The effect of financial development on renewable energy consumption in cameroon

Salomon, Nguiffo Joel; Bosco, Etoa Etoa Jean Article The effect of financial development on renewable energy consumption in cameroon Economic Review: Journal of Economics and Business Provided in Cooperation with: Faculty of Economics, University of Tuzla Suggested Citation: Salomon, Nguiffo Joel; Bosco, Etoa Etoa Jean (2024) : The effect of financial development on renewable energy consumption in cameroon, Economic Review: Journal of Economics and Business, ISSN 2303-680X, University of Tuzla, Faculty of Economics, Tuzla, Vol. 22, Iss. 1, pp. 73-88, https://doi.org/10.51558/2303-680X.2024.22.1.73 This Version is available at: https://hdl.handle.net/10419/307944 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. 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Economic Review: Journal of Economics and Business, Vol. XXII, Issue 1, May 2024/// * Faculty of Economics and Management, University of Yaoundé II, Cameroon, salomonjoelnguiff[email protected]r ** Rector of the University of Ebolowa, Cameroon, [email protected]. 73 /// THE EFFECT OF FINANCIAL DEVELOPMENT ON RENEWABLE ENERGY CONSUMPTION IN CAMEROON Nguiffo Joel Salomon* , Etoa Etoa Jean Bosco** DOI: 10.51558/2303-680X.2024.22.1.73 Abstract The improvement of the energy structure and the development of the renewable energy sector play an important and strategic role in Cameroon's responsibilities against climate change. So, the authorities and policy makers have made great efforts to achieve this. But one of the main constraints of Cameroon's energy transition lies in financial issues, which are inevitably linked to the country's financial development. At the heart of this reflection therefore arises the question of knowing: What could be the impact of financial development on the consumption of renewable energies in Cameroon? This study therefore aims to examine the impact of financial development on the consumption of renewable energies in Cameroon over the period from 2000 to 2022. Our research is based on a Vector Autoregressive (VAR) model; seven variables of financial development have been used to explain the consumption of renewable energies in Cameroon. The results of the empirical analysis show that foreign direct investments, the evolution of bond markets and energy prices represented by the consumer price have a negative effect on the consumption of renewable energies. On the other hand, domestic credit provided by the financial sector, banking availability, economic development, and income have a positive impact on renewable energy consumption. Our empirical results provide valuable insights into the best ways to deploy capital in the renewable energy sector, in order to provide customers with cost-competitive options, and to facilitate the implementation of policies that contribute to environmental sustainability and energy security. Keywords: financial development, renewable energies, VAR model, Cameroon. JEL: C22; Q01; Q20; Q43. 1. Introduction Energy is a critical component if countries are to achieve sustainable development. The ongoing demand for energy has intensified in previous decades and continues to grow now. Population expansion, improved lifestyles, increased output, and economic competitiveness all contribute to the growing demand for energy. As a result, worldwide energy consumption rose by 44% between 1971 and 2018 (World Bank, 2017a, 2017b). Furthermore, figures show that fossil fuels account for roughly 78.4% of the total energy consumption (REN21, 2017). Excessive combustion of fossil fuels emits excessive amounts of carbon dioxide (CO2) into the atmosphere, causing negative environmental effects such as global warming. Consumption of renewable energy contributes not only to a cleaner environment (by reducing greenhouse gas emissions), but also to independence from fossil fuel markets (e.g. oil and gas) and energy security. In Cameroon, increased consumption of renewable energies is one of the main energy policy objectives. "Cameroon has significant renewable energy potential as well as limited oil and gas reserves. There is a strong governmental commitment to developing the energy sector, thanks in large part to international donor support. However, universal access to energy is still far from being reached. The development of renewable energies other than hydroelectricity is embryonic, and load shedding is regular." (IFDD, 2022). Renewable energy has the potential to diversify the energy mix. Less reliance on fossil fuels results in increased resilience to energy market shocks. Furthermore, green energy production has the potential to avoid additional environmental harm. However, transitioning from fossil fuels to renewable energies can be difficult, and one of the most significant challenges is cost. There are several financial ///. Nguiffo Joel Salomon, Etoa Etoa Jean Bosco /// 74 Economic Review: Journal of Economics and Business, Vol. XXII, Issue 1, May 2024 challenges to overcome when compared to fossil fuel-based energy projects, including greater infrastructure, start-up, and operating expenses. In this environment, a strong