Vietnam and China both are quickly emerging market economies in Asia. China has had an unprecedented economic growth in Asia for the past 30 years. Also, Vietnam’s GDP is increasing, but more slowly. However, Vietnam is starting to catch up. Against this background, this article assesses the question what the economic and environmental impacts in Vietnam would be, if the country followed China’s development path. Based on econometric analysis, it is shown that currently, Vietnam is lagging behind China in terms of economic growth for 11 years. Although Vietnam and China have a similar primary energy mix in the early 1980s, China is still massively relying on coal, whereas Vietnam starts to develop hydro power in the late 1980s on large scale. Due to a quick growth of per-capita income, per capita emissions in China are already catching up with those of North-European economies such as Denmark, Finland and Germany. The question arises, what if Vietnam followed China’s development path. Using econometric models of GDP and CO 2-emissions, two scenarios for Vietnam are analyzed, a scenario following China’s development path and one alternative scenario pursuing the current development patterns until 2050. The results show that the additional impact of following China’s economic development path is minor. Vietnam would only have a 0.5% percentage point per annum higher GDP growth. In other words, Vietnam would grow relatively quickly anyway. However, following China’s development path also in terms of high CO 2-emissions per capita, would increase the growth of CO 2-emissions in Vietnam by 2.3 percentage points per annum and would lead to an increase of CO 2-emissions in 2050 by 2.6 bn. tons compared with the scenario in which Vietnam sticks to its own development patterns. However, in that case, Vietnam also had a 25% lower per capita income compared with the scenario following China’s development path. Here, the people and government in Vietnam have to make a strategic choice.
Vietnam and China are quickly growing and emerging market economies with increasing economic welfare in terms of growing disposable per-capita income [
Starting from a comparable per capita GDP level, since the late 1980s, China’s development has been much quicker than that of Vietnam. Between 1980 and 2013, China’s GDP per capita grew by 11.8%, Vietnam only by 7.8% [
Currently, the question, however, is open, whether Vietnam should follow China’s development path or continue its own way of development. This article is focusing on this issue and assesses the empirical difference of the development paths of the two countries and which economic and environmental implications it would have, if Vietnam followed China’s development patterns in the future. In order to answer these questions, an econometric analysis of Vietnam’s and China’s development paths is undertaken (Section 2), analyzing how many years Vietnam is lagging behind China economically. Based on the results of this ana- lysis, a forecast of Vietnam’s GDP, CO2-emissions and CO2-intensities per capita and GDP is made until 2050, if Vietnam followed China’s development path compared with a scenario with autonomous economic development patterns (Section 3). A summary (Section 4) concludes the article.
Since the 1960s, sequential regional economic development in Asia is being observed and described as a “flying geese formation” phenomenon of one or more countries following others ( [
Assessing Vietnam’s economic development relative to that in China,
In order to assess, how many years Vietnam is lagging behind China in terms of its economic development, a simple regression of GDP per capita in Vietnam (GDP_POP_VNt) on GDP per capita in China (GDP_POP_CHt−n) for different time lags (Ln = t − n) is performed using an ordinary least squares (OLS) estimator. Applying this model, it will be assessed which time lag of per-capita GDP
in China fits to the current time series of per-capita GDP in Vietnam between 1993 and 2013. A simple assessment, when the two countries had the same per-capita GDP does not take into account the deviations in the development paths over time. Thus, the logarithmic model employed here is:
In the model, εt represents the error term and C a constant. Before being able to run the model, however, the question of stationarity of the two time series has to be addressed. Estimating OLS including variables which follow a random walk may yield spurious results, i.e. the regressions present a relationship between these variables which in reality does not exist [
Spurious regressions will also not result, if there is a stable-long-term economic relationship between the two variables, or in other words, if the linear combination of the two variables is co-integrated [
In order to assess how many years Vietnam is lagging behind China in terms of its economic development patterns, the Model 1 above is run for of ln(GD- P_POP_VNt) and different lags (n = 0 - 13) of ln(GDP_POP_CHt−n).
Hence, following China’s development path would mean that Vietnam in the next year (t) would have the same growth patterns of GDP per capita as China had (t − 11) years ago.
