968 resultados para INDIVIDUAL SPATIAL CHOICE
Resumo:
This paper replicates the analysis of Scottish HEIs in Hermannsson et al (2010a) to identify the impact of London-based HEIs on the English economy in order to provide a self-contained analysis that is readily accessible by those whose primary concern is with the regional impacts of London HEIs. When we treat each of the 38 London-based Higher Education Institutions (HEIs) that existed in England in 2006 as separate sectors in conventional input-output analysis, their expenditure impacts per unit of final demand appear rather homogenous (though less so than HEIs in Wales and Scotland), with the apparent heterogeneity of their overall impacts being primarily driven by scale. However, a disaggregation of their income by source reveals considerable variation in their dependence upon general public funding and their ability to draw in income/funding from external sources. Acknowledging the possible alternative uses of the public funding and deriving balanced expenditure multipliers reveals large differences in the net-expenditure impact of London HEIs upon the English economy, with the source of variation being the origin of income. Applying a novel treatment of student expenditure impacts, identifying the amount of exogenous spending per student, modifies the heterogeneity of the overall expenditure impacts. On balance this suggests that the impacts of impending budget cut-backs will be quite different by institution depending on their sensitivity to public funding. However, predicting the outcome of budget cutbacks at the margin is problematic for reasons that we identify.
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Spatial econometrics has been criticized by some economists because some model specifications have been driven by data-analytic considerations rather than having a firm foundation in economic theory. In particular this applies to the so-called W matrix, which is integral to the structure of endogenous and exogenous spatial lags, and to spatial error processes, and which are almost the sine qua non of spatial econometrics. Moreover it has been suggested that the significance of a spatially lagged dependent variable involving W may be misleading, since it may be simply picking up the effects of omitted spatially dependent variables, incorrectly suggesting the existence of a spillover mechanism. In this paper we review the theoretical and empirical rationale for network dependence and spatial externalities as embodied in spatially lagged variables, arguing that failing to acknowledge their presence at least leads to biased inference, can be a cause of inconsistent estimation, and leads to an incorrect understanding of true causal processes.
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In this paper we examine whether variations in the level of public capital across Spain‟s Provinces affected productivity levels over the period 1996-2005. The analysis is motivated by contemporary urban economics theory, involving a production function for the competitive sector of the economy („industry‟) which includes the level of composite services derived from „service‟ firms under monopolistic competition. The outcome is potentially increasing returns to scale resulting from pecuniary externalities deriving from internal increasing returns in the monopolistic competition sector. We extend the production function by also making (log) labour efficiency a function of (log) total public capital stock and (log) human capital stock, leading to a simple and empirically tractable reduced form linking productivity level to density of employment, human capital and public capital stock. The model is further extended to include technological externalities or spillovers across provinces. Using panel data methodology, we find significant elasticities for total capital stock and for human capital stock, and a significant impact for employment density. The finding that the effect of public capital is significantly different from zero, indicating that it has a direct effect even after controlling for employment density, is contrary to some of the earlier research findings which leave the question of the impact of public capital unresolved.
Resumo:
This paper replicates the analysis of Scottish HEIs in Hermannsson et al (2010a) for the case of Northern Ireland in order to provide a self-contained analysis that is readily accessible by those whose primary concern is with the regional impacts of Northern-Irish HEIs. When we treat each of the four Higher Education Institutions (HEIs) that existed in Northern Ireland in 2006 as separate sectors in conventional input-output analysis, their expenditure impacts per unit of final demand appear rather homogenous, with the apparent heterogeneity of their overall impacts being primarily driven by scale. However, a disaggregation of their income by source reveals considerable variation in their dependence upon funding from the devolved Assembly and their ability to draw in income/funding from external sources. Acknowledging the binding budget constraint of the Northern Ireland Assembly and deriving balanced expenditure multipliers reveals large differences in the netexpenditure impact of HEIs upon the Northern Irish economy, with the source of variation being the origin of income. Applying a novel treatment of student expenditure impacts, identifying the amount of exogenous spending per student, modifies the heterogeneity of the overall expenditure impacts. On balance this suggests that the impacts of impending budget cut-backs will be quite different by institution depending on their sensitivity to public funding. However, predicting the outcome of budget cutbacks at the margin is problematic for reasons that we identify.
Resumo:
In multilevel modelling, interest in modeling the nested structure of hierarchical data has been accompanied by increasing attention to different forms of spatial interactions across different levels of the hierarchy. Neglecting such interactions is likely to create problems of inference, which typically assumes independence. In this paper we review approaches to multilevel modelling with spatial effects, and attempt to connect the two literatures, discussing the advantages and limitations of various approaches.
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Spatial heterogeneity, spatial dependence and spatial scale constitute key features of spatial analysis of housing markets. However, the common practice of modelling spatial dependence as being generated by spatial interactions through a known spatial weights matrix is often not satisfactory. While existing estimators of spatial weights matrices are based on repeat sales or panel data, this paper takes this approach to a cross-section setting. Specifically, based on an a priori definition of housing submarkets and the assumption of a multifactor model, we develop maximum likelihood methodology to estimate hedonic models that facilitate understanding of both spatial heterogeneity and spatial interactions. The methodology, based on statistical orthogonal factor analysis, is applied to the urban housing market of Aveiro, Portugal at two different spatial scales.
