HAPPY IN THE HOOD? THE IMPACT OF RESIDENTIAL SEGREGATION ON SELF‐REPORTED HAPPINESS

Previous research consistently finds that racially based residential segregation is associated with poor economic, health, and social outcomes. The purpose of this paper is to explore the relationship between residential segregation and self‐reported happiness. Using panel data from the National Survey of Families and Households (NSFH), we begin by estimating ordinary least squares (OLS) regressions of happiness on a measure of MSA‐level segregation, controlling for a rich set of individual, neighborhood, regional, and state characteristics. The OLS results suggest that increased segregation is associated with a reduction in happiness among blacks. To deal more appropriately with the potential endogeneity of location choice, we extend the methodology to fully exploit the panel structure of the NSFH and incorporate individual fixed effects into the happiness equation. Contrary to the OLS results, our fixed effects estimates imply that blacks are happier in more segregated metropolitan areas. The paper discusses the implications of these results within the context of current integration policies.     

AGGLOMERATION ECONOMIES: MICRODATA PANEL ESTIMATES FROM CANADIAN MANUFACTURING*

ABSTRACT This paper identifies the main sources of urban increasing returns, after Marshall. The geographical distance across which externalities flow is also examined. We bring to bear on these questions plant‐level data organized in the form of a panel across the years 1989 and 1999. Plant‐level production functions are estimated across the Canadian manufacturing sector as a whole and for five broad industry groups, each characterized by the nature of its output. The panel data overcome selection bias resulting from unobserved plant‐level heterogeneity that is constant over time. A related set of estimates using instrumental variables allay persistent concerns with endogeneity. Results provide strong support for Marshall's claims about the importance of buyer‐supplier networks, labor market matching and spillovers. We show that spillovers enhance plant productivity within industries rather than between them and that these spillovers are highly localized.     

ANALYZING THE IMPACT OF PUBLIC CAPITAL STOCK USING THE NEG WAGE EQUATION: A SPATIAL PANEL DATA APPROACH

ABSTRACT This paper examines the relationship between the level of public infrastructure and the level of productivity using panel data for the Spanish provinces over the period 1985–2004, a period that is particularly relevant due to the substantial changes occurring in the Spanish economy at that time. The underlying model used for the data analysis is based on the wage equation, which is one of a handful of simultaneous equations which when satisfied correspond to the short‐run equilibrium of New Economic Geography (NEG) theory. This is estimated using various spatial panel models with either fixed or random effects to allow for individual heterogeneity. Using these models, we find consistent evidence that productivity depends directly on the public capital stock endowment of each province, but also there is evidence of negative spillover effects from changes in capital stock in neighboring provinces.     

Spatial Autoregressive Models for Geographically Hierarchical Data Structures

This article discusses how standard spatial autoregressive models and their estimation can be extended to accommodate geographically hierarchical data structures. Whereas standard spatial econometric models normally operate at a single geographical scale, many geographical data sets are hierarchical in nature—for example, information about houses nested into data about the census tracts in which those houses are found. Here we outline four model specifications by combining different formulations of the spatial weight matrix W and of ways of modeling regional effects. These are (1) groupwise W and fixed regional effects; (2) groupwise W and random regional effects; (3) proximity‐based W and fixed regional effects; and (4) proximity‐based W and random regional effects. We discuss each of these model specifications and their associated estimation methods, giving particular attention to the fourth. We describe this as a hierarchical spatial autoregressive model. We view it as having the most potential to extend spatial econometrics to accommodate geographically hierarchical data structures and as offering the greatest coming together of spatial econometric and multilevel modeling approaches. Subsequently, we provide Bayesian Markov Chain Monte Carlo algorithms for implementing the model. We demonstrate its application using a two‐level land price data set where land parcels nest into districts in Beijing, China, finding significant spatial dependence at both the land parcel level and the district level.     

Growth and Convergence in a Multiregional Model with Space–Time Dynamics. 多区域时空动态模型的增长与收敛

The goal of this article is to test four distinct hypotheses about whether the relative location of an economy affects economic growth and economic well‐being using an extended Solow–Swan neoclassical growth model that incorporates both space and time dynamics. We show that the econometric specification takes the form of an unconstrained spatial Durbin model, and we investigate whether the results depend on some methodological issues, such as the choice of the time span and the inclusion of fixed effects. To estimate the fixed effects spatial Solow–Swan model, we adjust the Arrelano and Bond (1991) generalized method‐of‐moments (GMM) estimator to deal with endogeneity not only arising from the initial income level, as in the basic model, but also from the initial income levels and economic growth rates observed in neighboring economies.     

