Using annual data from 1991 to 2015 for Côte d’Ivoire, this study undertook an analysis of the dynamicimpact of renewableenergyconsumption on economicgrowth. The paper uses a neoclassical production function that includes capital and labor. We apply the ARDL approach of Pesaran et al. (2001) which offers a suitable framework for a dynamic analysis. In an attempt of obtaining unbiased results, additional methods have been used namely: the FMOLS and the DOLS. The results that emanate from the study is that in the short run, renewableenergyconsumption has a mixed impact on economicgrowth while in the long-run, the impact on economicgrowth is not significant. The mixed short-run effect seems to support that the transition between non-renewableenergy and renewableenergy is not yet effective but is under way. The absence of long-run effect could be due to three main reasons namely: the low current level of renewableenergy in the total energy mix, the low usage of renewableenergy in the key sectors of the economy and the low (but growing) investments in the renewableenergy sector.
The EKC hypothesis for the EU and Ukraine was shown and this allowed us to define the main ways of decreasing GHG emissions in the Ukraine. At the first stage, it is necessary to increase the GDP per capita through the diversification of the economic activity and implementation of clean technologies. The policies to combat corruption are also very important for achieving economicgrowth, penetration of RES, and GHG emission reduction in the Ukraine. The statistically significant impact at level 5% of the Corruption Index on GHG emissions shows the necessity to develop and implement effective mechanisms to decrease the level of corruption in order achieve to sustainable development in the Ukraine. The findings showed that increasing RE by 1% will lead to a decrease of GHG in the interval (0.166103, 0.220551). Thus, the Ukrainian government should promote renewableenergy sources and motivate the increased usage of renewableenergy to comply with goals of EU countries that have common boundaries with the Ukraine. In this case, the proposed way is developing a subsidies system for producing energy with the lowest level of pollution, attracting additional green investment for financing green projects to increase the share of renewableenergy in the total energyconsumption. The combating of corruption also allows one to define transparent support systems for cleaner and renewableenergy sources and guaranties GHG emission reduction.
According to Baltagi et al. (2005) , Panel modelling entails the combi- nation of both time series and the cross-sectional dimension of data that renders more insightful meaning into the pool of data. The current study utilized panel procedure to explain how other explanatory variables like real economicgrowth, renewableenergyconsumption, non-renewableenergyconsumption, trade openness and fertility rate explains the qual- ity of the environment as measured by ecological footprint in our case study. In an energy intense region, it would make theoretical and empir- ical sense to assume that β 1 will have a positive impact on the environ- ment. This is in line with the popular tradeoff between economicgrowth and environmental quality known in the energy literature as
On the other hand, research and development (R&D) expenditures were used as a proxy for technological progress and changes in the economic structure (Yin et al. 2015). It was emphasized that as per capita income increased, structural transformation in the economy increased R&D expenses, thus the advancement of technological production. As a consequence of this, a higher level of environmental quality would be achieved (Dinda et al. 2000). However, R&D expenditures were indicative of an entry for the emergence of a product. In this case, since not all R&D expenditures encouraged economicgrowth, it was not a suitable indicator of successful transformation (Mohnen and Hall 2013). In other words, R&D expenditures were not exactly a convenient parameter to examine the impact of structural change and technological advancement on environmental degradation. Some studies emphasized that technological production processes (technical effect) were closely related with an increase in per capita gross domestic product (GDP) (Dinda et al. 2000; Panayotou 1997). However, a high level of income per capita does not express a strong structure in an economy. For instance, oil exporter countries (e.g., Kuwait, Qatar, Saudi Arabia, and the United Arab Emirates) are at a high level of per capita income, but they cannot be classified in such category.
South Africa’s indigenous energy resource base is dominated by coal. Coal contributes close to 77 percent of South Africa’s primary energy demand. Apart from being one of the highest carbon dioxide emitters, a coal produced electricity saw the country into a crisis in 2008. The country experienced a failure from the national grid and experienced high increases in electricity demand while there was not enough supply to sustain the demand. The 2008 electricity power outages led to firms shutting down due to breakage in their machinery and loss of production. The household consumers were forced to buy electricity at high prices. On this accord, it is important to analyse the relationship between energyconsumption and economicgrowth in South Africa. The knowledge of the direction of causality between renewableenergyconsumption and economicgrowth is essential if energy policies which will support economicgrowth of the country are to be advised.
