Jamal Bouoiyour
email: jamal.bouoiyour@univ-pau.fr

Refk Selmi

Muhammad Shahbaz
email: shahbazmohd@live.com

THE ELECTRICITY CONSUMPTION IN A RENTIER STATE: DO INSTITUTIONS MATTER?

Keywords: Electricity consumption, institutions, rentier state

The core focus of this paper is to assess the relationship between the electricity consumption and institutions within rentierism phenomenon by incorporating economic growth, urbanization, trade openness and foreign direct investment in the case of Algeria. To this end, we have applied the ARDL bounds testing approach to cointegration and innovative accounting approach (variance decomposition and impulse response methods) over the period of 1971-2012. Our empirical results show that these variables are cointegrated in the long-run.

We find that institutions play an important role to explain this cointegration. The response of electricity demand is increasingly negative due to the one standard deviation shock in institutions. This highlights an insightful evidence, providing that the poor governance drawbacks in a rentier state may affect directly electricity consumption or indirectly via urbanization and foreign direct investment. The contribution of economic growth to electricity consumption appears minor (the conservation hypothesis is limitedly supported), while that of trade openness seems insignificant.

Introduction

Electricity is an important factor of production for both developed and developing countries. Controlling this factor seems a great challenge not only for businesses but also for policy makers. The first ones focused on controlling the production costs. The second ones aim to improve the rate of economic growth and to use cleaner energy forms to enhance environmental protection. This is why the relationship between energy consumption -in general and electricity consumption particularly-and economic growth has received appreciable attention in the existing energy economics literature, either theoretically or empirically.

Given the importance of this issue in formulating the energy policies, the causal relationship between energy consumption and economic growth has been and continues to be one of the main subjects of intense empirical economics' research. The purpose of assessing the causal link between these two variables is to make policy recommendation for government. For example, if there is an unidirectional causal relationship running from economic growth to energy consumption, this means that a conservative energy policy plays an important role to enhance economic development (the conservation hypothesis). In addition, if the energy consumption is a crucial component in economic growth (the growth hypothesis), this implies that while energy is a limiting factor to economic growth, a policy to increase investment in industrial sectors, particularly electrification is likely to stimulate economic development. We can also identify the bidirectional causality (the feedback hypothesis), emphasizing an interdependent relationship between electricity consumption and economic growth. Moreover, energy can have no impact on economic growth and vice versa (the neutrality hypothesis), suggesting that neither conservative nor expansive energy policies have any effect on economic growth. The results of these studies are mixed and inconclusive.

They depend to the different country coverage, econometric methodologies and data disponibility (see for example, [START_REF] Apergis | CO2 emissions, energy usage, and output in Central America[END_REF] and [START_REF] Ozturk | A literature survey on energy consumption-growth nexus[END_REF]). [START_REF] Bouoiyour | The Nexus between Electricity Consumption and Economic Growth: New Insights from Meta Analysis[END_REF] add that energy policies cannot be designed without considering economic and political factors, which are unfortunately excluded in the majority of researches.

Our study differs from the previous works on the same field. It not only re-assesses the above assumptions, but it attempts to give novel insights and some new explanations to elucidate understanding on the concerned relationship. Among these elements of explanation, this research considers institutions as the focal factor that explains the cointegration between electricity consumption and economic growth by incorporating other explanatory variables that may have effect on electricity consumption. Normally, the results should help policy makers in implementing future electricity policies for sustainable economic growth in longrun.

This study has focused on the Algerian case for six main reasons: Firstly, few studies have investigated how interact institutions with energy consumption-economic growth nexus on the case of Algeria. [START_REF] Alvarez | Rentierism in the Algerian economy based on oil natural gaz[END_REF] and [START_REF] Fuinhas | Rentierism, energy and economic growth: The case of Algeria and Egypt (1965-2010)[END_REF], for example, have well invoked the institutions to explain the fact that energy consumption negatively impacts economic growth, but this has not been demonstrated. This improves the need to an accurate investigation on the field. Secondly, the electricity sector concerns a major part of the population but it receives a low priority and a limited attention at policy level. This sector is not regulated, not organized between producers and consumers and stills an informal sector [START_REF] Mebtoul | L'Algérie face à la concurrence et à la transition énergétique mondiale[END_REF]. Thirdly, Algeria is a large consumer of electricity compared to its Maghreb neighbours. The electricity is largely produced from gas in Algeria, which covers 96% of electricity demand in the country in 2013. A 3% comes from diesel, especially for the isolated areas (the South), and 1% from water. This country has experienced an electrification rate of 41% in 1970 to nearly 99% in 2013, classed as one of the most important rates in the world.

Fouthly, residential consumption accounts for 60% of total electricity consumption, while consumption in the industrial sector is about 10%. For comparison, these percentages are respectively 30% and 45% in Europe. This highlights the gap that separates Algeria from its European neighbors. Then, an assessment of the relationship between electricity consumption and its determinants, with a predominant source of rent (hydrocarbons), refers to the issue of energy transition that the Algerian government tries to implement. This energy transition can be hardly achieved given the inherent constraints closely related to the question of the energy's usage in Algeria. This question is itself highly linked to the wider issue of governance in this country, especially in light of the Arab revolutions across the North Africa and Middle East region. Finally, Algeria is characterized by the existence of a powerful state and a well-established structure that has preserved its expansive prerogatives and has enhanced its power. Under these conditions, innovative or creative individual initiatives are, de facto, limited. The rentier economy allows the state to have sufficient resources to subsidize of most consumer products, which inhibit the emergence of an industrial spirit. The main aim of the paper is to explain why Algeria failed to join the club of higher performers.

The quality of institutions may properly constitute a substantial element of explanation. We address this issue by interplaying institutions with the relationship between electricity consumption and its determinants.

The remainder of the article is laid out as follows. In Section 2, we briefly review previous empirical research into the relationship between electricity consumption, institutions and economic growth. Section 3 presents an overview on the link between electricity demand and institutions in a rentier state. Section 4 presents the followed methodology. Section 5 describes and discusses the results, while the last section concludes and offers some economic implications.

