The main features of the contributions to this special issue on Simulating Land Use Change in Coastal Areas, are synthesized. Three key themes for coastal zone research and management are identified. These relate to the need for (1) making new analytic techniques relevant to coastal zone management, (2) communicating results to the public without inhibiting civic participation through technological over-kill and (3) designing public policy cognizant of the special conditions under which land use change operates in coastal areas.

This paper examines the displacement effects associated with new land use development in a congested coastal area. A land use micro-simulation model (UrbanSim) and statistical estimation are used to identify the expected future land use impacts arising from the proposed expansion of the Port of Haifa. Maximum and minimum development scenarios are simulated and compared to baseline (business-as-usual) conditions. Simulation outputs refer to future population, employment, residential and non-residential construction for the city of Haifa and its metropolitan area untill the year 2038. A key finding relates to the spatial substitution effects of additional non-residential floor space on residential development throughout the Haifa region. This highlights the zero sum effects of land use change under conditions of congestion. The challenge of efficiently using limited land use resources and balancing development across many competing uses and stakeholders, is stressed.

We examine the threat to coastal communities from sea level rise and extreme flooding. A distinction is drawn between the exposure of the physical property base of a community and its social composition. We investigate whether any correspondence exists between these two dimensions of vulnerability and whether it holds for both small and large communities. Flood scenarios along the Israeli coast are defined and we  look at the resultant property and exposure patterns in communities at different flooding increments. Results are presented for three select inundation increments. Using comparative and graphic methods, we analyze exposure rankings for different communities and property and social exposure at the intra-urban level. We use break point analysis to trace the evolution of community exposure at different flooding increments. We conclude with some cautionary policy implications with respect to opportunities for change in highly exposed communities in the wake of extreme flooding.

While the direct physical effects of an urban catastrophe are relatively straightforward to assess, indirect and long-term impact on the urban system is more circumspect. A large-scale shock such as an earthquake derails the complex urban system from its equilibrium path onto an unknown trajectory. Consequently, assessing the effect of policy intervention that aims to mitigate this shock and increase urban resilience is fraught with complexity. This paper presents the implementation of dynamic agent-based simulation to test long-run effects of a hypothetical earthquake in Jerusalem, Israel. It focuses on investigating the effectiveness of policy choices aimed at restoring the urban equilibrium. Cities are found to have a self-organising market-based mechanism that strives to attain a new equilibrium. They therefore may not always bounce back – they may also bounce forward. Decision-makers, engineers, emergency and urban planners need to be cognizant of this tendency when designing policy interventions. Otherwise, well-intentioned efforts may inhibit urban rejuvenation and delay the onset of city recovery.

Diverse pressures for change operate at the outer metropolitan fringe. This paper examines the spatial and temporal dynamics of change in this area. We set up a simple model that incorporates spatial and temporal dynamics of functional (land use) and structural (land cover) interactions. We posit that land use (development) changes the ecosystem functions at the edge of urban areas expressed in change in land cover. Additionally, the characteristics of land cover (forest, agriculture, bare soil, neighboring cover etc.) mutually influence the land use. We estimate a model where land values and land use are jointly determined while land use and land cover interact recursively. We use historical data, probability estimation and land use simulation to generate panel data of future patterns of land value, land use and land cover at the outer edge of the Tel Aviv metropolitan area for the period 1995–2023. The modeling system combines panel 2SLS (2-stage least squares) estimation to investigate land value-land use interactions. Land use-land cover dynamics are estimated using panel MNL (multi-nomial logit) estimation. Results of simple simulations of the probability of land cover change are presented. When coupled with an appropriate biodiversity model, this system could potentially be extended to forecasting other aspects of the environmental stress of metropolitan expansion, for example impacts on vegetation or ecological dynamics.

We use moments from the covariance matrix for spatial panel data to estimate the parameters of the spatial autoregression model, including the spatial connectivity matrix W. In the unrestricted spatial autoregression model, the parameters are underidentified by one when W is symmetric. We show that a special case exists in which W is asymmetric and its parameters are exactly identified. If the panel data are stationary and ergodic, spatially and temporally, the estimates of W and the spatial autoregression coefficients are consistent. Spatial panel data for house prices in Israel are used to illustrate this methodology.

This paper suggests a model of obtaining estimates of capital stock based on the theory of ‘flexible accelerator’. However, this represents a rather ‘indirect’ method independently for each year and each region. Clearly this is an unrealistic condition, especially for regional economies characterized by mutual spatial dependence. To add an extra injection of realism, we illustrate how a national model of capital stock (the stock –flow model) can effectively be ‘regionalized’

This paper presents a systematic framework for assessing the costs of sea-level rise (SLR) and extreme flooding at the local level. The method is generic and transferable. It is built on coupling readily available GIS capabilities with quantitative estimates of the effects of natural hazards. This allows for the ex ante monetization of the main costs related to different scenarios of permanent inundation and periodic flooding. This approach can be used by coastal zone planners to generate vital information on land use, capital stock and population at risk for jurisdictions of different sizes. The simple mechanics of the method are presented with respect to two examples: one relates to the two largest coastal cities in Israel (Tel Aviv and Haifa) and the other to the Northern Coastal Strip region containing a variety of small towns and rural communities. The paper concludes with implications for coastal zone planning praxis.

