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!