scholarly journals The trade-off between GDP and CO2 emissions in poor countries: A dynamic common correlated effects approach for unbalanced panel data

2021 ◽  
Author(s):  
Quoc Khanh Duong
Keyword(s):  
Climate Change ◽  
Panel Data ◽  
Co2 Emissions ◽  
Growth Models ◽  
Cross Sectional ◽  
Poor Countries ◽  
Trade Offs ◽  
Long Run ◽  
Common Correlated Effects ◽  
Unbalanced Panel Data

Abstract In recent years, the term "climate change" has been increasingly receiving a lot of attention from scholars and policy makers, adversely affecting the lives of people (mostly of the poor) around the world in the present, and threatening the environment quality in the future. With many concerns about environmental degradation, countries tend to transform economic growth models causing negative impacts on the environment, especially for those in the stage of industrialization and modernization. This study was aimed at investigating the trade-offs between economic development and climate change among poor nations – the most affected by and most likely causing to climate change. By using a dynamic common correlated effects approach for unbalanced panel data which deals with cross-sectional dependency and time-series persistence, the paper showed that GDP is strongly correlated to CO2 emissions both in the short and long run, and one of the reasons is the use of CO2-generating energy sources.JEL classification: C23, O44, Q54

scholarly journals Greening the Financial System in USA, Canada and Brazil: A Panel Data Analysis

Mathematics ◽  
2020 ◽  
Vol 8 (12) ◽  
pp. 2217
Author(s):  
Ioan Batrancea ◽  
Larissa Batrancea ◽  
Malar Maran Rathnaswamy ◽  
Horia Tulai ◽  
Gheorghe Fatacean ◽  
...  
Keyword(s):  
Climate Change ◽  
Economic Growth ◽  
Global Warming ◽  
Data Analysis ◽  
Panel Data ◽  
Co2 Emissions ◽  
Panel Data Analysis ◽  
Financial Sector ◽  
Financial Systems ◽  
Domestic Credit

Each country designs its own scheme to achieve green financing and, in general, credit is considered to be a fundamental source of greening financial systems. The novelty of this study resides in that we examined green financing initiatives in USA, Canada and Brazil by focusing on major components of the financial systems before, during and after the 2008 world financial crisis. By means of panel data analysis conducted on observations ranging across the period 1970–2018, we investigated variables such as domestic credit from banks, domestic credit from the financial sector, GDP, N2O emissions, CO2 emissions and the value added from agriculture, forest and fishing activities. According to our findings, domestic credit from banks was insufficient to achieve green financing. Namely, in order to increase economic growth while reducing global warming and climate change, the financial sector should assume a bigger role in funding green investments. Moreover, our results showed that domestic credit from the financial sector contributed to green financing, while CO2 emissions remained a challenge in capping global warming at the 1.5 °C level. Our empirical study supports the idea that economic growth together with policies targeting climate change and global warming can contribute to green financing. Over and above that, governments should strive to design sustainable fiscal and monetary policies that promote green financing.

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

2020 ◽  
Vol 12 (18) ◽  
pp. 7485 ◽  
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.

scholarly journals ASYMPTOTICALLY UNBIASED ESTIMATION OF AUTOCOVARIANCES AND AUTOCORRELATIONS WITH LONG PANEL DATA

2010 ◽  
Vol 26 (5) ◽  
pp. 1263-1304 ◽  
Author(s):  
Ryo Okui
Keyword(s):  
Time Series ◽  
Panel Data ◽  
Unobserved Heterogeneity ◽  
Small Samples ◽  
Unbiased Estimation ◽  
Series Length ◽  
Cross Sectional ◽  
Long Run ◽  
The Individual ◽  
Time Invariant

An important reason for analyzing panel data is to observe the dynamic nature of an economic variable separately from its time-invariant unobserved heterogeneity. This paper examines how to estimate the autocovariances of a variable separately from its time-invariant unobserved heterogeneity. When both cross-sectional and time series sample sizes tend to infinity, we show that the within-group autocovariances are consistent, although they are severely biased when the time series length is short. The biases have the leading term that converges to the long-run variance of the individual dynamics. This paper develops methods to estimate the long-run variance in panel data settings and to alleviate the biases of the within-group autocovariances based on the proposed long-run variance estimators. Monte Carlo simulations reveal that the procedures developed in this paper effectively reduce the biases of the estimators for small samples.

scholarly journals Nexus Between Carbon Emissions, Energy Consumption, Urbanization and Economic Growth in Asia: Evidence From Common Correlated Effects Mean Group Estimator (CCEMG)

2021 ◽  
Vol 8 ◽  
Author(s):  
Yusuf Babatunde Adeneye ◽  
Amar Hisham Jaaffar ◽  
Chai Aun Ooi ◽  
Say Keat Ooi
Keyword(s):  
Economic Growth ◽  
Energy Consumption ◽  
Carbon Emission ◽  
Panel Cointegration ◽  
Energy Prices ◽  
Asian Countries ◽  
Cross Sectional ◽  
Long Run ◽  
Cointegration Tests ◽  
Common Correlated Effects

