Renewable Energy Sources and Environment Protection

CHAPTER - 7

Linkage between Global Co2 Emission and

World GDP

Dr. Debesh Bhowmik

Retired Principal,

Associated with International Institute

for Development Studies, Kolkata, India.

Abstract

In this paper author attempted to verify the relationship between global CO2

emission and global GDP ,and between CO2 emission per capita and GDP

growth or GDP per capita growth rate during 1960-2015 through double log

regression model,Granger Cusality test,Johansen cointegration model and by

vector error correction model and impulse response functions.The trend of

emission and per capita emission are shown by semi-log regression model.The

structural breaks of emission is shown by Bai-Perron model. The paper

concludes that the global co2 emission has been rising at the rate of 2.19% per

year and per capita co2 emission is rising at the rate of 0.58% per annum

significantly during 1960-2015.Both of them are stationary,stable and

convergent according to ARIMA(1,1,1) model and they do not belong to random

walk hypothesis. Global CO2 emission during 1960-2015 contains four upward

structural breaks in 1968,1976,1988, and 2004 respectively and per capita

emission has two upward structural breaks in 1969 and 2004 respectively.World

CO2 emission is positively related significantly with global GDP,and GDP per

capita during 1960-2015.World CO2 emission per capita is positively related

significantly with world GDP,GDP growth per capita during the same

period.But global GDP growth is negatively related with global CO2 emission

significant during 1960-2015.There are no cointegration between world GDP

and world CO2 emission and CO2 emission per capita but there is one

CHAPTER - 7

94 Renewable Energy Sources & Environment Protection

cointegrating vector in each between global GDP growth ,global CO2 emission

and world CO2 emission per capita during 1960-2015 repectively.Both of them

have stable,stationary and convergent VEC model whose impulse response

functions are converging towards zero.

Keywords: world CO2 emission,world per capita CO2 emission,world GDP,

world GDP per capita,world GDP growth.

JEL- O13, O40, O44, P28, P48, Q43, Q53, Q56,

I. Introduction

During1960-2015, emissions of CO2 from fuel combustion have tripled and the

main actors have changed. In 1960 the contribution of emissions by China was

around 9%, 1% for India and 10% for rest of the world. By 2015, their

contribution was 24%, 5% and 23% respectively, and China becomes the largest

emitter in the world. Most previous studies of CO2 – Income relationship aim

either to verify and estimate the Environmental Kuznets Curve (EKC) hypothesis

of economic inequity or to describe the long-run equilibrium relationship

between GHG emissions and energy consumption, or GDP, or other. The first

application of Kuznets Curve to environmental studies is done by Grossman and

Krueger (1991, 1993, 1995) followed by Holtz-Eakin (1995) , or more recently

by Perman and Stern (2003), McKitrick and Strazicich (2005) , Aldy (2006) and

Dinda (2004). The results of these studies are controversial about EKC’s

hypothesis, giving opposite conclusions. Dinda and Coondoo (2006) performed

cointegration analysis between per capita CO2 emissions and per capita GDP on

a panel of 88 countries and conclude that a long-run relationship exists between

the variables. The econometric approach which is usually used to estimate the

relationship between GHG emissions and economic growth, as well as to test

EKC hypothesis, has been criticized in academic literature on many points. The

countries with the same level of economic development may have different

relationship between emissions and economic growth for many reasons. The

global CO2 emission scenario is clear since CO2 emission is increasing along

with global GDP or GDP growth rate. The relationship does not behave like EKC

hypothesis. This paper is an empirical attempt to show the relationship clearly

through econometric analysis.

Renewable Energy Sources & Environment Protection 95

II. LITERATURE REVIEW

There are huge economic literatures on climate change and environment

protection and with related themes. I have discussed some of the researches on

the subjects that are correlated with my article.

Azomahou, Laisney and Van(2005) examined the empirical relation between

CO2 emissions per capita and GDP per capita during the period 1960-1996, using

a panel of 100 countries. Estimation results show that this relationship is upward

sloping. Choi, Heshmati,& Cho(2010) took data (1971-2006) from China (an

emerging market), Korea (a newly industrialized country), and Japan (a

developed country) and estimated EKC which showed different temporal

patterns. China shows an N-shaped curve while Japan has a U-shaped curve.

