Economic Growth or Electricity, what come First in Spain after 1958?

Economic growth or electricity, what came first in Spain after 1958? Jaime Jesús Sanaú Villarroya and Isabel Sanz-Villarroya Estructura e Historia Econ omica y Economía Pública, Universidad de Zaragoza Facultad de Economia y Empresa, Zaragoza, Spain, and Luis Perez y Perez Economía Agroalimentaria y de los Recursos Naturales, Agrifood Research and Technology Centre of Aragon (CITA), Zaragoza, Spain Abstract Purpose –With the opening up of the economy since the 1959 Economic Stabilization Plan, was it the production of electricity that drove the growth of gross domestic product (GDP) in Spain or, on the contrary, was it the growth of GDP that drove the production of electricity well into the 21st century? The purpose of this paper is to answer this question. Design/methodology/approach –A cointegration approach based on the studies conducted by Pesaran and Shin (1999) and Pesaran et al. (2001) is applied, as it is suitable for short data series like those used in this paper. Findings –The results of this paper allow us to conclude that electricity production boosted economic growth in Spain during the period under study, confirming the growth hypothesis. Research limitations/implications –The results of this paper should be interpreted with caution, as electricity today amounts to less than a quarter of the total amount of energy used in Spain. It was not possible to incorporate other inputs to the production function (such as other energy inputs, technological or human capital), but the methodology used avoids the problems of omitted variables and of autocorrelation. Practical implications –The results show that a small economy with limited resources, such as the Spanish one, is more vulnerable to energy shocks than other energy-sufficient economies. As Spain is a country with high energy dependence from abroad, the government must first ensure the electricity supply. Increased availability and access to different sources of electricity will improve the outlook for the Spanish economy. Conversely, a shortage in supply of electricity will constrain the regular pace of economic growth. Social implications –Spain should investigate and explore more efficient and cost-effective sources of energy, in particular the renewable energies, as traditional energy sources will be scarce before long. Originality/value –This paper differs from previous ones carried out for Spain in several aspects: it considers a broader period of time, from 1958 to 2015; the relationships between electricity production and GDP are analysed for the first time in a neo-classical production function where electricity, capital and employment are considered as separate factors; and a cointegration approach based on the studies conducted by Pesaran and Shin (1999) and Pesaran et al. (2001) is applied, as it is suitable for short data series like those used in this paper. © Jaime Jesús Sanaú Villarroya, Isabel Sanz-Villarroya and Luis Perez y Perez. Published in Applied Economic Analysis. Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode This work was supported by European Social Fund, Government of Aragon and University of Zaragoza (proyects 269190, 269224 and 269247). Economic growth or electricity Received 20 February 2020 Revised 30 May 2020 6July2020 Accepted 7 July 2020 Applied Economic Analysis Emerald Publishing Limited 2632-7627 DOI 10.1108/AEA-02-2020-0013 The current issue and full text archive of this journal is available on Emerald Insight at: https://www.emerald.com/insight/2632-7627.htm Keywords Electricity, Causality, ARDL model, Bounds test, Spanish economic growth Paper type Research paper 1. Introduction Since the beginning of the industrial revolution, changes in production and the consumption of energy have been basic elements of successive transformations in the world economy. As is well known, electricity was swiftly adopted in Western countries, and activities related to it soon became economic sectors, leading to the modernization of the production system. In Spain, this form of energy followed the same steps as in other developed countries, although with delays and peculiarities. In the early 1950s, Spain’s energy production (and energy consumption) was weak with an absolute pre-eminence of coal and a scarce external dependence. The low energy consumption