Health Risk and the Demand for Red Meat

16 Pages·2008·0.39 MB·English

Health Risk andtheDemand for Red Meat: EvidencefromFuturesMarkets
RodneyG.Robenstein;Walter N.Thurman
Reviewof AgriculturalEconomics,Vol.18,No.4.(Oct.,1996),pp.629-641.
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HEALTH RISK AND THE DEMAND FOR RED MEAT:

EVIDENCE FROM FUTURES MARKETS

Rodney G. Robenstein and Walter N. Thurman
The literature on demand shifts for meat This interpretation is at least plausible: medi-
is extensive. Since 1977, a large number of cal science has accumulated evidence that diets
studies have documented instabilities in aggre- high in cholesterol and fat, both found in red
gate meat demand equations estimated from meat, increase the risk of heart disease. How-
time series data. (See Braschler; Chavas; Choi ever, the timing of the public's cholesterol
and Sosin; Dahlgran; Moschini; Moschini and concern is not obviously the same as the timing
Meilke [1984, 19891; Nyankori and Miller; and of the shifts found in empirical meat demand
Thurman.) The modal conclusion from these studies. While most demand studies find shifts
studies is that per-capita demands for red meats, in the mid-1970s, Shekelle and Liu reported
beef, and pork have shifted inwards over time that, as late as 1978, only 13 percent of a
and that per-capita demands for poultry and fish sample of Chicago consumers were aware that
have shifted out. In studies attempting to pin- too much cholesterol or fat in the diet might
point the timing of shifts, the shifts seem to increase the risk of heart attacks. Evidence pre-
have occurred, or to have begun, in the mid-to- sented here shows that firm scientific conclu-
late 1970s. sions as to the link between heart disease and
These studies are not without their critics. cholesterol or fat were not available until the
Chalfant and Alston found fault with the para- early 1980s.
metric conclusions of the structural shift litera- Annual time series data reveals only so
ture; they demonstrated that neither American much about consumer response to health infor-
nor Australian aggregate meat consumption data mation. This study explores an alternative, and
violate the weak axiom of revealed preference. potentially rich, source of information on
Both Wohlgenant and, later, Alston and consumer meat demands: red meat futures
Chalfant argued that perceived structural insta- markets. Contracts for live and feeder cattle and
bility may be due to the use of inappropriate for live hogs and pork bellies afford the oppor-
empirical functional forms. tunity and incentive for traders to register their
Almost no structural shift studies have beliefs about consumer demand. Daily futures
analyzed causes of the shifts.' However, most market data are analyzed to answer the ques-
authors are willing to attribute the shifts to tion: do traders, whose profits depend upon
changes over time in the way that consumers accurately forecasting meat demand, revise their
view the health implications of eating red meat. demand forecasts when significant information
is released on the negative health implications
of eating red meat? This research finds that they
Robenstein is a farm business consultant with the do not.
Illinois Farm Business Farm Management Association.
Thurman is a Professor of Agricultural and Resource
Economics and Professor of Economics at North Carolina
State University. The authors would like to thank Charles
R. Knoeber and participants in the Agricultural Economics
Workshop at North Carolina State University for helpful
comments.
'Two useful exceptions are articles by Brown and conclusion was reached despite the estimation of an
Schrader and by Capps and Schmitz. Brown and Schrader autonomous and negative egg demand trend. Capps and
developed an index of the frequency of occurrence of Schmitz used the same cholesterol information index in a
cholesterol discussion in professional medical journals time series analysis of meat demand. They found that the
and. in a time-series demand model, found that the index was correlated with a negative trend in meat demand
demand for eggs was negatively related to the index. This as well.
Review of Agricultural Economics 18(1996):629-641

Copyright 1996 North Central Administrative Committee
630 REVIEW OF AGRICULTURAL ECONOMICS, Vol. 18>N o. 4. October 1996
Announcement Effects in Red Meat
prices that should be affected by red meat
Futures Markets
health-related information is identified. Finally,
in a series of event study regressions, effects of
A simple story motivates our study and the information releases are analyzed. These
connects consumers' beliefs to observable data: three components are discussed in turn.
