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Global warming has become one of the most critical factors affecting the world, especially in the last decade. Therefore, it is of great importance to analyze the impact of global warming and take measures. The main factor leading to global warming is considered to be people’s consumption and production behaviors. The primary indicator of this is greenhouse gases. Relevant policy changes need to be made to control greenhouse gases. In this context, it is necessary to determine the differences in greenhouse gas emissions at the national level. To identify these differences, this study applies the convergence hypothesis, which has been the subject of numerous researchers since the 1980s. In this study, we analyzed the greenhouse gas intensity convergence for countries in the Organization for Economic Cooperation and Development (OECD) using linear and nonlinear panel unit root tests. The results of this study show that the greenhouse gas emissions in the OECD countries do not converge to the OECD average.

Today, global warming is one of the significant problems that affect the world and is projected to increase its impact in the upcoming years. The main factor leading to global warming is considered to be people’s consumption and production behaviors. The primary indicator of this is greenhouses gases. Relevant policy changes need to be made in order to control greenhouse gases. Global warming and the resulting carbon emissions have become one of the most controversial topics in the world. Tremendous efforts are spent on increasing environmental awareness, especially since the 1970s, and reducing greenhouse gas emissions has become the very first priority of international meetings. Global politics and global economic interests stand as essential obstacles to getting concrete results from these efforts.

The OECD countries generate a significant portion of the greenhouse gas emissions in the world. The consequences of the policies that these countries currently implement regarding production and consumption patterns will have a substantial impact on how global warming will take shape in the future.

This study aims to analyze whether there is a convergence between the OECD countries regarding greenhouse gas emissions using linear and nonlinear time series and panel unit root tests. The convergence hypothesis, which has been the subject of many studies since the 1980s, is one of the necessary inferences of the neoclassical growth theory and suggests that the relatively developing countries would converge with the more prosperous countries by eliminating income differences in general terms. The theory of convergence has become a controversial issue that attracts the attention of economists since it was first introduced. Studies investigated how these current differences of countries, regions, or international organizations with different natural resource distribution and different income levels will continue. In other words, the issue of how the inequalities between economies will change constitutes the basis of convergence discussions.

Convergence is an attractive concept used in areas such as economic growth, finance, theoretical econometrics, European political and monetary union, regional planning as well as geography, entertainment, multimedia technology, and the software industry. The fact that the countries do not converge to the country group indicates that the applied policies differ. From this point of view, it possible to ensure that the country for which convergence findings cannot be obtained converges to the group of the country with a policy change. The convergence hypothesis can be empirically investigated using unit root tests. The rejection of the unit root hypothesis indicates the existence of convergence.

Unlike many of the other studies which use linear methods, this study uses the tests that focus on nonlinearity recently introduced in literature and frequently seen in economic structures.

The article is organized as follows. The next section presents the literature review. Econometric methods are introduced in section three. Section four provides the data and empirical findings used in the study, and conclusions and suggestions for further research are covered in section five.

El-Montassera et al. [

Strazicich and List [_{2} emission convergence among 21 industrialized countries. Their study concluded that convergence existed in the years between 1960 and 1997. Romero-Ávila, D. [

Lee and Chang [

Barassi et al. [

Panopoulou and Pantelidis [_{2} emissions among all the countries in the early years of the sample period. Li and Lin [_{2} emissions) for 110 countries over the period 1971-2008. Their results showed that there was convergence within subgroups of countries with similar income levels, but no overall convergence was achieved.

This study is different from other studies in the sense that we use an empirical methodology and both linear and nonlinear panel unit tests, which have been recently introduced in the literature.

The econometric method used in the empirical part of the study is the linear and nonlinear panel unit root tests. It is clear that theoretical and practical studies on the panel data econometrics have considerably increased recently and that many researchers are interested in this topic. The reason for the growing interest in the panel data is that it offers certain advantages over using only time-series data or only horizontal cross-section data.

