A General Misspecification Test for Spatial Regression Models: Dependence, Heterogeneity, and Nonlinearity

There is an increasing awareness of the potentials of nonlinear modeling in regional science. This can be explained partly by the recognition of the limitations of conventional equilibrium models in complex situations, and also by the easy availability and accessibility of sophisticated computational techniques. Among the class of nonlinear models, dynamic variants based on, for example, chaos theory stand out as an interesting approach. However, the operational significance of such approaches is still rather limited and a rigorous statistical-econometric treatment of nonlinear dynamic modeling experiments is lacking. Against this background this paper is concerned with a methodological and empirical analysis of a general misspecification test for spatial regression models that is expected to have power against nonlinearity, spatial dependence, and heteroskedasticity. The paper seeks to break new research ground by linking the classical diagnostic tools developed in spatial econometrics to a misspecification test derived directly from chaos theory—the BDS test, developed by Brock, Dechert, and Scheinkman (1987). A spatial variant of the BDS test is introduced and applied in the context of two examples of spatial process models, one of which is concerned with the spatial distribution of regional investments in The Netherlands, the other with spatial crime patterns in Columbus, Ohio.     

Population Estimation Using Landsat Enhanced Thematic Mapper Imagery

An assessment of two groups of approaches for estimating urban population with remote-sensing information is presented in this article. These approaches, zonal and pixel-based models, are applied to Landsat Enhanced Thematic Mapper images of a portion of Columbus, Ohio , to generate population estimates. The zonal approach uses impervious surface fraction, spectral radiance, and land-use/land-cover classification to derive population estimates. The pixel-based approach uses impervious surface fraction and spectral radiance to estimate the population of residential areas. To assess robustness, these models were applied to Dayton, Ohio . A comparative study indicates that the models generated promising results in estimating regional population counts. However, zonal regression with spectral radiance produced large errors (76%) for census block groups, whereas other models gave significantly better estimation accuracy. Comparing the performance of the indicators, impervious surface fraction is competitive, and slightly but consistently better than land-use classification. In comparison with traditional zonal approaches, pixel-based models give somewhat better estimation accuracy.     

Determinants of Residential Location Choice: How Important Are Local Public Goods in Attracting Homeowners to Central City Locations?*

Abstract. A hybrid conditional logit choice model is estimated using data on the characteristics and destination of homeowners who engaged in intrametropolitan moves among 17 school districts within the Columbus, Ohio area in 1995. The model is used to test the relative influence of local fiscal and public goods versus household‐level characteristics in determining household location choices across central city and suburban school districts. Results provide evidence of both a “natural evolution” of households to the suburbs, due to job location, residential filtering, and household income and lifecycle effects, and “flight from blight,” due to lower school quality, higher crime levels, and lower average income levels in the city. In comparing the magnitudes of these variables, we find that school quality exerts the strongest influence: a 1‐percent increase in the school quality of the city district increases the probability of choosing a city residence by 3.7 percent. In contrast, the effects of household income and other individual characteristics are relatively modest. The findings provide support for a “flight from blight” suburbanization process that is dominated by differences in neighborhood quality between the city and suburbs. An implication is that investments that promote central city development and reduce suburbanization are justified on efficiency grounds if negative externalities are generated by increased concentration of poverty, crime, and low school quality.     

MODELING DYNAMIC INTERINDUSTRY REGIONAL GROWTH IN THE PRESENCE OF STRUCTURAL SHIFTS AND OUTLIERS*

ABSTRACT. Kraybill and Dorfman (1992) propose a model of intermediate and export demand which uses ordinary least-squares and linear systems techniques to produce a state-space representation of the time element of output change. Their model produces dynamic multipliers which trace the temporal path of regional growth, and has many advantages over previously employed time series methods. This study extends their methodology to accommodate structural shifts and outliers found in the least-squares relationship between industry and export output by using a recently-introduced technique–multiprocess mixture estimation. An application of the Kraybill-Dorfman method and the extensions proposed here to monthly time series data on Ohio employment is used to illustrate these issues.     

Exploratory Analysis of the Homeless Shelter System in Columbus, Ohio

Abstract: A geographic information system (GIS)-based framework is structured to analyse the spatial characteristics and patterns associated with a system of homeless shelters and services. Given the lack of detailed spatial information available to decision-makers and shelter operators, the siting of new shelters and services is often carried out with little supporting information. The shelter system in Columbus, Ohio is investigated. Personal interviews with shelter providers and local decision-makers offers a look at their collective understanding of the services needed by Columbus' homeless population and the spatial patterns and socio-economic characteristics that define the neighbourhoods in which shelters are located. The use of GIS facilitates an exploratory data analysis that allows these understandings to be examined, affording planners and decision-makers the opportunity to move beyond perceptions of the system. Findings indicate that while many perceptions are supported empirically, there are perceptions that are not substantiated. This research provides a basis for the evaluation of important social services in an urban area where perception influences planning and decision-making.     