the demand for a food product depends, in part,
upon its perceived health benefits. The health Health-related Research Announcements
consequences of eating red meat have been of
The Wall Street Journal is the source of
concern for the last 20 years and, to the extent
cholesterol announcement information. This
that beliefs concerning those consequences have
daily national publication pervades U.S. busi-
changed, one would expect demand shifts to
ness and, because of its extensive coverage of
have reflected those changes. Press reports
futures markets, is likely to be read by futures
about health consequences of red meat refer to
traders.' Relevant articles were located using
scientific studies. Medical researchers are
The Wall Street Journal Index from 1971 to
continually engaged in projects designed to
1987 and the National Newspaper Index from
establish causes of heart disease and the link to
1988 to 1990. In searching for public
eating red meat. Consumers learn of scientific
announcement dates, key words such as "choles-
results in this area in at least two ways. They
terol," "health," "beef," "pork," "cattle," and
learn about the results of research by reading
"hogs" were used.
popular media reports on research projects. In
The article titles and summaries identified
addition, they learn through the advice of their
by the indexes were studied to identify those
doctors. Doctors may change their own beliefs
that discuss dietary cholesterol, blood serum
about the red meat-heart disease connection by
cholesterol, or heart disease, in connection with
reading medical journals but they, too, may
red meat consumption. Relevant articles found
learn from the popular press.
prior to 1983 were sparse and less newsworthy
Whenever there is a release of new infor-
than those after 1983. In fact, no articles were
mation from a professionally credible source, it
found for the years 1973, 1974, 1975, 1977,
will have some impact on the beliefs of consum-
1979, and 1981.
ers and health care professional^.^ If consumers'
After culling irrelevant articles, 52 articles
beliefs are affected by the new information then
remained. Each article was categorized either as
their consumption patterns will be affected as
strengthening the links connecting red meat,
well. If new information serves to strengthen
dietary cholesterol, blood serum cholesterol, and
consumers' belief in the causal relation between
heart disease or weakening one or more of those
red meat consumption and heart disease, then
links. Thirty-three articles strengthen the red
the demand for red meats will shift inward.
meat and coronary disease link and 19 weaken
Such a shift in consumer demand would also be
the link, covering the period 1971 through
reflected in an inward shift in the derived, farm-
1990.
level demand for red meats. To the extent that
A further classification identified each
supply curves for red meats are upward sloping,
article as strong, moderate, or weak. Four
there should be near-term (if not long-term)
characteristics were used to rank the articles.
reductions in prices. The hypothesized release
The four criteria for "strong" articles were that
of information that shifts back demand for red
they: (1) contained actual news; (2) came from
meat over a future period also implies a current
a reliable source; 3) received both a prominent
lowering of red meat futures prices.
size and location in the paper; and (4) took a
The methodology consists of three parts.
firm stand, providing either positive or negative
First, credible new publicly-released information
and the dates near which it became public are
identified' Next' a of futures 'While 7%e WallStreetJ ou.r nal is certainly .not the only
media outlet to which consumers oav attention. it orovides us
, '
with aconsistent daily observation on announcements which is
'Consumers may respond to information from non- indexed. One could expand the analysis in the current article by
credible sources as well. including announcements from other media.
HEALTH RISK AND THE DEMAND FOR RED MEAT Robenstein, Thurman 631
information tied directly to one of the choles- from January 1983 through December 1990 for
terol links in question, especially dietary recom- the live cattle (LC), feeder cattle (FC), pork
mendations referring to red meat. "Moderate" bellies (PB), and live hogs (LH) contracts. To
articles contain information from respectable allow for later testing of long-term versus short-
sources, but failed to maintain one of the other term reactions in the market, prices from both
three ranking characteristics. Examples of the nearby contract and from the contract
"moderate" articles included editorials (not closest to maturing six months from the current
actual news), articles of only one or two para- date were collected. For example, in January,
graphs and not readily visible (possibly over- the nearby month for live hogs is February and
looked because of size and location), and the six-month contract is July.
