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Functional Linear Projection and Impulse Response Analysis

Won-Ki Seo, Dakyung Seong

arXiv 11 Mar 2025 · Econometrics

arXiv:2503.08364 · PDF · DOI · OpenAlex · Extracted main text

Abstract

This paper proposes econometric methods for studying how economic variables respond to function-valued shocks. Our methods are developed based on linear projection estimation of predictive regression models with a function-valued predictor and other control variables. We show that the linear projection coefficient associated with the functional variable allows for the impulse response interpretation in a functional structural vector autoregressive model under a certain identification scheme, similar to well-known Sims' (1972) causal chain, but with nontrivial complications in our functional setup. A novel estimator based on an operator Schur complement is proposed and its asymptotic properties are studied. We illustrate its empirical applicability with two examples involving functional variables: economy sentiment distributions and functional monetary policy shocks.

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44
references
215
in-text mentions
91
distinct cited
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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
1Inoue, A. and B. Rossi (2021) A new approach to measuring economic policy shocks, with an application to conventional and unconventional monetary policy1.000234100%
2Jordà, O (2005) Estimation and inference of impulse responses by local projections1.000103100%
3Shin, H (2009) Partial functional linear regression1.00084100%
4Barbaglia, L., S. Consoli, and S. Manzan (2023) Forecasting with economic news1.00083100%
5Mas, A (2007) Weak convergence in the functional autoregressive model0.8434375%
6Plagborg-Møller, M. and C. K. Wolf (2021) Local projections and VARs estimate the same impulse responses0.84333100%
7Hall, P. and J. L. Horowitz (2007) Methodology and convergence rates for functional linear regression0.81142100%
8Sims, C. A (1972) Money, income, and causality0.81142100%
9Florens, J.-P. and S. Van Bellegem (2015) Instrumental variable estimation in functional linear models0.7374275%
10Aneiros-Pérez, G. and P. Vieu (2006) Semi-functional partial linear regression0.73732100%

Showing the top 10 of 91 scored citations.