Inge Thorsen

Effects on housing prices of urban attraction and labor market accessibility

Through a hedonic approach the authors focus primarily on how house prices vary systematically with respect to some general spatial structure characteristics in a Norwegian region. The introduction of a gravity-based labor-market accessibility measure contributes significantly to explain variation in housing prices, and is used in a model formulation where the distance from the city center is accounted for. Based on these results we suggest a distinction between an urban-attraction effect and a labor-market accessibility effect. Quantitatively, the two distinct effects are found to contribute about equally to intraregional variation in housing prices.

Empirical Evaluation of Alternative Model Specifications to Predict Commuting Flows

This study is devoted to empirical and modeling aspects on how characteristics of spatial structure influence commuting flows. Within a doubly-constrained framework, results from a competing-destinations formulation are evaluated and compared to results from the traditional gravity model. The evaluation depends critically upon the specification of within-zone journeys-to-work. Specific labor-market characteristics are found to be significant to explain how workers are absorbed in diagonal elements of the trip-distribution matrix. We also find that the parametric specification of the accessibility measure is important, and that the competing-destinations formulation is superior to the traditional gravity model.

A Competing Destinations Approach to Modeling Commuting Flows: A Theoretical Interpretation and An Empirical Application of the Model

We introduce a modified version of the competing destinations model as a framework to estimate how discontinuities in the road network affect commuting flows. An economic interpretation of the model is presented in terms of random utility theory and hierarchical destination choice. Based on data from western Norway, we estimate a set of parameters which are assigned to different aspects of spatial structure in a region where the road network is disconnected owing to numerous topographical barriers. The model is applied to predict how commuting flows in the region are influenced by transportation innovations where ferry connections are subtituted by tunnels and bridges.

A Network Approach to Commuting

In this paper we present a model for commuting in a network of towns. A basic assumption is that all individuals have a given residential location and that every node in the network has a fixed number of jobs. We then propose a general model for the commuting of labor between the nodes in the network.

Replication/Prediction Problems in the Journey to Work

In this paper we will consider gravity models for journeys to work. In applications of the theory it is sometimes assumed that the parameters in such models are fixed. We will provide examples to show that this is not always a reasonable assumption, for instance, when the model is applied to predict how changes in the road transportation network influence commuting flows. Models where the parameters are subject to change usually comply with C-efficiency and random utility theory.

Spatial Impacts, Local Labour Market Characteristics and Housing Prices

This paper takes as a starting-point a model where spatial variation in housing prices is explained by urban attraction and labour market accessibility effects. Using data from a region in south-west Norway, estimation results are found to be encumbered, however, with significant spatial effects. The spatial Durbin model is used to account for this and to provide estimates of direct and indirect impacts. In addition, hypotheses are tested that some of the spatial variation in housing prices reflects local labour market characteristics. Some support is found for a hypothesis that a model specification should account for sub-centres located at some distance from the central parts of the region. The indirect impacts estimated in the spatial Durbin model suggest that spatially related misspecifications of implicit elasticities in the ordinary least squares model are mainly due to negative externalities close to areas of high labour market accessibility.

A SIMULATION APPROACH TO STUDYING THE SENSITIVITY OF COMMUTING-FLOW PREDICTIONS WITH RESPECT TO SPECIFIC CHANGES IN SPATIAL STRUCTURE

Economic evaluations of investments in transportation infrastructure in general call for traffic-flow predictions. In many studies such predictions are based on a doubly constrained modeling framework, with no explicit attempts to account for possible effects from changes in the location pattern of population and employment. In this paper we focus on the sensitivity of commuting-flow predictions to specific changes in the marginal totals of a trip-distribution model. We approach this problem through a series of simulation experiments where population and employment are systematically redistributed between different zones within the region. With this procedure we provide some quantitative estimates of prediction errors that follow from the inability to take into account long-term consequences of the location pattern of firms and households. We also carry through a simulation experiment that focuses on how benefits of different road investments are interrelated, and depend on spatial-structure characteristics.

ACCOUNTING FOR LOCAL SPATIAL HETEROGENEITIES IN HOUSING MARKET STUDIES

We adopt a novel method to deal with omitted spatial heterogeneities in hedonic house price analysis. A Gaussian variant of the conditional autoregressive (CAR) model is used to study the impact of spatial effects. In a general linear modeling framework, we include zone‐specific random effects that are allowed to interact spatially with neighboring zones. The results demonstrate that this estimator accounts for missing spatial information, producing more reliable results on estimated spatially related coefficients. The CAR model is benchmarked against a fixed effects model. Socioeconomic neighborhood characteristics are found to have only modest impact on spatial variation in housing prices.

Employment, Transport Infrastructure, and Rural Depopulation: A New Spatial Equilibrium Model

In this paper we propose a new spatial equilibrium model, and use it to discuss issues related to rural depopulation. The discussion focuses on how investments in transport infrastructure and the spatial distribution of basic-sector jobs can promote a relatively balanced growth of peripheral and central areas of a region. Through interdependencies in individual migration decisions and an economic base multiplier mechanism, negative exogenous shocks may take a peripheral zone beyond a bifurcation point, into an equilibrium of dramatically lower population and employment. We study how the location of bifurcation points depend on spatial interaction behavioural parameters and variables subject to regional policy. We also discuss the issue of the timing of interventions intended to prevent a process of rural depopulation.

Exploring the Determinants of Regional Unemployment Disparities in Small Data Sets

While standard economic theory suggests that unemployment should be evenly distributed across space, casual observation of unemployment rates shows that this is not the case. This has led to the development of a substantial literature on the topic. Due to the complexity of the problem, it is not always clear what the root cause is. This is particularly true when considering a small geographic area with limited data. This article will explore what insights can be gained through the use of formal concept analysis and association rules. It is hoped that these techniques will be of use to both theoreticians and policy makers.