IDEAS home Printed from https://ideas.repec.org/a/bla/ajarec/v68y2024i3p701-712.html
   My bibliography  Save this article

Estimating the productivity of US agriculture: The Fisher total factor productivity index for time series data with unknown prices

Author

Listed:
  • Thanh Ngo
  • David Tripe
  • Duc Khuong Nguyen

Abstract

In this paper, we propose a straightforward way to estimate the Fisher ideal total factor productivity (TFP) index (FI) in cases where price information is unavailable, using ‘shadow prices’ derived from data envelopment analysis (DEA). A Monte Carlo experiment shows that the shadow price Fisher ideal TFP index (SPFI) can effectively estimate the ‘true’ FI with relatively small (and stable) errors. The empirical application to the US agriculture sector (1948–2017) further suggests that the SPFI is a (superior) alternative to the traditional Malmquist DEA, especially in dealing with unbalanced panel or time series data when price data are unknown.

Suggested Citation

  • Thanh Ngo & David Tripe & Duc Khuong Nguyen, 2024. "Estimating the productivity of US agriculture: The Fisher total factor productivity index for time series data with unknown prices," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 68(3), pages 701-712, July.
    • Handle: RePEc:bla:ajarec:v:68:y:2024:i:3:p:701-712
    DOI: 10.1111/1467-8489.12565
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/1467-8489.12565
    Download Restriction: no
    File URL: https://libkey.io/10.1111/1467-8489.12565?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
    ---><---

