DOES FINANCIAL INCLUSIVENESS AFFECT ECONOMIC GROWTH? NEW EVIDENCE USING A DYNAMIC PANEL THRESHOLD REGRESSION

To verify whether the effect of tourism on environmental performance differs by the level of tourism development, a panel threshold regression approach is applied to observe the effects of tourism on environmental performance in 97 countries over the 2002–2012 periods. Our results suggest that tourism always has a significant negative influence on the environmental performance, implying that tourism will unavoidably result in environmental degradation, irrespective of how high the level of tourism development. However, when tourism development exceeds a certain value, tourism will relatively have less influence on environmental performance. In terms of policy prescriptions, considering that tourism wills inevitably worse environmental qualities, this finding implies that policymakers should consider the optimal level of tourism development at around the estimated threshold level to minimize the negative impact of tourism on environmental quality.

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New evidence for the relationship between government size and economic growth in Iran: an application for a three-regime Non-linear threshold regression model

Quarterly Journal of Economic Research and Policies ◽

10.52547/qjerp.28.93.297 ◽

2020 ◽

Vol 28 (93) ◽

pp. 297-328

Author(s):

Hassan Khodavaisi ◽

Ahmad Ezzati-Shourgoli

Keyword(s):

Economic Growth ◽

Regression Model ◽

Government Size ◽

Threshold Regression ◽

Linear Threshold ◽

Non Linear ◽

Threshold Regression Model ◽

New Evidence ◽

The Relationship

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Investigating the effects of fiscal and monetary policy on economic performance: Dynamic panel threshold regression analysis

10.1063/1.5136390 ◽

2019 ◽

Author(s):

Siti Fatimah Ismail ◽

Siok Kun Sek

Keyword(s):

Monetary Policy ◽

Regression Analysis ◽

Economic Performance ◽

Threshold Regression ◽

Dynamic Panel ◽

Fiscal And Monetary Policy ◽

Panel Threshold Regression

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Threshold Effect of Tourism Development on Economic Growth Following a Disaster Shock: Evidence from the Wenchuan Earthquake, P.R. China

Sustainability ◽

10.3390/su11020371 ◽

2019 ◽

Vol 11 (2) ◽

pp. 371 ◽

Cited By ~ 11

Author(s):

Jun Zhang ◽

Li Cheng

Keyword(s):

Economic Growth ◽

Wenchuan Earthquake ◽

Fixed Effects ◽

Industrial Structure ◽

Tourism Development ◽

Threshold Effect ◽

Development Stage ◽

Threshold Regression ◽

Fixed Effects Model ◽

Panel Threshold Regression

To examine whether tourism can effectively stimulate economic growth following a disaster shock, we apply a panel threshold regression technique to test the threshold effect of tourism development on economic growth of the 36 Wenchuan earthquake-affected counties in 2008–2016. The empirical results using the panel fixed-effects model show that tourism significantly contributes to economic growth, supporting the validity of the tourism-led growth hypothesis (TLGH) for the disaster-affected destinations. The results of the panel threshold regression model also indicate a threshold effect of tourism development on economic growth, implying that counties with different conditions of tourism specialization and industrial structure experience different impacts on the tourism-growth nexus. Specifically, the estimated coefficients of tourism on economic growth decrease with the levels of tourism specialization and industrial structure exceeding the threshold value. Based on the Tourism Area Life Cycle theory (TALC), we further divide the 36 disaster-stricken counties into six types based on the evolution of tourism specialization: Exploration-stage type, involvement-stage type, transition-stage type, development-stage type, consolidation-stage type, and stagnation-stage type. The empirical findings and managerial implications discussed are generally applicable to policymakers seeking new ways to invigorate the economy in other disaster-affected destinations.

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Growth threshold-effect on renewable energy consumption in major oil-producing countries in sub-Saharan Africa: a dynamic panel threshold regression estimation

International Journal of Energy Sector Management ◽

10.1108/ijesm-04-2020-0004 ◽

2020 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Idris Abdullahi Abdulqadir

Keyword(s):

Energy Consumption ◽

Threshold Effect ◽

Sub Saharan Africa ◽

Threshold Regression ◽

Renewable Energy Consumption ◽

Dynamic Panel ◽

Content Type ◽

Sub Saharan ◽

Panel Threshold Regression ◽

Growth Threshold

Purpose This study aims to explore the relationship between the growth threshold effect on renewable energy consumption (REC) in the major oil-producing countries in sub-Saharan Africa (SSA) over the period 1990–2018. Design/methodology/approach This article used a dynamic panel threshold regression model introduced by Hansen (1996, 1999 and 2000) threshold (TR) models. The procedure is achieved using 5,000 bootstrapping replications and the grid search to obtain the asymptotic distribution and p-values. For the long-run relationship among our variables, the author followed the process in Pesaran et al. (1999) pooled mean group (PMG) for heterogeneous panels. Furthermore, for the robustness of our empirical results due to the sensitivity of the results to outliers, the author used the approach by Cook (1979) distance measure. The author applied quantile (QR) regression to explore the distribution of dependent variables following Bassett and Koenker (1982) and Koenker and Bassett (1978) approaches. Findings The results from the threshold effect test and threshold regression revealed a significant single threshold effect of growth level on REC. Furthermore, the result from the PMG estimation showed the growth of the variable, energy intensity, consumer prices and CO2 emissions play a significant role in REC in major oil-producing countries in SSA. The growth threshold estimation results indicated one significant threshold value of 1.013% at one period lagged of real growth. The outlier’s sensitivity detention greatly influenced our empirical results. Originality/value The article filled the literature gap by applying a combined measure that is robustness to detect outliers in the data, which none of the studies in the literature addresses hitherto. Further, the article extends the quantile regression to growth – REC literature.

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