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Impulse Response Analysis of Structural Nonlinear Time Series Models

Giovanni Ballarin

arXiv 30 May 2023 · Econometrics · publishedThe Review of Economics and Statistics (2026)

arXiv:2305.19089 · PDF · DOI · OpenAlex · Extracted main text

Abstract

This paper proposes a semiparametric sieve approach to estimate impulse response functions of nonlinear time series within a general class of structural autoregressive models. We prove that a two-step procedure can flexibly accommodate nonlinear specifications while avoiding the need to choose fixed parametric forms. Sieve impulse responses are proven to be consistent by deriving uniform estimation guarantees, and an iterative algorithm makes it straightforward to compute them in practice. With simulations, we show that the proposed semiparametric approach proves effective against misspecification while suffering only from minor efficiency losses. In a U.S. monetary policy application, the pointwise sieve GDP response associated with an interest rate increase is larger than that of a linear model. Finally, in an analysis of interest rate uncertainty shocks, sieve responses indicate more substantial contractionary effects on production and inflation.

Citation extraction

64
references
167
in-text mentions
64
distinct cited
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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
1Gon calves, S., Herrera, A. M., Kilian, L., and Pesavento, E (2021) Impulse response analysis for structural dynamic models with nonlinear regressors0.96922691%
2Kilian, L. and Lütkepohl, H (2017) Structural Vector Autoregressive Analysis0.92843100%
3Lütkepohl, H (2005) New Introduction to Multiple Time Series Analysis0.8746567%
4Istrefi, K. and Mouabbi, S (2018) Subjective interest rate uncertainty and the macroeconomy: A cross-country analysis0.87462100%
5Tenreyro, S. and Thwaites, G (2016) Pushing on a string: US monetary policy is less powerful in recessions0.87462100%
6Gon calves, S., Herrera, A. M., Kilian, L., and Pesavento, E (2024) Nonparametric Local Projections0.84333100%
7Belloni, A., Chernozhukov, V., Chetverikov, D., and Kato, K (2015) Some new asymptotic theory for least squares series: Pointwise and uniform results0.7374350%
8Wu, W. B (2005) Nonlinear system theory: Another look at dependence0.7374350%
9Debortoli, D., Forni, M., Gambetti, L., and Sala, L (2020) Asymmetric Effects of Monetary Policy Easing and Tightening0.73732100%
10Forni, M., Gambetti, L., Maffei-Faccioli, N., and Sala, L (2023) Nonlinear transmission of financial shocks: Some new evidence0.73732100%

Showing the top 10 of 64 scored citations.

Cited by, within the corpus

arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.

Citing paperIntensityMentionsSections
1Dynamic Causal Effects in a Nonlinear World: the Good, the Bad, and the Ugly0.40511
2Semiparametric Local Projections0.40511