Georges Bresson

• PhD in Economics
• Professor at Univ. Paris II

This paper derives a feasible GLS estimator for a two-way error component model with serial correlation on both the time effects as well as the remainder disturbances. This estimator is based on two methods, one proposed by De Porres and Krishnaku mar(2013) for deriving the spectral decomposition of a general error component structure and the other...

For a panel data linear regression model with both individual and time effects, empirical studies select the two-way random-effects (TWRE) estimator if the Hausman test based on the contrast between the two-way fixed-effects (TWFE) estimator and the TWRE estimator is not rejected. Alternatively, they select the TWFE estimator in cases where this Ha...

This chapter surveys housing models using multi-dimensional panels. While there is a vast literature on housing models using two-dimensional panel data, there are only few papers using multi-dimensional panels. This chapter focuses on housing models, residential mobility and location choice models derived from discrete choice theory utilizing multi...

Excessive nighttime light is known to have detrimental effects on health and on the environment (fauna and flora). The paper investigates the link between nighttime light pollution and economic growth, air pollution, and urban density. We propose a county model of consumption which accounts for spatial interactions. The model naturally leads to a d...

Background Adult studies have shown that nursing overtime and unit overcrowding are associated with increased adverse patient events but there exists little evidence for the Neonatal Intensive Care Unit (NICU). We investigate the main determinants of nosocomial infections and medical accidents in a NICU using state-of-the-art machine learning techn...

This paper extends the Baltagi et al. (J Econom 202:108–123, 2018; Advances in econometrics, essays in honor of M. Hashem Pesaran, Emerald Publishing, Bingley, 2021) static and dynamic \(\varepsilon \)-contamination papers to dynamic space–time models. We investigate the robustness of Bayesian panel data models to possible misspecification of the p...

This paper extends the Baltagi et al. (J Econom 202:108–123, 2018; Advances in econometrics, essays in honor of M. Hashem Pesaran, Emerald Publishing, Bingley, 2021) static and dynamic \( \varepsilon \)-contamination papers to dynamic space–time models. We investigate the robustness of Bayesian panel data models to possible misspecification of the...

The paper investigates the effects of nursing overtime on nosocomial infections and medical accidents in a neonatal intensive care unit (NICU). The literature lacks clear evidence on this issue and we conjecture that this may be due to empirical and methodological factors. We model the occurrences of both events using a sample of 3979 neonates who...

This article develops a Bayesian approach for estimating panel quantile regression with binary outcomes in the presence of correlated random effects. We construct a working likelihood using an asymmetric Laplace error distribution and combine it with suitable prior distributions to obtain the complete joint posterior distribution. For posterior inf...

Linear regression with measurement error in the covariates is a heavily studied topic, however, the statistics/econometrics literature is almost silent to estimating a multi-equation model with measurement error. This paper considers a seemingly unrelated regression model with measurement error in the covariates and introduces two novel estimation...

Linear regression with measurement error in the covariates is a heavily studied topic, however, the statistics/econometrics literature is almost silent to estimating a multi-equation model with measurement error. This paper considers a seemingly unrelated regression model with measurement error in the covariates and introduces two novel estimation...

Linear regression with measurement error in the covariates is a heavily studied topic, however, the statistics/econometrics literature is almost silent to estimating a multi-equation model with measurement error. This paper considers a seemingly unrelated regression model with measurement error in the covariates and introduces two novel estimation...

This article develops a Bayesian approach for estimating panel quantile regression with binary outcomes in the presence of correlated random effects. We construct a working likelihood using an asymmetric Laplace (AL) error distribution and combine it with suitable prior distributions to obtain the complete joint posterior distribution. For posterio...

This article develops a Bayesian approach for estimating panel quantile regression with binary outcomes in the presence of correlated random effects. We construct a working likelihood using an asymmetric Laplace (AL) error distribution and combine it with suitable prior distributions to obtain the complete joint posterior distribution. For posterio...

The paper investigates the effects of nursing overtime on nosocomial infections and medical accidents in a neonatal intensive care unit (NICU). The literature lacks clear evidence on this issue and we conjecture that this may be due to empirical and methodological factors. We thus focus on a single NICU, thereby removing much variation in specialty...

This chapter surveys housing models using multi-dimensional panels. While there is a vast literature on housing models using two-dimensional panel data, there are few papers using multi-dimensional panels. This chapter focuses on housing models, residential mobility and location choice models derived from discrete choice theory, utilizing multi-dim...

The paper develops a general Bayesian framework for robust linear static panel data models using ϵ-contamination. A two-step approach is employed to derive the conditional type-II maximum likelihood (ML-II) posterior distribution of the coefficients and individual effects. The ML-II posterior means are weighted averages of the Bayes estimator under...

This paper estimates a hedonic housing model based on flats sold in the city of Paris over the period 1990–2003. This is done using maximum likelihood estimation, taking into account the nested structure of the data. Paris is historically divided into 20 arrondissements , each divided into four quartiers (quarters), which in turn contain between 15...

The paper develops a general Bayesian framework for robust linear static panel data models using ε-contamination. A two-step approach is employed to derive the conditional type-II maximum likelihood (ML-II) posterior distribution of the coefficients and individual effects. The ML-II posterior densities are weighted averages of the Bayes estimator u...

The paper develops a general Bayesian framework for robust linear static panel data models using epsilon-contamination. A two-step approach is employed to derive the conditional type-II maximum likelihood (ML-II) posterior distribution of the coefficients and individual effects. The ML-II posterior densities are weighted averages of the Bayes estim...

The paper develops a general Bayesian framework for robust linear static panel data models using ε-contamination. A two-step approach is employed to derive the conditional type-II maximum likelihood (ML-II) posterior distribution of the coefficients and individual effects. The ML-II posterior densities are weighted averages of the Bayes estimator u...

This paper estimates a hedonic housing model based on flats sold in the city of Paris over the period 1990-2003. This is done using maximum likelihood estimation taking into account the nested structure of the data. Paris is historically divided into 20 arrondissements, each divided into four quartiers (quarters), which in turn contain between 15 a...

This paper compares various forecasts using panel data with spatial error correlation. The true data generating process is assumed to be a simple error component regression model with spatial remainder disturbances of the autoregressive or moving average type. The best linear unbiased predictor is compared with other forecasts ignoring spatial corr...

This paper suggests a robust Hausman and Taylor (1981) estimator, here-after HT, that deals with the possible presence of outliers. This entails two modications of the classical HT estimator. The rst modication uses the Bramati and Croux (2007) robust Within MS estimator instead of the Within estimator in the rst stage of the HT estimator. The...

This paper proposes a functional connectivity approach, inspired by brain imaging literature, to model cross-sectional dependence. Using a varying parameter framework, the model allows correlation patterns to arise from complex economic or social relations rather than being simply functions of economic or geographic distances between locations. It...

This paper proposes a Bayesian approach to estimating a factor-augmented GDP per capita equation. We exploit the panel dimension of our data and distinguish between individual-specific and time-specific factors. On the basis of 21 technology, infrastructure, and institutional indicators from 82 countries over a 19-year period (1990 to 2008), we con...

Based on a non parametric panel data estimation, this study provides an accurate analysis related to the stay-over/cruise tourism relationship for fifteen Caribbean countries over the period 1985-2004. It reveals not only the heterogene-ity of the tourism flows across the different countries but, it alsoemphasizes the crowding-out effects of the cr...

This paper proposes maximum likelihood estimators for panel seemingly unrelated regressions with both spatial lag and spatial error components. We study the general case where spatial effects are incorporated via spatial errors terms and via a spatial lag dependent variable and where the heterogeneity in the panel is incorporated via an error compo...

The objective of this paper is to develop a stylized model of the hard competi-tion between Caribbean islands and between cruise lines to attract cruise and land-based tourist flows. The cruise lines industry and the land-based tourism sector are characterized by oligopolistic structures in which the producers compete to maximize their payoffs. Fol...

This paper proposes ML estimators for a panel SUR with both spatial lag and spatial error components. We study the general case where spatial effects are incorporated via spatial errors terms and via spatially dependent variable and where the heterogeneity in the panel is incorporated via an error component specification. This generalizes the appro...

Chamberlain [Chamberlain, G., 1982. Multivariate regression models for panel data. Journal of Econometrics 18, 5–46] showed that the fixed effects (FE) specification imposes testable restrictions on the coefficients from regressions of all leads and lags of dependent variables on all leads and lags of independent variables. Angrist and Newey [Angri...

This paper proposes a hierarchical Bayes estimator for a panel data random coefficient model with heteroskedasticity to assess the contribution of R&D capital to total factor productivity. Based on Hall (1993) data for 323 US firms over 1976–1990, we find that there appear to have substantial unobserved heterogeneity and heteroskedasticity across f...

We explore the impact of spatial and technological R&D spillovers on the innovative activities in Europe. We consider a linear feedback model to explain the dynamics of count data processes relative to patents and R&D expenditures. Estimations are made on a panel data set relative to public and private sectors in 113 regions of 9 European countries...

This paper derives a hierarchical Bayes estimator for a panel data random coefficient model with heteroskedasticity. Monte Carlo simulations show the good performance of such estimator as compared to classical ones. Empirical evidence on the contribution of R&D to the total factor produc-tivity in US manufacturing firms corroborates results obtaine...

This paper considers a general heteroskedastic error component model using panel data, and derives a joint Lagrange multiplier (LM) test for homoskedasticity against the alternative of heteroskedasticity in both error components. It contrasts this joint LM test with marginal LM tests that ignore the heteroskedasticity in one of the error components...

This paper studies the performance of panel unit root tests when spatial effects are present that account for cross-section correlation. Monte Carlo simulations show that there can be considerable size distortions in panel unit root tests when the true specification exhibits spatial error correlation. These tests are applied to a panel data set on...

