scholarly journals Cointegration Testing and Dynamic Simulations of Autoregressive Distributed Lag Models

2018 ◽  
Vol 18 (4) ◽  
pp. 902-923 ◽  
Author(s):  
Soren Jordan ◽  
Andrew Q. Philips
Keyword(s):  
Error Correction ◽  
Political Science ◽  
Applied Econometrics ◽  
Cointegration Test ◽  
Dynamic Simulations ◽  
Error Correction Models ◽  
Distributed Lag ◽  
Autoregressive Distributed Lag ◽  
Distributed Lag Models ◽  
Cointegration Testing

In this article, we introduce dynamac, a suite of commands designed to assist users in modeling and visualizing the effects of autoregressive distributed lag models and in testing for cointegration. We discuss the bounds cointegration test proposed by Pesaran, Shin, and Smith (2001, Journal of Applied Econometrics 16: 289–326), which we have adapted into a command. Because the resulting models can be dynamically complex, we follow the advice of Philips (2018, American Journal of Political Science 62: 230–244) by introducing a flexible command designed to dynamically simulate and plot a variety of types of autoregressive distributed lag models, including error-correction models.

scholarly journals Correction: Predicting the influence of climate on grassland area burned in Xilingol, China with dynamic simulations of autoregressive distributed lag models

PLoS ONE ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. e0245828
Author(s):  
Ali Hassan Shabbir ◽  
Jiquan Zhang ◽  
James D. Johnston ◽  
Samuel Asumadu Sarkodie ◽  
James A. Lutz ◽  
...  
Keyword(s):  
Dynamic Simulations ◽  
Area Burned ◽  
Distributed Lag ◽  
Autoregressive Distributed Lag ◽  
Distributed Lag Models

Growth impact of CO2 emissions caused by tourist arrivals in Turkey

2016 ◽  
Vol 8 (1) ◽  
pp. 19-37 ◽  
Author(s):  
Vedat Yorucu
Keyword(s):  
Error Correction ◽  
Error Correction Models ◽  
Content Type ◽  
Foreign Tourist ◽  
Distributed Lag ◽  
Autoregressive Distributed Lag ◽  
Long Run ◽  
Short Run ◽  
Dynamic Relationships ◽  
Long Run Equilibrium

Purpose – The purpose of this study is to analyze the determinants of changes in carbon dioxide (CO2) emissions for Turkey by utilizing the autoregressive distributed lag approach to investigate the long-run equilibrium relationships of CO2 emissions between foreign tourist arrivals (FTAs) and electricity consumption (ELC). The results reveal that foreign tourists and ELC are significant determinants of a long-run equilibrium relationship with CO2 emissions from electricity and heat production and CO2 emissions from transport for Turkey, respectively. The results of the conditional error correction models (CECM) confirm that there are long-run causal relationships from the growing number of foreign tourist arrivals and the increase of ELC toward the growth of CO2 emissions during 1960-2010. The results of autoregressive distributed lag (ARDL) error correction models for CO2 emissions also validate significant dynamic relationships between CO2 emissions, ELC and tourist arrivals in the short run. Design/methodology/approach – ARDL modeling and Bounds test approach were used in this study. Findings – Rapid tourism development in Turkey has triggered CO2 emissions. The growth of CO2 emissions in Turkey threatens sustainability. The hypothesis of “The growth of CO2 emissions in Turkey” is validated. Tourist arrivals, ELC and CO2 emissions are co-integrated. CECMs confirm the growth of CO2 emissions during 1960-2010. ARDL modeling shows significant relationships between CO2 emissions and other variables. Originality/value – Results of ARDL error correction models for CO2 emissions validate the hypothesis that there are significant dynamic relationships between CO2 emissions, ELC and tourist arrivals in Turkey for the short run.

scholarly journals The ARDL Method in the Energy-Growth Nexus Field; Best Implementation Strategies

