Advertising and quality in the U.S. market for automobiles.

• Author: Nichols, Mark W.

1. Introduction

   Each year, automobile manufacturers spend millions of dollars on advertising. Between January and September 1995, for example, General Motors (GM) spent $1.07 billion (Crain Communications, Inc. 1996). What function do such large outlays serve, and what is the correlation between these outlays and a vehicle's quality? Do high-quality producers use advertising as a means to signal their quality to relatively uninformed consumers or do low-quality producers take advantage of this information asymmetry and mimic their high-quality competitors, thereby inhibiting advertising's use as a signal? On the other hand, does advertising merely serve an informational role, reminding consumers that a product's recent ancestors proved to be high quality?

   These questions continue to be a perennial debate in economics. While recent game-theory literature thoroughly analyzes advertising's ability to signal quality (reviewed below), empirical evidence is somewhat limited and generally mixed. For example, Caves (1986) and Tellis and Fornell (1988), using the Profit Impact of Market Strategies database (a broad interindustry data set), show that high quality generally induces higher advertising expenditures. In contrast, Caves and Greene (1996), conducting a multiple-product analysis of quality, price, and advertising, find a positive correlation between advertising and quality when examining goods where buyers' experience and search are effective at guiding brand choice but a negative correlation for convenience goods.

   One explanation for these mixed findings is the use of broad cross-sectional data sets and treatment of advertising as a homogenous activity in different markets. Indeed, the findings of Caves and Greene (1996) support the idea that the use of advertising varies across industries depending on market structure, product characteristics, and consumer characteristics and that "empirical studies using individual industries as cross-sectional observations may be economically uninterpretable" (Leffler 1981, p. 46).

   In an attempt to avoid this potential pitfall, the present study employs data from the U.S. automobile market and compares outlays on superior products relative to inferior products for producers of otherwise identical goods, that is, it conducts an intraindustry analysis in order to avoid any potential bias introduced by analyzing multiple-product, cross-sectional data. Nevertheless, even in an intraindustry study there are several confounding factors to consider. For example, consumers' knowledge of the product will influence advertising. Ceteris paribus, greater knowledge about product quality should result in lower advertising expenditures. In addition, there may exist manufacturer-specific factors, such as the number of models produced, that influence advertising. A detailed description of the model and controlling factors employed in this study are provided in Section 3.

   The automobile industry is chosen to conduct the intraindustry analysis because model-specific information on advertising outlays and product quality is readily available. More importantly, however, the quality ratings for automobiles employed in this study are unobservable when a car is new and being advertised. The ratings, which first become available a year after a vehicle's introduction, therefore reflect information on quality that is unknown to the consumer at the time of purchase. This feature, current advertising expenditures and unknown quality, provides a unique opportunity to empirically examine hypotheses offered by the recent game-theory literature on the ability of advertising to signal product quality to relatively uninformed consumers.

   Before proceeding, it should be noted that, while quality ratings on the current model being advertised are unavailable, ratings on a previous model's quality do exist. To the extent that quality ratings are highly correlated over time, past quality may be a reliable indicator of current quality. In short, current quality may not be completely unknown to consumers. If true, advertising's role may be to simply inform or remind consumers of high quality in the past. To distinguish between these two hypotheses (signalling versus information), the current study controls for past quality, examines how changes in the (future) quality rating from past quality ratings impact advertising, and compares advertising and quality for introductory models where no past data exist. The results reveal that advertising is multidimensional and serves both as a signal of quality and a provider of information. Nevertheless, strong support for the signalling hypothesis is found when controlling for past quality and when examining changes in quality. Nowhere in the analysis is it found that low-quality automobiles are advertised more intensively.

   The next section reviews theories on the strategic use and determinants of advertising. Section 3 describes the empirical model and the choice of variables to empirically test the advertising-as-a-signal hypothesis. This is followed by a discussion of the methodology used to derive the results reported in section 4. Section 5 concludes the paper.

2. Theories on the Strategic Use and Determinants of Advertising

   There is a vast theoretical literature addressing the strategic use of advertising and its correlation to quality. Much of this literature focuses on experience goods whose quality is costly to ascertain prior to purchase and is only learned over time with consumption (Nelson 1970). While this literature varies dramatically in its assumptions and conclusions, a central theme is advertising's ability to signal quality to uninformed consumers.

   The origin of the signalling literature can be traced back to Nelson (1970, 1974). In this series of seminal articles, Nelson distinguishes between search and experience goods and the informational content of advertising. In the case of search goods, advertising provides direct, credible information about product characteristics and quality because consumers can verify this information prior to purchase. With experience goods, however, quality is not verifiable prior to purchase. Consequently, claims of high quality lack credibility because they can be freely made by all producers. Realizing this, consumers will rationally ignore any direct claims about high quality. Nevertheless, the consumer can extract indirect information. In particular, the consumer learns that the brand is being advertised. Therefore, in the case of experience goods, it is the level of advertising, not necessarily the information content, that provides information to consumers.

   The mechanism leading to a positive correlation between advertising levels and quality in Nelson's model is repeat purchases. There are two ways that repeat purchases induce a positive correlation between advertising and quality. First, when only high-quality products induce repeat purchases, high-quality producers have a greater incentive to advertise in order to increase demand and expected profits. Second, because high-quality products induce repeat purchases, high-quality producers will wish to distinguish themselves from low-quality producers. For this to occur through advertising, low-quality producers must be unable to recoup the costs of advertising necessary to mimic the advertising strategies of high-quality producers.

   There are subtle, but distinct, differences between these two strategies. In the first scenario, firms are not intentionally signalling their quality. Instead, they are merely trying to increase demand in the initial period in order to induce future sales and increase expected profits. In the second scenario, however, the firm is intentionally signalling its quality to consumers, thereby distinguishing itself from its low-quality competitors. In this latter case, it is immaterial whether advertising has any direct impact on demand.

   More recent studies on advertising as a signal of quality have followed the second scenario, focusing on cost differences between high- and low-quality firms. For example, Khilstrom and Riordan (1984) provide a formal game theoretic model to Nelson's argument where higher fixed, but not marginal, costs for high-quality firms result in advertising signalling quality. This requires that high-quality firms be able to recover their advertising costs (through repeat sales) while low-quality firms cannot and that consumers know enough about cost differences to realize that only high-quality firms can profitably advertise.

   Klein and Leffler (1981) model advertising as a signal of the existence of a firm-specific selling cost and the existence of a price premium. This, too, results in a positive correlation between advertising and quality. In particular, knowing that sunk costs (advertising) are only profitable if the expected future quasi-rents exceed the one-time gain from cheating, that is, providing low quality at the higher price, larger advertising expenditures signal larger price premiums and higher quality.

   Finally, Milgrom and Roberts (1986) extend this literature by providing a model where a monopolist signals quality through both price and advertising or other dissipative expenditures, The extension is perhaps best understood in the context of Klein and Leffler, recognizing that the price premium enjoyed by high-quality firms can be used by consumers to infer quality.

   All of the above studies are valuable contributions to the signalling literature. However, the ability to directly test them empirically is limited. Very little of the signalling literature deals with an oligopoly setting where the actions of rival firms may have an impact on advertising decisions. In fact, Milgrom and Roberts (1986, p. 802) note that "the assumption of monopoly seems natural in this context, at least in comparison with the perfectly competitive alternative. Treating the intermediate case of oligopoly would involve...