Modeling and forecasting electricity demand in Azerbaijan using cointegration techniques

Policymakers in developing and transitional economies require sound models to: (i) understand the drivers of rapidly growing energy consumption and (ii) produce forecasts of future energy demand. This paper attempts to model electricity demand in Azerbaijan and provide future forecast scenarios—as far as we are aware this is the first such attempt for Azerbaijan using a comprehensive modelling framework. Electricity consumption increased and decreased considerably in Azerbaijan from 1995 to 2013 (the period used for the empirical analysis)—it increased on average by about 4% per annum from 1995 to 2006 but decreased by about 4½% per annum from 2006 to 2010 and increased thereafter. It is therefore vital that Azerbaijani planners and policymakers understand what drives electricity demand and be able to forecast how it will grow in order to plan for future power production. However, modeling electricity demand for such a country has many challenges. Azerbaijan is rich in energy resources, consequently GDP is heavily influenced by oil prices; hence, real non-oil GDP is employed as the activity driver in this research (unlike almost all previous aggregate energy demand studies). Moreover, electricity prices are administered rather than market driven. Therefore, different cointegration and error correction techniques are employed to estimate a number of per capita electricity demand models for Azerbaijan, which are used to produce forecast scenarios for up to 2025. The resulting estimated models (in terms of coefficients, etc.) and forecasts of electricity demand for Azerbaijan in 2025 prove to be very similar; with the Business as Usual forecast ranging from about of 19½ to 21 TWh

A Macroeconometric Model for Saudi Arabia

This Open Access Brief presents the KAPSARC Global Energy Macroeconometric Model (KGEMM). KGEMM is a policy analysis tool for examining the impacts of domestic policy measures and global economic and energy shocks on the Kingdom of Saudi Arabia. The model has eight blocks (real sector, fiscal, monetary, external sector, price, labor and wages, energy, population, and age cohorts) that interact with each other to represent the Kingdom’s macroeconomy and energy linkages. It captures New Keynesian demand-side features anchored to medium-run equilibrium and long-run aggregate supply. It applies a cointegration and equilibrium correction modeling (ECM) methodology to time series data to estimate the model’s behavioral equations in the framework of Autometrics, a general-to-specific econometric modeling strategy. Hence, the model combines ‘theory-driven’ approach with ‘data-driven’ approach. The Brief begins with an introduction to the theoretical framework of the model and the KGEMM methodology and then walks the reader through the structure of the model and its behavioral equations. The book closes with simulations showing the application of the model. Providing a detailed introduction to a cutting-edge, robust predictive model, this Brief will be of great use to researchers and policymakers interested in macroeconomics, energy economics, econometrics, and more specifically, the economy of Saudi Arabia

how total factor productivity drives long run energy consumption in saudi arabia

In this study, we investigate how total factor productivity (TFP), alongside income, price, and population, shapes energy consumption in the long-run in Saudi Arabia, the world's number one oil exporter. To do so, we first estimate a production function and construct the associated TFP series, and then assess TFP's impact on energy consumption. To take into consideration the stochastic properties of the variables, we employ unit root and cointegration methods. We also correct estimations and test results for potential small sample bias. Our main finding is that TFP has a statistically significant impact on energy consumption in the long-run. The main contribution of our research is that to the best of our knowledge this is the first study that estimates energy consumption effects of TFP for Saudi Arabia. We believe that our research would be useful for Saudi Arabian policymakers in understanding how TFP, a representation of technological progress, institutional development, innovations, openness, and R&D development, influences energy consumption over time. Saudi Vision 2030, the strategic road map of Saudi Arabian development, implies rational behavior and lowering the pace of energy consumption in the country. Thus, TFP improvement is a sustainable way to attain these goals

Bank-Specific and Macroeconomic Determinants of Bank Profitability: Evidence from an Oil-Dependent Economy

This study investigated bank-specific and macroeconomic determinants of bank profitability in Azerbaijan, an oil-dependent economy in transition. A huge drop in oil prices, a significant devaluation of the national currency, and the financial distress were the main motivations of the study. We applied Panel Generalized Method of Moments to the data in the framework of dynamic model of the bank profitability. It was found that bank size, capital, and loans, as well as economic cycle, inflation expectation, and oil prices were positively related to the profitability, whereas deposits, liquidity risk, and exchange rate devaluation were negatively associated with it. We further found that the bank profitability demonstrated moderate persistence and ignoring the country-specific features could lead to bias and poor performance in estimations. The conclusions of this research would aid in setting banking policies towards increasing profitability. This may be supplemented by ensuring strong research departments within the banks tasked with analyzing and forecasting the main macroeconomic indicators. The novel features of the study include utilizing recent economic trends, accounting for country-specific features, and for the first time, examining the effects of the economic cycle on the bank profitability in Azerbaijan. In addition, the study featured proper addressing time series properties of the panel data, and performances of robustness checks for consistency of results

Revisiting Energy Demand Relationship: Theory and Empirical Application

In this paper, we revisit the theoretical framework for energy demand. We then use this theoretical framework to empirically model the Saudi Arabian industrial electricity demand. We show, in the case of Saudi Arabian data, that imposing parsimonious energy demand specification on data without testing relevant assumptions can lead to biased estimations and noticeably poor approximations, while imposing general energy demand specification without accounting for the data properties can lead to redundant estimations and lower approximation than what could be obtained otherwise. Combining the theory with the data can provide unbiased and irredundant estimations with high levels of approximations. Hence, this paper recommends, based on the empirical findings, that a better strategy would be the combination of theoretical coherence with data coherence in the General to Specific Modeling (GtSM) framework for the empirical analyses of energy demand