was coherent with the backwardness of Spanish economy, which had a predominantly agricultural productive system and a still incipient industry. Circumstances changed during the 1950s and the electricity sector became the engine of Spanish industrial expansion. The intense industrialization process, based on heavy industry sectors that are great consumers of energy, raised the energy intensity. This increase was also a consequence of a higher standard of living. The result was that electricity production since 1958 grew at a faster rate than gross domestic product (GDP). The aim of this research is to determine whether the increase in electricity production preceded Spanish GDP growth after 1958 when the Economic Stabilization Plan was implemented and the Spanish economy entered a phase of greatest economic growth or, on the contrary, whether GDP growth boosted electricity production. For that purpose, the relationships between electricity production and GDP are researched for the first time in Spain in a neo-classical production function where electricity production, capital and employment are considered as separate factors. A longer time span than that studied by Ciarreta and Z arraga (2010),Fuinhas and Marques (2012),Pirlogea and Cicea (2012) and Sanz-Villarroya and Sanaú (2016) is analysed here. Moreover, a cointegration approach based on the studies conducted by Pesaran and Shin (1999) and Pesaran et al. (2001) is applied, as it is suitable for short data series like those used in this work. The results of an autoregressive distributed lag (ARDL) model allow us to conclude that electricity investments were called for economic growth in Spain since the late 1950s. The paper is organized as follows. Section 2 concisely describes the evolution of the electricity sector in Spain since the late 1950s. Section 3 summarizes the literature that analyses the relation between GDP growth and electricity consumption or production. Section 4 gives an account of the methodology used and provides the data and empirical evidence for the Spanish case. The paper ends with a report of the main findings obtained. 2. Evolution of the Spanish electricity sector since 1958 Since 1958, two important stages can be distinguished in the evolution of growth of Spanish GDP and electricity sector. The first lasts until the mid-seventies and reflects the period of expansion and modernization of the electricity sector as well as the take-off of the Spanish economy. This marks the beginning of the second stage in which two subperiods can be differentiated: 1975–1984 and 1985–2015. Figure 1 summarizes the trajectory of GDP and electricity production between 1958 and 2015. Note that the evolution of electricity production coincides with the evolution of GDP. However, it cannot be concluded from the figure whether the growth of electrical production AEA preceded GDP growth or, conversely, whether it was GDP growth that boosted electricity production. Between 1958 and 1974, there was a strong GDP growth (at an annual average rate of 6.7% cumulative) and a higher expansion of electricity production (10.5% cumulative annual average) (Appendix 1). In these years, the capacity of power generation and oil refining rose very quickly and the energy sector managed to meet the energy demands by relying on imported oil and natural gas (since the late 1960s). During this first stage, many power plants were projected and partially financed, through public funds, under the Spanish National Electricity Plan (NEP) 1971–1981. This favoured a large expansion of hydroelectric power and, above all, of conventional thermoelectric power, both of which exhibited a very similar installed capacity in 1974. In these years, the transmission and distribution network was tripled and completed, achieving a full interconnection between the various electricity production enterprises. The second stage begins around 1975, when the effects of the economic crisis (originated by the sudden, sharp increase in oil prices and raw materials in 1973) begin to affect the Spanish economy. The economic crisis was a turning point in the Spanish evolution given that, from then until 2015, the last year with available data, the average annual GDP growth rate declined to 2.7% and the average annual growth rate of electricity production fell to 2.6%. The early years of this second stage were very hard