Brief literature survey

The sizeable growing energy consumption, the steady increase in energy prices and the continuous reconfiguration of energy markets present an array of problems often highlighted by policy makers. This, in turn, make economists increasingly pay attention to energy consumption as an important determinant of economic growth (see, for example, [START_REF] Kraft | On the relationship between energy and GNP[END_REF], [START_REF] Soytas | Energy consumption and GDP: causality relationship in G-7 countries and emerging markets[END_REF], [START_REF] Lee | The causality relationship between energy consumption and GDP in G-11 countries revisited[END_REF], [START_REF] Tang | A re-examination of the relationship between electricity consumption and economic growth in Malaysia[END_REF], [START_REF] Ghosh | Electricity supply, employment and real GDP in India: evidence from cointegration and Granger-causality tests[END_REF], Al-Mulati (2011[START_REF] Niu | Economic growth, energy conservation and emissions reduction: A comparative analysis based on panel data for 8 Asian-Pacific countries[END_REF][START_REF] Dobnick | Energy consumption and economic growth revisited: structural breaks and cross section dependenc[END_REF], Sadrosky (2012), [START_REF] Shahbaz | Is energy consumption effective to spur economic growth in Pakistan? New evidence from bounds test to level relationships and Granger causality tests[END_REF], [START_REF] Farooq | Does corruption impede economic growth in Pakistan?[END_REF], [START_REF] Bouoiyour | The nexus between electricity consumption and economic growth in MENA countries[END_REF], [START_REF] Bouoiyour | The Nexus between Electricity Consumption and Economic Growth: New Insights from Meta Analysis[END_REF], [START_REF] Sbia | A contribution of foreign direct investment, clean energy, trade openness, carbon emissions and economic growth to energy demand in UAE[END_REF]). Despite this huge amount of empirical research on this field, neither the theoretical nor the empirical literature finds one-sided evidence with respect to the nature of this relationship (short-run, long-run or joint links) or to the direction of causation. Due to different studied countries, econometric methodologies, time periods and variables, there is no cut-clear consensus for this focal relationship.

The different results frequently obtained by previous studies may be synthesized into four testable hypotheses 1 1 The denotations of neutrality hypothesis and the bidirectional link or the feedback hypothesis have been widely used by the previous studies on the energy consumption-economic growth nexus. However, the denotations of the other directions of causality (i.e. growth hypothesis and conservation hypothesis) were proposed by [START_REF] Apergis | CO2 emissions, energy usage, and output in Central America[END_REF].

. First, the conservation hypothesis is based on a unidirectional causal relationship running from economic growth to energy consumption [START_REF] Lee | Structural breaks, energy consumption, and economic growth revisited: evidence from Taiwan[END_REF], [START_REF] Tang | A re-examination of the relationship between electricity consumption and economic growth in Malaysia[END_REF], [START_REF] Arouri | Energy Consumption, Economic Growth and CO2 Emissions in Middle East and North African Countries[END_REF]). Second, the growth hypothesis suggests that energy consumption is a crucial component in economic growth. This means that while energy is a limiting factor to economic growth, a policy to increase investment in industrial sectors, particularly electrification is likely to stimulate economic activity and hence economic growth [START_REF] Wolde-Rufael | Energy demand and economic growth: the African experience[END_REF], [START_REF] Al-Ariani | Energy-GDP Relationship Revisited: An Example from GCC Countries Using Panel Causality[END_REF], [START_REF] Zamani | Energy consumption and economic activities in Iran[END_REF] and Gosh ( 2009)).

Third, the feedback hypothesis or the bidirectional causality emphasizes an interdependent relationship between electricity consumption and economic growth [START_REF] Masih | Energy consumption and real income temporal causality, results for a multi-country study based on cointegration and error-correction techniques[END_REF] and [START_REF] Ghali | Energy use and output growth in Canada: a multivariate cointegration analysis[END_REF]). Fourth, the neutrality hypothesis means that energy consumption is not correlated with economic growth and suggests that neither conservative nor expansive energy policies have any effect on economic growth (Soytas end Saris (2003) and [START_REF] Chiou-Wei | Economic growth and energy consumption revisited-evidence from linear and nonlinear Granger causality[END_REF]).

All the above researches have neglected the role that plays governance in explaining the relationship between electricity consumption and economic growth in rentier state. Surprisingly, Middle East specialists have long invoked poor governance (weakness of institutions), rentier economic development, severe social disparities and repression that characterize the region [START_REF] Schwarz | The Political Economy of State-Formation in the Arab MENA region: Rentier States, Economic Reform and Democratization[END_REF], [START_REF] Foley | The Arab Gulf States: Beyond Oil and Islam[END_REF], [START_REF] Gray | Towards A Theory of Late Rentierism[END_REF] and [START_REF] Elbadawi | Democracy in the Arab World: Explaining the Deficit[END_REF]). Despite these interesting conclusions that may have important economic implications, a limited strand of literature has focused on the interplay between electricty consumption, economic growth and institutions. For instance, [START_REF] Auty | The political economy of resource-driven growth[END_REF], [START_REF] Gylfason | Natural resources, education, and economic development[END_REF], [START_REF] Damania | Resources for sale: Corruption, democracy and the natural resource curse[END_REF], Aslaksen and Torvi (2005) and [START_REF] Farooq | Does corruption impede economic growth in Pakistan?[END_REF] argue that corruption could be blamed for the failure of a number of energy-rich economies to develop.

In the economies with rentierism characteristics, the relationship between electricity consumption and economic growth may be more complicated, i.e. given to poor governance in MENA countries, energy subsidies are infamously inefficient, which makes the dynamic interaction between electricity consumption and economic growth more complex that has been sometimes claimed [START_REF] Stevens | Resource curse: An analysis of causes, experiences and possible ways forward[END_REF] and [START_REF] Fuinhas | Rentierism, energy and economic growth: The case of Algeria and Egypt (1965-2010)[END_REF]). Due to the apparent lack of literature considering the link between electricity consumption, governance and economic growth in rentier states, we intend to fill this gap by providing new evidence on whether institutions matter or not for the focal nexus, with special reference to rentier countries highly exposed to external price shocks (Algeria).