One of the most significant studies in the studies on advanced panel data techniques is the panel unit root tests. It is essential to determine whether the series or the panel analyzed is stationary in the search for a theory of economy or finance. In the analysis of panel data, classical panel unit root, panel unit root with breaks, and nonlinear panel unit root tests with different properties have been developed in determining whether the panel contains a unit root. In this study, we used linear and nonlinear panel unit root tests, which have certain advantages over classical time series methods. The next section explains the nonlinear panel unit root tests by Ucar and Omay [

In the last quarter of a century, panel unit root applications have been expanded considerably in nonstationary panel data. Panel unit root tests are more powerful than standard time series unit root tests because they use both time-series and horizontal cross-section size [

Several panel unit root tests are introduced in the panel data literature. One of these areas is the nonlinear panel unit root tests. These tests have a decade-old history and are limited. The use of nonlinear panel unit root tests gives more reliable results when the series to be employed in the analysis and the panel exhibit a nonlinear structure. In this context, Ucar and Omay [

Ucar and Omay [

As suggested by Ucar and Omay [

Δ y i , t = α i + ϕ i y i , t − 1 + γ i y i , t − 1 [ 1 − exp ( − θ i y i , t − d 2 ) ] + ε i , t

in which case d ≥ 1 is the delay parameter and θ i > 0 implies the speed of mean reversion for all i.

Ucar and Omay [

t i , N L = Δ y ′ i M τ y i , − 1 3 σ ^ i , N L ( y ′ i , − 1 M τ y i , − 1 ) 3 / 2

where σ ^ i , N L 2 is the consistent estimator. Ucar and Omay [

t ¯ N L = 1 N ∑ i = 1 N t i , N L

where t i , N L is invariant concerning initial observations y i , 0 , heterogeneous moments σ i 2 and σ i 4 if y 10 = 0 for all i = 1 , 2 , ⋯ , N . Individual statistic t i , N L are iid random variables with finite means and variances, an average statistic t ¯ i , N L as defined in the previous equation have limiting standard normal distribution as N → ∞ [

Z ¯ N L = N ( t ¯ N L − E ( t i , N L ) ) V a r ( t i , N L ) → d N ( 0 , 1 )

where the values of E ( t i , N L ) and V a r ( t i , N L ) for different numbers of T are tabulated in

Methane | Nitrous | CO2 | Greenhouse | |
---|---|---|---|---|

Levin, Lin and Chu [ | 0.3278 | 0.1587 | −3.989* | −2.0174* |

Harris and Tzavalis [ | 0.9718 | 0.933 | 0.9468 | 0.9383 |

Breitung [ | 2.6478 | −0.0376 | 2.6297 | 2.8004 |

Im, Pesaran and Shin [ | −1.0118 | 0.5619 | −1.7418* | −1.5236 |

Maddala and Wu [ | 48.1682 | 54.5412 | 69.0915 | 51.1836 |

Choi [ | 43.6091 | 74.2681* | 101.79* | 82.7779* |

Hadri [ | 87.0710 | 103.349 | 121.916 | 99.4581 |

Pesaran t-bar [ | −1.0630 | −1.8640 | −1.7940 | −1.5460 |

Note: The symbol * means rejection of the null hypothesis of a unit root. Source: Authors’ calculation.

Emirmahmutoglu and Omay [

The unit root test by Kapetanios et al. [

Δ y i t = G i t ( γ 1 i , y i , t − 1 ) × { S i t ( γ 2 i , y i , t − 1 ) ρ 1 i + ( 1 − S i t ( γ 2 i , y i , t − 1 ) ) ρ 2 i } y i , t − 1 + ε i t

G i t ( γ 1 i , y i , t − 1 ) = 1 − exp ( − γ 1 i y i , t − 1 2 ) , γ 1 i ≥ 0 for all i ,

S i t ( γ 2 i , y i , t − 1 ) = [ 1 + exp ( − γ 2 i y i , t − 1 ) ] − 1 , γ 2 i ≥ 0 for all i ,

where ε i t ∼ i i d ( 0 , σ i 2 ) . In this case, the deviation is the negative of the state variable, the outer regime is Δ y i t = ρ i 2 y i , t − 1 + ε i t , and the deviation is in the positive direction, and the outer regime is Δ y i t = ρ i 1 y i , t − 1 + ε i t , where the transition function takes the extreme values 0 and 1, respectively, for these two cases.