financial system is required to ensure effective price discovery and financing, as well as market liquidity. Additionally, financial markets increase capital allocation. A highly developed financial system encourages investment in growth areas, whereas an underdeveloped financial system discourages investment in declining industries (Wurgler, 2000). Recent studies have focused on the relationship between energy consumption and economic growth, and have expanded to include a third dimension: financial development. The need to introduce financial development to explain this relationship is supported by several reasons: firstly, financial development attracts foreign direct investment (FDI), and hence high-level R&D investment, which amplifies economic growth and affects the dynamics of environmental performance. Secondly, financial development provides opportunities for developing countries to exploit new technologies, known as "green" technologies, and thus help them to improve the environment and sustainable development. Finally, financial development can also lead to increased pollution and environmental degradation. Investment costs are one of the most significant hurdles in deploying renewable energy. Indeed, renewable energies have a somewhat high initial investment cost when compared to traditional energy sources. Furthermore, renewable energy projects have long payback periods and require a large amount of capital. Financial development could thus play an essential role in increasing renewable energy use. Financial infrastructure can boost economic growth and influence energy demand (Sadorsky, 2010). Indeed, a high level of financial development promotes the growth of financial markets, banks, and stock exchanges, resulting in more cash available for investment (Sadorsky, 2010). According to Shahbaz and Lean (2012), financial development should have a favorable impact on economic growth and, consequently, energy consumption. They highlighted the key factors that explain how financial market improvements are linked to increased investment and economic growth. The initial mechanism is the level effect. This translates into matured financial markets raising capital for high-return initiatives. The second process is known as the efficiency effect. It indicates that financial development improves asset liquidity and diversity while also channeling financial resources to relevant enterprises. According to Sadorsky (2011), financial development enhances an access to financial resources, resulting in increased demand for expensive goods and energy. According to Sadorsky (2011), financial development influences energy use in three ways: directly, through commerce, and indirectly through wealth. The direct effect is linked to stronger financial development, which allows consumers to borrow more easily and at lower costs so as to purchase consumer durables, resulting in increased energy consumption. The commercial effect arises when financial development enables enterprises to obtain financial resources more simply and affordably (Caporale et al. 2009). The wealth effect happens as economic confidence rises, expanding the economy and driving up demand for energy. Improved financial development makes it easier to save, borrow, and invest. With cheap financing costs, customers are more likely to buy consumer durables, thus increasing energy demand. However, Islam et al. (2013) suggest that financial prosperity encourages the purchasing of energy-efficient appliances, hence lowering energy usage. According to Chiu and Lee (2020), financial institutions play a significant role in countries with a stable financial climate because they provide industries with an easy access to finance through the stock market and banking sector. As a result, businesses would have more resources to invest in modern, energy-efficient equipment and technologies, resulting in lower energy usage. In an environment where renewable energy investment is heavily promoted, financial development can play an important role. In the energy literature, there is an increasing interest in examining the factors that govern the use of renewable energy. As many empirical studies have focused on the interactions between the use of renewable energy and financial development, Habiba and Xinbang (2023) used the "Moment Quantile Regression" (MMQR) method to study the impact of different aspects of financial development on renewable energy consumption The effect of financial development on renewable energy consumption in Cameroon // Economic Review – Journal of Economics and Business, Vol. XXII, Issue 1, May 2024 75 /// using panel data from seven emerging economies (E7) from 1991 to 2018. It is confirmed that the influence of independent variables varies across quantiles of renewable energy. Overall, they discovered that all three aspects of financial growth—financial development in general, financial market-related development, and financial institution-related development—have a beneficial impact on renewable energy usage. Regean and Bulime (2024) investigated the impact of financial development on the clean energy transition in 20 low- and middle-income nations