Using our random effect model, we have obtained the following results (Table 2), and energy efficiency has a negative influence on per capita CO2 emissions and it is one of the most important factors to reduce CO2 pollutions. Thus, an increase in energy efficiency by 100 USD per 1 ton of oil decreases per capita CO2 emissions from 17 to 64 kg. per capita (Models 1, 3). It means that the more energy efficient the economy becomes, the less CO2 emissions per capita it produces. Thus, energy efficiency improvement is a powerful driver for environmentally friendly changes in post-communist economies. This conclusion is also confirmed by other theoretical and empirical studies (Chiu 2017; Liobikiene et al. 2016; Nepal et al. 2017).
Table 2. The random-effects general least square regression of CO2 emissions (metric tons per capita) for the panel of 10 countries during the 1996-2018
|
CO2 emissions (metric tons per capita)
|
VARIABLES
|
Model 1
|
Model 2
|
Model 3
|
Model 4
|
Life expectancy
|
0.203***
(0.0456)
|
0.374***
(0.0958)
|
0.241***
(0.0450)
|
0.280***
(0.0419)
|
GDP per unit of energy (USD per 1 ton of oil)
|
-0.00064**
(0.000247)
|
|
-0.000176**
(6.91e-05)
|
-0.00021***
(6.22e-05)
|
Forest area (percent)
|
-0.0842***
(0.00636)
|
-0.0296***
(0.0108)
|
-0.0903***
(0.00589)
|
-0.0919***
(0.00538)
|
Energy consumption
(toe) per capita
|
2.849***
(0.131)
|
|
3.019***
(0.114)
|
3.073***
(0.106)
|
Agriculture, forestry,
and fishing (% of GDP)
|
-0.134***
(0.0182)
|
-0.202***
(0.0301)
|
-0.0999***
(0.0155)
|
-0.0677***
(0.0144)
|
GDP per capita (USD)
|
|
0.00026***
(4.80e-05)
|
|
|
Industry (including construction) (% of GDP)
|
0.0373**
(0.0165)
|
0.110***
(0.0336)
|
0.0378**
(0.0169)
|
0.0692***
(0.0161)
|
Exports of goods and services
(% of GDP)
|
-0.0401***
(0.00421)
|
-0.0402***
(0.00878)
|
-0.0395***
(0.00405)
|
|
GDP per unit of energy squared (USD per 1 ton)
|
5.35e-08*
(2.89e-08)
|
|
|
|
Mobile cellular subscriptions (per 100 people)
|
-0.00650*
(0.00379)
|
0.0210***
(0.00697)
|
-0.0105***
(0.00365)
|
-0.00839***
(0.00325)
|
FDI per capita
|
-1.36e-05
(5.99e-05)
|
6.90e-06
(0.000124)
|
-1.33e-05
(6.12e-05)
|
|
Merchandise trade
(% of GDP)
|
|
|
|
-0.0239***
(0.00205)
|
Gross fixed capital formation
(% of GDP)
|
|
|
|
-0.0553***
(0.0141)
|
EU
|
1.082***
(0.410)
|
-5.499***
(0.573)
|
0.721
(0.377)
|
1.318***
(0.355)
|
Oil price ($/bbl)
|
0.00627
(0.0142)
|
-0.159***
(0.0252)
|
0.0124
(0.0143)
|
0.0127
(0.0130)
|
Population growth (annual %)
|
0.365***
(0.112)
|
|
|
|
y1997
|
0.221
(0.370)
|
0.216
(0.371)
|
0.212
(0.370)
|
0.232
(0.340)
|
Rest time year dummies 1998-2017
|
y2018
|
-0.142
(0.414)
|
-0.171
(0.413)
|
-0.105
(0.411)
|
-0.216
(0.379)
|
Constant
|
-14.17***
(2.870)
|
--11.03*
(6.475)
|
-14.14***
(2.866)
|
-17.32***
(2.665)
|
Observations
|
230
|
230
|
230
|
230
|
Number of id
|
10
|
10
|
10
|
10
|
Standard errors in parentheses, *** p<0.01, ** p<0.05, * p<0.1
Similar to the previous factor, GDP per capita plays a significant role for per capita CO2 emissions. However, unlike energy efficiency, per capita GDP growth has a positive effect: an increase in GDP per capita by 1000 USD per capita increases CO2 emissions 260 kilograms per capita. The richer the economy becomes, the more CO2 emissions per capita it generates. All these activities increase energy consumption and cause higher levels of CO2 emissions. These results are similar to such studies (Chiu 2017; Kasman & Duman 2015; Nepal et al. 2017; Sharma 2011; Melnyk et al. 2013).
