This paper shows that there is a natural trade-off when designing market-based executive compensation. The benefit of market-based pay is that the stock price aggregates speculators' dispersed information and therefore takes a picture of managerial performance before the long-term value of a...

Given the increased importance of fiscal monitoring, this study amends the existing literature in the field of intra-annual fi scal data in two main dimensions. First, we use quarterly fi scal data to forecast a very disaggregated set of fiscal series at annual frequency. This makes the analysis...

In this paper we develop a general framework to analyze state space models with time-varying system matrices where time variation is driven by the score of the conditional likelihood. We derive a new filter that allows for the simultaneous estimation of the state vector and of the time-varying...

We explore the impact of wage adjustment on employment with a focus on the role of downward nominal wage rigidities. We use a harmonised survey dataset, which covers 25 European countries in the period 2010-2013. These data are particularly useful for this paper given the firm-level information...

Monitoring economic conditions in real time, or nowcasting, is among the key tasks routinely performed by economists. Nowcasting entails some key challenges, which also characterise modern Big Data analytics, often referred to as the three \Vs": the large number of time series continuously...

Based on long US time series we document a range of empirical properties of the labor's share of GDP, including its substantial medium-run swings. We explore the extent to which these empirical regularities can be explained by a calibrated micro-founded long-run economic growth model with...

We document the impact of COVID-19 on frequently employed time series models, with a focus on euro area inflation. We show that for both single equation models (Phillips curves) and Vector Autoregressions (VARs) estimated parameters change notably with the pandemic. In a VAR, allowing the errors...

This paper develops Bayesian econometric methods for posterior inference in non-parametric mixed frequency VARs using additive regression trees. We argue that regression tree models are ideally suited for macroeconomic nowcasting in the face of extreme observations, for instance those produced...

This paper builds an unobserved components model that combines a multivariate filter approach with a Cobb-Douglas production function. This combination allows potential output estimates to incorporate more economic structure than the traditional production function approach, while retaining the...

In a globalised world economy, global factors have become increasingly important to explain trade flows at the expense of country-specific determinants. This paper shows empirically the superiority of direct forecasting methods, in which world trade is directly forecasted at the aggregate...