This paper contributes empirically to our understanding of informed traders. It analyzes traders' characteristics in a foreign exchange electronic limit order market via anonymous trader identities. We use six indicators of informed trading in a cross-sectional multivariate approach to identify traders with high price impact. More information is co...

This paper proposes to identify and to estimate the effects of research externalities in generating innovation across European regions. R&D externalities are identifed as the effect of R&D intensity from one region i on the innovative output of region j. In order to identify these externalities, we assume that they depend on the geographical distan...

This paper checks the sensitivity of two adaptive heteroskedastic estimators suggested by Li and Stengos (1994) and Roy (2002) for an error component regression model to misspecification of the form of heteroskedasticity. In particular, we run Monte Carlo experiments using the heteroskedasticity setup by Li and Stengos (1994) to see how the misspec...

This paper considers a general heteroskedastic error component model using panel data, and derives a joint Lagrange multiplier (LM) test for homoskedasticity against the alternative of heteroskedasticity in both error components. It contrasts this joint LM test with marginal LM tests that ignore the heteroskedasticity in one of the error components...

This paper presents a panel data analysis of annual time series from 1975 to 1995 for 62 urban areas in France. It compares the results obtained from a conventional fixed-effects (FE) model with a Bayesian approach (shrinkage estimators), which allows the computation of elasticities for each urban area. First, considering only three economic determ...

Elements of answer to this question are elaborated from …scal time series at the municipality level, covering the 1986-98 period (i.e. the rapid growth of the late 80's, followed by the recession of 1993 and a recover). During this period, the proportion of …scal households living in the outer suburbs is increasing. The average distance of …scal ho...

This paper checks the sensitivity of two adaptive heteroskedastic estimators suggested by Li and Stengos (1994) and Roy (2002) for an error component regression model to misspecification of the form of heteroskedasticity. In particular, we run Monte Carlo experiments using the heteroskedasticity setup by Li and Stengos (1994) to see how the misspec...

This paper reconsiders the Tobin q investment model studied by Hsiao et al. (1999) using a panel of 337 U.S. firms over the period 1982–1998. It contrasts the out-of-sample forecasts performance of hierarchical Bayes, shrinkage, as well as heterogeneous and homogeneous panel data estimators. Copyright Springer-Verlag 2004

In the spirit of White’s (1982) paper, this paper examines the consequences of model misspecification using a panel data regression model. Maximum likelihood, random and fixed effects estimators are compared using Monte Carlo experiments under normality of the disturbances but with a possibly misspecified variance-covariance matrix. We show that th...

This study analyses the impacts of changes in fares, service supply, income and other factors on the demand for public transport on the basis of panels of English counties and French urban areas. The analysis is based on dynamic econometric models, so that both short- and long-run elasticities are estimated. Conventional approaches (i.e. fixed- and...

This paper suggests a pretest estimator based upon two Hausman tests as an alternative to the fixed effects or random effects estimators for panel data models. The bias and RMSE properties of these estimators are investigated using Monte Carlo experiments.

This paper contrasts the performance of heterogeneous and shrinkage estimators versus the more traditional homogeneous panel data estimators. The analysis utilizes a panel data set from 21 French regions over the period 1973–1998 and a dynamic demand specification to study the gasoline demand in France. Out-of-sample forecast performance as well as...

Maddala et al. [Journal of Business and Economic Statistics, 15 (1997) 90] obtained short-run and long-run elasticities of energy demand for each of 49 US states over the period 1970–1990. They showed that heterogeneous time series estimates for each state yield inaccurate signs for the coefficients, while panel data estimates are not valid because...

We propose an oligopolistic competition model where exchanged products are simultaneously differentiated in horizontal and vertical dimensions. Perfect NASH equilibria are defined supposing that some decisions sequencies are expressed in terms of prices, technical characteristics and quality. In this context, it appears that horizontal differentiat...

In this article we pay attention to the conditions that make an aggregate labor demand equation consistent with the underlying model at a more disaggregated level when heterogeneity exists across firms or across workers. It is argued that this consistency rests on the condition that employment evolves in the same direction in all firms and for all...

When firms face a change in their environment, they do not necessarily adjust immediately their level of employment to the new business conditions. Since the pioneering work of Oi [1962], it is well-known that labour is not a fully flexible production factor, due to the existence of adjustment costs, namely hiring and firing costs. In his article,...

This study compares time series and panel data demand estima-tions and forecasts for public transport in the metropolitan area of Paris. The analysis is based on dynamic econometric models, so that both short-and long-run elasticities are estimated. Conventional ap-proach (GMM time series models) and random-coe¢cients approach are tested on the sam...

This article focuses on variance components estimators for a two-way error component model, written in a uni…ed matrix formulation as Maddala and Mount did in 1973 for the one-way error component model. Using Monte Carlo experiments, this paper also analyses biais and e¢ciency properties of all the available estimators for several time and individu...