This monograph deals with spatially dependent nonstationary time series in a way accessible to both time series econometricians wanting to understand spatial econometics, and spatial econometricians lacking a grounding in time series analysis. After charting key concepts in both time series and spatial econometrics, the book discusses how the spatial connectivity matrix can be estimated using spatial panel data instead of assuming it to be exogenously fixed. This is followed by a discussion of spatial nonstationarity in spatial cross-section data, and a full exposition of non-stationarity in both single and multi-equation contexts, including the estimation and simulation of spatial vector autoregression (VAR) models and spatial error correction (ECM) models. The book reviews the literature on panel unit root tests and panel cointegration tests for spatially independent data, and for data that are strongly spatially dependent. It provides for the first time critical values for panel unit root tests and panel cointegration tests when the spatial panel data are weakly or spatially dependent. The volume concludes with a discussion of incorporating strong and weak spatial dependence in non-stationary panel data models. All discussions are accompanied by empirical testing based on a spatial panel data of house prices in Israel.
Demand for household insurance is intuitively perceived as contributing to household and community resilience. However the causality in this relationship is not clear. This paper examines household insurance expenditure and the generation of urban resilience as jointly determined. Potential endogeneity is purged by estimating this relationship as a system and using an instrumental variable approach. Empirical analysis based on aggregated Israeli household expenditure data is used. Results show that instrumenting makes a difference, that a distinction needs to be drawn between personal resilience and environmental resilience and that insurance coverage has an independent effect on resilience different to that of classic social (personal) and economic (property and place-based) characteristics. The policy context of the findings are discussed.
A structural spatial econometric model for nine regions of Israel is estimated using non-stationary spatial panel data during 1987–2015. The model focuses on the relation between regional markets in labour, housing and capital when there is imperfect internal migration between regions, when capital is imperfectly mobile between regions, and when building contractors operate across regions. Since the regional panel data are non-stationary, the econometric methodology is based on spatial panel cointegration. The estimated model is used to simulate the temporal and spatial propagation of regional shocks induced, for example, by regional policy (land for housing, regional investment grants). Impulse responses are temporally and spatially state dependent. They are also highly persistent because of longevity in housing and capital.
The value of most ecosystem services invariably slips through national accounts. Even when these values are estimated, they are allocated without any particular spatial referencing. Little is known about the spatial and distributional effects arising from changes in ecosystem service provision. This paper estimates spatial equity in ecosystem services provision using a dedicated data disaggregation algorithm that allocates ‘synthetic’ socio-economic attributes to households and with accurate geo-referencing. A GIS-based automated procedure is operationalized for three different ecosystems in Israel. A nonlinear function relates household location to each ecosystem: beaches, urban parks and national parks. Benefit measures are derived by modeling household consumer surplus as a function of socio-economic attributes and distance from the ecosystem. These aggregate measures are spatially disaggregated to households. Results show that restraining access to beaches causes a greater reduction in welfare than restraining access to a park. Progressively, high income households lose relatively more in welfare terms than in low income households from such action. This outcome is reversed when distributional outcomes are measured in terms of housing price classes. Policy implications of these findings relate to implications for housing policies that attempt to use new development to generate social heterogeneity in locations proximate to ecosystem services.
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.
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.
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.
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.
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.
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 (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.