Chicken or egg? The PVAR econometrics of transportation

Abstract

Abstract:To analyse the mutually dependent relationship between local economic performance, demand for and supply of transport services, we employ the structural panel VAR method that is popular in the macroeconomic literature, but has not previously been applied to the modelling of the within-city dynamics of transportation. We focus on a within-city panel of Berlin, Germany during the heyday of the construction of its dense public transit network . Our results suggest that economic outcomes and a supply of transport infrastructure mutually determine each other. We find a short-run (long-run) elasticity of property prices with respect to transport supply of 2% (8.5%). Both transport demand and supply seem to be driven more by firms than by residents.

Ease vs. noise: Long-run changes in the value of transport (dis)amenities

“…Our main variable of interest are land prices which are extracted from various editions (1881, 1890, 1896, 1900, 1904, 1910, and 1914) Müller's maps are by now an established data source. They have been used, among others, by Ahlfeldt, Moeller, et al (2015), who also provide an extensive data appendix that describes in detail the nature of the data. More notably, the data are directly comparable to the more recent Berlin land price data (1928,1936,1986,2006) used by Ahlfeldt, Redding, et al (2015); they also share many similarities to Olcott's Chicago land values, which have been used in studies such as Ahlfeldt and McMillen (2018), Berry (1976), Kau and Sirmans (1979), McDonald and Bowman (1979), McMillen (1996), McMillen and McDonald (2002), Mills (1969), and Yeates (1965).…”

“…Fifth, we provide one of the few analyses of rail capitalization effects into land prices (e.g. Ahlfeldt, Moeller, et al 2015;Coffman & Gregson 1998), whereas most previous studies have looked at price responses of properties or housing units. The analysis of land prices comes with the advantage of not having to control for structural characteristics.…”

Culturally clustered or in the cloud? How amenities drive firm location decision in Berlin

“…First of all, I compute kernel densities around each point representing a consumption amenity (Silverman, 1986), applying a radius of 2 km. This radius goes back to Gibbons and Machin (2005) who predict a distance of 2 km as being the maximum distance people are willing to walk to the nearest station and has already been used in the context of urban amenities by Ahlfeldt, Moeller, Waights, and Wendland (2017) and Ahlfeldt, Moeller, and Wendland (2014). Even though the density measure fulfills the above-stated requirements, estimate interpretation is rather abstract and not intuitive.…”

The Dynamics of Subcenter Formation: Midtown Manhattan, 1861–1906

“…Ahlfeldt, Moeller, and Wendland () explore the “chicken and egg” question for Berlin from 1890 to 1914. Their results also show an endogenous relationship between land use and transportation investments.…”