The sheer scale of China’s urban renewal and CO2 emissions: multiple structural breaks, long-run relationship, and short-run dynamics

The aim of this study is to examine the empirical cointegration, long-run and short-run dynamics and causal relationships between carbon emissions, energy consumption and economic growth in 14 Danube region countries over the period of 1990–2019. The autoregressive distributed lag (ARDL) bounds testing methodology was applied for each of the examined variables as a dependent variable. Limited by the length of the time series, we excluded two countries from the analysis and obtained valid results for the others for 26 of 36 ARDL models. The ARDL bounds reliably confirmed long-run cointegration between carbon emissions, energy consumption and economic growth in Austria, Czechia, Slovakia, and Slovenia. Economic growth and energy consumption have a significant impact on carbon emissions in the long-run in all of these four countries; in the short-run, the impact of economic growth is significant in Austria. Likewise, when examining cointegration between energy consumption, carbon emissions, and economic growth in the short-run, a significant contribution of CO2 emissions on energy consumptions for seven countries was found as a result of nine valid models. The results contribute to the information base essential for making responsible and informed decisions by policymakers and other stakeholders in individual countries. Moreover, they can serve as a platform for mutual cooperation and cohesion among countries in this region.

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Multiple structural breaks in cointegrating regressions: a model selection approach

Studies in Nonlinear Dynamics & Econometrics ◽

10.1515/snde-2020-0063 ◽

2021 ◽

Vol 0 (0) ◽

Author(s):

Alexander Schmidt ◽

Karsten Schweikert

Keyword(s):

Structural Breaks ◽

Penalized Regression ◽

Adaptive Lasso ◽

Test Statistics ◽

New Approach ◽

Multiple Structural Breaks ◽

Long Run ◽

Model Selection Approach ◽

Regression Techniques ◽

Lasso Estimator

Abstract In this paper, we propose a new approach to model structural change in cointegrating regressions using penalized regression techniques. First, we consider a setting with known breakpoint candidates and show that a modified adaptive lasso estimator can consistently estimate structural breaks in the intercept and slope coefficient of a cointegrating regression. Second, we extend our approach to a diverging number of breakpoint candidates and provide simulation evidence that timing and magnitude of structural breaks are consistently estimated. Third, we use the adaptive lasso estimation to design new tests for cointegration in the presence of multiple structural breaks, derive the asymptotic distribution of our test statistics and show that the proposed tests have power against the null of no cointegration. Finally, we use our new methodology to study the effects of structural breaks on the long-run PPP relationship.

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Role of Information and Communication Technology, Foreign Direct Investment and Trade Openness in Environmental Sustainability

Journal of Accounting and Finance in Emerging Economies ◽

10.26710/jafee.v7i2.1656 ◽

2021 ◽

Vol 7 (2) ◽

pp. 263-272

Author(s):

Sulaman Hafeez Siddiqui ◽

Sohail Saeed ◽

Areeba Khan ◽

Hina Bhatti

Keyword(s):

Co2 Emissions ◽

Information And Communication Technologies ◽

Environmental Sustainability ◽

Trade Openness ◽

Communication Technologies ◽

Fdi Inflows ◽

Long Run ◽

Short Run ◽

Information And Communication ◽

The Government

Purpose: The benefits of Information and Communication Technologies (ICTs) in environmental resource management has been a topic of hot discussion for the policymakers across the world. For the purpose, the government of Pakistan took initiative in 2018 to use technology for the country’s social welfare, financial benefits and to enhance environmental sustainability and named it as “Digital Pakistan Initiative”.Design/Methodology/Approach: For analysis, this study took CO2 emissions as the dependent variable and ICT, FDI inflows, and Trade Openness as independent variables. Data were collected on bimonthly basis from 2004 through 2019, and analyzed employing ARDL approach. Main purpose of the study was to examine the short-run and long-run relationship among carbon emissions and ICT, FDI Inflows and Trade Openness.Findings: The findings show that there exists a short-run relationship among all the variables; however, FDI inflows and trade openness have a significant relationship with CO2 emissions. The results also exhibit that there is no long-run relationship between CO2 emissions, FDI inflows, and Trade openness while ICT has an insignificant long-run relationship with CO2 emissions. With the increase of information and communication, the country’s environmental sustainability is also increased. Implications/Originality/Value: The current study was based on least considered variables and the pioneer in testing the complex relationship through VAR estimation.

