I adopt a similar method to construct each individual’s exposure to alcohol advertising on television; however, there are some differences. The key difference is that the NCS includes many more television programs and the survey questions about these programs differ based on program type. The NCS provides data on the viewing of nationally broadcast network television programs, cable television programs, regular season sports, and special programs that air infrequently or only once. The Kantar advertising data measure the number of al-cohol advertisements that aired during each program over the whole sample period on all of these media. For broadcast network programming, the Kantar data also indicate whether the ad aired nationally or locally, and, if locally, the DMAs in which the ad appeared. As with print media, I use individual reports on what television each person watches and when. NCS respondents report how many of the last few episodes (four episodes for weekly shows, five episodes for daily shows) of regularly occurring major broadcast network programs (NBC, ABC, CBS, FOX, WB/CW, UPN/MY) that they watched. The survey also asks when re-spondents last watched (if ever) specific regularly occurring cable programs. Rere-spondents also indicate how often they watched regular season sports in the past year. Finally, respon-dents report whether they watched special programming the last time it aired. I use this information as follows:
Nationally broadcast television programs
I match alcohol advertising that appears on nationally broadcast television programs to programs included in the NCS. I generate a probability that a respondent viewed a specific airing of each program. This probability is equal to the number of previous airings the respondent reported viewing divided by the number they could have viewed. For example, if a respondent reports watching three of the last four episodes of Seinfeld, I assign her a probability of .75 that she viewed any one of the last four episodes. I then assume that this probability applies to every airing of that program in the previous six months. For each program a person views, I multiply the number of ads on that program in the six months prior to the survey times the fraction of airings she views. I sum this measure over the all broadcast programs to generate an estimate of exposure to alcohol ads on all broadcast programs.
Regular Sports
The NCS includes questions on how often one watches the regular season sports. The questions refer to particular sports on a specific networks (e.g., CBS College Football and ESPN MLB Baseball and to more generic sports titles (e.g., Bowling and MLS Soccer ).
Similar to broadcast programs, I create the fraction of airings a person reports viewing based on how many times he says he watched the sport in the last year. For each sport, I multiply the number of ads matched to that sports program from the Kantar data times the fraction of airings a person reports viewing to create their total exposure on that sports program. I then sum this measure over all regular sports programming to create the total exposure to alcohol advertising on regular season sports.
Cable television programs
I use a slightly different method to match advertisements aired on cable television programs because the NCS collects different information on cable television viewing and cable networks rerun their programming more often. To address repeats, I use the Kantar data to determine how many times a program aired in a given day. Since I cannot know which airing an individual viewed, I divide the number of ads appearing on every airing of that program by the number of times the program aired that day to create the average number of ads per airing for that day. This approach assumes people are more likely to view one airing of a program a day than watch several repeats. The NCS asks respondents whether they watch
each of approximately five programs for each cable network. The survey tells respondents to indicate whether they watched each program in the last four weeks and if they watched the program in the last seven days. If the respondent reports viewing a program in the last seven days I assume he watch the program every day it aired. If the respondent reports watching the program in the last four weeks but not in the last seven days, then I assume he watches the program half the days it airs. Similar to broadcast programs, I multiply the six month total of the daily average ads on a program times the fraction of days a person watches to estimate the number of ads he saw on that program. I then sum these estimates over all programs a person reports viewing.
Single-event specials
I use a similar procedure to count advertisements placed on single-airing specials (e.g., the Academy Awards) and special sporting events (e.g., the World Series). The NCS asks re-spondents if they viewed each of these special programs the last time they aired. If a person says he watched a special program, I assume he watched the event in its entirety (e.g., every game of the World Series). I include in his exposure measure all alcohol advertisements that aired in his DMA during the special programs he saw.
Taken together, I use all of the above information to measure each respondent’s exposure to television alcohol advertising. The television exposure measure is formally constructed as the sum of the advertisements that appeared on each program a person said he watches.
Thus potential exposure to alcohol television advertisements of respondent i in year t and market m is given by: where subscripts refer to the following: n refers to each nationally broadcast television show;
c refers to each cable television show; r refers to each regular season sports show; and s refers to special shows that aired only one time in a given year. viewimxt measures the fraction of airings of program x viewed by person i. watchimst measures whether person i watched special s the last time it aired.
Comparison Advertising of Television Exposure Measures
In Figure 1.6, I compare the average exposure of NCS respondents to television alcohol advertising with estimated average exposure to ads as computed by Nielsen from Gross Ratings Points (GRP)(CAMY, 2010a). GRPs measure the average number of advertisements a person in a specific demographic group saw in a year. The dashed lines plot Nielsen’s Gross Ratings Points for youth ages 12 to 20 (triangles) and adults ages 21 to 34 (diamonds). The solid line plots estimated exposure for my sample (age 18 to 24) in each year using my NCS data and exposure measure. The exposure measure used in my study tracks yearly trends in exposure closely. While the NCS estimated exposure is, on average, 4.4 times as large as Nielsen’s measure of 21 to 34 year old exposure and 6.6 times as large as the measure of 12 to 20 year old exposure, these difference likely arise because I use NCS time diary questions about television viewing while Nielsen more directly measures what a person watches. Nielsen uses in-home television tracking boxes and can therefore determine exactly which airing of a program an individual views. Though the Nielsen GRP is an average of exposure of all people in the age group in a given year or in a given year and media market, the NCS exposure estimates measure each individual’s exposure. Importantly, unlike the Nielsen GRP measure, the NCS measure does not assign the same level of exposure to every person in a given DMA. Instead I use variation in exposure that arises because individuals differ in their tastes, family composition, and work schedules. These differences cause people to watch different programs at different times. This individual variation in advertising exposure is vital when studying individual consumption behavior. Furthermore, since my measures likely overestimate exposure for all individuals, this difference will be fully captured by the size of the coefficient estimate of the effect of advertising. If the Nielsen GRP measures are taken as truth, scaling my coefficients by a factor of 4.4 to 6.6 would make them comparable to estimates using GRP advertising exposure measures. To further simplify the interpretation of my results, I relate my coefficient estimates in terms of percentage changes in average advertising exposure, which makes scaling unnecessary.
Figure 1.6 compares the average magazine advertising exposure of NCS respondents to similar GRP measures created using Mediamark Research Inc. (MRI) magazine ratings data and Kantar Media28advertising data (Center on Alcohol Marketing and Youth, 2010b).
Because MRI collects magazine ratings data using a survey similar to the NCS, the NCS magazine measure I use in this study is directly comparable to the independent MRI measure.
28Kantar Media was previously known as TNS Media.
Figure 1.6 shows that the NCS estimate measures a sharper decline in advertising exposure over the five year period. The average exposure of the NCS sample I use in this study is most comparable to the 12 to 20 year old MRI GRP measure. Because my magazine exposure measure is close in magnitude to independent measures used in other studies, the magazine advertising effect coefficient estimates found in this paper should be directly comparable.
Figure 1.8: Comparison of NCS and Nielsen GRP Exposure Measures: Television Advertis-ing. Source: 2002-2006 NCS, Kantar Media, and Center on Alcohol Marketing and Youth.
Figure 1.9: Comparison of NCS and Nielsen GRP Exposure Measures: Magazine Advertis-ing. Source: 2002-2006 NCS, Kantar Media, and Center on Alcohol Marketing and Youth.