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Threshold mixed data sampling logit model with an application to forecasting US bank failures

Author

Listed:
  • Lixiong Yang

    (Lanzhou University
    Lanzhou University)

  • Mingjian Ren

    (Lanzhou University)

  • Jianming Bai

    (Lanzhou University)

Abstract

This paper introduces a threshold mixed data sampling logit (TM-logit) model, which allows for a threshold effect of independent variables sampled at different frequencies on the log-odds of dependent variable. We propose model estimation procedure and develop test statistics for relevance of high-frequency predictors, threshold effect, and equal weighting scheme. We also suggest a test statistic for the difference in forecasting accuracy between two competing models. We then extend the model to the framework with a covariate-dependent threshold (CDTM-logit) and propose estimation procedure and test statistic for threshold constancy. Monte Carlo simulations are conducted to assess the finite sample performance of the proposed estimation procedure and test statistics. The simulation results show that the estimation procedure performs well and test statistics have good size and power properties in finite samples. We apply the proposed model to predict US bank failures, and the empirical results indicate that the TM-logit and CDTM-logit models have good forecasting performance.

Suggested Citation

  • Lixiong Yang & Mingjian Ren & Jianming Bai, 2025. "Threshold mixed data sampling logit model with an application to forecasting US bank failures," Empirical Economics, Springer, vol. 68(1), pages 433-477, January.
    • Handle: RePEc:spr:empeco:v:68:y:2025:i:1:d:10.1007_s00181-024-02639-3
    DOI: 10.1007/s00181-024-02639-3
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    More about this item

    Keywords

    Logit; Threshold effect; Mixed data sampling (MIDAS); Estimation; Testing; Bank failures;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • 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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