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Lumpy Price Adjustments : A Microeconometric Analysis

Lumpy Price Adjustments : A Microeconometric Analysis. E. Dhyne (NBB, UMH), C. Fuss (NBB, ULB), H. Pesaran (Cambridge U., USC), P. Sevestre (U. Paris I, BdF). "Price and Wage Rigidities in an Open Economy" National Bank of Belgium - Brussels, October 12-13, 2006.

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Lumpy Price Adjustments : A Microeconometric Analysis

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  1. Lumpy Price Adjustments :A Microeconometric Analysis E. Dhyne (NBB, UMH), C. Fuss (NBB, ULB), H. Pesaran (Cambridge U., USC), P. Sevestre (U. Paris I, BdF) "Price and Wage Rigidities in an Open Economy" National Bank of Belgium - Brussels, October 12-13, 2006 The views expressed are those of the authors and do not necessarily reflect the views of the National Bank of Belgium and of the Banque de France.

  2. Empirical analysis of the sources of price stickiness: nominal vs real rigidity Motivation : In modern macroeconomics, price rigidity = source of short-run non neutrality of money Degree of nominal rigidity One of the determinants of the slope of the NKPC Introduction

  3. New strand of empirical work on the evaluation of the frequency of consumer price changes Similar set of stylized facts in industrialized countries Price changes are infrequent US : 25% Bils and Klenow (2004), Klenow and Kryvtsov (2005) Euro area : 15% IPN, Dhyne et al. (2006) Belgium : 17% Aucremanne and Dhyne (2004) France : 19% Baudry et al. (2004) Heterogeneity in price stickiness (oil products => services) Asymmetry: 4 price changes out of 10 are price decreases Price changes are relatively large (around 8 -10 %) Introduction

  4. Main question : what’s behind infrequent price changes ? A firm may consider that it’s more profitable to keep its priceconstant between two periods because of large price adjustment cost: nominal rigidity small volatility of marginal costs / desired mark-up: real rigidity Other questions : Can prices be informative on the degree of "wage" stickiness ? Are asymmetric price changes caused by asymmetric price adjustment costs ? Introduction

  5. A firm i sets its price at time t based on pricing rule pit = p*it if |p*it-pit-1| > cit pit = pit-1 if |p*it-pit-1| ≤ cit With p*it the (unobserved) optimal price given as p*it = mcit + mit = ft + ui + eit A canonical model of price adjustment Idiosyncratic shock on marginal cost and desired mark-up Common component of marginal cost and desired mark-up Firm’s specific component heterogeneity in price levels, ability of firm i to set its prices above/below ft

  6. Common movement in marginal costs and desired mark-up Estimation by using cross-sectional averages : generalization of Pesaran (2006) to non-linear models where g(ft) non linear function of ft, pit-1 and other parameters q ft only equals to pt when E[cit] = c = 0 Iterative procedure : estimate ft given q estimate q given ft Can also be estimated jointly with q by ML Both estimation procedures need N and T large Summarizewith AR(p): Unobserved common component ft

  7. pit = pit-1 if |ft + ui + eit- pit-1| ≤cit = ft + ui + eit otherwise Nominal rigidity : Expected value of price adjustment cost cit, c Real rigidity : Unconditional volatility of ft,std(ft) or volatility of the common shock,sw Volatility of idiosyncratic shock eit, se Sources of nominal and real rigidities

  8. Belgian CPI : around 10.000.000 individual prices French CPI : around 13.000.000 individual prices Prices observed at the retail level from 07/94 to 02/03 Described in Aucremmane and Dhyne (2004, 2005), Baudry et al. (2004) Estimation method : Maximum Likelihood with 1 firm specific random effect (ui) 98 products (Belgian CPI) / 30 products (French CPI) The Belgian and French CPI data sets

  9. Price trajectories: Oranges (Belgium)

  10. Price trajectories: Men socks (France)

  11. Model's performance • Ability of the estimated model to replicate the frequency and size of price changes • Good results for 88 products for the Belgian CPI out of 98 • Good results for a large set of products : flexible or sticky prices, seasonal, with a trend, regulated or not • But bad performance for • products with few price quotes / month • products where cit highly volatile

