**2. Literature review and hypothesis setting**

Numerous studies related to the efficiency evaluation of renewable power plants have fo‐ cused primarily on single efficiency and have assisted in the selection of input and output variables used in this study [10] [9]. First, Criswell and Thompson [11] applied DEA with a sample of large-scale commercial power systems for earth in global. They used three input and three output variables are exogenously fixed for the research. Azadeh, Ghaderi and Maghsoudi [12] used data from 25 cities in Iran with six regions within each city. Four types of input variables and two types of output variables were used in their analysis. More re‐ cently, Madlener, Antunes and Dias [13] justified the use of DEA logically and systematical‐ ly in 41 agricultural biogas plants situated in Austria. They used three input and two output variables and identified that DEA offers considerable potential and advantages for seeking accurate evaluate productivity. Iglesias, Castellanos and Seijas [14] evaluated the perform‐ ance of a group of 57 Spanish wind farms located in the region of Galicia by using three in‐ put and two output variables. Azadh, Ghaderi and Nasrollahi [15] measured the efficiency of wind power plants with the lowest possible costs using DEA, with data collected from 25 cities in Iran with 5 regions within each city using DEA with four input and two outputs.

In this section, we propose several hypotheses. Considering Sahelian countries, energy ac‐ cess remained relatively low until recently, despite the abundance of renewable resources such as wind and solar energy. The abundance of renewable resources assumes that access to renewable technologies could increase and improve energy access in remote rural areas [16]. They are compatible with local conditions and resource endowment. Research on re‐ gional development specifically related to China's Western Development Program by the China Energy Strategic Research Group and Fan, Sun & Ren [17] discussed sustainable de‐ velopment issues for economically disadvantaged areas such as the ecological deterioration and sustainable livelihoods of rural households, and suggested reasonable approaches to address energy problems in these areas, such as the use of rich natural resources (endow‐ ment), development of renewable energy, and developing a moderate centralized energy supply that considers local energy endowment conditions. Shi [18] supported a similar type of energy development because a region's unique energy endowments reflect it is energy developmental differences. Chen and Zhu [19] specifically used resource endowment, zon‐ ing separation of wind power and solar power resources, the classification results for the preliminary study on China's energy and economic regionalization. Chen and Zhu argued that there is little evidence on whether the impact of economic development on the electrici‐ ty mix is affected by energy resource endowments [19]. Marcotullio and Schulz [20] provid‐ ed evidence of endowment's heterogeneity in energy mix transitions across countries. Therefore, we present the following hypotheses:

#### *H1a: Endowment and OE are positively causal related*

ment performance within renewable energy in the OECD countries. We measure managerial efficiency in two phases: operating efficiency (OE) and the energy density efficiency (DE).

This method is different from those of previous studies that focused primarily on assessing OE [8] [9]. We divide the efficiency of energy plants into two components. Management per‐ formance is no longer constrained with production efficiency but constitutes a broader di‐ mension that covers operating activities and the efficiency of energy use. Compared to the traditional single-efficiency model, the sub-processes model is more suitable for evaluating

This evaluation model is useful for energy managers and current policy-makers. For manag‐ ers, it provides a more detailed performance evaluation process including two essential op‐ erational elements in the energy generation industry; for policy- makers, it offers a complete measurement of efficiency and is based on variable combinations of these two dimensions; policy-makers can identify the most suitable policy (e.g., a subsidy) and develop the most

Taiwan is an island, country that is extremely lacking in energy and is more than 98% de‐ pendent on imported energy. Taiwan is also influenced by political and geographical con‐ straints; therefore, the capacity to acquire energy is difficult compared to other countries. Thus, implementation of renewable energy and the abolition of nuclear power generation is a potential policy priority for Taiwan. Seeking the most cost-effective strategy, Taiwan's na‐ tional conditions, if we can use the experience of other countries, will become Taiwan's de‐ velopment of a great help. OECD countries including highly and lowly developed countries, especially developing countries, is from the energy consumption, low efficiency and serious pollution to the economic development mode shift to energy efficient, less polluting eco‐ nomic development mode. In this study, we discuss and compare 34 OECD countries' re‐ newable energy OE and DE by DEA. Finally, we present our conclusions and provide

