Secondary housing supply

I estimate the impact of new housing supply on the local rent distribution, exploiting delays in housing completions caused by weather shocks during the construction phase. Increasing the flow of new supply by 1% lowers average rents by 0.2%, and increases disproportionately the number of second-hand units offered for rent. The supply shock affects the entire rent distribution. Employing a quantitative model, I explain this pattern by secondary supply: New supply triggers a cascade of moves that frees up units in all segments of the local market. The impact on rents is similarly strong in locations experiencing growing housing demand

Can Internet Ads Serve as an Indicator of Homeownership Rates?

In this paper, we propose an indicator of the homeownership rate based on Internet ads offering the housing for rent and sale. We constructed the HOR estimate using the number of ads in four different markets (flats for rent, flats for sale, houses for rent, and houses for sale). Our HOR indicator was tested using data of German NUTS1 and planning (ROR) regions. The correlation between our estimate of the HOR and the alternative HOR figures varies between 0.834 and 0.874 at NUTS1 level and is 0.761 at the ROR level. All correlation coefficients are statistically significant. Our HOR estimate is particularly highly correlated with the official HOR figures. Thus, it is shown that our Internet-based indices could serve as a good indicator of the homeownership rate in German regions.Internet ads, homeownership rate, German regions, NUTS, planning regions

Internet-Based Hedonic Indices of Rents and Prices for Flats: Example of Berlin

In this paper, we suggest to estimate the home rents and prices in German regions/cities using the data from Internet ads offering the housing for rent and sale. Given the richness of information contained in the ads, we are able to construct the quality-adjusted rent and price indices using the hedonic approach. The results can be applied both for investigating the dynamics of rents/prices and for examining their distribution by city districts or regions.Internet ads, home rents, home prices, German regions, Berlin, hedonic approach

Flat Prices, Cell Phone Base Stations, and Network Structure

The present paper analyses the effect of the distance to the nearest CPBS on listing prices of flats in the city of Nuremberg, and is related to a similar study of Brandt and Maennig (2012) in case of the city of Hamburg. Health effects of mobile phone radiation have been discussed vividly in the German public and there is still ongoing opposition against cell phone base stations (CPBS) in residential areas. Besides a negative health effect, a CBPS site is often perceived to be visually disruptive in a residential neighborhood. Therefore, a negative effect on property values due to the proximity to CBPS is expected. However, the empirical evidence is mixed and focused on rural areas (Bond 2007) while we consider an urban area. Furthermore, the endogeneity of CPBS locations and thus the identification of the effect is still an issue. The empirical approach applied here is based on a hedonic price function of housing prices. The hedonic regressions used to identify the effect of the distance to the nearest CPBS take account of housing and neighborhood characteristics but also a possible endogeneity of the variable of interest. Following the critique of Pinkse & Slade (2010) and Gibbons & Overman (2012) who advocate the use of the quasi-experimental approach, we develop an instrument for the estimation of local price effects of CPBS in an urban area. The instrument is derived from the spatial structure of the network and technical and regulatory requirements. Such a strategy could be also useful in other contexts in which location choice is endogenous but depends on an existing network structure. We find a significantly negative impact of nearby CPBS on flat prices. The discount amounts to 3.3% of a property's value when two similar flats at distances of 50 and 100 m to the nearest CPBS are compared. The effect size is comparable to findings of other studies. The results of the main OLS and IV specifications are robust to several modifications that include e.g. spatially lagged prices. The small difference between OLS and IV results suggests that the distance to the nearest CPBS is not endogenous, in opposition to Brandt & Maennig (2012). Both authors argue that CPBS are likely to be located on "visually disruptive" structures However, such structures are rare in city centres where the network is dense and distances to CPBS are smaller. Consequently, the endogeneity problem may be less relevant. Further theme: S_Y The Causal Impact of Infrastructure on Regional Economic Activit

Flat Prices, Cell Phone Base Stations, and Network Structure: An Instrumental Variable Approach to Endogenous Locations

