Forecast combinations, also known as ensemble models, routinely require practitioners to select a model from a massive number of potential candidates. Ten explanatory variables can be grouped into 21078 forecast combinations, and the number of possibilities increases further to 21078+21078 if we...

This paper summarizes and assesses several of the most popular methods to seasonally adjust weekly data. The industry standard approach, known as X-13ARIMA-SEATS, is suitable only for monthly or quarterly data. Given the increased availability and promise of non-traditional data at higher...

Chapter 1. Preliminaries -- Chapter 2. Topology -- Chapter 3. Metric Spaces -- Chapter 4. Normed Spaces -- Chapter 5. Sequences and Series -- Chapter 6. Differential Calculus of functions of one variable -- Chapter 7. Functions of several variables -- Chapter 8. Integral Calculus -- Chapter 9....

We propose a set of algorithms for testing the ergodicity of empirical time series, without reliance on a specific parametric framework. It is shown that the resulting test asymptotically obtains the correct size for stationary and nonstationary processes, and maximal power against non-ergodic...

This paper studies simulation-based optimization with multiple outputs. It assumes that the simulation model has one random objective function and must satisfy given constraints on the other random outputs. It presents a statistical procedure for testing whether a specific input combination...

Bayesian methods have become widespread in the marketing literature. We review the essence of the Bayesian approach and explain why it is particularly useful for marketing problems. While the appeal of the Bayesian approach has long been noted by researchers, recent developments in computational...

The purpose of this paper is to investigate the asymptotic null distribution of stationarity and nonstationarity tests when the distribution of the error term belongs to the normal domain of attraction of a stable law in any finite sample but the error term is an i.i.d. process with finite...

This article shows that, under some common assumptions, the pointwise synthetic control estimator would be unbiased if the outcome variable follows an autoregressive process. However, if such autoregressive process is nonstationary, then the variance of the pointwise estimator would be sensitive...

A decision maker tests whether the gradient of the loss function evaluated at a judgmental decision is zero. If the test does not reject, the action is the judgmental decision. If the test rejects, the action sets the gradient equal to the boundary of the rejection region. This statistical...