Rentierism : Algerian context

Despite the widespread use of the concept of rentierism within the literature on the energy MENA countries [START_REF] Anderson | The State in the Middle East and North Africa[END_REF], [START_REF] Talahite | La rente et l'état rentier recouvrent-ils la réalité de l'Algérie d'aujourd'hui?[END_REF], [START_REF] Jenkins | International Rentierism in the Middle East and North Africa, 1971-2008[END_REF]), rentierism stills a concept lacking an accurate definition. In general, a rentier state is a government that is able to extract significant rents from international transactions and thereby become the dominant actor in the political economy (Beblawi and Luciani, 1987). When the government has substantial income, it may reduce the tax burden and domestic expenditures. This weakens institutions 2 2 Institutions are the formal and informal constraints on political, economic and social interactions [START_REF] North | Institutions, Institutional Change, and Economic Performance[END_REF]. (Smith (2004 a), [START_REF] Herb | No Representations without Taxation? Rents, Development and Democracy[END_REF] and [START_REF] Aslaksen | Oil and Democracy: More Than a Cross-Country Correlation[END_REF]). In rentier economies, people have a little influence over political class and the state is free from the need to extract income from taxes on the domestic economy. Since resource rents highlight the need to levy taxes against the citizenry, the state is able to act independent of the will of the people [START_REF] Auty | Resource Abundance and Economic Development[END_REF][START_REF] Fearon | Primary Commodity Exports and Civil War[END_REF]), Ross (2006), [START_REF] Aslaksen | A theory of civil conflict and democracy in frontier states[END_REF], de Soysa and Neumayer (2007), de [START_REF] De Soysa | The 'Resource Curse': An Empirical Overview[END_REF] and [START_REF] Lotz | Rentierism and Repression[END_REF]). This may expose electricity sector (in particular electric projects) to strong barriers due to the ineffectiveness of institutions and to inflexible electricity market structures prevailing in rentier states [START_REF] Alvarez | Rentierism in the Algerian economy based on oil natural gaz[END_REF] and [START_REF] Fuinhas | Rentierism, energy and economic growth: The case of Algeria and Egypt (1965-2010)[END_REF]). With property rights highly disseminated through society [START_REF] Stevens | Resource curse: An analysis of causes, experiences and possible ways forward[END_REF] and with an energy market unliberalized, non-competitive and dominated by cumbersome state monopolies (Synder and Bhavanani (2005), [START_REF] Synder | Does Lootable Wealth Breed Disorder? A Political Economy of Extraction Framework[END_REF] and [START_REF] Jenkins | International Rentierism in the Middle East and North Africa, 1971-2008[END_REF], rentier state often encounter difficulties when seeking energy projects. Algeria is a typical example of rentier economy because most of the economic activity (90% of the national wealth and 96% of exports) is mainly linked to single sector, hydrocarbons. This creates several outcomes [START_REF] Alvarez | Rentierism in the Algerian economy based on oil natural gaz[END_REF]. First, the country seems highly dependent to ups and downs energy's movements, yielding to an exogenous economic development. The fluctuations of international markets generate excessive volatility. This prevents a long-run development-building strategy. Second, this great dependence and sizeable instability prevent the government and the administration to make credible forecasts of budget and economic growth in the short-and-medium terms. Finally, this dependence is harmful not only for an economy as a whole, but also at the societal perception of the values of work, efforts and self-sacrifice in order to achieve results. This may be the most disastrous consequence. It seems perverse of rentier economy. This obviously explains the wide diffusion of rentier mentality within society. Therefore, to take risk no longer offer guarantees to get rich. It is the clientelism rather than the predation that allow some close circles to get rich fastly. The reward is related to a fluke and not to a well organized production process, generating therefore a ''circulation economy'' instead of a ''production economy'' [START_REF] Chatelus | Brève histoire du pêtrole dans la peninsule Arabique[END_REF]. In good governance countries, the institutions promote the private initiatives. More precisely, entrepreneurs choose to invest in productive activities rather than rentier, nondevelopmental and non-productive resource sectors.

In Algeria, there exist several paradoxes. Residential electricity consumption represents 60% of total electricity consumption of the country. For comparison, this percentage amounts twice of that found in Europe3 . It should be noted that both wealthier and poor households pay the same price of electricity. This is also valid for other subsidized products (bread, fuel). In the same vein, industrial consumption is very low (10% against 45% in Europe). In other words, households consume more electricity than businesses. This paradox is related to generalized subsidies and non-target electricity prices. Obviously, these subsidies are very expensive and ineffective. They pushe households electricity use upwards.

It is recalled that the subsidies for energy products reached $ 10.59 billion in 2010, where electricity consumption subsidies amounted to $ 2.13 billion, while 8.46 billion dollars were directed to fuels. This represents 6.6% of the national wealth or 298 dollars per capita.

Accurately, it should be added that these rates vary between 2 Algerian dinar (DA) and 3.20 DA/ kwh depending on the level of electricty consumption, against respectively 3.45 DA and 4.94 DA / kwh in Tunisia and 5.27 DA and 6.40 DA / kwh in Morocco. Given the impossibility to remove or at least reduce the subsidies, some national reports [START_REF] Mebtoul | L'Algérie face à la concurrence et à la transition énergétique mondiale[END_REF] highlight the risk of going to 70 billion of gas cubic meters of domestic consumption on the horizon 2017-2020, surpassing the volume of exports in 2012 and making problematic the extrapolation of 85 billion gas cubic meters expected in 2014. It is true that the current context and the events that knows the MENA region (the aftermath of revolution) do not allow subsidies' limitations that may have detrimental effect on social peace. But the system slows down. Some researchers [START_REF] Mebtoul | L'Algérie face à la concurrence et à la transition énergétique mondiale[END_REF] predict the depletion of oil reserves in 2020 and conventional gas reserves in 2030, taking into account the strong domestic consumption, the cost-of-living and the increased competition facing the new world energy markets.

