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Identifying multiple regimes in the model of credit to households

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Abstract

This research proposes a new method to identify the differing states of the market with respect to lending to households. We use an econometric multi-regime regression model where each regime is associated with a different economic state of the credit market (i.e. a normal regime or a boom regime). The credit market alternates between regimes when some specific variable increases above or falls below the estimated threshold level. A new method for estimating multi-regime threshold regression models for dynamic panel data is also demonstrated.

Suggested Citation

  • Dobromil Serwa, 2011. "Identifying multiple regimes in the model of credit to households," NBP Working Papers 99, Narodowy Bank Polski.
    • Handle: RePEc:nbp:nbpmis:99
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    Cited by:

    1. Michal Rubaszek & Dobromil Serwa, 2011. "Determinants of credit to households in a life-cycle model," NBP Working Papers 92, Narodowy Bank Polski.
    2. Dobromił Serwa, 2013. "Measuring Non-Performing Loans During (and After) Credit Booms," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 5(3), pages 163-183, September.
    3. Rubaszek, Michał & Serwa, Dobromił, 2014. "Determinants of credit to households: An approach using the life-cycle model," Economic Systems, Elsevier, vol. 38(4), pages 572-587.

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    More about this item

    Keywords

    credit boom; threshold regression; dynamic panel;
    All these keywords.

    JEL classification:

    • E51 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Money Supply; Credit; Money Multipliers
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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