We propose a computationally feasible inference method in finite games of complete information. Galichon and Henry (2011) and Beresteanu, Molchanov, and Molinari (2011) show that the empirical content in such models is characterized by a collection of moment inequalities whose number increases...

We study the finite-sample properties of tests for overidentifying restrictions in linear regression models with a single endogenous regressor and weak instruments. Under the assumption of Gaussian disturbances, we derive expressions for a variety of test statistics as functions of eight...

This study investigates resourcing of computer software companies that have adopted cloud computing for the development and delivery of application software. Use of this innovative technology potentially impacts firm financing because the initial infrastructure investment requirement is much...

Efficient Global Optimization (EGO) is a popular method that searches sequentially for the global optimum of a simulated system. EGO treats the simulation model as a black-box, and balances local and global searches. In deterministic simulation, EGO uses ordinary Kriging (OK), which is a special...

We compare two bootstrap methods for assessing mutual fund performance. Kosowski, Timmermann, Wermers and White (2006) produces narrow confidence intervals due to pooling over time, while Fama and French (2010) produces wider confidence intervals because it preserves the cross-correlation of...

In this paper, we propose a novel entropy-based resampling scheme valid for non-stationary data. In particular, we identify the reason for the failure of the original entropy-based algorithm of Vinod and Lopez-de Lacalle (2009) to be the perfect rank correlation between the actual and...