The Macroeconomic Controversy Over Price Rigidity — How to Resolve it and How Bayesian Estimation has Led us Astray

Price rigidity plays a central role in macroeconomic models but remains controversial. Those espousing it look to Bayesian estimated models in support, while those assuming price flexibility largely impose it on their models. So controversy continues unresolved by testing on the data. In a Monte Carlo experiment we ask how different estimation methods could help to resolve this controversy. We find Bayesian estimation creates a large potential estimation bias compared with standard estimation techniques. Indirect estimation where the bias is found to be low appears to do best, and offers the best way forward for settling the price rigidity controversy.

Determinants of Price Rigidity and Flexibility: Some Survey Evidence for the Pakistan.

The objective of the study is to estimate the determinants of price stickiness or flexibility. Data is collected through structured questionnaire from 342 firms, which are selected through stratified random sampling technique from the Industrial Estate of Khyber Pakhtunkhwa. To estimate the determinants of price flexibility/rigidity, models are estimated through ordinary least squares technique and binary logistic technique. The most important factors for price stickiness are implicit/explicit price contracts and minimum price volatility. Imperfect competitive market structure, number of regular customers, backward-looking behavior, and credibility of central bank and size of the firm are important determinants of price rigidity. While economic literacy and information set regarding expected inflation make the prices flexible. Study recommend that monetary policy of Pakistan should use other transmission channels of money supply instead of traditional channel, because it is found that the degree of price rigidity is low in Pakistan. Keywords: Price Rigidity, Price Flexibility, Price Contract, Frequency of Price Change.

Shocks vs Menu Costs: Patterns of Price Rigidity in an Estimated Multi-Sector Menu-Cost Model

Sectoral heterogeneity matters for monetary policy. Using CPI microdata, we estimate for 227 products a time–varying menu-cost model to investigate the quantitative relevance of this heterogeneity. We find a substantial degree of cross-sectoral heterogeneity in all structural parameters. Heterogeneity in the Calvo component of the pricing friction is however the main source of heterogeneity in price rigidity. Cross-sectoral heterogeneity amplifies the output effect of a monetary shock by a factor of about 2.5, compared to a single-sector model estimated with mean moments. Heterogeneity in the Calvo parameter plays a key role in this amplification.

Price Stickiness under Stochastic Demand

This study develops a two-period model in which the manufacturer determines a price floor and sets production output prior to resolution of uncertainty. The closer the distance between the minimum price and the high-demand-state price, the higher the degree of price rigidity. Solving for the minimum resale price and production output, the model indicates that asymmetric price transmission could be a characteristic of competitive markets. The retail price in a highly concentrated retail market might be lower than that in a retail market with fierce competition. The relationship between price adjustments and the market competition suggests that the reason underlying price rigidity should be considered while formulating the antitrust and monetary policies.

Consumer Imperfect Information and Endogenous Price Rigidity

This paper studies the propagation of monetary shocks in an economy featuring a strategic microfoundation for price rigidities. Following an aggregate shock to money, most consumers are initially uninformed. The market for goods is decentralized. Firms are better off delaying the adjustment of prices until enough consumers learn. At the same time, consumers learn from firms that have adjusted prices. The implied endogenous information diffusion follows a Bernoulli differential equation, implying a nonlinear path of learning. Nonlinear learning implies hump-shaped dynamics of output and inflation. A quantitative exercise suggests that these dynamics can be sizable and persistent. (JEL D11, D21, D40, D82, E23, E31)