economics 490 beer and recessions

8/2/2019 Economics 490 Beer and Recessions

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Beer and Recessions: An Investment Analysis of Beer During the Great Recession of 2007-2010

UBC

Economics 490

Abstract

This paper examines the investment durability of beer stocks during pronounced economic downturns,

specifically the major worldwide recession that struck following the US mortgage crisis of 2007. Analysis

is focused on the performance of leading brewers relative to aggregate market indicators and the regional

impact of the recession. Using monthly data from 6 different stock prices, 3 different indices, and two ex-

change rates over nearly 5 years, the paper attempts to break the investment behavior of brewer stocks

down into their normal and recessionary components.


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I. Introduction

The study of economics, to its own great misfortune, is confined to the study of that which has already

happened. For those of us interested in economics who wish to ask new questions and find new an-

swers, this means that we need to scour situations from the past that are both appropriate to our question

and sporting sufficient data. The appropriate situations are often tough to find; the data however, is forev-

er harder. In the way that it is hard to study the rain on a sunny day, it is hard to study the effects of re-

cessions in a bull market. The recent great global recession that took root in 2007 has provided us with a

fantastic platform to ask many recession-based questions in models utilizing nearly current 21st century

data.


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Anyone holding investments through a recession will, without question, be interested in how well those in-

vestments may fare during the slow down. In a more future focused tone, they would like to know what

kind of investments would best weather the storm next time a recession shows up to threaten their hold-

ings. Borrowing some environmental motivation from the various service industry jobs I have worked dur-

ing my university career, this recession provided a ripe occasion to test the common investment adage

that, beer is recession proof. It is a saying that I have heard people talk about for years now, with inter-

esting arguments both for and against.

Expanding upon this personal motivation is an even more commanding economic one is beer a risk-free

investment during recessions? If it is so, or even partly so if beer-based investments are notably lower-

risk than the average during economic downturns then this gained insight could be massively beneficial

to those planning their portfolios. Especially following a recession such as that which we have just

emerged, one in which countless people lost huge sums of money, the discovery a decent protection

against these kinds of market wide losses would be exciting, at the very least. So, the important question

becomes: how does beer function, as an investment vehicle, relative to the rest of the market during a pe-

riod of recession? And herein lies my aim with this paper, to assess the notion that beer may be reces-

sion-proof.

II. Reviewing the Literature


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Surrounding the topic of beer and economics there is a significant amount of literature. Stemming from

interests in consumption, abuse, policy, investment, and psychology, the research is often varied in intent,

if not also in results. A commonly addressed theme amongst this host of studies is the concept that either

beer consumption or sales or both may behave in a manner not consistent with a normal, pro-cyclical

good.

In a paper focused on the abuse and policy implications of drinking during economically volatile times,

Cook and Moore (2002) look closely at the ties between economic performance and heavy or abusive

drinking patterns. Although their analysis is quite broad, many of their more interesting findings are cen-

tered on the nuanced effects that can be seen when heavy drinkers encounter heightened financial hur-

dles (a rise in the real cost of alcohol, whether through lost wages or increased price). In general, they

find that alcohol is no exception to the economic law of downward-sloping demand1. However, more

specifically they find that consumption levels are sticky for heavy drinkers, implying that a temporary eco-

nomic decline, as found in a recession, would have little effect on the habits of those with high rates of

consumption. They also note that short run behavior of drinkers from all consumption levels may be resis-

tant to their long run findings of pro-cyclical behavior during downturns. It is possible, they consider, that

many consumers may actually only change their specific choice of what and where to have drinks during

short-term economic disruptions; a transfer of purchases from bars and restaurants to retail outlets com-

bined with a shift towards alcoholic beverages with higher ethanol content could effectively smooth con-

sumption when faced with temporarily higher real costs.

1 Cook and Moore (2002), pg. 130


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Diverging from the harm and policy aspects of Cook and Moore (2002), Bentzen and Smith (2004) look at

the relationship that alcohol consumption has with business cycles. By studying consumption rates and

GDP per capita in several Scandinavian countries (Norway, Denmark, and Sweden) over an extended

time series, they are able to evaluate consumption patterns over the course of many business cycles.