Bank-Specific and Macroeconomic Determinants of Bank Profitability: Evidence from an Oil-Dependent Economy

This study investigated bank-specific and macroeconomic determinants of bank profitability in Azerbaijan, an oil-dependent economy in transition. A huge drop in oil prices, a significant devaluation of the national currency, and the financial distress were the main motivations of the study. We applied Panel Generalized Method of Moments to the data in the framework of dynamic model of the bank profitability. It was found that bank size, capital, and loans, as well as economic cycle, inflation expectation, and oil prices were positively related to the profitability, whereas deposits, liquidity risk, and exchange rate devaluation were negatively associated with it. We further found that the bank profitability demonstrated moderate persistence and ignoring the country-specific features could lead to bias and poor performance in estimations. The conclusions of this research would aid in setting banking policies towards increasing profitability. This may be supplemented by ensuring strong research departments within the banks tasked with analyzing and forecasting the main macroeconomic indicators. The novel features of the study include utilizing recent economic trends, accounting for country-specific features, and for the first time, examining the effects of the economic cycle on the bank profitability in Azerbaijan. In addition, the study featured proper addressing time series properties of the panel data, and performances of robustness checks for consistency of results

Saudi Non-Oil Exports before and after COVID-19: Historical Impacts of Determinants and Scenario Analysis

The diversification of the economy including its exports is at the core of Saudi Vision 2030. The vision targets to raise non-oil export from 16% to 50% of non-oil GDP by 2030. Achieving this, in addition to other goals, necessitates a better understanding of the non-oil export relationship with its determinants. However, we are not aware of a study that estimates the impacts of the determinants on Saudi non-oil exports covering the recent years of reforms and low oil prices and that conducts simulations for future. The purpose of this study is to develop an econometric modeling framework for Saudi non-oil export that can enhance informing the policymaking process through empirical estimations and simulations. For estimations, we applied cointegration and equilibrium correction methodology to the annual data for the period 1983–2018. Results show that Middle Eastern and North African countries’ GDP, as a measure of foreign income, and Saudi Arabia’s non-oil GDP, as a measure of production capacity, have statistically significant positive effects on Saudi non-oil exports in the long run. The real effective exchange rate (REER), as a measure of competitiveness, also exerts a positive effect in the long run if it depreciates and vice versa. Furthermore, our findings support the Export-led growth concept, which articulates that export can be an engine of economic growth and does not support the Dutch disease concept, which highlights the consequences of the resource sector for the non-resource tradable sector for Saudi Arabia. Macroeconometric model-based simulations conducted up to 2030 reveal out that the Saudi non-oil export is more responsive to the changes in REER than any other determinants. The simulation results also show that non-oil manufacturing makes a three times larger contribution to the future expansion of non-oil exports than agriculture. Moreover, the simulations discover that finance, insurance, and other business services, as well as transport and communication play an important role in improving the Saudi non-oil export performance in the coming decade. The key policy recommendation is that measures should be implemented in a coordinated and balanced way to achieve non-oil exports and other targets of the Vision

Saudi Non-Oil Exports before and after COVID-19: Historical Impacts of Determinants and Scenario Analysis

The diversification of the economy including its exports is at the core of Saudi Vision 2030. The vision targets to raise non-oil export from 16% to 50% of non-oil GDP by 2030. Achieving this, in addition to other goals, necessitates a better understanding of the non-oil export relationship with its determinants. However, we are not aware of a study that estimates the impacts of the determinants on Saudi non-oil exports covering the recent years of reforms and low oil prices and that conducts simulations for future. The purpose of this study is to develop an econometric modeling framework for Saudi non-oil export that can enhance informing the policymaking process through empirical estimations and simulations. For estimations, we applied cointegration and equilibrium correction methodology to the annual data for the period 1983–2018. Results show that Middle Eastern and North African countries’ GDP, as a measure of foreign income, and Saudi Arabia’s non-oil GDP, as a measure of production capacity, have statistically significant positive effects on Saudi non-oil exports in the long run. The real effective exchange rate (REER), as a measure of competitiveness, also exerts a positive effect in the long run if it depreciates and vice versa. Furthermore, our findings support the Export-led growth concept, which articulates that export can be an engine of economic growth and does not support the Dutch disease concept, which highlights the consequences of the resource sector for the non-resource tradable sector for Saudi Arabia. Macroeconometric model-based simulations conducted up to 2030 reveal out that the Saudi non-oil export is more responsive to the changes in REER than any other determinants. The simulation results also show that non-oil manufacturing makes a three times larger contribution to the future expansion of non-oil exports than agriculture. Moreover, the simulations discover that finance, insurance, and other business services, as well as transport and communication play an important role in improving the Saudi non-oil export performance in the coming decade. The key policy recommendation is that measures should be implemented in a coordinated and balanced way to achieve non-oil exports and other targets of the Vision

Modeling of Electricity Demand for Azerbaijan: Time-Varying Coefficient Cointegration Approach

Recent literature has shown that electricity demand elasticities may not be constant over time and this has investigated using time-varying estimation methods. As accurate modeling of electricity demand is very important in Azerbaijan, which is a transitional country facing significant change in its economic outlook, we analyze whether the response of electricity demand to income and price is varying over time in this economy. We employed the Time-Varying Coefficient cointegration approach, a cutting-edge time-varying estimation method. We find evidence that income elasticity demonstrates sizeable variation for the period of investigation ranging from 0.48% to 0.56%. The study has some useful policy implications related to the income and price aspects of the electricity consumption in Azerbaijan