In theory, new regional jobs yield two distinct sources of welfare gains to workers: (1) mobility gains achieved by workers as they move up job chains and (2) traditional Marshallian surpluses enjoyed by all workers as labor markets tighten. In the past, we have argued that the second channel is likely to be small relative to the first. This paper integrates a chain model (using PSID job change data) with a modified-Marshallian model based on “wage curves” (estimated from CPS data) to formalize and test that argument. High wage jobs with modest wage–unemployment elasticities show Marshallian effects only 10 percent to 20 percent the size of mobility effects. Low wage jobs with somewhat higher elasticities show Marshallian effects from 40 percent to 70 percent the size of mobility effects.

The tourism industry is characterized by severe shifts in demand that play havoc with forecasting future investment. Within the tourism industry, the need for large-scale initial capital investment in the hotel sector, make the latter particularly vulnerable to the vagaries of the tourism market. Given an up-turn in demand, the hotel industry cannot always respond immediately and its' response is likely to vary across regions. There is therefore a need for a forecasting tool that can estimate the magnitude of the demand 'push' that can stimulate the hotel sector into new investment and the extent to which this response is regionally differentiated. Using a multi-regional input output (MRIO) augmented by an investment matrix, this paper demonstrates the capabilities of such an approach. Regional hotel industry outputs for four classes of hotels in the six regions of Israel are estimated. Expected regional rates of return to hotel investment are compared with actual (reported) rates of return and the discrepancy between the two explained. Regional hotel (per room) capacity coefficients are also estimated and regional responses to an increase in demand of 100,000 extra tourists are calculated in terms of additional hotel rooms and capital investment.

The paper stresses the importance of accounting for regional heterogeneity in the dynamic analysis of regional economic disparities. Studies of regional growth mainly presume that regions are homogeneous in their socio-demographic composition. It is argued that the analysis of regional convergence needs to be tested conditionally, i.e. conditional upon the socio-demographic structure of the workers in the various regions. To this end, various measures of conditional regional earnings inequality are estimated using Israeli regional data for the period 1991–2002. The results show that about half of regional earnings inequality may be accounted for by the conditioning variables. Conditioning also makes a large difference to estimates of Gini and beta-convergence. Conditional beta and Gini mobility are about half their unconditional counterparts.

This paper tests the hypothesis that fear is a central factor in understanding human behaviour in the face of terror. This claim is addressed in the context of behaviour in the Jerusalem housing market over the terror-stricken years in the city, 1999—2004. Using a unique data source and the tools of spatial data analysis, the paper provides support for this hypothesis in three respects. First, patterns of terror in the city are shown to be increasingly deconcentrated over the period studied. Secondly, the types of terror having the sharpest effect on residential property prices are those most associated with randomness. Thirdly, the effect of terror is less on purchasing prices than on rental prices. The former represent revealed long-term behaviour less affected by fear and the latter, short-term behaviour more likely to be influenced by such disutility. The paper concludes with some of the policy implications arising from these findings.

A spatial vector autoregressive model (SpVAR) is defined as a VAR which includes spatial as well as temporal lags among a vector of stationary state variables. SpVARs may contain disturbances that are spatially as well as temporally correlated. Although the structural parameters are not fully identified in SpVARs, contemporaneous spatial lag coefficients may be identified by weakly exogenous state variables. Dynamic spatial panel data econometrics is used to estimate SpVARs. The incidental parameter problem is handled by bias correction rather than more popular alternatives such as generalised methods of moments (GMM). The interaction between temporal and spatial stationarity is discussed. The impulse responses for SpVARs are derived, which naturally depend upon the temporal and spatial dynamics of the model. We provide an empirical illustration using annual spatial panel data for Israel. The estimated SpVAR is used to calculate impulse responses between variables, over time, and across space. Finally, weakly exogenous instrumental variables are used to identify contemporaneous spatial lag coefficients.

The literature on regional growth convergence and economic disparities has tended to confound four interwoven measurement phenomena: 1) mean reversion (so-called beta convergence)—richer regions move towards the average from above and poorer regions from below; 2) diminishing inequality (so called sigma convergence)—the horizontal or spatial distribution of income becomes more equal; 3) mobility—the rank of a region in the overall distribution of income changes either upwards or downwards; and 4) leveling—the richer regions become poorer (leveling-down) or the poorer regions become richer (leveling-up). We use a new statistical methodology that treats these four phenomena on an integrated basis. The methodology is applied to Israeli regional earnings. We show that regional earnings are Gini divergent, but after adjusting earnings for regional cost-of-living differential, this picture is reversed. In the absence of genuine cost-of-living data, a simple and practical method is proposed, whereby regional house price data are used to proxy regional cost-of-living differentials.

This article introduces economic development planners to a new approach to evaluating local job creation efforts, an approach that explicitly considers the chains of employment vacancies that open up when new jobs are created. This “job chains” model is an analytic framework for assessing the employment impacts associated with economic development programs and the social value of those impacts. The approach focuses on measuring the wage gains to job changers and placing realistic values on jobs for those not previously employed in the area. It explicitly considers both efficiency and distributional effects of job creation. We discuss the simple mechanics of the technique and present an example relating to the establishment of a large auto plant in a major Midwestern city. We conclude with practical ground rules for planners carrying out a job chains analysis of an economic development effort.

Employment deconcentration has become a major issue on the policy and planning agenda in many metropolitan areas throughout the western world. In recent years, growing evidence indicates that in many developed countries, the deconcentration of employment - particularly of retail centres and offices - has become a key planning issue. This chapter uses the UrbanSim forecasting and simulation model in order to investigate some of the projected changes in land use, land value and sociodemographic characteristics of metropolitan areas undergoing employment deconcentration. The process of model application in the Tel Aviv metropolitan context is described. Two land-use scenarios of very different scales are simulated: a macro-level scenario relating to the imposition of an ‘urban growth boundary’ and a micro-level scenario simulating the effects of a shopping mall construction in different parts of the metropolitan area. The results are discussed in terms of the potential and constraints of microsimulation for analyzing metropolitan growth processes.

The job chains model of local labor market change is a demand-driven analytic device for estimating the effects of new job creation. This paper explores the effects of restricting supply, i.e., limiting job access, on the model’s primary outcomes: vacancy chain multipliers, welfare effects, and distributional impacts. Major sources of labor supply are the local unemployed, out of the labor force and in-migrants. Three simulations are reported relating to (1) restricting new jobs to current local residents (i.e., no in-migrants), (2) restricting new jobs to current residents in the first round of hiring only, and (3) restricting hiring to local unemployed/out of labor force on the first round alone. The results are compared to the basic model that assumes no supply-side restrictions. In terms of chain length, welfare effects, distributional impacts, and policy palatability, first-round restrictions on in-migrants would seem to be the most plausible option. However, as an economic development strategy, well-targeted demand-side initiatives would still seem to be preferable.

This paper revisits the commonly held view that small countries do not exhibit significant regional disparities. The issue is framed as one in which the attributes of small size (land area, population and the magnitude of the economy) are mediated by a series of spatial and non‐spatial factors such as distance, density, factor mobility, natural resources, land supply, social cohesion and governance structure. Given the existence of these mediators, the magnitude of regional disparities in small countries is not as surprising as it may seem at first glance.