Browsing by Author "Iacono, Michael J"

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    Accessibility Dynamics and Location Premia: Do Land Values Follow Accessibility Changes?
    (2016) Iacono, Michael J; Levinson, David M
    The structure of transportation networks and the patterns of accessibility they give rise to are an important determinant of land prices, and hence urban spatial structure. While there is ample evi- dence on the cross-sectional relationship between location and land value (usually measured from the value of improved property), there is much less evidence available on the changes in this rela- tionship over time, especially where location is represented using a disaggregate measure of urban accessibility. This paper provides evidence of this dynamic relationship using data on home sales in the Minneapolis-St Paul, MN, USA metropolitan area, coupled with disaggregate measures of urban accessibility for multiple modes, for the period from 2000 to 2005. Our investigation tracks the effects of marginal changes in accessibility over time, as opposed to static, cross- sectional relationships, by using an approach in which the unit of observation is a ‘representative house’ for each transportation analysis zone in the region. This approach allows us to control for changes in structural attributes of houses over time, while also isolating the effect of changes in accessibility levels. Results of this approach are compared with a cross-sectional model using the same variables for a single year to illustrate important differences. Empirical estimates indicate that while most of the models estimated using a cross-sectional specification yield positive and significant effects of accessibility on sale prices, these effects disappear when the models are transformed into first-difference form. We explain these findings in light of the state of maturity of urban transportation networks.
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    Intraurban Accessibility and Employment Density
    (2006-08-01) Iacono, Michael J; Cao, Jason X; Cui, Mengying; Levinson, David M
    This study investigates the relationship between urban accessibility and firm agglomeration, as reflected in patterns of urban employment densities. We use measures of accessibility derived from the regional highway network, combined with small-scale (Census block-level) data on employment from the Longitudinal Employer-Household Dynamics (LEHD) data set to generate proxies for different sources of agglomeration, specifically urbanization and localization economies. These variables are employed in a set of employment density regressions for 20 two-digit NAICS code sectors to identify the propensity of each sector to agglomerate in response to varying levels of accessibility. The density regressions are applied to sample data from the Minneapolis-St. Paul, Minnesota (Twin Cities) metropolitan region for the years 2000 and 2010. We find that in general urbanization effects tend to overshadow those of localization effects. Moreover, these effects tend to vary by sector, with many service-based sectors showing a stronger propensity to agglomerate than manufacturing and several "basic" sectors like agriculture, mining and utilities.
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    Location, Regional Accessibility and Price Effects: Evidence from Home Sales in Hennepin County, Minnesota.
    (Transportation Research Board, 2011) Iacono, Michael J; Levinson, David M.
    Regional location factors, with measures of regional accessibility foremost among them, exert a strong influence on urban property markets. While accessibility represents an important regional-scale factor, more local influences such as proximity to urban highway links may also positively or negatively influence the desirability of a location. In this paper, we use a cross-section of home sales in Hennepin County, Minnesota from the years 2001 through 2004, along with a set of disaggregate regional accessibility measures, to estimate the value of access to employment and resident workers. We also estimate the (dis)amenity effects of locations near major freeway links that have recently undergone, or were scheduled to undergo (as of the time period covered by the home sales), major construction to add capacity. The richness of the home sales data set allows us to control for a number of structural attributes, as well as some site characteristics, while additional neighborhood characteristics (such as income levels and local educational quality) are added from supplemental data sources. Empirical results indicate that households highly value employment access, while access to other resident workers (i.e. competition for jobs) is considered a disamenity. Proximity to local highway access points is positively associated with sale price, while proximity to the highway link itself is negatively associated with price. The paper concludes with some implications for research and practice of the concept and measurement of the relationship between location and land value.
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    Markov Chain Model of Land Use Change
    (2015) Iacono, Michael J; Levinson, David M; El-Geneidy, Ahmed; Wasfi, Rania A
    The set of models available to predict land use change in urban regions has become increasingly complex in recent years. Despite their complexity, the predictive power of these models remains relatively weak. This paper presents an example of an alternative modeling framework based on the concept of a Markov chain. The model assumes that land use at any given time, which is viewed as a discrete state, can be considered a function of only its previous state. The probability of transition between each pair of states is recorded as an element of a transition probability matrix. Assuming that this matrix is stationary over time, it can be used to predict future land use distributions from current data. To illustrate this process, a Markov chain model is estimated for the Minneapolis-St. Paul, MN, USA (Twin Cities) metropolitan region. Using a unique set of historical land use data covering several years between 1958 and 2005, the model is tested using historical data to predict recent conditions, and is then used to forecast the future distribution of land use decades into the future. We also use the cell-level data set to estimate the fraction of regional land use devoted to transportation facilities, including major highways, airports, and railways. The paper concludes with some comments on the strengths and weaknesses of Markov chains as a land use modeling framework, and suggests some possible extensions of the model.
