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The Macroeconomics of Sticky Prices with Generalized Hazard Functions

Author

Listed:
  • Fernando E. Alvarez

    (University of Chicago - Department of Economics; NBER)

  • Aleksei Oskolkov

    (University of Chicago - Department of Economics)

  • Francesco Lippi

    (Luiss University; EIEF)

Abstract

We give a thorough analytic characterization of a large class of sticky-price models where the firm’s price setting behavior is described by a generalized hazard function. Such a function provides a tractable description of the firm’s price setting behavior and allows for a vast variety of empirical hazards to be fitted. This setup is microfounded by random menu costs as in Caballero and Engel (1993) or, alternatively, by information frictions as in Woodford (2009). We establish two main results. First, we show how to identify all the primitives of the model, including the distribution of the fundamental adjustment costs and the implied generalized hazard function, using the distribution of price changes or the distribution of spell durations. Second, we derive a sufficient statistic for the aggregate effect of a monetary shock: given an arbitrary generalized hazard function, the cumulative impulse response to a once-and-for-all monetary shock is given by the ratio of the kurtosis of the steady-state distribution of price changes over the frequency of price adjustment times six. We prove that Calvo’s model yields the upper bound and Golosov and Lucas’ model the lower bound on this measure within the class of random menu cost models.

Suggested Citation

  • Fernando E. Alvarez & Aleksei Oskolkov & Francesco Lippi, 2020. "The Macroeconomics of Sticky Prices with Generalized Hazard Functions," Working Papers 2020-90, Becker Friedman Institute for Research In Economics.
  • Handle: RePEc:bfi:wpaper:2020-90
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    References listed on IDEAS

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    Cited by:

    1. Baley, Isaac & Blanco, Andres, 2022. "The Long-Run Effects of Corporate Tax Reforms," CEPR Discussion Papers 16936, C.E.P.R. Discussion Papers.
    2. Georgii Riabov & Aleh Tsyvinski, 2021. "Policy with stochastic hysteresis," Papers 2104.10225, arXiv.org.
    3. Fernando Alvarez & Francesco Lippi, 2022. "The Analytic Theory of a Monetary Shock," Econometrica, Econometric Society, vol. 90(4), pages 1655-1680, July.
    4. Hong, Gee Hee & Klepacz, Matthew & Pasten, Ernesto & Schoenle, Raphael, 2023. "The real effects of monetary shocks: Evidence from micro pricing moments," Journal of Monetary Economics, Elsevier, vol. 139(C), pages 1-20.
    5. Karadi, Peter & Schoenle, Raphael & Wursten, Jesse, 2020. "Measuring Price Selection in Microdata - It's Not There," CEPR Discussion Papers 15383, C.E.P.R. Discussion Papers.
    6. Lippi, Francesco & Alvarez, Fernando & Ferrara, Andrea & Gautier, Erwan & Le Bihan, Hervé, 2021. "Empirical Investigation of a Sufficient Statistic for Monetary Shocks," CEPR Discussion Papers 16626, C.E.P.R. Discussion Papers.
    7. Isaac Baley & Andrés Blanco, 2021. "Aggregate Dynamics in Lumpy Economies," Econometrica, Econometric Society, vol. 89(3), pages 1235-1264, May.
    8. Luo, Shaowen & Villar, Daniel, 2021. "The price adjustment hazard function: Evidence from high inflation periods," Journal of Economic Dynamics and Control, Elsevier, vol. 130(C).
    9. Isaac Baley & Andrés Blanco, 2022. "The Macroeconomics of Partial Irreversibility," Working Papers 1312, Barcelona School of Economics.

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    JEL classification:

    • C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis; Optimal Timing Strategies
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation

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