Frequency Of Price Changes Research Articles

Changing Prices ... Changing Times: Evidence for Italy

This paper examines the process of adjustment of prices in Italy to determine whether nominal flexibility, measured by the frequency of price changes, has increased in the recent years of protracted stagnation and double-dip recession. The analysis is based on a large micro-level dataset of individual prices collected monthly by Istat from 2006 to 2013 for the Consumer Price Index. We find that both the percentage of prices adjusted monthly and the average size of the adjustment have risen significantly since the 1996-2001 period, in particular for downward changes. This greater flexibility is related in part to the spread of modern distribution structures. Our estimates further indicate that the recession has affected the price adjustment mechanism: for manufactures, price cuts have become larger and more frequent, while increases are more moderate; for services, both the frequency and the size of price increases have diminished.

Should We Use Linearized Models to Calculate Fiscal Multipliers?

We calculate the magnitude of the government consumption multiplier in linearized and nonlinear solutions of a New Keynesian model at the zero lower bound. Importantly, the model is amended with real rigidities to simultaneously account for the macroeconomic evidence of a low Phillips curve slope and the microeconomic evidence of frequent price changes. We show that the nonlinear solution is associated with a much smaller multiplier than the linearized solution in long-lived liquidity traps, and pin down the key features in the model which account for the difference. Our results caution against the common practice of using linearized models to calculate fiscal multipliers in long-lived liquidity traps.

Should We Use Linearized Models to Calculate Fiscal Multipliers?

We calculate the magnitude of the government consumption multiplier in linearized and nonlinear solutions of a New Keynesian model at the zero lower bound. Importantly, the model is amended with real rigidities to simultaneously account for the macroeconomic evidence of a low Phillips curve slope and the microeconomic evidence of frequent price changes. We show that the nonlinear solution is associated with a much smaller multiplier than the linearized solution in long-lived liquidity traps, and pin down the key features in the model which account for the difference. Our results caution against the common practice of using linearized models to calculate fiscal multipliers in long-lived liquidity traps.

Pricing and Matching with Forward-Looking Buyers and Sellers

Motivated by the emerging sharing economy, we study a dynamic market of a single product or service, to which buyers with heterogeneous private valuations and sellers with heterogeneous private supply costs sequentially arrive following Poisson processes. A single market making intermediary dynamically decides on the ask and bid prices posted to buyers and sellers, respectively, and on the matching decisions after buyers and sellers agree to buy and sell, respectively. Buyers and sellers can strategically wait for better prices after their arrivals. The intermediary’s problem is a multi-dimensional mechanism design problem that is hard to analyze. We propose a simple heuristic policy, that is, a fixed ask price charged to the buyers and a fixed bid price offered to the sellers plus a price adjustment as compensation for expected waiting cost, in conjunction with the greedy matching policy on a first-come first-served basis. These fixed base prices balance demand and supply in expectation, and can be computed efficiently. The waiting adjusted ask and bid price processes are time dependent and tend to have opposite trends in the beginning and end of the horizon. Under this heuristic policy, forward-looking buyers and sellers behave myopically without wait. We show that this heuristic policy is asymptotically optimal for the intermediary and the waiting time compensation becomes negligible, as the volumes of demand and supply arrivals proportionally grow. Our results suggest that the random arrivals of heterogeneous buyers and sellers, alone, may not be sufficient to justify contingent pricing. Given Uber changes its prices every five minutes to rapidly micro-match supply with demand, our result suggests Uber may not lose much optimality by reducing the frequency of price changes, unless the underlying market conditions have significantly changed. This is because our fixed pricing has captured the first-order effect and the benefit of surge pricing diminishes as the volumes of the platform grow, not to mention frequent surge pricing may agonize riders and induce strategic behaviors of riders and drivers that are hard to account for.

The Real Effects of Monetary Shocks in Sticky Price Models: A Sufficient Statistic Approach

We prove that the ratio of kurtosis to the frequency of price changes is a sufficient statistic for the real effects of monetary shocks, measured by the cumulated output response following the shock. The sufficient statistic result holds in a large class of models which includes Taylor (1980); Calvo (1983); Reis (2006 ); Golosov and Lucas (2007 ); Nakamura and Steinsson (2010); Midrigan (2011); and Alvarez and Lippi (2014). Several models in this class are able to account for the positive excess kurtosis of the size distribution of price changes that appears in the data. We review empirical measures of kurtosis and frequency and conclude that a model that successfully matches the microevidence on kurtosis and frequency produces real effects that are about four times larger than in the Golosov-Lucas model, and about 30 percent below those of the Calvo model. We discuss the robustness of our results to changes in the setup, including small inflation and leptokurtic cost shocks. (JEL, E23, E31)