Typologies of Advantage and Disadvantage: Socio‐economic Outcomes in Australian Metropolitan Cities

Australia's metropolitan cities have undergone significant social, economic and demographic change over the past several decades. In terms of socio‐economic advantage and disadvantage these changes, which are often associated with globalisation, wider economic and technological restructuring, the changing demographics of the population and shifts in public policy are not evenly dispersed across cities, but represent a range of often contrasting outcomes. The current paper develops a typology of socio‐economic advantage and disadvantage for locations across Australian metropolitan cities. More specifically, the paper takes a range of Australian Bureau of Statistics data and uses a model‐based approach with clustering of data represented by a parameterised Gaussian mixture model and discriminant analysis utilised to consider the differences between the clusters. These clusters form the basis of a typology representing the range of socio‐economic and demographic outcomes at the local community level.     

Estimating Rapidity of Change in Complex Urban Systems: A Multidimensional,Local‐Scale Approach

This study illustrates an exploratory approach based on a Multiway Factor Analysis (MFA) to estimate rapidity of change in complex urban systems, based on “fast” and “slow” variables. The proposed methodology was applied to 18 socioeconomic indicators of long‐term (1960–2010) transformations in 115 municipalities of Athens’ metropolitan area (Greece), including demography, land‐use/planning, and urban form and functions. Athens was regarded as a dynamic urban area with diversified structures and functions at the local scale, expanding through a self‐organized pattern rather than a centralized planning strategy. Athens’ urban system was described using nine supplementary (topographic and territorial) variables and 30 independent indicators assessing the local context in recent times. Exploratory data analysis found an increasing connectedness and redundancy among socioeconomic indicators during the phase of largest urban expansion (1960–1990). Only the rate of population growth was classified as a “fast” variable for all five decades investigated. The overall rapidity of change was higher in 1960–1970, 1980–1990, and 2000–2010, decades that coincided with specific phases of urban expansion driven by migration inflow, second‐home suburbanization, and Olympic games, respectively. Rapidity of change was high for functional indicators during all five decades studied, while demography indicators changed more rapidly in the first three decades and land‐use/planning indicators in the last two decades. Rapidity of change was highest in peri‐urban municipalities with a highly diversified economic structure dominated by industry. Our methodology provides a comprehensive overview of the transformations of a complex urban system, quantifying low‐level indicators that are rarely assessed in the mainstream literature on urban studies. These results may contribute to design policies addressing complexity and promoting resilience in expanding metropolitan areas.     

Determinants of Variation in Population–Employment Interaction Findings: A Quasi‐Experimental Meta‐Analysis. 人口‐就业相互作用的决定因素研究：一种准实验元分析法

This article reports about a metaregression analysis of empirical results generated using data for the northern Netherlands (1988–2002) in order to investigate the ambiguity in results in the population–employment interaction literature. Specifically, the analysis deals with the issue whether “jobs follow people” or “people follow jobs.” The article starts with introducing the basics of quasi‐experimental meta‐analysis and with identifying some advantages of using quasi‐experimental meta‐analysis as compared with the standard meta‐analysis approach. Two subsequent sections document the selection of the population–employment interaction model and salient characteristics of the data set as well as the setup of the primary analyses. A total of 4,050 quasi‐experimental empirical results for the jobs–people direction of causality are generated using different specifications and estimators for a spatial econometric interaction model. The subsequent metaregression analysis reveals that the empirical results are largely shaped by the spatial, temporal, and employment characteristics of the data sampling. The results also appear much more sensitive to different measurements of the model's key variables when compared with alternative specifications of the spatial weights matrix. The main determinant driving empirical results about jobs–people causality are differences in model specification and estimation, as revealed by an inherent bias in parameter estimates and misguided inferences for some of the commonly used specifications. Finally, suggestions for future research are identified.     

Classes,elites and Iranian politics: an exchange

The Politics of Iran: Groups, Classes and Modernization. By James Alban Bill. Columbus, Ohio: Charles E. Merrill Publishing Company, 1972. ix + 174 pp.     

