IDEAS home Printed from https://ideas.repec.org/a/eme/caerpp/v7y2015i4p573-600.html
   My bibliography  Save this article

Agricultural productivity growth and drivers: a comparative study of China and India

Author

Listed:
  • Madhur Gautam
  • Bingxin Yu

Abstract

Purpose - – China and India have made significant strides in transforming their agricultural sectors to cut hunger and poverty for the masses through improved agricultural productivity. Given limited land and shift of labor to non-agricultural sector, increasing productivity will continue to be central in agricultural growth in the twenty-first century. The purpose of this paper is to provide comparative analysis of the agricultural total factor productivity (TFP) growth in the two countries. It complements existing literature by examining the evolution and drivers of TFP at disaggregated sub-national level. Richer data allows a deeper understanding of the nature and drivers of TFP growth in the two countries. Design/methodology/approach - – This paper applies different analytical framework to address different research questions using data since 1980. China study estimates a parametric output-based distance function using a translog stochastic frontier function. Productivity growth index and its multiple components are calculated using parameters derived from the parametric approach to identify the characteristics of technology such as structural bias. India study first applies data envelopment analysis to estimate the aggregate productivity growth index, technical change (TC), and efficiency change. Next productivity indexes by for traditional crops are estimated using growth accounting framework at state level. Finally, a panel regression links TFP on its determinants. Findings - – Several common themes emerge from this comparative study. Faced with similar challenges of limited resources and growing demand, improving productivity is the only way to meet long-term food security. Agriculture sector has performed impressively with annual TFP growth beyond 2 percent in China and between 1 and 2 percent in India since the 1980s. The TFP growth is mainly propelled by technological advance but efficiency had been stagnant or even deteriorated. This study provides a granular picture of within country heterogeneity: fast growth in the North and Northeast part of China, South and East of India. Research limitations/implications - – The study suggests some possible policy interventions to improve agricultural productivity, including investment in agricultural R & D to create advanced production technology, effective extension programs and supportive policies to increase efficiency, and diversification from staple crops for sector-wide growth. The India study suggests certain policies may not be contributing much to productivity growth in the long run due to a negative impact on environment. Further studies are needed to expand the productivity analysis to take into consideration of the negative externalities to the society. Data enhancement to account for quality-adjusted inputs could improve the estimation of productivity growth. Originality/value - – Each country study reveals certain prospects of the agricultural sector and production technology. China analysis statistically confirms the existence of technical inefficiency and technology progress, suggests the translog form is appropriate to capture the production technology and satisfies conditions stipulated in theoretical models. The results indicate TC does not influence the contribution of output or input to the production process. India study pinpoints the lagging productivity growth of traditional crops, which still derives growth from input expansion. Although different states benefited from different crops, sector-wide productivity gain is primarily the result of diversification to high-value crops and livestock products.

Suggested Citation

  • Madhur Gautam & Bingxin Yu, 2015. "Agricultural productivity growth and drivers: a comparative study of China and India," China Agricultural Economic Review, Emerald Group Publishing Limited, vol. 7(4), pages 573-600, November.
  • Handle: RePEc:eme:caerpp:v:7:y:2015:i:4:p:573-600
    DOI: 10.1108/CAER-08-2015-0094
    as

    Download full text from publisher

    File URL: https://www.emerald.com/insight/content/doi/10.1108/CAER-08-2015-0094/full/html?utm_source=repec&utm_medium=feed&utm_campaign=repec
    Download Restriction: Access to full text is restricted to subscribers

    File URL: https://www.emerald.com/insight/content/doi/10.1108/CAER-08-2015-0094/full/pdf?utm_source=repec&utm_medium=feed&utm_campaign=repec
    Download Restriction: Access to full text is restricted to subscribers

    File URL: https://libkey.io/10.1108/CAER-08-2015-0094?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.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zhao, Jingfeng & Tang, Jianmin, 2018. "Understanding agricultural growth in China: An international perspective," Structural Change and Economic Dynamics, Elsevier, vol. 46(C), pages 43-51.
    2. Zhihao Zheng & Shen Cheng & Shida R. Henneberry, 2023. "Total factor productivity change in China's grain production sector: 1980–2018," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 67(1), pages 38-55, January.
    3. K. L. Krishna & J. V. Meenakshi, 2022. "Agricultural Productivity Growth and Structural Transformation in Rural India: Some Recent Evidence," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 20(1), pages 277-302, September.
    4. Chengjun Wang & Zhaoyong Zhang & Ximin Fei, 2018. "Efficiency and Risk in Sustaining China’s Food Production and Security: Evidence from Micro-Level Panel Data Analysis of Japonica Rice Production," Sustainability, MDPI, vol. 10(4), pages 1-14, 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:eme:caerpp:v:7:y:2015:i:4:p:573-600. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Emerald Support (email available below). General contact details of provider: .

    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.