We emphasize using our solutions to the problems of omitted variables, measurement errors, and unknown functional forms to improve model specification, and to estimate the mean square error of an empirical best linear unbiased predictor of an individual drawing of the dependent variable of an...

Topographic finance is the study of surfaces to describe financial systems in multiple dimensions. The problem with finance and economics is to describe accurately what is actually governing price dynamics. The price dynamics are behavioral and do not exhibit a rational maximization of a utility...

We introduce machine learning in the context of central banking and policy analyses. Our aim is to give an overview broad enough to allow the reader to place machine learning within the wider range of statistical modelling and computational analyses, and provide an idea of its scope and...

In this paper we propose an algorithm for the solution of optimalcontrol problems with nonlinear models based on a generalised Gauss-Newton algorithm but making use of analytic model derivatives. Themethod is implemented in WinSolve, a general nonlinear model solution program

BayVAR_R is an R package designed to estimate and analyze Vec-tor Autoregressive (VAR) models from both a classical (UVAR) andBayesian (BVAR) perspective. The package includes functionalities forthe speci cation, estimation and diagnosis of such a models. It alsoprovides procedures for...

Covariates in regressions may be linked to each other on a network. Knowledge of the network structure can be incorporated into regularized regression settings via a network penalty term. However, when it is unknown whether the connection signs in the network are positive (connected covariates...

Many experimental research designs offer participants the opportunity to chat with each other. While experimental research has traditionally treated text as process data, this paper proposes a novel approach to interpret and use chat data in a structured supervised classification task....

Linear panel models and the "event-study plots" that often accompany them are popular tools for learning about policy effects. In this paper, we introduce the "xtevent" package for Stata, which enables the construction of event-study plots following the suggestions in Freyaldenhoven et al....

Linear panel models and the "event-study plots" that often accompany them are popular tools for learning about policy effects. In this paper, we introduce the "xtevent" package for Stata, which enables the construction of event-study plots following the suggestions in Freyaldenhoven et al....

Macroeconomic practitioners frequently work with multivariate time series models such as VARs, factor augmented VARs as well as time-varying parameter versions of these models (including variants with multivariate stochastic volatility). These models have a large number of parameters and, thus,...