    References listed on IDEAS

    as
    1. Giraleas, Dimitris & Emrouznejad, Ali & Thanassoulis, Emmanuel, 2012. "Productivity change using growth accounting and frontier-based approaches – Evidence from a Monte Carlo analysis," European Journal of Operational Research, Elsevier, vol. 222(3), pages 673-683.
    2. Thanh Ngo & Hung V. Vu & Huong Ho & Thuy T. T. Dao & Hai T. H. Nguyen, 2019. "Performance of Fish Farms in Vietnam–Does Financial Access Help Improve Their Cost Efficiency?," IJFS, MDPI, vol. 7(3), pages 1-10, August.
    3. Alois Kneip & Léopold Simar & Paul W. Wilson, 2016. "Testing Hypotheses in Nonparametric Models of Production," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(3), pages 435-456, July.
    4. Fabio A. Madau & Roberto Furesi & Pietro Pulina, 2017. "Technical efficiency and total factor productivity changes in European dairy farm sectors," Agricultural and Food Economics, Springer;Italian Society of Agricultural Economics (SIDEA), vol. 5(1), pages 1-14, December.
    5. Alejandro Plastina & Sergio H. Lence & Ariel Ortiz‐Bobea, 2021. "How weather affects the decomposition of total factor productivity in U.S. agriculture," Agricultural Economics, International Association of Agricultural Economists, vol. 52(2), pages 215-234, March.
    6. Cross, Robin M. & Färe, Rolf, 2009. "Value data and the Bennet price and quantity indicators," Economics Letters, Elsevier, vol. 102(1), pages 19-21, January.
    7. Helmi Hammami & Thanh Ngo & David Tripe & Dinh-Tri Vo, 2022. "Ranking with a Euclidean common set of weights in data envelopment analysis: with application to the Eurozone banking sector," Annals of Operations Research, Springer, vol. 311(2), pages 675-694, April.
    8. Zhiyong Li & Chen Feng & Ying Tang, 2022. "Bank efficiency and failure prediction: a nonparametric and dynamic model based on data envelopment analysis," Annals of Operations Research, Springer, vol. 315(1), pages 279-315, August.
    9. Per Andersen & Niels Christian Petersen, 1993. "A Procedure for Ranking Efficient Units in Data Envelopment Analysis," Management Science, INFORMS, vol. 39(10), pages 1261-1264, October.
    10. Alexakis, Christos & Izzeldin, Marwan & Johnes, Jill & Pappas, Vasileios, 2019. "Performance and productivity in Islamic and conventional banks: Evidence from the global financial crisis," Economic Modelling, Elsevier, vol. 79(C), pages 1-14.
    11. Caves, Douglas W & Christensen, Laurits R & Diewert, W Erwin, 1982. "The Economic Theory of Index Numbers and the Measurement of Input, Output, and Productivity," Econometrica, Econometric Society, vol. 50(6), pages 1393-1414, November.
    12. Silva Portela, Maria Conceição A., 2014. "Value and quantity data in economic and technical efficiency measurement," Economics Letters, Elsevier, vol. 124(1), pages 108-112.
    13. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    14. Mao, Weining & Koo, Won W., 1997. "Productivity growth, technological progress, and efficiency change in chinese agriculture after rural economic reforms: A DEA approach," China Economic Review, Elsevier, vol. 8(2), pages 157-174.
    15. Yoonhwan Oh & Dong-hyun Oh & Jeong-Dong Lee, 2017. "A sequential global Malmquist productivity index: Productivity growth index for unbalanced panel data considering the progressive nature of technology," Empirical Economics, Springer, vol. 52(4), pages 1651-1674, June.
    16. Fare, Rolf & Grosskopf, Shawna, 1992. "Malmquist Productivity Indexes and Fisher Ideal Indexes," Economic Journal, Royal Economic Society, vol. 102(410), pages 158-160, January.
    17. Timo Kuosmanen & Timo Sipiläinen, 2009. "Exact decomposition of the Fisher ideal total factor productivity index," Journal of Productivity Analysis, Springer, vol. 31(3), pages 137-150, June.
    18. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    19. Liu, John S. & Lu, Louis Y.Y. & Lu, Wen-Min & Lin, Bruce J.Y., 2013. "A survey of DEA applications," Omega, Elsevier, vol. 41(5), pages 893-902.
    20. Dyson, R. G. & Allen, R. & Camanho, A. S. & Podinovski, V. V. & Sarrico, C. S. & Shale, E. A., 2001. "Pitfalls and protocols in DEA," European Journal of Operational Research, Elsevier, vol. 132(2), pages 245-259, July.
    21. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    22. Timo Kuosmanen & Thierry Post & Timo Sipiläinen, 2004. "Shadow Price Approach to Total Factor Productivity Measurement: With an Application to Finnish Grass-Silage Production," Journal of Productivity Analysis, Springer, vol. 22(1), pages 95-121, July.
    23. Thiam, Abdourahmane & Bravo-Ureta, Boris E. & Rivas, Teodoro E., 2001. "Technical efficiency in developing country agriculture: a meta-analysis," Agricultural Economics, Blackwell, vol. 25(2-3), pages 235-243, September.
    24. W. Diewert & Alice Nakamura, 2003. "Index Number Concepts, Measures and Decompositions of Productivity Growth," Journal of Productivity Analysis, Springer, vol. 19(2), pages 127-159, April.
    25. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
    26. Fare, Rolf & Shawna Grosskopf & Mary Norris & Zhongyang Zhang, 1994. "Productivity Growth, Technical Progress, and Efficiency Change in Industrialized Countries," American Economic Review, American Economic Association, vol. 84(1), pages 66-83, March.
