Prices are sticky after all

Economists have interpreted the evidence that prices change every four months as implying that sticky prices cannot be important for monetary transmission. Theory implies that this interpretation is correct if most price changes are regular, but not if a large fraction are temporary, as in the data. Since regular prices are much stickier than temporary ones, our models predict that the stickiness of the aggregate price level matches that in a standard Calvo model or a standard menu cost model in which micro-level prices change about once a year. In this sense, prices are sticky after all.     

Timing of Sale,Pricing, and Cost Information: Evidence from the Airline Industry*

This study examines the association between when an airline sells its passenger seats and the pricing method (marginal cost or full cost) it employs. Prior literature suggests that when firms are able to change prices during the selling period, the optimality of full cost pricing or marginal cost pricing depends on when demand information is revealed during the period between capacity commitment decisions and time of sale. Full cost‐based pricing is appropriate in determining capacity commitment and prices simultaneously, while marginal cost provides more relevant information for pricing when capacity has been committed. Using the price and cost data from a sample of four U.S. domestic airlines, we find that full cost explains price variations of first‐day sales robustly. The adjusted R² of the marginal cost pricing model is larger in the sample of sales two days prior to departure than in the sample of first‐day sales. In the analysis of the sample of sales two days prior to departure, we find that, based on the adjusted R² of the full cost pricing and marginal cost pricing models, the explanatory power of marginal cost pricing is relatively weaker than full cost pricing. Our results document the use of different cost information along the dynamic change of price and provide implications in understanding the role of cost information in setting prices.     

Pricing Options in an Extended Black Scholes Economy with Illiquidity: Theory and Empirical Evidence

This article studies the pricing of options in an extended BlackScholes economy in which the underlying asset is not perfectlyliquid. The resulting liquidity risk is modeled as a stochasticsupply curve, with the transaction price being a function ofthe trade size. Consistent with the market microstructure literature,the supply curve is upward sloping with purchases executed athigher prices and sales at lower prices. Optimal discrete timehedging strategies are then derived. Empirical evidence revealsa significant liquidity cost intrinsic to every option.     

Price spreads and residential housing market liquidity

Most studies of housing market liquidity have measured liquidity in terms of time on the market (TOM), and have sought to explain TOM in terms of property characteristics and measures of market conditions. This paper departs from past studies of housing market liquidity by examining the spread between the listing and contract prices.We develop theory to explain the price spreads in the residential housing market. The model includes the list price of the home, the cost of the search, the standard deviation of offer prices, and TOM. Empirical tests using 3,597 sales for 25 months show a robust relationship of housing market spreads and these variables. Listing price and cost of search have the predicted positive coefficients, and the standard deviation of price offers is found to be negatively related to the price spread.     

Mean Reversion and Momentum: Another Look at the Price-Volume Correlation in the Real Estate Market

Based on behavioral finance and economics literature, we construct a theoretical framework in which consumers of newly constructed housing units perceive prices to follow a stochastic mean reversion pattern. Given this belief and the high carrying cost maintained by real estate developers, potential buyers opt to either exercise immediately or defer the purchase. We simulate the model within a real option framework by which we show that the optimal time to wait before exercising a purchase is positively related to the price level; hence, a negative (positive) correlation between transaction volume and price level (yield) emerges. Observing data on housing prices and new construction sales in Israel for the years 1998–2007, we apply an adaptive expectation regression model to test consumers’ belief in both mean reversion and momentum price patterns. The empirical evidence shows that while consumers’ demand pattern is simultaneously consistent with the belief in both momentum and mean reversion processes, the effect of the latter generally dominates. Moreover, while the data does not allow for testing the volume and price-level correlation, it does provide support to the positive volume-price yield correlation.     

The Choice of Methodology for Computing Housing Price Indexes: Comparisons of Temporal Aggregation and Sample Definition

Housing transactions are executed and recorded daily, but are routinely pooled into longer time periods for the measurement and analysis of housing price trends. We utilize an unusually rich data set, covering essentially all arm's length housing sales in Sweden for a dozen years, in an attempt to understand the effect of temporal aggregation upon estimates of housing prices and their volatilities. This rich data set also provides a unique opportunity to compare the results using the conventional weighted repeat sales model (WRS) to those based on a research strategy which incorporates all available information on house sales. The results indicate the clear importance of temporal disaggregation in the estimation of housing prices and volatilities—regardless of the model employed.The appropriately disaggregated model is then used as a benchmark to compare estimates of the course of housing prices produced by the two models during the twelve year period 1981–1993. These results indicate that much of the difference between estimates of price movements can be attributed to the data limitations which are inherent in the repeat sales approach. The results, thus, suggest caution in the interpretation of government-produced price indices or those produced by private firms based on the repeated sales model.     

More Facts about Prices: France Before and During the Great Recession

Using microprice data, we document new facts on price rigidity in France: (i) each month 20.1% of prices are changed, which compares to 24.1% in the United States—excluding sales, however, the fraction of prices modified each month is about the same in France and in the United States (around 17%); (ii) the distribution of price changes is quite dispersed; (iii) the frequencies of price increases and decreases contribute a lot to inflation variations, and price increases are more frequent in January (even when sales are excluded); (iv) sales contribute significantly to the volatility of inflation but play a minor role in the transmission of macroeconomic fluctuations to prices; and (v) during the Great Recession patterns of price adjustment were only slightly modified.     

Three New Real Estate Price Indices for Geneva,Switzerland

This paper develops constant-quality price indices for three categories of real estate-apartment buildings, vacant land, and condominiums—for the city of Geneva, Switzerland. We use both the hedonic and repeat sales models to estimate the price level and, in turn, the rate of price change. The general pattern of each series suggests that real estate prices in Geneva were fairly stable throughout the 1970s, increased sharply during the 1980s, but gave back some of these gains in the early 1990s. Interestingly, the sharp rise in prices in the second half of the 1980s is very similar to that found in some regions of the United States. We also consider the problem, implicit in the repeat sales method, of revisions in previously estimated price indices as additional data become available in later years.     

TRADE SIZE AND PRICE CLUSTERING: THE CASE OF SHORT SALES AND THE SUSPENSION OF PRICE TESTS

In this article, we compare trade size and price clustering of short sales with regular trades. We find that short sales cluster less on round sizes and round prices than do nonshort trades. When price tests are suspended, both trade size and price clustering markedly increase for short sales although the difference between shorts and nonshorts remains significant during the postsuspension period. These results are consistent with the idea that because of execution uncertainty caused by price tests, short sellers are less concerned with cognitive processing costs, negotiations costs, and the costs associated with revealing information through trade sizes.     

Intraday Behavior of Stock Prices and Trades around Insider Trading

Our evidence indicates that insiders' trades provide significant new information to market participants and they are incorporated more fully in stock prices as compared to noninsiders' trades. We find that market professionals do not front-run insiders' trades. Both insiders' purchases and sales result in significant contemporaneous and subsequent price impact, while sales by large shareholders result in a contemporaneous stock price decline that is subsequently reversed. The arrival of insider purchases reverse the prevailing negative order imbalances from third party trades and lead to piggy-backing by market professionals resulting in subsequent market purchase orders as well as stock price increases.     

Trading Frictions and House Price Dynamics

We model liquidity in housing markets. The model provides a simple characterization for the joint process of prices, sales, and inventory. We compare the implications of the model to certain properties of housing markets. The model can generate the large price changes and the positive correlation between prices and sales that we see in the data. Unlike the data, prices are negatively autocorrelated and high inventory predicts price appreciation. We investigate several amendments to the model. Informational frictions show promise.     

Catering through Nominal Share Prices

We propose and test a catering theory of nominal stock prices. The theory predicts that when investors place higher valuations on low‐price firms, managers respond by supplying shares at lower price levels, and vice versa. We confirm these predictions in time‐series and firm‐level data using several measures of time‐varying catering incentives. More generally, the results provide unusually clean evidence that catering influences corporate decisions, because the process of targeting nominal share prices is not well explained by alternative theories.     

Learning by lending

This paper studies bank learning through repeated interactions with borrowers from a new perspective. To understand learning by lending, we adapt a methodology from labor economics to analyze how loan contract terms evolve as banks acquire new information about borrowers. We construct “proxy” variables for this information using data from borrowers’ out-of-sample, future credit performance. Due to the timing of their construction, banks could not have used these variables directly to price loans. We nonetheless find that these proxies increasingly predict loan prices as relationships progress, even after controlling for possible omitted variable bias. Our methodology provides strong evidence that: (a) bank learning affects loan prices, and (b) relationship benefits are heterogeneous. In particular, higher quality borrowers face differentially lower spreads as their relationship with lenders develop – and banks learn about their quality – while lower quality borrowers see loan prices increase and their loan amounts fall. We further find suggestive evidence that banks incorporate CEO-specific information into loan prices.     

Predicting House Prices Using Multiple Listings Data

It is often necessary to accurately predict the price of a house between sales. One method of predicting house values is to use data on the characteristics of the area's housing stock to estimate a hedonic regression, using ordinary least squares (OLS) as the statistical technique. The coefficients of this regression are then used to produce the predicted house prices. However, this procedure ignores a potentially large source of information regarding house prices—the correlations existing between the prices of neighboring houses. The purpose of this article is to show how these correlations can be incorporated when estimating regression coefficients and when predicting house prices. The practical difficulties inherent in using a technique called kriging to predict house prices are discussed. The article concludes with an example of the procedure using multiple listings data from Baltimore.     