PERSISTENCE OF REGIONAL UNEMPLOYMENT: APPLICATION OF A SPATIAL FILTERING APPROACH TO LOCAL LABOR MARKETS IN GERMANY*

ABSTRACT The geographical distribution and persistence of regional/local unemployment rates in heterogeneous economies (such as Germany) have been, in recent years, the subject of various theoretical and empirical studies. Several researchers have shown an interest in analyzing the dynamic adjustment processes of unemployment and the average degree of dependence of the current unemployment rates or gross domestic product from the ones observed in the past. In this paper, we present a new econometric approach to the study of regional unemployment persistence, in order to account for spatial heterogeneity and/or spatial autocorrelation in both the levels and the dynamics of unemployment. First, we propose an econometric procedure suggesting the use of spatial filtering techniques as a substitute for fixed effects in a panel estimation framework. The spatial filter computed here is a proxy for spatially distributed region‐specific information (e.g., the endowment of natural resources, or the size of the “home market”) that is usually incorporated in the fixed effects coefficients. The advantages of our proposed procedure are that the spatial filter, by incorporating region‐specific information that generates spatial autocorrelation, frees up degrees of freedom, simultaneously corrects for time‐stable spatial autocorrelation in the residuals, and provides insights about the spatial patterns in regional adjustment processes. We present several experiments in order to investigate the spatial pattern of the heterogeneous autoregressive coefficients estimated for unemployment data for German NUTS‐3 regions. We find widely heterogeneous but generally high persistence in regional unemployment rates.     

THE FUTURE TRAJECTORY OF U.S. CO2 EMISSIONS: THE ROLE OF STATE VS. AGGREGATE INFORMATION*

ABSTRACT This paper provides comparisons of a variety of time‐series methods for short‐run forecasts of the main greenhouse gas, carbon dioxide, for the United States, using a recently released state‐level data set from 1960–2001. We test the out‐of‐sample performance of univariate and multivariate forecasting models by aggregating state‐level forecasts versus forecasting the aggregate directly. We find evidence that forecasting the disaggregate series and accounting for spatial effects drastically improves forecasting performance under root mean squared forecast error loss. Based on the in‐sample observations we attempt to explain the emergence of voluntary efforts by states to reduce greenhouse gas emissions. We find evidence that states with decreasing per capita emissions and a “greener” median voter are more likely to push toward voluntary cutbacks in emissions.     

Micro‐Level Interpretation of Exponential Random Graph Models with Application to Estuary Networks

The exponential random graph model (ERGM) is an increasingly popular method for the statistical analysis of networks that can be used to flexibly analyze the processes by which policy actors organize into a network. Often times, interpretation of ERGM results is conducted at the network level, such that effects are related to overall frequencies of network structures (e.g., the number of closed triangles in a network). This limits the utility of the ERGM because there is often interest, particularly in political and policy sciences, in network dynamics at the actor or relationship levels. Micro‐level interpretation of the ERGM has been employed in varied applications in sociology and statistics. We present a comprehensive framework for interpretation of the ERGM at all levels of analysis, which casts network formation as block‐wise updating of a network. These blocks can represent, for example, each potential link, each dyad, the out‐ or in‐going ties of each actor, or the entire network. We contrast this interpretive framework with the stochastic actor‐based model (SABM) of network dynamics. We present the theoretical differences between the ERGM and the SABM and introduce an approach to comparing the models when theory is not sufficiently strong to make the selection a priori. The alternative models we discuss and the interpretation methods we propose are illustrated on previously published data on estuary policy and governance networks.     

INTEGRATION OF IMMIGRANTS,BRIDGING SOCIAL CAPITAL,ETHNICITY, AND LOCALITY

This paper analyses a uniquely detailed data set of social integration characteristics of immigrants belonging to four non‐native ethnic groups (i.e., Turks, Moroccans, Surinamese, and Antilleans) living in Dutch neighborhoods. It is well known that an individual's level of social integration is related to the ethnic composition and economic development of an immigrant's residential locality, as well as the generation of the immigrant. Yet, what is not known is whether the social and economic characteristics of adjacent or neighboring localities also influence an individual's level of social integration. Using a multilevel hierarchical analysis with spatial interaction effects, we examine the extent to which four social integration aspects of the bridging social capital of these immigrant groups are related to their ethnicity, their generation, their immediate locality, and the effects of the neighboring localities. Our findings regarding the effects of the ethnic concentration and economic development of the immediate locality along with the immigrant's generation broadly concur with existing studies. At the same time, however, we also find that the features of neighboring localities exert an additional influence on an individual's social integration over and above those related to the immigrant's generation and immediate locality. These additional spatial spillover effects are broadly in line with those associated with the immediate locality, but they are also sensitive to particular proxies for social integration which are employed. These spatial spillover effects on social capital and social integration have not been observed before.     

