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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.

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Bibliographic Info

Paper provided by National Bank of Poland, Economic Institute in its series National Bank of Poland Working Papers with number 99.

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Length: 28
Date of creation: 2011
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Handle: RePEc:nbp:nbpmis:99

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Keywords: credit boom; threshold regression; dynamic panel;

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  1. Aaron Tornell & Frank Westermann, 2002. "Boom-Bust Cycles in Middle Income Countries: Facts and Explanation," CESifo Working Paper Series 755, CESifo Group Munich.
  2. Backé, Peter & Wójcik, Cezary, 2008. "Credit booms, monetary integration and the new neoclassical synthesis," Journal of Banking & Finance, Elsevier, vol. 32(3), pages 458-470, March.
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  24. Bai, Jushan & Kao, Chihwa & Ng, Serena, 2009. "Panel cointegration with global stochastic trends," Journal of Econometrics, Elsevier, vol. 149(1), pages 82-99, April.
  25. Coricelli, Fabrizio & Mucci, Fabio & Revoltella, Debora, 2006. "Household Credit in the New Europe: Lending Boom or Sustainable Growth?," CEPR Discussion Papers 5520, C.E.P.R. Discussion Papers.
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Cited by:
  1. Rubaszek, Michał & Serwa, Dobromil, 2012. "Determinants of credit to households in a life-cycle model," Working Paper Series 1420, European Central Bank.
  2. Dobromił Serwa, 2013. "Measuring Non-Performing Loans During (and After) Credit Booms," Central European Journal of Economic Modelling and Econometrics, CEJEME, vol. 5(3), pages 163-183, September.

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