Their analysis is broken into separate groups for each of beer, wine, and spirits; however, their results are

identical for all of them alcohol displays significant short run elasticity to income and is a normal, pro-

cyclical good.

Krger and Svensson (2008) have essentially identical findings when looking just at long run data from

Sweden. In a finding that directly supports the sticky behavior posited by Cook and Moore (2002), they

conclude that alcohol sales are a long memory process2.

Perhaps the most extensive piece of literature that I examined was by Freeman (2009). Clearly specified

in the second section, The main focus of this paper is the responsiveness of beer demand to the busi-

ness cycle3. In introducing his state level analysis of drinking in the US, Freeman appraises the popular

arguments about alcohol consumption along three separate channels: 1) consumption; 2) investment; and

3) psychology. Reporting first on alcohol as a consumption good, he states that the convention wisdom

in the economics literature is that alcohol is a procyclical normal good4. This is a particularly interesting

2 Krger and Svensson (2008), pg. 8

3 Freeman (2009), pg. 5

4 Freeman (2009), pg. 2


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review given his note on the following page that he personally in past work found no evidence of

short-run cyclical response of beer to economic variables5. As possibly confusing as those counter

claims are, his continued talk about the investment and psychology behind beer only manage to further

obscure the consensus. Psychologically speaking, he finds that stress and addiction provide strong ar-

guments for alcohol as a counter-cyclical good. On the investment side however, we are informed that,

the prevailing view from the investment side is that the beer industry is recession-proof or acyclical6.

Referencing Ahrens (2004)7, Freeman tells us that the stocks of American alcoholic beverage companies

rose by 46.02% during the five year period that saw the bursting of the dot-com bubble, the recession of

2000-2001, and the tragedy of the 11-September-20016, all while the S&P 500 lost 14.05%. Following

this discussion of the mixed literature, Freeman ironically goes on to show beer in much the same way as

the other economic literature does, as a pro-cyclical, normal good that is sensitive to excise taxes and

price6.

Almost as telling as that which I was able to discover, was that which I was not. None of the literature ex-

tensively focused on the investment response of a sharp economic downturn. Several talked about beer

during a slowdown, but none more pronounced that the lows of a standard business cycle. The only ex-

ception to this was Freemans fleeting reference to Ahrens book. Unexpectedly to me, the question of al-

cohols recession durability appears not to have been studied very extensively yet in academia. This real-

ization furthered my motivation to explore the topic at hand.

5 Freeman (2009), pg. 3

6 Freeman (2009), pg. 2

7 Ahrens, Dan (2004), Investing in Vice: The Recession-Proof Portfolio of Booze, Bets, Bombs, and Butts


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III. Methodology

In advancing my understanding of beer and its investment potential during recessions, I will examine the

investment value of beer relative to other holdings. Whenever talking about investment values and mar-

kets, the discussion almost inevitably converges upon stock markets and their explicit function as invest-

ment middle-men. Using stock prices and their movements as a measure of performance, I will compare

the performance of beer companies to that of the market at large during our recent worldwide recession.

With beer investment values as the dependent variables and various market indicators as the indepen-

dent variables, I will use linear OLS regressions to analyze the data. Lag variables for each independent

variable will be used and tested in preliminary regressions. Those that display adequate statistical signifi-

cance will be kept for the final regressions. The data itself will be subdivided into that which occurs before

the downturn and that which occurs during and slightly after. Using approximately half of the data before

and half after the split, I will be able to look at the behavior of beer investments under normal conditions

(period 1) and under recessionary conditions (period 2). This way, the pro- versus counter- versus a-cycli-

cal behavior of a stock found under regular conditions can be directly compared with its behavior during a

recession. Any defensiveness of a stock during the recession or any change in elasticity between periods

should come up in the coefficients following statistical analysis. Additionally, the lag variables, if signifi-

cant, will inform us if the investments have sticky responses to any of the independent variables.


