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This paper aims to study the relationship between the rental and selling prices, a very important topic that forms the fundamentals of real estate markets.

This theoretical paper makes use of a search and matching model of the housing market. The search and matching models are the benchmark models of the “matching” markets, such as the labour market and the housing market, where trade is a decentralised, uncoordinated and time-consuming economic activity.

Unlike the previous related literature, where this relation is usually analysed in the context of the present value equation, this paper shows the existence of a “dual” relation between rental and selling prices as follows: one in the homeownership market and another one in the rental market. This “dual” relation connects the rental and homeownership markets and allows to get equilibrium in both markets with positive house prices.

Several topics could be deepened for making the paper richer and more interesting, although at the cost of much more mathematics. First of all, the introduction of specific functional forms for both the rent function and the sale price function, so as to calculate both the elasticity of rent with respect to sale price and the elasticity of sale price with respect to rent. In this way, it would be possible to understand how each market (rental and homeownership) reacts to shock and policies that affect the other market.

In general, this framework could help policymakers to design housing policy reforms that take into consideration the effects on both markets. Indeed, some policies could have positive effects on rental markets but perverse effects on homeownership markets and vice versa.

None of the existing and related works of research have considered how to take advantage of the search and matching approach to derive both a “rent function” and a “sale price function” that connect closely the rental and homeownership markets.

This study deals with the main issues concerning the interplay between homeownership and labour market outcomes, namely (1) the relation between homeownership and labour market outcomes, at both the individual level and the aggregate level, and (2) the relation between homeownership and human capital.

This paper is both theoretical and empirical. A search and matching model of the labour market is developed to explain the strong relation between mortgage markets and wages. A regional panel analysis in Italy is used to verify the interplay between homeownership and wages.

Homeownership is not, by itself, a condition for receiving higher wages, but rather higher wages increase the probability to become a homeowner, since they positively affect the probability of acquiring a mortgage from the bank. Eventually, wages cause homeownership, but the reverse may not be true.

The paper focuses on the labour market, while the housing market model is restricted to the mortgage market.

The positive effect of homeownership on wages is hard to theoretically formalise and is not empirically proven. Before investigating a (potential) bidirectional relationship between homeownership and labour market outcomes, therefore, the related literature should assume a new theoretical link between homeowners and wages.

The result that “homeownership is not, by itself, a condition for receiving higher wages” has positive implications for human and social development. If homeownership could lead to better labour market outcomes, indeed, socio-economic inequalities would increase in the society, because homeownership would be the starting point of a “lucky” circle that increases the well-being of people who are already wealthy.

First, this study clearly explains why the microeconomic result that homeowners are more likely to be employed than tenants is consistent – at the aggregate level – with a negative relation between homeownership and better labour market outcomes. Second, the related literature has largely ignored the social implications of the topic. A potential bidirectional relation between homeownership and (better) labour market outcomes, indeed, could imply an increase in the well-being of people who are already wealthy.

This theoretical study aims to clarify the (a priori) ambiguous effect of homeownership on unemployment. In general, in fact, homeownership discourages job mobility, but homeowners are less likely to be unemployed than tenants, since homeownership would seem to be positively related to human capital.

This study develops a modified version of the benchmark theoretic model of the labour market – the well-known “equilibrium unemployment theory” – where homeownership affects both the “Beveridge Curve” (BC, by means of job immobility) and the “Job Creation Condition” (JCC, by means of human capital).

The general result is that an increase in homeownership increases unemployment. Therefore, policymakers could encourage job mobility, before facilitating homeownership. This policy implication, however, may not apply in the case of high inflation and/or low nominal interest rate, and when the job destruction rate depends on the homeownership rate.

The model studies the steady-state equilibrium of the labour market, so the policy implications only relate to the long-run. The model, therefore, does not consider the short-run effects of homeownership on unemployment (which may differ from the long-term results).

The model suggests a public policy characterised by large investment in rail lines and subsidised commuter fares. By promoting a more efficient allocation of workers across regions (and, thus, job mobility), indeed, this policy can be a good way to increase employment, without harming homeownership.

The practical implication of this model is also a social implication, since it relates to homeownership and housing tenure.

