the ordinary least squares method, they reported a positive relationship between quota policy instruments and development of wind power. Other researchers (Neuhoff et al. 2008; Smith and Urpelainen, 2014; Yin and Powers, 2010) have also found positive and significant relationships between quotas and the capacity of RE deployment. In this paper, section 2 will describe the methods and the data used in this study. This includes presenting the model and describing determinants of the variables in detail. Section 3 will present the empirical findings and discussion, and section 4 will provide the conclusions and discuss policy implications. 2. Methods and Data This study uses panel regression tests, resulting in a comprehensive analysis of the links between RE growth and policy trends. I assemble a country-level in the EU and in the US panel data set spanning 1990-2008 and employ a country/state model with regression test for reliability of the results of panel data models. Panel data controls for country heterogeneity using EU and US provide more information than analysing them separately. It is also crucial to consider the reliability of the present work undertaken to confirm appropriate interpretation of the regression test results. To this aim the things that may have an impact on test results will be accounted for (Khandker, 2005). One can use a fixed-effects estimator, since the unobserved heterogeneity is constant over time. A fixed-effect panel specification is used for testing unobserved heterogeneity and all the variables are expressed as deviations from their mean values (Waldfogel, 1997). In other words, panel data are used to examine the hypothesis that renewable electricity capacity is related to observable and unobservable characteristics influencing renewable electricity capacity. As the unobserved sources of renewable heterogeneity are relatively constant over time, this paper can treat these
the ordinary least squares method, they reported a positive relationship between quota policy instruments and development of wind power. Other researchers (Neuhoff et al. 2008; Smith and Urpelainen, 2014; Yin and Powers, 2010) have also found positive and significant relationships between quotas and the capacity of RE deployment. In this paper, section 2 will describe the methods and the data used in this study. This includes presenting the model and describing determinants of the variables in detail. Section 3 will present the empirical findings and discussion, and section 4 will provide the conclusions and discuss policy implications. 2. Methods and Data This study uses panel regression tests, resulting in a comprehensive analysis of the links between RE growth and policy trends. I assemble a country-level in the EU and in the US panel data set spanning 1990-2008 and employ a country/state model with regression test for reliability of the results of panel data models. Panel data controls for country heterogeneity using EU and US provide more information than analysing them separately. It is also crucial to consider the reliability of the present work undertaken to confirm appropriate interpretation of the regression test results. To this aim the things that may have an impact on test results will be accounted for (Khandker, 2005). One can use a fixed-effects estimator, since the unobserved heterogeneity is constant over time. A fixed-effect panel specification is used for testing unobserved heterogeneity and all the variables are expressed as deviations from their mean values (Waldfogel, 1997). In other words, panel data are used to examine the hypothesis that renewable electricity capacity is related to observable and unobservable characteristics influencing renewable electricity capacity. As the unobserved sources of renewable heterogeneity are relatively constant over time, this paper can treat these
Thesis_Final_%20Nurcan.docx