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Estimating the effect of state dependence in work-related training participation among British employees

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  • Panos Sousounis

    (Department of Economics, University of the West of England)

Abstract

Despite the extensive empirical literature documenting the determinants of training participation and a broad consensus on the influence of previous educational attainment on the training participation decision, there is hardly any reference in the applied literature to the role of past experience of training on future participation. This paper presents evidence on the influence of serial persistence in the work-related training participation decision of British employees. Training participation is modelled as a dynamic random effects probit model and estimated using three different approaches proposed in the literature for tackling the initial conditions problem by Heckman (1981), Wooldrgidge (2005) and Orme (2001). The estimates are then compared with those from a dynamic limited probability model using GMM techniques, namely the estimators proposed by Arellano and Bond (1991) and Blundell and Bond (1998). The results suggest a strong state dependence effect, which is robust across estimation methods, rendering previous experience as an important determining factor in employees’ work-related training decision.

Suggested Citation

  • Panos Sousounis, 2009. "Estimating the effect of state dependence in work-related training participation among British employees," Working Papers 0920, Department of Accounting, Economics and Finance, Bristol Business School, University of the West of England, Bristol.
    • Handle: RePEc:uwe:wpaper:0920
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    File URL: http://carecon.org.uk/DPs/0920.pdf
    File Function: First version, 2009
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    References listed on IDEAS

    as
    1. Douglas Holtz-Eakin & Whitney K. Newey & Harvey S. Rosen, 1989. "Implementing Causality Tests with Panel Data, with an Example from LocalPublic Finance," NBER Technical Working Papers 0048, National Bureau of Economic Research, Inc.
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    More about this item

    Keywords

    state dependence; unobserved heterogeneity; training; dynamic panel data models; generalised method of moments;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities

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