To the best of author’s knowledge, this is the first model that introduces the key role of homeownership in the so-called “Equilibrium unemployment theory”. Precisely, the model uses a modified version of both the BC (which includes the negative effect of homeownership on the overall job search intensity of unemployed workers) and the JCC (which includes the positive effect of homeownership on both the business start-up and the human capital of workers). By comparing these two opposite effects, this theoretical work makes clearer the net effect of homeownership on unemployment.

The purpose of this paper is to provide an integrated approach that combines the two methods usually used in the real estate appraisals, namely, the income capitalisation method and the hedonic model.

In order to pull out the link between the income capitalisation approach and the hedonic model, the standard hedonic price function is introduced into the basic model of income capitalisation instead of the house market value. It follows that, from the partial derivative, a direct relation between hedonic prices and discount rate can be obtained. Finally, by using the close relationship between income capitalisation and direct capitalisation, a mathematical relation between hedonic prices and capitalisation rate is also obtained.

The developed method allows to estimate the capitalisation rate using only hedonic prices. Indeed, selling and hedonic prices incorporate all of the information required to correctly estimate the capitalisation rate. Furthermore, given the close relation among going-in and going-out capitalisation rates and discount rate, the proposed method could also be useful for determining both the going-out capitalisation rate and the discount rate.

Obviously, it is always preferable to estimate the capitalisation rate by just using comparable transactional data. Nevertheless, the method developed in this paper is especially useful when: the rental income data are missing and/or not entirely reliable; the data on rental income and house price are related to different homes; the capitalisation rate, in fact, should compare the rent and value of identical homes. In these cases, therefore, the method can be a valuable alternative to direct estimation.

The large and important literature on real estate economics and real estate appraisal neglects the relationship between hedonic prices and capitalisation rate, thus considering the hedonic model and the income capitalisation approach as two separate and alternative methods. This paper, instead, shows that integration is possible and relatively simple.

The purpose of this paper is to comment upon the use of hedonic pricing models for the valuation of property. This model can be particularly useful for some housing markets.

This Education Briefing is an explanation of the how hedonic pricing can be useful in looking at the effect of “location” on the house prices within different submarkets using the Italian real estate market as an example.

Although, this case study is relatively straightforward, it shows how the application of the market approach can provide insights in cases where the comparable properties belong to different submarkets with relatively few transactions.

In cases of mass appraisals, hedonic pricing models can provide a broad indication of value across submarkets.

This paper develops a general framework that connects multiple regression analysis, direct comparison model and submarket binary variables.

This paper aims to study the phenomenon known as “house price dispersion”, one of the most important distinctive features of housing markets. House price dispersion refers to the phenomenon of selling two houses with very similar attributes and in near locations at the same time but at very different prices.

This theoretical paper makes use of a search and matching model of the housing market. The search and matching models are the benchmark models of the “matching” markets, such as the labour market and the housing market, where trade is a decentralised, uncoordinated and time-consuming economic activity.

Unlike the previous related literature that attributes to the heterogeneity of buyers and sellers a significant part of the price volatility, in this paper, the house price dispersion depends on the housing tenure status of home-seekers in the house search process. Indeed, in the presence of different housing tenure status of home-seekers, the house search process leads to different types of matching. In turn, this implies different surpluses (the sum of the net gains of the parties involved in the trade), and eventually, different surpluses produce different prices of equilibrium.

An interesting research agenda for future works would be an extension of the model to study the effect of “online housing search” on the house search and matching process, and thus, on the house price dispersion.

The main practical implication of this work is that the house price dispersion is an inherent phenomenon in the house search and matching process.

None of the existing and related works of research have considered how to take advantage of the search and matching approach to deal with the phenomenon known as “house price dispersion”, without relying on the ex ante heterogeneity of the parties but looking at the “core” of the house search and matching process.

This paper aims to explain the main empirical facts of housing markets, notably the trade-off between housing price and time-on-the-market, the positive correlation between housing price and the number of contracts traded during a given period (i.e. the trading volume) and the existence of price dispersion.

This theoretical paper makes use of a search and matching model. Search and matching, indeed, are two fundamental characteristics of the trading process in the housing market, and, thus, the search-and-matching models have become the new economic approach to the analysis of real estate markets.