Economies ◽  
2019 ◽  
Vol 7 (4) ◽  
pp. 105 ◽  
Author(s):  
Angeliki N. Menegaki
Keyword(s):  
Implementation Strategies ◽  
Research Papers ◽  
Vast Number ◽  
Energy Growth ◽  
Distributed Lag ◽  
Distributed Lag Model ◽  
Autoregressive Distributed Lag ◽  
Lag Model ◽  
Bounds Test ◽  
Cointegration Testing

A vast number of the energy-growth nexus researchers, as well as other “X-variable-growth nexus” studies, such as for example the tourism-growth nexus, the environment-growth nexus or the food-growth nexus have used the autoregressive distributed lag model (ARDL) bounds test approach for cointegration testing. Their research papers rarely include all the ARDL procedure steps in a detailed way and thus they leave other researchers confused with the series of steps that must be followed and the best implementation paradigms so that they not allow any obscure aspects. This paper is a comprehensive review that suggests the steps that need to be taken before the ARDL procedure takes place as well as the steps that should be taken afterward with respect to causality investigation and robust analysis.

The Effect of Foreign Direct Investment Inflows on Income Inequality: Evidence from China

2015 ◽  
Vol 15 (4) ◽  
pp. 443-453 ◽  
Author(s):  
Jai S. Mah
Keyword(s):  
Income Inequality ◽  
Direct Investment ◽  
Small Sample ◽  
Cointegration Test ◽  
Fdi Inflows ◽  
Linear Effect ◽  
Distributed Lag ◽  
Autoregressive Distributed Lag ◽  
Cointegration Tests ◽  
Bounds Test

This paper uses data for China during the period 1982–2010 and tests the effect of FDI inflows on income inequality, which is measured by the urban Gini coefficient. A small-sample cointegration test and autoregressive distributed lag bounds test are used as the cointegration tests. According to them, the variables under consideration are not cointegrated. The GMM estimation results show that income inequality worsens with FDI flows into China. The evidence from China shows a non-linear effect of FDI inflows on income inequality.

scholarly journals Nexus between Agriculture and Unemployment in Nigeria

2019 ◽  
pp. 1-13
Author(s):  
Oluwafemi S. Enilolobo ◽  
Saidi A. Mustapha ◽  
Onyeka P. Ikechukwu
Keyword(s):  
Error Correction ◽  
Granger Causality ◽  
Unit Root ◽  
Unit Root Test ◽  
Model Estimation ◽  
Correction Model ◽  
Agriculture Sector ◽  
Distributed Lag ◽  
Autoregressive Distributed Lag ◽  
Bounds Test

This study examined the impact of agriculture sector growth on unemployment level as well as the direction of causality between agricultural sector output and unemployment level in Nigeria. Secondary annual time series data between 1981 and 2016 were used for the study. Data on unemployment rate, agriculture sector output, public expenditure and industrial output were obtained from the Central Bank of Nigeria’s statistical Bulletin while data on FDI and population growth were obtained from the World Bank World Development Indicators. The data were analyzed using ADF (Augmented Dickey Fuller Test) unit root test, Autoregressive distributed lag Bounds test of cointegration, Autoregressive distributed lag error correction model estimation and Granger causality. The results of ADF unit root test revealed variables were at different orders of integration, the ARDL bounds test revealed cointegration between variables, and the Autoregressive distributed lag error correction model estimation revealed that change in agriculture output in the current period is negative and significant for current unemployment level in Nigeria, while the change in one period lagged agriculture output was positive and significant for current unemployment level in Nigeria. Also the error correction term indicated that about 74.10 percent of the disequilibrium in the system in the previous year would be corrected in the current year. Granger causality test results revealed bi-directional causality between agriculture output and unemployment level in Nigeria. The study recommends that the Nigeria government should using strategic policies targeted at boosting agriculture output such as increasing access to land for peasant rural farmers, investments in agricultural research, and so on, seek to boost agriculture output in order to reduce unemployment in Nigeria. Further, the Nigeria government should ensure that agriculture sector development policies are consistent with the objective of reducing unemployment in Nigeria.

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