We develop an “omitted variable bias” framework for sensitivity analysis of instrumental variable (IV) estimates that is immune to “weak instruments,” naturally handles multiple “side-effects” (violations of the exclusion restriction assumption) and “confounders” (violations of...

This paper presents a set of tests and an algorithm for agnostic, data-driven selection among macroeconomic Dynamic Stochastic General Equilibrium (DSGE) models inspired by structure learning methods for Directed Acyclical Graphs (DAGs). As the log-linear state-space solution to any DSGE model...

Interactive fixed effects are a popular means to model unobserved heterogeneity in panel data. Models with interactive fixed effects are well studied in the low-dimen\-sional case where the number of parameters to be estimated is small. However, they are largely unexplored in the...

A common practice in estimating parameters in DSGE models is to nd a set that when simulated gets close to an average of certain data moments; the model s simulated performance for other moments is then compared to the data for these as an informal test of the model. We call this procedure...

This paper presents a mini-review on our previous work presented in ref. [1-6] in which the neural networks (NNs) were used for estimating and then detecting the robot’s collisions with the human operator during the cooperation task. This review investigates and compares the designed NN...

Quantile regression has become widely used in empirical macroeconomics, in particular for estimating and forecasting tail risks to macroeconomic indicators. In this paper we examine various choices in the specification of quantile regressions for macro applications, for example, choices related...

Researchers typically use rank ordered logit regression to analyze consumer preference data collected with Best-Worst Scaling (BWS) surveys. We propose a generalized rank ordered logit (GROL) model that accommodates scale and preference heterogeneity. Both the GROL and mixed rank ordered logit...

This paper presents a novel test of cointegration that is robust to general forms of weak dependence in the innovation sequences and is simple to implement. In contrast to existing procedures, this is achieved without applying corrections to the test statistic for removing the effect of serial...

Time-varying coefficient models have been widely used to model changing relationships of economic and financial variables. The existing literature usually specifies the time-varying coefficient vector as a stochastic stationary process, a deterministic function of time, or a unit root process....

This paper studies panel data models with interactive fixed effects where the regressors are allowed to be correlated with the idiosyncratic error terms. We propose a two-step profile GMM estimation procedure to estimate the parameters of interest. In the first step we obtain a preliminary...