DETERMINING TELEVISION


                      Benjamin J. Bates

  Paper presented at the 33rd International Communication
Association conference, Dallas TX, May 1983.
                                                               Previous work has identified various factors as
                                                            contributing to the setting of television rates, without
                                                            giving indication or empirical verification of the
  A revised version was published as:
Bates, Benjamin J. "Determining Television Advertising      manner or size of such effects. This study proposes that
    Rates." In R. N. Bostrom (Ed.), Communication           such quantification of effects upon television spot advertising
    Yearbook 7 (pp. 462-475). Beverly Hills: Sage, 1983.    rates can be achieved through the development of a
                                                            predictive model for such rates over time. Using
                                                            multiple observations from the period 1973-1981, the
  Contact Info:                                             development of such a model provided strong evidence that the
  Benjamin J. Bates                                         identified factors, and the factor of inflation, did affect
  School of Journalism & Electronic Media                   the setting of spot rates. In addition, the examination of
  University of Tennessee                                   rates over time permitted the application of analysis of
  Knoxville, TN 37996-0333                                  covariance techniques which indicated that the effects of                                           certain factors had significantly changed over that period.
DETERMINING TELEVISION ADVERTISING RATES                            the station's broadcast frequency. While providing empirical
                                                                    evidence of effects, the work was limited in that the model did
    Commercial television stations are, for the most part,          not directly consider advertising spot rates and was limited to
supported through the sale of a part of their broadcast             the examination of a single year. French & McBrayer (1979),
schedule to advertisers. This time is sold primarily in the         in a qualitative article looking at the factors which determine
form of short spots interspersed among the stations'                station spot rates, found local market rates to be strongly
entertainment programming. As the supply of these spots is          influenced by three major factors: demand, competition, and
fairly constant, the rates which stations charge for these spots    ratings. And demand, they stated, was largely determined by
in their schedule are quite dependent upon the demand among         the size of the market and local economic conditions.
advertisers for those spots. Since the aim of advertising is to         This study will involve the empirical verification and
convey a message to an audience effectively, and television is      measurement of those factors cited in the previous studies,
essentially a medium to reach an audience, the demand for           namely the size of the market, the quality of the market, local
advertising on a station will be dependent upon the audience        economic conditions, the direct competition from other
that advertising message reaches.                                   commercial stations in the market, differences in station
    That is, since advertisers are actually purchasing access to    coverage, the network affiliation (if any) of the station, and the
an audience, it is expected that the price that advertisers would   broadcast band in which the station operates. It will refine the
be willing to pay for that spot will depend upon that audience.     cited factors where appropriate, define reasonable measures,
Therefore the price that stations are able to get for their spots   and then examine the possible effects of those measured factors
will depend on the audience that stations can attract for those     upon the rates for television spot advertising.
spots. In previous studies over the last fifteen years, a number        It is not the goal of this project to provide a deterministic
of audience factors have been identified as contributing to the     model of the rate setting process and proclaim its validity. The
determination of prices for broadcast time on television.           actual manner in which rates are set are too indistinct, relying
    In 1967, W. T. Kelley undertook a survey of broadcast           more upon instinct and response to market forces rather than
managers in the Philadelphia area, and found that market size       specific models or formulae. However, such processes are
and quality, station coverage, and competition were all major       likely to involve non-concrete consideration of certain key
factors which were considered in the rate-setting process.          factors. By modeling the apparent relationship between these
Kelley did not, however, provide any evidence or proposals as       factors and rates, it is possible to provide hard evidence in
to the manner in which these factors contributed to the             support of the role such factors play in the determination of
determination of rates. In an 1976 article, S. M. Besen             advertising rates. The goal of this research is to provide such
attempted to fill this gap in part by deriving an empirical model   evidence.
for the value of television time. Using pure, or block, time            METHOD
rates as the dependent variable, Besen's model included                 As the factors that this study addresses are considered to be
measures of market size, competition, network affiliation, and      determinants of spot rates, it was decided to base empirical
analysis upon predictive modeling procedures. These would            particular point in time were used, and were noted in
