## 2 Literature Review
### Studies Related to Other Countries  
In [17], the RE technology and diffusion of geothermal, wind, biomass, and solar PV across 26 countries of the Organization for Economic Co-operation and Development (OECD) were studied. The study used the list of patents for each of these technologies to assess the effect of technological change on investment in RE. In [17], the study showed that a 10% increase in knowledge stock in wind and biomass increases investment by 0.6% and 2.6%, respectively. Additionally, the authors revealed that technological changes lead to greater RE investment. [PERSON] and [PERSON] [18] investigated the empirical effect of RE policies and market regulation on the innovation activity in different RE technologies. The authors focused on European Union (EU) countries, and the adopted dataset covers eight different technologies, RE policies, and proxies of market regulation. The study revealed that reducing entry barriers to innovation activities is a major driver in RE innovation, with varying effects for different technologies. In [19], the effects of environmental policies on innovation under various levels of competition were investigated. A pre-sample mean count data econometric specification (which accounts for the endogeneity of policies) was developed using RE policies, competition, and green patents for OECD countries. The study revealed that RE policies are more effective in the promotion of green innovation in countries with modern energy markets. In addition, [PERSON] et al. [19] concluded that competition promotes the generation of low-quality green patents, whereas environmental policies are important for the generation of high-quality green patents. Other studies in the literature have focused on the use of panel data regression analyses to test the effect of RE policies on the RE development [20; 21; 22]. These research studies involved many countries over long time spans. For example, [PERSON] and [PERSON] [20] focused on a panel of 23 European countries for the time span of 1990-2007; [PERSON] and [PERSON] [21] focused on 38 countries for the period of 1990-2010; while, in [PERSON] et al. [22], the panel dataset was 29 countries analyzed during the period 2000-2015. The panel data techniques used in these studies were the corrected standard errors estimator [20], fixed effects vector decomposition [21], and variable intercept panel model [22]. However, all these research studies suffered from the demerit that many the countries involved in the studies did not implement some of the RE policies. Therefore, the econometric treatment could not be trustworthy. Moreover, the presence of unobserved heterogeneity, contemporaneous correlation, and cross-sectional dependency must be adequately addressed. Otherwise, the estimation of the model coefficients would be erroneous. This situation was obvious in the results obtained in [21], which found a negative effect of fiscal and financial incentives on RE development, while the results reported in [20; 22] were the opposite. Throughout the literature, a variety of different studies have tried to show the relationship between RE policies and RE development. However, most of the above-mentioned studies focus on specific policies or policy types, while some others focus on specific countries. This study, on the other hand, focuses on general RE policies using RE policy categories, and the main focus is on the countries which had the highest installed capacity at the end of 2017. As the selected countries (China, USA, Brazil) are very different from each other, the analysis also reveals the diversity of similar policy type applications. Additionally, this study provides a time-series analysis, covering an 18-years period. In order to avoid the problems that arose from the multidimensional panel dataset, such as cross-sectional dependency and heterogeneity, as found in [20; 21; 22], the time series analysis is applied here to each country individually.