Economic growth, exports, and role of energy conservation: Evidence from panel co-integration-based causality models in South Asia

2020 ◽  
pp. 0958305X1989937 ◽  
Author(s):  
Muhammad Shakeel ◽  
Aziz Ahmed
Keyword(s):  
Gross Domestic Product ◽  
Error Correction ◽  
South Asia ◽  
Energy Use ◽  
Fossil Fuel ◽  
Domestic Product ◽  
Causality Test ◽  
Environment Friendly ◽  
Gross Domestic Product Growth ◽  
Panel Causality

This study examines the relationship among energy use, real gross domestic product, and exports and thereby the impact of energy conservation for the quest of a sustainable environment-gross domestic product growth in the panel of five South Asian countries. The aggregate production function framework is estimated by employing first/second generational panel co-integration-based models for the panel data covering the years 1980–2014. The empirical findings demonstrate a statistically significant panel error correction mechanism among real gross domestic product, capital, labor, and energy use in both export-added and export-excluded models. The findings of panel causality test depict a significant causal relationship running from export and energy use towards gross domestic product in the long run. Furthermore, a significant feedback relationship between energy use and gross domestic product and between exports and gross domestic product has been found in the short run. These findings of vector error correction model-based panel causality test imply that reducing/cutting the extant aggregate energy use (fossil fuel dominant) via conservation policies are somewhat wanting and could be implemented at the cost of lower gross domestic product and export growths, ceteris paribus. Therefore, for reducing the level of carbon emissions arising from fossil fuel-based energy use and for a sustainable aggregate energy use to the production sector per se, there is an immense need of developing environment friendly/green sources of energy in the region. These consolidated and concerted strides of developing and substituting environment friendly energy options into the extant aggregate energy use will, inter alia, ensure the sustainability of environment-gross domestic product growth in South Asia.

scholarly journals Economic Crisis in Europe: Panel Analysis of Inflation, Unemployment and Gross Domestic Product Growth Rates

2017 ◽  
Vol 9 (10) ◽  
pp. 145 ◽  
Author(s):  
Bibi Rouksar-Dussoyea ◽  
Ho Ming-Kang ◽  
Raja Rajeswari ◽  
Benjamin Chan Yin-Fah
Keyword(s):  
Gross Domestic Product ◽  
Growth Rates ◽  
Fixed Effects ◽  
Domestic Product ◽  
Panel Analysis ◽  
Causality Test ◽  
Data Set ◽  
Gross Domestic Product Growth ◽  
European Crisis ◽  
The Relationship

This panel analysis study is conducted to examine the relationship between inflation rates (CPI) and unemployment rates (HUR) with the Gross Domestic Product growth rates (GDP), before and after the 2008 European crisis. Quarterly data for 18 consecutive years and six sample countries from Europe (Austria, France, Germany, Greece, Hungary and United Kingdom) have been considered in the panel. In order to get a more profound understanding of the impacts of the European crisis on the relationship between the variables, the panel data set has been classified into 3 separate panels, such that Panel 1 (1999Q1-2007Q4) represents before-crisis panel, Panel 2 (2008Q1-2016Q4) represents the during/after crisis panel and lastly, Panel 3 (1999Q1-2016Q4) represents the long-run panel. Panel 1 is subject to the Fixed Effects with LSDV model, whereby four out of the six countries are significant, and CPI and HUR are insignificant predictors of the GDP. Both Panel 2 and Panel 3 are subject to the Two-way Random Effects model, whereby both CPI and HUR have negative significant effect on GDP. Granger Causality test has also been carried out to determine whether causality is present among variables, based on each panel.

scholarly journals A Study Regarding the Advances of Political Stability and Economic Development Experienced in Turkey during the Periods of 1980-2015

2016 ◽  
Vol 8 (10) ◽  
pp. 167
Author(s):  
Mahmut Yardimcioglu ◽  
Ahmet Ilhan
Keyword(s):  
Gross Domestic Product ◽  
Error Correction ◽  
Political Stability ◽  
Correction Method ◽  
Domestic Product ◽  
Annual Data ◽  
Causality Test ◽  
Correction Model ◽  
Causality Tests

In this study, the causality relationship between the political stability and gross domestic product (GDP) in Turkey with the annual data for the period 1980-2015 has been analyzed. The cointegration and Engle-Granger causality tests have been applied in the study. As the Series were cointegrated, the Error Correction Method has been used in order to carry out the causality test. According to the analysis results, the cointegration test suggests the presence of a long-term relationship between political stability and gross domestic product (GDP). As for the Error Correction Model, it reveals the presence of one-way causal relationship from political stability to GDP.

