Reassessing the Carbon Kuznets Curve: Panel Data Model Analysis

for Prefecture-level Cities in China

Yanhong Li

North China Electric Power University, Baoding, Hebei, China

Keywords: Carbon emission; Carbon Kuznets curve; Co-integration test; Prefecture-level Cities.

Abstract: This article is based on Environmental Kuznets Curve, and analyzes the relationship between carbon

Emissions and Economic Growth in prefectural cities in China by using Panel Data Model. Variable time

span is 14 years. Cross-section covers more than 200 prefecture-level cities .It shows that with the

development of economic, carbon emissions are on the rise. The carbon Kuznets curve presents a curve with

an upper right slant. Inverse U-shaped relationship is not obvious or the inflection point is not reached .This

shows that passively waiting for economic growth to improve the quality of environment does not meet

China’s development model, and coordinated development of economic growth and quality of environment

is the fundamental way for China’s sustainable development.

1 INTRODUCTION

Carbon emission is the main reason that leads to the

global warming. Controlling emission has become

an important issue，for it’s about the interests of

people all over the world According to World

Development Report 2010: Development And

Climate Change published by World Bank. From

Industrial Revolution to now, the average

temperature of the world has risen by 1 degree.

What’s worse, in a decade of the 1980s, the

temperature rose by 0.48 degree from 100 yearsago.

As global temperature rises, there are lots of

disasters which have bad impact on the survival and

development of human. With the rapid development

of China’s economic, reliance on fossil fuels grows

in multiples. According to World Energy Outlook

2007 published by International Energy Agency, the

average rate of carbon emissions in China is 4.2%

which ranks first in the world. China is under great

pressure from domestic and international carbon

emission reduction. To balance the development of

economic and carbon emission is an important issue

for China’s current economic development. In 2015,

China Fragrance “Joint International Framework

Convention on Climate Change” Secretariat

submitted Strengthening Actions to Address Climate

Change-China’s national Independent Contribution.

It sets a goal for carbon emission, by 2030 China’s

carbon emissions per unit of GDP fell 60% to 65%

from 2005. In addition, to achieve the goals of

sustainable energy development and non-fossil

energy accounts for 20% of primary energy .

China’s per capita carbon emissions are lower

than that in developed countries such as the United

States, poor energy technology leads to energy

utilization and higher carbon emissions per unit of

GDP.As we all known, economics growth leads to

increased carbon emissions. If we take unreasonably

measures to control carbon emissions, it is true that

it will do harm to the development of the economic.

China will take economic development as its top

priority for a long time; therefore, it is not a wise

idea for a developing country like China to give up

the development of economic in order to protect the

environment. From the perspective of the

development of economic in other countries, the

rapid economic growth while low-carbon emission

development modal; does not exist, according to the

theory of the development of Environmental

Kuznets Curve in Environmental Economics, The

law “First pollution, after treatment” is summarized

by developed countries which is not suitable for

developing countries.

This article takes the environmental Kuznets

curve as the research perspective, collect the panel

data model and create panel data for each region

spanning more than 20 years, through empirical

analysis to find the relationship between the

development of economic and carbon emissions in

China. To have a comprehensive discussion of the

form of the Kuznets curve in various regions of

China according to panel data modal so that it can

provide theoretical support for the promotion of

building an environmentally friendly society.

2 REGRESSION RESULTS

ANALYSISOF PANEL DATA

MODEL

2.1 Panel Data Analysis Between

Energy Consumption and

Economic Growth

The theory of CKC is a great method to study the

relationship between carbon emissions and

economic growth. Main through regression analysis

to verify whether there is an inverted U shaped

relationship between economic growth and carbon

emissions and decoupling theory to analyze the

relationship between them. In 2008 Wagner studied

the relationship between carbon emissions and GDP

per capita and proved that CKC is also an inverted U

shape. The general expression of CKC is: C=

f(G,G





,W), C stands for environmental quality

and it usually measured by indicators of carbon

emissions. The formula of panel data model is:



=α



+α





+α







+α







+α





+ε



(1)

And α



is the model parameter, the relationship

between environment and economic growth can be

reflected by the parameter value.