in Sub-Saharan Africa. The study used two-stage, fixed effects, instrumental variable least squares models to investigate the impact of financial development on the shift to renewable energy. Their findings suggest that financial development has a positive effect on the shift to renewable energy. However, financial development has a considerable impact on financial institutions rather than financial markets. According to a 2016 analysis on Cameroon's energy condition, the country has a high potential for renewable energy as well as minor oil and gas reserves. There is a strong governmental commitment to developing the energy sector, thanks in large part to international donor support. However, universal access to energy remains a distant goal, the development of renewable energies other than hydroelectricity is in its early stages, and load shedding is common. This is primarily due to the presence of financial constraints and the ongoing search for financing sources and methodologies tailored to energy management projects (MINEE, 2016). The complexity of procedures for obtaining international financing in Cameroon is impedes the growth of renewable energy. The access to the local financial industry is likewise difficult. The local banking industry has yet to properly comprehend the significance and necessity of improving access to credit for the renewable energy sector. (IFDD, 2022). Our research consequently focuses on the following question: What impact might the financial development of renewable energy consumption have in Cameroon? This study examines how financial development affects renewable energy consumption. It contributes the following to the existing literature: first, while our research contributes to a substantial body of literature attempting to explain the relationship between financial development and energy consumption, we focus on renewable energy use, which is understudied in the existing literature. Second, this paper is one of the first to quantitatively examine the impact of financial development on renewable energy consumption in Cameroon, and third, we have added a new variable, bank availability, which represents the number of commercial banks and measures the accessibility of bank credit for adults. Our article is organized as follows: section 2 provides a review of the literature on the subject, section 3 the methodology, section 4 presents the results and discussion, and finally we will have the conclusion. 2. Literature Review 2.1 Theoretical review Financial development, which is defined as improving the efficiency and stability of the financial system, includes decisions to encourage foreign direct investment, banking system expansion, and stock and bond market activity (Sarkody, 2010). Financial development entails reduced financial risk, increased transparency, lower borrowing costs, and an improved access to finance (Sadorsky, 2010), all of which have a beneficial impact on the cost of renewable energy, which is a primary driver of renewable energy usage. The banking industry, as a critical component of the financial system, provides resources and encourages investment in renewable energy goods and technology. The expansion of the capital market raises the attractiveness of enterprises, allowing them to get extra resources to support investments in the energy sector, and also boosts confidence in the financial system, increasing demand for energy (Sadorsky, 2010). Financial development stimulates a number of changes within a country, including reduced financial risk and improved quality of life, lower borrowing costs, greater transparency between lenders and borrowers, access to greater financial capital and investment flows, and access to the latest energy-efficient products and advanced technologies, all of ///. Nguiffo Joel Salomon, Etoa Etoa Jean Bosco /// 76 Economic Review: Journal of Economics and Business, Vol. XXII, Issue 1, May 2024 which can affect energy demand by increasing consumption and fixed investment by firms. (Levine 1997; Xu 2000; and Fung 2009). Financial development can affect energy demand in several ways. One of the most direct ways that financial development can affect energy demand is by making it easier and cheaper for consumers to borrow to purchase high-value goods such as automobiles, homes, refrigerators, air conditioners, and washing machines (Mankiw & Scarth 2008). These consumer goods are typically energy intensive, which can negatively impact energy demand. Businesses also benefit from improved financial development, as it is easier for them to obtain and spend funds. The access to financial capital that can be used to expand existing businesses (purchase or construction of factories, buildings, etc.), to expand existing businesses, or to create new the ones. The development of stock markets is particularly attractive to businesses because it allows them to access an additional source of financing, equity financing, which can be used to expand the business in addition to capital investment. Increased stock market activity can increase risks for both consumers and businesses, which is an important component of wealth creation in an