Compared to China, Vietnam’s current GDP is less CO2-intensive (2013: Vietnam 0.3 t/1000 US$ PPP; China 0.6 t/1000 US$ PPP. Both countries, especially
ADF-Test | Integration order | Significance level |
---|---|---|
log(gdp_pop_vn) | I (1) | 5% |
log(gdp_pop_ch) | I (1) | 1% |
log(gdp_pop_ch(−1)) | I (1) | 1% |
log(gdp_pop_ch(−2)) | I (1) | 1% |
log(gdp_pop_ch(−3)) | I(1) | 5% |
log(gdp_pop_ch(−4)) | I (1) | 1% |
log(gdp_pop_ch(−5)) | I (1) | 5% |
log(gdp_pop_ch(−6)) | I (1) | 5% |
log(gdp_pop_ch(−7)) | I (1) | 5% |
log(gdp_pop_ch(−8)) | I (1) | 5% |
log(gdp_pop_ch(−9)) | I (1) | 1% |
log(gdp_pop_ch(−10)) | I (1) | 1% |
log(gdp_pop_ch(−11)) | I (1) | 1% |
log(gdp_pop_ch(−12)) | I (1) | 5% |
log(gdp_pop_ch(−13)) | I (1) | 5% |
Source: Own calculations based on data from [
China, reduced their CO2-intensity of GDP considerably and both intensities are converging (
Looking at the sect oral structure of GDP in China and Vietnam [
Vietnam’s industry is more light-industry driven (food processing, garments, shoes, mobile phones etc.) [
Variable | Coefficient estimates | t-Values |
---|---|---|
ln(GDP_POP_CHt−11) | 7.711098** | 2002.489 |
C | 0.688950** | 132.1147 |
adj. R2: 0.99; DW: 0.90, ** denotes significance at the 1% level. |
Sector | China | Vietnam |
---|---|---|
Agriculture | 10.0% | 18.4% |
Industry | 43.9% | 38.3% |
Services | 46.1% | 43.3% |
Source: [
To understand China’s high CO2-intensity of GDP compared to Vietnam does not only include to analyze energy intensity of GDP as discussed above, but also CO2-intensity of primary energy supply (
Since 1989, Vietnam massively invested into hydro energy, especially in the mountainous northern part of the country. With increasing per-capita income, oil demand for transportation purposes grew. In 2013, in China carbon-intensive coal still took about 67% of primary energy supply. In Vietnam, coal nowadays only represents less than 30% of total primary supply. Vietnam uses much more hydro energy for power generation than China (
In 2013, in Vietnam, the share of zero-carbon intensive hydro energy in total primary energy supply was 22.5%, much more compared to 7.2% in China. The share of oil and gas, which are less carbon intensive than coal, is also much higher in Vietnam (oil: 32.1%, gas: 16.1%) compared to China (oil: 18.2%, gas: 5.1%). The high share of gas in Vietnam is even more astonishing as it has only started to be used large scale since 2010.
Due to China’s one-child-policy introduced in the late 1970s [
Primary energy source | Vietnam | China | ||
---|---|---|---|---|
Mtsce | % | Mtsce | % | |
Coal | 22.7 | 29.2 | 2762 | 67.1 |
Oil | 24.9 | 32.1 | 750 | 18.2 |
Gas | 12.5 | 16.1 | 211 | 5.1 |
Nuclear | 0.0 | 0.0 | 36 | 0.9 |
Hydro | 17.5 | 22.5 | 295 | 7.2 |
Bio-fuels | 0.0 | 0.0 | 2 | 0.1 |
Other renewables | 0.0 | 0.1 | 61.3 | 1.5 |
Total | 77.7 | 100.0 | 4117 | 100.0 |
Source: [
than in Vietnam (1.6%) during the same period of time. By the end of 2013, China had a population of 1.4 billion people, Vietnam had 91 million inhabitants [
Translated into CO2-emissions per capita, in 2013, Vietnam accounted for 1.5 t CO2 per inhabitant, China (7.3 t) for over four times more (
Forecasting Vietnam’s GDP following China’s development path until 2050, the estimated results of GDP per capita (Model 1) are multiplied with population (POP_VNt). For China, a GDP growth rate of 7% p.a. is assumed for 2014-2020, 6% p.a. for 2021-2030, 5% p.a. for 2031-2040 and 4% p.a. for 2041-2050. This
development is compared to a business-as-usual path in Vietnam with an autonomous GDP growth without following China’s development patterns. To re- present this autonomous growth path of GDP, the following model of Vietnam’s GDP is applied (Equation (2)):
GDP_VN_NOTt is Vietnam’s GDP at a given time t, INVEST_VNt is the share of investments in total GDP and εt is the error term. GDP_VN_NOTt−1 represents the inertia in GDP development as based on long-term investment cycles, the macro-economic capital stock does not change completely from year to year [
The estimates of the logarithmic lagged GDP (ln(GDP_VN_NOTt−1)) is significant at the 1% level, the logarithmic share of investments (ln(INVEST_VNt)) is significant at the 5% level. All variables are stationary or integrated of order 0 [I (0)] on the 10% level.
