دانلود مقاله ISI انگلیسی شماره 11770
عنوان فارسی مقاله

گواهی ها و تخمین مهارت ها و عملکرد رشد بهره وری : مدارک و شواهد میان کشوری در سطح صنایع

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
11770 2012 10 صفحه PDF سفارش دهید محاسبه نشده
خرید مقاله
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عنوان انگلیسی
Certified and uncertified skills and productivity growth performance: Cross-country evidence at industry level
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Labour Economics, Volume 19, Issue 3, June 2012, Pages 351–360

کلمات کلیدی
- سرمایه انسانی - بهره وری - ابتلا - سرریز
پیش نمایش مقاله
پیش نمایش مقاله گواهی ها و تخمین مهارت ها و عملکرد رشد بهره وری : مدارک و شواهد میان کشوری در سطح صنایع

چکیده انگلیسی

We analyse the relationship between human capital and productivity growth using a five-country multi-industry dataset together with a measure of human capital which accounts for both certified skills (educational qualifications) and uncertified skills acquired through on-the-job training and experience. We find evidence of positive human capital effects on growth in average labour productivity, particularly when using our composite human capital measure. We also find some tentative evidence that multi-factor productivity (MFP) growth is positively related to the use of high-skilled labour. However, externalities of this kind are largely confined to industries which make intensive use of university graduates.

مقدمه انگلیسی

Research on the impact of human capital on productivity growth at country level has encountered many difficulties over the years. In a survey of the econometric literature in this area, Sianesi and van Reenen (2003) concluded that, while the evidence of a positive effect for human capital was ‘compelling’, the empirical evidence was nonetheless ‘still weak at various crucial points’ (Sianesi and van Reenen, 2003: 192). In particular, they emphasised the many methodological issues that remained unresolved in this field such as how best to measure skills and how to model possible channels of influence of skills on economic performance. Only a few years later considerable progress has been made in respect of both skills measurement and modelling the potential contribution of skills to performance. For example, de la Fuente and Domenech (2006) have developed new estimates of educational attainments for 21 OECD countries which take care to avoid sharp breaks and implausible changes in measured skill levels over very short periods of time that often derive from changes in primary data collection methods. At the same time Vandenbussche et al. (2006) have built on previous work by Nelson and Phelps (1966) and endogenous growth theorists such as Romer (1990) and Aghion and Howitt (1992) to develop a model in which human capital contributes to multi-factor productivity (MFP) growth in different ways depending on how close countries are to the technological frontier. However, these positive developments have hardly eliminated all the problems associated with measuring the impact of human capital on economic performance at country level. Skill measures based on certified educational attainments are unable to take account of uncertified skills acquired through employment-based training and learning. And, in a recent critique of Vandenbussche et al. (2006), Inklaar et al. (2008) suggest that any positive correlation between human capital and MFP growth at country level disappears if due account is taken in the estimation of MFP of inter-country differences in labour quality and in the number of hours worked. In this paper we present new evidence on the relationship between human capital and productivity growth at industry level, making use of measures of human capital which take account of uncertified as well as certified skills, and which are fully incorporated into quality-adjusted measures of labour inputs. While the construction of quality-adjusted indices of labour is a common practice in growth accounting studies, their use within an econometric framework has been less common.2 Here we use panel methods to estimate models of productivity growth that specify the potential channels of influence by which skills might be expected to influence performance. Our analysis makes use of a cross-country industry-level dataset which contains annual series for output, capital, labour input and workforce skills for 26 industries in five countries (UK, US, France, Germany and the Netherlands) over the period 1979–2000. Using industry-level data for a small number of advanced industrialised countries enables us to work with a more homogeneous sample than many previous cross-national studies of human capital which pooled together countries that were very different in terms of economic development. The difficulties inherent in this approach are discussed by Temple (2001) who also highlights potential differences in the quality of schooling across a wide range of countries. Although educational institutions differ in the countries included in the present study, we show below that we can minimise the effects of such differences in the construction of our human capital variable. Throughout our analysis we undertake a systematic comparison of how our quality-adjusted measure of labour inputs (reflecting uncertified skills as well as certified skills) compares with other measures of human capital based solely on certified skills. Our main findings can be summarised as follows: we find strong evidence of the impact of human capital on average labour productivity, both in the long and in the short run. In the short-run, the analysis needs to allow for a more complex dynamic specification that accounts for the stock of human capital and the distance of countries from the technological frontier. We also find some limited evidence of spillovers onto MFP growth from the use of high-level skills. However, we do not find any support for the argument that such externalities are stronger in countries/industries that are close to the technological frontier. The paper is ordered as follows. In Section 2 we discuss skills measurement issues in detail and outline the theoretical framework underlying the main hypotheses to be tested regarding the impact of human capital on relative labour productivity and MFP growth rates at country/industry level. Section 3 describes our dataset and our benchmark model. 4, 5 and 6 report our results and discuss our main findings on the impact of human capital on productivity growth at country/industry level. Section 7 concludes the paper.

نتیجه گیری انگلیسی

In this paper we have undertaken a detailed analysis of the relationship between human capital and productivity growth using a five-country multi-industry dataset together with a measure of human capital which accounts for both certified skills (educational attainments) and uncertified skills acquired through on-the-job training and experience. Our analysis finds evidence of positive human capital effects on average labour productivity, and also shows that our human capital measure outperforms traditional ones based solely on educational attainment. This work contributes to recent debates about the presence of human capital spillovers and whether such spillovers are stronger in countries closer to the technological frontier. Using a measure of technological proximity which makes appropriate adjustments for inter-country differences in the quality of labour inputs, we find that spillovers from the use of certified high-level skills onto MFP growth are mainly confined to industries which make intensive use of university-educated labour. On the other hand, and in contrast to some other researchers, we find no evidence that the contribution of high-skilled labour to MFP growth is higher, the closer the country is to the technological frontier. It should be noted that our results are based on a relatively homogeneous group of advanced industrial countries and this may partly explain differences from other analyses which include a more diverse set of countries. In addition, our analysis is based on industry data and this level of aggregation might be too high to capture externality effects. Further research would be useful to examine whether the same inferences about human capital externalities emerge from studies based on different units of analysis, such as firm or plant level data, and different specifications of the way human capital spillovers affect productivity.

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