Does Housing Really Lead the Business Cycle

TLDR: In this article, the authors characterize the cyclical properties of Spanish real and nominal housing related variables and find that home prices are positively related to residential investment, suggesting the dominant role of demand factors over supply ones.

Abstract: The aim of this paper is to characterize the cyclical properties of Spanish real and nominal housing related variables. Our three main results are: First, housing appears to lead the business cycle. Second, fluctuation in home prices are positively related to those of residential investment, suggesting the dominant role of demand factors over supply ones. Third, there are interesting asymmetries in cyclical fluctuations: contractions in GDP appear to be briefer than expansions.

Figures

Fig. 2 Alternative filters

Fig. 1 Butterworth and Epanechnikov filters

Table 3 Leading nature of housing. International comparison *

Table 5 Cyclical characterisation and classification of GDP and construction variables. Butterworth and Epanechnikov filters

Full text

DOES HOUSING REALLY LEAD
THE BUSINESS CYCLE?
Luis J. Álvarez and Alberto Cabrero
Documentos de Trabajo
N.º 1024
2010

DOES HOUSING REALLY LEAD THE BUSINESS CYCLE?

DOES HOUSING REALLY LEAD THE BUSINESS CYCLE?
Luis J. Álvarez and Alberto Cabrero
BANCO DE ESPAÑA
Documentos de Trabajo. N.º 1024
2010

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ISSN: 0213-2710 (print)
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Abstract
The aim of this paper is to characterize the cyclical properties of Spanish real and nominal
housing related variables. Our three main results are: First, housing appears to lead the
business cycle. Second, fl uctuation in home prices are positively related to those of
residential investment, suggesting the dominant role of demand factors over supply ones.
Third,there are interesting asymmetries in cyclical fl uctuations: contractions in GDP appear
to be briefer than expansions.
Keywords: Housing, business cycles, fi ltering.
JEL classifi cation: E32, R21, R32.

Frequently asked questions

Q1. What are the contributions mentioned in the paper "Does housing really lead the business cycle?" ?

The aim of this paper is to characterize the cyclical properties of Spanish real and nominal housing related variables. Second, fl uctuation in home prices are positively related to those of residential investment, suggesting the dominant role of demand factors over supply ones. 

Q2. What is the aim of an ideal band-pass filter?

The aim of an ideal band-pass filter is to pass through components of a time series belonging to a pre-specified band of frequencies (pass band), while removing components at higher and lower frequencies. 

Q3. What is the underlying idea of this nonparametric method?

The underlying idea of this nonparametric method is that, under suitable regularity conditions, any function can be well approximated by a Taylor series expansion in the neighbourhood of any point. 

Q4. What are the two families of Butterworth filters?

There are two families of Butterworth filters, which areBANCO DE ESPAÑA 25 DOCUMENTO DE TRABAJO N.º 1024based on the sine function (BFS) and the tangent function (BFT), respectively. 

Q5. How do the authors avoid the problem of the kernel filter?

To avoid this problem and make comparisons with results of the Butterworth filter easier, the authors do not employ original series in their empirical application, but rather the trend-cycle component using Gómez and Maravall (2001) procedure. 

Q6. What is the first stage of the process?

In the first stage, the series is extended with ARIMA forecasts and backcasts to minimise the size of revisions and then a model-based trend-cycle component is obtained following the methodology in Gómez and Maravall (2001). 

Q7. What is the way to get the ideal filter?

Approximations to the ideal filter are quite good for moderate values of d.Gómez (2001) suggests a model-based two-stage procedure to obtain the cyclical component based on Butterworth filters, which can be shown to be identical to joint estimation of all components. 

Q8. What are the underlying assumptions of the Hodrick and Prescott filter?

The underlying assumptions of the Hodrick and Prescott (1997) filter are that the trend is stochastic and it varies smoothly over time.