Elizabeth A. Mack

Geographic Exclusion

In the state of Ohio, House Bill 180, Senate Bill 175 and Senate Bill 5 collectively form Megans Law. This law requires individuals convicted of a sexually oriented offense to register with the local sheriff s office at least twenty days prior to the move-in date of the offender. Beginning July 31, 2003, Megans Law prohibited an offender of a sexually oriented offense from establishing or occupying a residence within 1,000 feet of any school-related properties. A major social concern with this law and its subsequent enforcement is the belief that the geographic constraints placed on registered sex offenders effectively eliminate nearly all residential housing options. The purpose of this paper is to explore issues of geographic exclusion by conducting a spatial analysis of registered sex offenders in Hamilton County, Ohio. Analysis using geographic information systems (GIS), proximity evaluation and basic statistical techniques enables the impacts of this law to be assessed.

The evolutionary dynamics of entrepreneurial ecosystems

Entrepreneurial ecosystems (EE) consist of interacting components, which foster new firm formation and associated regional entrepreneurial activities. Current work on EE, however, focuses on documenting the presence of system components, which means there is little understanding of interdependencies between EE components and their evolutionary dynamics. To address these issues, the objective of the present study is to develop an evolutionary framework of EE development that integrates important components from prior work and describes how critical elements of an entrepreneurial system interact and evolve over time. The value of this framework in understanding the evolutionary dynamics of EE will be demonstrated by profiling the EE of Phoenix, Arizona. The evolutionary perspective developed is valuable because it provides a sense of how history, culture and the institutional setting impact EE. It also provides stakeholders with action points to help maintain or propel an EE to the next level. This is a distinct improvement over static approaches that provide a list of EE ingredients with no sense of their relative importance over time. The proposed framework may also be used in a comparative context to compare and contrast the evolutionary trajectory of EE to better understand why particular places remain trapped in a specific phase of growth or continue to evolve over time.

Indices of Industrial Diversity and Regional Economic Composition

Attempts to differentiate regions from one another, whether in social, demographic, or economic terms, have led to the development of numerous indices to summarize the economic composition of regions. This study revisits classic indices of industrial diversity to evaluate their applicability for benchmarking local and regional economies. Specifically, we explore a multivariate extension of these diversity indices for measuring concentration in an effort to evaluate their ability to accurately depict spatial relationships of county level resources for the contiguous U.S. The relative abilities of the classic indices are compared to a developed measure of resource concentration, the County Similarity Index (CS-Index), which represents a computationally simple and flexible alternative to these indices. Results suggest the CS-Index produces superior results to the indices evaluated, particularly with regard to the spatial relationships of county resource concentrations, which are quantified using global and local indicators of spatial association.

Productivity and Broadband The Human Factor

While the productivity paradox has been largely resolved, debate persists about the impacts of information and communications technologies on productivity, particularly as regards broadband Internet connections. To date, the bulk of the literature has not addressed the impacts of broadband provision on regional variations in productivity. This study develops a series of spatial econometric models that examine the link between broadband provision and productivity for US counties. The models developed not only consider the link between productivity and broadband provision, but they also evaluate the variability in broadband impacts that are related to the quality of human capital stock within counties. The results of the models are evidence of skill-based technological change and suggest that in general, broadband has a positive impact on productivity only in locales with high levels of human capital and/or highly skilled occupations.

A hybrid geocoding methodology for spatio-temporal data

As tools for collecting data continue to evolve and improve, the information available for research is expanding rapidly. Increasingly, this information is of a spatio-temporal nature, which enables tracking of phenomena through both space and time. Despite the increasing availability of spatio-temporal data, however, the methods for processing and analyzing these data are lacking. Existing geocoding techniques are no exception. Geocoding enables the geographic location of people and events to be known and tracked. However, geocoded information is highly generalized and subject to various interpolation errors. In addition, geocoding for spatio-temporal data is especially challenging because of the inherent dynamism of associated data. This article presents a methodology for geocoding spatio-temporal data in ArcGIS that utilizes several additional supporting procedures to enhance spatial accuracy, including the use of supplementary land use information, aerial photographs and local knowledge. This hybrid methodology allows for the tracking of phenomenon through space and over time. It is also able to account for reporting inconsistencies, which is a common feature of spatio-temporal data. The utility of this methodology is demonstrated using an application to spatio-temporal address records for a highly mobile group of convicted felons in Hamilton County, Ohio.