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NON-LINEAR EFFECTS OF TERRORISM ON ECONOMIC GROWTH IN PAKISTAN: ACCOUNTING FOR CAPITAL PER WORKER AND STRUCTURAL BREAKS

The Singapore Economic Review ◽

10.1142/s0217590819500140 ◽

2019 ◽

pp. 1950014

Author(s):

RONALD RAVINESH Kumar ◽

SYED JAWAD HUSSAIN SHAHZAD ◽

PETER JOSEF STAUVERMANN ◽

NIKEEL Kumar

Keyword(s):

Economic Growth ◽

Capita Income ◽

Structural Breaks ◽

Per Capita Income ◽

Negative Effects ◽

Capital Share ◽

Long Run ◽

Non Linear ◽

Short Run ◽

Per Capita

In this study, we examine the asymmetric effects of terrorism and economic growth in Pakistan over the period 1970–2016, while considering the role of capital per worker and structural breaks. We use the non-linear ARDL approach to establish the long-run association and to estimate the short-run and long-run effects accordingly. The results indicate the presence of asymmetries in both long and short run. Moreover, 1% decrease in terrorism results in an increase of per capita income by 0.02% in the long run and 0.001% in the short run. Assuming symmetry, the long run capital share is 0.47. In asymmetric relation, a 1% increase in capital share increases output by 0.55%, whereas a 1% decrease in capital stock decreases output by 0.26%. The break effects show that the years 1993 and 2004 have negative effects on growth. The vector error correction model-based causality results indicate a unidirectional causality from terrorism to per capita income. Overall, the results highlight that terrorism is growth retarding.

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Does Economic Policy Uncertainty Affect CO2 Emissions? Empirical Evidence from the United States

Sustainability ◽

10.3390/su12219108 ◽

2020 ◽

Vol 12 (21) ◽

pp. 9108 ◽

Cited By ~ 1

Author(s):

Qing Wang ◽

Kefeng Xiao ◽

Zhou Lu

Keyword(s):

United States ◽

Economic Policy ◽

Co2 Emissions ◽

Structural Breaks ◽

Unit Root Test ◽

The United States ◽

Policy Uncertainty ◽

Energy Prices ◽

Economic Policy Uncertainty ◽

Long Run

This paper aims to examine the effects of economic policy uncertainty (measured by the World Uncertainty Index—WUI) on the level of CO2 emissions in the United States for the period from 1960 to 2016. For this purpose, we consider the unit root test with structural breaks and the autoregressive-distributed lag (ARDL) model. We find that the per capita income promotes CO2 emissions in the long run. Similarly, the WUI measures are positively associated with CO2 emissions in the long run. Energy prices negatively affect CO2 emissions both in the short run and the long run. Possible implications of climate change are also discussed.

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Does Chinese FDI, Climate Change, and CO2 Emissions Stimulate Agricultural Productivity? An Empirical Evidence from Pakistan

Sustainability ◽

10.3390/su12187485 ◽

2020 ◽

Vol 12 (18) ◽

pp. 7485 ◽

Cited By ~ 1

Author(s):

Shakeel Ahmad ◽

Muhammad Tariq ◽

Touseef Hussain ◽

Qasir Abbas ◽

Hamidullah Elham ◽

...