because the lower GDP growth was accompanied by a sharp rise in unemployment and inflation. Energy policy aimed to satisfy demand, at minimum cost and with maximum safety, and energy planning was initiated Figure 1. Real gross domestic product and electricity production in Spain (1958–2015). Evolution in logarithms 9.60 9.80 10.00 10.20 10.40 10.60 10.80 11.00 11.20 6.50 7.00 7.50 8.00 8.50 9.00 Electricity production Real GDP Sources: SEE (several years); UNESA (2016); Prados de la Escosura (2003); National Statistics Institute (several years) Economic growth or electricity through the Spanish NEP. After 1979, these plans also pursued diversification and energy saving. Until 1984, the increase in electric power was led by nuclear power plants (whose power increased at an annual rate cumulative average of 17.8% between 1975 and 1984) and, to a much lesser extent, by conventional thermal power plants (5.4%). The growth of hydroelectric power was lower, 1.9% (annual cumulative average). The extension of the installed power capacity enabled electricity production to advance between 1975 and 1984 at an annual cumulative average rate of 4.8% (less than half of that achieved in the first phase). After 1985, the Spanish economy experienced a new growth period, slower in some years (early 1990s) and abruptly stopped in 2008. The growth of the installed capacity is explained by the increase of renewable energy (at a cumulative rate of 4.2% per year between 1985 and 2015) and conventional thermoelectric power (2.9%), rather than by nuclear power (1.0%). 3. Economic growth and electricity Energy, besides allowing for the satisfaction of the consumers’needs, is a necessary input to transform materials into products and transport them, that is, to carry out any productive activity. Traditionally, the economic growth theory has hardly paid attention to the role of energy. The most renown models do not include resources or energy as relevant factors. By contrast, economic historians [(such as Allen (2009) or Carreras and Tafunell (2010)] believe that energy has played a crucial role in economic growth as well as in industrialization processes. Stern (2010) states that when energy is scarce, it imposes a strong constraint on economic growth; however, when energy is abundant, its impact on the growth of the economy is reduced. In other words, energy can be more important for economic growth in developing countries than in developed countries. Stern and Kander (2012) add energy as an input to Solow’s growth model that has low substitutability with capital and employment, allowing the elasticity of substitution between capital and employment to remain one. Their model considers innovations that directly increase the productivity of energy and those that increase the productivity of employment (labour-augmenting technological change). As all economic processes require energy and there are limits to the substitution of other production factors for energy, the latter is an essential production input (Stern, 1997). Consequently, the relationship between energy and the aggregate output can be affected by substitution between energy and the other inputs, by total factor productivity and even by shifts in the composition of the energy input and in the composition output (Stern, 2010). Empirical evidence suggests that energy intensity has declined during the past decades in developed countries. A part of the reduction in energy intensity can be explained by the development of electricity because electricity allows a more efficient use of the energy. As Burke et al. (2018) argue, electricity has offered advantages over other energy sources, enabling far more efficient technologies (like the information and communications technologies), a more productive organization of manufacturing and a more efficient lighting and providing productivity gains. To make the best of these advantages, a reliable supply of electricity and an adequate electricity network that answers to the volatile demand of electricity will be necessary. For all these reasons, the relationship between electricity and economic growth is an important issue to research, and the empirical evidence is inconclusive. Camarero et al. (2015) classify the research approaches into groups based on different estimations. The paper written by Kraft and Kraft (1978) initiated the debate on the