Variable | Coefficient estimates | t-Values |
---|---|---|
ln(GDP_VN_NOTt−1) | 1.004888*** | 154.1402 |
ln(INVEST_VNt) | 0.020889** | 2.093097 |
adj. R2: 0.99; DW: 0.35, *** denotes significance at the 1% level, ** at the 5% level, respectively. |
2015 | 2020 | 2025 | 2030 | 2035 | 2040 | 2045 | 2050 | Annual growth rate (%) | |
---|---|---|---|---|---|---|---|---|---|
GDP_VNt | 616 | 1136 | 1784 | 2488 | 3361 | 4515 | 5852 | 7516 | 7, 4 |
GDP_VN_NOTt | 547 | 776 | 1091 | 1091 | 1525 | 2123 | 4083 | 5648 | 6, 9 |
Source: Own calculations based on data from [
Estimating and forecasting primary energy, based on the exogenous resp. retrieved GDP per capita paths (GDP_VNt/POP_VNt resp. GDP_VN_NOTt, /PO- P_VNt), the lagged primary energy supply PES_VN_(NOT)t−1, a linear technological trend T, Dummy variables DOIMOI, D104 and D108 for atypical impact factors in the years 2004 and 2008, a constant (C) and the error term εt, the following model is applied (Equation (3), resp. (3a)):
Assessing the stationarity of the time series mentioned above reveals that PE- S_VNt and PES_VN_NOTt are both integrated of the Order 1 I (1) on the 1% level. PES_VNt/POP_VNt, PES_VN_NOTt/POP_VNt and CO2_VN_NOTt are all integrated of the Order 1 (I (1)) on the 5% level. Co-integration analysis shows that although the exogenous variables are non-stationary, the residuals of their linear combinations (Models 3, 3a and 4) are stationary. Thus, the model variables are co-integrated.
The coefficient estimates for GDP per capita, the lagged primary energy supply and the Dummy variable for the year 2004 are significant on the 1% level; the coefficient for the technological trend is significant on the 5% level. All variables are expressed as logarithmic values.
Vietnam’s CO2-emissions following China’s development path (CO2_VNt) are calculated by multiplying Vietnam’s per-capita emissions (CO2_POP_VNt) with its population (POP_VNt):
Vietnam’s per-capita emissions of CO2 are estimated by the following logarithmic model (Equation (5)):
GDP_VN_NOTt/POP_VNt is GDP per capita following China’s development path, DOIMOIt is a dummy variable being 0 for the years before the economic reforms in 1986 (Doimoi) and 1 taking into account potential increases of per capita income in the post-reform period. εt is the error term.
The coefficient estimates for the logarithmic GDP per capita and the dummy variable are all significant on the 1% level. GDP per capita is integrated of the order 1 (I (1)) on the 1% level.
Vietnam’s CO2-emissions (CO2_VN_NOTt) are estimated and forecasted in the following logarithmic model (Equation (4)):
GDP_VN_NOTt/POP_VNt is GDP per capita not taking China’s development path, DOIMOIt is a dummy variable being 0 for the years before the economic reforms in 1986 (Doimoi) and 1 taking into account potential increases of per capita income in the post-reform period. εt is the error term.
Variable | Coefficient estimates | t-Values |
---|---|---|
ln(GDP_VN_(NOT)t/POP_VNt) | 0.082394*** | 3.305562 |
ln(PES_VN_(NOT)t−1) | 0.938683*** | 3.305562 |
Log(Tt) | 0.026446** | 2.253827 |
D104t | 0.171312*** | 5.156001 |
adj. R2: 0.99; DW: 2.31. *** denotes significance at the 1% level, ** significance on the 5% level and * significance on the 10% level respectively. |
Variable | Coefficient estimates | t-Values |
---|---|---|
LOG(GDP_VN/POP_VN) | 0.538914*** | 8.802027 |
DOIMOI | −0.719350*** | −12.29030 |
adj. R2: 0.82; DW: 0.35. *** denotes significance at the 1% level. |
The coefficient estimates for the logarithmic GDP per capita, the dummy variable DOIMOI and the constant are all significant on the 1% level. All variables are integrated of the order 1 (I (1)) on the 1% level.
