Housing price gradients in a geography with one dominating center

We primarily focus on explaining housing prices and predicting housing price gradients in a Norwegian region with one dominating center (Stavanger). For such a geography spatial separation can be represented in a hedonic regression equation by a function of traveling distance from the city center. Several functions are tested, and some alternatives provide both a satisfying goodness-to-fit, consistent coefficient estimates, and intuitively reasonable predictions of housing price gradients. Still, not all commonly used functions are recommended. Spatial autocorrelation is removed when the hedonic function is properly specified.hedonic regression model; housing attributes; functional representation of spatial separation; spatial autocorrelation; housing price gradient; capitalization

Housing Price Gradients in a Region with One Dominating Center

This paper primarily focuses on predicting housing price gradients in a Norwegian region with one dominating center. Spatial separation is represented by a function of the traveling distance from the city center in a traditional hedonic regression equation. Several functions are tested, and some alternatives provide a satisfying goodness-of-fit, consistent coefficient estimates, and intuitively reasonable predictions of housing price gradients. Still, not all commonly used functions are recommended. The findings also indicate that the strength of spatial autocorrelation is reduced when the hedonic function is properly specified.

Misspecifications in modelling journeys to work

In this paper we perform a simulation procedure of testing models for journeys to work. The testing regime is carried out on a number of such models, mainly within the class of gravity models. We test the models on synthetic populations constructed from an aggregated set of a large number of worker subcategories, reflecting for instance different qualifications. Each subcategory is constructed from a gravity model where the population size and parameters are drawn from random distributions. The advantage of this approach is that a large number of tests can be carried out repeatedly to test the response of different kinds of models. We test how specific attributes of the spatial structure and worker heterogeneity are captured by different modelling alternatives. In addition we find that some model formulations falsely tend to report significant contributions to characteristics that were not taken into account in the data generating simulation process. This illustrates the imminent risk of drawing wrong conclusions in empirical work

The impact of labour market accessibility on housing prices

In this paper we study the relationship between labour market accessibility and housing prices in a Norwegian region. Through a hedonic approach we estimate implicit prices for a location with a marginally improved labour market accessibility. We test alternative measures of spatial separation between residential location alternatives and job opportunities. Gravity based accessibility measures in general improve model performance compared to a standard approach with one-dimensional measures of distance. We also discuss how sensitive the results are with respect to the delimitation of the geography. Based on our empirical results we finally enter into the discussion of how changes in the transportation infrastructure and the spatial distribution of employment opportunities capitalise through property values

The impact of labour market accessibility on housing prices.

In this paper we study the relationship between labour market accessibility and housing prices in a Norwegian region. Through a hedonic approach we estimate implicit prices for a location with a marginally improved labour market accessibility. We test alternative measures of spatial separation between residential location alternatives and job opportunities. Gravity based accessibility measures in general improve model performance compared to a standard approach with one-dimensional measures of distance. We also discuss how sensitive the results are with respect to the delimitation of the geography. Based on our empirical results we finally enter into the discussion of how changes in the transportation infrastructure and the spatial distribution of employment opportunities capitalise through property values.

Misspecifications in modelling journeys to work.

In this paper we perform a simulation procedure of testing models for journeys to work. The testing regime is carried out on a number of such models, mainly within the class of gravity models. We test the models on synthetic populations constructed from an aggregated set of a large number of worker subcategories, reflecting for instance different qualifications. Each subcategory is constructed from a gravity model where the population size and parameters are drawn from random distributions. The advantage of this approach is that a large number of tests can be carried out repeatedly to test the response of different kinds of models. We test how specific attributes of the spatial structure and worker heterogeneity are captured by different modelling alternatives. In addition we find that some model formulations falsely tend to report significant contributions to characteristics that were not taken into account in the data generating simulation process. This illustrates the imminent risk of drawing wrong conclusions in empirical work.

A disaggregated gravity model

The gravity model is used to estimate trip distributions. The estimates are in form of trip frequencies. This study is devoted to an entropy problem where the solution decomposes trip frequencies to the underlying probability distribution

Misspecifications due to aggregation of data in models for journeys-to-work

In this paper we develop a new simulation procedure that can be used to examine validity of model extensions. Our testing regime is carried out on a number of different trip distribution models. We test the models on synthetic populations contructed from an aggregated set of worker categories, reflecting for instance different qualifications. The advantage of this approach is that a large number of tests can be carried out repeatedly. We then examine how specific attributes of spatial structure and worker heterogeneity are captured by different modeling alternatives. It is quite surpricing to see how some model formulations systematically report significant contributions in cases where (by construction of the data) no such effects are present. This illustrates the imminent risk of drawing wrong conclusions in empirical work, i.e., that model extensions based on behavioral principles can sometimes report significant contributions that are in fact spurious