primarily involve the development of linear or essentially           conjunction with that date. The associated date was then used
linear models using a combination of real and categorical            to match the rate information with other dated measures.
(indicator) variables. As the various studies made no proposals          A second dependent variable was constructed by adjusting
or predictions as to the nature of effects, this modeling process    the rate data for the effects of inflation. The adjustment was
would not be directed towards the determination of a single          made through the use of the Consumer Price Index (as
predictive model for advertising spot rates. Rather, through the     advertising spots were considered to be finished goods) in an
model building process and the consideration of alternative          attempt to render the rates collected over time comparable. As
models, those factors having a general significant impact can        will be pointed out in the analysis section, this attempt was
be identified, and general indicators of the particular effects      only partially successful.
determined. The appearance of effects of similar size and type           The measurement of some of the cited factors as
across models would, in fact, reinforce the significance and         independent variables was quite straightforward. Reports of the
validity of a factor in the setting of rates.                        network affiliation and broadcast frequency of stations were
   It was also decided to model this process over a period of        obtained from the TV Factbook and Broadcasting Yearbook.
time. Consideration of the factors and rates over time would         A simple nominal measure was constructed to indicate whether
allow for the reliable examination of the general significance of    a particular station's frequency, or channel, assignment was in
the factors without restricting the validity of the procedure and    the UHF or the VHF bands. A nominal measure was also
the results to a single period. In addition, the presence of         constructed to indicate the primary network affiliation of the
multiple observations from a single station could allow for the      station, if any.
direct consideration of a factor's effect as well as reflect the         A consideration of the factors cited by the three studies
possible presence of additional explanatory factors. Further,        reveals the need for the refinement or addition of another
the examining of rates over time would allow for consideration       factor, as the size of the audience for a message or station is not
of possible changes in the size or significance of the various       directly considered. The factor of audience size would seem to
factors' effects over time, and the possible identification of       be the single most important factor in differentiating audiences,
trends.                                                              and thus the demand for broadcast spots, yet it is not directly
   The measures used for this analysis were constructed to take      cited in those three previous studies. It would appear,
advantage of data which are generally available. For the basic       however, that indirect consideration was given to audience size
dependent factor of rate, or the price of television spots, it was   in the inclusion of the market size factor, though reliance on
decided to use the highest rate quoted for a thirty second (:30)     that measure alone presumes that all stations in the market
television spot, as reported in the annual editions of either the    cover that market both fully and equally well. Both of
TV Factbook or the Broadcasting Yearbook. As these rates             these assumptions are generally suspect, leaving an audience
were to be collected and analyzed over a period of time, only        size measure of questionable reliability and validity. Some of
those rates which could be reliably determined to be valid at a      the studies attempted to rectify this condition with the added
consideration of the factor of station coverage differences,       provide competition for broadcast spots, although they did
removing major problems, but still leaving the consideration of    provide some competition for audience. The station's
audience size to indirect means.                                   competition in the market, however, will also affect audience
    Thus, it would seem appropriate to include the factor of       size, as it reflects the number of stations which must share the
audience size among the potential factors affecting television     potential audience. That is, the actual audience for a station
spot rates. This factor's inclusion in the analysis is not only    will be a share of potential audience, and that share is
theoretically indicated, but it should also provide for a more     determined in large part by the competition a station faces.
reliable analysis and relieve any confounding of those factors        This leaves only the rather ill-defined factors of market
which vary with station coverage.                                  quality and local economic conditions which had been cited
    It was decided to measure audience size through the use of     in earlier studies. One aspect of both factors which should
the Average Daily Circulation (ADC) for the station for a          also be of particular interest to potential advertisers would be
given season, as measured by Arbitron and reported in the TV       the wealth of the market; the ability of those in the audience
Factbook. While not giving a specific measure of absolute          to actually purchase the advertised goods or services. One
audience at any given time, the ADC is a reasonably valid          widely available measure of this ability to buy is the
and reliable indicator of the number of households who can,        Effective Buying Income (EBI) measure, as developed and
and do, watch that station regularly over a period of time.        reported by Sales & Marketing Management, Inc., in their
Thus, it can be considered a good measure of the potential (or     annual Survey of Buying Power. For this study, a scaled,
