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Unemployment and Suicide in the United States: The Import of Addressing Cross-Sectional Dependence

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  • Mitch Kunce

Abstract

Recent reviews of the sociological and economic-based ecological studies of suicide find cyclical unemployment to be a key suicide risk factor, though the evidence presented is mixed at best. The ambiguity of the ecological associations appear to stem from faulty statistical methodologies. Panel treatments offer advantages over conventional time-series methods by exploiting cross-section variation. However, if the added cross-section units are cointegrating (dependent) and independence is presumed, incorrect statistical inference and inconsistent coefficient estimation can result. Herein, we fully address the import of cross-sectional dependence on the ecological relationship between U.S. unemployment rates and suicide rates using an 81-year panel of the 48 contiguous states and the District of Columbia. When proper allowances are made for cross-section dependence at each step of the examination, we find no significant statistical association, short-run or long-run, running from unemployment to suicide rates in the U.S. Results of this sequential analysis highlight potential sources of the ambiguity found in the literature.

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  • Mitch Kunce, 2023. "Unemployment and Suicide in the United States: The Import of Addressing Cross-Sectional Dependence," Bulletin of Applied Economics, Risk Market Journals, vol. 10(1), pages 1-19.
    • Handle: RePEc:rmk:rmkbae:v:10:y:2023:i:1:p:1-19
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    More about this item

    Keywords

    Suicide rates; Cointegration; Cross-section dependence.;
    All these keywords.

    JEL classification:

    • B55 - Schools of Economic Thought and Methodology - - Current Heterodox Approaches - - - Social Economics
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C49 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Other

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