Productivity growth and convergence in the European Union

被引:54
|
作者
Färe, R
Grosskopf, S
Margaritis, D
机构
[1] AUT, Fac Business, Dept Finance, Auckland 1020, New Zealand
[2] Oregon State Univ, Dept Econ, Corvallis, OR 97331 USA
关键词
distance function; Malmquist index; DEA; TFP; productivity convergence;
D O I
10.1007/s11123-006-7134-x
中图分类号
F [经济];
学科分类号
02 ;
摘要
This paper analyses the determinants of labour productivity in the European Union (EU) area and examines the extent to which convergence in output per worker is occurring among Member States (plus Norway) using a recursive common trends analysis and non-parametric kernel density methods. Data Envelopment Analysis (DEA) is used to construct the best practice EU production frontier and compute a Malmquist index of total factor productivity (TFP) and its decomposition to the factors that affect productivity for each country. We consider a pent-partite decomposition of the growth in labour productivity in terms of (i) pure technological change (ii) input biased technical change (iii) efficiency change (iv) growth in human capital and (v) (physical) capital accumulation. This decomposition enables us to gain more insight on patterns of productivity growth for a cross section of countries as well as isolate the individual factor contributions to (or lack of) convergence and common trends for output per worker in the EU area. The use of human capital as an additional input in the description of technology has a small effect in the overall productivity measures but leads to a substantial fall in the contribution of capital accumulation to growth in output per worker for our sample of countries. Furthermore, there is evidence to suggest that the market reforms of the post 1980 period are likely to have induced considerable change in input prices and factor mix which in turn is reflected in input bias. This is evident from the pattern of the shift in the frontier of technology over time and the underlying trends in the components of technological change. Cross section regression analysis suggests that although there appears to be overall convergence in output per worker in the sample of countries, the input bias component of technological change is a source of divergence. Evidence on increasing convergence among the EU countries is also provided via an analysis of the distribution dynamics of output per worker. Non-parametric methods are used to determine the number of modes in the productivity distribution over time. The evidence suggests that the distribution of output per worker in the EU area has changed from bimodal (twin-peak) to unimodal over time. A recursive common stochastic trends analysis provides further evidence of increased convergence in output per worker among groups (convergence 'clubs') of European countries. In particular, the recursive tests show that a common stochastic trend was driving output per worker for the group of small northern European economies (Belgium, Denmark, Luxembourg, Netherlands and Sweden) by the 1990s. Similarly, increased convergence trends were detected for two more groups (1) Greece, Ireland and Portugal and (2) France, Germany and the UK. However, time series tests fail to support the hypothesis that the EU area is a single convergence club.
引用
收藏
页码:111 / 141
页数:31
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