Published Papers

In this paper, we propose a methodology to assess the structural drivers of inflation expectations, as measured by inflation-linked swaps. To this end, we estimate a Bayesian Vector Autoregressive (BVAR) model for the euro area (EA) and the United States (US) on daily asset price movements in the two economies. Shocks are identified using sign and magnitude restrictions, taking also into account international spillovers. The inclusion of inflation expectations allows to neatly differentiate between supply and demand innovations. The results suggest that over the course of 2021–23​ inflation expectations in the US were steadily sustained by domestic demand, while in the EA they mostly reflected the role of supply shocks, and only more recently a growing strength of demand factors. Our evidence also indicates that monetary policy shocks progressively contributed in soothing inflation expectations in both jurisdictions, although with a different timing and vigour.

(Econbrowser, WP version, SUERF Policy Brief)

Working Papers

This paper analyzes the role of changes in the structure of production networks on the flattening of the Phillips curve over the last decades. I build a multi-sector model with production networks, and heterogeneity in input-output linkages and in degree of nominal rigidities. In the production network model, inflation sensitivity to the output gap depends on the topology of the network of the economy. In particular, I show that two characteristics of the network matter for inflation dynamics: (i) the network multiplier and (ii) output shares. Analyzing the U.S. Input-Output structure from 1963 to 2017, I document  structural changes in the production network. Calibrating the model to these sectoral changes can account for a decrease in the slope of up to 15 percent. Decomposing the aggregate effect shows that the flattening is primarily due to an increase in the centrality of sectors with more rigid prices that is incompletely reflected by compositional changes in value-added.

Firms' market power, measured by markups, has risen substantially and unequally across sectors in the United States. This paper studies the implications of these trends for monetary non-neutrality. Particularly, we emphasize an increasing and concave relationship between market power and nominal rigidities. A quantitative menu cost model shows that the rising markup has led to a 30% increase in the degree of monetary non-neutrality. Moreover,  the degree of monetary non-neutrality would have increased by 42% had the markup increased equally across sectors. We provide empirical evidence to support the model mechanisms and predictions and to differentiate the proposed mechanisms from existing ones. 

Technology improvements are commonly believed to be disinflationary. This paper argues that this view may not be warranted, showing that the response of aggregate inflation to a technology shock may change sign depending on the sectoral origin of the shock. We start by establishing this result analytically in a tractable production-network economy where sectors differ in their degree of price rigidity and position in the network. We show that the response of aggregate inflation to a favorable technology shock is increasing in the price rigidity of the shocked sector. More importantly, this response may actually turn positive if the shock originates in a sector with a sufficiently higher-than-average degree of price rigidity. This condition holds to the extent that monetary policy reacts to the output gap, and is weaker when the shocked sector is located downstream in the supply chain. We validate these predictions in the context of highly disaggregated multi-sector model, which we calibrate to the U.S. economy. The model implies that aggregate inflation rises when the underlying technology shock originates in 18 (out of 60) industries. Finally, we provide empirical evidence supporting the predicted relationship between sectoral price rigidity and the response of aggregate inflation to sector-specific technology shocks using a panel of U.S. manufacturing industries