Since the sanctions in related to the Iran’s energy sector will be lifted under the nuclear agreement reached by Iran and P5+1 in July 2015, many scholars expect accelerating economicgrowth in Iran which stands for a higher level of energy producing and consuming. Besides, Iran will be able to promote its National Climate Change Action Plan (NCCAP) to reduce carbon dioxide emissions, while increasing economicgrowth rate. Therefore, in regards to making energy production and consumption decisions, it is important for Iranian policymakers to find out the contributions of consumption of various non-renewableenergy resources to economicgrowth and CO 2 emissions. Thus, this study has attempted to examine empirically the
The energy – environment – income nexus which was proved in the study to have a two way or bi-lateral long run co-integration relation in case of India throws a lot of challenges to policy makers in India. For India, this would mean that all long run growth targets must be sustainable e.g. replacing coal powered plants with plants that consume renewableenergy. However this may not be easy as it requires huge amount of resources which may not be presently feasible for developing countries like India, so attempt can be made to shift to renewableenergy plants in a phased manner. It is also very much possible that a complete overhaul may not possible/feasible, here the plants may be allowed to shift to alternative less environment impacting fuels e.g. natural gas based power which are proven to reduce the CO 2 emissions by approximately 50 %.
The data for the variables such as economicgrowth, capital and employment have been sourced from World Development Indicator while renewableenergyconsumption and carbon dioxide emissions were sourced from International Energy Agency (IEA). The data set comprises of observations for economicgrowth proxies by gross domestic product measured in millions of 2010 constant US dollars and renewableenergyconsumption, which is measured in million kilowatt- hours. Additional variables include, carbon dioxide emissions measured in metric tones, capital proxies by gross fixed capital formation and employment proxies by commercial, agricultural and manufacturing employments. The data used in this study covers a period between 1990 and 2014 and its extrapolated into quarterly data.
Since the seminal work of Kraft and Kraft (1978), examining the causal relationship between economicgrowth and energyconsumption has been subject to numerous empirical studies which tried to find the direction of causality between energyconsumption and economicgrowth using different econometric techniques. However, the results of empirical studies are mixed ranging from bi- and uni-directional causality to no causality for both developed and developing countries. These conflicting results may be due to the fact that countries have different energyconsumption patterns and various sources of energy. Therefore, different sources of energy may have varying impacts on the output of an economy (Soytas and Sari, 2007). For example, Erol and Yu(1987), Chontanawat et al.(2006), Halicioglu(2007), Yoo(2006), Lee(2006), Ghosh(2002), Cheng and Lai(1997) and Masih and Masih(1996) for the cases of Germany, Canada, Turkey, Thailand, France, India, Taiwan and Indonesia, respectively, find no causality running from energyconsumption to economicgrowth. While Soytas and Sari(2003), Lee(2006), Asafu-Adjaye(2000), Masih and Masih(1998), Soytas and Sari(2003), Masih and Masih(1996), Lee and Chang(2005) and Fatai et al.(2004), for the same countries, find uni-directional causality from energyconsumption to GDP growth. Uni-directional causality from energyconsumption to economicgrowth also were found in the cases of U.S.(Stern, 1993; 2000), Philippines(Yu and Choi, 1985), Singapore(Glasure and Lee, 1997), Sri Lanka(Masih and Masih, 1998; Morimoto and Hope, 2004), China(Shiu and Lam, 2004), Belgium, Netherland and Switzerland(Lee, 2006). On the other hand, a reverse uni-directional causality running from economicgrowth to energyconsumption was found for the cases of South Korea (Yu and Choi, 1985; Oh and Lee, 2004; Soytas and Sari, 2003), Italy (Erol and Yu
Over the past decades, many studies pertaining to the engines of growth have been conducted with respect to developing countries. This is mainly due to the reason that they attempt to find an effective pillar to upgrade their status to developed countries. From our reading, we observe that energy and tourism are two common factors that hotly debated in the economicgrowth literature. Numerous studies have been conducted to verify the role of energyconsumption and tourism in economicgrowth. However, their efforts failed to find a consistent causal relationship among economicgrowth, tourism and energyconsumption. Some studies suggested that energyconsumption and tourism stimulate long-term economicgrowth (e.g. Lean and Smyth, 2010; Lean and Tang, 2010; Hye and Khan, 2013; Tang and Shahbaz, 2013; Soares et al., 2014; Tang et al., 2016), while other studies claimed the other way around or not related at all (e.g. Cheng, 1999; Ghosh, 2002; Oh, 2005; Katircio ğ lu, 2009; Alam et al., 2011; Ghosh, 2011; Ozturk and Acaravci, 2009). Therefore, it is very hard to derive a useful guideline for policymakers elsewhere to design appropriate growth policies for their economies.
