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Construction of leading economic index for recession prediction using vine copulas

Author

Listed:
  • Lahiri Kajal

    (Department of Economics, University at Albany, SUNY, NY12222, USA. Tel.: +1 518 442 4758)

  • Yang Liu

    (School of Economics, Nanjing University, Nanjing, Jiangsu210093, PR China)

Abstract

This paper constructs a composite leading index for business cycle prediction based on vine copulas that capture the complex pattern of dependence among individual predictors. This approach is optimal in the sense that the resulting index possesses the highest discriminatory power as measured by the receiver operating characteristic (ROC) curve. The model specification is semi-parametric in nature, suggesting a two-step estimation procedure, with the second-step finite dimensional parameter being estimated by QMLE given the first-step non-parametric estimate. To illustrate its usefulness, we apply this methodology to optimally aggregate the 10 leading indicators selected by The Conference Board (TCB) to predict economic recessions in the United States. In terms of the discriminatory power, our method is significantly better than the Index used by TCB.

Suggested Citation

  • Lahiri Kajal & Yang Liu, 2021. "Construction of leading economic index for recession prediction using vine copulas," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 25(4), pages 193-212, September.
    • Handle: RePEc:bpj:sndecm:v:25:y:2021:i:4:p:193-212:n:4
    DOI: 10.1515/snde-2019-0033
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    Citations

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    Cited by:

    1. Kajal Lahiri & Cheng Yang, 2023. "ROC and PRC Approaches to Evaluate Recession Forecasts," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 19(2), pages 119-148, September.

    More about this item

    Keywords

    block bootstrap; leading economic index; receiver operating characteristic curve; vine copula; C14; C15; C32; C43; C51; C53; C37;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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