<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>In this study, investigation of the economic growth of the Organization for Economic Cooperation and Development (OECD) countries and the countries in different income groups in the World Data Bank is conducted by using causality analyses and Generalized Estimating Equations (GEEs) which is an extension of Generalized Linear Models (GLMs). Eight different macro-economic, energy and environmental variables such as the gross domestic product (GDP) (current US$), CO<sub>2</sub> emission (metric tons per capita), electric power consumption (kWh per capita), energy use (kg of oil equivalent per capita), imports of goods and services (% of GDP), exports of goods and services (% of GDP), foreign direct investment (FDI) and population growth rate (annual %) have been used. These countries have been categorized according to their OECD memberships and income groups. The causes of the economic growth of these countries belonging to their OECD memberships and income groups have been determined by using the Toda-Yamamoto causality test. Furthermore, various GEE models have been established for the economic growth of these countries belonging to their OECD membership and income groups in the aspect of the above variables. These various GEE models for the investigation of the economic growth of these countries have been compared to examine the contribution of the causality analyses to the statistical model establishment. As a result of this study, the highlight is found as the use of causally-related variables in the causality-based GEE models is much more appropriate than in the non-causality based GEE models for determining the economic growth profiles of these countries.</p>
</abstract>

In this study, investigation of the economic growth of the Organization for Economic Cooperation and Development (OECD) countries and the countries in different income groups in the World Data Bank is conducted by using causality analyses and Generalized Estimating Equations (GEEs) which is an extension of Generalized Linear Models (GLMs). Eight different macro-economic, energy and environmental variables such as the gross domestic product (GDP) (current US$), CO2 emission (metric tons per capita), electric power consumption (kWh per capita), energy use (kg of oil equivalent per capita), imports of goods and services (% of GDP), exports of goods and services (% of GDP), foreign direct investment (FDI) and population growth rate (annual %) have been used. These countries have been categorized according to their OECD memberships and income groups. The causes of the economic growth of these countries belonging to their OECD memberships and income groups have been determined by using the Toda-Yamamoto causality test. Furthermore, various GEE models have been established for the economic growth of these countries belonging to their OECD membership and income groups in the aspect of the above variables. These various GEE models for the investigation of the economic growth of these countries have been compared to examine the contribution of the causality analyses to the statistical model establishment. As a result of this study, the highlight is found as the use of causally-related variables in the causality-based GEE models is much more appropriate than in the non-causality based GEE models for determining the economic growth profiles of these countries.

Some Generalized Estimating Equations Models Based on Causality Tests for Investigation of The Economic Growth of The Country Groups

Faculty of Veterinary Medicine, Department of Biostatistics

Faculty of Science, Department of Statistics

Foundations of Computing and Decision Sciences

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

In this study, investigation of the economic growth of the Organization for Economic Cooperation and Development (OECD) countries and the countries in...

Some Generalized Estimating Equations Models Based on Causality Tests for Investigation of The Economic Growth of The Country Groups

Online veröffentlicht: 17. Sept. 2021

Seitenbereich: 297 - 315

Eingereicht: 23. Juni 2020

Akzeptiert: 30. Aug. 2021

DOI: https://doi.org/10.2478/fcds-2021-0019

Schlüsselwörter
Economic Growth, Organization for Economic Cooperation and Development, Causality Analyses, Generalized Estimating Equations, Generalized Linear Model, Toda-Yamamoto Causality Test

© 2021 Harun Yonar et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Some Generalized Estimating Equations Models Based on Causality Tests for Investigation of The Economic Growth of The Country Groups

Online veröffentlicht: 17. Sept. 2021

Seitenbereich: 297 - 315

Eingereicht: 23. Juni 2020

Akzeptiert: 30. Aug. 2021

DOI: https://doi.org/10.2478/fcds-2021-0019

SchlüsselwörterEconomic Growth, Organization for Economic Cooperation and Development, Causality Analyses, Generalized Estimating Equations, Generalized Linear Model, Toda-Yamamoto Causality Test

© 2021 Harun Yonar et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Schlüsselwörter
Economic Growth, Organization for Economic Cooperation and Development, Causality Analyses, Generalized Estimating Equations, Generalized Linear Model, Toda-Yamamoto Causality Test