consumption was almost as important as employment in explaining GDP forecast error variance. Wolde-Rufael (2004) used the Toda-Yamamoto causality test to investigate the causal relationship between various kinds of industrial energyconsumption and GDP in Shangai for the period 1952-1999. The study found unidirectional Granger causality from coal, coke, electricity and total energyconsumption to real GDP, but no causality in any direction, between oil and real GDP. In their 2005 study, Domac et al (2005) claimed that bio-energy should help increase the economies macroeconomic efficiency through the creation of employment and other economic gains. Later, Awerbuch and Sauter (2006) defended that RES had a positive effect on economicgrowth by reducing the negative effects of oil prices volatility 3 . Furthermore, they contributed to energy supply security. These effects have to be considered when fully assessing the comparative costs of RES and fossil fuels. Ewing et al (2007) used the generalized forecast error variance decomposition analysis to investigate the effect of disaggregated energyconsumption (coal, oil, natural gas, hydro power, wind power, solar power, wood and waste) on industrial output in the USA. The authors found that non-renewableenergy shocks (coal, gas and oil) had more impact on output variation than other energy sources. Even so, several renewable sources also exhibited considerable explanatory power. Regardless of the sources, energy had always less impact on output variations than employment. In 2008, Chien and Hu (2008) studied the effects of renewableenergy on GDP for 116 economies in 2003 through the Structural Equation Modeling (SEM) approach. They decomposed GDP by the “expenditure approach” and concluded that RES had a positive indirect effect on GDP through the increasing
According to the recent World Bank (2012) report, the most commercially established renewableenergy resource is the hydropower. This resource has been used to generate hydroelectricity. Traditionally this electricity power is generated along rivers by the force of flowing water and it remains the largest global renewableenergy source. At present, hydropower supplies less than 2.5 % of the MENA region’s electricity. The greatest technical potential for hydro development in the region can be found in Egypt, the Islamic Republic of Iran, and Iraq. Throughout the rest of the region, water scarcity cause serious problems in front of the hydroelectric for development potential. On the basis of the combined country- specific potential, if the countries exploit known hydropower resources using current technologies, the electricity will approximately generate 182.1 TWh per year (Table.1.B). The amount of this strategy can cover nearly 16 % of current electricity supplies in the region.
The literature on Granger causality has grown considerably, following his seminal work in 1969, slowly during the first years and more rapidly in recent years. Granger causality test suggests which variables in the models have significant impacts on the future values of each of the variables in the system. Among recent applied studies, a significant amount of work has been devoted to addressing the above mentioned question of causality between energyconsumption and economicgrowth. This paper studies the time series properties of energyconsumption and GDP and reexamines the causality relationship between the two series in the top 10 emerging markets excluding China due to lack of data and G-7 countries 1 . Soytas and Sarı (2003) show that there is a bi-directional causality in Argentina, causality running from GDP to energyconsumption in Italy and Korea, and from energyconsumption to GDP in Turkey, France, Germany and Japan.
From the table above, the computed J-statistic is 0.004531. This value was multiplied by the number of observations to obtained the calculated J-statistics. That is J 34 0.004531 0.154054 . The value for the calculated J-statistics is small and less than zero. We therefore do not reject the null hypothesis that the instruments are valid. This means that the model is valid and the coefficients were interpreted as found on the proceeding paragraphs. The result in table 2 indicates that the constant term is 0.005. This represents the average autonomous petroleum consumption in Cameroon. In other words, this is the quantity of petroleum that is consumed when all other determinants of petroleum consumption are held constant. The result that there is relationship between Real Gross Domestic Product (RGDP) and petroleum consumption. This means that as the growth rate of Cameroon increases, so too does the standard of living of the population leading to an increase in the demand of automobiles, generators and other equipment or machineries that use petroleum and thus an increase in petroleum consumption. Precisely a 1% increase in RGDP will lead to a 0.5095% increase in petroleum consumption. The statistical test of hypothesis reveals that the result is statistically significant at 1%. We therefore reject our null hypothesis and accept the alternative implying that RGDP is a significant determinant of petroleum consumption in Cameroon within our period of study and so should be given adequate attention when setting growth strategies.