economy. Increased stock market activity also creates a wealth effect, which in turn affects consumer and business confidence (Mankiw & Scarth, 2008). The stock market is often considered a leading economic indicator, and increased stock market activity can be seen as a sign of economic growth and improved competitiveness which in turn creates increased economic confidence and increased economic activity and demand for energy. According to Sadorsky (2010), financial development can affect energy use in two ways: Positive influence: This occurs through three channels: the direct influence, the business effect, and the wealth effect. Customers benefit directly from effective financial intermediation since they can quickly find resources and hence buy sustainable products, thus increasing demand for energy. The commercial impact is attributable to an increasing trend toward financial development, which improves enterprises' access to financial capital. Financial development enables businesses to obtain cheaper financial resources in order to expand their operations or establish a new company, hence increasing energy consumption. The wealth impact is caused by firms and families' confidence in established stock markets. In 2010, Sadorsky discovered a direct correlation between financial progress and energy use. In his key study, Sadorsky, (2010) employed the dynamic panel approach to examine the impact of financial development on energy consumption in 22 developing countries from 1990 to 2006. His findings showed that there is a considerable positive association between financial progress and energy usage. Sadorsky used a similar strategy to investigate the relationship between finance and energy in nine Central and Eastern European nations between 1996 and 2006, and discovered a positive relationship between the variables (Sadorsky 2011). Negative influence In this situation, financial development may cut energy use by enabling the development of innovative technology. The technological effect refers to the negative impact of financial development on energy consumption, which pushes the implementation of energy-saving and efficient technologies. It reduces energy use and CO2 emissions. It also increases energy efficiency by preserving technical innovation. 2.2 Empirical review In recent years, empirical research has focused on the relationship between financial development and energy usage, with varied results. On the one hand, several studies have found that more financial development leads to increased energy use. For example, Shahbaz et al. (2010) used the ARDL bounds testing approach to investigate the effects of financial development on energy usage in Pakistan and discovered a considerable positive effect. Similarly, Islam et al. (2013) employed the vector error correction model (VECM) to determine how economic growth and financial development effect energy consumption in Malaysia. Meanwhile, Tang and Tan (2014) conducted research on the Malaysian economy from 1972 to 2009 utilizing the Johansen- The effect of financial development on renewable energy consumption in Cameroon // Economic Review – Journal of Economics and Business, Vol. XXII, Issue 1, May 2024 77 /// Juselius cointegration test and the boundary testing approach. They discovered a long-term correlation between energy usage and financial progress. Xu (2012) used the GMM system to investigate financial development and energy consumption in 29 Chinese provinces from 1999 to 2009. His findings revealed a positive and statistically significant relationship between financial development and energy consumption when financial development is measured by the ratio of a financial institution's loans to GDP and the ratio of FDI to GDP. Coban and Topcu (2013) used the System GMM model to study the relationship between financial development and energy use in the European Union (EU) from 1990 to 2011. Their empirical findings give solid evidence that financial development has a positive impact on energy usage in the elderly, regardless of whether it originates from the banking sector or the stock market. Chang's (2015) analysis is based on a sample of 53 nations from 1999 to 2008, separated into two categories: highincome and non-high-income. Their findings revealed that in a non-high-income regime, energy consumption rises in tandem with financial development, which is measured by private and domestic credit. However, financial progress is measured by the value of traded shares and stock market turnover; in advanced nations, energy consumption declines slightly while increasing in higher-income countries in emerging and developing economies. Rashid and Yousaf (2015) discovered a positive and significant correlation between financial development and power use. Rafindadi and Ozturk (2016) discovered that financial development had a favorable impact on energy usage in Japan from 1970 to 2012. Paramati et al. (2016) examined the impact of foreign capital and stock market development on renewable energy usage in 20 emerging economies, using data from 1991 to 2012. They discovered that foreign capital and stock market development have a significant impact on enhancing