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Firm Heterogeneity and Macroeconomic Fluctuations: a Functional VAR model

Massimiliano Marcellino, Andrea Renzetti, Tommaso Tornese

arXiv 8 Nov 2024 · Econometrics

arXiv:2411.05695 · PDF · DOI · OpenAlex · Extracted main text

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 analyze the propagation of total factor productivity (TFP) shocks, examining their impact on both macroeconomic aggregates and the cross-sectional distribution of capital and labor across firms.

Citation extraction

36
references
49
in-text mentions
36
distinct cited
2
self-citations
8,823
main-text words

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Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Winberry, Thomas (2018) A method for solving and estimating heterogeneous agent macro models0.87462100%
2Chang, Minsu, Chen, Xiaohong, Schorfheide, Frank (2021) Heterogeneity and aggregate fluctuations0.73732100%
3Fernald, John (2014) A quarterly, utilization-adjusted series on total factor productivity0.58531100%
4Ottonello, Pablo, Winberry, Thomas (2020) Financial Heterogeneity and the Investment Channel of Monetary Policy0.5112250%
5Carroll, J. D., Chang, J.-J (1970) Analysis of individual differences in multidimensional scaling via an N-way generalization of "Eckart-Young" decomposition0.51121100%
6Harshman, Richard A (1970) Foundations of the PARAFAC procedure: Models and conditions for an "explanatory" multi-modal factor analysis0.51121100%
7Hung, Hung, Wu, Peishein, Tu, Iping, Huang, Suyan (2012) On multilinear principal component analysis of order-two tensors0.51121100%
8Carriero, A., Kapetanios, G., Marcellino, M (2009) Forecasting exchange rates with a large Bayesian VAR self0.40511100%
9Chan, Joshua C.C., Poon, Aubrey, Zhu, Dan (2023) High-dimensional conditionally Gaussian state space models with missing data0.40511100%
10Doz, Catherine, Giannone, Domenico, Reichlin, Lucrezia (2011) A two-step estimator for large approximate dynamic factor models based on Kalman filtering0.40511100%

Showing the top 10 of 36 scored citations.