Inflation and Price Adjustments: Micro Evidence from Norwegian Consumer Prices 1975–2004

This is the first paper documenting the frequency and size of price adjustments using micro data from both the high-inflation period in the 1970s and 1980s, and the period of low inflation since the early 1990s. When inflation is high and volatile, prices change more frequently and in smaller magnitudes. When inflation is low and stable, prices change less frequently but in larger magnitudes. The frequency of price changes is more important for the variation in inflation when inflation is high and volatile. When inflation is low and stable, the magnitude of the price changes is more important than the frequency. (JEL E31, E32, L11)

Why Don’t Prices Rise during Periods of Peak Demand? Synchronize Demand to Relax Competition

Abstract During periods of peak demand, frequent markdowns present an empirical puzzle. Based on the idea that stores face capacity constraints in times of high shopping volume, we show that stores keep their off-season prices high in order to lure all consumers to shop around the same time. This relaxes competition and allows stores to raise prices. Due to binding capacity constraints, stores randomize their prices. Thus, our model offers a unified explanation for both the countercyclicality and the high frequency of price changes during periods of peak demand.

Determinants of the Frequency of Price Changes in Vietnam

Determinants of the Frequency of Price Changes in Vietnam

Data-Driven Dynamic Pricing and Inventory Control with Censored Demand and Limited Price Changes

A firm sells a product over T periods. Demand in each period is random and price sensitive, and unsatisfied demands are lost and unobservable. The firm has limited prior knowledge about the demand process and needs to learn it through historical sales data. We consider the scenario where the firm is faced with the business constraint that prevents it from conducting extensive price experimentation. We develop data-driven algorithms for pricing and inventory decisions and evaluate their effectiveness using regret, which is the profit loss compared to a clairvoyant who has complete information about the demand process. We study three distinct scenarios and design algorithms that achieve the lowest possible regret rates: First, in a quite general case, when the number of price changes is bounded by a given number, the regret is O(T1/2). Second, in a special so-called well-separated case, when the number of price changes is limited to m, the regret is O(T1/m 1). Third, in the well-separated case allowing more frequent price changes that is limited to O(logT), the regret is O(logT). Numerical results show that these algorithms empirically perform very well.

Price Rigidity, Inflation and the Distribution of Relative Price Changes

This study examines whether skewness of the cross-sectional distribution of relative price changes is positively associated with aggregate inflation as predicted by the menu cost model of Ball and Mankiw (1994, 1995). Further, the study examines the size and frequency of price changes across various commodities and the distribution of relative price changes. The results from highly disaggregated Indian wholesale price index (WPI) data suggest that the skewness of relative price changes explains a significant proportion of short-run fluctuations in aggregate inflation. More importantly, the results indicate that the average size of price increases is greater than the size of price decreases implying downwards rigidity in the prices of various commodities. JEL Classification: E30, E31, E52

PRICE SETTING PRACTICES IN GREECE: EVIDENCE FROM A SMALL‐SCALE FIRM‐LEVEL SURVEY

ABSTRACTThe paper documents the price setting practices followed by some 400 or so firms operating in Greece. Survey replies reveal a low percentage of firms changing prices with frequency higher than annual and staggering of price changes during the year. As to firms’ reactions to unexpected shocks, prices appear to adjust sluggishly to cost shocks with asymmetries in price adjustment across positive and negative shocks. Adjustments to increases in costs appear speedier than those to reductions in demand. The data confirm a result found for other countries: the existence of cross‐sectional variations in price setting strategies and in the extent to which prices are adjusted in reaction to unexpected shocks. The results suggest a positive association between, on the one hand, product market competition and, on the other hand, state‐dependent pricing, frequent price changes and the likelihood of a price adjustment following an adverse demand shock.

Price Rigidity in Turkey: Evidence from Micro Data

In this study we investigate the duration of consumer price spells and price change patterns for Turkey by employing a comprehensive micro price data covering around 6,000 items over four years. In detail, we analyze how long typical price spell lasts and we investigate the size, frequency, distribution and synchronization of price changes. Compared to advanced economies, a higher frequency of price changes is estimated. Findings suggest substantial heterogeneity among sub-groups in terms of frequency and synchronization indicators. The mixed evidence of both state and time-dependent pricing is also relevant for Turkey, an emerging market economy.