Primary energy supply and CO2-emissions in China are modelled in a similar way employing the following logarithmic functions:
PES_CHt is the primary energy supply in China at a given time t, C is a constant, GDP_CHt the Chinese GDP in purchasing power parities, POP_CHt the population, TEMPA_CHt are representing temperature anomalies in China in a given year compared to the average of 1970-1999 as calculated in the UNDP Climate Change Country Profiles [
The coefficient estimates for GDP per capita (ln(GDP_CHt/POP_CHt)) and the constant (C) are all significant on the 1%, the coefficient estimates for the temperature anomaly (TEMP_CH) is significant on the 10% level, the coefficients of
Variable | Coefficient estimates | t−Values |
---|---|---|
C | 4.004558*** | 45.25037 |
ln(GDP_VN_NOTt/POP_VNt) | 0.681714*** | 11.20636 |
DOIMOIt | −0.476986*** | −4.062471 |
adj. R2: 0.82; DW: 0.35. *** denotes significance at the 1% level. |
Variable | Coefficient estimates | t-Values |
---|---|---|
ln (GDP_CHt/POP_CHt) | 0.559628*** | 33.45186 |
TEMPA_CHt | −0.057354* | −1.726528 |
D100t | −0.221263** | −2.603360 |
D101t | −0.188529** | −2.380397 |
C | 6.888359*** | 422.5090 |
adj. R2: 0.99; DW: 0.46. *** denotes significance at the 1% level, ** significance on the 5% level, * significance on the 10% level. |
the dummy variables D100 and D101 are significant on the 5% level. An increase of average temperature as signaled by the development of the temperature anomalies leads to a reduction of heating energy demand in China. The variables employed in the primary energy demand model (Model 7) are co-integrated as the residual of the co-integration function is stationary.
The coefficient estimates for the GDP per capita in China (GDP_CHt/PO- P_CHt), the lagged CO2-emissions (CO2_CHt−1) and the dummy variable for the year 2000 (D100t) are significant on the 1% level, the coefficients for the temperature anomaly (TEMPA_CHt) and the dummy variable for 2001(D101t) are significant at the 5% level. The linear combination of the variables employed in the CO2-emission model (Model 6) is co-integrated as the residual of the co-inte- gration function is stationary.
Using the Models 1 - 6 to forecast GDP per capita, primary energy supply, CO2-emissions, CO2-emissions per capita and per GDP as well as CO2-intensity of primary energy supply in Vietnam and China,
Econometric analysis indicates that CO2-emissions (−2.3 percentage points), CO2-emissions per capita (−2.3 percentage points), CO2-emissions per GDP (−0.2 percentage points) and CO2-intensity of primary energy supply (−1.6 percentage points) are considerably lower, if Vietnam does not follow China’s development path. In 2050, CO2-emissions per GDP would even be lower than 2015.
Based on these results, Vietnam is able to choose for a considerable environmental advantage of saving about 2.6 billion t of CO2 in 2050 compared to following China’s development path, but to the cost of about 19,000 US$ PPP or a 25% lower per capita income compared to a China-like economic growth (72,298 US$ PPP). Finally to decide which path to pursue is the task of the Vietnamese people and government.
Variable | Coefficient estimates | t-Values |
---|---|---|
ln(GDP_CHt/POP_CHt) | 0.124254*** | 3.054925 |
ln(CO2_CHt−1) | 0.801008*** | 10.33984 |
TEMPA_CHt | −0.036435** | −2.485593 |
D100t | −0.101756*** | −2.596669 |
D101t | −0.079399** | −2.145220 |
C | 1.600703*** | 2.657431 |
adj. R2: 0.99; DW: 1.15. *** denotes significance at the 1% level, ** at the 5% level respectively. |
2015 | 2020 | 2025 | 2030 | 2035 | 2040 | 2045 | 2050 | Annual growth rate (%) | |
---|---|---|---|---|---|---|---|---|---|
Following China’s development path | |||||||||
Population (Mill.) | 616 | 1136 | 1784 | 2488 | 3361 | 4515 | 5852 | 7516 | 7.4 |
GDP per capita (US$ PPP) | 92 | 96 | 99 | 101 | 103 | 104 | 104 | 104 | 0.3 |
Primary energy supply (Mtsce) | 6662 | 11,785 | 17,963 | 24,518 | 32,620 | 43,391 | 56,057 | 72,298 | 7.0 |
CO2-emissions (Mt) | 105 | 211 | 343 | 485 | 661 | 894 | 1175 | 1532 | 8.0 |
CO2-emissions per capita (t) | 207 | 463 | 790 | 1148 | 1601 | 2212 | 2927 | 3826 | 8.7 |
CO2-emissions per GDP (t/1000 US$ PPP) | 2.2 | 4.8 | 8.0 | 11.3 | 15.5 | 21.3 | 28.0 | 36.8 | 8.3 |
