We approximate the finite-sample distribution of impulse response function (IRF) estimators that are just-identified with a weak instrument using the conventional local-to-zero asymptotic framework. Since the distribution lacks a mean, we assess bias using the mode and conclude that researchers...

Directed acyclic graphs (DAGs) provide a transparent framework for encoding causal structures and identifying causal effects. This paper demonstrates how DAGs help specify local projections (LPs) for estimating causal impulse responses. Examples illustrate how graphical rules can be used to...

This paper studies the macroeconomic effects of global copper supply shocks. We identify exogenous disruptions to copper supply using a Bayesian structural VAR of the world copper market that combines sign and narrative restrictions. We then trace the international transmission of the identified...

Unlike past high-inflation episodes, the euro area labour market remained surprisingly resilient during the inflation surge of the early 2020s. This paper investigates the drivers of this resilience by combining long-span euro area macroeconomic data (1970-2025) with a structural VAR analysis...

We investigate the impact of structural shocks on the joint distribution of future real GDP growth and inflation in the euro area. We model the conditional mean of these variables, along with selected financial indicators, using a VAR and perform quantile regressions on the VAR residuals to...

We examine the state dependence of monetary policy transmission and the parameters of the Phillips curve, dynamic IS equation, and Taylor rule across four regimes defined by joint deviations of inflation from the Federal Reserve's target and output from potential. The analysis uncovers important...

This study examines the systemic operational risk in Morocco's banking sector using a Panel VAR model based on data from three banks over ten years. The model includes real GDP, interbank rate (TMP), and bank credit, alongside indicators of operational, credit, and liquidity risks. The Impulse...

This paper develops a novel empirical framework to analyse the drivers of business expectations in the euro area. Using harmonised data from the European Commission's business surveys for manufacturing, services, and construction, we build composite business expectations indices (BEI) for...

We design a Bayesian Mixed-Frequency vector autoregression (VAR) model for fiscal monitoring, i.e., to nowcast the government deficit-to-GDP ratio in real time and provide a narrative for its dynamics. The model incorporates both monthly cash and quarterly accrual fiscal indicators, together...

In recent years, because of the 2008 financial crisis and the evolution of the sovereign debt markets, there has been a significant increase in interest in understanding the factors that determine the risk premium, becoming a key indicator of the financial stability of countries, and a measure...

This research aims to explain the role of food processing in improving the sustainability of food security under the framework of 'Goal 2' associated with the Sustainable Development Goals (SDGs). The research methodology relied on descriptive and quantitative analysis methods, where the VAR...

Interest in empirical studies of monetary policy has grown over the past decade, and particularly since the post COVID-19 pandemic period characterized by a surge in inflation rates in every corner of the globe. Against this backdrop, central banks' traditional inflation forecast framework has...

This paper investigates the macroeconomic impacts of structural oil price shocks by employing a Global Vector Autoregression (GVAR) framework, utilizing the structural shocks as identified by Baumeister and Hamilton (2019). Our analysis differentiates among three types of oil shocks: economic...

This study focusses on the transmission of carbon pricing mechanisms in shaping trade dynamics between the Eurozone and key partners: the USA and China. Using Bayesian variable selection methods and a Time-Varying Structural Vector Autoregressions (TV-SVAR) model, the research identifies the key...