Methodology

Data

The study uses annual data of real GDP (Y), electricity consumption (EC), urbanization (URB) in percentage of population, foreign direct investment (FDI) and the global index of political rights as governance indicator or institutional quality's proxy(INS).

Theoretically, the poor governance has various detrimental effects on energy sector policies, particularly electricity sector. Accordingly, Smith (2004 b) argues that the electricity theft and weaker institutions are closely linked and adds that higher power fraud is intensely associated to corrupt practices within power sector organizations. Rencently, Fouinhas and Marques (2013) show that the corruption is one of the most difficult problem for electricity sector.

Nevertheless, some studies show that trade opennes reduces the detrimental effects of poor governance, suggesting therefore that countries which do not favor institutional improvements can establish a policy of open market [START_REF] Ades | Rents, Competition, and Corruption[END_REF] and [START_REF] Blake | Combating Corruption: Reexamining the Role of Democracy[END_REF]). Given this evidence, we include trade opennes (TR) in the same models to verify this evidence.

Obviously, the governance consists of the institutions by which authority in a state is exercised. This includes the capacity of the government to implement effective policies. (1)

t t t t t t INS b LFDI b LTR b LURB b LY b b LEC ζ + + + + + + = 5 4 3 2 1 0 (2)
Where ε and ζ are the error terms with normal distribution, zero mean and finite variance.

Economic growth affets electricty consumption via income and technique effects. If income effect dominates technique effect, 0 1 > a otherwise 0 1 < a . An incraese in urbanization leads industrialization, raises the demand for housing, public utilities etc which affects electricty demand (Shahbaz and Lean, 2012). We expect 0 2 > a . Trade openness affects electricty consumption via income effect, technique and composite effect (Sadorsky, 2011[START_REF] Sadorsky | Energy consumption, output and trade in South America[END_REF]. So, it is expected that 0 3 > a . Foreign direct direct investmnet stimulated eocnomic activity which impacts electricty demand positively. We expect that 0 4 > a . Similarly for equation 2, we

expect 0 1 > b (if income effect dominates technique effect), 0 2 > b , 0 3 > b , 0 4 > b .
However, the sign of b 5 seems ambiguous. More precisely, good institutions can improve electricity consumption in the sense that they allow optimal management of resources. But we cannot say at this stage that electricity should increase or decrease. This depends on the degree of development of the country in question.

The ARDL Bounds Testing Method

The ARDL bounds testing approach has been introduced by [START_REF] Pesaran | An Autoregressive Distributed Lag Modeling Approach to Cointegration Analysis[END_REF] and extended by [START_REF] Pesaran | Bounds testing approaches to the analysis of level relationships[END_REF]. It deals with single cointegration. This method allows us to see whether there is long-run relationship beteween a group of time-series, some of which may be stationary at level, while others are not. The ARDL bounds testing approach has three main advantages compared to other cointegration approaches: Firstly, the time series are assumed to be endogenous. Secondly, it obviates the need to classify the time series into I(0) or I(1) as Johansen cointegration. Thirdly, it allows us to assess simultanuously the shortrun and the long-run coefficients associated to the variables under consideration. This paper applies this method to investigate the relationship between electricity consumption, economic growth, urbanization, trade openness, foreign direct investment (with institutions versus without institutions). The ARDL representations of equations ( 1) and ( 2) or the equations of unrestricted error correction models (UECM) are formulated respectively as follows :

1 0 5 1 0 4 1 0 3 1 0 2 1 1 1 0 - = - = - = - = - = ∑ ∑ ∑ ∑ ∑ + + + + + = t v i i t h i i t l i i t m i i t n i i t DLFDI DLTR DLURB DLY DLEC DLEC α α α α α α t t t t t t LFDI LTR LURB LY LEC µ β β β β β + + + + + + - - - - - 1 5 1 4 1 3 1 2 1 1 (3) ∑ ∑ ∑ ∑ ∑ ∑ = - - = - = - = - = - = + + + + + + = q t t i t v i i t h i i t l i i t m i i t n i i t INS DLFDI DLTR DLURB DLY DLEC DLEC 0 1 6 1 0 5 1 0 4 1 0 3 1 0 2 1 1 1 0 ' ' ' ' ' ' α α α α α α α t t t t t t t v LINS LFDI LTR LURB LEC LY + + + + + + + - - - - - - 1 6 1 5 1 4 1 3 1 2 1 1 ' ' ' ' ' ' β β β β β β (4)
Where D denotes the first difference operator; µ and ν are the usual white noise residuals.

To evaluate whether there is a cointegration or not depends upon the critical bounds tabulated by Pesaran et al. (2001, p.300). There is a cointegration among variables if calculated F-statistic is more than upper critical bound. If the lower bound is superior to the computed F-statistic, we accept the null hypothesis of no cointegration. Moreover, if the F-statistic seems between lower and upper critical bounds, the cointegration is inconclusive.

The stability of ARDL approach to cointegration is assessed by carrying out various diagnostic tests and stability analyses. The diagnostic tests include the adjustment R-squared, the standard error regression, Breush-Godfrey-serial correlation and Ramsey Reset test. The stability of short-run and long-run estimates is checked by applying the cumulative sum of recursive residuals and the cumulative sum of squares of recursive residuals.

The innovative acounting approach

The previous studies on the relationship between electricity consumption and economic grwth have widely investigated whether there is a causal link between both variables. To this end, the majority of them use the standard Granger causality test augmented with a lagged error correction term. Based on [START_REF] Engle | Co-integration and error-correction: Representation, estimation and testing[END_REF]'s method, the Granger causality test through vector autoregression method may be inadequate. To overcome this gap, an inclusion of an additional variable to the vector autoregression may be effective and would allow us to detect the long-run relationship between variables under consideration.

