This paper proposes a new unit root test in the context of a random autoregressive coefficient panel data model, in which the null of a unit root corresponds to the joint restriction that the autoregressive coefficient has unit mean and zero variance. The asymptotic distribution of the test statistic is derived and simulation results are provided to suggest that it performs very well in small s...

In this note we revisit the use of exclusion restrictions in the semiparametric binary choice panel data model introduced in Honore and Lewbel (2002). We show that in a dynamic panel data setting (where one of the pre-determined explanatory variables is the lagged dependent variable), the exclusion restriction in Honore and Lewbel (2002) implicitly requires serial independence condition on an o...

This paper considers a random coefficients panel data model with individualspecific intercepts (or fixed effects). The identification of the distribution of random slope coefficients is established in two settings: when random slope coefficients are conditionally independent from individual-specific intercepts; and when individual-specific intercepts are allowed to depend on random slope coeffi...

An estimation framework and a user-friendly software implementation are described for maximum likelihood estimation of panel data models with random effects, a spatially lagged dependent variable and spatially and serially correlated errors. This specification extends static panel data models in the direction of serial error correlation, allowing richer modelling possibilities and more thorough...

This paper considers the problem of estimating a partially linear semipara-metric fixed effects panel data model with possible endogeneity. Using the series method, we establish the root N normality result for the estimator of the parametric component, and we show that the unknown function can be consistently estimated at the standard nonparametric rate. c 2002 Peking University Press

Most previous studies of binary choice panel data models with Þxed effects require strictly exogeneous regressors, and except for the logit model without lagged dependent variables, cannot provide rate root n parameter estimates. We assume that one of the explanatory variables is independent of the individual speciÞc effect and of the errors of the model, conditional on the other explanatory va...

This paper provides a survey of the existing literature on spatial panel data models. Both static and dynamic models will be considered. The paper also demonstrates that spatial econometric models that include lags of the dependent variable and of the independent variables in both space and time provide a useful tool to quantify the magnitude of direct and indirect effects, both in the short te...

Estimating and Testing a Quantile Regression Model with Interactive Effects This paper proposes a quantile regression estimator for a panel data model with interactive effects potentially correlated with the independent variables. We provide conditions under which the slope parameter estimator is asymptotically Gaussian. Monte Carlo studies are carried out to investigate the finite sample perfo...

We study how a provider’s technical support influences service demand in a business-tobusiness setting. The provider offers two levels of support, basic and full, reflecting its involvement with the buyer in co-producing the service. Using a unique nano-data set on public cloud infrastructure services consumption by 20,298 firms from March 2009 to April 2012, fixed effects panel data models, an...