Housing finance and real-estate booms: A cross-country perspective

Cerutti, Eugenio; Dagher, Jihad; Dell’Ariccia, Giovanni

doi:10.1016/j.jhe.2017.02.001

“…Huber (2016) provides further evidence on this relation based on turning point analysis for a sample of 18 OECD countries. The study confirms that home ownership rates are a key determinant of cross-country differences, being more important than characteristics of mortgage markets such as loan-to-value and mortgage-to-GDP ratios (see also Cerutti, Dagher, & Dell'Ariccia, 2015). 8 Third, estimating the GDP cycle jointly with financial series in a multivariate context emphasizes a medium-term component in the GDP cycle that is not fully present in the univariate estimates.…”

Section: Figuresupporting

confidence: 63%

Business, housing, and credit cycles

Rünstler

¹

,

Vlekke

²

2017

J of Applied Econometrics

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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. Note: This Working Paper should not be reported as representing the views of the European Central Bank (ECB). The views expressed are those of the authors and do not necessarily reflect those of the ECB. Terms of use: Documents in AbstractWe use multivariate unobserved components models to estimate trend and cyclical components in GDP, credit volumes and house prices for the U.S. and the five largest European economies. With the exception of Germany, we find large and long cycles in credit and house prices, which are highly correlated with a medium-term component in GDP cycles. Differences across countries in the length and size of cycles appear to be related to the properties of national housing markets. The precision of pseudo real-time estimates of credit and house price cycles is roughly comparable to that of GDP cycles. Studies have so far mostly used univariate non-parametric methods, i.e. band-pass filters and turning point analysis, to extract financial cycles. These methods require a priori assumptions on cyclical characteristics and are applied separately to each series. They are therefore not particularly suitable for assessing cyclical co-movements and evaluating the cyclical stance in real-time.Multivariate STSMs do not suffer from these shortcomings. We propose various modifications of the standard STSM to jointly model the cyclical dynamics in GDP and the financial series.In line with earlier studies, we find pronounced cycles in credit and house prices with a length of 12 to 18 years in most cases. There also arise important differences across countries. We find cycles to be particularly long and large for the U.K. and Spain, of more moderate length and size for the U.S., Italy, and France, and comparatively short and small for Germany. These differences turn out to be related to a specific structural characteristic of national housing markets: cycles are longer and larger for countries with high rates of private home ownership.Moreover, financial cycles are closely related to a medium-term component in the GDP cycle.More precisely, the multivariate estimates emphasize the presence of medium-term fluctuations in GDP, which are longer than the traditional business cycle (3 to 8 years). We find high correlations between the financial and GDP cycles in the medium term, but more moderate correlations over the business cycle. While previous studies have documented that peaks and troughs in financial cycles coincide with major turning points in ...

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“…These housing booms were not isolated incidents: Cerutti et al (2015) document 85 housing booms across 53 countries between 1970 and 2012. However, should governments be worried about such asset price movements?…”

Section: Introductionmentioning

confidence: 99%

House prices and macroprudential policy in an estimated DSGE model of New Zealand

Funke¹,

Kirkby

²

,

Mihaylovski³

2018

Journal of Macroeconomics

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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. We analyse the effects of macroprudential and monetary policies and their interactions using an estimated dynamic stochastic general equilibrium (DSGE) model tailored to New Zealand. We find that the main historical drivers of house prices are shocks specific to the housing sector. While our estimates show that monetary policy has large spillover effects on house prices, it does not appear to have been a major driver of house prices in New Zealand. We consider macroprudential policies, including the loan-to-value restrictions that have been implemented in New Zealand. We find that loan-to-value restrictions reduce house prices with negligible effects on consumer prices, suggesting that they can be used without derailing monetary policy. We estimate that the loan-to-value restrictions imposed in New Zealand in 2013 reduced house prices by 3.8 per cent and that greater forward guidance on their duration would have made them more effective. Terms of use: Documents inJEL-Codes: E320, E440, E520, E580.

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“…Finally, we add a set of institutional and housing market characteristics proposed by Cerutti, Dagher, and Dell'Ariccia (2017). Specifically, we use information on loan-to-value caps and the legal rights index.…”

Section: Methods and Datamentioning

confidence: 99%

Determinants of housing bubbles' duration in OECD countries

Amador-Torres

¹

,

Gómez-González

²

,

Sanín-Restrepo

³

2018

International Finance

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We study the determinants of housing price bubbles' duration for a set of OECD countries between 1970 and 2015. Our topic of study is of major importance, as duration is a proxy for other dimensions, such as the magnitude of bubbles, the extent of macroeconomic imbalances, and the chance that a rational bubble turns into an irrational one. We answer two related questions: (i) Does prolonged domestic monetary‐policy easing increase the duration of housing price bubbles? (ii) Does prolonged monetary‐policy easing in the United States influence the housing bubbles' duration in other OECD countries? We show that the answer to the first question is a clear yes but that the answer to the second question is not as clear. Our main result is that monetary‐policy tightening can accelerate the termination of a housing bubble. In this sense, our findings provide support for ‘leaning against the wind’ policies.

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Housing finance and real-estate booms: A cross-country perspective

Abstract: , and many IMF staff for helpful suggestions and help in the collection of data. Andreas Schaab and Yangfan Sun (data and coding) and Helen Hwang (editing) provided excellent assistance.

Cited by 184 publications

References 27 publications

Business, housing, and credit cycles

Business, housing, and credit cycles

House prices and macroprudential policy in an estimated DSGE model of New Zealand

Determinants of housing bubbles' duration in OECD countries

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