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This research paper aims to provide an empirical validation of the impact of human capital accumulation and labour market institutions on productivity growth. The primary objective of this study is to analyse economic and employment growth tendencies in the period between 1985 and 2007 in various OECD member countries. In our estimations we followed a specific taxonomy to identify the features of output per capita growth in different labour-skilled branches. Besides determining the sectoral differences of labour demand by standard comparative statistics, we used a dynamic panel regression method to investigate the relationships between employment, human capital, labour institutions, and output per capita. We conclude that the high-skilled branches have achieved better economic growth performance than the lower-skilled ones in most of the OECD countries. Analysing the time series panel data of these countries our results also yield valid relationships between the level of education, labour unions and productivity growth in different branches.

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Panel Data: Monte Carlo Evidence and an Application to Employment Equations. Review Economics Studies , 58: 277–297. Bond S. Some Tests of Specification for Panel Data: Monte

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. CPB Working Paper , 1–103. Ederveen, S. — Groot, H. de — Nahuis, R. (2006): Fertile soil for structural funds? A panel data analysis of the conditional effectiveness of European Cohesion Policy. KYLOS , 59

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The paper tests the hypothesis on whether refined economic value added (REVA) is highly associated with stock return compared to traditional performance measures. The goal of the study is to provide empirical evidence on the relative and incremental information content of REVA and traditional performance measures, such as net income (NI), net operational profit after tax (NOPAT), and earning per share (EPS). The study involves 395 non-financial companies listed in Bursa Malaysia over the period of 2002–2011. Pearson correlation coefficient and panel data single and multiple regression models were employed to analyze the data. The empirical results indicate that the relative information content of the REVA was not greater than that of NI and NOPAT to explain stock returns. NI and NOPAT were highly correlated with stock return compared to REVA. Additionally, the incremental information content test indicated that REVA makes some additional contribution to information content beyond the NI, NOPAT, and EPS. Finally, the panel multiple regression models showed that there was a strong relationship between NI, NOPAT, and REVA with stock return, but there was no meaningful association between EPS and stock returns. Overall, the results do not support the hypothesis that REVA can be considered superior to traditional accounting measures in association with stock returns.

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Hoshi, T., Kashyap, A. and Scharfstein, D. (1991): Corporate Structure and Investment: Evidence from Japanese Panel Data. Quarterly Journal of Economics , 105: 1, pp. 33-60. Corporate Structure and Investment: Evidence from

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217 Wooldridge, J. M. (2002): Econometric Analysis of Cross-section and Panel Data. Cambridge, Mass.: The MIT Press. Econometric Analysis of Cross

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64 73 Akça, H. - Ata, A.Y. - Karaca, C. (2012): Inflation and Corruption Relationship: Evidence from Panel Data in Developed and Developing Countries. International Journal of

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21 37 Battese, G.E. - Coelli, T.J. (1995): A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data. Empirical Economics , 20

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Hadri, K. (2000): Testing for Stationarity in Heterogeneous Panel Data. Econometrics Journal , 3: 148–161. Hadri K. Testing for Stationarity in Heterogeneous Panel Data

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Wikipedia: Foreign Hostages in Iraq ( http://en.wikipedia.org/wiki/Foreign_hostages_in_Iraq ) Wo, W. — Davis, O. (2005): Freedom and Growth: A Dynamic Panel Data Model . Paper prepared for the New Orleans Public

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