Empirical Model Specification

The relationship between the size of an economy and the intensity of CO2 emissions was examined

by Grossman and Krueger (1995) who reported that pollution tends to rise during the first stage of a country’s development, and decreases after reaching a certain income level. The standard EKC regression model is given as:

ln (𝐸/𝑃)𝑖𝑡 = 𝛾𝑖+ 𝛿𝑡+ 𝜑1 𝑙𝑛 ( 𝐺𝐷𝑃 𝑃 )𝑖𝑡+ 𝜑2 {𝑙𝑛 ( 𝐺𝐷𝑃 𝑃 )}𝑖𝑡 2 _{+ 𝜀} 𝑖𝑡 (4.1)

where E is emissions; P is population; GDP is gross domestic product; γi and δtare intercept parameters which may vary across countries or regions i and year t; 𝜀it is stochastic shock (Stern,

2003).

Empirically, the relationship between economic development and CO2 emissions has been widely

economic growth, and per capita income in a linear quadratic form (Stern, 2003). We specified a log linear quadratic equation to test the long-run relationship among CO2 emissions, energy

consumption, economic growth and foreign trade in Vietnam. The regression model is given as follows:

ln 𝐶𝑡 = 𝛼0+ 𝛼1𝑙𝑛𝐸𝑡+ 𝛼2𝑙𝑛𝑇𝑟𝑡+ 𝛼3𝑙𝑛𝑌𝑡+ 𝛼4(𝑙𝑛𝑌𝑡)2+ 𝜀𝑡 (4.2)

where 𝐶𝑡 is CO2 emissions per capita, 𝐸𝑡is commercial energy use per capita, 𝑇𝑟𝑡 is the openness ratio, 𝑌𝑡is real per capita income, 𝑌𝑡2 is the square of real per capita income, and 𝜀𝑡 is the regression error terms. All variables in equation (4.2) are in their natural logarithmic form.

Generally, the higher level of energy consumption would result in greater economic activity and stimulate CO2 emissions; therefore, 𝛼₁ is positive and significant in equation (4.2). Under the EKC

hypothesis, the sign of 𝛼3 is expected to be positive whereas a negative sign is expected for 𝛼4. Linh and Lin (2014) found that 𝛼4 is statistically insignificant, indicating that there is not enough statistical evidence to confirm that the environment will be rehabilitated at a time of specific higher per capita income in Vietnam. Tang and Tan (2015), in contrast, found that 𝛼4 is statistically significant,

reflecting that the environment can be restored at a higher level of income in Vietnam. The expected sign of 𝛼2 is mixed depending on the stage of economic development of the country under study. For developed countries, 𝛼2 is expected to be negative as the technology improvement allows them to produce less energy and pollution intensive goods, but this sign is expected to be positive for developing countries (Kohler, 2013). Therefore, in our study 𝛼2 is expected to be positive.

However, the inclusion of the real per capita GDP variable and square of real per capita GDP under the same framework as equation (4.2) may cause collinearity problems. Beside, our primary purpose is to examine the impact of trade openness on CO2 emissions, rather than the existence of EKC

theory in Vietnam. Thus we also use equation (4.3) to avoid the potential collinearity between the variables of Yt and Yt2.

𝑙𝑛 𝐶𝑡 = 𝛽0+ 𝛽1𝑙𝑛𝐸𝑡+ 𝛽2𝑙𝑛𝑇𝑟𝑡 + 𝛽3𝑙𝑛𝑌𝑡+ µ𝑡 (4.3)

where 𝐶𝑡 is CO2 emissions per capita, 𝐸𝑡is commercial energy use per capita, 𝑇𝑟𝑡 is the openness ratio, 𝑌𝑡is real per capita income, and µ𝑡 is the regression error terms. All variables in equation (4.3) are in their natural logarithmic form.

For equation (4.3), 𝛽1 is expected to be positive and significant as the higher energy consumption would result in higher CO2 emissions. The empirical estimation result of equation (4.3) can be

compared with the results of Al-Mulali et al. (2015), and Anwar and Alexander (2016). The study conducted by Al-Mulali et al. (2015) found a positive relationship between GDP and CO2 emissions in

the short-run and long-run in Vietnam. Al-Mulali et al’s (2015) study further found a significantly negative import impact and a positive export impact on CO2 emissions, which indicates that Vietnam

mainly imports highly polluted products (Al-Mulali et al., 2015). Anwar and Alexander (2016) found evidence that trade openness has minor effects on the CO2 emissions in Vietnam.

The variables used in equations (4.2) and (4.3) are defined in Table 4.1.

Table 4-1: Variable Definitions for Equations (4.2) and (4.3)

Variable Definition Measurement

t Year From 1985 to 2013

Ct CO2 emissions per capita CO2 emissions are those stemming from the

burning of fossil fuels and the manufacture of cement. They include CO2 produced during

composition of solid, liquid, and gas fuels and gas flaring

Et Energy used per capita The energy use variable is measured in kilograms

of oil equivalent per capita

Trt Trade openness The total value of exports and imports as a share of

nominal GDP

Yt Real per capita GDP The real per capita GDP is measured as a ratio of

real GDP to total population. (Yt)2 Square of the real per capita

GDP

εt Regression error term εt captures effects of other variables on CO2

emissions rather than economic development, trade openness and energy use.