Discussion of:
Reconciling micro-data and macro estimates of price stickiness
Discussant: Iulia Pasa
Summary
Reconcile the micro data on price setting with estimates from a macro model.
The Calvo framework is extensively used in many DSGE models.
The aggregate Phillips curve appears to overstate price stickiness
Ignoring heterogeneity has consequences
Methodology
Introduce into a standard model:- heterogeneity across firms- a richer production structure, incorporating intermediategoods Calibrate the model using the micro data, and
simulatemacro aggregates. Compare these macro estimates to the calibrated truevalues.
Comparisons on Calvo probabilities
Macro Evidence:– Assumption – all firms reset the prices
with the same probability– in theory macroec. estimate of aggregate
price stickiness should be less than the microeconomic based estimate
- In practice - opposite NKPC based estimates tend to imply
much more price stickiness
Comparisons on Calvo probabilities (cont.)
Micro Evidence:
Jensen’s inequality tells us that when firms face different Calvo probabilities, θmicro will be greater than the average Calvo probability.
Micro and Macro in tension
Relax the tension
Better way to calculate the coefficient on marginal costs for each of the sectorial NKPCs, and then use the weighted average of these sectorial coefficients as the coefficient on aggregate real marginal costs for the aggregate NKPC, in which case one should obtain θmacro
theory
Why Do Prices Look So StickyThrough the Lense of Calvo?
In Aggregate Data, Price Seems to
Respond Very Little to Marginal CostCalvo Interprets this as Reflecting Price
Setting Frictions
The Model
Agents- Households- Final goods firms- Intermediate goods
firms- Monetary authority
Sources of uncertainty
- Consumption shock- Aggregate technology
shock for i.g.f- Sector specific
technology shock for i.g.f
- M.P. shock
The model (cont.)
Complex interdependence between firms within and across sectors;
Each sector characterized by its production technology and Calvo probability;
Parameters were calibrated;A key part – heterogeneity in Calvo
probability across sectors
Properties of the model
Hazard functions - downward sloping precisely because of the sampling bias induced by heterogeneity;
Moments of the simulated data – growth in GDP/capita, inflation, nominal interest rate - inclusion of heterogeneity diminishes the persistence of inflation
Impulse response functions - initial response of value added to an aggregate shock is larger when heterogeneity or roundabout production is present. When combined, the two features appear to increase the persistence of value added responses to aggregate shocks.
Conclusion
Very Interesting Paper!
Heterogeneity and roundabout production have a non-trivial effect on model dynamics
Calvo probability used in most calibrated models is likely not accurate
The model helps resolve some of discrepancy between micro/macro data
We Also Need to Know About Wages!
Top Related