However, the Granger causality drawbacks still. It is unable to capture the possible effects of shocks and to indicate how much extent of causality exists from one variable to other [START_REF] Farooq | Does corruption impede economic growth in Pakistan?[END_REF]). To resolve these limitations, we explore an innovative accounting approach to assess the dynamic interaction among electricity consumption, economic growth, urbanization, trade openness, foreign direct investments and institutions. This method includes forecast error variance decomposition and impulse response function. The procedure decomposes forecast error variance for each series following a one standard deviation shock to a variable, and allows us to test the strength of its impact on the series.

Results

ARDL results

To investigate if there is a significant long-run relationship that runs from electricity consumption to economic growth or vice versa, we began by evaluating the validity of estimated coefficients. We worthy notice from From the first correlations reported in Table-2, we show that there is a positive interaction between urbanization and electricity consumption, economic growth and electricity consumption, trade openness and electricity demand and foreign direct investment and electricity consumption, while the correlation between the used governance index (the global index of political rights) and Algerian electricity demand seems negative. As the lowest scores are associated to the respect of political rights including the holding of fair and free elections and the highest scores are greatly linked to the absence of political rights, the negative correlation means that the poor governance (the high scores of governance proxy between 6 and 7) is closely related to the electricity demand in Algeria. Before proceeding ARDL estimation, we determine the degree of integration of variables. To do so, we apply Dickey-Fuller (ADF) and Phillips-Perron (PP) tests. The results are reported in Table-3. We clearly show that the variables are integrated either at level or first difference (I(0) and I( 1)). Given this finding, the ARDL bounds testing approach can be employed to test the cointegration hypothesis among concerned variables. According to the ARDL bounds testing approach, lag order of the variables is important for the model specification. Hence, we determine the lag optimazation based on lag-order selection using various information criteria including Akaike criterion, Bayesian and Hannan-Quinn criteria (Table -4). It is widely pointed that AIC has superior power properties for small sample data compared to any lag length criterion. Akaike information criterion is more parcimonious than other criteria since it provides more consistent results [START_REF] Lütkepohl | Structural vector autoregressive analysis for cointegrated variables[END_REF]. We find that the optimum lag is 1 over the period of 1975-2011 either for model 1 (without institutions) or model 2 (with institutions). In addition, we depict from Table-6 that the values of our F-statistics exceed the upper bound at the 1% significance level for the model that incorporates economic growth, urbanization, trade openness and foreign direct investment (equation 1), implying that there is evidence of a long-run relationship among variables at this level of significance or greater, while the F-statistic value appears insignificant when accounting for instruments (equation 2). These results seem vulnerable because ARDL bounds test is unable to detect structural breaks stemming in the variables. It neglects possible nonlinearities in the focal relationship. Due to the apparent drawback, we carried out [START_REF] Gregory | Residual based Tests for Co-integration in Models with Regime Shifts[END_REF]'s method to investigate this link. This technique accommodates on an unknown structural break in the studied series based on Engle-Granger residual [START_REF] Farooq | Does corruption impede economic growth in Pakistan?[END_REF]. The main findings of this test put in evidence that there is cointegration when taking into account institutions (equation 2, Table-7), while there is no evidence of cointegration between variables for equation 1. In the short run, economic growth positively and significantly impacts electricity consumption at 10 percent level , while this correlation becomes insignificant when including institutions (equation 2). Urbanization increases electricity consumption at 10 percent level either with or without institutions. The effects of trade openness and foreign direct investment on electricity demand are statistically insignificant (equations 1 and 2).

Seemingly, the relationship between institutions and electricity consumption is negative and significant. The electricity demand increases because intuitions are inadequate. The price of electricity, like that of many necessity products, are fixed too low. This allows to buy lack of the social peace, highlighting then the lack of political courage. The political power seems ineffective since it is not the result of free elections and therefore can not impose prices more or less free, or at least not far from the prices of world market. This country is unable to properly administer social programs [START_REF] Talahite | La rente et l'état rentier recouvrent-ils la réalité de l'Algérie d'aujourd'hui?[END_REF]. More precisely, the inefficient subsidy policy aggravates the lack of transparency in the conduct of public policy. This leads necessarely to the inability of government to reallocate resources to benefit the broader population that may have harmful effects on energy sector and thus on the whole economy.

Furthermore, the value of ECT is negative and statistically significant at 5 percent level for the two estimated equations, which is theoretically correct. This implies that the deviations in the short-run are corrected by 29% towards the long-run equilibvrium (without institutions) and becomes less important (27%) when considering institutions. This indicates that institutions mitigate the speed of adjustment towards long-run equilibrium path in the case of Algeria. The R-adjusted value shows that the electricity consumption is 14.28% explained by economic growth, urbanization, trade openness and foreign direct investment. This value increases when adding institutions (Equation 2, Table -8

Variance decomposition results

The variance decomposition approach findings of electricity consumption are reported in Table-9. The results of Equation 1 (without institutions) show that 50.92 percent of electricity demand is explained by its own innovative shocks and 10.97 percent of electricity consumption is explained by economic growth. The contribution of urbanization in explaining electricity demand is only 6.73, while that of trade openness seems minor, i.e. 4.55%. The support of foreign direct investments amounts 26.83%. The results change substantively when considering institutions (Equation 2, Table -9). 10.49% of electricity demand is explained by institutions. We clearly observe that the contribution of economic growth, foreign direct investments in explaining electricity consumption as well as its own innovative shocks become less important, which amount respectively, 6.36%, 15.93% and 33.28%.

