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Empirical studies on household-level inflation inequality have so far only focused on periods with positive inflation rates. However, the major concern on the policy agenda since the most recent financial crisis has been deflation rather than inflation. This naturally raises the question regarding the effect of deflation on the distribution of real income when households spend their budget on different consumption bundles. This chapter compiles annual household-level inflation rates in Denmark from 1930 to 1935 based on microdata from the Expenditure and Saving Survey of 1931 and price data from the official Retail Price Index. The results indicate that lower-income households faced a larger decline in prices on their consumption of goods and services during the deflation years 1930–1932 than higher-income households did. The deflation thus contributed to narrowing the difference in real incomes between the top and bottom parts of the income distribution during the recession. In the years 1933–1935 with positive inflation rates, the lower-income households experienced higher inflation rates than higher-income households. Over the period 1930–1935 seen as a whole, the price development contributed slightly to reducing real income inequality. The low degree of medium-term persistence of differences in household-specific inflation rates is consistent with previous findings in various time periods from the 1960s to the 2000s without any persistent deflation events. The chapter at hand is the first empirical study of the direct distributional effects of price developments at the household level in a period with persistent deflation.

The majority of economic crises impact the wealth of people which in turn affect their financial capacity to purchase residential properties. However, the home financing method may also have an impact on the behaviour of house prices. This chapter intends to test argued resilience of Islamic finance to situations of financial crisis by using an Islamic home financing product called Enhanced Musharakah Mutanaqisah (EMM) which was proposed by Asadov and Ibrahim (2018) as an example and compare its performance to conventional mortgage. Two different models of home financing, conventional and EMM based ones are developed with the former reflecting basic features of conventional mortgage and the latter using rental rates and house price indices for product pricing. Both models are compared using aggregate data for the US housing market for the past 30 years in order to demonstrate the resilience of the EMM model. The findings of the study show that EMM is more flexible in terms of reflecting real situations in both the housing market and aggregate economy as compared to the conventional model. Its pricing is more accommodating particularly during times of economic downturns, and it can potentially provide the solution to numerous mortgage defaults arising from such conditions. Despite the proposed models being tested using data only from the United States, the analysis can be generalized for other countries as well. The implementation of the EMM model, as an example of Shariah-based Islamic financial product, is expected to bring fairness and justice in the relationship between financial institutions and its clients. To the best of our knowledge, this is the first attempt of simulating a Musharakah Mutanaqisah based home financing using both actual rental rates and house prices for product pricing.

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.

Introduction: Financial development has a direct impact on the housing market by facilitating access to credit. The increase in housing loans resulting from the relaxation of the credit constraint causes an increase in housing demand and house prices. Purpose: This study aims to examine the relationship between financial development and house prices in Turkey, using the variables: the domestic credit to the private sector and total housing and consumer credits. Methodology: To determine any long-run relationship between financial development and house prices, the autoregressive distributed lag methods are used, covering the selected variables such as real GDP, inflation, mortgage interest rate, and stock price from 2010Q1 to 2020Q2. Findings: The study’s findings show that both variables representing financial development have a statistically significant and substantial positive effect on house prices. Besides, the selected macroeconomic variables have the theoretically expected impact on house prices.

The size and number of employment subcenters have increased in large metropolitan areas as the spatial distribution of jobs has become increasingly decentralized. Although employment decentralization is not a new phenomenon, only recently have concentrations of employment outside the central city begun to rival the traditional central business district (CBD) in size and scope. Because of this change, neither theoretical nor empirical models in urban economics now rely solely on the traditional monocentric city model of Muth (1969) and Mills (1972). Instead, recent research incorporates some version of a polycentric model, a trend that Anas et al. (1998) document in their excellent review article.

The 2007–2009 financial crisis initially appeared to have destroyed a huge amount of wealth in the United States. Housing prices dropped about 21% across the country and as much as 50% in some places, and the stock market dropped by nearly 50% as well. This chapter examines how the financial crisis differentially affected households at different parts of the income and wealth distributions. Our results show that all households lost about the same percentage of their wealth in that period. But because households in the top 10% of the wealth distribution owned many different kinds of assets, their wealth soon recovered. The bottom 80% of the wealth distribution had more of their wealth tied up in housing. We show that financial distress, indexed by foreclosures, being behind in mortgage payments, and changes in house prices were particularly concentrated in households in the bottom 80% of the wealth distribution. These households lost a large part of their wealth and have not yet recovered. Households that were most deeply affected were those who entered the housing market late and took out subprime loans. African American and Hispanic households were particularly susceptible as they bought houses late in the price bubble often with subprime loans.

Throughout the 1990s, the supply of new condominiums in Tokyo significantly increased while prices persistently fell. This article investigates whether the market power of condominium developers is a factor in explaining the outcome in this market and whether there is a relationship between production cost trend and the degree of market power that the developers were able to exercise. In order to respond to these questions, we construct and structurally estimate a dynamic durable goods oligopoly model of the condominium market – one incorporating time-variant costs and a secondary market – using a nested GMM procedure. We find that the data provide no evidence that firms in the primary market have substantial market power in this industry. Moreover, the counterfactual experiment provides evidence that inflationary and deflationary expectations on production cost trends have asymmetric effects to the market power of condominium producers. The increase in their markup when cost inflation is anticipated is significantly higher than the decrease in the markup when the same magnitude of cost deflation is anticipated.

In this paper we show, by means of an example of its application to the problem of house price forecasting, an approach to attribute selection and dependence modelling utilising the Gamma Test (GT), a non-linear analysis algorithm that is described. The GT is employed in a two-stage process: first the GT drives a Genetic Algorithm (GA) to select a useful subset of features from a large dataset that we develop from eight economic statistical series of historical measures that may impact upon house price movement. Next we generate a predictive model utilising an Artificial Neural Network (ANN) trained to the Mean Squared Error (MSE) estimated by the GT, which accurately forecasts changes in the House Price Index (HPI). We present a background to the problem domain and demonstrate, based on results of this methodology, that the GT was of great utility in facilitating a GA based approach to extracting a sound predictive model from a large number of inputs in a data-point sparse real-world application.