European Central Bank

The propagation of shocks across the production network and implications for monetary policy

The repeated occurrence of supply-chain disruptions since the COVID-19 pandemic reveals the need to complement traditional macroeconomic frameworks with approaches that better capture the complexity of modern economic productionstructures. This paper synthesises the findings of the ChaMP Research Network, highlighting how production network models and heterogeneity across firms, sectors and countries enrich our understanding of monetary policy transmission.

Monetary policy transmission through the financial system to households

This Occasional Paper reviews evidence from the ChaMP Research Network on the transmission of monetary policy to households in the euro area – an area of monetary policy that has attracted less attention among researchers. It highlights thecentral role of banks and non-bank intermediaries in shaping how policy affects borrowing, saving and consumption.

Monetary policy transmission and non-bank financial intermediation

The growing importance of non‑bank financial intermediaries (NBFIs) also has important implications for the transmission of monetary policy in the euro area. It alters the composition of credit supply and strengthens the role of market‑based finance for the corporate sector. In the aggregate, NBFIs tend to amplify the transmission of monetary policy within the financial sector. In particular, intermediaries with uninsured short‑term funding amplify monetary transmission to credit.

Monetary policy under multiple financing constraints

The fact that monetary policy tightening has stronger effects than easing is a longstanding puzzle in monetary economics. This article studies monetary transmission in settings where firms face multiple financing constraints – a common and well-documented feature of corporate financing. Our theory shows that the multiplicity of financing constraints notably dampens the transmission of expansionary policy to firm borrowing and investment, while amplifying the transmission of policy tightening.

Firm level heterogeneity and the impact of monetary policy on labour demand

Monetary policy asymmetrically affects the response of firms’ employment to an output shock and plays a role in cushioning employment adjustment over the business cycle. Combining annual firm-level data until 2020 with quarterly firm-level data until 2023 and high-frequency monetary policy surprises, we show that for a given change in output, monetary policy influences the extent to which firms hold on to labour, or “labour hoard”.

Identifying relationship-level effects using covariance restrictions

We propose a new model in which relationship-specific effects or shocks are identified in a bipartite network under mild covariance restrictions, generalizing the influential Abowd et al. (1999) framework. For example, separate demand shocks are identified for each bank from which a firm borrows. We show how previous approaches break down when confronted with such heterogeneity, while our novel identification strategy yields a simple estimator that is consistent and asymptotically normal, under weaker network density assumptions than previous approaches.

Stockholding in Europe: Evidence from the Consumer Expectations Survey

We examine recent changes in stock market participation using newly available survey data from eleven euro area countries over the period 2020–2024. The evidence points to substantial turnover, with around 10% of non-stockholders entering the market each year, and more than 20% of stockholders exiting. New entrants tend to have lower education, income, financial literacy, and risk tolerance than established investors, indicating a shift in the composition of market participants. We also highlight the growing importance of cryptocurrency investments among retail investors.

Sequential solution for DSGE models with deep neural networks

This paper develops a sequential deep learning algorithm for solving dynamic stochastic general equilibrium (DSGE) models. The algorithm trains a deep neural network to approximate the model’s policy functions across four progressive phases: steady-state anchoring, exploration around the steady state, simulation on the ergodic set, and Monte Carlo integration of stochastic expectations.

Employment effects of EU-ETS prices

This paper studies the employment effects of carbon pricing under the European Union’s Emissions Trading System (EU-ETS). I refer to standard methods from the literature to define and measure the environmental properties of jobs along two dimensions: how “green” a job is, and how polluting it is. I then leverage a series of shocks to EU-ETS prices to estimate their dynamic impacts on employment. The panel local projections estimates reveal that an exogenous 1% increase in EU-ETS prices leads to a roughly 0.2% decline in employment after one and a half years.

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