direction of causality between energy and GDP. Some of these analyses, included in the so-called growth AEA hypothesis,find a unidirectional causality that runs from electricity consumption or production to economic growth. This means that in countries that follow this pattern, a reduction in electricity consumption or production could lead to lower economic growth. This hypothesis is found to be prevalent in the developed world, as suggested by Chontanawat et al. (2008) and Narayan and Prasad (2008). However, Morimoto and Hope (2004) highlight that the increase in electricity supply played an important role in explaining economic growth in Sri Lanka. Altinay and Karagol (2005) provided evidence for unidirectional causality running from the electricity consumption to the real GDP in Turkey during the period 1950–2000. Tang and Shahbaz (2013) concluded that electricity consumption Granger-caused output for economy as a whole and also for the manufacturing and services sectors in Pakistan from 1972 to 2010 (not for the agricultural sector). More recently, Wolde-Rufael (2014) confirmed the growth hypothesis in Belarus and Bulgaria during the period 1975–2010 and Ali et al. (2020) in Pakistan from 1961 to 2015 (Table 1). Other studies, on the contrary, reveal the opposite relationship. That is, a higher rate of growth leads to a higher electricity consumption (or electricity generation), a result that fits into the conservation hypothesis. If this were the case, then policies implemented to stimulate or to reduce electricity consumption would not have any effects in terms of economic growth. This happens, for example, in countries such as Indonesia and Mexico or in Australia, a fact reflected in the analysis of Murry and Nan (1996) and Narayan and Smyth (2005), respectively. Yoo and Kim (2006) found a unidirectional causality that runs from economic growth to electricity generation in Indonesia. Squalli (2007) presented empirical evidence indicating that policies for energy conservation can have little to no impact on economic growth in Argelia from 1980 to 2002. Ang (2008) found a strong support for causality running from economic growth to energy consumption growth in Malaysia. Finally, Wolde-Rufael (2014) proved the conservation hypothesis in the Czech Republic, Latvia, Lithuania and the Russian Federation for the period 1975–2010. In other papers, there are some evidences of the feedback hypothesis, that is, of a bidirectional causality between electricity consumption and economic growth, with the consequent beneficial effects. Tang (2008), with quarterly data from 1972 to 2003, suggested that electricity consumption and economic growth in Malaysia Granger-causes each other. Yoo and Lee (2010) found this relationship in their sample of a large set of economies that included the OECD countries and other developing countries. Their results showed a statistically significant inverted-U-shaped relationship between per-capita income and electricity consumption. Bayar and Özel (2014) found that electricity consumption had a positive impact on the economic growth in emerging economies and that there was bidirectional causality between economic growth and electricity consumption (during the period 1970–2011). Wolde-Rufael (2014) found bidirectional causality in Ukraine during the period 1975–2010 and Lu (2017) found it in Taiwan. Some of the economies analysed point to the absence of a causal relationship between these variables, supporting the neutral hypothesis, as in the case of France, Germany, Portugal, India, Norway, the UK and the USA (Murry and Nan, 1996); in 11 Middle East and North Africa countries (Ozturk and Acaravci, 2011); or in transition economies (WoldeRufael, 2014). Finally, some studies have found seemingly contradictory empirical evidence. Abbas and Choudhury (2013), for instance, examined the causality between electricity consumption and economic growth in India and Pakistan at aggregated and disaggregated level. At the aggregated level, India confirmed the conservation hypothesis, while Pakistan confirmed the feedback hypothesis. Economic growth or electricity Authors Methodology Growth hypothesis Conservation hypothesis Feedback hypothesis Neutral hypothesis Bivariate models Morimoto and Hope (2004) Altinay and Karagol (2005) Tang and Shahbaz (2013) Wolde-Rufael (2014) Ali et al. (2020) Murry and Nan (1996) Narayan