Dynamics of global economic growth: a Bayesian exploration of basic and augmented Solow models
The Solow growth model has long served as a cornerstone in economic theory, offering critical insights for formulating growth policies. Nevertheless, its principal limitation is the omitted variable bias arising from the inclusion of constant exogenous variables. Furthermore, the frequentist framewo...
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Taylor & Francis Group
2025-12-01
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| Series: | Cogent Economics & Finance |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/23322039.2025.2452891 |
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| author | Nguyen Thi My Diem Nguyen Ngoc Thach |
| author_facet | Nguyen Thi My Diem Nguyen Ngoc Thach |
| author_sort | Nguyen Thi My Diem |
| collection | DOAJ |
| description | The Solow growth model has long served as a cornerstone in economic theory, offering critical insights for formulating growth policies. Nevertheless, its principal limitation is the omitted variable bias arising from the inclusion of constant exogenous variables. Furthermore, the frequentist framework's susceptibility to multicollinearity complicates the incorporation of multiple variables. In addressing these challenges, Bayesian methods present a compelling alternative. This study rigorously examines both the basic and augmented Solow growth models using a Bayesian non-linear approach applied to a global panel dataset spanning 1970 to 2019. The results demonstrate that the augmented Solow model, which incorporates heterogeneous population growth, savings, technology, and depreciation rates, significantly outperforms the basic model in predictive accuracy. Crucially, the elasticity of output with respect to capital, as estimated through this advanced econometric approach, aligns more closely with widely accepted empirical values. These findings reaffirm the validity of the Solow growth model when evaluated with enhanced econometric techniques and high-quality data. The study’s implications are particularly relevant for policymakers, who are encouraged to leverage the insights provided by the augmented model. Specifically, strategies such as increasing investment, fostering technological innovation, enhancing human capital, and optimizing resource allocation should be prioritized to drive sustainable economic growth. |
| format | Article |
| id | doaj-art-e8294021389e4f118b4ad4176867d9a4 |
| institution | Kabale University |
| issn | 2332-2039 |
| language | English |
| publishDate | 2025-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Cogent Economics & Finance |
| spelling | doaj-art-e8294021389e4f118b4ad4176867d9a42025-01-21T07:02:03ZengTaylor & Francis GroupCogent Economics & Finance2332-20392025-12-0113110.1080/23322039.2025.2452891Dynamics of global economic growth: a Bayesian exploration of basic and augmented Solow modelsNguyen Thi My Diem0Nguyen Ngoc Thach1Faculty of Finance and Banking, Ho Chi Minh City Open University, Ho Chi Minh City, VietnamHo Chi Minh University of Banking, Ho Chi Minh City, VietnamThe Solow growth model has long served as a cornerstone in economic theory, offering critical insights for formulating growth policies. Nevertheless, its principal limitation is the omitted variable bias arising from the inclusion of constant exogenous variables. Furthermore, the frequentist framework's susceptibility to multicollinearity complicates the incorporation of multiple variables. In addressing these challenges, Bayesian methods present a compelling alternative. This study rigorously examines both the basic and augmented Solow growth models using a Bayesian non-linear approach applied to a global panel dataset spanning 1970 to 2019. The results demonstrate that the augmented Solow model, which incorporates heterogeneous population growth, savings, technology, and depreciation rates, significantly outperforms the basic model in predictive accuracy. Crucially, the elasticity of output with respect to capital, as estimated through this advanced econometric approach, aligns more closely with widely accepted empirical values. These findings reaffirm the validity of the Solow growth model when evaluated with enhanced econometric techniques and high-quality data. The study’s implications are particularly relevant for policymakers, who are encouraged to leverage the insights provided by the augmented model. Specifically, strategies such as increasing investment, fostering technological innovation, enhancing human capital, and optimizing resource allocation should be prioritized to drive sustainable economic growth.https://www.tandfonline.com/doi/10.1080/23322039.2025.2452891Thoughtful Bayesian non-linear analysisomitted variable biasmulticollinearitybasic Solow modelaugmented Solow modelglobal sample |
| spellingShingle | Nguyen Thi My Diem Nguyen Ngoc Thach Dynamics of global economic growth: a Bayesian exploration of basic and augmented Solow models Cogent Economics & Finance Thoughtful Bayesian non-linear analysis omitted variable bias multicollinearity basic Solow model augmented Solow model global sample |
| title | Dynamics of global economic growth: a Bayesian exploration of basic and augmented Solow models |
| title_full | Dynamics of global economic growth: a Bayesian exploration of basic and augmented Solow models |
| title_fullStr | Dynamics of global economic growth: a Bayesian exploration of basic and augmented Solow models |
| title_full_unstemmed | Dynamics of global economic growth: a Bayesian exploration of basic and augmented Solow models |
| title_short | Dynamics of global economic growth: a Bayesian exploration of basic and augmented Solow models |
| title_sort | dynamics of global economic growth a bayesian exploration of basic and augmented solow models |
| topic | Thoughtful Bayesian non-linear analysis omitted variable bias multicollinearity basic Solow model augmented Solow model global sample |
| url | https://www.tandfonline.com/doi/10.1080/23322039.2025.2452891 |
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