Numerous studies related to the efficiency evaluation of renewable power plants have fo‐ cused primarily on single efficiency and have assisted in the selection of input and output variables used in this study [10] [9]. First, Criswell and Thompson [11] applied DEA with a sample of large-scale commercial power systems for earth in global. They used three input and three output variables are exogenously fixed for the research. Azadeh, Ghaderi and Maghsoudi [12] used data from 25 cities in Iran with six regions within each city. Four types of input variables and two types of output variables were used in their analysis. More re‐ cently, Madlener, Antunes and Dias [13] justified the use of DEA logically and systematical‐ ly in 41 agricultural biogas plants situated in Austria. They used three input and two output variables and identified that DEA offers considerable potential and advantages for seeking accurate evaluate productivity. Iglesias, Castellanos and Seijas [14] evaluated the perform‐ ance of a group of 57 Spanish wind farms located in the region of Galicia by using three in‐

the usage performance because of energy industry characteristics.

suggestions for renewable energy development in Taiwan. β

**2. Literature review and hypothesis setting**

effective strategy.

194 New Developments in Renewable Energy

### *H1b: Endowment and DE are positively causal related*

British Petroleum discussed China and India's rapid increase in energy use because they represent approximately one-third of the global population, the expected depletion of oil re‐ sources in the near future, and the effect of human activities on global climate change. Bet‐ tencourt [2] indicated that as economies and populations continue to grow rapidly, energy and power consumption also increase at the same rate. The Empresa de Pesquisa Energética (EPE) indicated that because of population growth, urbanization and higher income, annual electricity consumption in the residential sector is growing steadily from 4.7% in 2003 up to 6.2% in 2009. The International Energy Agency (IEA) [6] and United Nations (UN) [4] stated that approximately 4.9 billion people (80 % of the global population) lived in developing countries as of 2001. The current annual population growth rate is approximately 1.5 % in developing countries. However, despite the lower living standards and lower per capita en‐ ergy use in developing countries, total energy use in developing countries is increasing fair‐ ly rapidly. Crane and Kinzig [4] indicated that many countries in the pursuit of economic development, the population increase rapidly as the same time, but also face a requirement to increase energy. There is a growing need to implement energy efficiency. Therefore, we present the following hypotheses:

#### *H2a: Population and OE are positively causal related*

#### *H2b: Population and DE are positively causal related*

Because energy efficiency improvement relies on total-factor productivity improvement [21], the technical efficiency (TE) index is computed to analyze the energy efficiencies of economies. The TE index incorporates energy, capital, and labor as multiple inputs for pro‐ duction. They use DEA to find the TE of each economy. Chien and Hu [22] stated that it is possible that capital inputs may increase energy generations. From an economic production perspective, these practices imply that energy savings as well and emission reduction can be achieved by means of factor substitution between energy and capital [16] [23] [24]. This ef‐ fectively mitigates the dependence of economic growth on energy input and environmental capacity; in other words, it improves the aggregated energy and environmental efficiency (AEEE). Hudson and Jorgenson [25] stated that intensity effects in the industrial sector might depend on three strong interactions. Energy and capital are both, substitutes for la‐ bor, whereas capital and energy are complements. In other words, capital and energy can be increased simultaneously. Turner [26] proposed another factor of production that is critical in determining substitution and other effects driving economy-wide responses. Specifically, rebound effects, from increased energy efficiency are capital. Therefore, we present the fol‐ lowing hypotheses:

*H4a: GDP and OE are positively causal related*

*H4b: GDP and DE are positively causal related*

determinant of energy prices.

**3. Research methodology**

(HOP). Figure 1 shows this process.

