IDEAS home Printed from https://ideas.repec.org/a/emx/esteco/v20y2005i1p53-78.html
   My bibliography  Save this article

Crecimiento y la paradoja de la productividad: Una estimación en la forma de state-space con componentes no observables para el sector agropecuario argentino, 1955-2003

Author

Listed:
  • Luis Lanteri

    (Banco Central de Argentina)

Abstract

We estimate the total factor productivity for argentine agriculture over the period 1955 to 2003. One method of quantifying the impact of productivity is the use of growth accounting index numbers (Divisia index). However, some papers (see, for example, Hsieh, 2000) show that if technological change is not Hicks neutral then conventional total factor productivity index is not a satisfactory measure of this indicator, since that observed cost shares conflates the contribution of factor accumulation to output growth with that of technological change. In this paper, cost share equation system in the form of state-space model with latent variables are used to detect technological biased and to estimate the total factor productivity adjusted.

Suggested Citation

  • Luis Lanteri, 2005. "Crecimiento y la paradoja de la productividad: Una estimación en la forma de state-space con componentes no observables para el sector agropecuario argentino, 1955-2003," Estudios Económicos, El Colegio de México, Centro de Estudios Económicos, vol. 20(1), pages 53-78.
  • Handle: RePEc:emx:esteco:v:20:y:2005:i:1:p:53-78
    as

