1. Introduction
Subsequent to the oil crisis in the 1970s, energy economics has become one of the most popular research areas, which is broadly expanded in the context of the energy-growth nexus. Undoubtedly, energy economics with social and economic dimensions is followed closely by both scholars and policymakers. In the second decade of the 21st century, augmented energy demand functions have added some new variables in order to measure these social and economic impacts employing trade, urbanization, and financial development.
Papers studying the impact that financial development has on energy consumption are focused at the aggregate level. Some papers, however, suggest that a transition process that causes a gradual shift from agriculture, or from manufacturing to services, may exhibit some structural changes in the sectoral output composition of developing economies. Compared with a less energy-intensive industry, financial development is expected to create more energy demand in an energy-intensive industry. In a similar manner to aggregated analyses, one should anticipate financial development to have a significant impact at the disaggregated level. Given these assumptions, the primary hypothesis suggested herein is “the impact of financial development may affect energy consumption even at the disaggregate level”. As these impacts are expected to differ across the energy intensity of related industries, the second hypothesis is “financial development affects energy-intensive industries more than less energy-intensive industries”.
Departing from the hypotheses above, the goal of this paper is to investigate the impacts of financial development on sectoral energy consumption in Turkey. To this end, the relevant disaggregated relationship has been tested within a panel data framework over the period 1989–2011. We hope that the existing study will contribute to the empirical literature in several ways. First, previous studies on this issue have analyzed the nexus at the aggregate level and no micro-level analysis with disaggregated data has been carried out before to the best of our knowledge. The present study is therefore going to fill this gap. Second, Levine and Zervos (1998) [
1] argue that the impact of financial development on economic growth might differ across the source of financial development. There exist a few studies in the finance-energy literature in which the source of financial development has been separated (see, for example, Sadorsky, 2010 [
2]; Sadorsky, 2011 [
3], Coban and Topcu 2013 [
4]). Previous papers in the case of Turkey (Ozturk and Acaravci, 2013 [
5]; Zeren and Koc, 2014 [
6]) merely use bank-related variables as well. Thus, the existing study will be the first to measure the impact of financial development using both banking and stock market variables in the case of Turkey. Third, recent developments in panel data econometrics allow researchers to use new approaches, taking heterogeneity into account and obtaining cross-sectional results as well as pooled panel results. As a convenient framework for the latest trends, the empirical basis of this study depends on panel time series regression and causality methods.
The rest of the paper is structured as follows:
Section 2 explains the theoretical relationship and reviews the related literature,
Section 3 describes the data and model,
Section 4 presents methods and empirical results,
Section 5 discusses policy implications, and
Section 6 provides concluding remarks.
3. Model and Data
In line with theory and the empirical literature (see, for example, Sadorsky, 2010, 2011 [
2,
3]; Xu 2012 [
38], Khan et al., 2014 [
39]; Tang and Tan, 2014 [
19]), energy consumption in this study is described as a function of income (y), prices (p), and financial development (fd):
The Turkish Republic Ministry of Energy and Natural Resources calculates total energy consumption as a sum of five sectors. Therefore, micro-level energy consumption data includes the following sectors: (i) industrial; (ii) transportation; (iii) residential and services; (iv) agriculture; and (v) non-energy
1. The panel data augmented form of function (1) is presented in Equation (2) below:
where
v denotes the sector-specific variable and
є denotes the random error term. The time dimension consists of annual observations from 1989 to 2011. Energy consumption (e) is measured as energy use in kg of oil equivalent per capita and attained from the Turkish Republic Ministry of Energy and Natural Resources statistics [
40]. On the right-hand side, income (y) is measured by real GDP per capita (PPP, constant 2005 US$). Consistent with the literature, energy prices are proxied using real oil prices. Dubai and Brent oil prices
2 are converted into real terms by the consumer price index (CPI, 2005 = 100)
3. Data for income and the consumer price index are available from the World Bank World Development Indicators database. Oil price data are gathered from British Petroleum’s Statistical Review of World Energy database [
41].
Given the baseline proposed by Levine and Zervos (1998) [
1], financial development (
fd) is divided into two parts as described in function (3):
where
fdbank represents the banking sector development and
fdstock represents the stock market development.
where banking sector (
fdbank) is proxied using four bank-related variables: deposit money bank assets to GDP (
dbagdp), financial system deposits to GDP (
fdgdp), private credit by deposit money banks and other financial institutions to GDP (
pcrdbofgdp), and liquid liabilities as a share of GDP (
llgdp).
where stock market development (
fdstock), on the other hand, is represented by three proxies: stock market value traded to GDP (
stvaltraded), stock market turnover ratio (
stturnover), and stock market capitilization to GDP (
stmktcap).
The dataset for the financial development variables is obtained from the World Bank Financial Development and Structure database [
42]. Empirical estimations have been carried out using Eviews and Stata software.
5. Discussion and Policy Implications
The empirical results reported herein can be used for an extensive discussion addressing how consistent existing results are with the relevant theories and previous literature. For each model/specification, the positive and significant coefficients on income indicate the validity of the hypothesis “energy consumption rises with increases in income,” not only at the aggregate level but also at the disaggregated level
8. In non-energy use industry, in particular, the coefficients on income in all specifications are dramatically greater than those of other sectors. A possible reason for this finding could be the production structure of the industry, which is pretty homogeneous. For the pooled panel, although the impact of prices on energy consumption is negative, which is consistent with theory, it is not statistically significant, regardless of the proxy. This finding might explain why energy consumption is heavily influenced by income. Sadorsky (2011) [
3], for instance, finds for Central and Eastern European countries that income does not have a significant impact on energy consumption. Income, therefore, seems to be more important in determining energy demand in Turkey over this particular period of time. Furthermore, the negative and insignificant impact of energy prices on energy consumption is also in line with Xu (2012) [
38], who finds a downward sloping but insignificant energy demand equation in China. Note that the impact of energy prices on the transportation sector’s energy consumption is also insignificant in each specification. However, the estimated coefficients are positive even if they are close to zero. This could be evidence of a fully rigid price elasticity in the transportation industry, where fuel is considered a necessary input.
Results for the pooled panel reveal that both banking and stock market developments have a significant positive impact on energy consumption in Turkey. The magnitude of stock market development, however, is larger than that of banking development. This finding points out the efficiency of the wealth effect. It is also totally consistent with Sadorsky (2010) [
2], who reports the positive impact of stock market development on energy use in emerging economies. Findings obtained from nonlinear models indicate that the impact of financial development (no matter what the source is) on energy consumption in the industry sector is an inverted U-shaped curve. This result suggests that access to financial capital easily and less expensively leads to more manufacturing and an increase in energy consumption; a gradual shift later on from manufacturing to services leads to a drop in energy consumption. Both banking sector and stock market development affects energy consumption positively in the transportation sector via the direct effect channel in addition to the business effect channel. Results for residential services and the agricultural industry show that the impact of financial development on energy consumption displays a U-shaped pattern. This might be very hard to explain at first glance. Indeed, it goes with the results of the industry sector. In the early stages of financial development, the utilization of production factors in manufacturing leads to a decrease in energy consumption in other dominant industries. Expansion in the potential of manufacturing leads to factor mobilization from manufacturing to services. Expanded business potential is expected to lead to an increase in energy consumption in these industries
9. The only sector in which financial development does not significantly affect energy consumption in any specification/model is non-energy use. This makes sense given the relative unimportance of the non-energy use industry in the sectoral composition of energy consumption.
Overall, the results indicate that development in the financial system is expected to affect production and energy consumption in the industry sector initially, and then shift to other sectors. Furthermore, inflection points reveal that financial development leads to an increase in energy consumption in the residential and service sectors before the agricultural industry. This finding, which points out that residential services benefit from financial development earlier than the agricultural industry, is very robust to the source of financial development.
Causality analyses in the field of energy economics are expected to provide some preliminary information to policymakers on whether energy conservation policies would be in conflict with economic targets. Disaggregated evidence obtained from causality analysis indicates the existence of the conservation hypothesis in three sectors, namely (i) industrial; (ii) transportation; and (iii) residential services. In these sectors energy conservation policies could be implemented without a significantly adverse impact on the financial system. This finding clearly shows that policymakers could aim at decreasing energy intensity regardless of any economic or financial consequences. Moreover, tending towards alternative resources and investing in technologies that help to increase the use of renewable energy sources is expected not to have a harmful impact on the financial system. In short, the negative environmental impacts of using fossil fuels in these sectors, in particular transportation, can be kept down without considering any financial restriction.
Causality results suggest that the neutrality hypothesis is valid in the case of agricultural and non-energy use sectors. Given a gradual shift from agriculture to services, changing sectoral composition could make sense of why financial development and agricultural energy consumption is interdependent. No causality in the case of non-energy use sector, on the other hand, might be explained given the relative unimportance of this sector in the sectoral composition of energy consumption.
This study provides some macro level evidence as well as disaggregated findings. Financial development that occurs in the current period affects energy consumption during the two subsequent periods, while the opposite holds true for the following three periods. Thus, energy conservation policies at the aggregate level might deteriorate the financial sector after a certain period of time. Policymakers therefore have to keep in mind that policies increasing energy efficiency might eventually affect economic activity. Under such a long-term condition, growth can only be promoted via a well-functioning banking system and stock market, and thus the demand for energy will be enhanced.
When it comes to cross-sectional results in terms of lag lengths, the findings are of interest. It should be emphasized that financial development that occurs in a certain period of time initially affects energy demand in the industrial sector, and then transportation and residential services. For agricultural and non-energy use sectors, the only interpretation one could make is that the impact
10 of financial development needs at least four periods
11 to exist on energy consumption. At the aggregate level, financial development primarily affects energy consumption, which in turn affects financial development.
Although there are a limited number of studies on the finance-energy nexus in the case of Turkey, it is possible to compare the results of the existing study with those provided by the relevant literature. Findings obtained from the pooled panel show the validity of the feedback hypothesis between financial development and energy consumption. While this result is totally consistent with the results of Zeren and Koc (2014) [
6], it is partially consistent with the results of Ozturk and Acaravci (2013) [
5] that report uni-directional causality from energy consumption to financial development in the short term. In terms of the energy-growth literature, this study supports the bulk of the literature that reports bi-directional causality between energy consumption and growth (see, for example, Akan et al., 2010 [
56]; Erdal et al., 2008 [
57]; Kaplan et al., 2011 [
58]). In addition, it is also possible to compare the results of this study with the papers on energy-growth nexus at the disaggregated level. The findings of this study do not support those of Jobert and Karanfil (2007) [
59], who suggest the existence of the neutrality hypothesis either in pooled panel or in the industry sector. From an international energy-growth perspective, on the other hand, the findings of this study are consistent with the results of Tang and Shahbaz (2013) [
37], who report the validity of the neutrality hypothesis in Pakistan’s agricultural sector. Similarly, the results are consistent with those of Zhang and Xu (2012) [
34], who find support for the conservation hypothesis in industry, residential, transportation, and services in China.