Using province-level panel data in China, we examine the relationship between traffic accidents and economic growth. A semiparametric partial linear model is used to account for potential nonlinearity in the relationship. The estimation results indicate that the relationship exhibits an inverted U-shaped pattern; traffic fatality and injury increase as provincial GDP per capita rise up to about $1500 and $4000 respectively, and decline thereafter. Unlike cross-country studies in the literature, we show that traffic fatalities in the entire China are already in a decreasing phase.Traffic Accidents, Economic Growth, China, Semiparametric Analysis

Kazuyuki Iwata

English

Research Papers in Economics

     
 
 
  
  
Volume 30, Issue 4 
  
The relationship between traffic accidents and economic growth in China 
  
 
 
Kazuyuki Iwata  
Tohoku University 
Abstract 
Using province-level panel data in China, we examine the relationship between traffic accidents and economic growth. 
A semiparametric partial linear model is used to account for potential nonlinearity in the relationship. The estimation 
results indicate that the relationship exhibits an inverted U-shaped pattern; traffic fatality and injury increase as 
provincial GDP per capita rise up to about $1500 and $4000 respectively, and decline thereafter. Unlike cross-country 
studies in the literature, we show that traffic fatalities in the entire China are already in a decreasing phase.
I am grateful to Hajime Katayama (The University of Sydney) and Makoto Sugino (Sophia University) for their helpful comments. 
Citation: Kazuyuki Iwata, (2010) ''The relationship between traffic accidents and economic growth in China'', Economics Bulletin, Vol. 30 
no.4 pp. 3306-3314. 
Submitted: Apr 15 2010.   Published: December 09, 2010. 
 
      
 
1. Introduction 
 
Under the well-known environmental Kuznets curve (EKC) hypothesis (Grossman and 
Krueger 1991), the relationship between environmental externalities and economic growth 
exhibits an inverted U-shape. That is, environmental externalities increase as the economy 
grows in countries with low income; once the economy exceeds a certain threshold, the 
externalities start declining with further development. 
The hypothesis has been tested in numerous environmental studies. Besides the field, the 
curve has been found in other fields that deal with externalities. For example, Kellenberg and 
Mobarak (2008) show that there is an inverted U-shaped relationship between damages from 
specific  types  of  natural  disasters  and  economic  levels.  Also,  Andrés  (2006)  shows  the 
presence  of  a  concave  relationship  between  piracy  and  per  capita  income.  These  studies 
exhibit  the  potential  of  applying  the  concept  of  the  EKC  hypothesis  not  only  to  the 
environmental field but also to other fields. 
We may be able to observe the curve also in traffic accident externalities. In countries with 
low income, economic growth increases number of vehicles and traffic accidents because 
people’s  marginal  utilities  for  possessing  and  using  vehicles  are  larger  than  those  for 
protecting traffic accidents. However, the magnitude relation between the marginal utilities 
turns over at a certain economic level, and then traffic accidents start declining. 
Van Beeck et al. (2000) use data from 21 industrialized countries from 1962 to 1990 and 
show that the traffic fatality rate rises until per capita Gross Domestic Product (GDP) grows 
to around $3000; after this, it begins to decrease. Kopits and Cropper (2005) use panel data 
from  1966  to  1999  for  88  countries  (including  developing  countries)  and  show  that  the 
threshold for the fatality rate is $8600. Bishai et al. (2006) conclude that the threshold of the 
traffic  fatality  rate  is  around  $1500  to  $8000,  but  that  there  is  no  inverted  U-shaped 
relationship between traffic injury rate and prosperity. Anbarci et al. (2009) indicate that the 
threshold is $11454 and provide an economic theoretical framework of the traffic fatality rate. 
Previous  literature  has  used  panel  cross-country  data  and  has  assumed  homogeneous  
 
economic growth effects on the fatality/injury rate across countries. That is, all countries are 
assumed  to  have  the  same  threshold  and  to  follow  the  same  path.  This  assumption  may 
generate a misunderstanding. For example, even though a country is already in a decreasing 
phase for traffic fatality rate, if its income level is lower than the thresholds estimated in 
previous studies, it is expected that the rate in the country increases. 
  Unlike  previous  studies,  we  focus  only  on  China  in  order  to  avoid  country-specific 
heterogeneity on the slope of per capita GDP. This note attempts to examine the relationship 
between the traffic fatality/injury rate and economic growth in China.
1   
 
2. Empirical Framework 
 
Since the beginning of the twenty-first century, China has attained a double-digit annual 
average GDP growth rate. Despite this rapid growth, the Chinese have been experiencing 
severe traffic accidents. In 1996, the number of traffic fatalities per 10000 persons (hereafter 
referred to as the traffic fatality rate) was only 0.61; this rate increased to 0.86 in 2002 and 
declined thereafter. The number of traffic injuries per 10000 persons (traffic injury rate) 
demonstrates a similar trend. 
To capture the approximate trend of the relationship between traffic fatalities/injuries and 
per capita GDP, we have plotted the numbers in Figure 1 with Chinese provincial data for 
1996 to 2008. The vertical axes in Figure 1(a) and (c) represent traffic fatality and injury rates, 
respectively. The smooth lines obtained from a Kernel-weighted local polynomial regression 
have also been added in each figure. In the nonparametric analysis, as width assumed for 
estimation is large, the shape of line is smooth. In both figures, three lines under different 
width assumptions for robustness are shown. The number of observations is 389 (= 13 years 
times 30 provinces minus 1 missing value).
  2 
                                                   