and Smyth (2005) Yoo and Kim (2006) Squalli (2007) Ang (2008) Abbas and Choudhury (2013) Tang (2008) Yoo and Lee (2010) Bayar and Özel (2014) Lu (2017) Ozturk and Acaravci (2011) Cointegration Engle Granger The Dolado–Lütkepohl and the Granger causality tests The Granger causality test A bootstrap panel causality approach Vector error-correction model (VECM) The Granger causality test ARDL Bounds test Cointegration Engle Granger ARDL model and Toda– Yamamoto Granger causality test Causality tests Causality tests ARDL model and Granger causality Model estimated The Granger causality tests The Granger causality test Pedroni panel cointegration and VECM Granger causality Sri Lanka (1960–1998) Turkey (1950–2000) Pakistan (1972–2010) Belarus and Bulgaria (1975–2010) Pakistan (1961–2015) Czech Republic, Latvia, Lithuania and the Russian Federation (1975–2010) Indonesia (1970–1990) Australia (1966–1999) Indonesia (1971–2002) Argelia (1980–2002) Malaysia (1971–1999) India (1972–2008) Ukraine (1975–2010) Pakistan (1972–2008) Malaysia (1972–2003) 88 countries (1975–2004) Emerging economies (1970–2011) Taiwan (1975–2010) Transition economies (1975–2010) France, Germany, Portugal, India, Norway, the UK and the USA (1970–1990) 11 MENA countries (1971–2006) (continued) Table 1. Selection of papers analysing the relationship between economic growth and electricity consumption/ production AEA Authors Methodology Growth hypothesis Conservation hypothesis Feedback hypothesis Neutral hypothesis Multivariate models Iyke (2015) Sun and Anwar (2015) Ikegami and Wang (2016) Tang and Tan (2013) Tang et al. (2013) Polemis and Dagoumas (2013) Mohammadi and Parvaresh (2014) Ohler and Fetters (2014) Karanfil and Li (2015) Shahbaz et al. (2017) Trivariate VECM Trivariate vector autoregressive framework ARDL and Granger causality test Granger causality test Granger causality test within VECM VECM and Granger causality test Panel estimations techniques Panel error correction model Panel data techniques Estimation of panel regressions Nigeria (1971– 2011) Singapore (1983–2014) North America (1960–2014) Germany (1983–2014) Lower-middle-income, Middle East and North Africa and South Asia countries (1960–2014) Malaysia (1970–2009) Portugal (1974–2009) Greece (1970–2011) 14 oil-exporting countries (1980–2007) 20 OECD countries (1990–2008) 160 countries Upper-middle income, high income, OECD, East Asia & Pacific and Europe and Central Asia categories (1960–2014) Low-middle-income, the nonOECD, Latin America and Caribbean and Sub-Saharan Africa countries (1960–2014) Bivariate models for Spain Ciarreta and Z arraga (2010) SanzVillarroya and Sanaú (2016) Standard and non-linear Granger causality Cointegration model for short time series Renewable sources and nuclear power (1958–2011) 1973–2008 Conventional power plants (1958–2011) Table 1. Economic growth or electricity Apart from total electricity consumption, attention has also been paid to the role of the different types of electricity (Payne, 2010;Dogan, 2015a, 2015b; Cerdeira Bento and Moutinho, 2016;Cardoso Marques et al.,2016or Sanz-Villarroya and Sanaú, 2016). A common criticism is that many studies concentrate on the bivariate relationship of energy consumption and economic growth. In these cases, there may be an omittedvariable bias problem (when one or more relevant explanatory variables are ignored in the estimated model) and results may be biased and inconsistent. Many authors try to mitigate this criticism using control variables, that is, considering other potential variables such as electricity prices, export and import, capital, employment, inflation, entrepreneurship [...] that affect energy consumption and economic growth (multivariate models). Although this approach has limitations deriving from the selection process of the control variables, it highlights the importance of a disaggregate analysis of economic activity. The papers that incorporate new variables on examining the electricity–GDP growth relationship have limitations deriving from the selection process of the control variables and also provide mixed results, the direction of causality between these variables being controversial. Iyke (2015) and Sun and Anwar (2015) conclude that there is a positive causality running from electricity consumption to real GDP that supports the growth hypothesis in Nigeria and