This paper looks at capacity expansion relating to an airport and the derived tourist demand that this facilitates. The context is the airport relocation planned for the tourist destination of Eilat, Israel. The paper addresses three issues. First, using a multi-regional input output model for Israel, we estimate the magnitude of the static inter-sectoral impacts associated with airport construction and operation and their impact on the regional and national economy. Second, we focus on the lag effects in this process as increased tourism demand does not elicit an immediate response on the supply side in terms of new hotel investment. Third, on the demand side, we estimate additional tourism expenditure in non-hotel activities over the period that the market adjusts and beyond.

Over the past decade, the welfare evaluation of local economic development activities has become increasingly sophisticated. Projected or realized gains have been broken down by wage levels, household income levels, and race. However, relatively little attention has been paid to the distribution of gains by gender. In parallel, the gender literature has recognized the distribution of economic development activity by income group but not by vacancies. The authors present an evaluation approach—the job chains model—that combines the two. Occupations with a high proportion of women are identified and isolated at each wage level. The authors estimate the proportion of job chain vacancies induced by new “female” jobs and their welfare impacts. Findings suggest that women are underrepresented in welfare gains associated with both male and female high-wage jobs. The applicability of the authors’ approach for evaluating alternative industrial targets is demonstrated.

We present a simple reproducible methodology for constructing regional capital stock data, which we apply to Israel. We find that capital deepening has been sigma-convergent since 1985. This process is “inverted” since capital stocks and capital–labor ratios in the richer center have been catching-up with their counterparts in the poorer periphery. We explain this phenomenon in terms of fundamental changes in regional policy. Despite this, regional wages have not been sigma-convergent because other wage determinants have been sigma-divergent.

The paper looks at the sensitivity of commonly used income inequality measures to changes in the ranking, size and number of regions into which a country is divided. During the analysis, several test distributions of populations and incomes are compared with a ‘reference’ distribution, characterized by an even distribution of population across regional subdivisions. Random permutation tests are also run to determine whether inequality measures commonly used in regional analysis produce meaningful estimates when applied to regions of different population size. The results show that only the population weighted coefficient of variation (Williamson’s index) and population-weighted Gini coefficient may be considered sufficiently reliable inequality measures, when applied to countries with a small number of regions and with varying population sizes.

We “spatialize” residual-based panel cointegration tests for nonstationary spatial panel data in terms of a spatial error correction model (SpECM). Local panel cointegration arises when the data are cointegrated within spatial units but not between them. Spatial panel cointegration arises when the data are cointegrated through spatial lags between spatial units but not within them. Global panel cointegration arises when the data are cointegrated both within and between spatial units. Spatial error correction arises when error correction occurs within and between spatial units. We use nonstationary spatial panel data on the housing market in Israel to illustrate the methodology. We show that regional house prices in Israel are globally cointegrated in the long run and there is evidence of spatial error correction in the short run.

A strong inter-dependence exists between the decision to develop land and the expected returns to be gained from that development. Current practice in UrbanSim modeling treats developer behavior and the emergence of land prices as independent processes. This assumes that land prices are exogenous to the interaction between buyers and sellers—an assumption that is difficult to sustain in urban economics and real estate research. This paper presents an attempt to model the two processes as occurring simultaneously. Using the UrbanSim model for metropolitan Tel Aviv, we compare the results of forecasts for densities (residential and non-residential) and land values for the period 2001–2020. Our results show that simultaneous estimation tends to produce more accentuated outcomes and volatile trends. The validity of these results and the implications of this approach in the wider context of land use modeling are discussed.

Many countries evade the formal valuation of real property for taxation purposes by using qualitative and spatial criteria in order to pursue an equitable distribution of burden. This paper evaluates the performance of a prototypical setup as such, by analyzing the relationship between property value, household income and the actual tax paid, in the exact framework of which the qualitative criteria are set to determine tax assessment. Drawing on detailed data from the Israeli Household Expenditure Surveys 1997–2005, the strong correlation between the three variables is evident. Yet, the limited differences in rates, compared with large variation in property value, make it regressive. Policy implications are relevant for many other countries using non-ad valorem taxation.

Most models of regional agglomeration are based on the new economic geography (NEG) model in which returns to scale are pecuniary. We investigate the implications for regional agglomeration of a ‘Marshallian’ model in which returns to scale derive from technological externalities. Workers are assumed to have heterogeneous ‘home region’ preferences. The model is designed to explain how ‘second nature’ determines regional wage inequality and the regional distribution of economic activity. We show that agglomeration is not a necessary outcome of Marshallian externalities. However, if centrifugal or positive externalities are sufficiently strong relative to their centripetal or negative counterparts, the model generates multiple agglomerating equilibria. These equilibria multiply if, in addition, there are scale economies in amenities. A dynamic version of the model is developed in which external economies and inter-regional labour mobility grow over time. Regional wage inequality overshoots its long run equilibrium and, there is more agglomeration in the long run.