likely) audience for any station.                                  relative measure based upon the median market EBI was
    The measurement of several other factors depended to a         constructed. This market quality measure segmented the
certain extent upon the specification of television broadcast      median market EBI as to whether it was, in comparison with
markets. For the purposes of this study, it was decided to base    the national median, over 20% above, between 5-20% above,
market definitions upon those used by Arbitron, as reported in     within 5%, between 5-20% below, or over 20% below.
the Broadcasting Yearbook, only treating Arbitron's                   A second measure of market quality was included, in the
"supplemental" markets as separate markets. From this basis,       form of the forecast growth rate for the market. These
the factor of market size was measured relatively by the rank of   forecasts, in the form of the projected growth in households in
the market as reported by Arbitron for a season in the middle of   a market, were also obtained from the annual Survey of Buying
the data collection period, resulting in an ordinal measure.       Power volumes, and the rates scaled and segmented in the
Unranked markets were arbitrarily assigned ranks falling below     same manner as the EBI measure. It should be noted that the
the lowest of the ranked markets.                                  precise market definitions used in the Survey of Buying Power
    The factor of direct competition from other stations was       measures did not always precisely match those of Arbitron,
measured by the number of commercial television stations           although in all cases the major population center(s) were in
licensed and operating in the market at the given date.            accord.
Noncommercial stations were not included as they did not              All measures were obtained on an annual basis where
needed to match the dependent variables obtained for                the dependent variables, tending to confirm the importance
commercial stations within the continental United States over       and significance of this factor in the setting of television spot
the period 1974-1981. It should be noted, however, that valid       rates. High correlations were also found for the initial
rates were obtained from these sources for earlier periods, and     variables measuring the factors of market size (MKT), station
those rates reported for 1973 were also included, along with the    competition (COMP), the date of the observed rate (YEAR),
corresponding measures of the independent variables. An             broadcast band (UHF), and one of the market quality
additional variable was then constructed to denote and label the    measures (EBI). It should also be noted that there was a
stations for which data were collected and included for             significant amount of cross-correlation among the
analysis. The resulting data set was then restricted to those       independent variables as well.
data from stations for which at least four observations of rates                             [Table 1 about here]
were reported over the collection period. This yielded a set of         The high correlation of audience size with rates
856 observations from a total of 164 stations for preliminary       suggested the initial appropriateness of regression
analysis. Later, the data set was expanded to include               procedures in the modelling process. As there was no
observations from other stations in the same markets as those       initial reason to assume the inherent linearity of the
in the initial set of observations. This second, expanded data      relationship between audience size and spot rates, it was
set included a total of 1068 observations from 232 stations.        decided to examine a variety of essentially linear
    ANALYSIS                                                        regression models. An examination of the plot of RATE
    The analysis for the significance of the cited factors began    vs. ADC indicated the likelihood of an exponential
as an exploratory data analysis leading to the development of       relationship. To include the consideration of these types
predictive models for spot rates. First, the data sets were         of relationship in the modeling process, variables for the
examined to identify the significant predictive factors for         natural logarithms of RATE (LNRATE), ADJRATE
television spot rates. Note was taken of the different types of     (LNADJ), and ADC (LNADC), and the computation of
measures used to derive the various independent variables, and      regressions involved the original as well as transformed
those initial measures were treated or transformed where            variables.
appropriate to fit the kinds of effects or relationships revealed       These regressions, which are summarized in Table 2,
in these exploratory procedures.                                    indicated that the regression procedures "explained" about two-
    The analysis began with an examination of the cross-            thirds of the variation in spot rates between stations and over
correlation matrix among the ten variables. Several of the          time. These regressions also suggested the relative validity of
measures evidenced a correlation with the dependent                 the adjustment for inflation and the appropriateness of the
variables of spot rates (RATE) and the spot rates adjusted for      logarithmic transformations, in that an examination of the R2
inflation (ADJRATE). Those correlations greater than 0.1 are        statistic indicated that the models employing those adjustments
listed by factor in Table 1. A highly significant correlation       provided a better fit to the data than the models without the
was evidenced between the audience size measure (ADC) and           adjusted variables. The validity of these "essentially linear"
models was further supported by the analyses of the residuals        seemed invalid, particularly in comparison with the
