Search results for "SPATIAL ECONOMETRICS"
showing 10 items of 41 documents
The European Regional Convergence Process, 1980-1995: Do Spatial Regimes and Spatial Dependence Matter?
2002
International audience; The authors show that spatial dependence and spatial heterogeneity matter in the estimation of the ß-convergence process among 138 European regions over the 1980 to 1995 period. Using spatial econometrics tools, the authors detect both spatial dependence and spatial heterogeneity in the form of structural instability across spatial convergence clubs. The estimation of the appropriate spatial regimes spatial error model shows that the convergence process is different across regimes. The authors also estimate a strongly significant spatial spillover effect: the average growth rate of per capita GDP of a given region is positively affected by the average growth rate of …
Decomposing and Interpreting Spatial Effects in Spatio-Temporal Analysis: Evidences for Spatial Data Pooled Over Time
2017
Empirical applications using individual spatial data pooled over time usually neglect the fact that such data are not only spatially localized: they are also collected over time, i.e. temporally localized. So far, little effort has been devoted to proposing a global way for dealing with spatial data (cross-section) pooled over time, such as real estate transactions, business start-up, crime and so on. However, the spatial effect, in such a context, can be decomposed in two different components: a multidirectional spatial effect (same time period) and a unidirectional spatial effect (previous time period). Based on real estate literature, this chapter presents different spatio-temporal autor…
A Comprehensive Spatiotemporal Framework for Hedonic Pricing: Integrating the Comparable Sales Approach and Minimizing Spatial Omitted Variable Bias
2019
This paper develops a theoretical and methodological framework that integrates Hedonic Pricing (HP), grid comparable sales approach (CSA), and nearest neighbors into a general spatiotemporal specification. By explicitly providing a theoretical justification for introducing spatial (or spatiotemporal) econometrics to HP, this approach is not only relevant to house price forecasting and automated valuation models (AVM) but also to valuing environmental goods capitalized in housing and to all other fields employing house pricing models. The resulting econometric CSA and spatiotemporal Durbin models provide higher prediction accuracy and reliability to alternatives by reducing the spatially-del…
Modeling Spatial Data Pooled over Time: Schematic Representation and Monte Carlo Evidences
2015
The spatial autocorrelation issue is now well established, and it is almost impossible to deal with spatial data without considering this reality. In addition, recent developments have been devoted to developing methods that deal with spatial autocorrelation in panel data. However, little effort has been devoted to dealing with spatial data (cross-section) pooled over time. This paper endeavours to bridge the gap between the theoretical modeling development and the application based on spatial data pooled over time. The paper presents a schematic representation of how spatial links can be expressed, depending on the nature of the variable, when combining the spatial multidirectional relatio…
'Dual' Gravity: Using Spatial Econometrics to Control for Multilateral Resistance
2010
We propose a quantity-based `dual' version of the gravity equation that yields an estimating equation with both cross-sectional interdependence and spatially lagged error terms. Such an equation can be concisely estimated using spatial econometric techniques. We illustrate this methodology by applying it to the Canada-U.S. data set used previously, among others, by Anderson and van Wincoop (2003) and Feenstra (2002, 2004). Our key result is to show that controlling directly for spatial interdependence across trade flows, as suggested by theory, significantly reduces border effects because it captures `multilateral resistance'. Using a spatial autoregressive moving average specification, we …
Urban segregation and unemployment: A case study of the urban area of Marseille – Aix-en-Provence (France)
2018
International audience; In this paper, we study the effects of the spatial organization of the urban area of Marseille – Aix-en-Provence on unemployment there. More specifically, differences in the characteristics of the residential population induce urban stratification with the result that urban structure may affect the probability of employment. In order to evaluate the effects of spatial structure on unemployment, we implement a spatial probit model to reveal the employment probabilities of young adults still living with their parents. Our results support the hypothesis that living in or near a deprived neighborhood decreases the probability of employment.
Environmental expenditure interactions among OECD countries, 1995-2017
2021
International audience; How do countries respond to other countries when setting the level of their environmental expenditures? Using data from 1995-2017 on a sample of 28 OECD countries, we examine the nature and extent of strategic interactions in environmental expenditures among OECD countries using a spatial Durbin model including economic and political control variables and both economic and spatial weight matrices reflecting several interaction mechanisms. The results show the existence of significant positive spatial dependence in environmental spending suggesting that OECD countries consider their neighbors' behavior when making policy choices related to environmental expenditures. …
Geographical distribution of crime in Italian provinces: a spatial econometric analysis
2009
For a long time social sciences scholars from different fields have devoted their attention to identifying the causes leading to commit criminal offences and recently lots of studies have included the analysis of spatial effects. Respect to the Italian crime phenomenon some stylized facts exist: high spatial and time variability and presence of “organised crime” (e.g. Mafia and Camorra) deep-seated in some local territorial areas. Using explanatory spatial data analysis, the paper firstly explores the spatial structure and distribution of four different typologies of crimes (murders, thefts, frauds, and squeezes) in Italian provinces in two years, 1999 and 2003. ESDA allows us to detect som…
Nonlinear impact estimation in spatial autoregressive models
2018
International audience; This paper extends the literature on the calculation and interpretation of impacts for spatial autoregressive models. Using a Bayesian framework, we show how the individual direct and indirect impacts associated with an exogenous variable introduced in a nonlinear way in such models can be computed, theoretically and empirically. Rather than averaging the individual impacts, we suggest to graphically analyze them along with their confidence intervals calculated from Markov chain Monte Carlo (MCMC). We also explicitly derive the form of the gap between individual impacts in the spatial autoregressive model and the corresponding model without a spatial lag and show, in…
Putting time into space: the temporal coherence of spatial applications in the housing market
2016
International audience; Relationships between past events, future expectations and present decisions, typically examined through a temporal prism within applied economics, have been lately moving to the spatial dimension through spatial econometrics. However, violations of the “arrow of time”, and thus causality, have been identified in spatial econometric techniques applied to spatio-temporal data consisting of observations each at a specific location and distinct moment in time. A comprehensive review classifies for the first time several redresses to this issue in a currently fragmented literature. This paper puts back the temporal dimension into spatial Hedonic Pricing models through a …