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08.01.2025

Threshold nonlinear relationship between defense spending and unemployment in different income level countries: evidence from panel smooth transition regression model

verfasst von: Syed Ali Raza, Maiyra Ahmed

Erschienen in: Quality & Quantity

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Abstract

This study identifies the threshold level of military spending on unemployment in 82 different income level countries, utilizing annual data from 1995 to 2020. We emphasize the slope parameter and threshold ratio by applying PSTR-panel smooth transition regression technique. Particularly, we applied linearity and no-linearity test to verify the linear/non-linear connection and number of regimes. The findings of this study suggest that in low-income countries, the connection between military spending and unemployment is positive in both regimes. While in middle-income countries, the relationship varies with the regimes as in the first regime, the connection between both the variables is negative, but in the second regime, the connection becomes positive. However, in high-income countries, the connection between the variables under consideration remains the same for the first and second regimes, which is negative. At the same time, the relationship between unemployment and GDP is negative, whereas the connection between population and inflation with unemployment is positive for all income level countries. The study’s outcome implies that government should allocate more resources to other sectors to enhance economic growth and employment in low and middle-income-level countries. In high-income countries, military spending helps reduce unemployment; therefore, if the government allocates a higher budget for military expenditure, it will eventually generate more employment opportunities, leading to economic prosperity.

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Metadaten
Titel
Threshold nonlinear relationship between defense spending and unemployment in different income level countries: evidence from panel smooth transition regression model
verfasst von
Syed Ali Raza
Maiyra Ahmed
Publikationsdatum
08.01.2025
Verlag
Springer Netherlands
Erschienen in
Quality & Quantity
Print ISSN: 0033-5177
Elektronische ISSN: 1573-7845
DOI
https://doi.org/10.1007/s11135-024-02041-2

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