  12. Flexible prices : Heating oil True data Freq = 0.730 |Dp| = 0.073 c = 0.025 se = 0.036 sf = 0.063 Simulated data Freq* = 0.747 |Dp|* = 0.080

  13. Seasonal product : Oranges True data Freq = 0.619 |Dp| = 0.183 c = 0.079 se = 0.159 sf = 0.040 Simulated data Freq* = 0.731 |Dp|* = 0.232

  14. Asymmetric sticky prices : Special beer in a bar True data Freq = 0.030 |Dp| = 0.084 c = 0.545 se = 0.054 sf = 0.009 Simulated data Freq* = 0.028 |Dp|* = 0.110

  15. Asymmetric sticky prices : Calculator True data Freq = 0.057 |Dp| = 0.124 c = 0.727 se = 0.134 sf = 0.007 Simulated data Freq* = 0.062 |Dp|* = 0.240

  16. Main results • Based on 88 Belgian CPI products + 30 French CPI products • Average c : ≈ 0.35, comparable in magnitude with Levy et al. (1997) based on cost structure of supermarkets. • Idiosyncratic shocks always larger than common shocks, except for oil products (Golosov and Lucas, 2003)

  17. Sectoral heterogeneity • Oil products (Freq = 0.75) : small c (0.012), large sω(0.033),small se(0.027) → flexible • Perishable food (Freq = 0.24) : medium c (0.266), large sω(0.028) and se(0.098) → nominal rigidity • Non perishable food (Freq = 0.15) + non durable goods (Freq = 0.16) medium c (0.271 – 0.358), smaller sω (0.016 – 0.019) and se (0.076 – 0.086) → real and nominal rigidity • Durable goods (Freq = 0.08) + services (Freq = 0.06) : high c (0.493 – 0.384), smaller sω (0.015 – 0.013) and se(0.079 – 0.054) → strong real and nominal rigidity

  18. Analyzing the frequency of price changes • Examples • Belgian CPI : Kiwis / Beef Sirloin : ≠ freq, ≈ c, ≠ sω, ≠se • French CPI : Sugar / Men coat : ≈ freq, ≠ c, ≠ sω, ≠ se • Ratio (s2e + s2 ω)0.5/c

  19. Analyzing the frequency of price changes • OLS regression of the frequency of price changes

  20. Other results: tentative lessons on wage rigidity • Can prices say something about wage rigidity? (Belgian CPI) • 5 product categories for which price = labor cost (hourly rate of a plumber, hourly rate of a painter, hourly rate in a garage, central heating repair tariff, domestic services) • Lowest frequency of price changes • Lower c than other services (0.3 compared to 0.5) but similar to average perishable or non perishable food, non durable goods • Low magnitude of common and idiosyncratic shocks • → real rigidity is a major source of “wage” price rigidity

  21. Other results: asymmetric price changes • Exploring the asymmetry of price changes (Belgian CPI) • Stylized fact : price increases are slightly more common thanprice decreases. • Is this associated to stronger downward nominal rigidities ? • Baseline model generates asymmetric price changes if ft characterized by a positive (negative) trend (Ball and Mankiw,1994) • Estimation of a model of asymmetric price adjustment costs (cup, cdown) for oranges (% ups = 52 %) and special beer in a bar (% ups = 88 %) • Results : cup - cdw statistically significant but not economically relevant • Oranges : cdw - cup = 0.000 Special beer : cdw - cup = -0.002

  22. Conclusions • Comparable estimate of the magnitude of price adjustment costs with the existing empirical litterature (Levy et al. (1997)) : average level of c : close to 35% of the price level • Idiosyncratic shocks are larger than common shocks. • Heterogeneity in the frequency of price changes not only associated to heterogeneity in price adjustment costs but also … • … significant contribution of real rigidity • Implications for macro models: heterogeneity in the degree of real rigidity (Gertler and Leahy, 2006)

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