A real estate market model characterized by incomplete information, costly search, and varying expectations is presented. The model describes a self-selection process for market participants and a distribution of transaction prices. These transaction prices, which arise from a Nash equilibrium, can be expressed as a noisy signal, reflecting incomplete information as well as the conditions of sale. The appraiser's role is formalized as the task of signal extraction. The model emphasizes the differences in information available to individual buyers and sellers, who make transactions only infrequently, and the appraiser, whose expertise comes from observing many transactions. Based on the model, it is shown that contrary to popular perceptions, appraisal smoothing is consistent with an optimal updating strategy.Even in light of the development of general models of market imperfections, the simple competitive market model remains the dominant tool in real estate analysis. However, despite its popularity, the competitive market model provides an inadequate portrayal of the trading environment in real estate markets. Specifically, three important features of real estate markets distinguish the price formation process from that implied by the standard model:(1) Participants in real estate markets often have incomplete information about the attributes of the purchase, and decisions to buy and sell must often be made based on this partial knowledge.(2) Given the heterogeneity and fixity of real estate, some period of costly search must be incurred by potential buyers. (3) Trades are decentralized, and market prices are the outcome of pairwise negotiations. This price determination process represents a significant departure from Walrasian auction.This article introduces a model of real estate transactions which incorporates these three features, all of which play a crucial role in determining the eventual transaction price. The model is also useful in understanding the role of property appraisal in real estate markets and the techniques for making appraisals. This application to the appraisal function can be quite important. In real estate markets, purchases and sales of individual properties occur only infrequently. Thus the current market value of the stock of real capital, or the worth of any investor's holdings of real estate, must be inferred from limited information about recent transactions.

The relationship between stock prices and real estate prices has been the subject of substantial debate in both the academic and practitioner literatures. Existing studies have focused on the time series of stock and real estate returns using data from a single country, such as the U.S. By necessity, these studies examine return and price changes over short intervals, creating a bias when property values are smoothed from year to year. Using data from 17 different countries over 14 years, this paper examines the relation between stock returns and changes in property values and rents. Consistent with other country-specific studies, we find that, with the exception of Japan, the contemporaneous relation between yearly real estate price changes and stock returns is not statistically significant. However, when the data are pooled across countries and when we look at longer measurement intervals, a significant relation between stock returns and both rents and value changes becomes apparent. Real estate prices are also found to be significantly influenced by GDP growth rates and provide a good long-term hedge against inflation but a poor year-to-year hedge. Copyright American Real Estate and Urban Economics Association.

For nearly half a century, jobs have become increasingly characterized by employment insecurity. We examined the implications for sleep disturbance with cross-sectional data from the European Working Conditions Survey (2010). A group of 24,553 workers between the ages of 25 and 65 years in 31 European countries were asked to indicate whether they suffered from "insomnia or general sleep difficulties" in the past 12 months. We employed logistic regression to model the association between employment insecurity and sleep disturbance for all countries combined and each individual country. For all countries combined, employment insecurity increased the odds of reporting insomnia or general sleep difficulties in the past 12 months. Each unit increase in employment insecurity elevated the odds of sleep disturbance by approximately 47%. This finding was remarkably consistent across 27 of 31 European countries, including Albania, Austria, Belgium, Bulgaria, Croatia, Cyprus, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Latvia, Lithuania, Luxembourg, the Netherlands, Norway, Slovakia, Slovenia, Spain, Sweden, Turkey and UK. These results persisted with adjustments for age, gender, immigrant status, household size, partnership status, number of children, child care, elder care, education, earner status, precarious employment status, workplace sector, workplace tenure and workplace size. Employment insecurity was unrelated to sleep disturbance in four European countries: Malta, Poland, Portugal and Romania. Our research continues recent efforts to reveal the human costs associated with working in neoliberal postindustrial labour markets. Our analyses contribute to the external validity of previous research by exploring the impact of employment insecurity across European countries.

a b s t r a c tWe develop a novel, mixed methods approach to examine the relationship between political ideology and support for renewable energy and energy efficiency (REEE) policies. Through qualitative analysis of interviews with state-government legislators in the U.S., we show that when legislators evaluate and justify their support for and opposition to different types of renewable energy and energy efficiency (REEE) policies, they distinguish bills based on frames that are related to ideological differences (e.g., tax decreases, government efficiency, regulation, mandates, government spending). In turn the qualitative distinctions among bills are associated with quantitative differences in levels of support and success for the policies. Using data from a longitudinal analysis of 188 major state-government laws passed from 2004 to 2014 and a cross-sectional set of 709 passed and unpassed laws from 2011 to 2012, we show that REEE policies configured as mandates (e.g., renewable portfolio standards) have consistently lower levels of support than for similar REEE policies configured as tax reductions, reduction of government waste by increasing building efficiency, authorization of local government action, and regulatory reduction. Thus, via both quantitative and qualitative analysis, we show that there are important ideology-associated differences in REEE policy that point to opportunities for more successful policy design.