House prices in Israel have risen since 2008 by as much as 98%. Much of this increase is attributed to low levels of housing supply and housing supply elasticities. In Israel land is frequently owned by the state. This results in heavy government involvement in the housing market through the control of land supply via land tenders. This paper estimates the impact of state owned land on the Israeli housing market focusing on these unusual conditions of land supply. A model for the creation of new housing units is proposed. This incorporates land tenders, enabling the estimation of housing supply dynamics with an accurate measure of public land supply. The model is tested using regional panel data which facilitates the dynamic estimation of national and local supply elasticities and regional spillovers. The paper uses novel data sources resulting in a panel of 45 spatial units over a span of 11 years (2002–2012). Due to the nonstationary nature of the data, spatial panel cointegration methods are used. The empirical results yield estimates of housing supply price elasticities and elasticities with respect to land supply. Results show that housing supply is positively impacted by governmental decisions but the impact is low. Supply elasticity with regard to government land tenders stands at around 0.05 over the short run and 0.08 over the long run. Government policy of offering land in low demand areas and fixing minimum-price tendering does not seem to affect housing supply. Policy implications point to the need for more sensitive management of the delicate balance between public and private source of land in order to mitigate the excesses of demand shocks.

The assessment of land use plan implementation is a contentious issue. The debate centers on whether the crucial evaluation element is conformance of development to plan directives or alternatively, plan performance, i.e. the degree to which the plan is actually used. An analytic framework combining both conformance and performance in the evaluation of (regional) land use plans is applied to the case of the Central District Plan in Israel. Qualitative and quantitative simulation methods are exploited. Qualitative analysis reveals that both performance and conformance are greater than indicated by non-contextualized, numeric evaluations. Additionally, high conformance does not necessarily imply good plan performance. Quantitative simulation suggests that plan performance with respect to land values and densities is initially pronounced as expectations for development are subdued but subsequently tends to wane merging with the counterfactual trend. Findings imply that plan assessment needs to consider the transaction costs of land use re-designation and actors’ perceptions of the probability that plan amendments will be approved. These perceptions differ across actors as a function of the political influence that they wield.

This paper investigates the polarizing effect of FDI on regional earnings in host nations. A key hypothesis is that the link between FDI and regional inequality is mediated by regional capital–labor ratios. In the absence of regional FDI data, a method for estimating the effects of FDI on regional inequality is proposed in which national FDI is hypothesized to be a common factor for regional capital investment. Empirical analysis of regional panel data for Israel shows that regional capital stocks vary directly and heterogeneously with the stock of national FDI, and that regional earnings vary directly and homogeneously with regional capital–labor ratios. These two relationships are used to calculate the contribution of FDI to regional earnings inequality over time. We find a substantial polarizing effect. Between 1988 and 2010 the variance of log regional earnings increased from about 0.011 to 0.025. More than half of this increase may be attributed to the polarizing effects of FDI. Policy implications of these findings are discussed.

Standard hedonic house pricing assumes that house prices are independent of the intangible to be priced. A methodology is proposed in which the supply as well as the demand for housing depends on the intangible. The methodology is applied to value access to the Trans-Israel Highway (TIH). Using spatial panel data (2002–2008) we show that TIH had two effects on the housing market. It increased house prices in locations with greater access to TIH, and it affected housing construction. Standard hedonic pricing would have underestimated the value of access because it ignores the effects of housing construction on the intangible to be priced. House prices began to increase three years before TIH was inaugurated, but housing construction did not anticipate the inauguration of TIH.

An agent based model for assessing the welfare impacts of urban disasters is presented. This couples a population allocation algorithm with a simulation platform. The fully articulated model fuses both bottom-up (locational choice for workplace, residence and daily activities) and top-down (land use and housing price) protocols. This study moves beyond current research by addressing economic welfare consequences of urban disasters. The resilience capabilities of different income groups are identified. This is illustrated for the Jerusalem central business district. Empirical results at the micro-scale suggest that physical destruction leads to a zero-sum game within the housing market in which wealthier residents hold an advantage over the poor. This results in the transformation of neighborhoods and displacement of poor and vulnerable populations. Low income groups lose both physical ground and the social support systems that go with location. Policy implications of these findings are discussed.

