Diego Legros

Spatial econometrics and the hedonic pricing model : what about the temporal dimension?

Recent ready access to free software and toolbox applications is directly impacting spatial econometric modelling when working with geolocated data. Spatial econometric models are valuable tools for taking into account the possible latent structure of the price determination process and ensuring that the coefficients estimated are unbiased and efficient. However, mechanical applications can potentially bias estimated coefficients if spatial data is pooled over time because the applications consider the spatial dimension alone. Spatial models neglect the fact that data (e.g. real estate) may consist of a collection of spatial data pooled over time, and that time relations generate a unidirectional effect as opposed to the multidirectional effect associated with spatial relations. Through an empirical case study, this paper addresses the possible bias in spatial autoregressive estimated parameters when data consist of spatial layers pooled over time. An empirical study is made using apartment sales in Paris between 1990 and 2001. Estimation results and out-of-sample predictions confirm, at least for this case, the hypothesis that ignoring the time dimension and applying spatial econometric tools generate divergence among the estimated autoregressive coefficients, which can potentially engender other serious problems.

Testing for Complementarities between Team, Incentives, Training and Knowledge Management: Evidence from France

This paper examines theknowledge creation, sharing and transferring process within manufacturing …rms in an innovation perspective. Using French data set, we study complementari- ties between speci…c human resource management practices (HRMP) and knowledge management. We focus on four speci…c practices : team, incentives, training and knowledge management. We use a new testing procedure for complementarity and substitutability in case there are multiple organizational practices that aect innovative performance. This procedure is based on multiple inequality restriction. The result supports the notion that knowledge management is more eective if accompanied by team organization and associated incentives. It pleads in favour of the impor- tant interrelations and couplings between speci…c HRMP and knowledge management to enhance innovation performance.

Research and Development, Innovation, Training, Quality and Profitability: Evidence from France

This paper simultaneously explores the firm-level relationships between R&D investments, innovation, training investments, quality and firm performance. It offers empirical evidence on how innovation, training and quality affect firm profitability. One new feature we introduce is the link between training and quality. Using asymptotic least square, we estimate a five-equation model including censored, dichotomous and linear variables with a specific circular scheme. The data are from the French innovation survey combined with firm-level register data. This allows us to consider a number of training and quality related variables which are usually neglected in the literature. While traditional determinants are controlled for, our results show there exists a virtuous circle. Our results are also in line with a number of stylized facts.

A Spatiotemporal Solution for the Simultaneous Sale Price and Time-on-the-Market Problem

There exists an important methodological challenge when dealing with sale price and time-on-the-market variables because both variables are simultaneously determined and related to the motivation of the sellers and buyers. Exploiting the fact that transactions occur over space and time, we propose a two-stage approach based on instrumental variables (IV) built from information collected from previous transactions. The unidirectional temporal property and the fact that other transactions are exogenous from the perspective of a single buyer or seller are exploited to evaluate the effect of the sale price on time-on-the-market, and the effect of time-on-the-market on the sale price. Based on 29,471 transactions occurring in the suburban neighborhood of Montreal (1992-2000), the results suggest that, everything else being equal, houses staying longer on the market provide negative information to the market, which results in a lower final sale price, while the final sale price is negatively related to time-on-the-market, indicating that houses of better quality (better amenities) stay less time on the market.

The Dynamics of Car Availability in EU Countries: A Comparison Based on the European Household Panel Survey

In this paper, the authors examine the dynamics of car availability in EU countries. Factors that are studied in the analysis include income levels, number of adults and children in households, and the gender of household residents. Survey data from the European Community Household Panel (ECHP), as well as econometric modeling, are used in the analyses.

Past price “memory” in the housing market: testing the performance of different spatio-temporal specifications.

ABSTRACT Recent methodological developments provide a way to incorporate the temporal dimension when accounting for spatial effects in hedonic pricing. Weight matrices should decompose the spatial effects into two distinct components: bidirectional contemporaneous spatial connections; and unidirectional spatio-temporal effects from past transactions. Our iterative estimation approach explicitly analyses the role of time in price determination. The results show that both spatio-temporal components should be included in model specification; past transaction information stops contributing to price determination after eight months; and limited temporal friction is exhibited within this period. These findings highlight the decidedly non-linear temporal patterns of such information effects.

Dynamics of female labour force participation in France

ABSTRACT This article formulates and estimates a structural intertemporal model of labour force participation. Relying on theoretical characterizations derived from an economic model of lifetime behaviour, we estimate a dynamic probit model with correlated random effects using longitudinal data to allow for a dynamic structure. The model is applied to a panel of married women drawn from the 1997–2002 French Labour Force surveys in order to represent their participation behaviour. It is estimated by maximum simulated likelihood. Our results show that women’s decisions to go out to work are characterized by significant state dependence, unobserved heterogeneity and negative serial correlation in the transitory error component. In addition, we find that the presence of young children in a woman’s household reduces her labour participation, but unequally according to their age and number. As expected, educational level has a positive impact on women’s participation. Last, a rise in the husband’s wage is found to raise female participation initially and to lower it subsequently. This empirical finding suggests that leisure may not systematically be a normal good, contrary to what is frequently assumed in the literature.

HOW DO SPATIAL SPILLOVERS DIFFUSE IN SCIENCE–INDUSTRY INTERACTIONS? THE CASE OF FRENCH BIOTECH SECTOR

The objective of this article is to study the interactions that exist between public research and private research in the French biotechnology sector. These interactions are observable at a double level. On the one hand, public research can influence private research, and conversely. Researchers of these two spheres develop important relations of cooperation. We then seek to identify these mutual influences and to measure their spatial dimension. Using asymptotic least squares method, we show that spillovers can diffuse through cooperation in upstream and downstream phases of the innovation process. On the other hand, spillovers resulting from public or private research, when measured by an external stock of knowledge, would be located, in so far as they exist.

Decomposing and Interpreting Spatial Effects in Spatio-Temporal Analysis: Evidences for Spatial Data Pooled Over Time

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 autoregressive (STAR) models and shows how spatial econometrics models can be extended for empirical investigation. Using a Monte Carlo experiment, we underline the effect of neglecting the decomposition of the spatial effect on the bias of the autoregressive coefficients as well as on the interpretation of the marginal effect. An empirical experiment using apartment sales in Paris between 1990 and 2003 supports the global results obtained through the Monte Carlo experiment.