Analysis of energy and electricity intensity trends in the frame of development basis

Since ancient times people use primary energy supplies, oil, coal, natural gas etc, for their needs. In the next period, after urban life and technology are improved, environment and pollution begins to get more important. Depending on these two basic reasons, secondary energy supplies are started to be used in the market. Secondary energy supplies consist of using primary energy supplies. An example of secondary energy supplies is electricity, which is easy use and clean sort of energy. It is used largely depending on its superior specifications although cannot be stored effectively except small quantities. It can also be transmitted easily from manufacturing places to regions to be used and it can be easily controlled when it is needed. Electricity consumption per capita is a very good development indicator due to connection of environment and technology. In these days, because of some reasons such as industrialization and fast population increase, energy demand is getting much more than usual. While demand is increasing, to meet this demand is getting more difficult due to limited reserves in time. Depending on such conditions, it is needed and obligation that energy must be used effectively and efficiently. Energy efficiency means to decrease supply to be used to a minimum level and get maximum output. So, by using the same supply, it may be got more output than before. One of important indicator for energy efficiency is energy intensity concept. Energy intensity can be identified as energy use per gross domestic product (GDP) and represented by TPES/GDP ratio. TPES is given by total primary energy supply. Energy Intensity is an important indicator that represents using energy whether efficiently or not. It is said that if energy intensity of a country is lower, then this country has a developed economy. Also, it is a very important and useful subject for politics makers to forecast how energy consumption increases before facing significant changes in economy management system and economic structure. Since 1973, industrialized countries focus and take into account of energy efficiency. These countries, due to oil crises in 70's, get improve their energy efficiency politics and enforce them in all sectors. Because of energy politics contribution, energy intensity decreases last year's in these developed countries. There are a lot of studies whether unbalanced levels in gross domestic product per capita to be solved and balanced or not until recent days. As a result, convergence hypothesis appears regarding this issue. Convergence hypothesis states that poor countries or regions' level are going to reach rich countries or regions' level of development in time and they converge each other according to their GDP per capita. The basic of this hypothesis consists of an expectation due to a capital transition from developed countries or regions to developing countries or regions. After convergence hypothesis is used in economic growth literature, it is also used in energy matters and some studies are realized in energy sector. Energy and electricity intensity may be submitted as an example. Depending on these studies, some concepts such as beta convergence, sigma convergence and gamma convergence by borrowing from economic growth literature are used for energy intensity and electricity intensity of countries to examine whether any convergence or not in between them. In my study, convergence concept is examined and given some information regarding its improving in history in time. Beta, sigma and gamma convergence are explained and submitted information about their applications in energy and electricity intensity. Then, I separate countries according to their developing of developed position and examine OECD, Non-OECD, world total countries nad Turkey's values. After that, total primary supply (TPES), total electricity consumption (EC), gross domestic product according to purchasing power parity (GDP-PPP), population (POP), energy intensity and electricity intensity and their values depending on per capita according to data set are examined. Their graphs are created according to years and both real and normalized values are used. In addition, OECD, Non-OECD, world total and Turkey's energy intensity and electricity intensity are examined. It is found that while avregae of world total's energy intensity is getting better, developed countries' values converge lower energy inetensity values of average of world total and developing countries converge higher energy intensity values of average. While calculating energy and electricity convergence, histograms belongs to sigma convergence are applied. The purpose is to examine energy and electricity improvements depending on development frame and Turkey to compare obtained values according to terms given by data set 1971 and 2010. The first measuring that is used for energy intensity and electricity intensity is beta convergence. It tests catch up process whether it comes true or not for examining a country or a region. Some factors in a country, for example energy intensity can exhibit a fast moving. It is said that beta convergence can test such a value or decline of average growth rate at beginning of process. A negative and statistical significant value is specified for an indicator for beta convergence. Other convergence measure applied to calculations is called sigma convergence. It focuses the change of dispersion of the distribution concept. It is said that beta convergence is necessary, but not efficient for sigma convergence. Sigma convergence is important because it makes dispersion of the distribution be extended as soon as possible to be passed through the powerful countries by the old poor countires. In addition, sigma convergence measure catch up process that collects countries how effective is. It is put forward that sigma convergence has two measures to measure convergence in energy intensity and electricity intensity. One measure of sigma convergence is coefficient of variation (cv) that implies change between times (for example to normalize a value according to initial value). CV is achieved by standard deviation by dividing mean in energy or electricity intensity distribution for a country. If this measure declines in time, it means that convergence occurs. The other sigma convergence measure is Kernel density which depends on histograms that achieve if the distribution is changing in time. In the second measure of sigma convergence, the shape of the distribution is significant. The shape can be single mode, bimodal or multimodal. Multimodal and bimodal distribution is called as convergence clubs in convergence literature. In this study, sigma convergence's histogram measure is applied both energy intensity and electricity intensity of countries. When density of dispersion of distribution is measured, each countries' intensity is divided by current countries' group average for current year. Thus, it is achieved relative energy and electricity intensity. Then, each country is divided seven categories according to average: (<0,50) less than half of average, (0,50-0,75) between half of average and three quarter of average, (0,75-1,00) between three quarter of average and average, (1,00-1,25) between average and one and one quarter of average, (1,25-1,50) between one and one quarter of average and one and one half of average, (1,50-2,00) between one and one half of average and twice of average. It is done a scale by using these values on the graph and achieved histograms. Seven categories are defined on the histogram by putting years used in analyzed 1971-1980-1990-2000-2010 that covers fourty years. The vertical axis shows country numbers and horizontal axis shows the seven categories. Then, narrowing and compress areas on the histogram is observed. Dispersion gives information in the stated intervals. The intervals gives information how many country in the which section. According to this, by using excel program, the numbers of countries in the categories are defined. As a result, it informs numbers of converged countries and convergence concept of that period. In the next step, sigma convergence's histogram measure is applied for the same group of countries, which are OECD, Non-OECD and world total. Depending on average some distribution are calculated for both energy and electricity intensity. As a result, sigma convergence for these group of countries are detected. In OECD member countries including Turkey and world total, electricity convergence trend is stronger than energy intensity convergence. In Non-OECD countries, convergence level of energy and electricity intensity are similar convergence level. Detected convergence implies that numbers of countries that have high and low energy and electricity intensity in 1971 are more than present day. It also implies that some transitions occur in time among these countries. Generally, member of OECD countries give single mode (bell shaped) distribution for energy intensity. Non-OECD countries give bimodal or multi modal distribution for energy intensity. Bell shaped (single mode) distribution means that there is a trend toward average among countries. Bimodal or Multi modal distribution means convergence clubs among countries. While developing countries converge to higher energy intensity values, developed countries converge lower energy intensity values. Convergence in developed and developing countries are not similar levels for all countries. Targets for energy and environment are very important both developed and developing countries. Some international agreements are needed to identify energy future and prevent global warming by covering all countries. Fossil fuel consumption quantity is still very high both developed and developing countries. In order to prevent fossil fuel consumption, encourage countries to use less harmful fuel for environment and support them to make policies that is more sensitive sustainable environment. Steps for increasing energy efficiency should cover all countries in the world and force them to obey these steps like European Union sample by compulsory international agreements. In this context, investment cost for research and development regarding energy efficiency must be increased.