I am a senior economist at the Central Bank of Malta's Research Department. I was previously working as an economist at the European Central Bank, and as a macroeconomic researcher at the Rokos' hedge fund in London.
My research interests include monetary policy, time-series econometrics, and forecasting. I am also involved in understanding the effects of monetary policy surprises on financial assets. In the last years, I have extensively worked on this topic using high-frequency data.View my CV
Ph.D. in Economics, 2013-2018
University of Rome Tor Vergata
Visiting Ph.D. Student, 2015
University College London (UCL)
Graduate Programme, 2013-2014
Einaudi Institute for Economics and Finance (EIEF)
M.Sc. in Economics, 2011-2013
University of Rome Tor Vergata
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 rate decision announcement and the window that contains the press conference. We also show that the QE-related policy factor has been dominant in the recent period and that its effects have been very persistent on the long-end of the yield curve, with a half-life nearing two years. To carry out the analysis, we construct and describe the euro area Monetary Policy Event-Study Database. This database, which contains both daily and intraday asset price changes around the rate decision announcements as well as around press conferences, is a contribution on its own right and we expect it to be the standard in monetary policy research for the euro area.
I compare the performance of the VAR impulse response function (IRF) estimator with the Jordà (2005) local projection (LP) methodology. I show by a Monte Carlo exercise that when the data generating process (DGP) is a well-specified vector autoregressive model (VAR), the standard estimator is a better alternative. However, in the general case in which the sample size is small, and the lag length of the model is misspecified, the local projection estimator is a competitive alternative to the standard VAR impulse response function estimator. Along the way, I highlight some lack in the local projection literature, which can lead to potential improvement in the estimation procedure.
We analyse the macroeconomic effects of a debt consolidation policy in the Euro Area mimicking the Fiscal Compact Rule (FCR). The rule requires the signatory states to target a debt-to-GDP ratio below 60%. Within the context of Dynamic Stochastic General Equilibrium models (DSGE), we augment a fully micro-founded New-Keynesian model with a parametric linear debt consolidation rule, and we analyse the effects on the main macroeconomic aggregates. To fully understand its implications on the economy, we study different debt consolidation scenarios, allowing the excess debt to be re-absorbed with different timings. We show that including a debt consolidation rule can exacerbate the effects of the shocks in the economy by imposing a constraint on the public debt process. Secondly, we note that the effect of loosening or tightening the rule in response to a shock is heterogeneous. Shocks hitting nominal variables (monetary policy shock) are not particularly sensitive. On the contrary, we prove that the same change has a more pronounced effect in case of shock hitting real variables (productivity and public spending shocks). Finally, we show that the macroeconomic framework worsens as a function of the rigidity of the debt consolidation rule. As a limiting case, we show that the effects on output, employment, real wages, inflation, and interest rates are sizable.
I assess and forecast the probability of deflation in the EA at different horizons using a binomial probit model. I select the best predictors among more than one-hundred variables adopting a two-step combinatoric approach and exploiting parallel computation in Julia language. I show that the best-selected variables coincide to those standardly included in a small New Keynesian model. Also, I assess the goodness of the models using three different loss functions: the Mean Absolute Error (MAE), the Root Mean Squared Error (RMSE) and the Area Under the Receiver Operating Characteristics (AUROC). The results are reasonably consistent among the three criteria. Finally, I compute an index averaging the forecast to assess the probability of being in a deflation state in the next two years. The index shows that having inflation above the 2% level before March 2019 is extremely unlikely.