Measuring Prices and Price Competition Online: Amazon and Barnes and Noble

Despite the interest in measuring price sensitivity of online consumers, most academic work on Internet commerce is hindered by a lack of data on quantity. In this paper we use publicly available data on the sales ranks of about 20,000 books to derive quantity proxies at the two leading online booksellers. Matching this information to prices, we can directly estimate the elasticities of demand facing both merchants as well as create a consumer price index for online books. The results show significant price sensitivity at both merchants but demand at Barnes and Noble is much more price-elastic than is demand at Amazon. The data also allow us to estimate the magnitude of retail outlet substitution bias in the CPI due to the rise of Internet sales. The estimates suggest that prices online are much more variable than the CPI, which understates inflation by more than double in one period and gets the sign wrong in another.

Are Durable Goods Consumers Forward Looking? Evidence from College Textbooks

Popular wisdom holds that publishers revise college textbooks mainly to kill off the secondary market for used books. While this behavior might be profitable if consumers are myopic, uninformed or have high short-run discount rates (that exceed the publishers'), neoclassical authors have noted that it will typically not be profitable if publishers can precommit not to cut prices and if consumers are forward-looking and have similar discount rates as the publishers; the consumer's willingness to pay for new books falls if they know that they cannot resell their used books. Using a large new dataset on all textbooks sold in psychology, biology and economics in the 10 semesters from 1997 to 2001, we estimate a demand system for books to test whether textbook consumers are forward-looking. The data strongly support the view that students are forward-looking with low short-run discount rates and that they have rational expectations of publishers' revision behavior. When the students buy their textbooks, they correctly take into account the probability that they will not be able to resell their books at the end of the semester due to a new edition release. Conditional on faculty assignment behavior, simulation results suggest that students are sufficiently forward-looking that publishers could not raise revenues by accelerating current revision cycles.

The Effect of Word of Mouth on Sales: Online Book Reviews

We examine the effect of consumer reviews on relative sales of books on Amazon.com and BarnesandNoble.com. We find that 1) reviews are overwhelmingly positive at both sites, but there are more reviews and longer reviews at Amazon.com, 2) an improvement in a book's reviews leads to an increase in relative sales at that site, and 3) the impact of 1-star reviews is greater than the impact of 5-star reviews. The results suggest that new forms of customer communication on the Internet have an important impact on customer behavior.

State Casket Sales and Restrictions: A Pointless Undertaking?

We utilize a new micro dataset of prices of funeral goods and services at individual funeral homes, plus data from the Census to examine the effects of state regulations that restrict entry into funeral goods market. In particular, some states have regulations that allow only licensed funeral homes to sell caskets, while others allow unlicensed retailers, such as Costco, to compete with funeral homes in the sale of caskets. However, as caskets and funeral services are complements, generally purchased in one-to-one proportions, it is not a priori clear that casket sale restrictions can expand the rent extraction capabilities of licensed funeral homes. Our results suggest that when courts lift funeral goods sales restrictions the prices of funeral goods fall but the prices of funeral services rise by nearly as much. Overall, our results support the "one monopoly rent" hypothesis; we do not find that overall funeral home revenues decline when funeral goods sales are lifted.

Free Riding and Sales Strategies for the Internet

We examine manufacturers' decisions of whether and how to offer their products for sale over the internet. Manufacturers that rely on promotion of their products by brick and mortar retailers must consider the possibility that internet retailers can free ride off of that promotional effort. This creates an incentive for manufacturers to limit the availability of their products over the internet and to control the pricing of their products over the internet. We examine three categories of products: fragrances, DVD players, and side by side refrigerators. Our evidence suggests that manufacturers that limit distribution in the physical world also use various mechanisms to limit distribution online. In particular, we find evidence that these manufacturers attempt to prevent the sale of their products by online retailers who sell goods at deep discounts. Furthermore, we show that manufacturers who distribute their goods directly through manufacturer websites tend to charge very high prices for the products, consistent with the hypothesis that manufacturers internalize free rider issues. While our main focus is on free riding, our evidence on pricing practices is germane to the growing literature on price dispersion on the internet.

Risk Taking by Mutual Funds as a Response to Incentives

This paper examines the agency conflict between mutual fund investors and mutual fund companies. Investors would like the fund company to use its judgement to maximize risk-adjusted fund returns. A fund company, however, in its desire to maximize its value as a concern has an incentive to take actions which increase the inflow of investment. We use a semiparametric model to estimate the shape of the flow-performance relationship for a sample of growth and growth and income funds observed over the 1982-1992 period. The shape of the flow-performance relationship creates incentives for fund managers to increase or decrease the riskiness of the fund which are dependent on the fund's year-to-date return. Using a new dataset of mutual fund portfolios which includes equity portfolio holdings for September and December of the same year, we show that mutual funds do alter their portfolio riskiness between September and December in a manner consistent with these risk incentives.

Why Don't Prices Rise During Periods of Peak Demand? Evidence from Scanner Data

We examine the retail prices and wholesale prices of a large supermarket chain in Chicago over seven and one-half years. We show that prices tend to fall during the seasonal demand peak for a product and that changes in retail margins account for most of those price changes; thus we add to the growing body of evidence that markups are counter-cyclical. The pattern of margin changes that we observe is consistent with loss leader' models such as the Lal and Matutes (1994) model of retailer pricing and advertising competition. Other models of imperfect competition are less consistent with retailer behavior. Manufacturer behavior plays a more limited role in the counter-cyclicality of prices.

Promotional Reviews: An Empirical Investigation of Online Review Manipulation

Firms\u27 incentives to manufacture biased user reviews impede review usefulness. We examine the differences in reviews for a given hotel between two sites: Expedia.com (only a customer can post a review) and TripAdvisor.com (anyone can post). We argue that the net gains from promotional reviewing are highest for independent hotels with single-unit owners and lowest for branded chain hotels with multi-unit owners. We demonstrate that the hotel neighbors of hotels with a high incentive to fake have more negative reviews on TripAdvisor relative to Expedia; hotels with a high incentive to fake have more positive reviews on TripAdvisor relative to Expedia

Best Prices

We explore the role of strategic price-discrimination by retailers for price determination and inflation dynamics. We model two types of customers, "loyals" who buy only one brand and do not strategically time purchases, and "shoppers" who seek out low-priced products both across brands and across time. Shoppers always pay the lowest price available, the "best price". Retailers in this setting optimally choose long periods of constant regular prices punctuated by frequent temporary sales. Supermarket scanner data confirm the model's predictions: the average price paid is closely approximated by a weighted average of the fixed weight average list price and the "best price". In contrast to standard menu cost models, our model implies that sales are an essential part of the price plan and the number and frequency of sales may be an important mechanism for adjustment to shocks. We conclude that our "best price" construct provides a tractable input for constructing price series.

The "CAPS" Prediction System and Stock Market Returns

We study the predictive power of approximately 2.5 million stock picks submitted by individual users to the “CAPS” website run by the Motley Fool company (www.caps.fool.com). These picks prove to be surprisingly informative about future stock prices. Indeed, a strategy of shorting stocks with a disproportionate number of negative picks on the site and buying stocks with a disproportionate number of positive picks produces a return of over nine percent per annum over the sample period. These results are mostly driven by the fact that negative picks on the site strongly predict future stock price declines; positive picks on the site produce returns that are statistically indistinguishable from the market. A Fama French decomposition suggests that these results are largely due to stock-picking rather than style factors or market timing