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a. The Data

My dataset is a collection of stock prices, index prices, and currency exchange rates spanning from July

2005 to February 2010. Once the data has been spliced to accommodate the two different periods, we

are left with 26 times series points from July 2005 to Aug 20078and 30 times series points from Sept

2007 to Feb 2010. Individual data points were taken on a monthly basis from a total of six different stocks,

three market indices, and two relevant exchange rates. This results in a total of 616 observations before

statistical manipulation.

i. Dependant Variables

The dependent variables are made up of the stock prices of three leading brewers each from the Euro-

pean marketplace and the Tokyo Stock Exchange. Each brewer was selected for its status as a market

leader in its own exchange, its own region, and even the entire world. Also important in the selection was

an absence of major mergers in the relevant time frame events that would have lent unrepresentative

volatility to the model. In the European market, Anheuser-Busch Inbev of the Euronext: Brussels Ex-

change, SABMiller plc of the London Stock Exchange, and Heineken N.V. of the Euronext: Amsterdam

Exchange were selected in accordance with these requirements. Similarly, from the Tokyo Stock Ex-

change we have Sapporo Holdings Limited, Asahi Breweries LTD, and Kirin Holdings Company LTD. Re-

spectively, the ticker symbols for these six are: EBR:ABI, LON:SAB, AMS:HEIA, TYO:2501, TYO:2502,

and TYO:2503. Data for the European three was taken collectively from the Share Monitor on AB-Inbevs

8 Only 26 monthly data points were possible in the first period data set as breaks in the data sets begin to appear pri-

or to that initial July 2005 point.


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Corporate site9 while the points for the Asian three were taken individually from their particular pages on

Google Finance10. For consistency, the price taken for each beer stock was that at closing on the first day

of trading in each month.

ii. Explanatory Variables

As explanatory variables, I chose one market index for each of the two regions that was not only well rec-

ognized, but also representative of the market as a whole. In accordance with this, the Nikkei 225 and the

MSCI: Europe were chosen. Similar to the stock prices above, the data points chosen were those closing

out the first day of trading in each month. Data for the Nikkei 225 was collected from Yahoo Finance11

while the points for the MSCI: Europe were collected from the AB-Inbev site together with the European

stock prices.

Being mindful of the United States role as the catalyst and major influence in this recent recession, it was

pertinent to also look at variables that would benchmark the aggregate US market and that would il lus-

trate the relative effect of the US on each region. Again chosen as an index with a broad grasp of the

market, the NYSE Composite Index (NYSE:NYA) was taken to represent a US aggregate. Unlike all data

previously introduced, the price taken for the NYSE Composite index was that at the opening of the first

trading day of the month. This was done for the ease it provided over closing prices in terms of data re-

9 Anheuser-Busch Inbev: Investors,

10Google Finance Beta,

11 Yahoo! Finance,
http://www.ab-inbev.com/go/investors/share_information/share_monitor.cfmhttp://www.ab-inbev.com/go/investors/share_information/share_monitor.cfmhttp://www.google.com/financehttp://www.google.com/financehttp://finance.yahoo.com/http://finance.yahoo.com/http://www.google.com/financehttp://finance.yahoo.com/http://www.ab-inbev.com/go/investors/share_information/share_monitor.cfm


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trieval. It should be noted that I assume little statistical error should result from this irregularity given the

inherent long-term trending of my data together with the minimal intraday variance of prices and the con-

sistency of time-of-day choices within the variable. These data points were taken from all Yahoo Finance.

