Comparison of Business Environments in Oil-Rich MENA Countries: A Clustering Analysis of Economic Diversification and Performance

Aker, Şule L.; Aghaei, İman

doi:10.1080/1540496x.2018.1537185

Cited by 15 publications

(6 citation statements)

References 37 publications

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“…Harding & Javorcik (2011) focus on FDI [13], Aker and Aghaei (2019) [14] on the business environment, Olander (2019) [15] focuses on institutional quality, and Matallah (2020) [16] on the relationship between governance indicators and economic diversification.…”

Section: Literature Reviewmentioning

confidence: 99%

Driving Factors of Economic Diversification in Resource-Rich Countries via Panel Data Evidence

2022

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Economic diversification is an essential aspect of sustainable development as diversification enhances macroeconomic stability and promotes structural and long-term transformation not only in the economy but also in other pillars of development such as social institutions and dimensions. There is empirical evidence suggesting an impact of economic and structural factors on diversification. However, there is no consensus on the results in the literature because of various factors, such as the employment of different variables, methodologies, countries, and periods. This paper empirically explores the relations driving economic diversification in 14 resource-rich countries between 2001 and 2019, with six alternative models. In this regard, feasible generalized least squares regression was employed for the proposed model specifications. It provides strong evidence that gross capital formation, financial development, labor force participation, education, and the rule of law have statistically significant and positive impacts on economic diversification performance. On the other hand, inward foreign direct investment, real GDP growth, and self-employment rate also have statistically significant, but negative, impacts on economic diversification, probably because they further promote or are a result of resource-based growth rather than diversification into other technology- and knowledge-based sectors.

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Section: Literature Reviewmentioning

confidence: 99%

Driving Factors of Economic Diversification in Resource-Rich Countries via Panel Data Evidence

2022

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“…Although unsupervised classification techniques are not commonly used in economics, examples include defining economic regions (Crone, 2005;Mimis & Georgiadis, 2013), and analysis of energy policy (Aker & Aghaei, 2019;Liu et al, 2016;Xu et al, 2020). The approach is highlighted in the paper Machine Learning Methods That Economists Should Know About (Athey & Imbens, 2019).…”

Section: Data (Representation)mentioning

confidence: 99%

A Data-Driven Algorithm to Redefine the U.S. Rural Landscape: Affinity Propagation as a Mixed-Data/Mixed-Method Tool

Heumann

Graziano

Fiaschetti

2022

Economic Development Quarterly

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This study demonstrates the application of affinity propagation as a data-driven approach to identifying and mapping typologies of place along the urban-rural continuum. The authors characterize Zip Code Tabulation Areas using demographic, economic, land cover, and accessibility to transportation infrastructure, which results in 22 clusters, 15 of which have a major rural component. The spatial pattern of these clusters varies, reflecting the heterogeneity in U.S. rurality. Rural is not a single concept that can be simply defined by population density. By comparing three economic indicators before and after the global financial crisis of 2007 to 2012, the authors find that the degree of economic recovery is captured by rural typologies. They compare both the methodological results and analysis of socioeconomic resilience to two of the most used threshold-based regional typologies, one developed by the U.S. Department of Agriculture Economic Research Service and one used by the American Communities Project.

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“…Seçilen uzaklık ölçütü, iki elementin ( , ) benzerliğinin nasıl hesaplandığını ve kümelerin şeklini nasıl etkileyeceğini tanımlamaktadır. Öklid uzaklık ölçütü, Manhattan uzaklık ölçütü veya Minkowski uzaklık ölçütü gibi birçok uzaklık ölçütü bulunsa da uygulamada en çok popüler olan ve kullanılan uzaklık ölçütü Öklid uzaklık ölçütüdür (Repkine, 2012: 35;Huskinson & Lawson, 2014: 1071Hiziroglu vd., 2018: 159;Aker & Aghaei, 2019: 2876Tunalı & Aytekin, 2017: 107;Bulum vd., 2013: 156;Zontul vd., 2004: 53). Bu çalışma kapsamında kullanılan tüm kümeleme yöntemlerinde Öklid uzaklık ölçütü kullanılmış olup bu ölçüt şu şekilde tanımlanmaktadır:…”

Section: Veriunclassified

Dış Ticaret Verileri İçin Kümeleme Analizi: Türkiye, Azerbaycan ve Kazakistan Örneği

Çilgin

Kurt

2021

Sosyoekonomi

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Foreign trade is one of the most critical sources of welfare. Factors such as population, per capita income, and the distance between countries is among the crucial determinants of foreign trade. This paper aims to cluster the data set regarding the export and import of Turkey and Turkic Republics by considering other determinants of foreign trade for 2017. In this study, Kazakhstan and Azerbaijan, of which data sets are available, are considered, and Turkey. For this paper, K-means, Ward hierarchical clustering, and self-organizing maps are used. The findings of this paper present detailed evidence as to the export and import of the countries handled.

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Comparison of Business Environments in Oil-Rich MENA Countries: A Clustering Analysis of Economic Diversification and Performance

Cited by 15 publications

References 37 publications

Driving Factors of Economic Diversification in Resource-Rich Countries via Panel Data Evidence

Driving Factors of Economic Diversification in Resource-Rich Countries via Panel Data Evidence

A Data-Driven Algorithm to Redefine the U.S. Rural Landscape: Affinity Propagation as a Mixed-Data/Mixed-Method Tool

Dış Ticaret Verileri İçin Kümeleme Analizi: Türkiye, Azerbaycan ve Kazakistan Örneği

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