This paper shows that a slightly modified version of the baseline search and matching model à la Mortensen-Pissarides can explain the main empirical facts of housing markets. There are two key mechanisms that allow to achieve this notable goal: a simple formalisation of the (reasonable) assumption that buyers today are potential sellers tomorrow (and vice versa); and the direct relationship between market tightness and house price, derived by the standard matching model and underestimated by the related literature.

The developed theoretical model only studies the equilibrium conditions. Indeed, it would be interesting to also study the disequilibrium in housing markets.

The explanation of the main empirical facts of housing markets is embodied in the same and relatively simple theoretical model.

In addition to the explanation of the main empirical facts of housing markets, the developed theoretical model can generate an upward sloping Beveridge curve in the housing market (the positive relation between home-seekers and vacant houses). Instead, according to a recent criticism in the related literature, a model à la Mortensen-Pissarides inherently generates a (empirically unrealistic) downward sloping Beveridge curve.

The aim of this education briefing is to comment upon how basic hedonic pricing models for the valuation of property can be expanded and developed. In this case, the briefing illustrates the use of the new economic approach to the analysis of housing markets, namely the search-and-matching models.

This education briefing discusses the connection of two important economic theories: the hedonic price theory and the search-and-matching theory.

This education briefing gives an example of a (non-linear) form of the hedonic price function.

In cases of mass appraisals, hedonic pricing models can provide a broad indication of value across submarkets and this education briefing demonstrates a theoretical model that can be used to provide a theoretical groundwork for the use of a concave hedonic price function in empirical estimates.

This education briefing shows how basic hedonic pricing models can be enhanced by a search-and-matching approach to determine property values.

This paper aims to pose an important starting point for the application of the search-and-matching models to real estate appraisals, thus reducing the “gap” between practitioners and academicians. Due to relevant trading frictions, the search-and-matching framework has become the benchmark theoretical model of the housing market. Starting from the large related literature, this paper develops a simplified approach to modelling the frictions that focuses on the direct relationship between house price and market tightness (a common feature only for the labour market matching models). The characterization of the equilibrium through two main variables simplifies the analysis and allows using the theoretical model for empirical purposes, namely, the real estate appraisals.

This work is both theoretical and empirical. Theoretically, a long-run equilibrium model with a positive share of vacant houses and home seekers is determined along with price and market tightness. Also, the conditions of existence and uniqueness of the steady-state equilibrium are determined. Unlike most of the search-and-matching models in the housing literature, the out-of-the steady-state dynamics are also analyzed to show the stability of the equilibrium. Empirically, to show the usefulness of the theoretical model, a numerical simulation is performed. By using two readily available housing market data – the expected time on the market and the average number of trades – it is possible to determine the key variables of the model: price, market tightness and matching opportunities for both buyers and sellers. Although the numerical simulation concerns the Italian housing market, the proposed model is generally valid, being empirically applicable to all real estate markets characterized by non-negligible trading frictions. Indeed, the proposed model can be used to compare housing markets with different features (concerning the search and matching process), as well as analyse the same housing market in different time periods (because the efficiency of the search and matching process can change).

Several important results are obtained. First, the price adjustment – i.e. the difference between the actual selling price and the price obtained in an ideal situation of frictionless housing market – is remarkable. This means that the sign and the size of the price adjustment depend on the extent of trading frictions in the housing market. Precisely, the higher the trading frictions on the demand side (more buyers and less sellers), the higher the actual selling price (the price adjustment is positive), whereas the higher the trading frictions on the supply side (less buyers and more sellers), the lower the actual selling price (the price adjustment is negative). Accordingly, the real estate appraisers should assess the trading frictions in the housing market before determining the price adjustment. Second, an increase in the number of trades affects the house price only if the time on the market varies. Also, the higher the variation in the time on the market, the larger the house price adjustment. Indeed, the expected time on the market reflects the opportunities to matching for both parties and thus the trading frictions. If the time on the market increases (decreases), the seller will receive less (more) opportunities to match; thus, the actual selling price will be driven downwards (upwards).

As far as the authors are aware, none of the existing works in the search and matching literature has considered how to take advantage of this theoretical approach to estimate the house price in the presence of trading frictions in the housing market. Indeed, the proposed theoretical model may be a useful tool for real estate appraisers, as it is able to derive the trading frictions from the time on the market and the number of trades, thus estimating properly the house price.