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The similar faces of Swiss working Poor. An empirical analysis across Swiss regions using logistic regression and classification trees

Author

Listed:
  • Fabio Beniamino Losa

    (Office cantonal de la statistique du canton du Tessin, African Development Bank Group - African Development Bank Group)

  • Emiliano Soldini

    (Department of Business Management and Social Work - SUPSI - Scuola universitaria professionale della Svizzera italiana = University of Applied Sciences and Arts of Southern Switzerland [Manno])

Abstract

Are the determinants of working poverty the same across Swiss regions? Does the phenomenon primarily affect similar social groups from Zurich to Ticino and from the Lake Geneva Region to Eastern Switzerland? Or are there significant regional peculiarities in terms of risk factors and/or groups, calling for regional policies? The present paper – an empirical investigation into working poverty across the seven statistical regions in Switzerland – aims at providing answers to these questions by analysing the determinants of working poverty and by detecting the key characteristics of the population groups at major risk. Considering that at the bottom of the emergence of this social problem many see the rise of labour flexibility in the context of globalization and of the principle changes affecting labour markets, comparative empirical evidence is certainly a crucial element for policy design, especially in a federal system like Switzerland. Acknowledging that in order to assist policymakers in understanding and eventually defining suitable intervention measures it is of primary concern to be able to convey empirical evidence in a way which is both satisfying and easily understandable, two different multivariate statistical methods – logistic regression and classification trees – are applied in the analysis of the data. Due to their complementary characters, the combined use of these methods will prove very efficient in bringing research evidence closer to policy needs. The phenomenon of the working poor has come to attention in Switzerland since the economic slowdown of the 90s. The national report on poverty by LEU, BURRI and PRIESTER (1997) is considered, except for some initial contributions (most of them at cantonal level), the first milestonefor research on the topic. This report was followed by a series of studies which specifically tackle the issue of the working poor (e.g. DEUTSCH, FLÜCKIGER and SILBER, 1999; STREULI and BAUER, 2002). The present paper contributes, through its comparative and methodological approach, to this stream of research. The paper is organised into different sections. Following this introduction, section two tackles the question of defining working poverty, highlighting the complexity of this task and the resulting wide variety of definitions across countries and across different studies. It also describes the operational definition adopted by the Swiss Federal Statistical Office (FSO), which is the one usedin the empirical analysis. Section three presents the data, the models and the methodological approach. Section 4 is devoted to the results of the empirical applications. As a conclusion, the paper assesses the results in the light of implications for policy-making.

Suggested Citation

  • Fabio Beniamino Losa & Emiliano Soldini, 2011. "The similar faces of Swiss working Poor. An empirical analysis across Swiss regions using logistic regression and classification trees," Post-Print halshs-01182926, HAL.
  • Handle: RePEc:hal:journl:halshs-01182926
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    References listed on IDEAS

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    1. G. V. Kass, 1980. "An Exploratory Technique for Investigating Large Quantities of Categorical Data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 29(2), pages 119-127, June.
    2. Jean-Marc Falter, 2006. "Equivalence Scales and Subjective Data in Switzerland," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 142(II), pages 263-284, June.
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    More about this item

    Keywords

    working poor; classification trees; logistic regression;
    All these keywords.

    JEL classification:

    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty
    • J3 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs

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