Tiwari (2011) found that environmental degradation (i.e., CO2 emissions)

Granger causes economic growth in the long-run in India during 1971-2005.

Arouri, Youssef, M'Henni, & Rault(2012) taking 12 Middle East and North

African Countries (MENA) data over the period 1981–2005 showed that real

GDP exhibits a quadratic relationship with CO2 emissions for the region as a

whole. Farhani (2012) verified 15 MENA countries covering the annual period

1973-2008 and found that there is a unidirectional causality running from GDP

and CO2 emissions to EC. The results indicate that an increase in energy

consumption may lead to increase in the income and the CO2 emission. Lean &

Smyth(2013) examined in ASEAN countries over the period 1980 to 2006. The

long-run estimates indicate that there is a statistically significant positive

association between electricity consumption and emissions and a non-linear

relationship between emissions and real output, consistent with the

Environmental Kuznets Curve. Chueh(2014) showed that the emissions of

carbon dioxide may not depend on the growth of per capita GDP using the

hierarchical clustering approach to cluster 36 countries during 1990-2011. Alam

(2014) examined the relationship between economic growth (GDP per capita)

and CO2 emissions of Bangladesh based on the environmental Kuznets curve

hypothesis, using World Bank data over 1972-2010 and found that the existence

of EKC “U” shape does not hold. Antonakakis , Chatziantoniou and Filis(2015)

took data of 106 countries during 1971-2011 which revealed that the effects of

the various types of energy consumption on economic growth and emissions are

heterogeneous on the various groups of countries. Moreover, causality between

total economic growth and energy consumption is bidirectional, and the

continued process of growth aggravates the greenhouse gas emissions

phenomenon. Omri(2015) examines the nexus between CO2 emissions, energy

96 Renewable Energy Sources & Environment Protection

consumption and economic growth using simultaneous-equations models with

panel data of 14 MENA countries over the period 1990-2011. His results show

that there exists bidirectional causal relationship between energy consumption

and economic growth and there exists bidirectional causal relationship between

economic growth and CO2 emissions for the region as a whole. Muhyidin,

Saifullah,& Fei(2015) showed that CO2 emission, income development level,

total energy usage within the country and industrial production index growth to

be cointegrated thus indicating a long-run cointegrating relationship among all

the series in Malaysia during 1970 to 2012. Mesagan(2015) studied in Nigeria

during 1970-2013 and verified that growth relates positively with CO2 emission

using VECM.In China, during 1990–2012, Wang ,Li , Fang , & Zhou(2016)

found that surprisingly, no such causal relation was found between economic

growth and CO2 emissions. Mir and Storm(2016) verified that CO2 emissions

are monotonically increasing with per capita GDP for 40 countries (and 35

industries) during 1995-2007. Magazzino(2016) showed that the predominance

of the “growth hypothesis” emerges in three GCC countries (Kuwait, Oman, and

Qatar), since energy use drives the real GDP. Moreover, only for Saudi Arabia a

clear long-run relation has not been discovered. Finally, the results of the

variance decompositions and impulse response functions broadly confirm their

previous empirical findings. Their results significantly reject the assumption that

energy is neutral for growth during 1960-2013. Xiongling (2016) suggests that

there is evidence that economic development can improve environmental

degradation in the long-run and economic growth may have an adverse effect on

the CO2 emissions in China during 1961-2010. Cederborg & Snöbohm(2016)

conducted on 69 industrial countries as well as 45 poor countries using crosssectional

data and conclude that there is a relationship between economic growth

and environmental degradation, the impact of this relationship is however

different. The empirical result of the cross-sectional study implies there is in fact

a relationship between per capita GDP and per capita carbon dioxide emissions.

The correlation is positive. Ahmada, Azreen, Zulkiflib, Aziz,Hassanc,Yaseer &

Abdoh(2016) found strong positive relationship between GDP and energy

consumption during 1980-2011 in Malaysia.

III. Objectives of study

This study endeavours to verify the empirical relationship through econometric

models between world CO2 emission in kilo ton and world GDP(current

US$),world CO2 emission per capita in metric ton with world GDP and GDP per

capita (in current US$ ) and with their growth rates respectively during 1960-

2015 showing the empirical evidences in several countries.