Emirmahmutoglu and Omay [

Δ y i t = ρ 1 i γ 1 i y i , t − 1 3 S i t ( γ 2 i , y i , t − 1 ) + ρ 2 i γ 1 i y i , t − 1 3 ( 1 − S i t ( γ 2 i , y i , t − 1 ) ) + ε i t

The augmented auxiliary equation is obtained as

Δ y i t = ϕ 1 i y i , t − 1 3 + ϕ 2 i y i , t − 1 4 + ∑ j = 1 p i δ i j Δ y i , t − j + ε i t

The proposed test statistic is computed by taking the average of the individual F i , A E statistic.

F ¯ A E = N − 1 ∑ i = 1 N F i , A E

Sollis [

The convergence of the intensity and the components of the greenhouse gas concentrations for OECD countries have been analyzed using linear and nonlinear time series and panel unit root tests. The data utilized in the study were obtained from the World Bank-World Development Indicators database. The variables are CO_{2}, Methane, Nitrous, and total greenhouse gas. The data of 29 OECD countries for the period 1970-2012 were investigated in the study. Czech Republic, Germany, Estonia, Latvia, Slovakia, and Slovenia were not included in the study.

In this part of the study where per capita greenhouse gas convergence in OECD countries is investigated, linear and nonlinear panel methods have been used, which attract the attention of many researchers and have significant advantages in empirical studies. The linear panel unit root test results and the nonlinear panel unit root test results for greenhouse gas convergence are shown in

The validity of the greenhouse gas convergence in _{2} gas per capita according to the results of Levin et al. [_{2} gas convergence is applied in OECD countries. In the last column, the analysis results for total greenhouse gas per capita were given. According to this, Levin et al. [

In _{2} gas. Finally, the presence of the null hypothesis of a unit root cannot be rejected according to the results of both tests for per capita total greenhouse gas; in other words, convergence is not valid. Looking at the results of greenhouse gas nonlinear panel unit root tests per capita in OECD countries in general, we conclude that convergence is not valid in all cases.

Methane | Nitrous | CO_{2} | Greenhouse | |
---|---|---|---|---|

Ucar and Omay [ | −1.3850 | −1.4890 | −1.5970 | −1.4450 |

Emirmahmutoglu and Omay [ | 1.7330 | 1.9570 | 2.2290 | 2.3580 |

Note: The symbol * means rejection of the null hypothesis of unit root. Source: Authors’ calculation.

Global warming is on the rise in the world and is expected to have more impact in the upcoming years. Different measures have been taken in recent years to control global warming. In this context, the convergence of greenhouse gas, which is regarded as the core indicator of global warming, for OECD countries is necessary to guide policy makers.

The convergence analysis has been carried out in recent years using linear and nonlinear panel unit root tests in the literature. The conclusion is that the convergence of per capita greenhouse gas emissions in OECD countries is not valid. The findings indicate that the long-term greenhouse gas emissions in the OECD countries will not be close to the same long-term values. According to these results, the differences in the long-term greenhouse gas emissions in the OECD countries will not disappear. Various policy changes need to be made in order to take these gases under control.

Future studies can focus on a similar analysis for country groups. Different results could be obtained from homogenous country groups.

The authors declare no conflicts of interest regarding the publication of this paper.

Canel, C., Güriş, S., Öktem, R., Güriş, B., Öktem, B., Yaşgül, Y.S. and Tıraşoğlu, M. (2020) An Examination of Greenhouse Gas Convergence in OECD Countries. Modern Economy, 11, 79-88. https://doi.org/10.4236/me.2020.111008