Shahzad, Shakeel
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The Most Powerful Test of Independence in W× K Contingency Tables for Ordinal Data Using Monte Carlo Simulations Shahzad, Shakeel; Khan, Saud Ahmed; Rehman, Atiq-Ur-
International Business and Accounting Research Journal Vol 8, No 2 (2024): July 2024
Publisher : Sekolah Tinggi Ekonomi dan Bisnis Islam Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35474/ibarj.v8i2.280

Abstract

This study aims to analyze the performance of tests of independence for ordinal data. Tests of independence is one of the most frequently used statistical tools in econometrics. Researchers are often interested about the independence of variable summarized in Contingency Tables. Many tests are available in literature to test independence in Contingency Tables, however, there is no clarity about the choice of tests which are incapable to provide comparison of large number of tests. A central problem and question facing researcher is to decide which tests of independence is most powerful for ordinal data. Most of the studies make pairwise comparison of tests and such studies are unable to guide about optimal test among a wide set of tests. This study used Monte Carlo Simulations (MCS) and compares seven popular tests of independence for ordinal data namely, Spearman  coefficient of correlation, Kendall’s , Kendall’s  coefficient, Goodman and Kruskal , Sumer’s D and Novel Phi_k . For ordinal data the stringency criteria cannot be applied to compare tests. Therefore, the comparison was made on the basis of power analysis and our MCS concludes based on solid estimations using power criterion that the most powerful test is Novel in  k CT’s for ordinal data.    
Artificial Intelligence and Economic Growth; Sustainable Development Challenges in Muslim World Shahzad, Shakeel; Ahmed Khan, Saud; Waheed, Taraq
IKONOMIKA Vol 10, No 2 (2025)
Publisher : Universitas Islam Negeri Raden Intan Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/cd6xct55

Abstract

While the world rushes to implement Artificial Intelligence (AI), there are some concerns that arise. AI has the capability to have an impact on economic expansion and the employment sector. The influence is assumed to be substantial, since increased productivity and lowered wages and prices combined with a high level of automation implies labor substitution. The widespread adoption of artificial intelligence has the potential to impact the global economy and specifically the Muslim world countries drastically. We studied the influence of AI over economic growth using mathematics, emphasizing the fact that AI is unlike any other production factor. Moreover, the study modified the production function as per the axioms of correct specification of the model and according the current situations. We have established AI's potential impacts on the economic growth. Nations with lower workforce ratios are expected to shift towards technology that increases labor productivity. On the other hand, capital productivity increasing technology can be used by nations grappling with the problems of an aging population. Care must be taken in determining the optimal deployment of models.