Do energy consumption and carbon emissions impact economic growth? New insights from India using ARDL approach

• Published date: 01 March 2022
• Author: Kamaljit Singh,Jasvinder Kaur
• Date: 01 March 2022
• DOI: http://doi.org/10.1111/opec.12223

Do energy consumption and carbon

emissions impact economic growth? New

insights from India using ARDL approach

Kamaljit Singh*and Jasvinder Kaur**

*University School of Management, Kurukshetra University, Kurukshetra, Haryana 136119, India.

Email: kamaljitsehjanusm17@kuk.ac.in

**Department of Commerce, Kurukshetra University, Kurukshetra, Haryana 136119, India.

Email: jasvinderkaurphd@kuk.ac.in

Abstract

This paper investigates the association among energy consumption, carbon-dioxide emission, and

India’s economic growth along with supplemental variables including foreign direct investment,

population density, inflation, and agricultural land. An autoregressive distributive lag model is

applied over annual time-series data from 1985 to 2019. Further, the robustness and novelty of the

model are confirmed by applying fully modified ordinary-least-square, dynamic ordinary-least-

square, canonical co-integrating regression, variance decomposition, and impulse response

function. The analysis results indicate that a cointegration association exists among variables. In

the short run, the profound determinants of economic development are energy consumption,

carbon-dioxide emission, inflation, and agricultural land. In the long run, both inflation and

agricultural land significantly negatively influence economic growth while carbon emission drives

a positive impact. Interestingly, a one-way Granger causality runs from economic growth towards

energy consumption, carbon emission, and agricultural land. The new research presents a

comprehensive understanding of economic growth indicators, aiding policymakers, and advancing

existing literature. Consequently, as a recommendation, the policymakers should constitute explicit

goals for renewable energy consumption to stimulate sustainable economic growth with carbon

emission reduction.

1. Introduction

Globally, energy development is inextricably related to well-being and prosperity. The

vital aspect is to meet the rising energy demand in a sustainable and environmentally

friendly manner. At the time of global market volatility, one sure thing is that the world

requires energy in growing quantities to drive economic and social prosperity and

improve living standards, especially in developing countries (Yohe and Tol, 2002;

Soytas and Sari, 2003). For emerging regions, the requirement for sustainable and

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affordable energy becomes even more pertinent. It has the potential to change as well as

save lives. Reliable energy enables developing economies to promote trade, modernise

agriculture, facilitate investment, and enhance infrastructure (Ang and Zhang, 2000;

Apergis and Payne, 2010). These are also the fundamental components that enable

people to overcome poverty and ensure a good lifestyle.

In India, energy consumption increases every day because incomes are rising, and

the population is also growing faster. India stands at the second number after the

Republic of China in the world’s most populated nations. Thermal power plants are the

major source of fulfilling the growing energy demand of India. As per the report of the

Central Electricity Authority, India (2021), 61.4 per cent of the power is generated by

thermal plants, followed by renewable energy sources (24.6 per cent), hydro (12.2 per

cent), and nuclear (1.8 per cent). The thermal power plants use coal, gas, lignite, and

diesel sources for power generation. There is a need for regular and reliable electricity to

meet the growing demand of different consumer categories, that is, residential, industrial,

commercial, agricultural, and traction. These consumer categories contribute signifi-

cantly to the country’s economic growth (Altinay and Karagol, 2005; Mozumder and

Marathe, 2007). A Nation has to bear the heavy cost of any constraint in electricity

supply to different consumer categories. The significant consequences can be the

sluggish economic growth, low credibility and confidence among potential investors,

low productivity by agriculture and industrial sectors, lower exports, and higher

dependence on imports (Shiu and Lam, 2004; Yoo, 2005). Therefore, a proper power

supply is required for the growing economic growth of the nation.

More dependence is on coal, gas, lignite, and diesel sources to provide electricity to

different consumer categories. The excessive use of these resources produces carbon

dioxide emission, which is a crucial point of concern globally and creates an

environmental threat (Tol, 2005; Gerlagh, 2008). The India Green House Gases

Program, National Action Plan on Climate Change, and National Wetland Conservation

Program are some of the major initiatives taken by the Indian government from time to

time to reduce CO

2

emission (IEA-India, 2020). However, there is a need for alternatives

in technology and policy implications to control carbon dioxide emissions and provide

electricity to required sectors without any hindrances.

This article looks into the association between energy usage, carbon dioxide

emissions, and India’s economic growth, considering recent phenomena and the vital

role of energy in economic growth. Consequently, in earlier studies, researchers have

only focused on the domestic capital, labour force, and financial development while

examining growth’sinfluence (e.g., Cheng, 1999; Wolde-Rufael, 2010; Shahbaz et al.,

2017; Raghutla and Chittedi, 2020). This research gap motivates the researchers to frame

the research question to accomplish the current study’s objective. The study also

examines explanatory variables that have been overlooked in previous studiesbut may

©2022 Organization of the Petroleum Exporting CountriesOPEC Energy Review March 2022

Energy consumption and carbon emissions69

significantly impact and address India’s economic growth. Foreign direct investment

(FDI), population density, agricultural land area, and inflation are the explanatory

variables. These indicators are included as potential contributors to economic growth and

account for omitted variables, which results in more impartial, coherent, and reliable

results (Ahmad and Du, 2017).

Foreign investments should not be overlooked as it has a decisive role in expanding

and building an economy in today’s global environment. Natural surroundings have

endowed India with land and resources. For this reason, researchers included the

agricultural land area to ascertain whether India’s land is suitable for agriculture or

industrial usage. Inflation is often included as an explanatory variable to determine

whether it is long-run detrimental to the economy or not (Mehrara, 2008). The

population density variable is being used instead of the workforce to look at how a

congested environment can affect economic growth in India, whether it can influence

economic growth positively or negatively. These indicators have been calibrated using

data from various research because they could be potential growth determinants

(Thornton, 1996; IEA, 2004; Loizides and Vamvoukas, 2005; Alam et al., 2016).

The most recent autoregressive distributed lag (ARDL) approach was employed to

check the variables’linkages. The model’s accuracy and reliability were not verified

using only several diagnostic tests, such as the functional type of the model, the

autoregressive conditional heteroscedasticity (ARCH) test for heteroscedasticity, serial

correlation, the normally distributed test, and the recursive estimates for coefficient

stability. Consequently, fully modified ordinary least square (FMOLS), dynamic

ordinary least square (DOLS), and canonical cointegrating regression (CCR) are also

performed to verify the model’s robustness. It is another novel feature of the study. The

FMOLS and DOLS estimation methods also are employed as Kao and Chiang (2000)

illustrate that DOLS outstrips FMOLS. Only the data transformation is used by the CCR,

which chooses a canonical regression from each of the models that reflect asimilar

cointegrating relationship (Park, 1992; Kwakwa, 2017). As a result, these tests are used

to assess the robustness of the ARDL model. FMOLS, DOLS, and CCR estimators’

superiority are that they are exempt from unobserved heterogeneity, small sample size

biases, and serial correlation issues (Phillips and Hansen, 1990; Hotelling, 1992; Stock

and Watson, 1993).

1.1.Brief overview for selected macroeconomic indicators

In this section, the yearly trend of selected macroeconomic indicators is discussed. As

shown in Fig. 1, India’s per capita gross domestic product (GDP) is growing over the

study period 1985–2019. From the year 1985–1990, the growth rate is sluggish. Since

the mid-1980s, India has slowly opened its markets through economic liberalization.

Surprisingly, after introducing the liberalization, privatization, and globalization concept

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70 Kamaljit Singh and Jasvinder Kaur