resulting from these regressions, as those residuals evidenced       multiplicative effects presumed in the other models.
less systematic effects.                                                                      [Table 3 about here]
                          [Table 2 about here]                          It seemed that a fairly firm basis had been established for
    While the use of the audience size measure in essentially        the determination and development of predictive models for
linear models "explained" a great deal of the variation in rates,    spot rates in television. At this point, the remaining factor
it also left some to be explained by other factors. The              measures (such as affiliation, competition, and market size and
residuals of these regressions were examined, and all showed         quality) were molded, where necessary, into a set of indicator
a high correlation with the YEAR variable, even those coming         variables which would demonstrate their significance to the
from models using the adjusted rates as dependent variables.         model, and thus their role in the determination of rates. The
This correlation with time, in fact, was in all cases higher than    precise derivation of the indicator variables for the nominal
the correlation with any other single factor.                        and ordinal measures was accomplished through an iterative
    This finding was somewhat of a surprise, as it was               procedure of model-building and residual analysis.
surmised that correcting for inflation would remove any such            This procedure involved the construction of models which
effects in models using the adjusted rates. The manner in            included the factor in question, then fitting the same model
which the YEAR variable appeared to contribute to the                without that factor. Examination of the resulting residuals was
determination of price indicated, however, that while adjusting      then used to indicate the manner in which the factor under
for the effects of inflation was appropriate, the Consumer           development contributed to the original predictive model.
Price Index was not a good measure of inflation in television        Separate indicator variables were then constructed to mirror
spot advertising rates.                                              that effect. In addition, it should be noted that as factors were
    Thus, the factor of time, as measured by the YEAR                converted to indicator variables, the appropriateness of those
variable, was entered into all of the developing models,             constructed variables were checked by repeating the above
resulting in a series of multiple regressions which are              process.
summarized in Table 3. All the resulting linear models proved           After the iterative procedures were used to develop the
to be significant predictors of rate, both when considered in        appropriate variables, a series of stepwise regression
toto and by variable. The addition of the YEAR variable              procedures was used to identify the significant indicator
increased in all cases the predictive power of the model,            variables within the various model permutations. With the
resulting in one case of a model which explained over 80             focus on the transformed, multiplicative, models, the effects of
percent of the variation in rates. At this time, it was decided to   the individual indicator variables upon the prediction of rates
remove the linear, additive, models from further analysis. Not       were assumed to be multiplicative, resulting in what could be
only was the inappropriateness of these models suggested in          considered to be either a bonus or a discount associated with a
the analyses of residuals, but the presumption of constant           certain state of the basic factor. As the procedure involved the
additive effects for the factors which the model implied also        consideration of multiple models, both a forward and
backwards selection procedure was instituted in the stepwise          measure in the models. This was not totally unexpected, as the
regressions, resulting in the consideration of eight separate         use of transformations placed differing emphases on certain
linear models, with multiple R statistics running between             ranges of audience size, and the ADC and market size factors
.83510 and .92080. A brief summary of these models, fitted to         were highly correlated. Still, there was evidence of a separate
the data set of 1068 observations, is given in Table 4.               effect accruing to the market size factor, although for one
                          [Table 4 about here]                        treatment that effect was of marginal significance.
   The effects of station affiliation were apparent in all eight         The factor of station competition was also found to have
models. In all cases, independent stations were found to have         significant effects towards the prediction of spot rates, though
significantly lower station rates than other stations. Rates for      the size of these effects also varied somewhat with the
independent stations were about half of those for network             particular treatment of the audience size measure. In
affiliated stations with similar audiences. In addition, spot rates   particular, a bonus of around 20 percent for all stations in
for NBC affiliates were found to be uniformly about 10%               markets having at least four stations was indicated, although
lower than the rates for affiliates of the other two major            no statistically significant difference was noted for markets of
networks, when all other factors were taken into account. No          four, five, six, or more stations. That is, although rates were
significant difference was found between ABC and CBS                  generally higher in those markets with at least four competing
affiliation in any of the models. An indicator variable was also      commercial television stations, no additional increase was