renewable energy use across all country groupings. Kahouli (2017) used the autoregressive distributed lag limits (ARDL) approach to investigate the relationship between energy use and financial development in southern Mediterranean countries. It discovered evidence of a long-term beneficial relationship between financial development and energy use in Israel, Morocco, and Tunisia. Liu et al. (2018) used the ARDL limits technique and discovered that between 1980 and 2014, financial development in China had a favorable short- and long-run impact on energy demand. Other research, however, shows a negative relationship between financial progress and energy usage. For example, in a sample of 20 developing nations, Mielnik and Goldemberg (2002) discovered a clear drop in energy intensity when FDI (a measure of financial progress) grew. Sadorsky (2010) demonstrated that financial development could cut energy use by enabling the development of innovative technologies. The negative influence of financial development on energy consumption is known as the technology effect (Tamazian et al. 2009, Jalil and Feridun 2011, Shahbaz et al. 2013, Mahalick and Mallick 2014, Shahbaz et al. 2017). Later, Topcu and Payne (2017) investigated the impact of financial development on energy use in a panel of 32 high-income countries from 1990 to 2014. Their findings indicate that there is no statistical correlation between the total financial development index and energy use. They do, however, demonstrate that an increase in the stock market index results in a modest drop in energy use. Destek (2018) investigated the relationship between financial development, energy prices, real income, and energy consumption in 17 rising economies from 1991 to 2015 using a three-dimensional financial development management model (banking sector, stock market, and bond market). The empirical findings indicate that the development of the banking and bond markets has a negative and statistically significant impact on energy usage. Ouyang and Li (2018) used the GMM panel VAR technique to analyze the endogenous relationship between financial development, energy consumption, and economic growth in China, using quarterly frequency data from 30 Chinese provinces from 1996 to 2015. Their findings indicated that financial development in terms of M2, credit, and inventory turnover might dramatically cut energy use. More recently, Canh et al. (2020) examined the ///. Nguiffo Joel Salomon, Etoa Etoa Jean Bosco /// 78 Economic Review: Journal of Economics and Business, Vol. XXII, Issue 1, May 2024 relationship between financial development and the energy intensity of consumption and production in 81 economies from 1997 to 2013. Their studies demonstrated that over time, financial institutions had a greater impact on energy intensity than financial markets. Furthermore, in the event of an oil shock, nations with higher levels of financial development see a decrease in the energy intensity of their output, whereas those with stronger financial institutions see a decrease in the energy intensity of their consumption. From 1984 to 2015, Chiu and Lee (2020) investigated the relationship between energy consumption, financial development, and country risk in 79 nations and two subgroups. Their findings revealed that under a stable country-risk context, financial development leads to less energy usage. Benkraiem et al. (2019) claimed that positive and negative shocks to financial development affect energy usage in opposite directions. Aside from the research cited above, which examines the relationship between financial development and traditional energy consumption, just a few publications address renewable energy consumption. Wu and Broadstock (2015) evaluated data from 22 emerging nations between 1990 and 2010, and discovered that financial development and institutional quality have a favorable and significant impact on renewable energy use. Best (2017) used data from up to 137 nations from 1998 to 2013 to study the role of financial capital in the growth of energy use. He discovered that financial capital facilitates the shift to more capital-intensive energy sources. For high-income countries, financial capital serves as a stimulus for the shift from fossil fuels to modern renewable energy sources, particularly wind power. Kutan et al. (2017) examined data from Brazil, China, India, and South Africa from 1990 to 2012 and found that FDI flows and stock market development have a significant impact on renewable energy use. Similarly, Burakov and Freidin (2017) examined the causal relationship between financial development, economic growth, and renewable energy usage in Russia from 1990 to 2014. Their findings indicated that there was no causal relationship between financial development and renewable energy consumption. Ji and Zhang (2019) demonstrated, using a time series analysis of Chinese stock market data from 1992 to 2013, that financial development is critical and accounts for more than 40% of the variation in the evolution of renewable energy share. Anton and Nucu (2020) conducted empirical research based on a fixedeffects panel model using panel data from 28 EU nations between 1990 and 2015 to investigate the effect of financial development on renewable energy usage. The results they obtained show that various components of financial development (banking sector, bond market, and capital market) raise the proportion of renewable energy use. They also stated that the expansion of the capital market had little impact on renewable energy use in the new EU member states. Our paper differs from others in the literature in two ways. First, it is the first to investigate the role of financial development in determining renewable energy consumption while accounting for the ratio of commercial banks per adult and economic development as additional factors. Second, available literature indicates a growing interest in increasing renewable energy use. Clear evidence of the role of financial development has been found, but only in a select group of countries. While these cross-national studies provide important information on the impact of financial development on renewable energy usage, they do not address Cameroon's specific conditions. As a result, this article is one of the first to quantify the influence of financial development on Cameroon's renewable energy usage. The empirical findings may assist policymakers in taking steps to promote renewable energy consumption and create an economically efficient and environmentally sustainable energy system. Given that renewable energies are more expensive than traditional energy sources (Anton and Nucu 2020), they require a greater access to financial resources (debt and/or equity). In other words, the growth of the financial industry can spur investment in clean and renewable energy. A positive relationship between financial development and renewable energy consumption is expected. Based on recent literature, the following hypothesis is tested: There is a positive relationship between The effect of financial development on renewable energy consumption in Cameroon // Economic Review – Journal of Economics and Business, Vol. XXII, Issue 1, May 2024 79 /// financial development and renewable energy consumption in Cameroon. Our equation model will represent a general specification, aimed at examining the role of financial development indicators on renewable energy consumption in Cameroon over a period from 2000 to 2022, where renewable energy consumption is treated as a dependent variable while banking, stock and bond indicators, FDI, the consumer price index and GDP per capita are treated as explanatory variables. We will therefore use time series econometrics. 3. Methodology 3.1 Data source and choice of variables The data used in this article are based on the annual time series data for Cameroon over the period 2000 to 2022. The period was chosen on the basis of the availability of all the data series. The source of the data is the World Bank's World Development Indicators (WDI). The dependent variable is renewable energy consumption (REN), measured as the share of renewable energy in total final energy consumption. In line with previous work, Chang (2015); Coban and Topcu, (2013), Regean and Bulime, (2024), financial progress is possibly quantified by the factors below: • Foreign direct investment (FDI) is measured as net inflows as a proportion of GDP. • Domestic credit granted by the financial sector (CIF) (% of GDP): as an indicator of the development of the banking sector. • Outstanding international private debt securities (ETDPI) in relation to GDP (%), as an indicator of the development of the bond market. • The Consumer Price Index (CPI) is used as an indicator of energy prices, as data on energy prices is not readily available following previous studies. • The ratio of commercial banks per adult (BCA): Represents the number of commercial banks likely to grant credit per 100,000 adults, and measures the accessibility of bank credit for adults. • The economic development (ED): measured by GDP per capita based on purchasing power parity (PPP) (constant 2011 international). • GDP growth (CPIB), (annual %): represents income, and is measured by the annual percentage growth rate of GDP per capita based on a constant local currency. Table 1. Description of variables Names Abbreviations Source Renewable energy consumption REN WDI (World Development Indicators), World Bank 2022 Foreign direct Investment FDI Domestic credit granted by the financial sector CIF Outstanding international private debt securities ETDPI Consumer Price index CPI Commercial bank ratio per adult BCA Economic development ED GDP growth (annual %) CPIB Source: author, taken from WDI ///. Nguiffo Joel Salomon, Etoa Etoa Jean Bosco /// 80 Economic Review: Journal of Economics and Business, Vol. XXII, Issue 1, May 2024 3.2 Model specification Following the most relevant previous studies (Chang 2015; Regean and Bulime, 2024), our model is written as: RENt = a0 + a1 FDIt + a2 CIFt + a3 ETDPIt + a4 CPIt + a5 BCAt + a6 EDt + a7 CPIBt + µt, where the time period is denoted by the index t (t=1, ..........T); a1 ,....,a7; a0 and µt represent the constant and the error term respectively. The regression coefficients are estimated by the regression analysis. They show that, assuming that the other variables remain fixed, an increase of one unit in an explanatory variable increase (or decreases) the renewable energy consumption of units "a". Before estimating the long-term relationship, the nonstationarity of the variables must be tested. The Augmented Dickey Fuller (ADF) test developed by Dickey and Fuller (1981) and the Phillips Perron (PP) test are used for this exercise. After indicating the integration of the variables in the same order, in the next stage the variables will be tested for a long-term cointegration relationship. The Johansen tests will be used to test the cointegrating relationship. 4. Results 4.1 Descriptive statistics and Stationarity test We can see that the series analyzed show significant variations over time, and the standard deviation for all the variables is high (Table 2). We would check to see if our different variables are stationary, as they are usually stationary at the level (Greene, 2002). If they contain trends and hence are nonstationary, we must make them stationary to avoid the possibility of regressions across variables. This test will be performed using Stata 17 with the ADF (Augmented Dickey- Fuller) and PP (Phippips Perron) tests. From the Table 3, we can see that none of our variables is stationary at level according to the ADF and PP tests. On the other hand, for these same tests, all our variables become stationary in first difference. 4.2. Optimal delay and cointegration To find the lag number (p) of our VAR model, we will use the Akaike (AIC) and SBIC criteria. Table 4 reports the results obtained. The optimal delay, i.e. the one that minimizes the AIC and SBIC criteria, is p=1, so our model is a VAR (1). To analyze the long-term relationship between our variables, we will use Johansen's cointegration test, with the following hypotheses: H0: no cointegration; H1: cointegration The results of the cointegration test are shown in Table 5. According to Table 5, we accept the hypothesis H0, i.e. that there is no cointegrating relationship at the 5% threshold, as the trace statistic is below the critical value (11.9671 ˂ 15.41). The most suitable model for this analysis is therefore the VAR (Vector Autoregressive) model. The VAR technique is appropriate in this case because of its ability to characterize the dynamic structure of the model as well as its ability to avoid imposing excessive identification restrictions associated with different economic theories. The use of VAR in macroeconomics has generated a wealth of empirical evidence, providing fundamental support for many economic theories (Blanchard and Watson, 1984, Bernanke, 1986 among others). The VAR model is adopted for this study because of its predictive power relative to large structural models. Again, one of the common virtues of the VAR model is that it avoids having to decide which contemporaneous variables are exogenous, all variables being endogenous. 4.3 VAR model results (1) The results of the estimation of the parameters of our VAR model (1) are summarized in Table 6. The regression results appear to be fairly satisfactory. The log likelihood is fairly high (Log likelihood = -1068.406), which means that our model fits well. The probability of the F- statistic (0.0000) is less than 5%, which shows that the model is significant overall. The selected variables significantly explain renewable energy consumption in Cameroon. 4.4. Model validity tests The effect of financial development on renewable energy consumption in Cameroon // Economic Review – Journal of Economics and Business, Vol. XXII, Issue 1, May 2024 87 /// Table 5. Results of the cointegration test Johansen test for cointegration Rank Trend : Constant Number of obs : 22 Sample : 2001 thru 2022 Number of lags : 1 Trace statistic Critical value 5% 0 32.2375 29.68 1 11.9671* 15.41 2 1.3955 3.76 *selected rank Source: author, based on STATA 17 Table 6. VAR model regression results (1) Note: ***, ** and * represent significance at 1%, 5% and 10% respectively Figures in brackets are standard deviations. Source: Author, based on STATA 17 Table 7. Results of normality test for residuals Variables Coef T-Stat REN (1) FDI L1. -1.99** (8.63) 0.021 CIF L1. 1.119** (0.561) 0.046 ETDPI L1. -2.489*** (0.670) 0.000 CPI L1. -5.493*** (1.181) 0.000 BCA L1. 14.243* (7.725) 0.065 ED L1. 3.02*** (7.90) 0.000 CPIB L1. 2.974** (1.551) 0.055 Cons 385.402 (81.923) 0.000 Sample: 2001 thru 2022 Log likelihood = -1068.406 FPE = 2.20e+35 Det (Sigma_ml) = 2.10e+32 P>chi2 = 0.0000 Number of obs = 22 AIC = 103.6733 HQIC = 104.5144 SBIC = 107.244 ///. Nguiffo Joel Salomon, Etoa Etoa Jean Bosco /// 88 Economic Review: Journal of Economics and Business, Vol. XXII, Issue 1, May 2024 Source: author, based on STATA 17 Table 8. Autocorrelation test results for residuals Source: author, based on STATA 17 Figure 1. Breusch-Pagan test result Source: author, based on STATA 17 Equation Chi2 Df Prob > chi2 REN 1.922 2 0.78258 FDI 1.309 2 0.51959 CFI 1.296 2 0.88318 ETDPI 0.046 2 0.97717 CPI 0.441 2 0.80224 BCA 1.278 2 0.52783 ED 0.017 2 0.99139 CPIB 0.300 2 0.86065 ALL 22.609 16 0.12459 Lag Chi2 df Prob˃chi2 1 34.0907 25 0.10598 2 60.4348 25 0.28799