An Analysis of Migration Streams for the Canadian Regional System, 1952–1983 1. Migration Probabilities

This is part one of a two-part series that seeks to specify the factors and processes contributing to aggregate change in the Canadian population distribution over the recent past. In part one, we use a model of migration probabilities to identify socioeconomic factors that explain the observed interregional migration flows. In part two, we use an adjustment process for our regional population system to calculate equilibrium population distributions. The estimated migration probabilities of part one are essential for this calculation, thus linking equilibria with the socioeconomic factors previously identified. Disequilibrium, defined as the difference between observed and equilibrium population distributions, is then used to infer relative growth and decline tendencies in the system. We examine and justify our results in the larger context of contemporary Canadian history.     

Their Views Matter: Frontline Regulators' Perceptions of the Regulated Community in Ohio

Frontline regulators are largely responsible for the implementation and ongoing compliance with environmental laws. Yet, as with other frontline worker populations, environmental regulators are routinely overlooked. Existing acknowledgment of these regulators typically only extends to the regulatory enforcement strategy their agency employs. Missing in these conversations is a focused study on regulators themselves and their perceptions of the regulated community that they interact with daily. Understanding these perceptions will provide insights into how regulators approach their interactions and how they ensure regulatory compliance. This research reports on one‐on‐one interviews and a statewide survey of Ohio Environmental Protection Agency frontline regulators and their perceptions of the regulated community. Findings from this survey reveal generally positive perceptions of the regulated community in Ohio and experiences with them. These findings call attention to a neglected population and emphasize the importance of regulators' perceptions in their regulatory approach.     

An Analysis of Migration Streams for the Canadian Regional System, 1952–1983: 2. Disequilibrium

This is part two of a two-part series that seeks to specify the factors and processes contributing to aggregate change in the Canadian population distribution over the recent past. In part one, we use a model of migration probabilities to identify socioeconomic factors that explain the observed interregional migration flows. In part two, we use an adjustment process for our regional population system to calculate equilibrium population distributions. The estimated migration probabilities of part one are essential for this calculation, thus linking equilibria with the socioeconomic factors previously identified. Disequilibrium, defined as the difference between observed and equilibrium population distributions, is then used to infer relative growth and decline tendencies in the system. We examine and justify our results in the larger context of contemporary Canadian history.     

INCOME INEQUALITY,ECONOMIC GROWTH,AND THE DISTRIBUTION OF INCOME GAINS: EVIDENCE FROM THE U.S. STATES*

ABSTRACT This paper first investigates a relationship between economic growth and income inequality using U.S. states data, a state cost‐of‐living deflator, and nonlinearity. It then explores the distribution of income gains among different income groups. We find that the impact of inequality on growth is nonlinear. Lowering inequality or increasing it substantially reduces growth; thus stable inequality may be good for growth. Economic growth affects incomes of the poor, the middle‐income group, and the rich similarly with the elasticity of one. Education and labor market policies become important in promoting growth and improving income gains of the poor.     

Persistence of Crime Hot Spots: An Ordered Probit Analysis

The temporal persistence of crime hot spots is recognized as a valuable indicator of consistent problem areas. The current literature has not adequately addressed the mechanisms that perpetuate or interrupt persistent crime hot spots. Investigating the persistence of violent crime hot spots in Columbus, Ohio, from 1994 to 2002, this study fills a gap in the literature by identifying neighborhood structural correlates that drive the persistence of hot spots. Specifically, this study identifies yearly crime hot spots, and estimates an ordered probit model to explore the neighborhood structural determinants. The results indicate that socio‐economic factors, identified from a synthesis of social disorganization theory and routine activity theory, significantly correlate with persistent patterns of violent crime hot spots. This gives evidence that a combination of the two ruling spatial theories of crime provides an applicable framework for understanding the temporal dimension of violent crime hot spots. By identifying the factors that contribute to the persistence of hot spots of crime, insights gained from the results can help to inform focused crime prevention efforts.     

Interannual fluctuations of the stratospheric temperature over the north polar region

The monthly means for the years 1964–1991 of 30 hPa temperatures over the North Pole and averaged over the 70–90°N region are analyzed. A multiple regression model is used to find long-term monthly trends and possible linear associations between these temperatures and the QBO, ENSO, and the 11-yr solar cycle. The model's residuals are examined for detection of other periodic interannual fluctuations in Arctic temperatures.It is found that the interannual variations of temperature at 30 hPa over the Arctic are a superposition of the oscillations due to the QBO, ENSO, the 11-yr solar cycle, and approximate 6-yr periodic fluctuations of unknown origin. The QBO, ENSO, and the solar cycle effects in the Arctic temperature explain about 35% of the total variance of the temperature monthly anomalies. In winter, the QBO, ENSO, and the 11-yr solar cycle signals in the temperature data depend on the phase of the equatorial QBO. The polar vortex seems to be warmer (colder) than normal when the West (East) phase of the equatorial QBO in a period of high solar activity. The monthly temperature trends over the Arctic show seasonal variations with positive trends in February and March. The year-round trends (sum of the monthly trends) are about −0.5 K per decade.     