CO2-intensity of primary energy supply (t CO2/t PES) | 2.0 | 2.2 | 2.3 | 2.4 | 2.4 | 2.5 | 2.5 | 2.5 | 0.7 |
Not following China’s development path | |||||||||
Population (Mill.) | 547 | 776 | 1091 | 1525 | 2123 | 2947 | 4083 | 5648 | 6.9 |
GDP per capita (US$ PPP) | 92 | 96 | 99 | 101 | 103 | 104 | 104 | 104 | 0.3 |
Primary energy supply (Mtsce) | 5922 | 8052 | 10,981 | 15,025 | 20,603 | 28,324 | 39,108 | 54,326 | 6.5 |
CO2-emissions (Mt) | 91 | 132 | 191 | 274 | 391 | 556 | 789 | 1120 | 7.4 |
CO2-emissions per capita (t) | 143 | 191 | 258 | 351 | 479 | 655 | 902 | 1250 | 6.4 |
CO2-emissions per GDP (t/1000 US$ PPP) | 1.5 | 2.0 | 2.6 | 3.5 | 4.6 | 6.3 | 8.6 | 12.0 | 6.0 |
CO2-intensity of primary energy supply (t CO2/t PES) | 1.6 | 1.4 | 1.4 | 1.3 | 1.2 | 1.2 | 1.1 | 1.1 | −0.9 |
Source: Own calculations based on data from [
Vietnam and China are emerging economies in Asia with a tremendous economic growth and subsequent increase of economic welfare in terms of GDP per capita. Between 1980 and 2013, in China, GDP per capita grew by 11.8% p.a., in Vietnam more slowly by 7.8% p.a. Observing this development, the question arises, what if Vietnam followed China’s development path? Regressing Vietnam’s GDP per capita on China’s GDP per capita for different time lags shows that Vietnam is lagging behind China for 11 years. Hence, following China’s development path would mean that Vietnam in the next year would have the same growth patterns of GDP per capita as China had 11 years ago. Although the two time series of GDP per capita in Vietnam and China both are non-stationary, the linear combination of the time series in the GDP per capita model is co-inte- grated. Hence, OLS estimators can be used without producing spurious results.
Comparing CO2-intensity of GDP in Vietnam and China shows that China’s CO2-intensity is higher than Vietnam’s due to a higher share of (carbon-intensive) industry such as iron and steel, cement or aluminum. However, China realizes considerable gains in energy efficiency so that the intensities in China and Vietnam are converging. The comparatively high CO2-intensity of GDP in China, however, is also due to its high share of coal in primary energy supply. In China, the share of coal is still about 70%, in Vietnam only about 30%. Since the late 1980s, Vietnam developed zero carbon hydro power on large scale to produce clean electricity. Due to China’s one-child-policy since the late 1970s, between 1980 and 2013, population in China only grew by 1.1% p.a. In Vietnam, annual population growth during the same period of time was 1.6%. Together with the quick growth of CO2-emissions, high CO2-intensity of primary energy supply and a slower population growth, China’s CO2-emissions per capita (7.1 t) were considerably higher than those of Vietnam (1.5 t). Vietnam is still well below world average (5.0 t), China already surpasses e.g. those of South-European economies such as Portugal and Spain and is already about to catch up with North-European economies such as Denmark, Finland or even Germany.
Forecasting Vietnam’s GDP, CO2-emissions and CO2-intensities following China’s development path and comparing the results with an autonomous growth path not following China’s development path, GDP, primary energy supply and CO2-emissions in Vietnam are modeled econometrically. Co-integration analysis revealed a stable long-term economic relation between the variables in the models. Hence, here as well, no spurious regressions result. The comparison of the two scenarios shows that following China’s economic development path would imply an additional growth in Vietnam of 0.5% p.a. This means, Vietnam’s economy would grow considerably anyway. However, pursuing Vietnam’s current development path would result in much lower CO2-emissions (−2.3 percentage points per annum). By 2050, Vietnam’s CO2-emissions could be 2.6 bnt lower, if the country did not follow China’s way. GDP per capita, however, in 2050 would be about 18,000 US$ or about 25% lower than that if Vietnam would follow China’s development path. Here, the population and government of Vietnam have to make a strategic choice.
Oberheitmann, A. (2017) Economic Growth and CO2-Emi- ssions: What If Vietnam Followed China’s Development Path? American Journal of Cli- mate Change, 6, 99-115. https://doi.org/10.4236/ajcc.2017.61006