used to distinguish the affiliates of the Spanish International       then noted for the addition of other stations to the market. This
Network (SIN), and this variable was found to make a                  result was fairly uniform across models. Differences in station
significant contribution to the prediction of spot rates in all but   rates were also noted between stations with one, two, and
two of the models. Also, SIN affiliate rates were significantly       three competing stations, although the size of these effects
different from those for the other network audience (ceteris          evidenced greater variation. This, again, was not totally
paribus) for half of the models, and only marginally significant      unexpected, as the number of stations in a market is highly
with opposite effects for the other half. This variability was        correlated with market and audience size.
possibly due to the small number of observations from SIN                The two measures of market quality also proved to make
affiliates, and the limitation of the SIN affiliates to the largest   significant contributions to the predictive models, which
markets.                                                              indicated the presence of some effect upon station spot rates,
   Significant effects for the factor of market size were found       although the precise nature of that effect varied from model
in all but two of the predictive models. The market size              to model. In all cases, however, the basic effect indicated
measure was segmented into three groups through the use of            was that stations in markets with higher EBI or higher
indicator variables: the top twenty five markets, the next            growth rates were able to get higher prices for their spots,
twenty five markets (ranks 26-50), and all other markets. The         with effects in the range of ten percent.
size, direction, and significance of these indicator variables           Finally, examination of these linear models indicated that
differed greatly for the two treatments of the audience size          stations in the VHF band were able to charge higher rates for
their spots than stations situated in the UHF band, but this        indicated that that portion of the model remaining was possibly
bonus was uniformly less than ten percent. Thus, the                not uniform over the period. That is, the statistics indicated the
consideration of the multiple models confirmed the                  likelihood that some or all of the modeled factors' effects may
significance of the cited factors in the determination of           have changed over time. The analysis of covariance procedure
television spot rates, although the effects did not appear to be    used provided for, along with the general model estimation, the
uniform across models for all factors.                              fitting of separate models for each of the covariate values. This
   For a final estimation of the specific size of the effects, it   provided estimates of coefficients for each year.
was necessary to pick out a specific predictive model. On the           Several interesting developments emerged from a
basis of predictive power and other indicators of fit such as       consideration of these estimated coefficients. First, it appeared
residual analysis, it appeared that the best predictive model was   that there were statistically significant differences among the
that using LNRATE as the dependent variable and LNADC as            fitted coefficients for most of the factors, in the sense that
the primary independent variable. The specific estimations of       either some coefficients could not be statistically distinguished
coefficients, and thus effects, are given in Table 5, along with    from zero (indicating the possibility of no effect), or that one or
the appropriate statistical measures.                               more of the estimates greatly varied from other years'
                         [Table 5 about here]                       coefficients for that variable. While some of this may have
   As a further indication of the type of effects evidenced by      resulted in part from the small sample size of some component
these factors, a series of analyses of covariance models was        factors, enough regularity in the pattern of estimates remained
also derived from the enlarged data set. These models allow         in some cases to indicate some interesting relationships in the
for the examination of the fitted models on a year by year          model.
basis, and allow the consideration of the uniformity of effects         First, it was noted that the effect of the broadcast band
over time. As the relatively small number of observations from      factor effectively disappeared after 1976. Uniform, significant
certain years made estimation impossible due to problems of         coefficients were estimated for the corresponding indicator
singularity, the analysis was restricted to the period from 1975    variable for 1975 and 1976, but in all following years the fitted
to 1979, inclusive, using the expanded data set of 1068             coefficients were an order of magnitude lower, and could not
observations. With the restriction, the data set for analysis was   be reliably distinguished from zero. Thus there was no
reduced to 812 observations. Further, the consideration of the      evidence that a station's frequency had an effect upon the
analysis of covariance findings will be restricted to the           determination of its rates after 1976.
LNRATE-LNADC model which was selected as the "best"                     In a similar vein, there seemed to be a change in the size of
predictive model for television spot rates.                         the effects attributable to station competition over time.
   The basic analysis of covariance table yielded several test      Specifically, the coefficients for the indicator variable
statistics which indicated the validity of this approach. While     reflecting those markets large enough to field an independent
these statistics indicated the general significance of the          station (i.e. four or more stations) evidenced two distinct