Accounting for the relative effect of the US on the European and Asian markets respectively, I used the

Euro per USD and Yen per USD exchange rates. The data for these, collected from FreeLunch.com12, is

an average of the daily exchange rates for the month previous to stock and index prices. That is, for a de-

pendent variable stock price taken on 1 July 2007, the independent exchange rate variable would be an

average of the daily values for June 2007. Again noting the statistical inconsistency as with the NYSE

Composite this was done with an intention of easing data retrieval. Since these values are averages,

they should still effectively represent the exchange rate as an independent variable.

iii. Preparation

Prior to doing any actual statistical analysis, the data needed to be organized and prepared in order to

maximize the cogency of the results. Due to the varying magnitudes of the variables, both dependent and

independent, all data has been normalized using the July 2005 data points as a base. This allows for an

analysis in which the resulting coefficients will be easier to understand and discuss. In addition, the nor-

malization makes possible the creation of aggregate dependent variables that preserve relative perfor-

12 FreeLunch, < http://www.economy.com/freelunch/default.asp>
http://www.economy.com/freelunch/default.asphttp://www.economy.com/freelunch/default.asp


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mance movements in the independent stocks13. I created a normalized aggregate dependent variable of

this type for each of the European and Asian markets. They are in turn re-normalized to a value of one at

time=0 (1 July 2005).

iv. Basic Statistics

As displayed in the appendices between subsections I.a) and II.b), the basic statistics on the data set are

very helpful in providing insights to the potential outcomes of the paper. Extrapolating from the mean of

the normalized data values14, we can see that in periods one and two of the European data as well as the

second period of the Asian data, brewers generally outperform the market average. Even in the first peri-

od of the Asian data, the brewers perform better than the NYSE Composite Index, just not as well as the

exceptional Nikkei 225. This is very well represented in the graphs15. We can clearly see the separate

beer stocks of the European market as well as its corresponding aggregate outperforming the MSCI Eu-

rope and the NYSE Composite. They have stronger and sharper rises before, retreat fairly pro-cyclically

during, and then rebound strongly directly after the recession. Notable turnarounds occur in late 2007

and then again in early 2009. The Asian graph shows less of a trend and much denser data in the first

period. Going into the second period, we see declines and rebounds at approximately the same time as

the European firms and, just as was the case in Europe, the beer stocks emerge from the recession faster

and more smoothly that then market indices.

13Without normalization, one stock with a considerably larger magnitude of value than another would very simply

overshadow it in a data set of the aggregate values.

14 See Appendix, Sections I.b and I.d

15 See Appendix, Section II


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b. The Model

As laid out in the methodology and with the subsequent data choices, this model will use normalized

stock prices and their aggregates as the dependent variables in each times series OLS regression. The

dependent variables for each regression will be a combination of the NYSE Composite, the pertinent re-

gional index for the particular dependent variable in use, the pertinent exchange rate, and whichever lag

variables are deemed appropriate in preliminary testing. Depending on the outcomes of that testing, there

will be between 3 and 6 independent variables in each regression. Taking Yt as the independent variable

with Xti (i=1,2,3) as the non-lagged dependent variables and Xt-1i (i=1,2,3) as the possible dependent lag

variables, we have an OLS regression that looks like such:16

Yt = 0Xt1 + 1Xt-11 + 2Xt1 + 3Xt-11 + 4Xt1 + 5Xt-11 + t

Although I will run regressions on each stock and each aggregate for each of the two periods, my atten-

tion in the results will be centered on the output of the aggregate based regressions. Those results of the

individual stocks will be of primary concern during the choice of lag variables to accept in the preliminary

regressions and then will be used mostly as supporting evidence in the discussion of the final regression

results.

c. Expectations

16 Note: t is the error value for each point along the regression line.)


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Given the long-term findings in all of the reviewed literature, I expect to find behavior representative of a

normal, pro-cyclical good in all of the period one regressions. This corresponds with my intuitive, eco-

nomic expectations that beer, under normal economic conditions, is consumed as a normal, price sensi-

tive good. In the second period I expect something a little different. Similar to the way in which Freeman

describes beers investment potential, I expect to see a defensive nature in which the stock values react to

the plunging market indicators; neither counter-cyclical or a-cyclical, but rather a dampened pro-cyclical

effect would correspond not only with Freemans description but also with the sticky downward behavior

uncovered by Krger and Svensson (2008) and Cook and Moore (2002). Therefore, it is implicitly as-

sumed that the lag variables should be more significant (statistically and in magnitude) in the second peri-

od than found in the first. Though this does not readily show itself in the basic statistics or the graphs, I

think it should become readily apparent with the onset of analysis.

