5 resultados para Dependent Variable

em Archive of European Integration


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Since 1999, countries have voluntarily chosen to reform their higher education systems to join the European Higher Education Area. This paper compares Bologna Process implementation across four regions within the European Union. While there are 47 countries participating in the Bologna Process, this paper uses statistical analysis to consider 25 of the 28 EU Member States. The time period of analysis is 2000-2011, prior to Croatia’s accession to the EU on 1 July 2013. Across Europe there are inter-regional differences in how the Bologna Process has been implemented and in the political economy contexts that influence higher education reform for policy convergence. There are three explanatory variables in the political economy context: 1. competitive economic pressures and globalization 2. domestic politics at the national level 3. leadership from the supranational European Union that socially constructs regional norms Tertiary education attainment is the dependent variable of interest in this research. The objective of 40%, for 30-34 year olds, is Europe 2020 benchmark target. There are additional higher education reform criteria encompassed in the Bologna Process. These criteria concern Credit and Degree Structure, Quality Assurance, and Recognition of academic degrees among countries in the EHEA. This tertiary education attainment variable, which is of interest in this paper, does not capture the entire implementation process. Nevertheless, it is a measure of one important indicator of success in providing higher education access to populations within the context of democratic governance. This research finds that statistically GDP Per Capita is the most significant variable in relationship to tertiary education attainment across four regional areas in the European Union.

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This paper empirically analyses a dataset of more than 7,300 agricultural land sales transactions from 2001 and 2007 to identify the factors influencing agricultural land prices in Bavaria. We use a general spatial model, which combines a spatial lag and a spatial error model, and in addition account for endogeneity introduced by the spatially lagged dependent variable as well as other explanatory variables. Our findings confirm the strong influence of agricultural factors such as land productivity, of variables describing the regional land market structure, and of non-agricultural factors such as urban pressure on agricultural land prices. Moreover, the involvement of public authorities as a seller or buyer increases sales prices in Bavaria. We find a significant capitalisation of government support payments into agricultural land, where a decrease of direct payments by 1% would decrease land prices in 2007 and 2001 by 0.27% and 0.06%, respectively. In addition, we confirm strong spatial relationships in our dataset. Neglecting this leads to biased estimates, especially if aggregated data is used. We find that the price of a specific plot increases by 0.24% when sales prices in surrounding areas increase by 1%.

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This study investigates whether trade-related, targeted, government policies had an impact on the total factor productivity (TFP) of manufacturing firms in Eastern Europe and Central Asia (ECA region) between 1995 and 2009. It does so by looking at how different types of primarily industry-specific trade policies (or their combinations) impacted firm productivity. The dependent variable is firm total factor productivity (TFP), calculated using the Levinsohn-Petrin approach. As an alternative measure of firm productivity, this study uses labor productivity. This study finds that, in most instances (10 out of 14 times), targeted policies do not show a significant impact on manufacturing firms’ TFP. Based on the analysis of 588 manufacturing firms in the ECA region, this study finds that, contrary to proponents of targeted policies, targeted trade-related government policies have a limited impact on the total factor productivity (TFP) in developing countries.

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This paper estimates the immediate impact of the European Central Bank’s asset purchase programmes on sovereign bond spreads in the euro area between 2008 and 2015 using a country-by-country GARCH model. The baseline estimates are rigorously diagnosed for misspecification and subjected to a wide range of sensitivity tests. Among others, changes in the dependent variable, the independent variables and the number of (G)ARCH terms are tested. Moreover, the model is applied to subsamples and dynamic conditional correlations are analyzed to estimate the effects of the asset purchases on the contagion of spread movements. Generally, it is found that the asset purchase programmes triggered an reduction of sovereign bond spreads. More specifically, the Securities Markets Programme (SMP) had the most significant immediate effects on sovereign bond spreads across the euro area. The announcements related to the Outright Monetary Transactions (OMT) programme also yielded substantial spread compression in the periphery. In contrast to that, the most recent Public Sector Purchase Programme (PSPP) announced in January 2015 and implemented since March 2015 had no significant immediate effects on sovereign bond spreads, except for Irish spreads. Hence, immediate effects seem to be dependent upon the size of the programme, the extent to which it targets distressed sovereigns and the way in which it is communicated.