A SPATIAL AND TEMPORAL AUTOREGRESSIVE LOCAL ESTIMATION FOR THE PARIS HOUSING MARKET

ABSTRACT This original study examines the potential of a spatiotemporal autoregressive Local (LSTAR) approach in modeling transaction prices for the housing market in inner Paris. We use a data set from the Paris Region notary office (Chambre des notaires d’Île‐de‐France) which consists of approximately 250,000 transactions units between the first quarter of 1990 and the end of 2005. We use the exact X–Y coordinates and transaction date to spatially and temporally sort each transaction. We first choose to use the STAR approach proposed by Pace et al., 1998 . This method incorporates a spatiotemporal filtering process into the conventional hedonic function and attempts to correct for spatial and temporal correlative effects. We find significant estimates of spatial dependence effects. Moreover, using an original methodology, we find evidence of a strong presence of both spatial and temporal heterogeneity in the model. It suggests that spatial and temporal drifts in households socio‐economic profiles and local housing market structure effects are certainly major determinants of the price level for the Paris Housing Market.     

The Impact of Demographic Representation on Absences and Suspensions

Representative bureaucracy theory is central to public administration scholarship due to the likely relationship between the demographic composition of the public workforce and both the actual and perceived performance of public organizations. Primary school classrooms provide an ideal context in which to test the predictions of representative bureaucracy theory at the micro (student) level. Specifically, as parents have at least some agency over primary school students’ daily attendance, absences partially reflect parental assessments of their child's school, classroom, and teacher. Ensuring students attend school each day represents an effort at coproduction on the part of parents. The representativeness of the teacher workforce, and specifically that of the student's classroom teacher, is therefore likely to influence student absenteeism. Similarly, student suspensions reflect students’ relationships with their teacher, students’ comfort level in the classroom, and teachers’ discretion in the referral of misbehavior. These academically and socially important outcomes provide convenient, objective measures of behaviors that are likely influenced by street‐level representation. Using longitudinal student‐level administrative data from North Carolina, we use a two‐way (student and classroom) fixed effects strategy to identify the impact of student–teacher demographic mismatch on primary school students’ absences and suspensions. We find that representation among street‐level bureaucrats significantly decreases both absenteeism and suspensions and that these effects can be given a causal interpretation. This pushes literature forward by establishing the importance of demographic representation in shaping productive relationships between individual bureaucrats and clients.     

Laboratories of (In)equality? Redistributive Policy and Income Inequality in the American States

Prior literature has emphasized demographic, economic, and political explanations for increasing income inequality in the United States, with little attention paid to the role of state‐level policy. This is despite great variation across states in both the level of inequality and the rate at which it is rising. This paper asks whether differences in state policy choices can help explain this variation; specifically, we examined a range of state redistributive policies enacted between 1980 and 2005 and identified four common approaches likely to impact inequality: taxes on the wealthy, taxes on the poor, spending on the poor, and labor market policies. We used pooled cross‐sectional time‐series data and a fixed‐effects model to assess the relationship between states’ use of each policy approach and two measures of market income inequality: the Gini coefficient and the income share of the top 1 percent. We find policies played a significant role in shaping income inequality in the states. For three of these four policy approaches, we found less inequality following expansions of state redistributive policy. Yet, for another, we identified the opposite pattern. These findings highlight the importance of state policy choices in shaping market inequality, and have implications for designing state policies to reduce income inequality since the success of these efforts depends on the policy approach used to redistribute income and wealth.     

Latent trajectory models for space‐time analysis: An application in deciphering spatial panel data

This article introduces latent trajectory models (LTMs), an approach often employed in social sciences to handle longitudinal data, to the arena of GIScience, particularly space‐time analysis. Using the space‐time data collected at county level for the whole United States through webpage search on the keyword “climate change,” we show that LTMs, when combined with eigenvector filtering of spatial dependence in data, are very useful in unveiling temporal trends hidden in such data: the webpage‐data derived popularity measure for climate change has been increasing from December 2011 to March 2013, but the increase rate has been slowing down. In addition, LTMs help reveal potential mechanisms behind observed space‐time trajectories through linking the webpage‐data derived popularity measure about climate change to a set of socio‐demographic covariates. Our analysis shows that controlling for population density, greater drought exposure, higher percent of people who are 16 years old or above, and higher household income are positively predictive of the trajectory slopes. Higher percentages of Republicans and number of hot days in summer are negatively related to the trajectory slopes. Implications of these results are examined, concluding with consideration of the potential utility of LTMs in space‐time analysis and more generally in GIScience.     