However, the contributions of urbanization and trade openness become more strong, (23.19% and 10.76% respectively). This confirms the evidence, providing that institutional quality plays an important role in explaining electricity consumption in the rentier states [START_REF] Jenkins | International Rentierism in the Middle East and North Africa, 1971-2008[END_REF]. Unfortunately, in MENA rentier economies in general and Algeria in particular [START_REF] Fuinhas | Rentierism, energy and economic growth: The case of Algeria and Egypt (1965-2010)[END_REF], public institutions responsible for the energy sector management are weak and ineffective. Hence, it will substantially important to strengthen the human capacity to effectively administer the electricity sector [START_REF] Jenkins | International Rentierism in the Middle East and North Africa, 1971-2008[END_REF]). It appears also necessary to improve energy governance including the development of appropriate systems of energy pricing, the implementation of effective subsidy policy that allows a gradual reduction of energy subsidies, the publication of electricity contracts and information on active shareholders and the conflicts of interest between official state and politicians who occupy responsibility positions in electricity companies in order to enhance the transparency of electricity sector.

Impulse responses results

The impulse response function is alternative to the variance decomposition method showing how long independent variable reacts to shocks stemming in the dependent variables.

By applying this technique, we can identify the magnitude of the response of electricity consumption to its own shocks, those of economic growth, urbanization, trade openness, demand is positive due to one standard deviation shock in foreign direct investment, while its response appears increasingly negative due to one standard deviation shock in instruments.

Given these observed outcomes, there is a need to improve the governance situation and the quality of institutions by strengthening civil and political liberties, government effectiveness, the political stability, by reducing burdensome regulations (the implementation of regulatory burdens program that has as main objectives to check if there are inopportune rules) and by developing various initiatives aimed at establishing the traceability systems for electricity sector in favour of technological investments.

Figure 3. Impulse Response Function

(1) Response of TR to FDI

Conclusion and some economic implications

The article attempts to assess empirically the relationship between electricity consumption and institutions in Algeria by incorporating economic growth, urbanization, trade openness and foreign direct investment over the period of 1971-2012. The main aim is to check whether institutions play an important role to explain electricity demand whithin rienterism framework. To do so, we applied the ARDL bounds testing approach to test cointegration and the innovative accounting approach to capture the responses of electricity consumption to the shocks stemming in the above variables.

Our results show that the series in model 1 (without institutions) are cointegrated, similarly for those in model 2 (with institutions) but only when accounting for structural breaks using [START_REF] Gregory | Residual based Tests for Co-integration in Models with Regime Shifts[END_REF]'s test. This means that it is crucial to consider regime shifts when investigating the linkage between electricity demand and institutions. The innovative accounting approach indicates that institutions play an important role in explaining electricity consumption. The variance decomposition results reveal that the interaction dynamics between series change intensely when considering institutions (i.e. by adding institutions (model 2), the contributions of urbanization and trade openness become stronger and those of economic growth and foreign direct investment become less important).

Intuitively, the impulse response method puts in evidence that the response of electricity consumption seems increasingly negative due to the one standard deviation shock in instituions. This may have interesting economic implications.

First, the Algerian government must take proactive measures to improve governance.

The institutional weaknesses in energy sector needs to be overcome. Such expertise will be needed for years to come in the public sector for the development and management of energy policies and regulations. Additionally, policy makers should provide accurate solutions to overcome financial and technical constraints on energy efficiency investments [START_REF] Marino | A snapshot of the European energy service market in 2010 and policy recommendations to foster a further market development[END_REF] and [START_REF] Kevin | Energy Conservation in China's Higher Education Institutions[END_REF]). Well developed institutions will support and push foreign direct investment on progress. For example, the communication and the sensitisation among policy makers, investors and consumers can play a prominent role in promoting energy conservation in different sectors.

Second, Algeria should mitigates its dependence on hydrocarbons by adopting incentive measures including appropriate systems of energy pricing and the gradual reduction of fuel subsidies. This should be granted indiscriminately to all energy consumers, to mitigate then a great rise in electricity consumption. Obviously, the over consumption may prompt power cuts especially during the high heat periods (summer). This requires courageous political decisions and transparent elections. Therefore, there is a need for legislative frameworks that would take into account the way in which authority is organized and legitimated [START_REF] Fjelde | Buying Peace? Oil Wealth, Corruption and Civil War, 1985-99[END_REF].

Thirdly, due to the significantly negative effect of institutions on the electricity demand and thus to governance drawbacks, it is crucial to implement various commitments to ensure better energy sector governance. For example, it seems important to facilitate the right of access to information from executive bodies related to power policies, to develop the rights to participate in policy-making decisions by implementing timelines for electricity system, and to enhance the access to the reports of institutions in order to strengthen the transparency of electricity sector governance.

Finally, because the economic growth and the increased cost-of-living in Algeria remain despite the abundance of natural resources, this latter may be beneficial if it is accompanied by important internal changes. These positive outcomes cannot be significant without an improvement of the management strategy. This highlights the utmost importance of human resources development including employee training, employee career development, innovative incentives and performance management. 50 years after independence, Algeria lacks human capital with creative thinking skills able to create innovative projects and establish solid institutions, prerequisite for self-sustaining and durable growth. Far from being independent, these elements are mutually reinforcing [START_REF] Beblawi | The International Bank for Reconstruction and Development/ World Bank-On behalf of the Commission on Growth and Development[END_REF]. However, the development of human resources cannot ignore the necessity of profound institutional changes, not only in terms of the different training and educational levels, but also on how the country is governed.

  period of 1971-2012. During this period, Algeria had a population explosion. To deal with this fact, Y and EC were converted into values per capita (in thousands of person). To improve the precision power of results, we carry out a log-linear specification that incorporates Y, URB, TR and FDI (Model 1). Then, we add the INS used as an indicator of governance (Model 2).

  ), it becomes 19.22%. This highlights the role of institutions to explain electricity demand in Algeria.The diagnostic tests indicate that there is no evidence of serial correlation. The Ramsey reset test statistic confirms the well construction of the short-run model. The results obtained from the CUSUM and CUSUM squares tests show that either considering institutions or not, the graphs are between the critical bounds at 5% level of significance (Figure-1), which reinforces the adequacy of the ARDL bounds testing approach, the stability and the efficience of the ARDL parameters.