    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. Mai, Nhat Chi, 2015. "Efficiency of the banking system in Vietnam under financial liberalization," OSF Preprints qsf6d, Center for Open Science.
    2. Nocera Alves Junior, Paulo & Costa Melo, Isotilia & de Moraes Santos, Rodrigo & da Rocha, Fernando Vinícius & Caixeta-Filho, José Vicente, 2022. "How did COVID-19 affect green-fuel supply chain? - A performance analysis of Brazilian ethanol sector," Research in Transportation Economics, Elsevier, vol. 93(C).
    3. Sebastian Kohl & Jan Schoenfelder & Andreas Fügener & Jens O. Brunner, 2019. "The use of Data Envelopment Analysis (DEA) in healthcare with a focus on hospitals," Health Care Management Science, Springer, vol. 22(2), pages 245-286, June.
    4. Adel Hatami-Marbini & Aliasghar Arabmaldar & John Otu Asu, 2022. "Robust productivity growth and efficiency measurement with undesirable outputs: evidence from the oil industry," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 44(4), pages 1213-1254, December.
    5. Aparicio, Juan & López-Torres, Laura & Santín, Daniel, 2018. "Economic crisis and public education. A productivity analysis using a Hicks-Moorsteen index," Economic Modelling, Elsevier, vol. 71(C), pages 34-44.
    6. Zhao, Yu & Morita, Hiroshi & Maruyama, Yukihiro, 2019. "The measurement of productive performance with consideration for allocative efficiency," Omega, Elsevier, vol. 89(C), pages 21-39.
    7. Mariano, Enzo Barberio & Sobreiro, Vinicius Amorim & Rebelatto, Daisy Aparecida do Nascimento, 2015. "Human development and data envelopment analysis: A structured literature review," Omega, Elsevier, vol. 54(C), pages 33-49.
    8. Holý, Vladimír, 2024. "Ranking-based second stage in data envelopment analysis: An application to research efficiency in higher education," Operations Research Perspectives, Elsevier, vol. 12(C).
    9. Mousavi, Mohammad M. & Ouenniche, Jamal & Xu, Bing, 2015. "Performance evaluation of bankruptcy prediction models: An orientation-free super-efficiency DEA-based framework," International Review of Financial Analysis, Elsevier, vol. 42(C), pages 64-75.
    10. Tran, Trung Hieu & Mao, Yong & Nathanail, Paul & Siebers, Peer-Olaf & Robinson, Darren, 2019. "Integrating slacks-based measure of efficiency and super-efficiency in data envelopment analysis," Omega, Elsevier, vol. 85(C), pages 156-165.
    11. Tingting Yang & Xuefeng Guan & Yuehui Qian & Weiran Xing & Huayi Wu, 2019. "Efficiency Evaluation of Urban Road Transport and Land Use in Hunan Province of China Based on Hybrid Data Envelopment Analysis (DEA) Models," Sustainability, MDPI, vol. 11(14), pages 1-18, July.
    12. Chen, Chien-Ming, 2013. "Super efficiencies or super inefficiencies? Insights from a joint computation model for slacks-based measures in DEA," European Journal of Operational Research, Elsevier, vol. 226(2), pages 258-267.
    13. Arabi, Behrouz & Munisamy, Susila & Emrouznejad, Ali & Toloo, Mehdi & Ghazizadeh, Mohammad Sadegh, 2016. "Eco-efficiency considering the issue of heterogeneity among power plants," Energy, Elsevier, vol. 111(C), pages 722-735.
    14. repec:lan:wpaper:1031 is not listed on IDEAS
    15. Apostolos Christopoulos & Ioannis Dokas & Sofia Katsimardou & Eleftherios Spyromitros, 2022. "The Malmquist Productivity measure for UK-listed firms in the aftermath of the global financial crisis," Operational Research, Springer, vol. 22(2), pages 1617-1634, April.
    16. Joohwan Kim & Hwayoung Kim, 2021. "Evaluation of the Efficiency of Maritime Transport Using a Network Slacks-Based Measure (SBM) Approach: A Case Study on the Korean Coastal Ferry Market," Sustainability, MDPI, vol. 13(11), pages 1-17, May.
    17. E Thanassoulis & M Kortelainen & G Johnes & J Johnes, 2011. "Costs and efficiency of higher education institutions in England: a DEA analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(7), pages 1282-1297, July.
    18. Victoria Wojcik & Harald Dyckhoff & Marcel Clermont, 2019. "Is data envelopment analysis a suitable tool for performance measurement and benchmarking in non-production contexts?," Business Research, Springer;German Academic Association for Business Research, vol. 12(2), pages 559-595, December.
    19. Arabmaldar, Aliasghar & Sahoo, Biresh K. & Ghiyasi, Mojtaba, 2023. "A generalized robust data envelopment analysis model based on directional distance function," European Journal of Operational Research, Elsevier, vol. 311(2), pages 617-632.
    20. Chen, Nengcheng & Xu, Lei & Chen, Zeqiang, 2017. "Environmental efficiency analysis of the Yangtze River Economic Zone using super efficiency data envelopment analysis (SEDEA) and tobit models," Energy, Elsevier, vol. 134(C), pages 659-671.
    21. Dimitrios Giokas & Nicolaos Eriotis & Ioannis Dokas, 2015. "Efficiency and productivity of the food and beverage listed firms in the pre-recession and recessionary periods in Greece," Applied Economics, Taylor & Francis Journals, vol. 47(19), pages 1927-1941, April.

    More about this item

    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:bla:ajarec:v:68:y:2024:i:3:p:701-712. 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: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/aaresea.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.