Singapore, respectively. Conversely, Ikegami and Wang (2016) find evidence that there is a unidirectional and positive causality running from real GDP to combustible fuels electricity supplied in Germany, supporting the conservation hypothesis. The evidence in favour of the feedback hypothesis is very common. Tang and Tan (2013) show that electricity consumption and economic growth Granger-cause each other in the short and long term. Tang et al. (2013) confirm the same results in Portugal and Polemis and Dagoumas (2013) in Greece in a multivariate framework. Mohammadi and Parvaresh (2014), examining the nexus between energy consumption and output in 14 oil-exporting countries over 1980–2007, support bidirectional causality in both long and short run and the robustness of the results to the inclusion of additional variables in the models. Ohler and Fetters (2014) examine the causal relationship between economic growth and electricity generation from renewable sources across 20 OECD countries. Among their results, it is worth highlighting that there is a bidirectional relationship between aggregate renewable generation and real GDP and that the energy conservation policies positively impact GDP, if biomass or waste energy decrease and hydroelectricity and wind energy increase. Karanfil and Li (2015) find a long-run cointegration relationship between electricity consumption and economic growth, implying a feedback hypothesis in 160 countries for the period 1980–2010. Shahbaz et al. (2017) analyse the relationship between economic growth, electricity consumption, oil prices, capital and labour in 157 countries. They find countries where the growth hypothesis is confirmed, others that do not depend on electricity for economic growth (conservation hypothesis), others supporting the feedback hypothesis and countries in which the neutrality hypothesis is proved. In sum, there are a lot of works that deal with this matter, but the results obtained from them are mixed. Although there are studies covering a wide range of countries, the particular case of Spain has hardly been investigated, despite the importance of the electricity sector in explaining the process of industrialization that began in the late fifties. Ciarreta and Z arraga (2010), focusing on the 1973–2008 period, find a unique relationship that runs from economic growth to electricity consumption, supporting the conservation hypothesis. On the contrary, Sanz-Villarroya and Sanaú (2016) conclude that renewable sources and nuclear power stimulated GDP growth between 1958 and 2011, but the AEA economic growth led to the production of electricity in conventional power plants. Two other studies, considering energy consumption, obtain support for the feedback hypothesis (Fuinhas and Marques, 2012) and the growth hypothesis (Pirlogea and Cicea, 2012). In other words, the results are not conclusive for Spain either. 4. Methodology, data and empirical results Several authors [(such as Dogan (2015b),Narayan et al. (2008) or Apergis and Payne (2010)] considered energy as an additional factor in the production function. Following this literature, the shortand long-run relationships and the direction of causality between electricity production and GDP are investigated, in a neo-classical production function: GDP ¼f CAP;EMP;EP ðÞ (1) where CAP is the capital stock, EMP is the employment and EP is electricity production. Including CAP and EMP in the model changes the direction of causality and the magnitude of estimates in the short and long run as compared to the bivariate models. Annual data for the period 1958–2000 for real GDP and employment are from Prados de la Escosura (2003) and from the National Statistics Institute (2020) since 2000. Annual data for the net capital stock are from Fundaci on BBVA e Ivie (Instituto Valenciano de Investigaciones Econ omicas) (2015,2019). The necessary information about electricity production (in megawatts hour) for the same time span has been collected from the Secretaría de Estado de Energía (SEE) (2020) and UNESA (2016). The methodology used in this paper is a vector error-correction model (VECM). The VECM for equation (1) is based on that proposed by Pesaran and Shin (1999) and Pesaran et al. (2001). They developed a new cointegration approach, the ARDL bounds testing approach, that has many advantages over the traditional one proposed by Engle and Granger (1987) and Johansen and Juselius (1990). The first and the most important advantage is that the order of integration of the series does not matter, so non-stationary and stationary variables can both be taken into account. The second advantage is that this new methodology produces robust results even in small sample sizes. The third advantage is that this methodology leads us to estimate the shortand long-run equilibrium relationship at the same time, avoiding the problems of omitted variables and of autocorrelation. Moreover, the bounds test permits us to obtain the causal relationship between the variables and distinguish between the dependent and the explanatory variables. The application of the ARDL model has become very popular in some areas of economics and especially in energy market analysis, a field in which the temporal dimension of the data available is usually short (Narayan and Smyth, 2005;Narayan et al., 2008;Ghosh, 2009). For all the reasons mentioned above, it seems that this approach is appropriate for studying the case of Spain: we have a relatively small sample (58 observations); we want to Table 2. 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(2010), “Electricity consumption and economic growth: a cross-country analysis”, Energy Policy, Vol. 38 No. 1, pp. 622-625, available at: https://doi.org/10.1016/j.enpol.2009.05.076 Corresponding author Jaime Jesús Sanaú Villarroya can be contacted at: [email protected] Economic growth or electricity Appendix Electricity production (in megawatts hour) Electric power installed at December 31 (in megawatts) Hydroelectric power Conventional thermal Nuclear power Total 1958 16,350 4,195 1,878 0 6,073 1959 17,353 4,436 1,948 0 6,384 1960 18,614 4,600 1,967 0 6,567 1961 20,879 4,768 2,242 0 7,010 1962 22,905 5,190 2,298 0 7,488 1963 25,897 5,895 2,492 0 8,387 1964 29,526 7,020 2,706 0 9,726 1965 31,723 7,193 2,980 0 10,173 1966 37,699 7,680 3,457 0 11,137 1967 40,637 8,227 4,671 0 12,898 1968 45,851 8,543 5,292 153 13,988 1969 52,124 9,335 6,165 153 15,653 1970 56,490 10,883 6,888 153 17,924 1971 62,516 11,057 7,403 613 19,073 1972 68,904 11,136 9,615 1,120 21,871 1973 76,272 11,470 10,617 1,120 23,207 1974 80,857 11,841 11,376 1,120 24,337 1975 82,515 11,954 12,393 1,120 25,467 1976 90,822 12,497 12,974 1,120 26,591 1977 93,804 13,096 13,334 1,120 27,550 1978 99,534 13,530 13,628 1,120 28,278 1979 105,779 13,515 15,267 1,120 29,902 1980 110,483 13,577 16,447 1,120 31,144 1981 111,232 13,579 17,158 2,051 32,788 1982 114,569 13,821 17,637 2,051 33,509 1983 117,196 14,087 17,614 3,911 35,612 1984 120,042 14,119 19,898 4,885 38,902 1985 127,363 14,661 20,991 5,815 41,467 1986 129,149 15,201 20,987 5,815 42,003 1987 133,390 15,269 21,087 5,815 42,171 1988 139,571 15,673 21,119 7,854 44,646 1989 147,842 16,545 21,227 7,854 45,626 1990 151,741 16,924 21,370 7,364 45,658 1991 159,392 17,026 21,855 7,367 46,248 1992 161,105 17,282 21,922 7,400 46,604 1993 160,890 17,294 21,989 7,400 46,683 1994 164,942 17,906 22,346 7,400 47,652 1995 169,094 18,037 22,849 7,417 48,303 1996 176,510 18,279 23,960 7,498 49,737 1997 189,381 18,538 25,339 7,580 51,457 1998 196,792 19,139 26,228 7,638 53,005 1999 209,885 20,201 26,847 7,749 54,797 2000 225,105 20,855 28,180 7,798 56,833 2001 237,684 22,162 28,980 7,816 58,958 2002 246,789 23,758 31,683 7,871 63,312 2003 265,071 25,337 33,818 7,896 67,051 2004 282,209 27,663 37,905 7,878 73,446 2005 294,422 29,355 42,593 7,878 79,826 (continued) Table A1. Electricity production and electric power installed on December 31 st , Spain AEA For instructions on how to order reprints of this article, please visit our website: www.emeraldgrouppublishing.com/licensing/reprints.htm Or contact us for further details: [email protected] Electricity production (in megawatts hour) Electric power installed at December 31 (in megawatts) Hydroelectric power Conventional thermal Nuclear power Total 2006 303,450 31,437 45,790 7,728 84,955 2007 312,972 34,638 49,209 7,728 91,575 2008 318,238 39,316 49,681 7,728 96,725 2009 291,374 42,022 50,097 7,728 99,847 2010 304,618 43,358 51,117 7,795 102,270 2011 293,805 46,036 52,319 7,849 106,204 2012 298,174 48,725 50,425 7,867 107,017 2013 287,162 49,827 50,921 7,866 108,613 2014 280,101 49,867 50,400 7,866 107,615 2015 280,289 50,771 49,203 7,867 107,841 Source: UNESA (2016) Table A1. Economic growth or electricity