Labour quality and ICT capital skill complementarity: International comparisons Mary OMahony NIESR.

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Presentation transcript:

Labour quality and ICT capital skill complementarity: International comparisons Mary OMahony NIESR

Introduction Summary of two strands of research –Growth accounting: using data from M. OMahony and B. van Ark eds, EU Productivity and Competitiveness: An Industry Perspective –Labour Demand (Econometric) M.OMahony, C.Robinson and M.Vecchi The Impact of ICT on the Demand for Skilled Labour: A cross-country comparison

Data: Divide labour into a number of types of skills (country specific)

Data US: Current Population Survey (microdata) UK: Labour Force Survey (microdata) France: Labour Force Survey (INSEE tabulations) Germany: Employment & wage and salary statistics (Statistiches Bundesamt tabulations)

Growth Accounting Results, Market Economy average percentage points per annum

Market Economy

Manufacturing

ICT Producing Manufacturing (office machinery, electrical & electronic equipment, instruments)

Distribution (wholesale and retail)

Financial services

Business Services

Other Services

Capital-Skill complementarity Panel Regressions US, UK, France, Germany , sectoral datasets for each country (~30 industries) Employment, value added, ICT capital and non-ICT capital and skills as above (exception Germany – six categories from microzensus)

Specification Employment share equations Estimated separately for each country Estimated for the whole period, and then split between the 1980s and 1990s Also wage share equations for US, UK and France

Results – US employment HigherAssociate degree Some college, no degree High School Graduation No Qualifications Model I k/y0.019 (0.011) (0.003) (0.008) * (0.014) (0.006) ICTk/K0.009* (0.003) 0.004* (0.001) 0.007* (0.002) (0.004) * (0.003) Model II k/y* (0.013) * (0.002) (0.008) * (0.015) 0.036* (0.013) k/y* * (0.010) (0.007) (0.013) (0.016) * (0.009) ICTk/K* * (0.002) 0.004* (0.000) 0.008* (0.001) (0.004) * (0.005) ICTk/K* (0.007) (0.002) (0.004) (0.013) (0.004)

Results – UK employment HigherNVQ 4NVQ 3NVQ12No qualifications Model 1 k/y0.053* (0.015) 0.013* (0.006) (0.064) (0.075) (0.051) ICTk/K0.003 (0.003) (0.002) (0.006) 0.025* (0.009) (0.016) Model 2 k/y* (0.021) (0.026) (0.108) (0.064) * (0.067) k/y* * (0.014) (0.013) (0.061) (0.100) (0.034) ICTk/K* (0.007) (0.006) (0.007) 0.026* (0.005) (0.019) ICTk/K* * (0.006) 0.010* (0.002) (0.011) (0.018) * (0.019)

Results – French employment HigherBaccalaur eate +2yrs Baccalaur eate Voc. qualification General Education No qualification Model 1 k/y (0.018) (0.017) 0.026* (0.012) (0.022) (0.015) (0.039) ICTk/K0.025 (0.013) 0.034* (0.010) (0.016) (0.020) (0.007) * (0.016) Model 2 k/y* (0.022) (0.017) 0.044* (0.021) 0.066* (0.033) (0.042) * (0.050) k/y* (0.025) (0.023) (0.018) (0.038) (0.015) (0.054) ICTk/K* (0.012) 0.026* (0.008) 0.015* (0.006) (0.021) (0.012) * (0.012) ICTk/K* * (0.013) 0.040* (0.012) (0.024) (0.020) (0.008) * (0.016)

Results – German employment HigherTechnical degree Vocational (high) Vocational intermediate Vocational (low) No qualification Model 1 k/y0.003 (0.002) (0.002) (0.002) (0.001) (0.007) (0.006) ICTk/K0.002 (0.002) 0.002* (0.001) (0.002) 0.002* (0.001) 0.021* (0.005) * (0.005) Model 2 k/y* (0.003) (0.002) (0.004) (0.003) (0.016) (0.016) k/y* (0.002) 0.003* (0.002) 0.003* (0.001) (0.001) (0.007) (0.005) ICTk/K* (0.001) (0.001) (0.001) 0.002* (0.001) 0.024* (0.005) * (0.004) ICTk/K* (0.003) (0.001) (0.003) 0.002* (0.001) 0.018* (0.008) * (0.010)

Conclusions In all countries the low skilled have seen a loss in employment share and wage share ICT has had a positive and generally significant impact on numbers of the highest skilled workers Similar results found for wage share equations Timings vary considerably between countries, with the US showing the first and clearest signs of an ICT impact on the demand for skilled labour

Conclusions Further work Controlling for age and gender, small impacts in UK and US but do not change conclusions Testing for structural changes Future Research Estimate industry by industry – country panel Consider time series properties