This paper illustrates how synthetic big data can be generated from standard administrative small data. Small areal statistical units are decomposed into households and individuals using a GIS buildings data layer. Households and individuals are then profiled with socio-economic attributes and combined with an agent based simulation model in order to create dynamics. The resultant data is ‘big’ in terms of volume, variety and versatility. It allows for different layers of spatial information to be populated and embellished with synthetic attributes. The data decomposition process involves moving from a database describing only hundreds or thousands of spatial units to one containing records of millions of buildings and individuals over time. The method is illustrated in the context of a hypothetical earthquake in downtown Jerusalem. Agents interact with each other and their built environment. Buildings are characterized in terms of land-use, floor-space and value. Agents are characterized in terms of income and socio-demographic attributes and are allocated to buildings. Simple behavioral rules and a dynamic house pricing system inform residential location preferences and land use change, yielding a detailed account of urban spatial and temporal dynamics. These techniques allow for the bottom-up formulation of the behavior of an entire urban system. Outputs relate to land use change, change in capital stock and socio-economic vulnerability.

This paper tests the visa-led tourism hypothesis which contends that easing of visa restrictions increases international tourism. Israel acts as a natural laboratory in this case with clear before and after junctures in visa restrictions. We use panel data on tourism to Israel from 60 countries during 1994–2012. In contrast to previous work we take account of nonstationarity in the data and test for the effect of multilateral resistance on tourism. Partial waivers of visa restrictions are estimated to increase tourism by 48 % and complete waivers increase tourism by 118 %. Other results include the adverse effect of Israel’s security situation on tourism, the beneficial effect of real devaluation on tourism, and the fact that the elasticity of tourism to Israel with respect to tourism to all destinations is very small.

The location of tide gauges is not random. If their locations are positively (negatively) correlated with sea level rise (SLR), estimates of global SLR will be biased upwards (downwards). Using individual tide gauges obtained from the Permanent Service for Mean Sea Level during 1807–2010, we show that tide gauge locations in 2000 were independent of SLR as measured by satellite altimetry. Therefore these tide gauges constitute a quasi-random sample, and inferences about global SLR obtained from them are unbiased. Using recently developed methods for nonstationary time series, we find that sea levels rose in 7 % of tide gauge locations and fell in 4 %. The global mean increase is 0.39–1.03 mm/year. However, the mean increase for locations where sea levels are rising is 3.55–4.42 mm/year. These findings are much lower than estimates of global sea level (2.2 mm/year) reported in the literature and adopted by IPCC (2014), and which make widespread use of imputed data for locations which do not have tide gauges. We show that although tide gauge locations in 2000 are uncorrelated with SLR, the global diffusion of tide gauges during the 20th century was negatively correlated with SLR. This phenomenon induces positive imputation bias in estimates of global mean sea levels because tide gauges installed in the 19th century happened to be in locations where sea levels happened to be rising.

A model is proposed in which building contractors have regional preferences so that housing construction in different regions are imperfect substitutes. The model hypothesizes spatial and national spillovers in construction. Although the government does not engage directly in housing construction, it influences regional housing markets by auctioning land to contractors. Contractors are hypothesized to use housing-under-construction as a buffer between starts and completions. Spatial panel data for Israel are used to test the model and investigate the determinants of regional housing construction. Because the spatial panel data are nonstationary, we use spatial panel cointegration methods to estimate the model. The estimated model is used to calculate impulse responses which propagate over time and across space.

An important, but overlooked component of disaster managment is raising the awareness and preparedness of potential stakeholders. We show how recent advances in agent-based modeling and geo-information analytics can be combined to this effect. Using a dynamic simulation model, we estimate the long run outcomes of two very different urban disasters with severe consequences: an earthquake and a missile attack. These differ in terms of duration, intensity, permanence, and focal points. These hypothetical shocks are simulated for the downtown area of Jerusalem. Outcomes are compared in terms of their potential for disaster mitigation. The spatial and temporal dynamics of the simulation yield rich outputs. Web-based mapping is used to visualize these results and communicate risk to policy makers, planners, and the informed public. The components and design of this application are described. Implications for participatory disaster management and planning are discussed.

