Point allocation experiments are widely used in the social sciences. In these experiments, survey respondents distribute a fixed total number of points across a fixed number of alternatives. This paper reviews the different perspectives in the literature about what respondents do when they...

We consider some asymptotic distribution theory for M-estimators of the parameters of a linear model whose errors are non-negative; these estimators are the solutions of constrained optimization problems and their asymptotic theory is non-standard. Under weak conditions on the distribution of the...

We investigate the estimation of models of dynamic discrete-choice games of incomplete information, formulating the maximum-likelihood estimation exercise as a constrained optimization problem that can be solved using state-of-the-art constrained optimization solvers. Under the assumption that...

Estimating structural models is often viewed as computationally difficult, an impression partly due to a focus on the nested fixed-point (NFXP) approach. We propose a new constrained optimization approach for structural estimation. We show that our approach and the NFXP algorithm solve the same...

Professional economists rarely write on questions of genocide. This surprises because a workhorse tool of the economics discipline concerns the analysis of behavior that takes place under constraints. All parties in genocide—perpetrators, victims, and third parties—face cost and resource...

This paper presents a method capable of estimating richly parametrized versions of the dynamic conditional correlation (DCC) model that go beyond the standard scalar case. The algorithm is based on the maximization of a Gaussian quasi-likelihood using a Bregman-proximal trust-region method to...

The paper identifies a necessary and sufficient condition for a deterministic local optimum to be locally improved upon by a stochastic deviation. When this condition is satisfied, a method to construct the stochastic allocations that increase the objective is provided. This technique is applied...

The paper identifies a necessary and sufficient condition for a deterministic local optimum to be locally improved upon by a stochastic deviation. When this condition is satisfied, a method to construct the stochastic allocations that increase the objective is provided. This technique is applied...

In this working paper we study some properties of a particular mapping in Rn related to an optimization problem with one equality constraint. We motivate the definition of the relevant mapping starting from a portfolio selection problem, in which we minimize the risk of an investment (the...

We consider some asymptotic distribution theory for M-estimators of the parameters of a linear model whose errors are non-negative; these estimators are the solutions of constrained optimization problems and their asymptotic theory is non-standard. Under weak conditions on the distribution of the...