We study how and why local biodiversity affects residential property values. Leveraging remotely sensed greenness indicators and a novel dataset of granular property listings, we examine how changes in vegetation load on real estate prices. Hikes in greenness are associated with higher listing prices, fewer properties listed, and reduced liquidity in housing markets. These results suggest that price hikes in housing markets are driven by supply-side constraints instead of a “greenium” that buyers might be willing to pay due to innate preferences. Exogenous zoning shocks to foster biodiversity corroborate the presence of supply side constraints as price drivers in residential housing markets. Our findings emphasize the need to calibrate biodiversity and (social) housing policy objectives more explicitly.

We study real estate lending responses to tighter macroprudential policy (MPP) in the form of lower required loan-to-value (LTV) ratios. Contract details of 2.4 million mortgage loans originated between 2008 and 2020 reveal significantly fewer new loan issuances in response to contractionary MPP, commensurate with an average reduction in aggregate lending of 21 percent. Loan-level analyses reveal, however, that banks comply with lower LTVs by systematically more benevolent valuations of residential real estate pledged as collateral instead of reducing loan size. Exploiting earthquakes as plausible exogenous shocks to property values corroborates these risk-shifting patterns by banks in the form of inflated property valuations after LTV shocks.

Although the phase of euphoria seems to be over, policy makers and regional agencies have maintained their interest in cluster policy. Modern cluster theory provides reasons for positive external effects that may accrue from interaction in a group of proximate enterprises operating in common and related fields. Although there has been some progress in locating clusters, in most cases only limited knowledge on the geographical extent of regional clusters has been established. In the present article, we present a hybrid approach to cluster identification. Dominant buyer–supplier relationships are derived by qualitative input–output analysis from national input–output tables, and potential regional clusters are identified by spatial scanning. This procedure is employed to identify clusters of German research and development-intensive industries. A sensitivity analysis reveals good robustness properties of the hybrid approach with respect to variations in the quantitative cluster composition.

The focus of this paper is on the steady state of a two-sector economy with undirected search where employed and unemployed workers can search for jobs, both within a sector and between the sectors. As in the one-sector model, on-the-job search generates wage dispersion among homogeneous workers. The analysis of the two-sector model uncovers a property called constant tension that is responsible for analytical tractability. We characterize the steady state in all cases with constant tension. When time discounting vanishes, constant tension yields the endogenous separation rate in each sector as a linear function of the present value for a worker. The one-sector economy automatically satisfies constant tension, in which case the linear separation rate implies that equilibrium offers of the worker value are uniformly distributed. Constant tension also has strong predictions for worker transitions and value/wage dispersion, both within a sector and between the two sectors. When constant tension does not hold, we compute the steady state numerically and illustrate its properties.

This paper makes the following original contributions to the literature. (i) We develop a simpler analytical characterization and numerical algorithm for Bayesian inference in structural vector autoregressions (VARs) that can be used for models that are overidentified, just‐identified, or underidentified. (ii) We analyze the asymptotic properties of Bayesian inference and show that in the underidentified case, the asymptotic posterior distribution of contemporaneous coefficients in an n‐variable VAR is confined to the set of values that orthogonalize the population variance–covariance matrix of ordinary least squares residuals, with the height of the posterior proportional to the height of the prior at any point within that set. For example, in a bivariate VAR for supply and demand identified solely by sign restrictions, if the population correlation between the VAR residuals is positive, then even if one has available an infinite sample of data, any inference about the demand elasticity is coming exclusively from the prior distribution. (iii) We provide analytical characterizations of the informative prior distributions for impulse‐response functions that are implicit in the traditional sign‐restriction approach to VARs, and we note, as a special case of result (ii), that the influence of these priors does not vanish asymptotically. (iv) We illustrate how Bayesian inference with informative priors can be both a strict generalization and an unambiguous improvement over frequentist inference in just‐identified models. (v) We propose that researchers need to explicitly acknowledge and defend the role of prior beliefs in influencing structural conclusions and we illustrate how this could be done using a simple model of the U.S. labor market.

Programme zur Stadtsanierung greifen in lokale Wohnungsmärkte u.a. über zwei Kategorien von Subventionen ein: Subventionen zur Verbesserung des lokalen Umfelds; Subventionen zum Rückbau von Wohnungen. Der vorliegende Artikel untersucht die (indirekten) Effekte solcher Subventionen auf die Eigentümer von Mietwohnungen, die nicht unmittelbare Empfänger der Subventionen sind. Bislang gibt es hierzu keine gesicherten Erkenntnisse. Auf der Basis der Realoptionstheorie wird davon ausgegangen, dass es durch die Stadtsanierung zu einer Erhöhung der Optionsprämien kommt; in der Folge werden Wohnungseigentümer zu Investitionen veranlasst. Diese Hypothese wird auf der Basis empirischer Daten für das Programm „Stadtumbau Ost“ überprüft.

Informationally efficient prices are a necessary requirement for optimal resource allocation in the real estate market. Prices are informationally efficient if they reflect buildings’ benefit to marginal buyers, thereby taking account of all available information on future market development. Prices that do not reflect available information may lead to over- or undersupply if developers react to these inefficient prices. In this study, we examine the efficiency of the UK commercial property market and the interaction between prices, construction costs, and new supply. We collated a unique data set covering the years 1920 onwards, which we employ in our study. First, we assess if real estate prices were in accordance with present values, thereby testing for informational efficiency. By comparing prices and estimated present values, we can measure informational inefficiency. Second, we assess if developers reacted correctly to price signals. Development (or the lack thereof) should be triggered by deviations between present values and cost; if prices do not reflect present values, then they should have no impact on development decisions.