  Notes : ***, ** and * imply significance at the 1%, 5% and 10% levels, respectively ; (1) : Equation of electricity consumption without taking into account the institutions ; (2) : Equation of electricity consumption considering institutions; [.] : p-values ; ARS denotes the adjustment R-squared. SER means the standard error regression ; LM means the Breush-Godfrey serial correlation. Reset denotes Ramsey Reset test; Diagnostic tests results are based on F-statistic.

Figure 1 .

 1 Figure 1. Plots of cumulative sum of recursive and of squares of recursive residuals(1)

  foreign direct investment and to see then whether the behaviours of the dynamic interactions between these variables change when including institutions. The results reported in Figure-2 indicate that the response in electricity consumption owing to forecast error stemming in economic growth is initially positive, goes downwards after 2th time horizon and becomes negative until 4th time horizon. The contribution of urbanization to electricity demand is positive over time and becomes less stable after 10th time horizon. The response of electricity consumption seems initially positive and becomes negative after 4th time horizon due to the forecast error stemming in trade openness. The response of Algeria's electricity demand due to foreacast error stemming in foreign direct investment appears negligible at the two first time horizons and becomes positive untile the 3rd time horizon (first graph, Figure-2). When considering institutions, the behaviours of the relationships under consideration change intensely (second graph, Figure-2). The electricity demand reacts to growth as it reponds positively (slightly) for the first 2 time horizons and then subsides to zero afterwards. The contribution of urbanization to electricity consumption seems negligeable until 2th time horizon and then becomes a positive contributor factor. Trade openness contributes negatively electricity consumption, especially after the firt 3 time horizons. The response of electricity

  1) : Equation of electricity consumption without taking into account the institutions ; (2) : Equation of electricity consumption considering institutions.

  To test claims about the impact og institutions on electricity demand, adequate measurements of institutional quality are needed. While some data are available, they are problematic because they are not an accurate effective governance proxy. Data come from expert assessments and surveys of government officials. The coverage of most sources of data is limited and do not

		All the data are collected from perspective Usherbrooke 4
	t LEC	=	a	+	a	t LY	+	a	t LURB	+	a	t LTR	+	a	LFDI	t	+	ε	t

share a common methodology, set of questions or measurement scale of responses. Freedom House (United States) tried to address these problems by developing aggregate governance indicators that draw from many available sources. The global index of political rights is a quantitative assessment tool that presents a comprehensive set of indicators on the possible situations in which the political rights may have a direct impact on the lives of ordinary people. This indicator combines various dimensions of political rights including fundamental rights, open government, effective regulatory enforcement, access to civil justice, among others. The lowest score (1 and 2) in the scale of political rights are awarded to countries that respect the holding of fair elections, the presence of opposition parties and the rights of minority groups. The highest scores (6 and 7) are granted to states where political rights are absent, either because of an oppressive regime or a situation of political instability.

  Table-1 a great variability of data, which highlights the need to use robust models to handle possible shocks. The coefficient of kurtosis appears inferior to 3 for all variables under consideration (except Y and TR), implying that the distribution is less flattened than the Gaussian distribution. The Skewness coefficient is negative for Y, EC and FDI, while it seems negative for URB and TR. This indicates that the symmetrical distribution is plausible for the first ones and inversely for the second ones. The Jarque-Bera test revealed low and insignificant values (except Y and INS), leading to accept the assumption of normality for all variables except Y.

	Table 1. Summary of statistics
		LEC	LY	LURB	LTR	LFDI	LINS
	Mean	6.197305 9.050105	3.974662	11.12861	18.35663	5.974359
	Median	6.309388 9.053522	3.975133	11.08701	19.04662	6.000000
	Maximum	6.943259 9.257345	4.306198	14.16968	21.83939	7.000000
	Minimum	4.945555 8.646407	3.680494	9.303406	12.72163	4.000000
	Std. Dev.	0.552327 0.122415	0.198924	1.014125	2.768434	0.584321
	Skewness	-0.741402 -0.631308	0.047553	0.580637	-0.646494 -1.603734
	Kurtosis	2.695106 4.223384	1.746310	3.677718	2.354147	8.275203
	Jarque-Bera 4.010415 5.409016	2.766373	3.163754	3.394532	61.93788
	Probability	0.134632 0.066903	0.250778	0.205589	0.183184	0.000000

Source: Usherbrooke perspectives dataset.

Table 2 . First correlations between electricity consumption and its determinants

 2

		LEC	LY	LURB	LTR	LFDI	LINS
	LEC	1
	LY	0.7406542	1
	LURB	0.9510890 0.64406628	1
	LTR	0.275828 0.27525291 0.41326495	1
	LFDI	0.3517625 0.1722970 0.5509528 0.49325713	1
	LINS	-0.0819792 -0.0906488 -0.0167425 0.04329295 0.3161668	1

Source: Usherbrooke perspectives dataset.

Table 3 . Results of ADF and PP Unit Tests

 3

	Variables	ADF test	PP test
		Level	First difference	Level	First difference
	LEC	-4.1086 (1) ***	---	-3.7297 (4) ***	---
	LY	-0.5487 (1)	-8.4468 (0) ***	-3.1257 (4) **	----------
	LURB	-0.2377 (6)	-3.0834 (0) ***	1.3492 (4)	-3.46787 (12) **
	LTR	-2.4402 (0)	-8.4485 (0) ***	-2.5021 (3)	-8.4596 (1) ***
	LFDI	-0.9446 (1)	-9.6209 (0) ***	-2.2221 (1)	-10.0241(4) ***
	LINS	-4.3724 (0)	---	-4.16637 (0)	---

Notes: ***, ** and * imply significance at the 1%, 5% and 10% levels, respectively ; The numbers within parentheses for the ADF and PP statistics represents the lag length of the dependent variable used to obtain white noise residuals ; The lag lengths for the ADF and PP tests were selected using Akaike Information Criterion (AIC).

