Financial dollarization: The role of foreign-owned banks and interest rates

Basso, Henrique S.; Calvo-Gonzalez, Oscar; Jurgilas, Marius

doi:10.1016/j.jbankfin.2010.11.018

Cited by 108 publications

(109 citation statements)

References 19 publications

(33 reference statements)

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“…By testing these hypotheses with bank-level data for a broad set of transition economies, we provide micro-evidence on FX lending to both firms and households and complement cross-country studies of aggregate FX lending such as Luca and Petrova (2008) and Basso et al (2010), firm-level and household-level studies such as Brown et al (2011) and Fidrmuc et al (2011), as well as bank-level studies for individual countries such as Brown et al (2010) and Degryse et al (2011).…”

Section: Bank Ownership and Client Structurementioning

confidence: 90%

“…Basso et al (2010) examine aggregate credit dollarization for 24 transition countries for the period [2000][2001][2002][2003][2004][2005][2006]. They find that countries in which banks have a higher share of foreign funding display a higher share of FX loans.…”

Section: Bank Fundingmentioning

confidence: 99%

“…Surprisingly, the widespread view that FX lending in Eastern Europe is driven by foreign bank subsidiaries with access to ample FX funding has not yet been substantiated by empirical analysis. Comparisons of cross-country data document higher shares of FX lending in countries where banks have larger cross-border liabilities (Bakker and Gulde, 2010;Basso et al, 2010). However, whether such liabilities are causing or being caused by FX loans is hard to establish from aggregate data.…”

mentioning

confidence: 99%

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Foreign banks and foreign currency lending in emerging Europe

Brown

Haas

2012

Economic Policy

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SUMMARYBased on survey data from 193 banks in 20 countries we provide the first bank-level analysis of the relationship between bank ownership, bank funding and foreign currency (FX) lending across emerging Europe. Our results contradict the widespread view that foreign banks have been driving FX lending to retail clients as a result of easier access to foreign wholesale funding. Our cross-sectional analysis shows that foreign banks do lend more in FX to corporate clients but not to households. Moreover, we find no evidence that wholesale funding had a strong causal effect on FX lending for either foreign or domestic banks. Panel estimations show that the foreign acquisition of a domestic bank does lead to faster growth in FX lending to households. However, this is driven by faster growth in household lending in general not by a shift towards FX lending.-Martin Brown and Ralph De Haas

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Section: Bank Ownership and Client Structurementioning

confidence: 90%

Section: Bank Fundingmentioning

confidence: 99%

mentioning

confidence: 99%

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Foreign banks and foreign currency lending in emerging Europe

Brown

Haas

2012

Economic Policy

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“…Another example might be the existence of an implicit government guarantee to bail out debtors in case of depreciation. For detailed discussion of these mechanisms, see Basso et al (2007) or Ranciere et al (2010). The availability of cheaper FX loans also improves the balance sheet of borrowers (see Ranciere et al, 2010).…”

Section: Abstract öSszefoglalómentioning

confidence: 99%

Corporate foreign currency borrowing and investment: The case of Hungary

Endresz

Harasztosi

2014

Emerging Markets Review

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte.

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“…Zettelmeyer et al 2010;Bethlendi 2011;Király -Banai 2012;Hudecz 2013). Basso et al (2007) established that, among other factors, an easy access to foreign currency financing, large interest rate differentials between domestic and foreign currencies, and the openness of economies all shifted households' focus to foreign currency borrowing. All these factors were prominently present in Hungary at the time.…”

Section: Relevant Literaturementioning

confidence: 99%

Modelling probability of default and optimal PTI level by using a household survey

Balás

Banai

Hosszú³

2015

Acta Oeconomica

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The risks of household lending are still a major issue in Hungarian banking. The proportion of nonperforming loans is rising continuously. We constructed a model to fi nd those factors which have signifi cant effect on the probability of default of households' mortgages. We also used this model to calibrate the optimal level of household mortgages' payment-to-income ratios, which is important from a regulatory point of view. Our results show that the denomination of the loan and the indebtedness of the household are crucial factors in the performance of the loan. We also show that loans contracted via agents are riskier than others. The results carry two important messages from a regulatory perspective. Prescribing the same payment-to-income (PTI) ratios for HUF and FX loans may be unnecessarily restrictive for the former and excessively permissive for the latter. The uniform regulation of households with different income levels may also lead to undesired anomalies. JEL classifi cation indices: E58, G01, G21Keywords: FX lending, probability of default, payment-to-income ratio, bank regulation *We are grateful to the two anonymous reviewers for their valuable comments and suggestions.

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Financial dollarization: The role of foreign-owned banks and interest rates

Cited by 108 publications

References 19 publications

Foreign banks and foreign currency lending in emerging Europe

Foreign banks and foreign currency lending in emerging Europe

Corporate foreign currency borrowing and investment: The case of Hungary

Modelling probability of default and optimal PTI level by using a household survey

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