Academic journal article Real Estate Economics

From Central Planning to Centrality: Krakow's Land Prices after Poland's Big Bang

Academic journal article Real Estate Economics

From Central Planning to Centrality: Krakow's Land Prices after Poland's Big Bang

Article excerpt

We examine commercial land markets in Krakow, Poland over a 10-year period of transition from socialist management to a market economy. We explore the spatial and temporal evolution of land prices over this period. In particular, we are interested in identifying trends toward or away from centrality, and in discovering whether or not these trends acted on the city center alone or over a set of centers. The data set we employ is uniquely appropriate for this purpose as the densifying force of "highest-and-best" use--typically found in market-oriented cities--was absent under four decades of socialist planning, leaving undeveloped land scattered throughout the city. Free of quality control issues associated with disentangling the value of land from properties in which land and structures are bundled, the data offer a clean assessment of land prices within an urban area. We employ a novel, iterative approach to identify pricing centers--"nodes" of similarly sized residuals--which we interpret as evidence of omitted spatial amenities. Using this approach, we find that the price gradient in Krakow evolved toward concentration, but concentration in several centers rather than in just one. We find that the exclusion of proximity to these centers leads to biased coefficients in the hedonic regressions; we also find that the majority of the apparent spatial autocorrelation in the aspatial regressions results from the omission of proximity to these centers.


It is now clear that simple monocentric models are inadequate to represent many metropolitan areas--indeed, few cities look like the "isolated state" described by von Thunen (1966). The rise of subcenters, suburban office parks and retail concentrations, "edge cities," etc. has meant that convenient parameterizations of the land-rent gradient used in applied urban research are often misspecifications of the effect of location on the price of land. This is especially true in metropolitan areas that are undergoing rapid change. It is not uncommon to see specifications for the land-rent gradient that allow neither for polycentricity nor variation over time. The complexity of the value of location over time is the focus of this article.

To address this question, we model land-rent surfaces in a city undergoing rapid and substantial change. We examine the evolution of pricing for vacant lots in Krakow, Poland, from 1993 to 2001. The 9-year sample period begins shortly after the implementation of the package of legal and economic reforms known as Poland's "Big Bang." The data reveal distinct variation in pricing over space and time and underscore the substantial weakness of time-invariant and/or simple monocentric models. Over the sample period, there was a substantial movement from smaller, more scattered nodes of pricing to fewer, more influential nodes.

Our approach to modeling the price surfaces over time is iterative and flexible. We estimate a hedonic regression that includes covariates that control for a parcel's access to infrastructure and its allowable uses in order to focus on residuals that contain the value of proximity to locational amenities. Our approach is to use these residuals to estimate a smooth price surface and model its significant features. Peaks on the smoothed surface are "nodes" of like-sized and -signed residuals; land near these locales systematically trades at above the price predicted by the hedonic models. Proximity to these nodes is included in subsequent hedonic regressions. This way we allow the data to reveal which locations are systematically valued over others.

We find that the city center is highly valued throughout this era, but so too are other locations. Broadly speaking, the handful of small nodes in the northwest of the city in the early years gives way to fewer, larger and more centrally located nodes as time passes. We find that the inclusion of the proximity to these locales in the hedonic regression greatly reduces measured spatial autocorrelation. …

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