Table 4 . Lag-order selection

 4

	Lag	LogL	LR	FPE	AIC	SC	HQ
				(1)
	0	60.12773	NA	0.002931	-3.007514	-2.603477	-2.869726
	1	67.85856	10.91411* 0.001982* -3.403445	-2.954515*	-3.250347*
	2	68.90888	1.421012	0.001989 -3.406405*	-2.912582	-3.237997
	3	69.63692	0.942176	0.002036	-3.390407	-2.851692	-3.206690
				(2)
	0	96.36237	NA*	0.000371	-5.080139	-4.631210	-4.927041
	1	98.55212	2.962601	0.000348* -5.150125* -4.656302*	-4.981717*
	2	98.71004	0.204367	0.000368	-5.100590	-4.561875	-4.916873
	3	98.75296	0.053024	0.000393	-5.044292	-4.460683	-4.845265
	Notes : * indicates lag order selected by the criterion; (1) : Equation of electricity consumption without taking into account
	the institutions ; (2) : Equation of electricity consumption considering institutions ; LR: sequential modified LR test statistic
	(each test at 5% level) ; FPE: Final prediction error ; AIC: Akaike information criterion ; SC: Schwarz information criterion ;
	HQ: Hannan-Quinn information criterion.

Next, we present our empirical results based on ARDL bounds testing (Table

-5

). We show that economic growth has an insignificant impact on electricity consumption (equations 1 and 2, Table

-5

). Urbanization contributes positively and significantly to electricity consumption when including institutions-particularly the global index of political laws-(equation 2, Table

-5

). Accurately, an increase of urbanization by 10% leads to an increase in electricity consumption by 39.3%. The trade openness has no influence on electricity demand in Algeria, while foreign direct investments and institutions affect negatively and significantly elecrticity consumption. More precisely, an increase by 10% in foreign direct investment and institutions leads to a drop in electricity demand by 0.011% and 0.14% respectively (equation 2, Table

-5

). Using different diagnostic tests such as serial correlation and Ramsey Reset tests, the adequacy of these models are checked.

Table 5 . The ARDL Bounds Testing Analysis

 5 ARS denotes the adjustment R-squared. SER means the standard error regression ; LM means the Breush-Godfrey serial correlation ; Reset denotes Ramsey Reset test; Diagnostic tests results are based on F-statistic.

	Dependent variable: ΔLEC t
	(1)	(2)

Table 6 . The ARDL Bounds Testing Analysis

 6

		Estimated model	Optimal lag length	F-statistic	Prob.
	(1)	F EC (EC/Y, URB, TR, FDI)	1, 1, 6, 0, 1	10.1657***	0.0007
	(2)	F EC (EC/Y, URB, TR, FDI, INS) 1, 1, 0, 0, 1, 2	0.0037	0.9509
	Significance level	Critical values: T=23
			Lower bounds I(0)	Upper bounds I(1)
	1%		6.84	7.84
	5%		4.94	5.73
	10%		4.04	4.78
	Notes: ***, ** and * imply significance at the 1%, 5% and 10% levels, respectively ; (1) : Equation of electricity
	consumption without taking into account the institutions ; (2) : Equation of electricity consumption considering institutions ;
	Critical values were obtained from Pesaran et al. (2001).

Table 7 . Gregory-Hansen Structural Break Cointegration Test

 7

	Estimated model	(1)	(2)
		F EC (EC/Y, URB, TR, FDI) F EC (EC/Y, URB, TR, FDI, INS)
	Structural break year	1997	2002
	ADF-test	-4.6972***	-4.2680
	Prob.values	0.0000	0.2135
	Significance level	Critical values of the ADF test
	1%	-5.71
	5%	-4.86
	10%	-4.59
	Notes: ***, ** and * imply significance at the 1%, 5% and 10% level, respectively ; (1) : Equation of electricity consumption
	without taking into account the institutions ; (2) : Equation of electricity consumption considering institutions.

Table 8 . Short-run and long-run Analysis

 8

	Dependent variable: LEC t
	(1)	(2)
	Short-run

Table 9 . Variance Decomposition of Electricity Consumption

 9

	Period	S.E.	LEC	LY	LURB	LTR	LFDI	LINS
					(1)
	1	0.037466 100.0000 0.000000 0.000000 0.000000 0.000000	---
	2	0.038269 95.85230 3.610005 0.005937 0.375789 0.155973	---
	3	0.045122 79.03017 2.816987 12.69830 0.839084 4.615465	---
	4	0.057562 70.57462 3.951738 8.714615 5.172940 11.58609	---
	5	0.061551 66.19041 6.008333 8.137104 5.056548 14.60761	---
	6	0.068542 60.65183 7.963584 7.498157 4.456970 19.42946	---
	7	0.073781 56.96610 9.341106 7.017138 4.763999 21.91166	---
	8	0.077386 54.41681 10.01879 6.902700 4.791627 23.87008	---
	9	0.080729 52.39140 10.64713 6.727147 4.656163 25.57816	---
	10	0.082891 50.92714 10.97532 6.735621 4.553169 26.80875	---
					(2)
	1	0.031842 100.0000 0.000000 0.000000 0.000000 0.000000 0.000000
	2	0.035433 81.04281 8.925533 4.213529 1.011339 3.666561 1.140225
	3	0.041108 71.03186 6.658812 10.62393 1.426997 5.615896 4.642510
	4	0.056931 61.26317 3.526467 14.11910 10.52043 4.155385 6.415443
	5	0.065231 46.85499 5.718320 18.70492 8.680000 15.11069 4.931082
	6	0.070761 44.16903 6.393693 21.16796 8.072030 15.99746 4.199824
	7	0.082930 41.16901 6.835441 18.25306 7.938125 15.88966 9.914703
	8	0.087722 38.00078 6.501868 19.13884 7.724652 17.51696 11.11690
	9	0.092172 34.42882 5.892172 23.70122 9.496603 16.40441 10.07677
	10	0.097242 33.23831 6.368909 23.19980 10.76670 15.93377 10.49250
	Notes : (1) : Equation of electricity consumption without taking into account the institutions ; (2) : Equation of
	electricity consumption considering institutions.

The comparison with Europe is given for illustrative purposes. We are well aware that Algeria and Europe are totally different at all levels.

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