Forecasting broadband provision

The provision of broadband telecommunication services in the United States is spatially heterogeneous. Previous studies find that urban locales typically have a larger selection of access platforms and providers when compared to rural or remote areas. Therefore, the ability to forecast broadband provision is important to understanding regional trends in telecommunications competition and availability. This paper provides a comparative analysis of cross-sectional and spatial econometric forecasts of broadband provision, with results suggesting that the integration of spatially referenced demand-side variables significantly improve the accuracy of short and mid-range forecasts.

Businesses and the need for speed: The impact of broadband speed on business presence

Abstract Despite the widespread attention devoted to broadband and its anticipated impacts, surprisingly little is known regarding the linkages between broadband provision and establishment location. This is particularly true with respect to broadband speed. Given the understudied nature of this relationship, this study estimates econometric models to examine the linkages between broadband speed and firms using Ohio as a case study. Models results indicate broadband speed is most important to agricultural and rural firms. These findings provide case study support for policy and funding initiatives designed to improve the quality of broadband infrastructure in rural locations.

Sex offenders and residential location: A predictive-analytical framework

Despite the growing body of research examining the collateral consequences of legislation governing sex offenders, a complete understanding of their residential choices post release remains elusive. This paper develops a predictive–analytical framework that helps determine which demographic and socioeconomic factors best forecast the residential choices of convicted sex offenders. Specifically, a derived index of social disorganization (ISDOR) is implemented in both statistical and nonlinear data mining approaches to predict the presence of sex offenders in a community. The results of the analysis are encouraging, predicting nearly 75% of registered offender locations correctly. The utility of this framework as a tool for public policy and law enforcement is discussed.

Population shift bias in tests of space–time interaction

Abstract Common to all tests of space–time interaction is the assumption that the population underlying the events of interest exhibits a trajectory of growth that is consistent through time and across space. In practice, however, this assumption is often untenable and, when violated, can introduce population shift bias into the results of these tests. While this problem is widely recognized, more work remains to compare its effect across tests and to determine the extent to which it is a problem for study short periods. This paper quantifies and compares the population shift bias present in the results of the Knox, Mantel, and Jacquez tests of space–time interaction. A simulation study is carried out which quantifies the bias present in each test across a variety of population movement scenarios. Results show a positive relationship between population shift bias and the heterogeneity in population growth across all the tests. They also demonstrate variability in the size of the bias across the three tests for space–time interaction considered. Finally, the results illustrate that population shift bias can be a serious problem for short study periods. Collectively, these findings suggest that an unbiased approach to assessing the significance of space–time interaction test results is needed whenever spatially heterogeneous population change is identified within a study area.

Enhancing the Jacquez k nearest neighbor test for space–time interaction

The Jacquez k nearest neighbor test, originally developed to improve upon shortcomings of existing tests for space-time interaction, has been shown to be a robust and powerful method of detecting interaction. Despite its flexibility and power, however, the test has three main shortcomings: (i) it discards important information regarding the spatial and temporal scales at which the detected interaction takes place; (ii) the results of the test have not been visualized; and (iii) recent research demonstrates the test to be susceptible to population shift bias. This study presents enhancements to the Jacquez k nearest neighbors test with the goal of addressing each of these three shortcomings and of improving the utility of the test. Data on Burkitts lymphoma cases in Uganda between 1961 and 1975 are used to illustrate the modifications and enhanced visual output of the test. Output from the enhanced test is compared with that provided by alternative tests of space-time interaction. Results show the enhancements presented in this study transform the Jacquez test into a complete, descriptive, and informative metric that can be used as a stand-alone measure of global space-time interaction.