Sofia Velasco - Research

Publications

Macro-financial imbalances and cyclical systemic risk dynamics: understanding the factors driving the financial cycle in the presence of non-linearities

Macroeconomic Dynamics, April 2024, Research Technical paper Vol. 2020 No.9, Central Bank of Ireland , with Martin O'Brien

This paper develops a multivariate filter based on an unobserved component model to estimate the financial cycle. Our model features: (1) a dynamic relationship between the financial cycle and key variables; (2) time-varying shock volatility for trend and cycle components. We demonstrate that our approach not only exhibits superior early warning properties for banking crises but also outperforms commonly used indicators in terms of data fit for decomposition exercises, as evidenced by the higher marginal likelihood. We document three important properties of the financial cycle. First, the sensitivity of the financial cycle to changes in real estate valuations increased during the post-90s period. Second, the sensitivity of the cycle to changes in financial conditions displays volatility and country specificities. Finally, our reduced form estimates suggest that the banking crisis of 1988 was preceded by positive contributions from the risk appetite shock, while the primary source of vulnerabilities emanated from the housing market in the run-up to the Global Financial Crisis.

Working Papers

Modern Monetary Analysis

CEPR Discussion Paper DP20182, April 2025, with Ramon Adalid, Alessandro Ferrari, Andrew Hannon and Philip Lane

The role of monetary analysis at the ECB has evolved over the past several decades, expanding from a narrow focus on the quantity of money towards a comprehensive assessment of monetary policy transmission and the credit creation process. This natural evolution was driven by the vulnerabilities of the transmission mechanism unveiled by the global financial crisis and the sovereign debt crisis, along with the need to better understand the new transmission channels set in motion by unconventional monetary policy. The move has also been facilitated by the increased availability of granular data and a parallel expansion in computation capacity. For these reasons, monetary analysis plays a central role at a central bank like the ECB which, as part of a data-dependent approach, has monetary policy transmission as a key element of its reaction function. We illustrate this role by discussing how monetary analysis contributed to the assessment of financing conditions during the pandemic, how it informed the diagnosis of the 2021-2022 surges in inflation, and how it contributed to the calibration of the tightening cycle. Finally, we explore some of the challenges that monetary analysis may face in the years to come.

Asymmetries in the transmission of monetary policy shocks over the business cycle: A Bayesian Quantile Factor Augmented VAR

This paper introduces a Bayesian Quantile Factor Augmented VAR (BQFAVAR) to examine the asymmetric effects of monetary policy throughout the business cycle. Monte Carlo experiments demonstrate that the model effectively captures non-linearities in impulse responses. Analysis of aggregate responses to a contractionary monetary policy shock reveals that financial variables and industrial production exhibit more pronounced impacts during recessions compared to expansions, aligning with predictions from the 'financial accelerator' propagation mechanism literature. Additionally, inflation displays a higher level of symmetry across economic conditions, consistent with households' loss aversion in the context of reference-dependent preferences and central banks' commitment to maintaining price stability. The examination of price rigidities at a granular level, employing sectoral prices and quantities, demonstrates that during recessions, the contractionary policy shock results in a more pronounced negative impact on quantities compared to expansions. This finding provides support for the notion of stronger downward than upward price rigidity, as suggested by 'menu-costs models'.

BEAST: A model for the assessment of system-wide risks and macroprudential policies

ECB Working Paper No. 2855, October 2013, with Katarzyna Budnik, Johannes Gross, Gianluca Vagliano, Ivan Dimitrov, Max Lampe, Jiri Panos, Louis Boucherie and Martina Jancokova

The Banking Euro Area Stress Test (BEAST) is a large-scale semi-structural model developed to analyse the euro area banking system from a macroprudential perspective. The model combines the dynamics of approximately 90 of the largest euro area banks with those of individual euro area economies. It reflects the heterogeneity of banks by replicating the structure of their balance sheets and profit and loss accounts. Additionally, it allows banks to adjust their assets, funding mix, pricing decisions, management buffers, and profit distribution along with individual bank conditions, including their capital and liquidity requirements, and other supervisory limits. The responses of banks impact credit supply conditions and have feedback effects on the macroeconomic environment. Stochastic solutions of the model provide a solid foundation for investigating multiple scenarios, deriving at-risk measures, and estimating model uncertainty.

The benefits and costs of adjusting bank capitalisation: evidence from euro area countries

ECB Working Paper No. 2261, April 2019, with Katarzyna Budnik et. al

The paper proposes a framework for assessing the impact of system-wide and bank-level capital buffers. The assessment rests on a factor-augmented vector autoregression (FAVAR) model that relates individual bank adjustments to macroeconomic dynamics. We estimate FAVAR models individually for eleven euro area economies and identify structural shocks, which allow us to diagnose key vulnerabilities of national banking systems and estimate short-run economic costs of increasing banks’ capitalisation.