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Baltagi, B. (1995): Econometric Analysis of Panel Data . Chichester: Wiley. Econometric Analysis of Panel Data

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Arellano, M. — Bond, S. (1991): Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations. Review of Economic Studies , 58: 277

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1617 Wooldridge, J. (2001): Econometric Analysis of Cross Section and Panel Data . Cambridge, MA: MIT Press. Wooldridge J

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Benjamin, C. — Phimister, E. (2002): Does Capital Market Structure Affect Farm Investment? A Comparison Using French and British Farm-level Panel Data. American Journal of Agricultural Economics , 84: 1115

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

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. Levin , A. – Lin , C. – Chu , C. ( 2002 ): Unit Root Tests in Panel Data: Asymptotic and Finite Sample Properties . Journal of Econometrics 108 ( 1 ): 1 – 24 . Lichtenberg

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China has persevered its market-oriented economic transition since 1978. In this paper, we use the provincial-level NERI Index of Marketization from 1997 to 2014 and a panel data model to investigate the quantitative contribution of market-oriented reforms to China’s total factor productivity (TFP) and economic growth. Our results indicate that marketization reforms contributed 1.3 percentage points to China’s annual economic growth rate and accounted for 35 percent of the increase in TFP. This means that the institutional reforms significantly improved resource allocation. However, economic transition in China has not yet been completed and sustainability of future growth will depend on further market-oriented reforms.

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unemployment. We aim to analyse this relationship on the level of the European Union Member States (EU-28) for the period between 2006 and 2018 using a panel data regression approach. The sample was split into sub-samples in order to get more homogeneous groups

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Logistics industry, being the modern industry integrating information, forwarding, warehousing, and transportation, plays an important role in optimizing the industrial structure in regional economic development. There have been many experts and scholars interpreting the relationship between the level of regional economy and logistics industry from the aspect of econometric model. Referring to existing research results, Panel Vector Autoregressive Model and Factor Analysis are applied to study panel data of 5 coastal provinces in past 20 years and construct relevant indicators reflecting logistic competitiveness, the level of regional economy, and degree of openness in order to explore the linkage effect between logistic competitiveness and the level of regional economy. The results suggest that the 5 coastal provinces can merely achieve the long-term and steady development of regional economy by moving towards the linkage development between logistic industry and manufacturing industry.

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Our aim is to explain why the post-communist countries were inclined to implement proportional income taxation schemes, given the broad variety of personal tax regimes and rates applied in the rest of the world. To resolve this problem a new type of social welfare function, allowing for variable (including negative) marginal utility of income, is introduced. This new approach improves our ability to comprehend the communist and post-communist social policy attitudes from a comparative standpoint. To verify our assertions, a probit regression model is applied. The empirical investigation is based on panel data including 42 countries from Europe and Central Asia for the period of 2000–2015. The primary inference is that the decisions to implement flat tax can be explained by the law of diminishing marginal utility of income and some additional policy-related factors. As it concerns the future, a successful catching-up strategy by the post-communist countries creates conditions for gradual abandonment of the flat tax practices.

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