This study investigates the dynamic relationships between carbon emission, urbanization, energy consumption, and economic growth in a panel of 42 Asian countries for the period 2000–2014 using dynamic common correlated effects panel data modeling. This study employs second generation cross-sectional Pesaran (J. Appl. Econom., 2007, 22(2), 265-312) panel unit root, Westerlund panel cointegration tests (Econom. Stat., 2007, 69(6), 709-748), and Pesaran’s (Econometrica, 2006, 74(4), 967-1012) common correlated effects mean group estimation technique. These approaches allow for cross-sectional dependence, and are robust to the presence of common factors, serial correlation, and slope heterogeneity. The Common Correlated Effect Mean Group test reveals a high average coefficient of 0.602 between carbon emission and energy consumption while low coefficients of 0.114 and 0.184 for the pairs of carbon emission-urbanization and carbon emission-GDP, respectively for the panel as a whole, suggesting a cointegration between carbon emission, urbanization, energy consumption, and economic growth. The results indicate that there is relatively high carbon emission especially for highly populated and geopolitical risk Asian countries in the short run. Findings reveal long run relationships between the variables, which is attributed to the on-going carbon taxation and energy prices. Our results are robust to PMG-ARDL estimator. Overall, these findings cast important implications on renewable energy policy and urban planning insights for the policymakers.

scholarly journals Does Climate Change Have Real Negative Impact on Economic Growth in Poor Countries? Evidence from Cote d’Ivoire (Ivory Coast)

2018 ◽  
Vol 4 (2) ◽  
pp. 204
Author(s):  
Felix Fofana N’Zué ◽  
Keyword(s):  
Climate Change ◽  
Economic Performance ◽  
Negative Impact ◽  
Value Added ◽  
Poor Countries ◽  
Distributed Lag ◽  
Long Run ◽  
Per Capita ◽  
Growth Change ◽  
The Impact

The objective of this paper is to determine the impact of climate change on Cote d’Ivoire’s economic performance via per capita gross domestic product (GDP) growth, change in agricultural value added, and change in the country’s cereal yield. The data ranged from 1960 to 2016. An autoregressive distributed lag (ARDL) model is used to investigate the long run dynamics between climate variables (precipitation and temperature) and the country’s per capita GDP, agricultural value added as % of GDP, and cereal yield. We found that climate change has not significantly impacted the economic performance of the country. However, precipitation has been found to have positively and significantly influenced the country’s cereal yield and agricultural value added contribution to GDP at large, and thus there is no need to worry more than it is necessary.

scholarly journals The effectiveness of Vietnamese policies response to climate change through ARDL analysis

2021 ◽  
Vol 11 (2) ◽  
pp. 42-52
Author(s):  
Le Hoang Nghiem ◽  
Dang Bac Hai ◽  
Tran Thi Diem Nga ◽  
Su Thi Oanh Hoa
Keyword(s):  
Climate Change ◽  
Economic Growth ◽  
Foreign Direct Investment ◽  
Renewable Energy ◽  
Energy Consumption ◽  
Co2 Emissions ◽  
Direct Investment ◽  
Economic Factor ◽  
Renewable Energy Consumption ◽  
Long Run

Being a highly vulnerable country due to climate change, Vietnam has issued various climate policies while trying to keep the pace of economic growth. The study evaluates the effectiveness of these policies by examining the effect of economic and energy factors in the efforts of controlling CO2 emissions. Approach by Autoregressive Distributed Lag (ARDL) analysis, the model of a linear regression between CO2 emissions and Gross Domestic Product (GDP), Foreign Direct Investment (FDI) & sources of energy consumption has been developed from 1985 to 2018. The study indicates that the economic factor as Foreign Direct Investment (FDI) is a possible significant element to mitigate the emission. In addition, sources of energy consumption have the important role of controlling CO2 emissions. In the long run, the consumption of non - renewable energy is a positive and significant effect on CO2 emissions while renewable energy is vice versa. These outcomes show the Foreign Direct Investment (FDI) and renewable energy consumption factors lead to the decrease of CO2 emissions in the long run for Vietnam, which implies the co-exist of economic growth and decarbonization.

scholarly journals Capital mobility in Latin American and Caribbean countries: new evidence from dynamic common correlated effects panel data modeling

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Vasudeva N. R. Murthy ◽  
Natalya Ketenci
Keyword(s):  
Panel Data ◽  
Error Correction ◽  
Latin American ◽  
Capital Mobility ◽  
Goods And Services ◽  
Stochastic Trends ◽  
Long Run ◽  
Common Correlated Effects ◽  
Short Run ◽  
Latin American And Caribbean

