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An Application of Smooth Transition Regression Models to Homeless Research

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  • Jadidzadeh, Ali

Abstract

This article discusses the limitations of linear models in explaining certain aspects of homelessness-related data and proposes the use of nonlinear models to allow for state-dependent or regime-switching behavior. The threshold autoregressive (TAR) model and its smooth transition autoregressive (STAR) extensions are introduced as a popular class of nonlinear models. The article explains how these models can be applied to univariate time series data to investigate variations in weather conditions on the flow of homeless shelters over time. The objective is to identify the sensitivity of publicly-funded emergency shelter use to changes in weather conditions and better inform social agencies and government funders of predictable and unpredictable changes in demand for shelter beds. The smooth transition regression (STR) model is proposed as a useful tool for investigating nonlinearities in non-autoregressive contexts using both time series and panel data. The article concludes by highlighting the advantages of STR models and their three-stage modeling procedure: model specification, estimation, and evaluation.

Suggested Citation

  • Jadidzadeh, Ali, 2022. "An Application of Smooth Transition Regression Models to Homeless Research," MPRA Paper 116356, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:116356
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    File URL: https://mpra.ub.uni-muenchen.de/116356/1/MPRA_paper_116356.pdf
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    References listed on IDEAS

    as
    1. Dick van Dijk & Timo Terasvirta & Philip Hans Franses, 2002. "Smooth Transition Autoregressive Models — A Survey Of Recent Developments," Econometric Reviews, Taylor & Francis Journals, vol. 21(1), pages 1-47.
    2. Raphael Espinoza & Hyginus Leon & Ananthakrishnan Prasad, 2012. "When Should We Worry about Inflation?," The World Bank Economic Review, World Bank, vol. 26(1), pages 100-127.
    3. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521779654.
    4. Maria Hanratty, 2017. "Do Local Economic Conditions Affect Homelessness? Impact of Area Housing Market Factors, Unemployment, and Poverty on Community Homeless Rates," Housing Policy Debate, Taylor & Francis Journals, vol. 27(4), pages 640-655, July.
    5. Fischer, Stanley, 1993. "The role of macroeconomic factors in growth," Journal of Monetary Economics, Elsevier, vol. 32(3), pages 485-512, December.
    6. Hany Fahmy, 2014. "Modelling nonlinearities in commodity prices using smooth transition regression models with exogenous transition variables," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 23(4), pages 577-600, November.
    7. By Mohsin S. Khan & Abdelhak S. Senhadji, 2001. "Threshold Effects in the Relationship Between Inflation and Growth," IMF Staff Papers, Palgrave Macmillan, vol. 48(1), pages 1-1.
    8. Ali Jadidzadeh & Ron Kneebone, 2015. "Shelter from the Storm: Weather-Induced Patterns in the use of Emergency Shelters," SPP Research Papers, The School of Public Policy, University of Calgary, vol. 8(6), February.
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    More about this item

    Keywords

    Homelessness; nonlinear models; smooth transition regression (STR) model.;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty

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