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Estimating (S,s) rule-regression models

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  • David Vincent

Abstract

There are many economic variables such as prices or wages that exhibit infrequent or lumpy adjustments. These outcomes occur when there are costs associated with making such changes, which lead agents to adopt an (S,s) decision rule. These rules are characterized by a band of inaction, where agents tolerate some deviation from an optimal frictionless outcome, provided that the deviation is within the (S,s) interval thresholds. The purpose of this presentation is to describe a new command, xtss, that estimates the parameters of a simple (S,s) rule model, for panel-data applications. This extends the specification developed by Dhyne et al. (2011) for modelling sticky prices by allowing the thresholds to have truncated Normal distributions and depend on regressors that vary over time and across individuals.

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  • David Vincent, 2019. "Estimating (S,s) rule-regression models," London Stata Conference 2019 03, Stata Users Group.
    • Handle: RePEc:boc:usug19:03
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    1. Dhyne, Emmanuel & Fuss, Catherine & Pesaran, M. Hashem & Sevestre, Patrick, 2011. "Lumpy Price Adjustments: A Microeconometric Analysis," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(4), pages 529-540.
    2. Erwan Gautier & Ronan Le Saout, 2015. "The Dynamics of Gasoline Prices: Evidence from Daily French Micro Data," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 47(6), pages 1063-1089, September.
    3. Denis Fougère & Erwan Gautier & Hervé Le Bihan, 2010. "Restaurant Prices and the Minimum Wage," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 42(7), pages 1199-1234, October.
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