articles which may mention dietary cholesterol To keep a continuous daily data series, the
and red meats, but concentrate more on drug price from the nearby contract month is rolled
use to lower cholesterol (leaving the signifi- over to the next trading contract month as the
cance of dietary cholesterol in question). nearby contract expires. Since the nearby
"Weak" articles contained at least one of the contract month becomes more noisy as it con-
four ranking characteristics, but tended to be verges to the cash price in the month of expira-
less newsworthy, such as from sources with tion, the nearby contract month is rolled over on
possible vested interests, and were written the first notice day. First notice occurs on the
without a firm positive or negative stand toward last trading day of the month before the expira-
the cholesterol links. tion month for FC, PB, and LH and on the
Of the 52 articles, nine "strong" articles second to last trading day of the previous month
were found, each positively supporting the for LC. For example, the June 1992 contract for
cholesterol links, 14 "moderate" articles with LH would roll over Friday, May 29 and the
nine positive and five negative links, and 30 June 1992 contract for LC on Thursday, May
"weak" articles with 16 positive and 14 negative 28. The six-month contract simply rolls over on
links. Since all the "strong" articles and most of the last trading day when the next trading
the "moderate" and "weak" articles occurred contract becomes a closer approximation to six
after 1982, only those articles between 1983 and months from the current date. For example, on
1990 were considered. Among these 36 articles January 31, 1992 the July 1992 six-month
were nine "strong" articles which positively contract for LC rolls over to the August 1992
supported red meat-heart disease links, eight of ~ontract.~
the 10 "moderate" articles were positive, and Possible differences in short-run and long-
the nine of the 17 "weak" were positive. Be- run effects are accounted for with different
cause none of the "strong" and only two of the versions of the red meat index. One version
"moderate" articles took a negative stand to- includes all four red meat contracts in both the
ward the cholesterol links, negative articles nearby and six-month contracts. Another in-
were not used. The final sample comprised 26 cludes all four red meat contracts, but only in
articles supporting the link between either red the nearby contracts. A third version includes
meat consumption and blood cholesterol, blood the four red meat contracts, but only in the six-
cholesterol and heart disease, or red meat month contracts. If an announcement effect has
consumption and heart disease directly. Because both current and long-term effects, reactions
the categorization of articles is somewhat should be detected in all four versions of the
subjective, the larger sample of 52 articles is index. Otherwise, the longer-term six-month
summarized in the Appendix. index should pick up announcement reactions
that the nearby index does not, or vice versa. A
Portfolios of Red Meat Futures Contracts and fourth version of the red meat index includes
a Market Index both live cattle and feeder cattle in the nearby
and six-month contracts but excludes the pork
Daily futures price data were collected for
red meats traded on the Chicago Mercantile
4When measuring price changes, it is inappropriate to
Exchange. The data consisted of daily closes
include roll-over dates. so they are dropped from the sample
632 REVIEW OF AGRICULTURAL ECONOMICS, Vol. 18, No. 4, October 1996
contracts. Because beef consumption falls more
dramatically in the 1980s than pork consump-
tion, this portfolio is used to study specific
effects that announcements may have on beef where ri,=rate of return on the ith contract on
demand. day t, In pi,-natural log of the price of the ith
contract on day t, and In p,,,=natural log of the
Event Study Regressions price of the ith contract on day t-1. The rate of
return on the red meat index is then calculated
The methodology in this study was first
as:
applied by Fama et al. (FFJR). FFJR maintained
the following market model:
where k is the number of contracts included in
where R,,-rate of return on security i at time t,
the red meat index.
M,=rate of return on the market index at time t,
To test effects of announcements on red
and e,,srandom error for security i at time t.
meat futures, a regression model based on the
In this study, the Commodity Research
structure proposed by FFJR is formed which
Beureau (CRB) index serves as the market
includes dummy variables to indicate announce-
index.' The role of the individual security is
ment dates and the 20-day periods before and
played by a portfolio of red meat futures con-
after:
tracts. The market model is adapted to control
for uninteresting market-wide influences on red
meat futures prices. The sensitivity of the return
of security (futures contract) i to the return on
the market index reflects co-movements among
the commodities. Correlated movements among
where AD, equals 1 on the 26 announcement
the commodities may indicate normal adjust-
dates; BEF,, equals 1 on the ithd ay before the
ments to macroeconomic influences such as
announcement; and AFT,, equals 1 on the ithd ay
interest rates, inflation, strength of the U.S.
after the announcement. Rates of return com-
dollar, exports, and supply shocks. Conditioning
puted from the red meat and CRB indices are
on the CRB index increases the power of tests
used for Rt and MI.
by holding constant futures price variation
If the announcement date, when AD,
clearly unrelated to health announcements.
equals 1, was the only date on which an effect
The rate of return on the red meat index occurred, then p, would be expected to be
is constructed such that an equal dollar amount
negative and all the y,'s and 0,'s to equal zero.
is invested in each of the four red meat futures
However, information may be leaked to the
contracts: live cattle, feeder cattle, pork bellies,
market before the announcement date or mar-
and live hogs. The portfolio is rebalanced daily.
kets may not digest the announcement instantly.
The return on this portfolio is calculated as
For these reasons, a 20-day window on either
follows. First, a daily return on a particular side of the announcement is introduced. The
contract is defined as: sum of p,, the y,'s, and the 0,'s is the regression
estimate of the cumulative impact on returns
from a single announcement.
'The index "is an unweighted geometric mean of the
To test announcement leaks or delays
individual price relatives of 27 (changed to 21 after 1986)
commodity futures prices. ... The current price value in the measured in months rather than days, a monthly
index for each commodity is found by averaging all futures futures returns model also is analyzed. The
contracts up to, but not including, those that mature twelve
monthly returns model estimated is:
months in advance ofthe present date" (Commodity research
Bureau, 1984. p. 38). The ratio of current prices to the 1967
annual average price (1967=100) ofeach commodity completes
the CRB calculation. See the Appendix for a list of contracts
included in the CRB index.
HEALTH RISK AND THE DEMAND FOR RED MEAT Robenstein, Thurman 633
where R, and M, now represent monthly rates of change in the red meat index when RRM,,
return on the appropriate indexes; AM, refers to RNB,, and R6Mt are used and a 0.25 percent
an announcement month dummy variable; and increase if RCAT, is used. Since the CRB index
BEF, and AFT, signal months that are one is less representative of cattle contracts alone,
month before and after months in which an- its parameter estimate is lower when RCAT, is
nouncements are made. The daily market returns used.
model is estimated first. Without dummy vari- The estimated announcement date dummy
ables representing announcement effects, the parameter (not shown) has an insignificant t-
estimate of the market returns model from statistic, so the collective effect of the days on
January 1983 to December 1990 is: and around the announcement date are exam-
ined for evidence of abnormal market behavior.
R, = 0.0057 + 0.5199M, + u,,
Testing for a collective effect using the t-statis-
(6)
(0.0207) (0.0334)
tics of the individual dummy coefficients (which
with an adjusted R2of 0.1 15 1, a Durbin-Watson represent days on and around the announce-
Statistic of 2.016, and 1,858 observations. The ment) is unreliable. In fact, under the null hy-
standard errors for the regression parameters are pothesis, one would expect to find one or two
shown in parentheses. The red meat index, R,, of the 41 dummy coefficient estimates signifi-
cant when such a test is performed at the 5
used as the dependent variable includes all eight
percent leveL6 Therefore, an F-test is performed
red meat contracts, live cattle, feeder cattle,
pork bellies, and live hogs in both the nearby to determine if the dummy variables are jointly
significant. At the 5 percent level, none of the
and six-month contracts. The parameter estimate
f9r the CRB index is significantly different from red meat index models show a significant joint
zero. It can partially be explained by the fact F-statistic for the nine strongest announcement
that three of the red meat contracts are included dates.'
in the index. However, it primarily reflects the An F-test to determine if the sum of the
reaction of red meats to other related commodi- dummy estimates is significantly different from
ties included in the index, especially grains. zero is also performed. For the nine strongest
Significance of the CRB index persists through- announcement dates, none of the models exhibit
out all of the market returns testing. a sum of coefficients that is significantly differ-
The event study regressions, estimates of ent from zero at the 5 percent level
equation (4), are reported in Table 1 for the Beyond testing for statistical significance,
economic significance of the results is consid-
four versions of the red meat futures index.
ered. A 90 percent confidence interval for the
Table 2 defines four indices used to measure
red meat price changes. Initial regressions that sum of the dummy coefficients is computed for
used all 26 announcements (strong, moderate, the following reasons. If zero is contained
and weak) showed no significance, individually
or joint, of the announcement day dummies. 6Dummy variables include the announcement date. 20
days preceding, and 20 days following. The inclusion of
Therefore, only regressions using "strong"
dummies for several announcement dates ensures that each
announcement dates are presented in Table 1. dummy variable lands on anon-rolluver date, validating all 41
As expected, the CRB market index dummy variables. However, when testing a single announce-
parameter estimate is highly significant in the ment date, three contract roll-over dates will occur within this
window, leaving three dummy variables invalid.
four regressions with different measures of red
'Results reported in Table 1 measure red meat return
meat price changes. The four measures are: with the four portfolios described in Table 2. The four
RRM, (the change in nearby and six-month beef portfolios represent different combinations of the eight pork
and beef contracts. Numerous other portfolios could be
and pork contracts); RNB, (the change in nearby
constructed from other subsets of the eight contracts. We
beef and pork contracts); R6Mt (the change in
investigated the same empirical relationships using other
six-month beef and pork contracts); and RCAT, portfolios, including portfolios consisting ofjust one of the
(the change in nearby and six-month beef eight futures contracts. The key result described in the text, the
non-significance of the cumulative announcement effect. is
contracts). A 1 percent change in the market
robust to choice of portfolio.
index is associated with about a 0.5 percent
634 REVIEW OF AGRICULTURAL ECONOMICS. Vol. 18, No. 4. October 1996
Table 1. Daily Market Returns Model Results, Nine Strong Announcement Dates
RRM, RNB, R6M, RCAT,
Intercept 0.0037 0.0032 0.0062 0.0272
(0.0225)" (0.0246) (0.0215) (0.0189j
M, 0.5 130" 0.5050" 0.5219" 0.2407"
(0.0336) (0.0367) (0.0321) (0.0282)
Sum of Dummy Coefficients 0.1505 0.3718 -0.0708 -0.3100
F-stat (joint) 0.9220 1.0139 0.8426 0.7952
(0.6131) (0.4470) (0.7468) (0.8171)
F-stat (sum) 0.0058
(0.9394)
90 percent C.I. (sum) (-3.09.
3.39)
Average Returnc 3.9187
Adjusted R' 0.1136
Mean Squared Error 0.800
Durbin-Watson 2.012
n 1,858
Dependent variables are measured in daily percentage changes, not annualized
Wumbers in parentheses represent standard errors for coefficients and p-values for F-statistics
bIndicates coefficient significantly different from zero at the 5 percent level
'The average of absolute percentage changes of the red meat index over all 41-day intervals in the sample
Table 2. Futures Contracts Included in the Four Red Meat
Futures Indices
Contract RRM, RNB, R6M, RCAT,
LC-nearby J J J
LC-sixth month J J J
FC-nearby J J J
FC-sixth month J J J
PB-nearby J J
PB-sixth month J J
LH-nearby J J
LH-sixth month J J
LC = live cattle,
FC = feeder cattle,
PB = pork bellies,
LH = live hogs.
HEALTH RISK AND THE DEMAND FOR RED MEAT Robenstein, Thurman 635
within the interval (as is found), an argument excess returns. Similar results hold for regres-
for abnormal returns around the announcement sions that use all positively ranked announce-
date is weak. This settles the issue of statistical ment dates: strong, moderate, and weak. Fur-
significance. However, a failure to reject a null ther, each of the nine strong dates is analyzed
hypothesis can be interpreted in two ways. One in its own regression. All the announcement
could conclude either that there is no dates, except one, exhibit similar insignificant
announcement effect or that the data are too results. The one significant date is October 5,
weak to detect it. But, if the 90 percent confi- 1987 and its regressions are reported in Table
dence interval contains only returns that are 3. On that date, an article in The Wall Street
deemed to be economically small then the Journal appeared on the first page of the second
regression estimates the announcement effect to section, "Doctors' Orders: Cholesterol Study
be economically insignificant, and this is found. Calls for Broad Treatment Change." Included
The question arises: what is a reasonable were recommendations by the National Heart,
measure of the economic significance of a daily Lung, and Blood Institute that "doctors monitor
return? Because the sum of the dummy vari- every American adult's cholesterol level and
ables in the event study regressions represents prescribe specific diets ...with detailed lists of
the cumulative effect, over 41 days, of a single unacceptable and acceptable foods, mostly
announcement, it is compared to the uncondi- recommending that patients avoid high-fat
tional average of the market's movements over foods... and limit their intake of fatty beef and
all 41-day periods. The 41-day average return veal" (p. 13 1). For this announcement date, the
is computed by summing the daily returns over F-statistic for the sum of the dummy coeffi-
a 41-day interval, taking its absolute value, and cients was significant at the 5 percent level.
averaging all of the possible 41 -day returns for Events surrounding the specific date were
the entire sample period. The resulting figure further investigated. Cattle prices dropped
can be interpreted as the average amount by precipitously in October 1987.' According to
which the market goes up or down over a 41- reports in The Wall Street Journal, traders
day period. began worrying about falling cattle demand and
All of the confidence intervals in Table 1 excess fat cattle inventories as cattle futures
are zero, establishing the lack of statistical began a two-week slump starting in the last
significance of the announcement effect. As to week of September. The week of October 19
economic significance, the lower (negative) end through 22 saw cattle futures drop by $4.50 per
of the confidence interval is compared with the hundredweight, making for "the worst week
average absolute 41-day return. For example, since spring 1986, when the U.S. announced
the 90 percent confidence interval for RRM, is plans to pay dairy operators to slaughter their
bounded by -3.09 percent and 3.39 percent. herds" (Siconolfi, p. 40). On October 26, cattle
Relative to the 41-day average movement of and hog contracts fell by the permissible limit
4.92 percent, the confidence interval bounds of $1.50 per hundredweight and pork bellies by
support with 90 percent confidence that excess $2.00 per hundredweight. Analysts blamed a
returns due to announcements are economically bearish cattle-inventory report from the United
insignificant for the nine strongest announce- States Department of Agriculture and stock
ment dates. The 41-day average movement is market declines. Given the extraordinary cir
compared with the low, and negative, end of the cumstances in the cattle market during this
confidence interval because of interest are period and that no Wall Street Journal commen-
negative effects of cholesterol announcements tary at the time attributed the meat futures drop
as demonstrated by negative returns in the red to the October 5 health announcement, the
meat market. abnormal returns were unlikely to have been
The 4 1-day average movement in the red caused by cholesterol announcement effects.
meat index is reported in Table 1 for each of
the four index versions. For the nine
announcements, each of the four models exhib-
'Coincidentally or not, October 19, 1987 was the date
its statistically and economically insignificant of the stock market crash.
636 REVIEW OF AGRICULTURAL ECONOMICS: Vol. 18: No. 4. October 1996
Table 3. Daily Market Returns Model Results, Individual Announcement Date,
October 5, 1987
RRM, RNB, R6M, RCAT,
Intercept 0.0122 0.01 13 0.0130 0.03 12
(0.0209)" (0.0229) (0.0199) (0.0 173)
M, 0.5 182b 0.5107b 0.5257b 0.2367b
(0.0337) (0.0369) (0.0321) (0.0280)
Sum of Dummy Coefficients -1 1.998 -11.538 -12.458 -9.8128
F-stat (joint) 1.2978 1.1103 1.4389 2.0301
(0.1065) (0.2971) (0.041 1) (0.0002)
F-stat (sum) 4.675 1 3.6104 5.5566 4.5367
(0.0307) (0.0576) (0.0185) (0.0333)
90 percent C.I. (sum) (-21.10, (-21.50, (-21.13, (-17.37:
-2.90) -1.58) -3.79) -2.26)
Average Return' 4.9187 5.7158 4.3322 3.6120
Adjused R2 0.1205 0.0978 0.1360 0.0588
Mean Squared Error 0.7938 0.9506 0.7200 0.5471
Durbin-Watson 2.007 1.993 1.994 2.023
n 1,858 1,858 1,858 1.858
Dependent variables are measured in daily percentage changes, not annualized.
Wumbers in parentheses represent standard errors for coefficients and p-values for F-statistics
bIndicates coefficient significantly different from zero at the 5 percent level.
'The average of absolute percentage changes of the red meat index over all 41-day intervals in the sample
The monthly market returns model is Conclusions
tested next. Without dummy variables represent-
ing the announcement month or the month The most obvious times that public
before and after, the empirical estimate of the knowledge of the links between red meat con-
market model is: sumption and heart disease could be said to
have changed were identified. On those dates,
RRM, = 0.0072 + 0.3501Mt + v,, reactions in futures markets, the most obvious
(7) place for immediate adjustments to occur, were
(0.021 1) (0.1393)
examined. No evidence was found of any such
with an adjusted R2of 0.0530, a Durbin-Watson adjustment. Further, failure to find evidence of
Statistic of 1.8626, and 96 observations. a reaction is not due to weak data. Probable
The announcement effect regressions are bounds on the size of a futures price reaction to
repeated with the monthly average data, but health information were identified and were
again the null hypothesis of no announcement small in economically relevant terms.
effect cannot be rejected. Further, the confi- The link between health perceptions and
dence intervals for the estimated effect are red meat demand has been discussed extensively
always small relative to actual average returns. and previous empirical work has shed useful,
For individual announcement date regressions, albeit indirect, light on the question. What
only the October 1987 announcement proves seems clear is that structural change analysis of
significant. Only the announcement month is time series demand models has not settled the
significant, not the month before or the month issue of whether or not red meat demands have
after. This result strengthens the argument that shifted. The current article examines a different
both the monthly and daily tests for this period sort of information and expands the set of tested
are affected by extraneous forces. implications of a health-linked demand shift.
HEALTH RISK AND THE DEMAND FOR RED MEAT Robenstein, Thurman 637
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