The increase in life expectancy by one year lead on average to increase in CO2 emissions per capita 200 to 370 kilograms per capita, with average values of 260 kilograms per capita. Thus, it is not the life expectancy itself that increase in CO2 emissions per capita, it is the way of life which is more common to more developed economies (e.g. elderly people may have more traveling during retirements).
Countries with larger forest area (percentage of territory) tend to have smaller CO2 emissions per capita. The last is rather policy appealing results, since countries with smaller forest area (percentage of territory) don’t have reasonable instruments to compensate the CO2 emissions.
Energy consumption (toe) per capita is a factor that positively adds to the CO2 emissions per capita, and in a group of selected economics one additional ton of energy consumption in terms oil equivalent lead to the 3 tons increase in carbon dioxide.
It is appeared to be that structure of the economy has a significant influence on carbon dioxide emissions. Thus, industrial share growth (% of GDP) increase the CO2 emissions per capita, while the growth of agriculture, forestry, and fishing (% of GDP) reduses it. It was found that an incrase in agriculture, forestry, and fishing sector by one percentage lead to the decrease of CO2 emissions per capita from 67 to 200 kg per capita. While an increase in industrial share sector by one percentage lead to the increase of CO2 emissions per capita from 37 to 110 kg per capita.
Exports of goods and services (% of GDP) incrae by one percentage leads to the decrease of CO2 emissions per capita by 40 kg per capita.
Mobile cellular subscriptions (per 100 people) is an indicator of digital economy and an increase in Mobile cellular subscriptions by 10 person per 100 people) leads to decrease of CO2 emissions from 37 to 110 kg per capita
The next factor influencing CO2 emissions is EU energy policy, and countries that became members of EU are characterized by lower CO2 emissions, as stated by model 2. However the first and third model show the other results, and more of research have to be done in this direction, comparing the whole set of EU states with not EU ones.
Results in Table 2 show a insignificant influence of gas and oil prices on CO2 p.c. emissions. This outcome can be explained that world energy prices did not have any influence on selected countries (Carvalho 2016; Nepal et al. 2017; Sineviciene et al., 2017).
Foreign direct investment is another statistically insignificant factor for CO2 emissions in our model. The reason is its dual effect on those emissions. On the one hand, investment in a national economy is responsible for faster economic growth and, as a rule, for an increase in fossil fuels consumption that causes an increase in CO2 emissions. On the other hand, investment in energy efficiency, development of environmentally friendly technologies and service sector expansion may significantly contribute to a reduction in per capita CO2 emissions. Those are two mutually exclusive trends affecting the dynamics of CO2 p.c. emissions. The dominance of one of these tendencies at a particular stage of development determines the direction of impact on CO2 emissions. These results are in accordance with other papers (Nepal et al. 2017; Omri et al. 2014; Melnyk et al. 2014). However, the survey by Bae J.H. et al. (2016) on post-Soviet Union independent states proves a positive influence of foreign direct investment on CO2 emissions.
The incresse in polulation for the panel of 10 countries has no positive impact on the decarbonization of national economies. Its multidirectional influence on CO2 emissions can explain this result as it had been discussed in the Methodology and data section, which is consistent with other studies (Lin et al. 2016; Martínez-Zarzoso & Maruotti 2011).
To sum up, the obtained results support the majority of hypotheses concerning the influence of various factors on CO2 emissions in pre-selected post-communist countries. Among confirmed hypotheses are:
1) The positive impact from GDP p.c., share of industry (including construction) (% of GDP), life expectancy and population growth on per capita CO2 emissions;
2) Negative impact from energy efficiency, share of agriculture, forestry, fishing (% of GDP), progress in digital economy (Mobile cellular subscriptions) on p. c. CO2 emissions;
3) The ambiguous impact from FDI as well as Oil prices, EU energy policy access, on per capita CO2 emissions. Contrary to other views, our study shows the insignificant influence of these factors on CO2 emissions due to their ambiguous consequences.