We propose two novel methods to "bring ABMs to the data". First, we put forward a new Bayesian procedure to estimate the numerical values of ABM parameters that takes into account the time structure of simulated and observed time series. Second, we propose a method to forecast aggregate time...

We provide a critique of the standard methodology which bases welfare comparisons between households on deflating household income and consumption by an equivalence scale. We argue that this leads to support for tax/transfer policies that significantly disadvantage low to middle in-come...

We present a general framework for Bayesian estimation and causality assessment in epidemiological models. The key to our approach is the use of sequential Monte Carlo methods to evaluate the likelihood of a generic epidemiological model. Once we have the likelihood, we specify priors and rely...

We examine how financial crises redistribute risk, employing novel empirical methods and micro data from the largest financial crisis of the 20th century – the Great Depression. Using balance-sheet and systemic risk measures at the bank level, we build an econometric model with incidental...

This paper investigates the robustness of determinants of economic growth in the presence of model uncertainty, parameter heterogeneity and outliers. The robust model averaging approach introduced in the paper uses a flexible and parsimonious mixture modeling that allows for fat-tailed errors...

We study the information flow from the ECB on policy dates since its inception, using tick data. We show that three factors capture about all of the variation in the yield curve but that these are different factors with different variance shares in the window that contains the policy decision...

This study is the first scientific attempt to calculate the size of the informal economy in agriculture. The Multiple indicators multiple causes model (MIMIC) was developed for the estimation of levels of informal economy in 15 “Old” European Union Member States’ agricultural sectors for...

Why do cities differ so much in productivity? We document that most of the measured dispersion in productivity across US cities is spurious and reflects granularity bias: idiosyncratic heterogeneity in plant-level productivity and size, combined with finite plant counts. As a result, economies...