An improved grey Markov chain model with ANN error correction and its application in gross domestic product forecasting

2021 ◽  
pp. 1-11
Author(s):  
Yuan Zou ◽  
Daoli Yang ◽  
Yuchen Pan
Keyword(s):  
Neural Network ◽  
Markov Chain ◽  
Gross Domestic Product ◽  
Error Correction ◽  
Historical Data ◽  
Markov Chain Model ◽  
Back Propagation ◽  
The United States ◽  
Domestic Product ◽  
Chain Model

Gross domestic product (GDP) is the most widely-used tool for measuring the overall situation of a country’s economic activity within a specified period of time. A more accurate forecasting of GDP based on standardized procedures with known samples available is conducive to guide decision making of government, enterprises and individuals. This study devotes to enhance the accuracy regarding GDP forecasting with given sample of historical data. To achieve this purpose, the study incorporates artificial neural network (ANN) into grey Markov chain model to modify the residual error, thus develops a novel hybrid model called grey Markov chain with ANN error correction (abbreviated as GMCM_ANN), which assembles the advantages of three components to fit nonlinear forecasting with limited sample sizes. The new model has been tested by adopting the historical data, which includes the original GDP data of the United States, Japan, China and India from 2000 to 2019, and also provides predications on four countries’ GDP up to 2022. Four models including autoregressive integrated moving average model, back-propagation neural network, the traditional GM(1,1) and grey Markov chain model are as benchmarks for comparison of the predicted accuracy and application scope. The obtained results are satisfactory and indicate superior forecasting performance of the proposed approach in terms of accuracy and universality.

FINANCIAL TECHNOLOGIES FOR THE DEVELOPMENT OF ENTERPRISES AND THE RUSSIAN ECONOMY

2021 ◽  
Vol 1 (10) ◽  
pp. 91-106
Author(s):  
Evgeny V. Sokolov ◽  
◽  
Evgeny V. Kostyrin ◽  
Svetlana V. Lasunova ◽  
◽  
...  
Keyword(s):  
Gross Domestic Product ◽  
Pension Fund ◽  
Social Problems ◽  
The State ◽  
Domestic Product ◽  
Technological Equipment ◽  
Gross Domestic Product Growth ◽  
Development Fund ◽  
Russian Economy ◽  
Competitive Products

The proposed technology of financing enterprises and the Russian economy, harmoniously combining the interests of working citizens, owners and the state, makes it possible, at quite achievable rates of gross domestic product growth (enterprise revenue) by 3.5% per year, to ensure a 46.6% increase in wages of working citizens over 5 years, which will practically end poverty. To increase contributions to the development fund for 5 years by 25%, which the owners of enterprises and the entire workforce are interested in, since this ensures the growth of their incomes and the possibility of constant modernization and updating of technological equipment and the release of new competitive products. Increase in 5 years (despite a gradual decrease to 14.51% of contributions to the Pension Fund RF) the amount of funds received by budgets of all levels by 22%, which will allow the state to solve many social problems.

Financial Deepening, Financial Intermediation and Nigerian Economic Growth: Time Variant Analysis

2019 ◽  
pp. 60-73
Keyword(s):  
Economic Growth ◽  
Interest Rate ◽  
Gross Domestic Product ◽  
Private Sector ◽  
Money Supply ◽  
Domestic Product ◽  
Financial Deepening ◽  
Causality Test ◽  
Real Gross Domestic Product ◽  
Long Run

This study examines financial deepening, financial intermediation and Nigerian economic growth. The main purpose is to examine the relationship between financial deepening and Nigerian economic growth while the specific objectives are to examine the impact of interest rate, capital market development, rational savings, credit to private sector and broad money supply on the growth of Nigerian. Secondary data of the variables were sourced from the publications of Central Bank of Nigeria (CBN) from 1981-2017. Nigerian Real Gross Domestic Product (RGDP) was used as dependent variable while Broad money supply (M2), Credit to Private Sector (CPS), National Savings (NS), Capital Market Capitalization (CAMP) and Interest Rate (INTR) was used as independent variables. Multiple regressions with E-view statistical package were used as data analysis techniques. Cointegration test, Augmented Dickey Fuller Unit Root Test, Granger causality test was used to determine the relationship between the variable in the long-run and short-run. R2, F – statistics and β Coefficients were used to determine the extent to which the independent variable affects the dependent variable. It was found from the regression result that Broad Money Supply, credit to private sector have position effect on the growth of Nigerian Real Gross Domestic Product while National Savings, Capitalization and Interest Rate on Nigeria Real Gross Domestic Product. The co-integration test revealed presence of long-run relationship among the variables, the stationary test indicated stationarity of the variables at level. The Granger Causality Test found bi – variant relationship from the dependent to the independent and from the independent to the dependent variables. The regression summary found 99.0% explained variation, 560.5031, F – statistics and probability of 0.00000. From the above, the study concludes that financial deepening has significant relationships with Nigerian economic growth. We recommend that government and the financial sector operators should make policies that will further deepen the functions of the financial system to enhance Nigerian economic growth.

The Optimum Level of Income Inequality in South Asia: An Econometric Analysis

2021 ◽  
pp. 139156142110390
Author(s):  
Fahmida Khatun ◽  
Syed Yusuf Saadat
Keyword(s):  
Economic Growth ◽  
Income Inequality ◽  
Gross Domestic Product ◽  
South Asia ◽  
Gini Coefficient ◽  
Econometric Analysis ◽  
Domestic Product ◽  
Optimum Level ◽  
Capita Gross Domestic Product ◽  
Per Capita

Inequality in the distribution of income can be beneficial or detrimental for economic growth depending on the level of inequality. This study advocates that when income inequality is low, increase in income inequality increases economic growth, whereas when income inequality is high, increase in income inequality decreases economic growth. The level of inequality that maximizes economic growth is defined as the optimum level of income inequality. This article attempts to determine the optimum level of income inequality for South Asia through an econometric analysis. It uses panel data from Bangladesh, India, Nepal, Pakistan and Sri Lanka, over a 34-year period to undertake a systematic investigation using panel instrumental variables techniques. The results of this study confirm that an optimum level of income inequality does exist, and occurs at a Gini coefficient value of 0.4492. Thus, this research empirically confirms that the relationship between income inequality and economic growth is non-linear. Further calculations show that for an economy that is at the optimum level of income inequality, the per capita gross domestic product can be expected to double within approximately 13 years, provided all other factors are held constant. However, a change in the Gini coefficient by 0.10 units in either direction—higher or lower—away from the optimum level, can increase the number of years for the per capita gross domestic product to double by 55 to 57 years, depending on the method of approximation. JEL: D31, D63, O15, O40

scholarly journals Agricultural exports and the growth of agriculture in India

2013 ◽  
Vol 59 (No. 5) ◽  
pp. 211-218 ◽  
Author(s):  
O. Ramphul
Keyword(s):  
Gross Domestic Product ◽  
Causal Link ◽  
Domestic Product ◽  
Bounds Testing ◽  
Causality Test ◽  
Vector Error Correction ◽  
Agricultural Exports ◽  
Distributed Lag ◽  
Long Run ◽  
Equilibrium Relationship

The study empirically investigates the causality between agricultural exports and gross domestic product (GDP) agriculture in India using the Granger causality test via Vector Error-Correction Model over the period 1970–1971 to 2009–2010. The results of unit-root tests suggest that the series of India’s GDP agriculture and farm exports are integrated of order one. The results of the Auto Regressive Distributed Lag bounds testing approach to co-integration show that there is a positive and stable long-run equilibrium relationship between India’s agricultural exports and GDP of agriculture. We find a unidirectional causal link running from farm exports to gross domestic product of agriculture. It indicates that in India, agricultural products export Granger causes the growth in GDP of agriculture, which supports the export-led growth hypothesis. It is suggested that in order to accelerate the agricultural growth rate in India, there is a need to implement the policies encouraging the agricultural exports.  

The relationship between energy consumption and gross domestic product in Hong Kong (1992–2015): Evidence from sectoral analysis and implications on future energy policy

2019 ◽  
Vol 31 (2) ◽  
pp. 215-236
Author(s):  
Ruixiaoxiao Zhang ◽  
Geoffrey QP Shen ◽  
Meng Ni ◽  
Johnny Wong
Keyword(s):  
Time Series ◽  
Energy Consumption ◽  
Gross Domestic Product ◽  
Causal Relationship ◽  
Granger Causality ◽  
Value Added ◽  
Granger Causality Test ◽  
Domestic Product ◽  
Causality Test ◽  
Per Capita

The causal relationship between energy consumption and gross domestic product in Hong Kong from 1992 to 2015 is investigated in this study. Different from the previous studies focusing on the causal relationship between total energy consumption and total gross domestic product per capita, this study further investigates the causal relationship from sectoral perspective, including residential, commercial, industrial and transportation sectors. For each sector, the time series data of sectoral energy consumption and sectoral per capita value added are collected. To conduct the Granger causality test, the unit root test is first applied to analyse the stationarity of time series. The cointegration test is then employed to examine whether causal relationship exists in long-term. Finally, based on the aforementioned tests, both vector error correction model and vector autoregression model can be selected to determine the Granger causality between time series. It is interesting to find that the sectoral energy consumption and corresponding sectoral per capita value-added exhibit quite different causal relationships. For both residential sector and commercial sectors, a unidirectional causal relationship is found running from the sectoral per capita value added to sectoral energy consumption. Oppositely, for industrial sector and transportation sector, a unidirectional causal relationship is found running from sectoral energy consumption to sectoral per capita value added. Regarding the Granger causality test results, the indicative suggestions on energy conservation policies, energy efficiency policies and greenhouse gas emission reduction policies are discussed based on the background of Hong Kong’s economic structure and fuel types.

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