Forecasting and the casual relationship of sectorial energy consumptions and GDP of Pakistan by using AR, ARIMA, and Toda-Yamamoto Wald models (original) (raw)

Forecasting Energy Consumption and CO2 Emission Using ARIMA in Pakistan

2017

This study forecasts the energy consumption of Pakistan which is facing a huge and permanent shortfall of electricity. Being a fast developing economy in the current era, water and power development authority has to plan power production project by keeping in mind the future needs of the country. Carbon Dioxide (CO2) emission is a major concern for environmental protection agency for fast developing economies, so we have forecasted CO2 using ARIMA forecasting modeling. Further, we forecasted Energy Consumption as this country is facing a shortfall of almost half of the total electricity consumption using ARIMA.

A Time Series Analysis of Energy Consumption, Energy Prices and Economic Growth in Pakistan

European Online Journal of Natural and Social Sciences, 2019

The present study is conducted to investigate the impact of Energy Consumption (EC) on the Economic Growth (EG) in Pakistan by using a trivariate model. Time series data of macroeconomic determinants of Energy Consumption (EC), Energy Prices (EP) and Economic Growth (EG) are used to analyze the linkage among the variables. Annual data are collected from different published sources like World Development Indicators (WDI), BP Statistical Review and Economic Surveys of Pakistan for the period 1971-2014. Augmented Dickey Fuller (ADF) unit root test and Phillips Perron unit root test are used to examine the stationarity of data and all the variables are found stationary in differenced form. Short run and long run linkage among the variables is examined through Johansen co-integration test and the results confirm the existence of one co-integrating vector among the variables. Granger causality test under Vector Error Correction Model (VECM) is applied to observe the direction of between E...

Forecasting aggregate and disaggregate energy consumption using arima models: A literature survey

Journal of Statistical and Econometric Methods, 2012

The paper is aimed at contributing to the body of knowledge that exist in the area of energy forecasting by reviewing relevant empirical works on energy forecasting using ARIMA models. This paper is relevant in the face of frequent power outage and the dependence on external economies for energy supply. The study is based on secondary data obtained from electronic journals through archival studies. In all 10 articles were selected through purposive sampling method and were analysis using content analysis method. The results indicate that future energy consumption is expected to increase in economies in which these forecasts have been done. Hence, energy use must be efficient to avoid energy crisis in future. Future research should look at review of works on forecasting in a comparative manner comparing other models that have been used in forecasting energy demand. The paper is limited by the use of only secondary data. Errors in variables and omissions may not be known by the resear...

Relationship of Energy Consumption and Economic Growth in Pakistan

Journal of Business and Social Review in Emerging Economies

The paper analyzed the fundamental relationship among the uses of energy, uses of electricity and gas, total consumption of oil, and economic development of Pakistan. This analysis used time series data for the sample span of 1972-2017, retrieved from economic survey of Pakistan (ESP, 2018). Vector Auto Regressive (VAR) model is used for analyzing the causal link amongst the variables. Before estimating VAR, Augmented Dickey Fuller (ADF) and breusch-Godfrey serial correlation LM tests are applied for confirming a stationarity characteristic of every variable, initial with intercept and then, with interrupt along with the linear deterministic trend. The Schwartz Information Criterion (AIC) is applied for the selection of optimal lag. Johansen Co-integration analysis is adopted for identifying long run association. Result of the VAR model reveals that 1% increase in consumption of natural gas accelerates economic growth by 1.5%.Similarly 1% increase in consumption of petroleum...

Dynamic Relationship between Energy Consumption and Economic Growth: Time Series Analysis from Pakistan & India

Scarcity of natural resources including energy resources motivated many researchers to extensively study the association between energy usage and country's economic growth. Therefore, this article is also an attempt to examine causal relationship between energy consumption and GDP in the long and short run of two developing countries of Asia. Empirical results driven from co-integration and vector error correction (VECM) analysis reveal that unidirectional causality in the long run is running from GDP to energy consumption in both India and Pakistan. Furthermore, researcher fails to identify any short causality (neutrality effect) between two variables in Pakistan, whereas bidirectional (feedback effect) causality in the short run for India was established. These results have significant policy implications for concerned countries. The outcomes recommend that both countries can openly initiate energy conservation methods and procedures in the long run and can go for a well-adjusted group of alternative strategies and polices for energy consumption and economic growth in the short run.

A Historical and Econometric Analysis of Energy Consumption and Industrial Output in Pakistan (1990-2019)

PERENNIAL JOURNAL OF HISTORY

This paper examines the nexus of disaggregated energy consumption and industrial output in Pakistan. The annual time series data over the period 1990-2019 has been taken for current research. ARDL technique has been employed for empirical analysis. The results show that oil consumption, electricity consumption and gas consumption are positively and significantly connected with the industrial output in long run. Similarly, trade openness, labour and capital also have the same association with the industrial output and have significant outcomes in the long run. The results of Granger causality show that there exists a unidirectional causality from electricity consumption to industrial output. The study concludes that oil, gas and electricity are contributing a large share in industrial growth so that it would be made an effort to install the plants relevant with these energy sources to meet the affordable demand in the industry sector.

Disaggregate Energy Consumption, Agricultural Output and Economic Growth in Pakistan

The basic goal of the study is to make a vigorous endeavour to analyse the impact of energy consumption (i.e., electricity, oil and gas) on economic growth and agriculture sector output in Pakistan. It is desirable to find out relationship between disaggregate energy consumption, economic growth and agricultural sector outputs of Pakistan because energy crisis has become a central issue now-a-days. Production sector of Pakistan relying on electricity and gas consumption to large extent and these sources of energy are falling short because of many reasons which is upsetting output and consequently exports and real output of the country. To analyse the relationship, we employed time series data ranges from 1972 to 2011 from a reliable source. To find out long run and short run effects of energy consumption on Agricultural output and economic growth, ARDL modelling approach to cointegration is applied which is most appropriate technique over some other techniques of integration after scrutinizing the stationarity of data through ADF Test. Where, bound testing procedure is utilized for cointegration to judge the existence of long run relationship among variables and ECM models are formulated for short run analysis. Our econometric models give the intuition of including agricultural output and economic growth as dependant variables and electricity, coal and gas consumption as independent and core variables. The findings of the study indicate that Gas and Oil consumption turns out very efficient factors for raising economic growth and Agricultural output.