1  Using Chinese provincial data for 1992 to 2003, Kaneko et al. (2009) reveals there is an inverted U-shape between income 
and environmental quality in China. 
2  The 30 provinces in this paper consist of 22 provinces, four autonomous regions and four government-ruled cities. Note 
that we exclude Tibet from the analysis owing to a missing value.  
 
To clearly see the shapes of the lines, we have inserted Figure 1(b) and (d) on the right 
without the observations in the figures on the left. The concave features are observed in each 
line. The peaks for both rates seem to be at around $5000. 
 
Figure 1. Nonparametric estimation result on per capita GDP (Left: with observations. 
Right: without observations) 
     
   
 
However,  the  estimator  in  the  nonparametric  analysis  does  not  isolate  the  provincial 
unobserved fixed effects from the error term. In addition, the provincial characteristics other 
than GDP are not controlled. To tackle this issue, we consider the semiparametric model as 
follows: 
 
Tit = f(GDPit) + δLHit + µi + εit, 
 
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witdh = 1500 
 
where Tit is the traffic fatality/injury rate in province i in year t. GDP and LH denote per 
capita GDP and length of highway per 10000 persons, respectively. The function of per capita 
GDP, f, is not linear but is an unspecified smooth. The coefficient δ is linear parametric. µ and 
ε are provincial fixed effects and an independent identically distributed error term with mean 
zero, respectively. 
Governments  expand  road  infrastructure  as  a  countermeasure  to  traffic  issues  like  car 
crashes and congestion (Forkenbrock and Foster 1990). To control the influence of roads on 
the fatality/injury rate, we have incorporated LH. Though some may claim that the correlation 
between per capita length of road and GDP is large, it is only 0.03 in our data.   
 
3. Estimation Results 
 
All data in this note are collected from the Chinese Statistical Yearbook, which is published 
by the National Bureau of Statistics of China.
  3  The estimated smooth lines of per capita 
GDP by partial linear regression are shown in Figure 2. Figure 2(a) to (d) correspond to the 
similarly labeled figures in Figure 1. Other coefficients are shown in Table 1.   
We can easily recognize the inverted U-shaped patterns in Figure 2. The thresholds for the 
fatality and injury rates are around $1500 and $4000, respectively, which are smaller than the 
values of the nonparametric analysis. Hence, upward biases on the thresholds are generated 
unless we control the provincial fixed effects and length of highway. Patterns between the 
fatality rate and economic growth may be different among countries because our peaks are 
smaller than those of the previous studies and the difference of the peaks may be generated 
from country heterogeneous relationship between the accident and growth. 
The null hypothesis that GDP does not have effect on T is rejected at the 1% significant 
level.  The  coefficients  of  road  infrastructure  on  fatality  and  injury  rates  are  significantly 
negative. This shows governments can mitigate traffic casualty by increasing the length of 
highways. 
                                                   
3  The statistics are available at http://www.stats.gov.cn/english/statisticaldata/.  
 
Additionally, we restrict the unspecified function f to the quadratic linear. The result under 
the constraint is also presented in Figure 2 and Table 1. Even with the restriction, inverted-U 
shape  is  observed.  The  thresholds  are  $1383  and  $3710  for  fatality  and  injury  rates, 
respectively.   
An incorrect conclusion, however, may be obtained if we introduce the quadratic form 
assumption. Using mean squared errors, the specification tests on the semiparametric and 
quadratic estimators significantly indicate that the former is appropriate. It is also remarkable 
that the former can capture surge of fatality rate until the peak, unlike the later. This comes 
from the asymmetric form of per capita GDP on the rate. 
 
Figure 2. Estimation results on per capita GDP (Left: with observations. Right: without 
observations) 
   
   
Notes: The quadratic line is derived under the constraint that other explanatory variables are 
fixed at sample means. 
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Quadratic Semiparametric
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Table 1. Estimation results of semiparametric and quadratic regressions 
Dependent Variables
Explanatory Variables Coefficient Coefficient Coefficient Coefficient
per capita GDP 0.000013 0.001135 ***
(0.000023) (0.000207)
squared per capita GDP -4.52E-09 * -1.53E-07 ***
(2.49-E09) (2.23-E08)
Length of Highway -0.003845 ** -0.001064 -0.046844 *** -0.021118 *
(0.001576) (0.001246) (0.014575) (0.011147)
Adj. R-square 0.804 0.770 0.583 0.608
F-value 53.97 *** 41.58 *** 19.09 *** 19.83 ***
mean squared error 0.191 0.222 1.633 1.785
significance of GDP 3.97 *** 4.85 ***
specification test 3.20 *** 1.84 **
threshold about $1500 $1383 about $4000 $3710
Traffic Fatality Rate Traffic Injury Rate
Quadratic Semiparametric Semiparametric Quadratic
 
Notes: All estimations include provincial fixed effects. The values in parenthesis represent 
standard deviations. ***, ** and * indicate significant level at 1%, 5% and 10%, respectively. 
 
Furthermore, we aggregate the provincial predicted fatality and injury rates from the partial 
linear regression into country levels. The aggregated rates and entire per capita GDP from 
1996 to 2008 are depicted in Figure 3. The left and right vertical axes indicate traffic fatality 
and injury rate, respectively. 
    It is concluded that traffic fatality in China is already in a decreasing phase because the 
Chinese fatality rate increased until 2005, and  declined thereafter.
  4  In  contrast, China is 
about to face downward phase for traffic injury as the peak for injury rate is 2007, whereas 
the 2007 and 2008 rates are not far from each other.   
 
Figure 3. Relationship between per capita GDP and traffic fatality/injury rate in entire 
China 
                                                   
4  Per capita GDP in 2005 is about $1883.  
 
 
Notes:  The  data  of  Guizhou  province  in  1996  is  dropped  in  the  calculation  because  we 
employ partial linear regression and Guinzhou’s values for the rates are smallest in our data. 
 
    Our results show two implications. First, when we examine the relationship between traffic 
fatality/injury rate and economic growth, it is preferable to allow flexible functional form 
because function of the relationship may be asymmetric. This suggestion is similar to that of 
Kopits and Cropper (2005), which use spline function. Second, it is important to consider 
country  specific  heterogeneous  effect  of  income  on  the  traffic  accidents.  If  the  Chinese 
government makes policies against traffic accidents with the facts from previous studies, they 
may fail to choose proper policies. 
 
4. Conclusion 
 
Using  Chinese  provincial  data  for  1996  to  2008,  this  note  examines  whether  the 
fatality-/injury-income relationship is inverted-U shaped, similar to the EKC. We employ the 
semiparametric  partial  linear  model  in  order  to  observe  the  flexible  relationship.  The 
estimation results show that the peaks for traffic fatality and injury in China are $1500 and 
$4000,  respectively.  Unlike  previous  cross-country  studies,  it  is  concluded  that  China  is 
already and about in decreasing phases for traffic fatality and injury, respectively. 
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References 
 
Andrés, A. R. (2006) “The Relationship between Copyright Software Protection and Piracy: 
Evidence from Europe” European Journal of Law and Economics 21, 29-51. 
Anbarci,  N.,  Escaleras,  M.  and  Register,  C.  A.  (2009)  “Traffic  Fatalities:  Does  Income 
Inequality Create an Externality?” Canadian Journal of Economics 42, 244-266. 
Bishai,  D.,  Quresh,  A.,  James,  P.  and  Ghaffar,  A.  (2006)  “National  road  casualties  and 
economic development” Health Economics 15, 65-81. 
Forkenbrock, D. J. and Foster N. S. J.    (1990) “Economic benefits of a corridor highway 
investment” Transportation Research Part A 24, 303-312. 
Grossman, G. M. and Krueger, A. B. (1991) “Environmental impacts of a North American 
Free Trade Agreement” NBER working paper number W3914. 
Kaneko, S., Managi, S., Fujii, H. and Tsurumi, T. (2009) “Does an Environmental Kuznets 
Curve for Waste Pollution Exist in China?” International Journal of Global Environmental 
Issues 9, 4-19. 
Kellenberg, D. K. and Mobarak, A. M. (2009) “Does rising income increase or decrease 
damage risk from natural disasters?” Journal of Urban Economics 63, 788-802. 
Kopits, E. and Cropper, M. (2005) “Traffic fatalities and economic growth” Accident Analysis 
and Prevention 37, 169-178. 
van Beeck,E. F., Borsboom, G. JJ. And Mackenbach, J. P. (2000) “Economic development 
and traffic accident mortality in the industrialized world, 1962-1990” International Journal 
of Epidemiology 29, 503-509. 

Does an Environmental Kuznets Curve for Waste Pollution Exist in China?”

Does rising income increase or decrease damage risk from natural disasters?”

Economic benefits of a corridor highway investment”

Economic development and traffic accident mortality in the industrialized world, 1962-1990”

Environmental impacts of a North American Free Trade Agreement” NBER working paper number W3914.

National road casualties and economic development”

The Relationship between Copyright Software Protection and Piracy: Evidence from

Traffic fatalities and economic growth”

Traffic Fatalities: Does Income Inequality Create an Externality?”

The relationship between traffic accidents and economic growth in China

http://www.accessecon.com/Pubs/EB/2010/Volume30/EB-10-V30-I4-P305.pdf

The relationship between traffic accidents and economic growth in China

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