Nonparametric Local Projections

Silvia Goncalves, Ana María Herrera, Lutz Kilian and Elena Pesavento

No 2414, Working Papers from Federal Reserve Bank of Dallas

Abstract: Nonlinearities play an increasingly important role in applied work when studying the responses of macroeconomic aggregates to policy shocks. Seemingly natural adaptations of the popular local linear projection estimator to nonlinear settings may fail to recover the population responses of interest. In this paper we study the properties of an alternative nonparametric local projection estimator of the conditional and unconditional responses of an outcome variable to an observed identified shock. We discuss alternative ways of implementing this estimator and how to allow for data-dependent tuning parameters. Our results are based on data generating processes that involve, respectively, nonlinearly transformed regressors, state-dependent coefficients and nonlinear interactions between shocks and state variables. Monte Carlo simulations show that a local-linear specification of the estimator tends to work well in reasonably large samples and is robust to nonlinearities of unknown form.

Keywords: impulse response; Local Projection; nonparametric estimation; nonlinear structural model; potential outcomes (search for similar items in EconPapers)
JEL-codes: C14 C32 E52 (search for similar items in EconPapers)
Pages: 40
Date: 2024-11-20
New Economics Papers: this item is included in nep-ecm and nep-ets
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Persistent link: https://EconPapers.repec.org/RePEc:fip:feddwp:99177

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DOI: 10.24149/wp2414

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