Q2. What have the authors stated for future works in "An econometric study of co2 emissions, energy consumption, income and foreign trade in turkey" ?
Therefore, it is possible to forecast the future levels of these variables from the past levels of each other. The stability of the CO2 emissions equation suggests that policy changes considering the explanatory variables of CO2 emissions equation will not cause major distortion in the level of CO2 emissions. Currently, the high economic growth gives rise to environmental degrading but the reduction in economic growth will increase unemployment further which is already running at around 10 % annually. It is suggested that Turkey should impose a carbon tax of 15-20 % over 2006-2020.
Q3. What criteria were used to determine the optimal length of the level variables of equations?
In search of finding the optimal length of the level variables of the short-run coefficients, several lag selection criteria such as 2R , AIC, SBC and Hannan-Quinn Criterion (HQC) were utilized at this stage.
Q4. What are the main concerns of humans in the last two decades?
The increasing threat of global warming and climate change have been the major ongoing concerns of humans in the last two decades.
Q5. What is the expected sign in equation 1?
As for the expected signs in equation (1), one expects that because higher levelof energy consumption should result in greater economic activity and stimulate CO 01 >a 2 emissions.
Q6. What is the significance of the coefficient on the lagged error-correction term?
According to the coefficient on the lagged error-correction term, there exists a long run relationship among the variables in the form of equation (1) as the error-correction term is statistically significant, which also confirms the results of the bounds test.
Q7. What is the elasticity of CO2 emissions with respect to openness ratio in the long run?
The elasticity of CO2 emissions with respect to openness ratio in the long run is 0.07, suggesting the contribution of the foreign trade to CO2 emissions is rather minimal during the estimation period.
Q8. How does the study calculate the elasticity of CO2 emissions with respect to income?
Using the input-output approach, they compute that 75% of the estimated CO2 emissions is due to production to satisfy domestic final amount, 11% is due to production to satisfy export demand and 13% is due to direct private consumption and public consumption.
Q9. What is the significance of the plots of the regression equations?
Provided that the plots of these statistics fall inside the critical bounds of 5% significance, one assumes that the coefficients of a given regression are stable.
Q10. What are the stability tests of Brown et al. (1975)?
stability tests of Brown et al. (1975), which are also known as cumulative sum (CUSUM) and cumulative sum of squares (CUSUMSQ) tests based on the recursive regression residuals, may be employed to that end.
Q11. What is the ARDL procedure used to estimate the parameters of equation (2)?
Given the existence of a long-run relationship, in the next step the ARDL cointegration procedure was implemented to estimate the parameters of equation (2) with maximum order of lag set to 2 to minimize the loss of degrees of freedom.
Q12. How is the Granger causality test used in equation (4)?
The Granger causality test may be applied to equation (4) as follows: i) by checking statistical significance of the lagged differences of the variables for each vector; this is a measure of short-run causality; and ii) by examining statistical significance of the error-correction term for the vector that there exists a long-run relationship.
Q13. How much does the elasticity of CO2 change with the level of income?
The error-correction term is –0.72 with the expected sign, suggesting that when per capita CO2 is above or below its equilibrium level, it adjusts by almost 72% within the first year.
Q14. What is the way to determine the effect of policy changes on the level of CO2 emissions?
the preferred CO2 emissions model can be used for policy decision-making purposes such that the impact of policy changes considering the explanatory variables of CO2 emissions equation will not cause major distortion in the level of CO2 emissions, since the parameters in this equation seems to follow a stable pattern during the estimation period.
Q15. What is the critical value of the general error correction model of equation (2)?
A general error correction model (ECM) of equation (2) is formulated as follows:ttmiitimimimiitiitimiitiititECfcycycecccccμλ ++Δ+Δ+Δ+Δ+Δ+=Δ−= − = = = −− = −− ∑∑ ∑ ∑∑1051 0 02430210 (3)where λ is the speed of adjustment parameter and ECt-1 is the residuals that are obtained from the estimated cointegration model of equation (1).
Q16. What is the significance of the coefficients associated with the error correction term?
The statistical significance of the coefficients associated with the error correction term provides evidence of an error correction mechanism that drives the variables back to their longrun relationship.