Advertising and R&D: theory and evidence from France

Abstract

Advertising and innovation are two engines for firms to escape competition and improve profits. We propose a model that encompasses both the static and dynamic interactions between R&D, advertising and competitive environment. It provides three main predictions. First, for a given competitive environment, quality leaders spend more in advertising in order to extract maximal rents; thus, lower costs of ads may favor R&D. Second, the inverted-U relation between competition and R&D still holds with the introduction of advertising. Third, more competition is associated with on average more advertising expenditures. Empirical evidence from a large panel of 59,000 French firms over 1990–2004 supports these three properties.

Keywords:

• advertising
• R&D
• innovation
• competition
• Lerner

JEL Classification:

• D4
• O31
• D12

Acknowledgments

The authors would like to thank Philippe Aghion, Catherine Bobtcheff, Daniel Cohen, Bruno Jullien and Jacques Mairesse for helpful suggestions on previous versions and participants to seminars at the Banque de France, Paris School of Economics, and the AFSE congress.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1. See Villas-Boas (2004) on the communication strategies and the design of product lines when consumers differ by their preference for quality.

2. In 2004, the overwhelming majority of the French advertising market was on TV, radios, general Press and poster compagnain; Internet share was only 4%. With the rise of internet advertising based on consumers web search, a recent literature (Iyer, Soberman, and Villas-Boas 2005) assumes that firms do have information on these individual preferences. This allows for targeted ads according to consumers' preferences.

3. For alternative models of advertising in a duopoly framework, see Schoonbeek and Kooreman (2007) or Piga (2000).

4. The large literature on dynamic advertising for which the advertising is a state variable assumes that the innovative environment is given (see Huang, Leng, and Liang 2012 for a review). Our paper departs from this literature by studying dynamic innovations that change the nature of the products that are advertised by firms.

5. Since ; let us note that: and .

6. These items have a precise counterpart in the official accounting plan (plan comptable gnral). Advertising comes from category 623, whereas R&D expenditures are the sum of elements in categories 61, 62 and 64.

7. Lerner=(value added−(depreciation cost of capital)*(capital Stock)-provision)/sales. Using the standard mnemonics of French tax forms: Lerner=[VA−(AQ+AS+AU+AW+AY− AQ−1−AS−1−AU−1−AW−1−AY−1)−0.085·capital−(DR−DR−1)]/FL.

8. FIBEN includes balance sheet data only; namely, the value of physical assets that it reports is given at historical costs. Using standard methods based on the depreciation rate, we estimate the average age of capital to adjust for this price effect.

9. See online appendix for a check using non-normalized advertising and R&D expenditures. Note that we should not normalize R&D and advertising by sales as the positive effect of advertising on sales is a key feature of our model that allows us to derive the other predictions. We do find a positive effect of advertising on sales in our data (results not reported), consistent with our modeling choices and the huge empirical literature on this.

10. See Lauga and Ofek (2009) on the interplay between market research and R&D.

11. This is a natural assumption that is supported by our theoretical framework where f is used to measure (the inverse of) competition: see formulas in Table 1 and Figure 3.

12. Indeed .