Analysis of Fixed Effects

It is clear that firm-specific effects reduce the observed durability of advertising. Landes and Rosenfield (1994) attribute the fixed effects to product quality. It is equally plausible, however, that advertising plays a large part in contributing to these fixed effects. Here, this hypothesis is tested by retrieving the fixed effects from

Tables 6.1 and analysing their determinants. This is a sim ilar procedure to that

em ployed by Geroski and Pom roy (1990) in an analysis o f changes in concentration

over tim e.

The methodology is to regress the fixed effect (Fixed,) for firm i on various firm- specific factors: the mean level of log of advertising over the time period; the mean of the log of tangible assets (to control for size effects); indicator variables for whether the firm operates mainly in producer or consumer goods industries. The model is thus:

Fixedj = « 0 + a, log(A)i + « 2 log(Assets)i 4- consumer; -t- producer; + U; (6.9)

Table 6 . 8 presents the results of OLS estimation of this model. In the first column,

the impact of the log of advertising is considered on its own. The coefficient is positive and significant. However, a Ramsey reset test rejects the null hypothesis of no missing variables. Thus, in column 2, a quadratic advertising term is included. This attracts a positive and highly significant coefficient and improves the explanatory power of the model. In other words, advertising seems to play at least some part in explaining the firm fixed effects.

In colunrn 3, dummy variables for the importance of quality^^, consumer and

producer firms are included as well as the log of tangible assets. The latter proves to

^^This variable equals 1 if the firm states that quality is an important form of

be highly significant and greatly reduces the impact of the advertising variables. Of the dummy variables, only that for producer firms has a significant (positive)

coefficient. The importance of quality seems to play no part in the firm fixed effects. Column 4 reports the more parsimonious model which is left after removing variables not significant at the 10% level. The quadratic advertising term is once again highly significant, albeit still of a lower magnitude than in columns 1 and 2.

Table 6.9 summarises the key results of the analysis of the fixed effects in the models where advertising effects are allowed to vary with industry, advertising media and year respectively.

In the case of the ‘industry’ model the consumer and producer dummies are omitted. As a Cook-Weisberg test rejects the null hypothesis of homoscedasticity, adjusted standard errors are reported^\ Due to the omission of industries with less than three firms, the sample size is reduced to 81 and the mean fixed effect is somewhat higher than in the basic model. In this case, both the advertising coefficients are strongly significant, even though the size variable is included.

In the media and year models, the mean fixed effect, and consequently the coefficients, are greatly reduced. In the media model, only the linear advertising effect is significantly positive, whilst in the year model, only the quadratic term is significant. In no case is the coefficient on the quality dummy ever significant at the

1 0% level and in the first two columns it is actually negative.

6.5 CONCLUSIONS

This chapter has investigated some of the dynamics of the adveitising-sales

relationship. In contrast to the other empirical sections of the thesis, it has drawn on panel data which is held for a restricted sample of firms.

Once firm-specific effects are controlled for, the measured effect of advertising on sales seems to be restricted to one year or less. This result is robust to charges of bias due to correlation between the lagged dependent variable and the error terms, to the omission of firms with particularly short time series and to the inclusion of variables to control for capital and employment.

When advertising effects are allowed to vary across 16 SIC two-digit industries, effects which last longer than one year are only found in six industries and are

significant in only two of these. In addition similar results are found when effects are allowed to vary across different advertising media and with time. Only in the case of advertising via direct mail and directories are durable effects of advertising found.

Previous authors have attributed this result to product quality which gives firms an incentive to have high levels of advertising. This chapter has questioned that interpretation by extracting the fixed effects and exploring their determinants.

Advertising seems to be have a positive and significant impact which is robust to the inclusion of other explanatory variables. The importance of product quality in the firm’s market has no impact on the fixed effects. To the extent that this acts as a proxy for firm product quality, this suggests that the Landes and Rosenfield (1994)

imerpretation o f their results is flaw ed. A s advertising is likely to be fairly persistent

over tim e, the conclusion that it plays a large part in firm fixed effects should not be

surprising.

These results also shed some light on the interpretation of the findings in Chapter Five based on cross-sectional data. Advertising is fairly stable over time within firms. This leads to a permanent effect on sales (as shown in this chapter by the analysis of fixed effects) and on profitability (as demonstrated in Chapter Five). Increases in advertising do lead to increases in sales, but this effect is essentially a short run one. In turn, this suggests that an assumption of very low advertising depreciation rates is not appropriate when modelling the advertising-profitability relationship.

Table 6.1: Mean Advertising and Sales by Year

Year Number of Firms Mean Level of Advertising (£m) Mean Sales (£m) 1992 95 3.529 1047.8 1991 104 2.340 760.9 1990 77 2.461 826.5 1989 6 6 2.589 840.0 1988 50 2.459 934.4 1987 38 2.811 1219.0 1986 30 3.562 1896.3 1985 26 1.464 1538.1 1984 19 1.117 851.2 Note:

Table 6.2: Long Run Effects of Advertising on Sales (1) OLS (2) Random Effects (3) LSDV Log (Advertising) .0596*** .0657*** 2724*** (.0139) (.0147) (.0351) Log (Sales)n 9213*** .9127*** 2257*** (.0168) (.0179) (.0609) Constant 5696** .5696 3.511*** (.1385) (.1385) (.2634) Implied Depreciation 8 .2% 9.1% 96.8%

Y ear Effects Yes Yes Yes

Industry Effects No No No SD(Vi) - .0894 1.197 0 - .0590 - N x T 505 505 505 F Statistic 516.16*** - 61.5*** Adj R" 0.9109 - - W ithin R^ - .1446 .2692 Overall R^ - .9126 .6971 Notes: