Abstract

This study examines the relationship between primary energy consumption (PEC) and real gross domestic product (real GDP) in the top four major energy consumers in Asia, namely, China, India, Japan, and South Korea. The study period is from 1982–2018, covering 37 years of data after the second oil crisis (1979–1981). Bootstrap panel Granger causality method is applied to examine the causal relationship between PEC and real GDP. This method is capable of controlling cross-sectional dimension and cross-country heterogeneity. In addition, few studies investigate the relevance of real GDP to energy consumption, although real GDP adjusted by inflation provides an accurate picture of a country’s economic situation. Our results contribute to existing literature in the field of PEC and real GDP. Through rigorous empirical research, we derive the main conclusion as follows. The real GDP and PEC of the top four energy consumers in Asia seem to be affected by the burst of the speculative Internet bubble from 2000–2001. Therefore, this study divides the research period into three periods: 1982–2018, 1982–2001, and 2002–2018. During the 1982–2018 period, an independent causal relationship is observed between real GDP and PEC for all four countries, thus supporting the neutrality hypothesis. During the 1982–2001 period, a unidirectional causal relationship running from PEC to real GDP is observed, thus supporting the energy growth hypothesis. Moreover, the coefficient is significantly negative in India; that is, PEC constrains economic development. Thus, the Indian government should reform its energy efficiency and consumption technologies to reduce energy waste. During the 2002–2018 period, an independent causal relationship is observed between real GDP and energy consumption for all four countries, thus supporting the neutrality hypothesis. This study then changes real GDP into nominal GDP and finds a unidirectional causal relationship running from PEC to nominal GDP in South Korea, thus supporting the growth hypothesis. A unidirectional causal relationship is also observed running from nominal GDP to PEC in India, thus supporting the energy conservation hypothesis. As mentioned above, we find that the relationship between PEC and real GDP adjusted by the GDP deflator is weaker than that between PEC and nominal GDP. Nominal GDP strengthens its relationship with PEC through the effect of prices for all the goods and services produced in an economy.

Highlights

  • The British Petroleum Global Energy Statistical Yearbook 2019 reported that the growth in 2018 was remarkably strong because primary energy consumption (PEC) increased by 2.9% from 2017

  • During the 1982–2018 period, an independent causal relationship is observed between real GDP and PEC for all four countries, supporting the neutrality hypothesis

  • During the 2002–2018 period, an independent causal relationship is observed between real GDP and energy consumption for all four countries, supporting the neutrality hypothesis

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Summary

Introduction

The British Petroleum Global Energy Statistical Yearbook 2019 reported that the growth in 2018 was remarkably strong because primary energy consumption (PEC) increased by 2.9% from 2017. The level of primary energy prices deeply affects the profitability of various industries Decreases in such prices are good for the economic growth (EG) of countries that rely on energy imports and can increase profits for manufacturers. The decline in oil prices has benefited Asian countries, such as Japan, South Korea, China, and India, helping them to engage in public construction and infrastructure, curb inflation, and increase GDP. This study first uses the bootstrap causality test to determine the relationship between energy consumption and real GDP for the top four major energy consumers in Asia, namely, China, India, Japan, and South Korea. This test can effectively overcome cross-sectional correlation and heterogeneity problems. The results of this study will contribute to the academic and practical fields

Literature Review
Methodology
Cross-Sectional Dependence Test
Slope Homogeneity Test
Empirical Results and Policy Implications
Conclusions
Full Text
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