If α



>0,α



=0,α



=0 , there is a

monotonically increasing positive correlation

between carbon emissions and economic growth. In

other words carbon emissions increase with

economic growth, there will be no turning point of

carbon emission reduction.

If α



>0,α



<0,α



=0, at this point, there is

an inverted U-shaped curve between carbon

emissions and economic growth, carbon emissions

increase first and then decrease as the economic

grows.

If α



<0,α



>0,α



=0, CKC curve is U

shaped ,with the development of economic, carbon

emissions first decrease and then increase.

If α



>0,α



<0,α



>0, the curve is N shaped.

It shows that carbon emissions first increase and

then decrease and then increase again as the

economic grows.

If α



<0,α



>0,α



<0, the curve is inverted

N-shaped. It shows that carbon emissions first

decrease and then increase and then decrease as the

economic grows.

In my perspective, the EKC curve is based on the

analysis of the industrialization process in the

developed countries and its inverted U pattern

mainly reflects the law of economic growth in

developed countries as a function of the

environmental quality .However the developing

world in different developing countries is different

.The development path of developing countries is

different from the analysis of the industrialization

process of developed countries. Developing

countries will not wait for the natural improvement

of the environment and will therefore intervene early

in the process of industrialization .These factors

have an impact on the morphology of the EKC curve

.So whether the inverted U shaped of the

environmental Kuznets curve in developing

countries needs to be verified in more sophisticated

data fitting. Due to data limitations most of the

literature is mainly limited to national or provincial

data and the information obtained is limited.

This article will use data from various regions of

China on carbon emissions and economic growth to

fit the shape of the EKC curve. Since regional-level

data contains more relevant information on

environmental and economic growth the fitting

effect is more convincing.

2.2 Reassessing the Carbon Kuznets

Curve

Because the carbon emissions in prefecture level

cities cannot be obtained directly and the differences

between energy consumption structure and

production technology in the same period in the

same province are small, we use the percentage of

the prefectural city GDP in the province as a weight.

Estimating carbon emissions of prefecture level

cities through the provincial carbon emissions. This

article uses the carbon emission panel date of

prefecture level cities from 2013 to 2016. According

to 《China City Statistical Yearbook》covers 283

prefecture level cities , however, in some western

regions , some key date are missing . The final panel

date covers 251 prefecture level cities. We use the

following regression model because most studies use

quadratic curve to fit the EKC:

plc



= α





+α







+α



FAI



+α





+δ



+φ





（2）

The subscript ‘it’ represents the index of the t-

th year of the i-th prefecture level city, α represents

the corresponding regression coefficient, PICit

represents the carbon emissions of the t-th year of

the i-th prefecture level city, ICit represents the per

capita GDP, the date use the GDP of prefecture level

city divided by the total population at the end of a

year and adjusted the price index based on 2003.

FAIit represents fixed asset investment of the t-th

year of different regions, ISit represents the

industrial structure of the t-th year of different

regions, φi represents regional fixed effect variable,

δt represents fixed time effect variable. This article

uses a variable that lags by one period as a tool

variable to conduct model estimation because there

are certain entophytes in the model’s explanatory

variables GDP and fixed assets investment

indicators.

LM =



()



∑



∑

















∑∑















−1



（3）



(







)









(







)

~χ



(k) （4）

Through the Hausman and LM tests, the results

show that fixed effect model is better, and the

specific regression results are shown in the table 1.

Model 1 just see per capita GDP and its

quadratic term as explanatory variables, the result

shows that at the 1 ％ level of significance, the

coefficient of one term is obviously a positive value,

the coefficient of quadratic term is not obvious. This

indicates that when the model does not include other

explanatory variables, the relationship between

carbon emission and economic growth is linear

relationship. With economic growth, carbon

emission is also growing. CKC curve is a straight

line that leans toward upper right.

Table 1 Regression results of panel date.

Note: ‘*’ means the significance level is 5%.

‘**’ means the significance level is 1%.

Model 2 adds the influence of fixed assets

investment and industrial structure, regression result

shows that carbon emission and economic growth

still take on positive linear correlation. The influence

of fixed assets investment on the carbon emission

will show some continuity, therefore, in order to

solve the sequence related problems in the model,

the model evolved into the form of model 3, that is,

fixed assets investment will lag one phase before

participating in regression. The quadratic coefficient

is still not obvious at this time; the coefficient of one

term is a positive value. Further consideration of the

problem of mutual cause and effect between carbon

emission and per capita GDP, therefore, model 4

uses the date on per capita GDP which lags one

phase, the result still indicate a positive linear

relationship between the two variables. A

comprehensive analysis of these four models, the

relationship between carbon emission and economic

growth is monotone increasing; indicating that they

are linear relationship or they are in the ascending

phase of an inverted u-shaped curve with the

inflection point has not yet appeared.

In the model, the percentage of secondary

industry in explanatory variable is not significant,

mainly because when these models were established,

author used various type of primary energy

consumption to calculate carbon emission, but

carbon emission from the primary and tertiary

industries mainly occur during the production of the

products that people used, mainly because of the use

of electric energy, so carbon emission actually

happens in the secondary industry. So, industrial

structure cannot influence the carbon emission in the

prefecture level city obviously. Besides, the impact

of fixed asset investment on carbon emissions in

prefecture level cities is obviously positive and it has

a lasting influence in the future.

In summary, there is a positive linear correlation

between carbon emission in prefecture level cities

and economic growth; it can also be explained as the

inflection point of inverted u-shaped curve has not

appeared. But CKC curve means that we cannot

simply expect economic growth to the inflection

point so that the environmental quality in China can

be improved naturally, we should take the initiative

to improve the environment, improve the efficiency

of energy using, and reduce carbon emission.

3 CONCLUSIONS AND POLICY

RECOMMENDATIONS

Traditional library environmental Kuznets curve

shows that, with the growing of economy, the

carbon emission will first increase and then

decrease. Associated with economic growth, the

change of environmental quality will improve

gradually. But traditional EKC curve is according to

the experience of the developed country

industrialization, so the trend of developing

countries is not applicable. Developing countries

with the advantage of backwardness can draw

lessons from experiences and lessons in the process

of industrialization in developed countries, and take

measures to control environmental quality

management.

According to the district cities more than 20

years of data, this paper draws a conclusion that the

relationship between carbon emissions and

economic growth mainly appears a sloping straight

line, so the Kuznets Curve is not an inverted U

curve. This means that the carbon emissions control

problem and environment problem in economic

growth cannot be solved automatically. After

pollution then management way is not suitable for

our country's development present situation; we

should take active measures, reasonably control

energy consumption, and improve the efficiency of

energy utilization.

REFERENCES

1. Brajer, V.R. Mead and F. Xiao. 2011. Searching for an

Environmental Kuznets Curve in China’s Air

Pollution, China Economic Review, 22(3): 383-397.

2. Galeotti M, Lanza A, Pauli F. 2006. Reassessing the

environmental Kuznets Curve for CO2 emissions: a

robustness exercise, Ecological Economics, 57: 152-

163.

3. Harbaugh, W., A. Levinson and D. Wilson. 2002.

Reexamining the Empirical Evidence for an

Environmental Kuznets Curve, Review of Economics

and Statistics, 84(3): 541-551.

4. Jalil, A., S. F. Mahmud. 2009. Environment Kuznets

Curve for CO2 Emissions: A Co-integration Analysis

for China, Energy Policy, 37(12): 5167-5172.

5. Yang G.Y. Econometric analysis of the relationship

between carbon emission and economic growth in

Anhui province. [J] Statistics and Decision 2012, 17:

106-109.

6. Zhang B, Chen GQ. Methane emissions in China

2007, Renew Sustain Energy Rev [M] 2014, 30: 886-

901.