Development of Sport Tourism Attraction in Small Town

Latif, Rohaizah Abd.; Abidin, Rohaizah Abd Latif

doi:10.34218/ijm.11.12.2020.042

Cited by 1 publication

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“…Whereas, a 1% decline in economic growth will upsurge unemployment by 0.053% in the long-run term. Latif et al (2021) tried to study the relationship among the two variables in Pakistan over the period 1972-2019 using the ARDL model. As a result, the outcomes concluded to the existence of the inverse linkage but with a very low intensity of association.…”

Section: Literature Reviewmentioning

confidence: 99%

Testing the Validity of Okun’s Law in Algeria: Is there a difference between Maki’s Cointegration and Quantile’s Regression Results?

Chenini

Ayad²,

Attouchi

et al. 2023

Folia Oeconomica Stetinensia

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Research background This paper examines the existence of Okun’s law in Algeria over the period of 1970–2020 using both the gap and differences model. Purpose The main objective of this paper is to econometrically examine, explore and test the nexus among unemployment rate and economic growth, in order to have a clear explanation about unemployment in Algeria. Research methodology Firstly, the Kapetanios unit root test and Maki cointegration test are employed for the gap model to deal with the structural breaks than the estimation of the coefficients in this case, secondly, the quantile regression is used for the differences model; finally, three categories of causality tests are used in this research. Results The findings revealed that unemployment rates are not affected by output over the period of study both in the gap and differences model. Hence, Okun’s law is not held in Algeria. Novelty The study focused on Okun’s law in different ways. This latter carries out structural breaks in both the unit root and co-integration analysis. On the other hand, the study uses the quantile regression for the first time in the examination of Okun’s law. In the same line of thought, this research introduces an asymmetric analysis in the Maki cointegration and quantile regression.

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Section: Literature Reviewmentioning

confidence: 99%