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In recent years, multi-atlas fusion methods have gainedsignificant attention in medical image segmentation. Inthis paper, we propose a general Markov Random Field(MRF) based framework that can perform edge-preservingsmoothing of the labels at the time of fusing the labelsitself. More specifically, we formulate the label fusionproblem with MRF-based neighborhood priors, as an energyminimization problem containing a unary data term and apairwise smoothness term. We present how the existingfusion methods like majority voting, global weightedvoting and local weighted voting methods can be reframedto profit from the proposed framework, for generatingmore accurate segmentations as well as more contiguoussegmentations by getting rid of holes and islands. Theproposed framework is evaluated for segmenting lymphnodes in 3D head and neck CT images. A comparison ofvarious fusion algorithms is also presented.
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We reformulate neoclassical consumer choice by focusing on lambda, the marginal utility of money. As the opportunity cost of current expenditure, lambda is approximated by the slope of the indirect utility function of the continuation. We argue that lambda can largely supplant the role of an arbitrary budget constraint in partial equilibrium analysis. The result is a better grounded, more flexible and more intuitive approach to consumer choice.
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In this paper we challenge the conventional view that strikes are caused by asymmetric information regarding rm profitability such that union members are uninformed. Instead, we build an expressive model of strikes where the perception of unfairness provides the expressive benefi t of voting for a strike. The model predicts that larger union size increases both wage offers and the incidence of strikes. Furthermore, while asymmetric information is still important in causing strikes, we find that it is the employer who is not fully informed about the level of emotionality within the union, thereby contributing to strike incidence. An empirical test using UK data provides support for the predictions. In particular, union size has a positive effect on the incidence of strikes and other industrial actions even when asymmetric information regarding profitability is controlled for.
Resumo:
There is a long and detailed history of attempts to understand what causes crime. One of the most prominent strands of this literature has sought to better understand the relationship between economic conditions and crime. Following Becker (1968), the economic argument is that in an attempt to maintain consumption in the face of unemployment, people may resort to sources of illicit income. In a similar manner, we might expect ex–ante, that increases in the level of personal indebtedness would be likely to provide similar incentives to engage in criminality. In this paper we seek to understand the spatial pattern of property and theft crimes using a range of socioeconomic variables, including data on the level of personal indebtedness.
Resumo:
In this paper we challenge the conventional view that strikes are caused by asymmetric information regarding firm protability such that union members are uninformed. Instead, we build an expressive model of strikes where the perception of unfairness provides the expressive benefit of voting for a strike. The model predicts that larger union size increases both wage offers and the incidence of strikes. Furthermore, while asymmetric information is still important in causing strikes, we find that it is the employer who is not fully informed about the level of emotionality within the union, thereby contributing to strike incidence. An empirical test using UK data provides support for the predictions. In particular, union size has a positive effect on the incidence of strikes and other industrial actions even when asymmetric information regarding protability is controlled for.
Resumo:
There is a long and detailed history of attempts to understand what causes crime. One of the most prominent strands of this literature has sought to better understand the relationship between economic conditions and crime. Following Becker (1968), the economic argument is that in an attempt to maintain consumption in the face of unemployment, people may resort to sources of illicit income. In a similar manner, we might expect ex–ante, that increases in the level of personal indebtedness would be likely to provide similar incentives to engage in criminality. In this paper we seek to understand the spatial pattern of property and theft crimes using a range of socioeconomic variables, including data on the level of personal indebtedness.
Resumo:
We model a boundedly rational agent who suffers from limited attention. The agent considers each feasible alternative with a given (unobservable) probability, the attention parameter, and then chooses the alternative that maximises a preference relation within the set of considered alternatives. We show that this random choice rule is the only one for which the impact of removing an alternative on the choice probability of any other alternative is asymmetric and menu independent. Both the preference relation and the attention parameters are identi fied uniquely by stochastic choice data.
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Biological features and social preferences have been studied separately as factors influencing human strategic behaviour. We run two studies in order to explore the interplay between these two sets of factors. In the first study, we investigate to what extent social preferences may have some biological underpinnings. We use simple one-shot distribution experiments to attribute subjects one out of four types of social preferences: Self-interested (SI), Competitive (C), Inequality averse (IA) and Efficiency-seeking (ES). We then investigate whether these four groups display differences in their levels of facial Fluctuating Asymmetry (FA) and in proxies for exposure to testosterone during phoetal development and puberty. We observe that development-related biological features and social preferences are relatively independent. In the second study, we compare the relative weight of these two set of factors by studying how they affect subjects’ behaviour in the Ultimatum Game (UG). We find differences in offers made and rejection rates across the four social preference groups. The effect of social preferences is stronger than the effect of biological features even though the latter is significant. We also report a novel link between facial masculinity (a proxy for exposure to testosterone during puberty) and rejection rates in the UG. Our results suggest that biological features influence behaviour both directly and through their relation with the type of social preferences that individuals hold.
Resumo:
This paper discusses how to identify individual-specific causal effects of an ordered discrete endogenous variable. The counterfactual heterogeneous causal information is recovered by identifying the partial differences of a structural relation. The proposed refutable nonparametric local restrictions exploit the fact that the pattern of endogeneity may vary across the level of the unobserved variable. The restrictions adopted in this paper impose a sense of order to an unordered binary endogeneous variable. This allows for a uni.ed structural approach to studying various treatment effects when self-selection on unobservables is present. The usefulness of the identi.cation results is illustrated using the data on the Vietnam-era veterans. The empirical findings reveal that when other observable characteristics are identical, military service had positive impacts for individuals with low (unobservable) earnings potential, while it had negative impacts for those with high earnings potential. This heterogeneity would not be detected by average effects which would underestimate the actual effects because different signs would be cancelled out. This partial identification result can be used to test homogeneity in response. When homogeneity is rejected, many parameters based on averages may deliver misleading information.