What Survey Data Reveal about Price and Wage Rigidity in Portugal

AbstractThis paper exploits the information collected from a survey conducted on a sample of Portuguese firms to study the patterns of firms’ price and wage adjustments and the extent of nominal price and wage rigidities. The evidence shows that the frequency of price changes varies substantially across sectors and depends on the intensity of competition, the share of labor costs and firms’ price reviewing behavior. The results also suggest that the constraint imposed by the presence of downward nominal wage rigidity is less important in firms where the fraction of permanent and high‐skilled workers is lower and the share of flexible pay components is higher.

Competition and Price Stickiness: Evidence from the French Retail Gasoline Market

Using daily price quotes from about 10,000 French gas stations, this paper empirically analyses whether the level of competition determines the degree of price stickiness on the retail gasoline market. The degree of price rigidity is measured by the frequency of price changes as well as the average duration of uncensored price spells, while the distance to the nearest station and the number of gas stations within a given radius are considered as proxies for local competition. The results confirm that local competition is an important determinant of the price-setting behavior of gas stations. Indeed, for both measures of price stickiness, we find that the degree of price rigidity is positively related to the distance to the nearest station, and negatively related to the concentration of firms in a given geographical area. This result can be notably explained by the fact that gas stations facing a high competitive pressure are more likely to adjust their prices more quickly and more frequently in response to crude oil price decreases than stations enjoying market power.

Costly Information, Planning Complementarities and the Phillips Curve

Standard sticky information pricing models successfully capture the sluggish movement of aggregate prices in response to monetary policy shocks but fail at matching the magnitude and frequency of price changes at the micro level. This paper shows that in a setting where firms choose when to acquire costly information about different types of shocks, strategic complementarities in pricing generate planning complementarities. This results in firms optimally updating their information about monetary policy shocks less frequently than about idiosyncratic shocks. When calibrated to match frequent and large price changes observed in micro pricing data, the model is still capable of producing substantial non-neutralities. In addition, I use the model consistent Phillips curve and data from the Survey of Professional Forecasters to estimate the frequency at which firms update their information about monetary policy shocks. I find that the frequency of updating was higher in the 1970s compared to subsequent decades and hence conclude that monetary policy in the U.S. was relatively less effective prior to the 1980s.

Overtime Labor, Employment Frictions, and the New Keynesian Phillips Curve

Abstract This paper presents a New Keynesian (NK) model that is extended to differentiate between straight time and overtime work. The model proposes that the New Keynesian Phillips curve (NKPC) should be estimated with marginal cost measured in terms of overtime labor; the resulting coefficient estimates are in accordance with theory and statistically significant for the hybrid NKPC (which allows for backward-looking price setters) but not for the purely forward-looking NKPC. In the hybrid model, backward-looking behavior is found to be predominant. The paper also shows that the incorporation of employment frictions (predetermined employment and convex adjustment costs) in NK models helps reconcile the frequent price changes found in the microdata with the degree of sluggishness in inflation adjustment to output changes at the macro level.

Small and Large Price Changes and the Propagation of Monetary Shocks

We document the presence of both small and large price changes in individual price records from the CPI in France and the US. After correcting for measurement error and cross-section heterogeneity, the size-distribution of price changes has a positive excess kurtosis. We propose an analytical menu cost model that encompasses several classic models, as Taylor (1980), Calvo (1983), Reis (2006), Golosov and Lucas (2007) and accounts for observed cross-sectional patterns. We show that the ratio of kurtosis to the frequency of price changes is a sufficient statistics for the real effects of monetary policy in a large class of models.

The effect of VAT rate on inflation in Latvia: evidence from CPI microdata

This article evaluates the inflation effect of recent value added tax (VAT) rate changes in Latvia by using consumer price index (CPI) microdata. Our findings suggest that the pass-through of the tax rate to consumer prices is strong in case of upward tax adjustments, especially when there are no demand restrictions, while the pass-through is weaker for tax reductions. The frequency of price changes peaks at the moment of VAT adjustment, which, however, is partially compensated by lower average size of price revisions. The level of pass-through exhibits a high degree of heterogeneity with higher pass-through for goods, especially food, and lower for services.