Earnings response coefficients of OECD banks: Tests extended to include bank risk factors

We investigate two issues: Do share prices of banks in European markets respond to unexpected accounting earnings disclosures? Are share prices as well as unexpected earnings changes correlated with bank-relevant risk factors? Results reveal that bank share prices respond to unexpected earnings changes at the time of accounting reports in the same manner as the shares of the more widely-researched non-bank firms. Apart from finding significant earnings response coefficients in eight countries, we find that credit risk, price risk, exchange rate risk, and solvency risk are significantly correlated with share price changes. Third, three bank risk factors are significantly correlated with unexpected earnings changes. These results are obtained after corrections for several statistical and econometric problems so our reported parameters are robust, certainly more so than in earlier studies using ordinary least square regressions. These new findings extend earnings response literature to several banking sectors, and also identify bank's key risk factors.     

Inventories and the automobile market

This article studies the within‐model‐year pricing, production, and inventory management of new automobiles. Using new monthly data on U.S. transaction prices, we document that, for the typical vehicle, prices fall over the model year at a 9.0% annual rate. Concurrently, both sales and inventories are hump shaped. To explain these time series, we formulate an industry model for new automobiles in which inventory and pricing decisions are made simultaneously. The model predicts that automakers' build‐to‐stock inventory management policy substantially influences the time series of prices and sales, accounting for four tenths of the price decline observed over the model year.     

Strategic price complexity in retail financial markets

There is mounting empirical evidence to suggest that the law of one price is violated in retail financial markets: there is significant price dispersion even when products are homogeneous. Also, despite the large number of firms in the market, prices remain above marginal cost and may even rise as more firms enter. In a non-cooperative oligopoly pricing model, I show that these anomalies arise when firms add complexity to their price structures. Complexity increases the market power of the firms because it prevents some consumers from becoming knowledgeable about prices in the market. In the model, as competition increases, firms tend to add more complexity to their prices as a best response, rather than make their disclosures more transparent. Because this may substantially decrease consumer surplus in these markets, such practices have important welfare implications.     

Collusion with intertemporal price dispersion

We develop a theory of optimal collusive intertemporal price dispersion. Dispersion clouds consumer price awareness, encouraging firms to coordinate on dispersed prices. Our theory generates a collusive rationale for price cycles and sales. Patient firms can support optimal collusion at the monopoly price. For less patient firms, monopoly prices must be punctuated with fleeting sales. The most robust structure involves price cycles that resemble Edgeworth cycles. Low consumer attentiveness enhances the effectiveness of price dispersion by reducing the payoff to deviations involving price reductions. However, for sufficiently low attentiveness, price rises are also a concern.     

Selectivity,Quality Adjustment and Mean Reversion in the Measurement of House Values*

This paper develops a model of price formation in the housing market which accounts for the non-random selection of those dwellings sold on the market from the stock of existing houses. The model we develop also accounts for changes in the quality of dwellings themselves and tests for mean reversion in individual house prices. The model is applied to a unique body of data representing all dwellings sold in Sweden's largest metropolitan area during the period 1982–1999. The analysis compares house price indices that account for selectivity, quality change and mean reversion with the conventional repeat sales models used to describe the course of metropolitan housing prices. We find that the repeat sales method yields systematically large biased estimates of the value of the housing stock. Our comparison suggests that the more general approach to the estimation of housing prices or housing wealth yields substantially improved estimates of the course of housing prices and housing wealth.     

The intraday speed of stock price adjustment to major dividend changes: Bid−ask bounce and order flow imbalances

This paper examines the intraday stock price reaction to substantial shifts in dividend policy. The results indicate the price reaction to be slower than that previously found by Patell and Wolfson (1984) and closer to that found with earnings announcements by Woodruff and Senchack (1988). Possible order flow imbalances are examined by looking at the proximity of transaction prices to contemporaneous bid and ask quotes. While order flow imbalances are evident for bad news announcements, this is not the case for the dividend increase sample. This is interpreted as evidence that the price reaction to major dividend increases are in general anticipated. Fifteen minute holding period returns are computed to measure the movement of equilibrium prices during the announcement period. Results show a rapid adjustment of prices to positive announcements with adjustment to negative announcements taking up to 75 minutes. Finally, fifteen minute lagged bid—ask returns are calculated to determine whether an investor could respond to the announcement and earn positive returns. These results are found to be dependent on the transaction cost assumptions being made.