AbstractThis study investigates the degree of capital mobility in a panel of 16 Latin American and 4 Caribbean countries during 1960 to 2017 against the backdrop of the Feldstein-Horioka hypothesis by applying recent panel data techniques. This is the first study on capital mobility in Latin American and Caribbean countries to employ the recently developed panel data procedure of the dynamic common correlated effects modeling technique of Chudik and Pesaran (J Econ 188:393–420, 2015) and the error-correction testing of Gengenbach, Urbain, and Westerlund (Panel error correction testing with global stochastic trends, 2008, J Appl Econ 31:982–1004, 2016). These approaches address the serious panel data econometric issues of cross-section dependence, slope heterogeneity, nonstationarity, and endogeneity in a multifactor error-structure framework. The empirical findings of this study reveal a low average (mean) savings–retention coefficient for the panel as a whole and for most individual countries, as well as indicating a cointegration relationship between saving and investment ratios. The results indicate that there is a relatively high degree of capital mobility in the Latin American and Caribbean countries in the short run, while the long-run solvency condition is maintained, which is due to reduced frictions in goods and services markets causing increase competition. Increased capital mobility in these countries can promote economic growth and hasten the process of globalization by creating a conducive economic environment for FDI in these countries.

scholarly journals DO ECONOMIC GROWTH AND ENVIRONMENT QUALITY CONTRIBUTE TO TOURISM DEVELOPMENT IN EU COUNTRIES? A PANEL DATA ANALYSIS

2021 ◽  
Vol 27 (6) ◽  
pp. 1509-1538
Author(s):  
Daniel Badulescu ◽  
Ramona Simut ◽  
Ioana Mester ◽  
Simona Dzitac ◽  
Mariana Sehleanu ◽  
...  
Keyword(s):  
Economic Growth ◽  
Energy Consumption ◽  
Panel Data ◽  
Co2 Emissions ◽  
Positive Impact ◽  
Panel Data Analysis ◽  
Tourism Development ◽  
Tourism Industry ◽  
Long Run ◽  
Tourism Sector

The positive impact of the tourism industry on economic growth, revenues, infrastructure, employment, social inclusion and poverty reduction, although widely recognised, has been lately weighted against the appearance and exacerbation of several problems, such as: environmental footprint, increase of income inequality, cost increases related to solid waste collection, energy consumption, increased global CO2 emissions. On the other hand, the tourism sector is not just an active economic, societal, or environmental change agent; in turn, the tourism sector supports or is highly influenced by various factors, such as climate change, economic, political, or social factors. More recently, this industry has been highly impacted by the pandemic, technological developments and cultural trends. In this article we examined both the short and long-run relationship between tourism development and economic growth, CO2 emissions and energy consumption in European Union member states (EU27), by using the Principal Component Analysis (PCA) technique and autoregressive distributed lag (ARDL) model for panel data. The findings suggest that economic growth and energy consumption have a statistically significant impact on the tourism index both in the short and long-run, whereas CO2 emissions only have a significant impact upon the tourism index on the long run.

scholarly journals Domestic Credit and the Balance of Payment Deficit: Evidence from a Heterogeneous Panel of Five Selected Mena Countries

2021 ◽  
Vol 35 (1) ◽  
pp. 133-148
Author(s):  
Azeddine Ghilous ◽  
Adel Ziat
Keyword(s):  
Negative Impact ◽  
Panel Data Analysis ◽  
Policy Instruments ◽  
Cross Sectional ◽  
Net Foreign Assets ◽  
Mena Countries ◽  
Long Run ◽  
Domestic Credit ◽  
Common Correlated Effects ◽  
Foreign Assets

Abstract This study investigated the relationship between domestic credit and net foreign assets in the long run through the monetary approach to the balance of payments (MABP) for a panel of five selected MENA countries (Jordan, Egypt, Algeria, Morocco, Tunisia) during the period extending from 1980 to 2019. It employed the second-generation methods in panel data analysis to deal with cross-sectional dependence (CSD) and slope heterogeneity. According to the panel results for Common Correlated Effects Mean Group (CCEMG) and Augmented Mean Group (AMG) estimators, domestic credit has a significant negative impact on net foreign assets in the long run. The country-specific results for the AMG estimator strongly supported the MABP propositions in Jordan, Morocco, and to a lesser extent, in Egypt and Algeria. As for Tunisia, the results do not conform with what MABP predicted. The implicit conclusion is that an increase in domestic credit causes a continuous loss of net foreign assets in Egypt, Jordan, Morocco, and Algeria. Thus, monetary authorities should formulate an appropriate monetary policy to control the domestic credit creation as a mechanism toward improving the balance of payment (BOP) position. Furthermore, the policymakers should concentrate on other policy instruments to correct the BOP deficit rather than focusing on monetary tools, especially in Tunisia, where the findings showed that BOP was not a monetary phenomenon.

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