David Hendry and Hans-Martin Krolzig have demonstrated that PCGets, an automatic model selection algorithm that implements general-to-specific search procedures, can be successfully applied to the individual equations of vector autoregressions (VARs), provided that the contemporaneous causal...

In economics and finance, test statistics and confidence regions are typically probabilistically dependent on previously-used data. However, the Bayesian and classical justifications for usual tests and confidence regions are known to be invalid in this case. Given the success of empirical...

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...

This paper develops particle-based methods for sequential inference in nonlinear models. Sequential inference is notoriously difficult in nonlinear state space models. To overcome this, we use auxiliary state variables to slice out nonlinearities where appropriate. This induces a Fixed-dimension...

The fundamental problem of external validity is not to generalize from one experiment, so much as to experimentally test generalizable theories. That is, theories that explain the systematic variation of causal effects across contexts. Here we show how the graphical language of causal diagrams...

This paper studies nonparametric series estimation and inference for the effect of a single variable of interest x on an outcome y in the presence of potentially high-dimensional conditioning variables z. The context is an additively separable model E[y|x, z] = g0(x) + h0(z). The model is...

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...

We represent affine sub-manifolds of exponential family distributions as minimum relative entropy sub-manifolds. With such representation we derive analytical formulas for the inference from partial information on expectations and covariances of multivariate normal distributions; and we improve...

In this paper, we construct confidence sets for models defined by many conditional moment inequalities/equalities. The conditional moment restrictions in the models can be finite, countably infinite, or uncountably infinite. To deal with the complication brought about by the vast number of...

In this paper, we construct confidence sets for models defined by many conditional moment inequalities/equalities. The conditional moment restrictions in the models can be finite, countably in finite, or uncountably in finite. To deal with the complication brought about by the vast number of...