predictive model and of the covariate YEAR, they also               levels. There appeared to be a sizeable effect for that factor
until 1978, when the effect was about half that estimated for       basis for that verification. While not specifically implying
the previous three years.                                           causation in the direction of factors to rates, the unlikelihood of
   The analysis of covariance also indicated an interesting         rates affecting factors such as broadcast frequency, audience
elaboration of the effect of station affiliation with NBC which     size, and station affiliation infer an asymmetrical relationship
had been noted in the earlier models. The results of this           in the other direction. That is, the presence of such an effective,
procedure indicated that there seemed to be no significant          useful, predictive model supports the claim that the factors
difference in rates among network affiliated stations until 1977,   represented by the variables in the model do have some sort of
when the "discounting" effects of NBC affiliation began. In         effect upon the setting of television advertising rates.
fact, the coefficient for the NBC indicator variable showed             In the general models, some effect was indicated for all of
steady increase from that point, indicating a worsening of the      the factors mentioned in the earlier studies by Kelley(1967),
relative position of NBC affiliates. This, it should be noted,      Besen(1976), and French & McBrayer(1979). Specifically, the
coincided with the dramatic fall of the effectiveness of NBC's      empirical study of spot rates indicated the following general
prime time programming in attracting audience and the               and specific effects.
resultant fall of NBC to a distant third in the ratings race.           The factor with the greatest effect upon the determination
   Another regularity which was noted was the overall               of spot rates in television was the audience size. This effect
consistency of the the market quality measure EBI. While the        was strong, and was fairly consistent, explaining on its own
individual coefficients showed a fair amount of variability, the    roughly two thirds of the variation in rates between stations
overall effect noted from high to low values remained fairly        over time. The second most important factor found in the
consistent. The consistency of the other market quality             study, time, was not mentioned specifically in the earlier
measure, household growth, was not as evident.                      research. It is a factor, however, that would only show up in a
   The coefficients for the other indicator variables, and the      consideration over time. The interesting result of this analysis
real audience measure LNADC, remained fairly consistent. As         was not only the affirmation of the importance of considering
no other general pattern in the estimated coefficients emerged,     inflation over time, but the models' indication that the rate of
they were judged to have had consistent effects over the period     inflation in television spot advertising rates was roughly twice
1975-1979.                                                          that indicated by the Consumer Price Index over the same
                                                                    period. Inflation in spot rates, the model estimated, ran about
   CONCLUSIONS                                                      19 percent a year over the period for which data were
   The goal of this research was to provide quantitative            collected.
verification of the role of certain specified factors in the            The remaining contributions to the predictive models were
determination of television spot advertising rates. The             made by indicator variables. It should be noted that the
development of a predictive model accounting for about 85           possible confounding of market size with a number of the
percent of the variation in spot ad rates over a period of eight    indicator variables, such as those for the factors of competition
years for a group of 232 stations across the U. S. serves as the    and market quality, acts to restrict the kind of conclusions
which can be drawn. In addition, the differing strengths of the      appearances, this is not an unexpected finding. The audience
contributions to the predictive model made by the indicator          size measure is more a measure of potential audience than
variables for separate aspects of factors make any specific          actual audience, so the amount of competition will then
statements about relative strengths of those factors' impacts        indicate how close potential and actual audience is to be for a
difficult.                                                           station. That is, the ADC measure for a station with no direct
    Having mentioned the appropriate caveats, the following          competition (i.e., located in a single station market) is apt to
conclusions and interpretations are offered. The factor of           match the actual viewing audience for that station, while the
station affiliation proved to be fairly significant in the           actual viewing audience for a station with competition is likely
determination of station rates, particularly in the distinction      to be only a fraction of the ADC (potential audience) measure.
between network and non-network affiliates. This may have            Thus, the pattern of discounts and bonuses for the set of
resulted in part from the relative accuracy of the audience size     indicator variables is not unexpected. The effects
measure, ADC, as an indicator of prime time audience for             demonstrated through these independent variables may reflect
stations. Traditionally, and for most markets, independent           the differences between a station's potential audience and their
stations are not equal competitors with network stations during      actual share of prime time audience.
