This event features a paper presentation by Massimiliano Marcellino (Bocconi University) and Fabio Canova (Norwegian Business School).
'Firm heterogeneity and aggregate fluctuations: a functional VAR model for multidimensional distributions'.
Abstract:
We develop a functional augmented vector autoregression (FunVAR) model to explicitly incorporate firm-level heterogeneity observed in more than one dimension and study its interaction with aggregate macroeconomic fluctuations. Our methodology employs dimensionality reduction techniques for tensor data objects to approximate the joint distribution of firm-level characteristics. More broadly, our framework can be used for assessing predictions from structural models that account for micro-level heterogeneity observed on multiple dimensions. Leveraging firm-level data from the compustat database, we use the FunVAR model to analyse the propagation of total factor productivity (TFP) shocks and monetary policy shocks on the US macroeconomy, examining their impact on both macroeconomic aggregates and the cross-sectional distribution of capital and labor across firms. Then, we use the proposed framework to identify cross-sectional uncertainty shocks and evaluate their effects on aggregate macroeconomic fluctuations.
Author: Massimiliano Marcellino (Bocconi University).
Co-authors: Andrea Renzetti (Bank of England), and Tommaso Tornese (Università del Sacro Cuore Milano).
'Low frequency movements and VAR analyses'.
Abstract:
We study the consequences of using a deterministic steady state in Vector Autoregressive (VAR) models, when the data is potentially characterised by structural breaks, transitional dynamics or significant low-frequency fluctuations. We show the presence of upward biases in the estimated coefficients. We analyse how these biases interact with the identification scheme. We propose an alternative setup that allows the steady states to be stochastic and show that distortions are reduced. We revisit the technology shocks-hours link and show that when low-frequency movements are taken into account, hours significantly fall in response to technological improvements.
Author: Fabio Canova (BI Norvegian Business School)
Co-author: Luca Fosso, European Central Bank.