The Journal of Regional Science (JRS) publishes original analytical research at the intersection of economics and quantitative geography. Since 1958, the JRS has published leading contributions to urban and regional thought. This includes rigorous methodological contributions and seminal theoretical pieces. The JRS is one of the most highly cited journals in urban and regional research, planning, geography, and the environment. The JRS continues to publish work that advances our understanding of the geographic dimensions of urban and regional economies, human settlements, and policies related to cities and regions.
An explanation for the rank‐size distribution for human settlements based on simple stochastic models of settlement formation and growth is presented. Not only does the analysis of the model explain the rank‐size phenomenon in the upper tail, it also predicts a reverse rank‐size phenomenon in the lower tail. Furthermore it yields a parametric form (the double Pareto‐lognormal distribution) for the complete distribution of settlement sizes. Settlement‐size data for four regions (two in Spain and two in the U.S.) are used as examples. For these regions the lower tail rank‐size property is seen to hold and the double Pareto‐lognormal distribution shown to provide an excellent fit, lending support to the model and to the explanation for the rank‐size law.
ABSTRACT At the regional level in‐migrant and indigenous workers are likely to have different income levels and consumption propensities. The effects that these differences have upon a local economy are explored within an extended input‐output modeling framework. Two iterative input‐output models, due to Miernyk et al. and Blackwell, are recast as systems of simultaneous equations and are shown to produce identical results. A detailed analysis is made of model structure and a method is outlined for the decomposition of income multipliers. Empirical versions of the two models, for Boulder and Cork, are reconstructed with data from the original studies and are used to make comparisons of the two local economies.
ABSTRACT: While research conducted over the last two decades has pointed to the important role played by household consumption in regional economic models, little attention has been directed to the consumption impacts associated not only with income changes, but also life‐cycle changes. Using Japanese data, this paper explores some of the implications of life‐cycle changes on consumption behavior using a modified AIDS (Almost Ideal Demand System) estimation system. Testing is directed to differences in age‐specific consumption behavior and the potential differences in consumption by age and province.
Rafael Suárez‐Vega, Dolores Rosa Santos Peñate, Pablo Dorta‐González
Abstract. We investigate the (r∣Xp)‐medianoid problem for networks. This is a competitive location problem that consists of determining the locations of r facilities belonging to a firm in order to maximize its market share in a space where a competitor is already operating with p facilities. We consider six scenarios resulting from the combination of three customer choice rules (binary, partially binary, and proportional) with two types of services (essential and unessential).Known discretization results about the existence of a solution for the set of nodes are extended. Some examples and computational experience using heuristic algorithms are presented.
When dealing with the design of service networks, such as health andemergency medical services, banking or distributed ticket‐selling services, the location of servicecenters has a strong influence on the congestion at each of them, and, consequently, on thequality of service. In this paper, several probabilistic maximal coveringlocation—allocation models with constrained waiting time for queue length are presentedto consider service congestion. The first model considers the location of a given number ofsingle‐server centers such that the maximum population is served within a standard distance, andnobody stands in line for longer than a given time or with more than a predetermined number ofother users. Several maximal coverage models are then formulated with one or more servers perservice center. A new heuristic is developed to solve the models and tested in a 30‐node network.