In today's volatile business environment, manufacturers often face the challenge of making sales and production decisions despite unstable market demand. Companies must strategically determine which customer orders to fulfill or which products to stock under limited resources. This study...

This article considers the problem of orders selections of vector autoregressive moving-average (VARMA) models and the sub-class of vector autoregressive (VAR) models under the assumption that the errors are uncorrelated but not necessarily independent. We relax the standard independence...

This paper develops a new nonparametric series estimator for the average treatment effect for the case with unconfounded treatment assignment, that is, where selection for treatment is on observables. The new estimator is efficient. In addition we develop an optimal procedure for choosing the...

Autoregressive models are commonly employed to analyze empirical time series. In practice, however, any autoregressive model will only be an approximation to reality and in order to achieve a reasonable approximation and allow for full generality the order of the autoregression, h say, must be...

This paper develops a new efficient estimator for the average treatment effect, if selection for treatment is on observables. The new estimator is linear in the first-stage nonparametric estimator. This simplifies the derivation of the means squared error (MSE) of the estimator as a function of...