Working Paper Revision

The Sine Aggregatio Approach to Applied Macro


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;

JEL Classification: E3;

https://doi.org/10.20955/wp.2022.014

Access Documents

File(s): File format is application/pdf https://s3.amazonaws.com/real.stlouisfed.org/wp/2022/2022-014.pdf
Description: Full text

Authors

Bibliographic Information

Provider: Federal Reserve Bank of St. Louis

Part of Series: Working Papers

Publication Date: 2022-11-11

Number: 2022-014

Related Works