Keyword(s):

Climate Change ◽

Co2 Emissions ◽

Agricultural Production ◽

Direct Investment ◽

Granger Causality Test ◽

Test Results ◽

Causality Test ◽

Agriculture Sector ◽

Long Run ◽

Short Run

Pakistan’s agricultural sector growth is dwindling from the last several years due to insufficient foreign direct investment (FDI) and a drastic climate change-induced raise in temperature, which are severely affecting agricultural production. The FDI has paramount importance for the economy of developing countries as well as the improvement of agricultural production. Based on the time series data from 1984 to 2017, this paper aims to highlight the present situation of the agriculture sector of Pakistan and empirically analyze the short-run and long-run impact of Chinese foreign direct investment (CFDI), climate change, and CO2 emissions on agricultural productivity and causality among the variables. The Autoregressive Distributed Lag Model (ARDL) model and Granger Causality test were employed to find out the long-run, short-run, and causal relationships among the variables of interest. Furthermore, we have employed the Error Correction Model (ECM) to know the convergence of the equilibrium path. The bound test results verified the existence of a long-run association, and the empirical findings confirmed that Chinese FDI has a significant and positive impact, while climate change and CO2 emissions has negative impact on the agricultural growth of Pakistan both in the short-run and long-run. Granger Causality test results revealed that variables of interest exhibit bi-directional and uni-directional causality. The sector-wise flow of FDI reveals that the agriculture sector of Pakistan has comparatively received a less amount of FDI than other sectors of the economy. Based on the findings, it was suggested to the Government of Pakistan and policymakers to induce more FDI in the agriculture sector. Such policies would be helpful for the progress of the agriculture sector as well as for the economic growth of Pakistan.

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DYNAMIC EFFECTS OF REMITTANCES ON EXTERNAL RESERVES IN NIGERIA: THE ROLE OF INFLATION AND STRUCTURAL BREAKS

Journal of Humanities, Social Science and Creative Arts ◽

10.51406/jhssca.v13i1.1934 ◽

2019 ◽

Vol 13 (1) ◽

pp. 119-141

Author(s):

E. A. OLUBIYI ◽

A. RAHEEM ◽

A. A. ADEMOKOYA

Keyword(s):

Exchange Rate ◽

Structural Breaks ◽

Flexible Exchange Rate ◽

Jel Classification ◽

Additional Information ◽

Distributed Lag ◽

Autoregressive Distributed Lag ◽

Long Run ◽

Floating Exchange Rate ◽

Short Run

This study provides additional information about the drivers of external reserves in Nigeria. The result using Autoregressive Distributed Lag (ARDL) model estimation approach for the period 1980-2015 shows that remittances, among other macroeconomic variables, increased external reserves in the short run but weakens it in the long run. Remittances depletes external reserves through its effect on inflation rate and the nonsterilized intervention of the Central Bank. Furthermore, regime shift to relatively floating exchange rate causes remittances to increase reserves. From the foregoing, it is important for the authorities to continue operating relatively flexible exchange rate, and curtail excessive spending of remittances. Keywords: , , , , . JEL Classification: F31, F24, C22, F31

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ECONOMETRIC MODELLING OF THE CONSUMPTION OF ELECTRICITY IN GHANA WHEN STRUCTURAL BREAKS EXIST

Journal of Economic Info ◽

10.31580/jei.v7i3.1612 ◽

2020 ◽

Vol 7 (3) ◽

pp. 205-220

Author(s):

Samuel Asuamah Yeboah

Keyword(s):

Structural Breaks ◽

Trade Openness ◽

Electricity Consumption ◽

Annual Data ◽

Explanatory Variables ◽

Long Run ◽

Development Indicator ◽

Short Run ◽

World Development Indicator ◽

World Development

The research modelled electricity consumption for Ghana using annual data for the period 1971-2011, obtained from world development indicator. The research adopts the Gregory and Hansen model of cointegration for the estimation in the presence of structural breaks. The results reveal stable short run and long-run relationships among the explanatory variables and electricity consumption. The findings suggest that financial development explain electricity consumption in Ghana both in the short run and in the long run. The other variables (trade openness, price, and income) in the estimated model do not significantly explain electricity consumption. Therefore, they are not reliable policy variables in managing electricity consumption.