SPACE–TIME MEASURES OF DEMAND FOR SERVICE: BRIDGING LOCATION MODELLING AND ACCESSIBILITY STUDIES THROUGH A TIME‐GEOGRAPHIC FRAMEWORK

Demand for service in location modelling is often evaluated based on the spatial proximity of fixed and static reference locations of demand (e.g. home) to a facility, which ignores person‐specific activity–travel patterns and the temporal changes in demand for service throughout the day. To address these limitations, this study draws upon recent developments in space–time measures of individual accessibility to explore the spatial and temporal structures of demand by considering individuals' space–time constraints and impact of existing urban structures. Based on a time‐geographic framework, eight space–time demand measures were developed and compared with three conventional location‐based demand measures for 12 hospitals through an empirical study conducted in Columbus, Ohio. The results show that geographic proximity between clients' home and facilities may not be an effective indicator for service demand, and conventional demand measures tend to underestimate potential demand for service in most situations. The study concludes that space–time demand measures that take into account people's activity‐travel patterns in space–time would lead to better estimation of demand for service in most cases.     

Classification Analysis of World Economic Regions

Economic classifications of countries are of continuing utility for comparative and analytic purposes. However, traditional methods of arriving at classifications are often ad hoc, subjective, and imprecise, not permitting the assignments to be used for closer analysis. Discriminant analysis is used in this paper to isolate a time‐specific set of economic factors delimiting economic state categories that correspond to core‐periphery states. The core‐periphery framework is shown to be a special case of a hierarchical market scheme. The purposes of this work are (1) to create a theoretically grounded, empirically derived classification over several time periods to permit dynamic comparisons to be made and provide an explanation of change in the global economy, and (2) to provide feedback information from the classification to supply the necessary rigor and quantitative insight to the world‐systems theoretical framework. Results of the analysis suggest that different economic variables provide varying levels of explanation at different times. In particular, variables representing factor endowment provide a greater measure of explanation early in the sequence (for example, 1960) while trade and investment measures are of greater importance in the latter part of the study sequence (for example, 1990). OPEC countries significantly bifurcate the world‐economy classification in 1970 and exhibit separate class characteristics. Even within the short time period, a number of countries are shown to transit among the classes. The model is also able to capture the dependence structure implicit in the world‐systems framework.     

Space-Time and Integral Measures of Individual Accessibility: A Comparative Analysis Using a Point-based Framework

Conventional integral measures of accessibility, although valuable as indicators of place accessibility, have several limitations when used to evaluate individual accessibility. Two alternatives for overcoming some of the difficulties involved are explored in this study. One is to adapt these measures for evaluating individual accessibility using a disaggregate, nonzonal approach. The other is to develop different types of measures based on an alternative conceptual framework. To pursue the former alternative, this study specifies and examines eighteen gravity-type and cumulative-opportunity accessibility measures using a point-based spatial framework. For the latter option, twelve space-time accessibility measures are developed based on the construct of a prism-constrained feasible opportunity set. This paper compares the relationships and spatial patterns of these thirty measures using network-based GIS procedures. Travel diary data collected in Columbus, Ohio, and a digital data set of 10,727 selected land parcels are used for all computation. Results of this study indicate that space-time and integral indices are distinctive types of accessibility measures which reflect different dimensions of the accessibility experience of individuals. Since space-time measures are more capable of capturing interpersonal differences, especially the effect of space-time constraints, they are more “gender sensitive” and helpful for unraveling gender/ethnic differences in accessibility. An important methodological implication is that whether accessibility is observed to be important or different between individuals depends heavily on whether the measure used is capable of revealing the kind of differences the analyst intends to observe.     

Nonlinear Static Procedure for Multi-Story Asymmetric Frame Buildings Considering Bi-Directional Excitation

The present article focuses on a nonlinear static procedure (NSP) for a multi-story asymmetric frame building with regular elevation subjected to bi-directional ground motion. In this procedure, two simplified models—an equivalent single-story model and an equivalent single-degree-of-freedom (SDOF) model—are used to predict the peak response of multi-story asymmetric buildings. The peak response is predicted through pushover analysis of an equivalent single-story model considering the effect of bi-directional excitations and an estimation of the nonlinear response of equivalent SDOF models. The predicted results are compared with the nonlinear dynamic analysis results, and satisfactory predictions can be obtained by the proposed procedure.