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Time Series Models

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Handbook of Labor, Human Resources and Population Economics

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Abstract

This chapter surveys the conventional and recent literature on time series models for forecasting with special reference to labor market variables and the disruptions caused by the COVID-19 pandemic. Possible gains in nowcasting and backcasting using big data and a variety of machine learning models are illustrated.

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Author information

Authors and Affiliations

  1. Department of Economics, University at Albany – SUNY, Albany, NY, USA

    Kajal Lahiri

  2. Li Anmin Institute of Economic Research, Faculty of Economics, Liaoning University, Shenyang, China

    Cheng Yang

Authors
  1. Kajal Lahiri
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  2. Cheng Yang
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Correspondence to Kajal Lahiri .

Editor information

Editors and Affiliations

  1. UNU-MERIT & Princeton University, Maastricht, The Netherlands

    Klaus F. Zimmermann

Section Editor information

  1. Center for Policy Research; Institute of Labor Economics (IZA) and Global Labor Organization (GLO), Syracuse University, Syracuse, NY, USA

    Alfonso Flores-Lagunes

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Lahiri, K., Yang, C. (2022). Time Series Models. In: Zimmermann, K.F. (eds) Handbook of Labor, Human Resources and Population Economics. Springer, Cham. https://doi.org/10.1007/978-3-319-57365-6_53-1

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  • DOI: https://doi.org/10.1007/978-3-319-57365-6_53-1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-57365-6

  • Online ISBN: 978-3-319-57365-6

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