In addition to being consistent with the specifications in Eqs. (2) and (3), the model in Eqs. (6)-(7) describes the intertemporal interaction between output and the factor input included in the production function. Once the equilibrium conditions represented by the cointegrating relations are imposed, the VEC model describes how, in each time period, output growth is adjusting towards its long-run equilibrium state. Since the variable are supposed to be cointegrated, then in the short term, deviation of output from its long-run equilibrium path will feed back on its future changes in order to force its movement towards the long-run equilibrium state. The cointegrating vectors from which the error- correction terms are derived are each indicating an independent direction where a stable, meaningful long run equilibrium state exists. The coefficients of the error correction terms, however, represent the proportion by which the long-run disequilibrium in the dependent variables is corrected in each short- term period.
Studies exposed that consumption of energy per capita is the key sign of development of an economy. It is considered that energy is the most significant resource using in every production procedures and it positively contributes to foreign earnings of those nations which are exporting the energy goods. Most of the nations, particularly the less developed nations get benefited by the transfer of technologies into the procedure of research, creation and marketing. The energy sectors have also given employment opportunities to the huge amount of public who were without jobs. Developments have done in the infrastructure and socioeconomic actions of group of people in a progression of energy resource operation. On the basis of this point of view, continuous supply of energy therefore become vital for the economic and infrastructural renovation of an economy of a country (Alam, 2006). The relationship amongst the uses of energy and economic expansion has been examined over times but there is a requirement of a continuous research in this area. Number of studies is based upon whether an development of an economy increases the energyconsumption and vice-versa. The results of various empirical analyses explained the strong correlation among the use of electricity and economicgrowth. Using the Pearsons correlation coefficient, Moremoto and Hoppe (2004) exposed that the growth of economy and uses of energy in Sri Lanka is greatly correlated. Their work is opposing to that of Stem (1993) who observed that association among GDP of United States of America and energy with the multivariate co-integration technique but no such a relation was found for these two variables. A link with uses of energy and growth of gross domestic products is a diesoline for the better investigation in research (Jobirt and karinfil, 2007: Akinllo, 2008: Errdal et al, 2008: Yoo and Kuu, 2009).
By using the data for the period 1955 to 1996 for Pakistan, Aqeel and Butt (2001) concluded that economicgrowth causes total energyconsumption. The study further investigated that economicgrowth leads to growth in petroleum consumption. On the other hand, in the case of gas sector, neither economicgrowth nor gas consumption affects each other. In power sector, electricity consumption leads to economicgrowth. Lee (2005) tested the cross sectional and time series data of 18 developing countries to find the relationship between energyconsumption and GDP. He concluded that energyconsumption Granger causes GDP. Asafu (2000) found a unidirectional Granger causality from energy to income in India and Indonesia while bi directional causality between energy an income in the case Thailand and Philippines. By using a data for three SAARC countries, Imran and Masood (2010) found a long run relationship between economicgrowth and energyconsumption and a unidirectional causality from energyconsumption to economicgrowth but no causality found in short run. Jumble (2004) found that the causality running from electricity consumption to the income in the case of Turkey.
Our major result to emerge from this analysis on Côte d'Ivoire’s economy is consistent with the finding of Jang (2000) for the East Asia's fast growing countries about the relationship between openness and growth. In effect our results concerning Côte d'Ivoire’s economy show that the relationships between openness and growth do not replicate assessments of the new growth theory where increasing openness affects the long-run growth of the economy through its effects on technological change. The results concerning the effects of globalization on Côte d'Ivoire’s economicgrowth also contrast with the forecasts of the World Trade Organization (WTO) and the Multilateral Trade System (MTS) assessments about the expected benefits about increasing the dynamism of economicgrowth. These results could be due to the lack of basic requirements as transfer of technology, education and training necessary to impact the long-run behaviour of the growth process in this country.
pilot and scaled investment loan vehicle. A critical piece of Phase 2 will be to design a farmer loan delivery mechanism appropriate to the local environment. At present, because of structural bar- riers inherent to Côte d’Ivoire, cocoa farmers have very limited access to finance. Designing the right delivery mechanism and intermediary will require working with all actors along the cocoa value chain as well as service, input and technical assistance providers. To evaluate multiple possibilities, the Rainforest Alliance aims to evaluate several models for the implementation of a targeted $2.5 million pilot project including about 1,000 farmers (depend- ing on funding).
10. The country has experienced several political and economic shocks recently, including: i) dissolution of the electoral commission in February 2010, leading to further uncertainty on long-awaited presidential elections; ii) recurrent civil unrest throughout the country; and iii) a north/south division of the country which contributes to poverty and inability to adjust to economic shocks, thereby raising malnutrition and food insecurity. This has led the Special Representative of the Secretary General to comment that the country is experiencing a “calm before the storm.”