Some researchers have reached an opposing conclusion that energy subsidy reform would produce positive results. Steenblik and Coroyannakis [30] used the computable general equilibrium (CGE) model to simulate the positive effects of removing coal subsidies in West‐ ern European countries, such as promoting the industrialization of the power sector and in‐ creasing coal production and exports. United Nations [3] concluded that cutting energy subsidies could have significant impacts on residents, although this requires a more indepth analysis in the future. Conversely, some researchers believed that fossil energy reform would increase energy use efficiency and household income levels. Choi, Roh and Yoon [9] indicated that increase in energy price could improve energy efficiency significantly. Thus, the energy price mechanism is at the core of energy reform, and energy subsidies are crucial

Comparative Analysis of Endowments Effect Renewable Energy Efficiency Among OECD Countries

http://dx.doi.org/10.5772/52020

197

Anderson and Leach [27] showed that energy subsidies in the United States would impede the use of new energy and reduce energy use efficiency. Shah and Larsen [31] showed that if the total energy subsidies worth almost \$230 billion in 1990 could be removed, CO2 emis‐ sions worldwide would decrease by 9.5%. Using the global coal model, Lam and Shiu [32] analyzed coal subsidy reform in Japan; the results showed that removing the coal subsidies in the power supply and industrial boiler sector would reduce global CO2 emissions by 0.2%. The IEA [5] also indicated that global CO2 emissions would decrease by more than 6% by 2010 if the fossil energy subsidies in the power sector were removed. We use these re‐ search data to test and verify these countries, and the relationship between subsidies policy

We adopted a two-stage DEA [7] to evaluate the level of management performance in re‐ newable energy industries in OECD countries. These two types of efficiency are based on sub-processes that detail the two essential phases of a country's renewable power plants: outputs provided and use generation. We then followed the approach by Seiford and Zhu [33], who divided the entire production activity into two sub-production processes. Fuel, la‐ bor, generating capacity, and operating expenses were the original input variables, whereas total primary renewable energy supply (TPES)/GDP ratio, TPES/population ratio, and grid were final output variables. Medial input variables included electricity-only plants (EOP), combined heat and power plants (CHP) of electricity, and CHP of heat, and heat-only plants

and efficiency. Therefore, Hypotheses 5a and 5b are as follow:

*H5a: Verify that causal relationship between subsidy and OE*

*H5b: Verify that causal relationship between subsidy and DE*

**3.1. Two-phase data envelopment analysis framework**

#### *H3a: Capital and OE are positively causal related*

#### *H3b: Capital and DE are positively causal related*

The renewable energy-developing indicators of an economy are obtained from Renewables Energy Information [5] and have been published by the IEA since 2002. Indicators such as household consumption, capital formation, trade balance, energy imports, and gross domes‐ tic product (GDP) are obtained from the world energy development. Anderson and Leach [27] also indicated that if renewable energy technologies supply a significant share of total energy supply, then the energy storage problem must be solved in advance. First, the man‐ ner in which GDP affects the promotion of energy policies must be studied. Bettencourt [2] indicated that there seems to be a long way to go to fully use renewable resources. Until the early 1980s, changes in the energy–GDP ratio were the subject of many studies. Questions were raised as to how the ratio would evolve over time if a country experiences different stages of economic development. Understanding such trends provides indicators for how future energy demand would evolve. A number of studies have suggested that as the proc‐ ess of industrialization advances, with agriculture replaced by manufacturing, energy con‐ sumption tends to increase more rapidly than GDP, creating an increasing value of the energy–GDP ratio. Among the theories on the relationship between energy consumption (or energy-related environmental indicators) and GDP, the most famous is the environmental Kuznets curve. A recent overview was provided by Ang and Liu [28]. With the GDP meas‐ ured in common units, comparisons can be made between countries. Cross-country varia‐ tions in the energy–GDP ratio have been studied for industrialized countries and for developing countries [27] [29].

Therefore, we present the following hypotheses:
