Journal of Resources and Ecology >
Measuring the Effect of Foreign Direct Investment on CO_{2} Emissions in Laos
Received date: 20190423
Accepted date: 20190709
Online published: 20191209
Supported by
The Strategic Priority Research Program of the Chinese Academy of Sciences(XDA20010202)
Major Project of National Social Science Foundation of China(16ZDA041)
Copyright
This paper aims to explore the determinants of CO_{2} emissions in Laos by accounting for the significant role played by foreign direct investment (FDI) in influencing CO_{2} emissions during the period 19902017. We apply a Johansen cointegration testing approach to investigate the presence of cointegration, and the empirical findings underscore the presence of a longrun cointegration relationship between CO_{2} emissions, FDI, per capita GDP, and industrial structure. We also employ an errorcorrecting model to examine the shortterm dynamic effect of FDI on CO_{2} emissions. The empirical results show that FDI has a significant shortterm dynamic effect on changes in CO_{2} emissions, indicating that the relationship between FDI and CO_{2} emissions is an inverted Ushaped curve. This is a validation of the EKC. Changes of FDI, per capita GDP, and industrial structure increase CO_{2} emissions. Based on the analysis results, this paper puts forward policy suggestions emphasizing the need for both Laotian policymakers and Chinese investors to improve ecoenvironmental quality.
XIONG Chenran , WANG Limao , YANG Chengjia , QU Qiushi , XIANG Ning . Measuring the Effect of Foreign Direct Investment on CO_{2} Emissions in Laos[J]. Journal of Resources and Ecology, 2019 , 10(6) : 685 691 . DOI: 10.5814/j.issn.1674764X.2019.06.014
Table 1 Global trends in per capita GDP, FDI, and CO_{2} emissions 
Year  Per capita GDP (US$)  Per capita FDI (US$)  Per capita CO_{2} emissions (tons) 

19811985  2493.59  12.03  4.06 
19861990  3596.67  29.28  4.20 
19911995  4674.34  38.61  4.09 
19962000  5205.36  126.37  4.08 
20012005  6023.82  126.96  4.30 
20062010  8579.57  265.76  4.75 
20112015  9984.41  415.84  4.98 
Source: World Bank, World Investment Report (19922017), Shahbaz et al. (2015) 
Table 2 Description of variables 
Variable  Symbol  Definition  Unit  Source 

Carbon emissions  CO_{2}  CO_{2} emissions from fossil fuels  Kiloton  World Bank 
Foreign direct investment  FDI  FDI inward stock  Millions of dollars  UNCTAD 
Per capita GDP  PCGDP  GDP to Population  USD  World Bank 
Industrial structure  IS  Share of industrial sectors covering GDP  %  the ASEAN Secretariat 
Next, we adopted the augmented DickeyFuller (ADF) unit root test with intercept, trend and intercept, and none to determine the stability of the variables. The results are presented in Table 4. Note that the original sequence of all variables does accept the null hypothesis and has a unit root at the 5% significance level, indicating that the sequence is nonstationary. However, after first difference, we found stationary for all variables. This rejects the null hypothesis of having a unit root at significance level within 10%, indicating that sequence is stationary at first difference. The stationary at first difference shows that a longterm equilibrium relationship exists between variables of CO_{2} emissions, FDI, PCGDP and IS time series. Therefore, we require further verification and adopt the cointegration test. 
Table 3 Descriptive statistics of variables (19902017) 
lnCO_{2}  lnFDI  lnPCGDP  lnIS  

Mean  6.777592  6.422771  6.720911  3.177491 
Median  6.927747  6.446374  6.660189  3.175600 
Maximum  7.701083  8.788746  7.461870  3.558201 
Minimun  5.359836  2.564949  6.135565  2.667228 
Std.dev.  0.747343  1.634706  0.416619  0.231562 
Skewness  0.679633  0.780247  0.261508  0.343778 
Kurtosis  2.141819  3.060081  1.825126  2.314039 
JarqueBera  3.014756  2.845212  1.929521  1.100489 
Probability  0.221490  0.241085  0.381075  0.576809 
Table 4 The results of unit root analysis (19902017) 
Variables  Type (C,T,K)  ADF value  Critical values  Test result  

1%  5%  10%  
lnCO_{2}  (C,0,0)  2.375  2.653  1.954  1.610  unstable 
lnFDI  (C,0,1)  1.010  2.657  1.954  1.609  unstable 
(lnFDI)^{2}  (C,T,1)  2.697  4.356  3.595  3.233  unstable 
lnPCGDP  (C,T,0)  2.257  4.339  3.587  3.229  unstable 
lnIS  (C,T,1)  3.084  4.356  3.595  3.233  unstable 
DlnCO_{2}  (C,0,0)  4.067  2.657  1.954  1.609  stable 
DlnFDI  (C,0,0)  1.848  2.656  1.844  1.609  stable 
D(lnFDI)^{2}  (C,T,0)  2.868  3.711  2.861  2.629  stable 
DlnPCGDP  (C,T,0)  4.364  4.356  3.595  3.233  stable 
DlnIS  (C,T,1)  4.861  4.374  3.603  3.238  stable 
Note: The type C,T,K represent constant, trend and the lag length, respectively. The optimal results are determined by consideration of AIC. The results remain valid figures in a unified manner. 
Table 5 The results of the Johansen cointegration test 
No. of Eqn(s)  Eigenvalue  Trace statistic  5% critical value  Pvalue 

None*  0.820  116.592  69.819  0.000 
At most 1*  0.688  71.994  47.856  0.000 
At most 2*  0.614  41.682  29.797  0.001 
At most 3*  0.435  16.933  15.495  0.030 
At most 4  0.077  2.077  3.841  0.150 
* Denotes rejection of the hypothesis at the 5% level 
Fig. 2 FDI inward flows in Laos by source countries, 2014 2017 (The ASEAN Secretariat, 2018). 
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