We show that tests for differences in trade execution costs using standard nearest neighbor matching estimation techniques typically have comparable empirical power but less bias than more “sophisticated” alternatives. However, estimation techniques that place more weight on distant firms (e.g. kernel-based matching) have better testing power and produce tighter confidence intervals when there ...

This paper considers identification and estimation of structural interaction effects in a social interaction model. The model allows unobservables in the group structure, which may be correlated with included regressors. We show that both the endogenous and exogenous interaction effects can be identified if there are sufficient variations in group sizes. We consider the estimation of the model ...

An important challenge of portfolio allocation arises when the (true) characteristics of returns distribution are replaced by some estimates. This introduces estimation risk, which is crucial for portfolio management just like traditional financial risk. This paper contrasts with existing literature by focusing on a different measure of performance. We borrow from practitioners and evaluate dif...

This chapter discusses estimation, specification testing, and model selection of predictive density models. In particular, predictive density estimation is briefly discussed, and a variety of different specification and model evaluation tests due to various authors including Christoffersen and Diebold (2000), Diebold, Gunther and Tay (1998), Diebold, Hahn and Tay (1999), White (2000), Bai (2003...

During financial crises equity portfolios have suffered large losses. Methodologies for portfolio selection taking into account the possibility of large losses have existed for decades but their economic value is not well established. This article investigates the economic value in reducing the probability of large losses in portfolio selection. We combine mean-variance analysis with semi-param...

This chapter gives an account of the recent literature on estimating models for panel count data. Specifically, the treatment of unobserved individual heterogeneity that is correlated with the explanatory variables and the presence of explanatory variables that are not strictly exogenous are central. Moment conditions are discussed for these type of problems that enable estimation of the parame...

Following Lancaster (2002), we propose a strategy to solve the incidental parameter problem. The method is demonstrated under a simple panel Poisson count model. We also extend the strategy to accomodate cases when information orthogonality is unavailable, such as the linear AR(p) panel model. For the AR(p) model, there exists a correction function to fix the incidental parameter problem when t...

Local search is a basic building block in memetic algorithms. Guided Local Search (GLS) can improve the efficiency of local search. By changing the guide function, GLS guides a local search to escape from locally optimal solutions and find better solutions. The key component of GLS is its penalizing mechanism which determines which feature is selected to penalize when the search is trapped in a...

Estimation of the dynamic error components model is considered using two alternative linear estimators that are designed to improve the properties of the standard firstdifferenced GMM estimator. Both estimators require restrictions on the initial conditions process. Asymptotic efficiency comparisons and Monte Carlo simulations for the simple AR(1) model demonstrate the dramatic improvement in p...

The structural characterization of the insulin-insulin receptor (IR) interaction still lacks the conformation of the crucial B21-B30 insulin region, which must be different from that in its storage forms to ensure effective receptor binding. Here, it is shown that insulin analogues modified by natural amino acids at the TyrB26 site can represent an active form of this hormone. In particular, [A...