On the Finite Optimality Set of the Vector Assignment p‐Median Problem

The vector assignment p‐median problem (VAPMP) is one of the first discrete location problems to account for the service of a demand by multiple facilities, and has been used to model a variety of location problems in addressing issues such as system vulnerability and reliability. Specifically, it involves the location of a fixed number of facilities when the assumption is that each demand point is served a certain fraction of the time by its closest facility, a certain fraction of the time by its second closest facility, and so on. The assignment vector represents the fraction of the time a facility of a given closeness order serves a specific demand point. Weaver and Church showed that when the fractions of assignment to closer facilities are greater than more distant facilities, an optimal all‐node solution always exists. However, the general form of the VAPMP does not have this property. Hooker and Garfinkel provided a counterexample of this property for the nonmonotonic VAPMP. However, they do not conjecture as to what a finite set may be in general. The question of whether there exists a finite set of locations that contains an optimal solution has remained open to conjecture. In this article, we prove that a finite optimality set for the VAPMP consisting of “equidistant points” does exist. We also show a stronger result when the underlying network is a tree graph.     

IS PRODUCTIVITY HIGHER IN BRITISH CITIES?*

ABSTRACT This paper examines the determinants of total factor productivity (TFP) using a GB plant‐level data set. The main findings relate to whether spatial spillovers and “place” effects are important: plants located in cities generally perform better than plants in the same region outside of these cities; but with the exception of Bristol, no city has significantly higher TFP levels than the South East. This suggests that spatial externalities associated with city location are not as important as the benefits of being situated in the South East region.     

Lithology and fluid prediction from amplitude versus offset (AVO) seismic data

Seismic reflection data as used in the oil industry is acquired and processed as multitrace data with source‐receiver offsets from a few hundred metres (short offset) to several kilometres (long offset). This set of data is referred to as ‘pre‐stack’. The traces are processed by velocity analysis, migration and stacking to yield a data volume of traces with ‘zero‐offset’. The signal‐to‐noise enhancement resulting from this approach is very significant. However, reflection amplitude changes in the pre‐stack domain may also be analysed to yield enhanced rock physics parameter estimates. Pre‐stack seismic data is widely used to predict lithology, reservoir quality and fluid distribution in exploration and production studies. Amplitude versus offset (AVO) data, especially anomalous signals, have been used for decades as indicators of hydrocarbon saturation and favourable reservoir development. Recently, enhanced quantification of these types of measurement, using seismic inversion techniques in the pre‐stack domain, have significantly enhanced the utility of such measurements. Using these techniques, for example, probability of the occurrence of hydrocarbons throughout the seismic data can be estimated, and as a consequence the many pre‐stack volumes acquired in a three‐dimensional (3D) can be survey, reduced to a single, more interpretable volume. The possibilities of 4D time lapse observation extend the measurements to changes in fluid content (and pressure) with time, and with obvious benefits in establishing the accuracy of dynamic reservoir models and improvements in field development planning. As an illustration, recent results from the Nelson Field (UK North Sea), are presented where we show the method by which probability volumes for oil sands may be calculated. The oil–sand probability volumes for three 3D seismic datasets acquired in 1990, 1997 and 2000 are compared and production effects in these data are demonstrated.     

Isothermal Time‐Series Determination of the Rate of Diffusion of Water in Pachuca Obsidian*

