We use decision theory to confront uncertainty that is sufficiently broad to incorporate “models as approximations.” We presume the existence of a featured collection of what we call “structured models” that have explicit substantive motivations. The decision maker confronts uncertainty...

We derive analytic formulae which link $\alpha$, $\nu$ and $\rho$ parameters in Andreasen-Huge style SABR model to the ATM price and option prices at four strikes close to ATM. Based on these formulae we give a characterisation for the SABR parameters in terms of derivatives of the swap rate...

This paper considers the identification and estimation of hedonic models. We establish that in an additive version of the hedonic model, technology and preferences are generically identified up to affine transformations from data on demand and supply in a single hedonic market. For a very...

In this article we are going to review the modelling of NMDs via replicating portfolios due to the revived interest in NMDs in the context of the interest rate risk of the banking book (IRRBB). The main goal is to provide a self contained presentation of the replicating portfolio approach from...

We propose simple mathematical models for the legal concept of balancing of interests, to resolve the conflict between the rights to privacy and to the protection of personal data in Art. 7 and Art. 8 of the EU Charter of Fundamental Rights (EUCh) against the right of access to information...

This paper explores ways to integrate model uncertainty into policy evaluation. We first describe a general framework for the incorporation of model uncertainty into standard econometric calculations. This framework employs Bayesian model averaging methods that have begun to appear in a range of...

This paper seeks to contribute to discussion of the reasonableness of sometimes seemingly innocent assumptions used in theoretical trade models that the direction of trade is both predetermined for each good for each country and fixed. Here, we provide computational evidence as to the...

This paper presents a way of estimating how accurate VAR models are likely to be for answering structural questions. Data are generated from a dynamic deterministic solution of a structural model; a VAR model is estimated using a subset of these data; and the properties of the VAR model are...

It is common in empirical research to use what appear to be sensible rules of thumb for cleaning data. Measurement error is often the justification for removing (trimming) or recoding (winsorizing) observations whose values lie outside a specified range. This paper considers identification in a...

The authors show that in weakly identified models (1) the posterior mode will not be a consistent estimator of the true parameter vector, (2) the posterior distribution will not be Gaussian even asymptotically, and (3) Bayesian credible sets and frequentist confidence sets will not coincide...