The Sine Aggregatio Approach to Applied Macro

Timothy Conley, Bill Dupor and Mahdi Ebsim

No 2022-014, Working Papers from Federal Reserve Bank of St. Louis

Abstract: We develop a method to use disaggregate data to conduct causal inference in macroeconomics. The approach permits one to infer the aggregate effect of a macro treatment using regional outcome data and a valid instrument. We estimate a macro effect without (sine) the aggregation (aggregatio) of the outcome variable. We exploit cross-equation parameter restrictions to increase precision relative to traditional, aggregate series estimates and provide a method to assess robustness to departures from these restrictions. We illustrate our method via estimating the jobs effect of oil price changes using regional manufacturing employment data and an aggregate oil supply shock.

Keywords: aggregation; macroeconomic causal effect (search for similar items in EconPapers)
JEL-codes: E3 (search for similar items in EconPapers)
Pages: 20 pages
Date: 2022-07-11, Revised 2022-11-11
New Economics Papers: this item is included in nep-ecm
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Persistent link: https://EconPapers.repec.org/RePEc:fip:fedlwp:94511

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DOI: 10.20955/wp.2022.014

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