Danilo Leiva-Leon

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Staff Working Papers

Monetary Policy Independence and the Strength of the Global Financial Cycle

Staff Working Paper 2020-25 Christian Friedrich, Pierre Guérin, Danilo Leiva-Leon
We propose a new strength measure of the global financial cycle by estimating a regime-switching factor model on cross-border equity flows for 61 countries. We then assess how the strength of the global financial cycle affects monetary policy independence, which is defined as the response of central banks' policy interest rates to exogenous changes in inflation.

Endogenous Time Variation in Vector Autoregressions

Staff Working Paper 2020-16 Danilo Leiva-Leon, Luis Uzeda
We introduce a new class of time-varying parameter vector autoregressions (TVP-VARs) where the identified structural innovations are allowed to influence — contemporaneously and with a lag — the dynamics of the intercept and autoregressive coefficients in these models.

Markov‐Switching Three‐Pass Regression Filter

We introduce a new approach for the estimation of high-dimensional factor models with regime-switching factor loadings by extending the linear three-pass regression filter to settings where parameters can vary according to Markov processes.
Content Type(s): Staff Research, Staff Working Papers Topic(s): Econometric and statistical methods JEL Code(s): C, C2, C22, C23, C5, C53

Model Averaging in Markov-Switching Models: Predicting National Recessions with Regional Data

Staff Working Paper 2015-24 Pierre Guérin, Danilo Leiva-Leon
This paper introduces new weighting schemes for model averaging when one is interested in combining discrete forecasts from competing Markov-switching models. In particular, we extend two existing classes of combination schemes – Bayesian (static) model averaging and dynamic model averaging – so as to explicitly reflect the objective of forecasting a discrete outcome.

The Propagation of Industrial Business Cycles

Staff Working Paper 2014-48 Maximo Camacho, Danilo Leiva-Leon
This paper examines the business cycle linkages that propagate industry-specific business cycle shocks throughout the economy in a way that (sometimes) generates aggregated cycles. The transmission of sectoral business cycles is modelled through a multivariate Markov-switching model, which is estimated by Gibbs sampling.

Real-Time Nowcasting of Nominal GDP Under Structural Breaks

Staff Working Paper 2014-39 William A. Barnett, Marcelle Chauvet, Danilo Leiva-Leon
This paper provides a framework for the early assessment of current U.S. nominal GDP growth, which has been considered a potential new monetary policy target. The nowcasts are computed using the exact amount of information that policy-makers have available at the time predictions are made. However, real-time information arrives at different frequencies and asynchronously, which poses challenges of mixed frequencies, missing data and ragged edges.

A New Approach to Infer Changes in the Synchronization of Business Cycle Phases

Staff Working Paper 2014-38 Danilo Leiva-Leon
This paper proposes a Markov-switching framework to endogenously identify the following: (1) regimes where economies synchronously enter recessionary and expansionary phases; and (2) regimes where economies are unsynchronized, essentially following independent business cycles.

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