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Publications | Daniel Felsenstein

Publications

2016
Hedonic Pricing when Housing is Endogenous: The Value of Access to the Trans-Israel Highway
M., Beenstock, Feldman D., and Felsenstein D. 2016. Hedonic Pricing when Housing is Endogenous: The Value of Access to the Trans-Israel Highway. Journal of Regional Science 56(1):134-155. Retrieved (). Publisher's VersionAbstract
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.
Dynamic Agent-Based Simulation of Welfare Effects of Urban Disasters
Y., Grinberger, and Felsenstein D. 2016. Dynamic Agent-Based Simulation of Welfare Effects of Urban Disasters. Computers, Environment and Urban Systems 59:129-141. Retrieved (). Publisher's VersionAbstract
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.
Spatial Dependence in the Econometrics of Gravity Modeling
M., Beenstock, and Felsenstein D. 2016. Spatial Dependence in the Econometrics of Gravity Modeling. in Patuelli R and Arbia G (eds) Chapter 11 in The Spatial Econometrics of Spatial Interaction Modeling. Heidelberg: Springer Retrieved (). Publisher's Version
Dynamic Agent Based Simulation of an Urban Disaster using Synthetic Big Data
Grinberger, A. Y., M. Lichter, and D. Felsenstein. 2016. Dynamic Agent Based Simulation of an Urban Disaster using Synthetic Big Data. in Thakuria P, Tilahun N and Zellner M (eds) Seeing Cities Through Big Data: Research, Methods and Applications in Urban Informatics. Heidelberg: Springer Retrieved (). Publisher's VersionAbstract
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.