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Borrowing in foreign currency: Austrian households as carry traders

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  • Beer, Christian
  • Ongena, Steven
  • Peter, Marcel

Abstract

Household borrowing in a foreign currency is a widespread phenomenon in Austria. Thirteen percent of Austrian households report their housing loan to be denominated in foreign currency, mostly Swiss franc. Yet, despite its importance, peculiar character, and acute policy concerns, we know little about the attitudes and characteristics of the households involved in this type of carry trade. We analyze a uniquely detailed financial wealth survey of 2556 Austrian households to sketch a comprehensive profile of the attitudes and characteristics of the households involved. We employ both univariate tests and multivariate multinomial logit models. The survey data suggest that risk seeking, affluent, and married households are more likely to take a housing loan in a foreign currency. Financially literate or high-income households are more likely to take a housing loan in general. These findings partially assuage policy concerns about household default risk on foreign-currency housing loans or household retirement security.

Suggested Citation

  • Beer, Christian & Ongena, Steven & Peter, Marcel, 2010. "Borrowing in foreign currency: Austrian households as carry traders," Journal of Banking & Finance, Elsevier, vol. 34(9), pages 2198-2211, September.
  • Handle: RePEc:eee:jbfina:v:34:y:2010:i:9:p:2198-2211
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    More about this item

    Keywords

    Foreign currency borrowing Mortgages Banking sector Austria Swiss francs;

    JEL classification:

    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • F34 - International Economics - - International Finance - - - International Lending and Debt Problems
    • F37 - International Economics - - International Finance - - - International Finance Forecasting and Simulation: Models and Applications

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