that time, as the strength of independent stations in attracting         It should be noted that for the final predictive model, the
an audience lies in periods outside normal prime-time,               discount for the single station market was actually less than
whereas prime time spots usually yield the highest rates. Thus,      that for the two station market, indicating that there was likely
the audience size measure upon which rates are predominantly         to be some monopoly benefit accruing to stations without
based is apt to be skewed for independent stations as a result       competition. However, the nature of the variables and
of their apparent inability to compete on an equal basis with        measures used did not allow for a precise separation of effects.
network affiliates during prime time.                                It should further be noted that the number of stations in a
    This may also explain the finding of the growing difference      market is confounded with market size, further clouding the
in rates for NBC affiliates. The models indicated that, over the     precise nature of this effect.
sample period, NBC affiliates generally earned less than ABC             Lesser effects were noted for the two market quality
or CBS affiliates. In fact, the analysis of covariance indicated     measures. Stations in markets with higher than average
that this was a growing difference over the period from 1975 to      Effective Buying Income measures tended to have higher rates
1979, roughly matching that period when NBC was not                  than stations in markets with lower than average measures. The
competing on an equal basis during prime time impact upon            bonus accruing to those stations ranged between seven and ten
station rates, at least when measured in terms of the number of      percent in the various predictive models. As for the growth
commercial television stations licensed to a market. In general,     measure of market quality, that also showed some effect in the
the models indicated that the more competition, the higher the       predicted direction, with stations in markets with significantly
rates in a market, at least to the point where there were at least   higher growth rates (20 percent above the national rate) having
four commercial stations in the market. Despite initial              about a ten percent higher rates than stations in other markets.
It should be noted that these differences showed up only in           restrictive measurement of market size.
those markets with extreme differences in growth rates from              In summation, it appears reasonable to reach the following
the national average, indicating that this measure is likely          conclusion from this analysis. First, that the factors of
considered only subjectively in the determination of rates.           audience and market size, station competition, station
    There did appear to be a UHF/VHF difference in the                affiliation, broadcast band, and market quality/local economic
rates charged by stations for spot advertising. This effect           conditions did have some kind of influence in the
was small, however, amounting to only about a seven                   determination of television spot advertising rates. A listing of
percent difference, and did not contribute a great deal to            these factors, ranked by their relative importance of their
the explanatory power of the models. In fact, the                     contribution, is given in Table 6. Second, that there has been
separate analysis of covariance indicated that this effect            inflation in spot rates, and the rate of that inflation has been
seems to have disappeared after 1976. The                             about twice that of the CPI. And last, but not necessarily least,
disappearance of effect can possibly be traced to the rise            that the effects of factors upon rates need not be, and have not
of cable systems in fringe areas, where the signal                    been, constant; that changing conditions may diminish or even
strength differences (resulting in differing picture                  invalidate the significance of specific factors, or bring forth
quality) are greatest, and the resultant diminishing of               new factors to consider in the determination of rates.
qualitative differences between UHF and VHF stations                                            [Table 6 about here]
which might result in differences in audience and thus
the rates stations can charge for their advertising spots.
    Finally, there is the consideration of the market size, which
was presumed to have been largely dismissed by the                    BIBLIOGRAPHY
consideration of the audience size. The development of the
predictive models did indicate directly (and possibly indirectly)     Besen, S. M. "The Value of Television Time."
the presence of a market size factor above and beyond audience           Southern Economic Journal, 42:435-441 (1976)
size. The precise nature of the market size effect indicated by       Broadcasting. Yearbook. (annual)
the model, however, was dependent upon the nature of the              French, W. A., and McBrayer, J. T. "How Television Stations
relationship assumed between audience size and rates in the              Price Their Service." Journal of Advertising, 8:15-18
particular model which was fitted (that relationship being               (1979)
determined by the transformations used). Such differences in          Kelley, W. J. "How Television Stations Price Their
effects, while reaffirming the link between audience and                 Service." Journal of Broadcasting, 11:313-323
market size, also indicates a differential effect at various levels      (1967)
of market/audience size. Should this area be studied further,         Sales and Marketing Management, Inc. Survey of Buying
this is one aspect which should be further investigated, as this         Power. (annual)
procedure was hampered in that regard by a possibly too               Television Digest, Inc. Television Factbook. (annual)
Table 1. Correlations