Purpose – The purpose of this paper is to examine the determinants of immigration from European Neighborhood (EN) and new member states to the EU core countries over the period 2000- 2010. Apart from income differentials, unemployment rates and other standard variables hypothesized to determine immigration, the paper focusses attention on welfare-chasing as well as measures to enforce immigration policy. Using a variant of the gravity model, the paper investigates whether tests of these hypotheses are robust with respect to spatial misspecification.
Design/methodology/approach – The determinants of migration from the European Neighborhood and new member states to the EU core countries is estimated using a spatial variant of the gravity model. The methodology is used for both multilateral and spatial flows. Gravity model estimations are presented for immigration into the EU core destinations using standard, non-spatial econometrics, as well as spatial econometrics for single and double-spatial dynamics
Findings – Immigration to EU core countries varies directly with the change in social spending per head in the destination. This result stands out in all the models, both OLS and spatial. Immigrants are attracted by economic inequality as measured by the Gini coefficient. However, in this case it is the level that matters rather than its change. No evidence is found that the threat of apprehension at the destination deters migrants from the European Neighborhood and other countries. 
Research limitations/implications – The authors assume multilateralism is spatial. This means that everything else given, destinations are closer substitutes the nearer they are, and that immigration shocks are likely to be more correlated among origins the closer they are. This implicit assumption is restrictive because multilateralism is just spatial.
Social implications – While immigration to EU core countries varies directly with the change in (not level of ) social spending per head. If a given country becomes more benevolent it attracts more immigration. The results suggest that if during 2000-2010 social spending per capita grew by 1 percent, the immigration rate increased by between 1 and 2 percentage points relative to the number of foreign-born in 2000. This is a large demographic effect.
Originality/value – Uniquely, this paper does not assume immigration flows are independent and stresses their spatial and multilateral nature. A series of new non-spatial and spatial (single and double-spatial lag) models are used to empirically test hypotheses about the determinants of immigration to the EU core countries.

The role of human capital and physical capital in determining regional productivity and innovation is examined. Two specific mechanisms through which knowledge becomes an inherently regional asset are investigated: the generation of local externalities (a stock mechanism) and human capital accumulation and mobility (a flow mechanism). Empirically, this connection is investigated using recent advances in spatial panel data analysis applied to regions in Israel. Panel co-integration is used to entangle issues of spurious relationships. Results show that human capital stock has large and relatively consistent effects on both regional earnings and regional innovation levels. Human capital mobility is inversely related to innovation. This is interpreted as reflecting the ‘conduit’ role of the region in the innovation process. Regional capital-to-labour ratios are also inversely related to innovation, implying that physical capital substitutes rather than complements human capital.

An agent based (AB) simulation model of urban dynamics following a disaster is presented. Data disaggregation is used to generate ‘synthetic’ data with accurate socio-economic profiling. Entire synthetic populations are extrapolated at the building scale from survey data. This data is coupled with the AB model. The disaggregated baseline population allows for the bottom-up formulation of the behavior of an entire urban system. Agent interactions with each other and with the environment lead to change in residence and workplace, land use and house prices. The case of a hypothetical earthquake in the Jerusalem CBD is presented as an illustrative example. Dynamics are simulated for a period up to 3 years, post-disaster. Outcomes are measured in terms of global resilience measures, effects on residential and non-residential capital stock and population dynamics. The visualization of the complex outputs is illustrated using dynamic web-mapping.

This paper assesses the socioeconomic consequences of extreme coastal flooding events. Wealth and income impacts associated with different social groups in coastal communities in Israel are estimated. A range of coastal flood hazard zones based on different scenarios are identified. These are superimposed on a composite social vulnerability index to highlight the spatial variation in the socioeconomic structure of those areas exposed to flooding. Economic vulnerability is captured by the exposure of wealth and income. For the former, we correlate the distribution of housing stock at risk with the socioeconomic characteristics of threatened populations. We also estimate the value of residential assets exposed under the different scenarios. For the latter, we calculate the observed change in income distribution of the population under threat of inundation. We interpret the change in income distribution as an indicator of recovery potential.