IDEAS home Printed from https://ideas.repec.org/a/jed/journl/v29y2004i2p107-130.html
   My bibliography  Save this article

An Econometric Model Of Employment In Zimbabwe¡¯S Manufacturing Industries

Author

Listed:
  • Almas Heshmati

    () (MTT Economic Research)

  • Mkhululi Ncube

    (Gothenburg University)

Abstract

This paper is concerned with the estimation of employment relationship and employment efficiency under production risk using a panel of Zimbabwe¡¯s manufacturing industries. A flexible labour demand function is used consisting of two parts: the traditional labour demand function and labour demand variance function. Labour demand is a function of wages, output, quasi-fixed inputs and time variables. The variance function is a function of the determinants of labour demand and a number of production and policy characteristic variables. Estimation of industry and time-varying employment efficiency is also considered. The empirical results show that the average employment efficiency is 92%.

Suggested Citation

  • Almas Heshmati & Mkhululi Ncube, 2004. "An Econometric Model Of Employment In Zimbabwe¡¯S Manufacturing Industries," Journal of Economic Development, Chung-Ang Unviersity, Department of Economics, vol. 29(2), pages 107-130, December.
  • Handle: RePEc:jed:journl:v:29:y:2004:i:2:p:107-130
    as

    Download full text from publisher

    File URL: http://www.jed.or.kr/full-text/29-2/Almas_Heshamati.pdf
    Download Restriction: no

    References listed on IDEAS

    as
    1. Heshmati, Almas, 1994. "Estimating random effects production function models with selectivity bias: an application to Swedish crop producers," Agricultural Economics, Blackwell, vol. 11(2-3), pages 171-189, December.
    2. Kumbhakar, Sabul C., 1993. "Production risk, technical efficiency, and panel data," Economics Letters, Elsevier, vol. 41(1), pages 11-16.
    3. Just, Richard E. & Pope, Rulon D., 1978. "Stochastic specification of production functions and economic implications," Journal of Econometrics, Elsevier, vol. 7(1), pages 67-86, February.
    4. 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.
    5. 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.
    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. Almas Heshmati & Ilham Haouas, 2011. "Employment Efficiency and Production Risk in the Tunisian Manufacturing Industries," Working Papers 602, Economic Research Forum, revised 07 Jan 2011.

    More about this item

    Keywords

    Labour demand; Variance; Efficiency; Manufacturing; Industries; Zimbabwe;

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • E24 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity

    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:jed:journl:v:29:y:2004:i:2:p:107-130. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Sung Y. Park). General contact details of provider: http://edirc.repec.org/data/eccaukr.html .

    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 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.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.