    Download full text from publisher

    File URL: https://estudioseconomicos.colmex.mx/index.php/economicos/article/view/168/170
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Kuo S. Huang, 1991. "Factor Demands in the U.S. Food-Manufacturing Industry," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 73(3), pages 615-620.
    2. A. Bailey & K. Balcombe & J. Morrison & C. Thirtle, 2003. "A comparison of proxy variable and stochastic latent variable approaches to the measurement of bias in technological change in south african agriculture," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 12(4), pages 315-324.
    3. Esposti, Roberto & Pierani, Pierpaolo, 1997. "The Source of Technical Change in Italian Agriculture: A Latent Variable Approach," Staff Papers 200593, University of Wisconsin-Madison, Department of Agricultural and Applied Economics.
    4. Olmstead, Alan L & Rhode, Paul, 1993. "Induced Innovation in American Agriculture: A Reconsideration," Journal of Political Economy, University of Chicago Press, vol. 101(1), pages 100-118, February.
    5. Elías, Victor Jorge, 1985. "Government expenditures on agriculture and agricultural growth in Latin America:," Research reports 50, International Food Policy Research Institute (IFPRI).
    6. Bailey, Alastair & Irz, Xavier T. & Balcombe, Kelvin George, 2003. "An Appliation Of The Stochastic Latent Variable Approach To The Correction Of Sector Level Tfp Calculations In The Face Of Biased Technological Change," 2003 Annual Meeting, August 16-22, 2003, Durban, South Africa 25842, International Association of Agricultural Economists.
    7. J. Stephen Clark & Curtis E. Youngblood, 1992. "Estimating Duality Models with Biased Technical Change: A Time Series Approach," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 74(2), pages 353-360.
    8. Subhash C. Sharma, 2002. "The Morishima Elasticity of Substitution for the Variable Profit Function and the Demand for Imports in the United States," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 43(1), pages 115-135, February.
    9. Blackorby, Charles & Russell, R Robert, 1989. "Will the Real Elasticity of Substitution Please Stand Up? (A Comparison of the Allen/Uzawa and Morishima Elasticities)," American Economic Review, American Economic Association, vol. 79(4), pages 882-888, September.
    10. Chambers,Robert G., 1988. "Applied Production Analysis," Cambridge Books, Cambridge University Press, number 9780521314275, January.
    11. Archibald, Sandra O. & Brandt, Loren, 1991. "A flexible model of factor biased technological change An application to Japanese agriculture," Journal of Development Economics, Elsevier, vol. 35(1), pages 127-145, January.
    12. Felipe, Jesus & McCombie, J. S. L., 2001. "Biased Technical Change, Growth Accounting, and the Conundrum of the East Asian Miracle," Journal of Comparative Economics, Elsevier, vol. 29(3), pages 542-565, September.
    13. Stevenson, Rodney, 1980. "Measuring Technological Bias," American Economic Review, American Economic Association, vol. 70(1), pages 162-173, March.
    14. David K. Lambert & J.S. Shonkwiler, 1995. "Factor Bias under Stochastic Technical Change," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 77(3), pages 578-590.
    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. Bailey, Alastair & Irz, Xavier T. & Balcombe, Kelvin George, 2003. "An Appliation Of The Stochastic Latent Variable Approach To The Correction Of Sector Level Tfp Calculations In The Face Of Biased Technological Change," 2003 Annual Meeting, August 16-22, 2003, Durban, South Africa 25842, International Association of Agricultural Economists.
    2. Bailey, Alastair & Irz, Xavier & Balcombe, Kelvin, 2004. "Measuring productivity growth when technological change is biased--a new index and an application to UK agriculture," Agricultural Economics, Blackwell, vol. 31(2-3), pages 285-295, December.
    3. Getu Hailu & John Cranfield & Rawlin Thangaraj, 2010. "Do U.S. food processors respond to sweetener-related health information?," Agribusiness, John Wiley & Sons, Ltd., vol. 26(3), pages 348-368.
    4. Lundmark, Robert & Olsson, Anna, 2015. "Factor substitution and procurement competition for forest resources in Sweden," International Journal of Production Economics, Elsevier, vol. 169(C), pages 99-109.
    5. Fernando S. Machado, 1995. "Testing The Induced Innovation Hypothesis Using Cointegration Analysis," Journal of Agricultural Economics, Wiley Blackwell, vol. 46(3), pages 349-360, September.
    6. Napasintuwong, Orachos & Emerson, Robert D., 2004. "Labor Substitutability In Labor Intensive Agriculture And Technological Change In The Presence Of Foreign Labor," 2004 Annual meeting, August 1-4, Denver, CO 20048, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    7. Roberto Esposti, 2000. "Stochastic Technical Change and Procyclical TFP The Case of Italian Agriculture," Journal of Productivity Analysis, Springer, vol. 14(2), pages 119-141, September.
    8. Liu, Qinghua & Shumway, C. Richard, 2003. "Induced Innovation Tests On Western American Agriculture: A Cointegration Analysis," 2003 Annual meeting, July 27-30, Montreal, Canada 22237, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    9. Esposti, Roberto & Pierani, Pierpaolo, 1997. "The Source of Technical Change in Italian Agriculture: A Latent Variable Approach," Staff Papers 200593, University of Wisconsin-Madison, Department of Agricultural and Applied Economics.
    10. K. K. Gary Wong & Belton M. Fleisher & Min Qiang Zhao & William H. McGuire, 2022. "Technical progress and induced innovation in China: a variable profit function approach," Journal of Productivity Analysis, Springer, vol. 57(2), pages 177-191, April.
    11. Balcombe, Kelvin George & Bailey, Alastair & Morrison, Jamie & Rapsomanikis, George & Thirtle, Colin G., 2000. "Stochastic biases in technical change in South African agriculture," Agrekon, Agricultural Economics Association of South Africa (AEASA), vol. 39(4), pages 1-9, December.
    12. Qingsong Tian & Lukas Cechura & J. Stephen Clark & Yan Yu, 2023. "Induced innovation and spillover effects of US and Canadian research expenditures in Canadian agriculture," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 71(2), pages 153-169, June.
    13. Frank W. Agbola & Stephen R. Harrison, 2005. "Empirical investigation of investment behaviour in Australia's pastoral region," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 49(1), pages 47-62, March.
    14. Townsend, Rob F. & van Zyl, Johan & Thirtle, Colin G., 1997. "Machinery and labour biases of technical change in South African agriculture: A cost function approach," Agrekon, Agricultural Economics Association of South Africa (AEASA), vol. 36(4), pages 1-9, December.
    15. Elisabetta Magnani & David Prentice, 2006. "Unionization and Input Flexibility in U.S. Manufacturing, 1973 – 1996," ILR Review, Cornell University, ILR School, vol. 59(3), pages 386-407, April.
    16. David Stern, 2011. "Elasticities of substitution and complementarity," Journal of Productivity Analysis, Springer, vol. 36(1), pages 79-89, August.
    17. Paul, Saumik, 2019. "A Decline in Labor's Share with Capital Accumulation and Complementary Factor Inputs: An Application of the Morishima Elasticity of Substitution," IZA Discussion Papers 12219, Institute of Labor Economics (IZA).
    18. Arnade, Carlos A., 1992. "Productivity of Brazilian Agriculture: Measurement and Uses," Staff Reports 278673, United States Department of Agriculture, Economic Research Service.
    19. Giulia BETTIN & Alessia LO TURCO & Daniela MAGGIONI, 2011. "A firm level perspective on migration," Working Papers 360, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    20. Ma, Chunbo & Stern, David I., 2016. "Long-run estimates of interfuel and interfactor elasticities," Resource and Energy Economics, Elsevier, vol. 46(C), pages 114-130.

    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:emx:esteco:v:20:y:2005:i:1:p:53-78. 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: Ximena Varela (email available below). General contact details of provider: https://edirc.repec.org/data/cecolmx.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.