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Wage determination in oligopsonistic labour markets: evidence from Russia and Central Asia. Umid Aliev Supervisors: Prof. Virginie Perotin and Dr. Dan Coffey. What’s on today?. Introduction ‘Modern monopsony’ theories Empirical model Results Limitations. Evidence.
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Wage determination in oligopsonistic labour markets: evidence from Russia and Central Asia Umid Aliev Supervisors: Prof. Virginie Perotin and Dr. Dan Coffey
What’s on today? • Introduction • ‘Modern monopsony’ theories • Empirical model • Results • Limitations
Evidence • Wage dispersion – Bowlus et al. (1995), Machin and Manning (2004), and Bhaskar et al. (2002) • Effect of wages on separation rates – Bhaskar et al. (2002) • Positive relationship between the firm’s wage and its financial performance - Nickell and Wadhwani (1990), Denny and Machin (1991), Abowd and Lemieux (1993) and Blanchflower et al. (1996), Dong (1998) and Christev and FitzRoy (2002)
Evidence Findings of Bowlus et al. (1995), Machin and Manning (2004), and Bhaskar et al. (2002) suggest wage dispersion for such occupations as janitors, day care workers and fast food employees, which are usually unspecialized and non-unionized. Dong (1998) and Clarke (2002) indicate dependence of wage on the employer’s financial characteristics for labour markets of China and Russia respectively, where trade unions are weak and have little participation in wage determination.
- net revenue product of labour for i=0, 1,…., (n-1), where for j=0, 1,…., [n/2] and Modern monopsony td – “transportation” costs Oligopsony by Bhaskar and To (2003) wi – tx ≥ wj – t(1/n-x)
Why is it important? Manning (2004) • Minimum wages • Trade unions • Unemployment benefits • Progressive tax systems The market interventions can actually improve the efficiency.
Russia and Central Asia • Empirical evidence for Russia: Commander et al. (1996), Luke and Schaffer (2000), Clarke (2002), Kapelushnikov (2003), Dohmen et al. (2007), …. • Unorganized labour market for Central Asia.
Data 2005 Business Environment and Enterprise Performance Survey The European Bank for Reconstruction and Development and the World Bank 34 countries – Central and Eastern Europe and former USSR Self-weighted stratified sampling from the national registries
Distance deflation: or Empirical model • Inclusion of control variables: • Industry dummies: vertical differentiation and common effects • Regional dummies: common effects • Percent of university education: quality of a given labour force
Hypotheses • all slope coefficients of the productivity variables will be positive; • largest value will be attained to β1; • β2>β4>β6; • β2>β3; β4>β5; β6>β7.
Limitations • Data: few hundreds of observations for each country – inaccuracy in measuring of Y1(2), Z1(2) and H1(2). • Model specification errors: variable omission