French firms’ strategies for protecting their intellectual property.

In attempting to protect their innovations, firms can choose from a range of mechanisms, which may be either non-statutory (trade secrets, design complexity, and lead-time advantage over competitors) or statutory (patent, design registration, trademark, copyright). Yet, little is known about how firms do actually make their choices from among these different appropriability mechanisms. The aim of this paper is to determine how French firms’ use of intellectual property protection mechanisms relates to the type of innovation, the characteristics of the market sector in which they operate, the firms’ characteristics, and their human resources strategies. Our empirical model draws on four French databases covering the period 2001–2004. Our results show that the choice of a means of protection matters and emerges out of a complex strategy. Our results also reveal that the different statutory and non-statutory means of protection are complementary within their own categories but hardly so between categories.Intellectual property rights; Multivariate probit; Appropriability; Innovation; Human resources strategies;

Vocational Training and Innovation.

Human capital is considered as one of the main inputs in economic growth. Human capital can generate endogenous growth thanks to a continuous process of knowledge and externalities accumulation (Aghion and Howitt, 1998). In that context, this paper explores the relationship between innovation and vocational training. Our methodological approach allows to contribute to the literature in three manners. First, we propose different indicators of vocational training. Second, we build a count data panel with a long time data series. This deals with the issue of non-random selection and potentially with measurement error from short panels. Finally, we explicitly allow for endogeneity and fixed effects using GMM techniques. Estimations are made on a panel data set relative to French industrial firms over the period 1986-1992. Our results indicate that whatever the indicators, vocational training has a positive impact on the technological innovation.R&D; count panel data; training; patents; linear feedback model;

Innovation and training: a dynamic count data model.

This paper explores the relationship between innovation and vocational training. We consider a linear feedback model to explain the dynamics of count data processes relative to patenting activities, R&D and training expenditures. Estimations are made on a panel data set relative to French industrial rms over the period 1986-1992. Our results indicate that the vocational training have a positive impact on the technological innovation.count panel data; linear feedback model; patents; R&D; training;

Firms’ human capital, R&D and innovation: a study on French firms.

This article investigates the effects of human capital and technological capital on innovation. While the role of technological capital as measured by research and development (R&D) expenditure has been intensively investigated, few studies have been made on the effect of employee training on innovation. This article explores the relationship between innovation and firm employee training. Our methodological approach contributes to the literature in three ways. We propose various indicators of firm employee training. We build a count data panel with a long time-data series to deal with the issue of firms’ heterogeneity. We propose a dynamic analysis. Using dynamic count data models on French industrial firms over the period 1986–1992, we find positive and significant effects of R&D intensity and training on patenting activity. Whatever the indicators of training our results show that the firm employee training has a positive impact on technological innovation.Patents; R&D; Employee training; Count panel data; Linear feedback model;

NEIGHBORHOOD EFFECTS IN SPATIAL HOUSING VALUE MODELS. THE CASE OF THE METROPOLITAN AREA OF PARIS (1999)

In hedonic housing models, the spatial dimension of housing values are traditionally processed by the impact of neighborhood variables and accessibility variables. In this paper we show that spatial effects might remain once neighborhood effects and accessibility have been controlled for. We notably stress on three sides of neighborhood effects: social capital, social status and social externalities and consider the accessibility to the primary economic center as describing the urban spatial trend. Using spatial econometrics specifications of the hedonic equation, we estimate whether spatial effects impact the housing values. Our empirical case concerns the Metropolitan Area (MA) of Paris in France which is divided in 2 636 neighborhood areas. We estimate the housing price distribution from a sample of 21,000 apartments sold in 1999. Our empirical results highlight the lumpy distribution of unit price along the general decreasing spatial trend from the Central Business District once neighborhood effects have been introduced. More precisely, a spatial error model is estimated revealing a positive and significance spatial effects across housing values which extend beyond their neighborhood area. Social capital, social status and social externalities play local role and may positively or negatively impact the housing prices. We showed a positive impact of diversified building patterns but a negative impact of social mixity which is somewhat conflictual but which is in fact in line with many current questions about social segregation and spatial segregation in urban areas.Hedonic model, housing value, neighborhood effects, spatial econometrics

Location Theories and Business Location Decision: A Micro-Spatial Investigation of a Nonmetropolitan Area in Canada

International audienceThis paper draws on location theories to statistically identify the relationship between the location of individual business establishments and the characterization of their local economic environment. Taking a microspatial perspective, the paper develops indicators from distance-based measures (DBM) to serve as independent variables in a discrete choice model (DCM). Using a 2006 database of individual business establishments in the Lower-St-Lawrence region—a coherent, nonmetropolitan subsystem of cities in the province of Québec, Canada—we provide an empirical analysis of the determinants of individual establishments’ location decisions in relation to their main economic activity within a random utility model (RUM) framework. The results show that distance to nearby centers, co-location (specialization), and the size of establishments are statistically related to location decisions.However, unlike previous studies, it is also found that discrete location choices of business establishments in service dustries are not necessarily influenced by economic diversity or co-location, whereas manufacturing firms’ location decisions are not impacted by distance to markets. All told, we believe the results provide further evidence of the importance of scale in the study of business location decisions

Micro-foundations and empirical evidence of the dynamic model for female labor force participation

International audienc

Spatial econometrics using microdata

This book provides an introduction to spatial analyses concerning disaggregated (or micro) spatial data.Particular emphasis is put on spatial data compilation and the structuring of the connections between the observations. Descriptive analysis methods of spatial data are presented in order to identify and measure the spatial, global and local dependency.The authors then focus on autoregressive spatial models, to control the problem of spatial dependency between the residues of a basic linear statistical model, thereby contravening one of the basic hypotheses of the ordinary least squares app