Following the critique of Pinkse & Slade (2010) and Gibbons & Overman (2012), we develop an instrument for the estimation of local price effects of cell phone base stations (CPBS) in an urban area. The instrument is derived from the spatial structure of the network and technical and regulatory requirements. Such a strategy could be useful in other contexts in which location choice is endogenous but depends on an existing network structure. We find a significantly negative impact of nearby CPBS on flat prices. The discount amounts to 3.3% of a property s value when two similar flats at distances of 50 and 100 m to the nearest CPBS are compared. The small difference between OLS and IV results suggests that the distance to the nearest CPBS is not endogenous, in opposition to Brandt & Maennig (2012)

Internet-based hedonic indices of rents and prices for flats: Example of Berlin

In this paper, we suggest to estimate the home rents and prices in German regions/cities using the data from Internet ads offering the housing for rent and sale. Given the richness of information contained in the ads, we are able to construct the quality-adjusted rent and price indices using the hedonic approach. The results can be applied both for investigating the dynamics of rents/prices and for examining their distribution by city districts or regions

German cities to see further rises in housing prices and rents in 2013

Over the past few years, prices and rents for flats went up in most German cities. This trend is expected to continue in 2013. Berlin, Hamburg, Munich, and Frankfurt am Main will still see the highest increases in property prices and rents. In these cities, housing prices are rising much faster than rents. By contrast, stagnating or even falling prices are forecast for the cities in the Ruhr area

Forecasting the prices and rents for flats in large German cities

In this paper, we make multi-step forecasts of the monthly growth rates of the prices and rents for flats in 26 largest German cities. Given the small time dimension, the forecasts are done in a panel-data format. In addition, we use panel models that account for spatial dependence between the growth rates of housing prices and rents. Using a quasi out-of-sample forecasting exercise, we find that both pooling and accounting for spatial effects helps to substantially improve the forecast performance compared to the benchmark models estimated for each of the cities separately. In addition, a true out-of-sample forecasting of the growth rates of flats' prices and rents for the next six months is done. It shows that in most cities both prices and rents for flats are going to increase. In some cities, the average monthly growth rate even exceeds 1%, which is a very strong increase compared to the overall price level increase of about 2% per year

Ein Instrument zur Messung der Preisentwicklung auf dem Wohnungsmarkt: Das Beispiel Berlin

Untersuchungen über die Preise auf dem Markt für Wohnimmobilien geben in aller Regel Aufschluss über die Preise für Wohnungen in einer bestimmten Lage oder mit einer bestimmten Beschaffenheit. Das DIW Berlin hat ein Verfahren entwickelt, mit dem die Preise für verschiedenartige Wohnungen zu einer einheitlichen Größe zusammengefasst werden. Damit kann die Preisentwicklung übergreifend etwa für alle Neuvermietungen und Käufe von Wohnimmobilien in einer Region bestimmt werden. Das Verfahren ist wenig aufwändig und kann sehr zeitnahe Informationen liefern. Erstmals wurde das Verfahren auf Berlin angewendet. Hier stiegen in der Zeit von Juni 2011 bis März 2012 die Angebotspreise bei Neuvermietungen um acht Prozent, und bei Eigentumswohnungen zogen die geforderten Preise um zwölf Prozent an. Auf ein Jahr umgerechnet ergibt sich eine Teuerung von zehn Prozent (Mieten) und 15 Prozent (Eigentumswohnungen). Bei den Mieten ist der Preisauftrieb weiterhin hoch, aber nicht mehr so stark wie noch im Sommer letzten Jahres, bei Eigentumswohnungen setzen sich die Preissteigerungen unvermindert fort

Why have house prices risen so much more than rents in superstar cities

In most countries – particularly in supply constrained superstar cities – house prices have risen much more strongly than rents over the last two decades. We provide an explanation that does not rely on falling interest rates, changing credit conditions, unrealistic expectations, rising inequality, or global investor demand. Our model distinguishes between short- and long-run supply constraints and assumes housing demand shocks exhibit serial correlation. Employing panel data for England, our instrumental variable-fixed effect estimates suggest that in Greater London labor demand shocks in conjunction with supply constraints explain two-thirds of the 153% increase in the priceto-rent ratio between 1997 and 2018