Friedman and Smith's (1960) article introducing an exciting, potentially precise and inexpensive method of dating obsidian artefacts has thus far failed to reach its potential. Numerous efforts to refine, improve and even redevelop the method since that time have similarly failed to achieve the original promise. Only within the last eight years have significant improvements been made, due to both improved analytical techniques and a better understanding of the hydration process. However, most of our mechanistic understanding of the interaction of water with rhyolitic glass is based on experiments performed on melts and glasses at temperatures above their glass transitions, conditions inappropriate for investigation of near‐surface environmental conditions. Unfortunately, studies detailing the temporal evolution of the diffusion profile at low temperatures are rare, and few useful data are available on the low‐temperature diffusive hydration of silicate glasses. This paper presents data on the experimental hydration of obsidian from the Pachuca source (a.k.a. Sierra de las Navajas, Basin of Mexico) at 75°C for times ranging from 3 to 562 days, and compares these results with data for samples obtained from a stratigraphic excavation of the Chalco site in the Basin of Mexico. Samples have been analysed using secondary ion mass spectrometry (SIMS) to provide concentration/depth data. While 75°C is still significantly above the temperatures at which archaeological obsidians hydrate, it is well below the glass transition temperature (approx. 400°C) and thus processes are likely to be similar to those that occur in nature, but fast enough to be observed over a laboratory timescale. The results demonstrate that a simple square‐root‐of‐time model of the evolution of the diffusion profile is not adequate to describe the diffusion process, as measured diffusion profiles exhibit the effects of concentration‐ and time‐dependent, non‐Fickian diffusion. With progressive hydration, characteristic diffusion coefficients first decrease, then increase with time. Surface concentration increases with time, but an intermediate plateau is observed in its time evolution that is consistent with results obtained from the suite of Chalco samples. Both of these effects have been observed during diffusion in glassy polymer systems and are associated with the build‐up and relaxation of self‐stress caused by the influx of diffusing material.     

GIS Methods in Time-Geographic Research: Geocomputation and Geovisualization of Human Activity Patterns

Over the past 40 years or so, human activities and movements in space‐time have attracted considerable research interest in geography. One of the earliest analytical perspectives for the analysis of human activity patterns and movements in space‐time is time geography. Despite the usefulness of time geography in many areas of geographical research, there are very few studies that actually implemented its constructs as analytical methods up to the mid‐1990s. With increasing availability of geo‐referenced individual‐level data and improvement in the geo‐computational capabilities of Geographical Information Systems (GIS), it is now more feasible than ever before to operationalize and implement time‐geographic constructs. This paper discusses recent applications of GIS‐based geo‐computation and three‐dimensional (3‐D) geo‐visualization methods in time‐geographic research. The usefulness of these methods is illustrated through examples drawn from the author's recent studies. The paper attempts to show that GIS provides an effective environment for implementing time‐geographic constructs and for the future development of operational methods in time‐geographic research.     

Accessibility Measurement in Transportation Networks and Application to the Seoul Bus System

This study presents an algorithm for measuring the time‐distance accessibility based on the flow data of actual transportation networks and examines resulting accessibility distributions. Specifically, we construct an extended graph of the transportation network to take into account not only the average speed and transfer time extracted from the data set but also various possible trajectories taken via transfers. Employing the modified Floyd algorithm which finds the shortest time distance, we compute the time‐distance accessibility of every bus stop in the Seoul bus system, which yields distinctive skew distributions. We then introduce a time‐distance cutoff to focus on effective connections and probe the emergent spatial distributions as the cutoff is varied. Revealed are the characteristic scales as well as spatial structures of the system. It is suggested that the time‐distance accessibility can serve as a significant measure to describe and predict the urban land use pattern.     

Positive Returns and Equilibrium: Simultaneous Feedback Between Public Opinion and Social Policy

This paper pushes forward political research from across disciplines seeking to understand the linkages between public opinion and social policy in democracies. It considers the thermostatic and the increasing returns perspectives as pointing toward a potentially stable set of effects running between opinion and policy. Both theoretical perspectives argue that opinion and policy are reciprocally causal, feeding back on one another. This is a general argument found in opinion‐policy literatures. However, much empirical research claims to model “feedback” effects when actually using separate unidirectional models of opinion and policy. Only a small body of research addresses opinion‐policy endogeneity directly. In this paper I consider an opinion‐policy system with simultaneous feedback and without lags. I argue that there is a theoretical equilibrium in the relationship of opinion and policy underlying the otherwise cyclical processes that link them. Given that available cross‐national data are cross‐sectional and provide limited degrees of freedom, an ideal theoretical model must be somewhat constrained in order to arrive at empirically meaningful results. In this challenging and exploratory undertaking I hope to open up the possibility of a general system of effects between public opinion and social policy and how to model them in future research. I focus on social welfare policy as it is highly salient to public interests and a costly area of government budgets, making it an area of contentious policymaking. Social policy is also a major part of the thermostatic model of opinion and policy, which was recently extended to the cross‐national comparative context (Wlezien & Soroka, 2012) providing a critical predecessor to this paper because identification of equilibrium between public opinion and social policy in any given society is greatly enhanced through comparison with other societies. This counterfactual approach helps to identify opinion‐policy patterns that may not change much within societies, but can be seen as taking on discrete trajectories between societies.