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Micro responses to macro shocks

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Abstract

We study panel data regression models when the shocks of interest are aggregate and possibly small relative to idiosyncratic noise. This speaks to a large empirical literature that targets impulse responses via panel local projections. We show how to interpret the estimated coefficients when units have heterogeneous responses and how to obtain valid standard errors and confidence intervals. A simple recipe leads to robust inference: including lags as controls and then clustering at the time level. This strategy is valid under general error dynamics and uniformly over the degree of signal-to-noise of macro shocks.

Suggested Citation

  • Martín Almuzara & Víctor Sancibrián, 2024. "Micro responses to macro shocks," Working Papers wp2024_2412, CEMFI.
  • Handle: RePEc:cmf:wpaper:wp2024_2412
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    Cited by:

    1. Saroj Bhattarai & Arpita Chatterjee & Gautham Udupa, 2024. "Food, Fuel, and Facts: Distributional Effects of Global Price Shocks," CAMA Working Papers 2024-45, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    2. S. Borağan Aruoba & Thomas Drechsel, 2024. "The Long and Variable Lags of Monetary Policy: Evidence from Disaggregated Price Indices," NBER Chapters, in: Inflation in the COVID Era and Beyond, National Bureau of Economic Research, Inc.

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    Keywords

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    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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