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The purpose of this paper is to provide a dating system for the Italian residential real estate market from 1927 to 2019 and investigate its interaction with credit and business cycles.

To detect the local turning point of the Italian residential real estate market, the authors apply the honeycomb cycle developed by Janssen et al. (1994) based on the joint analysis of house prices and the number of transactions. To this end, the authors use a unique historical reconstruction of house price levels by Baffigi and Piselli (2019) in addition to data on transactions.

This study confirms the validity of the honeycomb model for the last four decades of the Italian housing market. In addition, the results show that the severe downsizing of the housing market is largely associated with business and credit contraction, certainly contributing to exacerbating the severity of the recession. Finally, preliminary evidence suggests that whenever a price bubble occurs, it is coincident with the start of phase 2 of the honeycomb cycle.

To the best of the authors’ knowledge, this is the first time that the honeycomb approach has been tested over such a long historical period and compared to the cyclic features of financial and real aggregates. In addition, even if the honeycomb cycle is not a model for detecting booms and busts in the housing market, the preliminary evidence might suggest a role for volume/transactions in detecting housing market bubbles.

The purpose of this paper is to assess whether the rapid accumulation of bank deposits before the global financial crisis and their subsequent drastic reduction was the main driving force of the Cyprus house price cycle over the period 2006–2015.

To this aim we estimate a three-equation model in which house prices are determined by housing loans, among other factors, and housing loans are determined by bank deposits. All equations are estimated using partial adjustment model specifications.

Our findings indicate that housing loans, which capture the effect of credit availability on housing demand, had the smallest effect on house prices, thus providing little support to our proposition of a deposits-driven cycle in house prices.

The main limitation of the study is the use of the housing loan stock instead of the actual volume of housing loans in each period due to lack of such data. As a result our econometric estimates may not accurately capture the magnitude of the effect of housing loans on house prices.

The study has important practical implications for policy makers as it highlights the importance of availability of credit in supporting effective demand for housing during periods of economic growth. Furthermore, it highlights the key role of house price increases in combination with the collateral effect in driving the house price cycle.

This is among the few studies internationally and the first study in Cyprus that attempts to link econometrically the credit and house price cycles that were caused by the global financial crisis.

In this paper we investigate the relationship between loose monetary policy, low inflation, and easy bank credit and house price booms.

Using a panel of 11 OECD countries from 1920 to 2011 we estimate a panel VAR in order to identify loose monetary policy shocks, low inflation shocks, bank credit shocks, and house price shocks.

We show that during boom periods there is a heightened impact of all three “policy” shocks with the bank credit shock playing an important role. However, when we look at individual house price boom episodes the cause of the price boom is not so clear. The evidence suggests that the house price boom that occurred in the United States during the 1990s and 2000s was not due to easy bank credit.

Shocks from the shadow banking system are not separately identified. These are incorporated into the fourth “catch-all” shock.

Our evidence on housing price booms that expansionary monetary policy is a significant trigger buttresses the case for central banks following stable monetary policies based on well understood and credible rules.

This paper uses historical evidence to evaluate the relative importance of three main causes of house price booms. Our results bring into question the commonly held view that loose bank credit was to blame for the U.S. house price bubble of the later 1990s.

This paper aims to investigate the mutual dependence between housing prices and housing credit in Estonia, a country that experienced rapid debt accumulation during the 2000s and big swings in house prices during that period.

The authors use Bayesian econometric methods on data spanning 2000–2015.

The estimations show the interdependence between house prices and housing credit. More importantly, negative housing credit innovations had a stronger effect on house prices than positive ones.

The asymmetry in the linkage between housing credit and house prices highlights important policy implications, in that if central banks increase capital buffers during good times, they can release credit conditions during hard times to alleviate the negative spillover into house prices and the real economy.

This paper aims to investigate Malaysia’s house prices behaviour by decomposing trend, cycle and stochastic component.

The authors perform an unobserved component model of a structural time series and Markov switching model that covers the period 1999Q1 to 2015Q4.

The results reveal that the variation in house price in Malaysia is best explained by its trend level, with a small role played by the cycle component; this implies the potential for gaining returns on investments in property by investors and households. The results also show that Malaysia’s HPI cycle is between 8 and 17 years which, in relative terms, is twice the length of the growth cycle and the business cycle in the economy. Meanwhile, the overall movement of HPI is forecast to have a marginal price increase up to 2028Q2.

As house prices remained elevated during the year, the house price dynamic is pivotal for understanding the source of changes in house price. With major findings centred on the relationship between house prices and macroeconomic as well as policy variables, little attention has been paid to composing the trend, cycle and seasonal pattern from the house price index, thus understanding the behaviour of house prices’ unobserved components.

The equation of unified knowledge says that S = f (A,P) which means that the practical solution to a given problem is a function of the existing, empirical, actual realities and the future, potential, best possible conditions of general stable equilibrium which both pure and practical reason, exhaustive in the Kantian sense, show as being within the realm of potential realities beyond any doubt. The first classical revolution in economic thinking, included in factor “P” of the equation, conceived the economic and financial problems in terms of a model of ideal conditions of stable equilibrium but neglected the full consideration of the existing, actual conditions. That is the main reason why, in the end, it failed. The second modern revolution, included in factor “A” of the equation, conceived the economic and financial problems in terms of the existing, actual conditions, usually in disequilibrium or unstable equilibrium (in case of stagnation) and neglected the sense of right direction expressed in factor “P” or the realization of general, stable equilibrium. That is the main reason why the modern revolution failed in the past and is failing in front of our eyes in the present. The equation of unified knowledge, perceived as a sui generis synthesis between classical and modern thinking has been applied rigorously and systematically in writing the enclosed American‐British economic, monetary, financial and social stabilization plans. In the final analysis, a new economic philosophy, based on a synthesis between classical and modern thinking, called here the new economics of unified knowledge, is applied to solve the malaise of the twentieth century which resulted from a confusion between thinking in terms of stable equilibrium on the one hand and disequilibrium or unstable equilibrium on the other.

Compiled by K.G.B. Bakewell covering the following journals published by MCB University Press: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes 8‐18; Property Management Volumes 8‐18; Structural Survey Volumes 8‐18.

Index by subjects, compiled by K.G.B. Bakewell covering the following journals: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes 8‐18; Property Management Volumes 8‐18; Structural Survey Volumes 8‐18.