We suggest that the proximity of a country to other countries is a factor that affects its choice as an MNE location. We introduce the concept of a country's proximity to the global distribution of knowledge, markets and resources, and frame this concept as a function of both geographic distance...

The wild bootstrap was originally developed for regression models with heteroskedasticity of unknown form. Over the past thirty years, it has been extended to models estimated by instrumental variables and maximum likelihood, and to ones where the error terms are (perhaps multi-way) clustered....

Sorting and spillovers can create correlation in individual outcomes. In this situation, standard discrete choice estimators cannot consistently estimate the probability of joint and conditional events, and alternative estimators can yield incoherent statistical models or intractable estimators....

In this paper, we compare the performance of two non-parametric methods of classification, Regression Trees (CART) and the newly Multivariate Adaptive Regression Splines (MARS) models, in forecasting bankruptcy. Models are implemented on a large universe of US banks over a complete market cycle...

We study the internationalisation process in a representative sample of 786 firms in the Italian automotive supply chain. Most of these firms have agglomerated in the Turin industrial district, the cradle of FIAT, the dominant Italian car-maker and one of the global players in the automotive...

We study the role played by geographical distance in the peering decisions between Internet Service Providers. Firstly, we assess whether or not the Internet industry shows clustering in peering; we then concentrate on the dynamics of the agglomeration process by studying the effects of...

This paper analyzes the effects of geographical proximity and agglomeration of FDIs (foreign direct investments) on domestic firms in the privatized glass sector in the Czech Republic. The motivation for this research is based on the scant evidence in Central and Eastern Europe of the effects of...

Efficient computational algorithms for bootstrapping linear regression models with clustered data are discussed. For OLS regression, a new algorithm is provided for the pairs cluster bootstrap, and two algorithms for the wild cluster bootstrap are compared. One of these is a new way to express...

Reliable inference with clustered data has received a great deal of attention in recent years. The overwhelming majority of this research assumes that the cluster structure is known. This assumption is very strong, because there are often several possible ways in which a dataset could be...

Using comprehensive, anonymized tax administrative data for the 2008-14 period, we examine firm-level productivity in South Africa. Measures of firm-level productivity are included in a spatial autoregressive model that assesses spillovers from total factor productivity originating from...