                                              Correlation with Variable
                                             RATE                       ADJRATE
          ADC                             .7832                         .8502
          MKT                            -.4950                       -.5530
          COMP                            .4558                         .4909
          YEAR                            .2984                         .1936
          EBI                            -.2184                       -.2421
          UHF                             .1387                         .1574
       Note: all the above correlations were significant at the p=.01 level

      Table 2. Initial Regressions

                            Variables                                           R-square
              Rate                              Audience
RATE                                  ADC                             .61352
ADJRATE                               ADC                              .72288
LNRATE                                ADC                              .63199
LNADJ                                 ADC                              .69935
LNRATE                                LNADC                            .66762
LNADJ                                 LNADC                            .73723
    Note: the F-test statistic for all the regressions indicated their significance at a level
    of p<.001

Table 3. Multiple Regressions

        Dependent                                   Independent
 RATE                                        ADC, YEAR                             .67428
 ADJRATE                                     ADC, YEAR                             .74164
 LNRATE                                      ADC, YEAR                             .78342
 LNADJ                                       ADC, YEAR                             .74717
 LNRATE                                      LNADC, YEAR                           .80957
 LNADJ                                       LNADC, YEAR                           .77947

     Note: the F-test statistics for all regressions indicated their significance at a level of
Table 4. Predictive Models

        Variablesa                    Forward Selection                  Backwards Selection
     Rate               Audience      Mult R               R               Mult R               R2

    LNRATE              LNADC         .92049            .84730             .92078              .84783
    LNRATE              ADC           .90951            .82720             .91041              .82884
    LNADJ               LNADC         .90871            .82576             .90910              .82646
    LNADJ               ADC           .89588            .80200             .89689              .80441
Note: the F-test statistics for all models indicated their significance at a level of p<.001
 The stepwise procedure also selected from the full set of indicator variables and the
variable YEAR in all cases

Table 5. Estimates of Effectsa

               Factor      Variable              Partial           Coefficient             T-Stat
                           Constant                                   -.49926       -1.420
    Audience               LNADC                 .70111                .72056       31.906+++
    Inflation              YEAR                  .68332                .17264       30.370+++
    Bdcst Band             UHF'                  .07210                .07094        2.346+
    Network                 INDb                 .37406                .79780       13.089+++
    Affiliation             SINb                 .10242                .45169        3.341+++
                           NBCb                  .12431                .10662        4.0654++
    Competition            ONESTNb               .11455                .16134        3.742+"
                           TWOSTN                .19065                .24874        6.302+++
                           FOUR+-              -.14904                -.19519       -4.891+++
    Mkt Size               TOP25b               -.29171               -.63604       -9.900+++
                           NEXT4               -.12483                -.18446       -4.023+++
    Mkt Quality            HIEBI'              -.07108              -.072008        -2.312+
                            LOEBI                .05862                .05337        1.905
                           HIHHGROb            -.06938              -.054387        -2.2574

  + p<.05                          " p<.01                     +++      p<.001
 With LNRATE as dependent variable, using the backwards
     selection procedure
  Due to the requirements of the particular statistical package used, these indicator variables
were given a value of 1 if true, and 2 if false (i.e. not having the indicated value)
Table 6.Factors Affecting the Determination of Rates
(ranked in order of relative importance)

                       Factor                                   Variables

         1   Audience Size                             ADC, LNADC
         2   Time (Inflation)                          YEAR
         3   Network Affiliation                       IND, SIN, NBC
         4   Market Size                               TOP25, NEXT25
         5 Competition                                 ONESTN, TWOSTN, FOUR+
         6 Market Quality                              HIEBI, LOEBI, HIHHGRO
         7 Broadcast Band                              UHF

To top