DERIVATIVES OF FLOWS IN A DOUBLY CONSTRAINED GRAVITY MODEL

For many practical applications it is important to know how the flows in a doubly constrained gravity model react to slight variations in the predetermined marginal totals. The first-order approximation of these variations is a linear function on the set of feasible variations of marginal totals, i.e., the set of variations not violating the consistency constraint of the model. Several methods to find a matrix describing this linear function are developed and compared with former contributions to this issue. Finally, applicability of the methods to sensitivity and error propagation analysis is demonstrated.     

THE DETERMINANTS OF THE RECENT INTERREGIONAL MIGRATION FLOWS IN ITALY: A PANEL DATA ANALYSIS*

ABSTRACT This study investigates the determinants of interregional migration flows in Italy in the light of the upsurge occurred in 1996, after two decades of decreasing internal migration rates. The fixed‐effect vector decomposition estimator (FEVD) is applied to a gravity model using bilateral migration flows for the period 1996–2005. It is shown that the FEVD improves the estimates with respect to the traditional panel data estimators. The GDP per capita and the unemployment rate appear to be the key determinants whose changes push migrants out from their regions and direct them to “better off” destinations. Migrants leaving the regions in the Center‐North respond differently to the push and pull forces compared to southern migrants. The dynamic model provides evidence for the presence of social networks, which in this analysis take place for each pair of regions.     

圆形城市商品销售的空间受限模型

本文首先提出商品价格空间分布的分形函数,以此为基础导出商品销售的空间受限模型,该模型揭示了人地非线性相关的某些机制,并为企业选择投资区位提供了分析方法。     

ARTIFICIAL NEURAL NETWORKS: A NEW APPROACH TO MODELING INTERREGIONAL TELECOMMUNICATION FLOWS*

ABSTRACT. During the last thirty years there has been much research effort in regional science devoted to modeling interactions over geographic space. Theoretical approaches for studying these phenomena have been modified considerably. This paper suggests a new modeling approach, based upon a general nested sigmoid neural network model. Its feasibility is illustrated in the context of modeling interregional telecommunication traffic in Austria, and its performance is evaluated in comparison with the classical regression approach of the gravity type. The application of this neural network approach may be viewed as a three-stage process. The first stage refers to the identification of an appropriate network from the family of two-layered feedforward networks with 3 input nodes, one layer of (sigmoidal) intermediate nodes and one (sigmoidal) output node (logistic activation function). There is no general procedure to address this problem. We solved this issue experimentally. The input-output dimensions have been chosen in order to make the comparison with the gravity model as close as possible. The second stage involves the estimation of the network parameters of the selected neural network model. This is performed via the adaptive setting of the network parameters (training, estimation) by means of the application of a least mean squared error goal and the error back propagating technique, a recursive learning procedure using a gradient search to minimize the error goal. Particular emphasis is laid on the sensitivity of the network performance to the choice of the initial network parameters, as well as on the problem of overfitting. The final stage of applying the neural network approach refers to the testing of the interregional teletraffic flows predicted. Prediction quality is analyzed by means of two performance measures, average relative variance and the coefficient of determination, as well as by the use of residual analysis. The analysis shows that the neural network model approach outperforms the classical regression approach to modeling telecommunication traffic in Austria.     

ON THE SENSITIVITY OF GRAVITY MODEL FORECASTS*

In this paper we present a procedure for estimating small changes in gravity model forecasts in response to small changes in input values (trip end totals and/or parameter values). The procedure can be used to derive covariance matrices from which confidence intervals may be obtained and which may be used for tests of hypotheses. While this type of problem has been addressed by others, our approach is the only one that is conveniently applicable to the doubly constrained model and can accommodate the large numbers of origin and destination zones one typically encounters.     

THE GRAVITY MODEL AND HIERARCHICAL SPATIAL SYSTEMS: THEORETICAL AND EMPIRICAL OBSERVATIONS

The gravity model in its basic forms postulates that the volume of interaction between two places will be positively related to the populations (masses) of the two places and inversely related to their distance apart. Although it is not strictly speaking a hierarchical model, it is often used to explain flows among places that constitute a hierarchical spatial system. This paper is specifically concerned with the effect of hierarchical spatial structure on the performance of the gravity model. Accordingly, I will examine first the effect of hierarchical structure on the volume of interaction between places and second the degree to which the gravity model incorporates these hierarchical effects. Third, suggestions will be made for the improvement of the gravity model's performance by an explicit incorporation of a hierarchical element. The performance of the gravity model will be examined for both one-way and two-way flows between places.     

INTERREGIONAL ARBITRAGE AND THE SUPPLY OF LOANABLE FUNDS: A MODEL OF INTERMEDIATE FINANCIAL CAPITAL MOBILITY*

ABSTRACT This paper develops a model of regional financial markets which can encompass different degrees of spatial financial integration. The behavior of the system is analyzed under alternative assumptions about the time frame of analysis and the extent of the flexibility of interest rates. It is argued that links may exist between regional real and financial sectors even in the short run and that such links must, through the regional balance of payments, exist in the long run, even where there is perfect financial spatial integration. It is observed that these relationships have generally been ignored by regional economic model builders.