Controls, Not Shocks: Estimating Dynamic Causal Effects in Macroeconomics

Simon Lloyd and Ed Manuel

No 2422, Discussion Papers from Centre for Macroeconomics (CFM)

Abstract: A common approach to estimating causal effects in macroeconomics involves constructing orthogonalised ‘shocks’ then integrating them into local projections or vector autoregressions. For a general set of estimators, we show that this two-step ‘shock-first’ approach can be problematic for identification and inference relative to a one-step procedure which simply adds appropriate controls directly in the outcome regression. We show this analytically by comparing one- and two-step estimators without assumptions on underlying data-generating processes. In simple OLS settings, the two approaches yield identical coefficients, but two-step inference is unnecessarily conservative. More generally, one- and two-step estimates can differ due to omitted-variable bias in the latter when additional controls are included in the second stage or when employing non-OLS estimators. In monetary-policy applications controlling for central-bank information, one-step estimates indicate that the (dis)inflationary consequences of US monetary policy are more robust than previously realised, not subject to a ‘price puzzle’.

Keywords: Identification; Instrumental Variables; Local Projections; Omitted-Variable Bias; VARs (search for similar items in EconPapers)
JEL-codes: C22 C26 C32 C36 E50 E60 (search for similar items in EconPapers)
Pages: 46 pages
Date: 2024-04
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Related works:
Working Paper: Controls, not shocks: estimating dynamic causal effects in macroeconomics (2024)
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Persistent link: https://EconPapers.repec.org/RePEc:cfm:wpaper:2422

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