technische Universität Dresden, Center of Public and International Economics (CEPIE).
    19. Christine Amsler & Peter Schmidt & Wen-Jen Tsay, 2015. "A post-truncation parameterization of truncated normal technical inefficiency," Journal of Productivity Analysis, Springer, vol. 44(2), pages 209-220, October.
    20. repec:cte:wsrepe:ws121007 is not listed on IDEAS
    21. Satya Paul & Sriram Shankar, 2020. "Estimating efficiency effects in a panel data stochastic frontier model," Journal of Productivity Analysis, Springer, vol. 53(2), pages 163-180, April.

    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:spr:endesu:v:24:y:2022:i:7:d:10.1007_s10668-021-01821-2. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.