Central banks

A statistical approach to identifying ECB monetary policy

10/23/2024 European Central Bank Central banks

We construct monetary policy indicators from high-frequency asset price changes following policy announcements, emphasising the concentration of asset price responses along specific dimensions and their leptokurtic distribution. Traditionally, these dimensions are identified by rotating principal components based on economic assumptions that overlook information in excess kurtosis. We employ Varimax rotation, leveraging excess kurtosis without using economic restrictions.

Heterogeneous effects of monetary tightening in response to energy price shocks

10/23/2024 European Central Bank Central banks

This article analyses how monetary policy shapes the aggregate and distributional effects of an energy price shock. Based on the observed heterogeneity in consumption exposures to energy and household wealth, we build a quantitative small open-economy Heterogeneous Agent New Keynesian (HANK) model that matches salient features of the euro area data. The model incorporates energy as both a consumption good for households with non-homothetic preferences as well as a factor input into production with input complementarities.

Government-guaranteed credit and populism

10/22/2024 European Central Bank Central banks

The phenomenon of political populism and its financial determinants have proved elusive. We utilise the sudden and uneven change in credit conditions during the COVID-19 pandemic and the unprecedented government credit guarantee programme in France to investigate whether liquidity support to firms affects political preferences. Drawing on credit registry data – which provides the universe of loans and credit lines to firms – we build a postcode-municipality-level dataset and show that government-guaranteed credit reduced the support for the far right but increased it for the incumbent.

Government-guaranteed credit and populism

10/22/2024 European Central Bank Central banks

The phenomenon of political populism and its financial determinants have proved elusive. We utilise the sudden and uneven change in credit conditions during the COVID-19 pandemic and the unprecedented government credit guarantee programme in France to investigate whether liquidity support to firms affects political preferences. Drawing on credit registry data – which provides the universe of loans and credit lines to firms – we build a postcode-municipality-level dataset and show that government-guaranteed credit reduced the support for the far right but increased it for the incumbent.

Using structural models to understand macroeconomic tail risks

10/21/2024 European Central Bank Central banks

Understanding asymmetric risks in macroeconomic variables is challenging. Most structural models used for policy analysis are linearised and therefore cannot generate asymmetries such as those documented in the empirical growth-at-risk (GaR) literature. This report examines how structural models can incorporate non-linearities to generate tail risks. The first part reviews the various extensions to dynamic stochastic general equilibrium (DSGE) models and the computational challenges involved in accounting for risk distributions.

Inputs in distress: geoeconomic fragmentation and firms’ sourcing

10/21/2024 European Central Bank Central banks

We study how disruptions to the supply of foreign critical inputs (FCIs) —that is, inputs primarily sourced from extra-EU countries with highly concentrated supply, advanced technology products, or which are key to the green transition —might affect value added at different levels of aggregation. Using firm-level customs and balance sheet data for Belgium, France, Italy, Slovenia and Spain, our framework allows us to assess how much geoeconomic fragmentation might affect European economies differently.

Variational inference for Bayesian panel VAR models

10/21/2024 European Central Bank Central banks

We study the application of approximate mean field variational inference algorithms to Bayesian panel VAR models in which an exchangeable prior is placed on the dynamic parameters and the residuals follow either a Gaussian or a Student-t distribution. This reduces the estimation time of possibly several hours using conventional MCMC methods to less than a minute using variational inference algorithms. Next to considerable speed improvements, our results show that the approximations accurately capture the dynamic effects of macroeconomic shocks as well as overall parameter uncertainty.

Inputs in distress: geoeconomic fragmentation and firms’ sourcing

10/21/2024 European Central Bank Central banks

We study how disruptions to the supply of foreign critical inputs (FCIs) —that is, inputs primarily sourced from extra-EU countries with highly concentrated supply, advanced technology products, or which are key to the green transition —might affect value added at different levels of aggregation. Using firm-level customs and balance sheet data for Belgium, France, Italy, Slovenia and Spain, our framework allows us to assess how much geoeconomic fragmentation might affect European economies differently.

Variational inference for Bayesian panel VAR models

10/21/2024 European Central Bank Central banks

We study the application of approximate mean field variational inference algorithms to Bayesian panel VAR models in which an exchangeable prior is placed on the dynamic parameters and the residuals follow either a Gaussian or a Student-t distribution. This reduces the estimation time of possibly several hours using conventional MCMC methods to less than a minute using variational inference algorithms. Next to considerable speed improvements, our results show that the approximations accurately capture the dynamic effects of macroeconomic shocks as well as overall parameter uncertainty.

Climate capitalists

10/18/2024 European Central Bank Central banks

Firms’ perceived cost of green capital has decreased since the rise of sustainable investing. Green and brown firms perceived their cost of capital to be the same before 2016, but after the post-2016 surge in sustainable investing, green firms perceived their cost of capital to be on average 1 percentage point lower. This difference has widened as sustainable investing has intensified. Within some of the largest energy and utility firms, managers have started applying a lower cost of capital to greener divisions.

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