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FINANCIAL DEVELOPMENT, INCOME, TRADE, AND URBANIZATION ON CO2 EMISSIONS: NEW EVIDENCE FROM KYOTO ANNEX COUNTRIES

Journal on Innovation and Sustainability RISUS ISSN 2179-3565 ◽

10.24212/2179-3565.2018v9i3p17-37 ◽

2018 ◽

Vol 9 (3) ◽

pp. 17 ◽

Cited By ~ 10

Author(s):

Muhammad Rizwan Nazir ◽

Muhammad Imran Nazir ◽

Shujahat Haider Hashmi ◽

Zeeshan Fareed

Keyword(s):

Co2 Emissions ◽

Financial Development ◽

Environmental Degradation ◽

Trade Openness ◽

Negative Influence ◽

Financial Reforms ◽

Long Run ◽

Short Run ◽

Carbon Dioxide Co2 ◽

The Impact

This study attempts to empirically investigate the impact of financial development, income, trade openness, and urbanization on carbon dioxide (CO2) emissions for the 21 Kyoto Annex countries using a balance panel data and GMM system over the period of 1970-2016. The results show a positive relationship between income and CO2 emissions in long-run. All models support the EKC hypothesis which assumes an inverted U-shaped relationship among income and environmental degradation. Financial development has a long-run negative influence on CO2 emissions, indicating that financial development reduces the environmental degradation. This means that financial development can be used as an implement to keep the degradation environmental clean by presenting financial reforms. The urbanization declines the CO2 emissions; however, it is essential for the policymakers and urban planners in these countries to control the rapid increase in urbanization. The panel causality confirms that bi-directional causal relationship between financial development, CO2 emissions, income, trade openness, and Urbanization in short-run.

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Evaluating the EKC Hypothesis for the BCIM-EC Member Countries under the Belt and Road Initiative

Sustainability ◽

10.3390/su12041478 ◽

2020 ◽

Vol 12 (4) ◽

pp. 1478 ◽

Cited By ~ 6

Author(s):

Arifur Rahman ◽

S. M. Woahid Murad ◽

Fayyaz Ahmad ◽

Xiaowen Wang

Keyword(s):

Panel Data ◽

Carbon Emission ◽

Structural Breaks ◽

Energy Use ◽

Trade Openness ◽

Gdp Per Capita ◽

Ekc Hypothesis ◽

Long Run ◽

Short Run ◽

Per Capita

This paper attempts to examine the environmental Kuznets curve (EKC) hypothesis for the BCIM-EC (Bangladesh–China–India–Myanmar economic corridor) member countries under the Belt and Road Initiative (BRI) of China. Both time series and panel data are covered, with respect to carbon dioxide (CO2) emissions, GDP per capita, energy use, and trade openness. For panel data analysis, GDP per capita and energy consumption have positive effects on CO2, while the effect of the quadratic term of GDP per capita is negative in the short-run. However, the short-run effects do not remain valid in the long-run, except for energy use. Therefore, the EKC hypothesis is only a short-run phenomenon in the case of the panel data framework. However, based on the Autoregressive Distributed Lag (ARDL) approach with and without structural breaks, the EKC hypothesis exists in India and China, while the EKC hypothesis holds in Bangladesh and Myanmar with regard to disregarding breaks within the short-run. The long-run estimates support the EKC hypothesis of considering and disregarding structural breaks for Bangladesh, China, and India. The findings of the Dumitrescu and Hurlin panel noncausality tests show that there is a unidirectional causality that runs from GDP per capita to carbon emission, squared GDP to carbon emission, and carbon emission to trade openness. Therefore, the BCIM-EC under the BRI should not only focus on connectivity and massive infrastructural development for securing consecutive economic growth among themselves, but also undertake a long-range policy to cope with environmental degradation and to ensure sustainable green infrastructure.

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