Comment on “Micro Price Dynamics during Japan's Lost Decades”

Sudo et al. (2014) use point of sales (POS) data to investigate micro price dynamics. POS data are highly disaggregated, high-frequency data on retail prices. Macroeconomists have been paying attention to micro price data not only because they are useful in testing theories about the pricing decisions made by firms, but also because micro price data are considered useful for understanding important macroeconomic questions, such as the transmission mechanism of monetary policy and inflation dynamics. Standard textbooks explain that, when prices are sticky, monetary policy can affect the real interest rate, which in turn affects aggregate expenditure through the intertemporal substitution of demand. This transmission mechanism is represented by, for example, the Euler equation for consumption. Since micro price data are, by definition, disaggregated, they may provide rich information about agents' behavior that lies behind aggregate price data. For example, if one is interested in the degree of price stickiness, it would be very useful to measure how frequently each firm changes its price. For this reason, the measures of the frequency of price changes are useful for investigating the degree of price stickiness. Another reason for looking at micro price data is that one can study the heterogeneity of pricing decisions across firms. Sudo et al. (2014) provide a number of interesting facts about Japanese micro price data. In this comment, I focus my discussion on how to interpret two of their findings from the viewpoint of macroeconomic theory. The first finding is that posted prices in Japan are ten times as flexible as those in the USA. What is the implication of this for macroeconomics? One might be tempted to conclude that monetary policy in Japan is less effective since prices are more flexible. However, from a theoretical point of view, what matters for consumption decisions is the cost per unit of consumption flow not the price of unit consumption expenditure per se. As Aguiar and Hurst (2007) argue, consumption flow is a product of purchased goods and home production. By spending more time on home production, a consumer can save spending while achieving the same level of consumption flow. Furthermore, purchasing goods requires shopping time. A consumer can find a cheaper price by spending more time on shopping. This implies that he/she can substitute his/her time (spent on shopping and home production) for the amount of money spent on purchasing goods. A change in the price of the consumption flow consists not only of a change in the price of purchased goods, but also a change in the shadow value of shopping time and home production. Therefore, it is not theoretically obvious that the degree of stickiness in the price of purchased goods has a one-to-one mapping to the degree of stickiness in the price of the consumption flow. Furthermore, what matters for aggregate demand (and the monetary transmission mechanism) is whether purchase prices of each consumer are sticky or not. It does not necessarily matter how sticky the prices of goods sold at a particular shop are. Consider the following example. Household A goes shopping only on the weekend and household B goes shopping only on weekdays, but both of them go to the same shop. Suppose the shop charges different prices on weekends and weekdays, but that these two prices are kept fixed for a year. In this example, even though the prices are considered as being flexible, the prices facing each household are sticky. This implies that the analysis using POS data should be complemented with information provided by household-level data. Abe and Shiotani (2014) investigate household-level scanner data and provide interesting findings. However, a limitation of their household-level data is the fact that the data are not available over a long time horizon. In contrast, POS data are available for long time horizon, which makes POS data more useful for investigating price dynamics. Second, Sudo et al. (2014) find that the frequency of bargain sales are correlated with labor market conditions. This is consistent with the observation that the consumption flow is a product of goods purchases, shopping, and home production. When the labor market is slack, a consumer may have more time for shopping and home production. In response to this, retailers may increase the frequency of sales. From a macroeconomic point of view, this can be represented by a negative markup shock in the New Keynesian Phillips curve. It has been argued that the negative markup shock has contributed to Japanese deflation. Sudo et al.'s findings are consistent with this view. However, again, their result does not necessarily mean that the nominal price of consumption flow has declined because more bargain hunting may just mean that a consumer substitutes money spent on goods for shopping time.

Real Rigidities and the Cross-Sectional Distribution of Price Stickiness: Evidence from Micro and Macro Data Combined

We use a standard sticky-price model to provide evidence on three mechanisms that can reconcile somewhat frequent price changes with large and persistent real effects of monetary shocks. To that end, we estimate a semi-structural model for the U.S. economy that allows for varying degrees of real rigidities, and cross-sectional heterogeneity in price stickiness. The model can extract some information about these two features of the economy from aggregate data, and discriminate between different distributions of price stickiness. Hence it can also speak to the debate about the role of sales and other temporary price changes in shaping the effects of monetary policy. Employing a Bayesian approach, we combine macroeconomic time-series data with information about empirical distributions of price stickiness derived from micro price data for the U.S. economy. Our estimates point to the presence of both large real rigidities and an important degree of heterogeneity in price stickiness. Moreover, cross-sectional distributions of price stickiness that factor out sales improve the empirical fit of the model. Our results suggest that bridging the gap between micro and macro evidence on nominal price rigidity may require the combination of several mechanisms.