VII. Concluding remarks

The paper concludes that the global co2 emission has been rising at the rate of

2.19% per year and per capita co2 emission is rising at the rate of 0.58% per

annum significantly during 1960-2015.Both of them are stationary, stable and

convergent according to ARIMA(1,1,1) model and they do not belong to random

walk hypothesis. Global CO2 emission during 1960-2015 contains four upward

structural breaks in 1968, 1976, 1988, and 2004 respectively and per capita

emission has two upward structural breaks in 1969 and 2005 respectively. World

CO2 emission is positively related significantly with global GDP, and GDP per

capita during 1960-2015.World CO2 emission per capita is positively related

significantly with world GDP,GDP growth per capita during the same period.

But global GDP growth is negatively related with global CO2 emission

significant during 1960-2015.There are no cointegration between world GDP and

world CO2 emission and CO2 emission per capita but there is one cointegrating

vector in each between global GDP growth , global CO2 emission and world CO2

emission per capita during 1960-2015 repectively. Both of them have stable,

stationary and convergent VEC model whose impulse response functions are

converging towards zero.

Read from

www.irphouse.com

NEXUS BETWEEN GROWTH AND HUMAN DEVELOPMENT INDEX:EVIDENCE FROM INDIA AND INDIAN STATES.

 Article No-10, Vol-3,Issue-2,2018,96-118,July-December, Assumption University e Journal of Interdisciplinary Research, Graduate School of e Learning.Thailand.

NEXUS BETWEEN GROWTH AND HUMAN DEVELOPMENT INDEX:EVIDENCE FROM INDIA AND INDIAN STATES.
.......................Dr.DEBESH BHOWMIK

Assumption University-eJournal of Interdisciplinary Research (AU-eJIR): Vol. 3. Issue.2, 2018
ISSN: 2408-1906 Page 1
NEXUS BETWEEN GROWTH AND HUMAN DEVELOPMENT INDEX: EVIDENCE FROM INDIA AND INDIAN STATES
Dr. Debesh Bhowmik
(Retired Principal and Associated in Indian Economic Association and
The Indian Econometric Society)
Abstract: In this paper, the author endeavors to show the nature of HDI and the relation between HDI of India and economic growth, rate of unemployment, GDP and GDP per capita respectively during 1990-2016. The author used semi log and double log regression model and also used Bai-Perron Model (2003) for structural breaks, Granger model (1969) for causality, Johansen model (1988,1996) for cointegration and vector error correction and Sala-i-Martin(1996) model for convergence test in Indian States. The paper concludes that HDI of India has been increasing at the rate of 1.55% per year from 1990 to 2016.HDI has three upward structural breaks in 1996, 2004 and 2011 respectively. HDI of India does not follow random walk hypothesis. One per cent increase in HDI of India led to 1.41% increase in growth rate per year during 1990-2016. This relationship is co-integrated and they have no bidirectional causality. Their VECM is unstable and non-stationary and error correction is significant and fast for equation Δlog (GDP growth rate). Moreover, one per cent rise in HDI per year led to 5.86% rise in GDP, 4.828 % increase in GDP per capita and 0.5028% decrease in unemployment rate per year respectively during 1990-2016 in India. There is positive association between HDI, GSDP and GSDP per capita of all states in 1983, 1987-88, 1999-00, 2004-05, 2009-10 and 2011-12. These relationships are valid for high plus medium human development and low human development states of India for those years. In Fixed effect model of panel data, the regression between of all states’ HDI and GSDP per capita is positive. This paper finds sigma convergence of HDI of all states. Only four states showed negative growth of HDI in spite of their rising trends of social sector expenditure. The paper recommended to enhance government expenditure on education and health and to emphasis gender budgeting and FDI inflows.
Key Words-Human Development Index, Economic Growth, Cointegration, Causality, Vector Error Correction, HDI of Indian States

JEL Codes-O10, O15, O57, C23

1. INTRODUCTION

Economic thoughts on the recognition of human capital as central force in economic theory since long period were relevant when Adam Smith (1776) argued that growth means not only capital accumulation and technical progress but also growth of human capital which play a critical role in the progress of economic development. With obvious reason, Marshall (1890) stressed education and parental care as investment in human capital. Then Schultz (1963) in the human capital model showed how education allows the production process to benefit from positive externalities and promotes growth. Gary Becker (1964) said that human capital investment increases the ability of people to increase wealth because human capital is the investment in training, education, health, values and other aspect of human potential. After a decade, Lucas (1988) in the endogenous growth theory emphasized investment in human capital more directly and linked it to long term rates of economic growth. In internal growth models, Romer (1986; 1990), and later economists investigated economic growth through physical and human capital accumulation. Besides labor and capital, human capital had a significant place in endogenous growth models and additionally the effects of human capital on economic growth were pointed out in previous studies in the literature (Telatar & Terzi,2010). In analyzing the process of human capital, Hahbub Ul Haq (1995) defined human development paradigm as “the process of enlarging people’s choices”. Amartya Sen (1999) went further and argued that standard of living of a society should be judged not by the average level of income but by people’s capabilities to lead the life they value. Author argued that development ought to be viewed as capability expansion and freedom, rather than being viewed as purely economic phenomenon. Additionally, Becker, Murpy, & Tamura (1990) in a study titled “Human Capital, Fertility and Economic Growth”, indicated higher returns of human capital and education in developed countries than in developing countries. Based upon the aforementioned information, one can see that the size of a population alone is not sufficiently effective on economic growth and the bottom line is the knowledge, skills, and experience-like attributes of the population.
Human development has positive impact on economic growth through improvement of human capital because education has strong effects on labour productivity and improvement in health and nutrition enhances productivity and income. More educated people are likely to innovate and thus affect everyone’s productivity. Even, education may affect per capita income growth through reducing population growth. Distribution of income and assets has an effect on economic growth because of better nutrition and strong demand for education and hence higher productivity. Education alone, of course, cannot transform an economy. The quantity and quality of investment, domestic and foreign together constitute other important determinants of economic performance. Education and health may also have strong indirect impacts on economic growth through their effects on distribution of income and education even more so through its impact on health. Tailor et al (1999) expressed that in developing countries economic growth is needed for reducing poverty, providing access to basic social services, building of basic capabilities in the people and generating the resources required for human development. Economic growth is a necessary but not sufficient condition for the promotion of human development. Beyond quantity, it is the quality of growth that is crucial for human well-being. Growth that is jobless, ruthless, voiceless, rootless and futureless is not favorable to human development .Economic growth must be equitable for its benefits to have an impact on people’s lives. Human development and economic growth have two-way causal relationship. Human development raises levels of education, health, and nutrition in an economy all of which enhance productivity of the economy. And growth can also be linked to many other elements of human development such as political freedom, cultural heritage, societal progress and environmental sustainability. Because, modern growth theory explains economic growth rate primarily in terms of expanded human and social capital rather than physical capital. On the one hand, economic growth provides the resources to permit sustained improvement in human development. On the other hand, sustained improvement in the quality of human capital is an important contribution to economic growth.
7. CONCLUSIONS

The paper concludes that HDI of India has been increasing at the rate of 1.55% per year from 1990 to 2016.HDI has three upward structural breaks in 1996, 2004 and 2011 respectively. One per cent increase in HDI of India led to 1.41% increase in growth rate during 1990-2016.This relationship between HDI and growth is co-integrated and they have no causality. Their VECM is stable but nonstationary and error correction is significant and fast for equationΔlogx3t.Moreover, one per cent rise in HDI per year led to 5.86% rise in GDP, 4.828 % increase in GDP per capita and 0.5028% decrease in unemployment rate per year respectively during 1990-2016 in India. Even, HDI has unidirectional causality with GDP and GDP per capita .There is positive association among GSDP and GSDP per capita with high plus medium human development and low human development states of India for those years. In Fixed effect model of panel data, the regression between of all states’ HDI and GSDP percapita is positive .This paper finds sigma convergence of HDI of all states. Only four states showed negative growth of HDI in spite of their rising trends of social sector expenditure. The paper recommended to enhance government expenditure on education and health including gender budgeting and FDI inflows.

DOWNLOAD
www.ejir.au.edu