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    Methods for Estimating the Economic Impacts of Transportation Improvements: An Interpretive Review
    (Edward Elgar Publishers, 2015) Iacono, Michael J; Levinson, David M
    This chapter reviews several methods of evaluating the economic impacts of transportation improvements. We begin with a discussion of basic project-based methods, such as benefit- cost analysis, and discuss some issues which may complicate the accurate estimation of user benefits over the life of a project, especially the dynamic and recursive relationship between transportation networks and land development. We discuss the possible role of capitalized land value changes as an alternate source of estimated user benefits. We then move on to a discussion of regional economic analysis models as a tool for examining the effects of large- scale projects or packages of transportation improvements. Their linkages with non-traditional sources of benefits, such as agglomeration effects, and also network effects is considered. Lastly, we consider aggregate analysis methods. These include production function analy- ses, cliometric studies, and other types of empirical investigations of the relationship between transportation and econometric growth at an aggregate scale. We close by commenting on the merits of each approach, and where and how they might usefully be applied.
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    Models of Transportation and Land Use Change: A Guide to the Territory
    (Sage, 2008) Iacono, Michael J; Levinson, David M
    Modern urban regions are highly complex entities. Despite the difficulty of modeling every relevant aspect of an urban region, researchers have produced a rich variety models dealing with inter-related processes of urban change. The most popular types of models have been those dealing with the relationship between transportation network growth and changes in land use and the location of economic activity, embodied in the concept of accessibility. This paper reviews some of the more common frameworks for modeling transportation and land use change, illustrating each with some examples of operational models that have been applied to real-world settings.
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    Mutual Causality in Road Network Growth and Economic Development
    (2016) Iacono, Michael J; Levinson, David M
    This paper investigates the relationship between the growth of road networks and regional development. We test for mutual causality between the growth of road networks (which are divided functionally into local roads and highways) and changes in county-level population and employment. We employ a panel data set containing observations of road mileage by type for all Minnesota counties over the period 1988 to 2007 to fit a model describing changes in road networks, population and employment. Results indicate that causality runs in both directions between population and local road networks, while no evidence of causality in either direction is found for networks and local employment. We interpret the findings as evidence of a weakening influence of road networks (and transportation more generally) on location, and suggest methods for refining the empirical approach described herein.
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    Predicting Land Use Change: How Much Does Transportation Matter?
    (Transportation Research Board, 2009) Iacono, Michael J; Levinson, David M
    In this paper, we propose to measure the extent of the influence of transportation systems on land use change. Using a set of high-resolution land use data for the Twin Cities metropolitan region, we estimate logistic regression models of land use change covering a 10-year period from 1990 to 2000. The models account for existing land use types, neighboring land uses, and transportation network variables that measure the physical proximity of highway networks, as well as the level of accessibility associated with a specific location. The models are estimated with and without the transportation variables and compared to assess the extent of their influence. We find (perhaps not surprisingly) that transportation-related variables exert some influence on changes to land use patterns, though not as much as variables representing existing and neighboring land uses.
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    Rural Highway Expansion and Economic Development: Impacts on Private Earnings and Employment
    (2012) Iacono, Michael J; Levinson, David M
    With the interstate system substantially complete, the majority of new investment in highways is likely to take the form of selective capacity expansion projects in urban areas, along with incremental expansions and upgrades to expressway or freeway standards of existing intercity highway corridors. This paper focuses specifically on the latter type of project, rural highway expansions designed to connect smaller outstate cities and towns, and examines their effects on industry-level private earnings and local employment. We examine three case study projects in rural Minnesota and use panel data on local earnings and employment to estimate the impacts of the improvements. Our results indicate that none of the projects studied generated statistically significant increases in earnings or employment, a finding we attribute to the relatively small time savings associated with the projects and the maturity of the highway network. We suggest that for rural highway expansion projects, as with other types of transportation projects, user benefits should be a primary evaluation criterion rather than employment impacts.
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    Value Capture for Transportation Finance
    (2012) Zhao, Zhirong; Iacono, Michael J; Lari, Adeel; Levinson, David M
    As vehicles become more fuel-efficient and overall levels of travel stagnate in response to increases in fuel prices, conventional sources of revenue for transportation finance such as taxes on motor fuels have been put under increasing pressure. One potential replacement as a source of revenue is a set of policies collectively referred to as value capture policies. In contrast to fuel taxes and other instruments that impose charges on users of transportation networks, value capture policies seek to generate revenue by extracting a portion of the gains in the value of land that result from improvements to transportation networks. In this paper we identify a set of eight policies that contain elements of the value capture approach. These policies include land value taxes, tax increment financing, special assessments, transportation utility fees, development impact fees, negotiated exactions, joint development, and air rights. We evaluate each of the policies according to four criteria: efficiency, equity, sustainability (in terms of revenue adequacy and stability), and feasibility. The value capture concept is placed within a more general framework of transportation finance that emphasizes the relationship between different types of charges and groups of beneficiaries from transportation investments.