With respect to the exchange rates, I think that this model will show a persistently positive correlation be-

tween the exchange rate and the stock value. Intuitively, an appreciation of the domestic currency (Euro

or Yen) will lead to a depreciating stock value. This assumption is founded in the status of these brewers

as multinationals with extensive export businesses. If the producing currency appreciates, the goods be-

come more expensive to import in other parts of the world and demand falls. As this process has inher-

ently slower response time than say, share prices, I expect to see significant positive lag variables present

for the exchange rates in both regions.


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In summary, I think that the stickiness of beer consumption to downward pressure will commute itself to

stock prices and slow the effects of the downturn on stock values. Once faced with a return of upward

pressure, the stocks will show a rapid return beyond that of the relevant market indices. This all translates

into an investment that, although likely not recession-proof as Ahrens (2004) claims, will be recession re-

sistant and perhaps a good choice of protection against unexpected market contractions.

d. The Preliminary Regressions

Before setting forth with the final regression functions, regressions isolating individual lag variables were

run for each dependent variable in each period. Their statistical significance was assessed based on the

confidence intervals in which the null hypothesis (that they are equal to zero) could be rejected. An em-

phasis was placed on the regressions of the aggregate dependent variables and a 95% confidence inter-

val was chosen as the minimum requirement to keep that particular lag term in the final regression equa-

tions.

As presumed by the literature and my methodology, the lag variables were all considerably less significant

in the period from July 2005 Aug 2007. The only lagged-variable in the first period to successfully reject

the null hypothesis (H0: =0) at a 95% confidence interval is Euro per USD. In the second period all three

lagged-variables in the Asian model were statistically significant, however, in the European regressions

only the lagged- Euro per USD was above the 95% confidence level.


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Going into the final regressions this leaves us with the OLS equations:17

Asian Model- First Period

Yt = 0(Nikkei 225)t + 1(NYSE Comp.)t + 2(Yen/USD)t + t

Asian Model- Second Period

Yt = 0(Nikkei 225)t + 1(Nikkei 225)t-1 + 2(NYSE Comp.)t + 3(NYSE Comp.)t-1 + 4(Yen/USD)t +

5(Yen/USD)t-1 + t

European Model- First Period

Yt = 0(MSCI Europe)t + 1(NYSE Comp.)t + 2(Euro/USD)t + 3(Euro/USD)t-1 + t

European Model- Second Period

Yt = 0(MSCI Europe )t + 1(NYSE Comp.)t + 2(Euro/USD)t + 3(Euro/USD)t-1 + t

IV. The Results and Discussion18

The normalized stock price aggregates in each market bring to light interesting results when analyzed un-

der the scope of an OLS regression. Looking at the first period initially, we see that expectations are split

in their fit to the model. As previously stated and assumed, beers in both regions behave as normal, pro-

cyclical investment goods during the normal period of economic activity. The null hypothesis is rejected

at the 99% confidence interval for the NYSE Composite Index on both markets and in the Asian market

17 All regression equations can be found in the Appendix, section III

18 See Appendix, Section IV, parts a.4), a.8), b.4), and b.8) for detailed full-output regression data. For summarized

regression output data, refer to Appendix, Section V.


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the Nikkei 225 is robust to a similar degree. In line with the basic data analysis, the coefficient values in-

form us that brewers outperform the market in Europe and slightly underachieve in Asia the NYSE Com-

posite Index has a coefficient of nearly 3 when compared to the European aggregate while neither it nor

the Nikkei 225 has a coefficient of more then 1 with respect to the Asian aggregate. It is interesting that

neither the MSCI Europe, nor any of the exchange rates, or even the lagged-exchange rates are statisti-

cally significant. This could perhaps be explained by excessive correlation between the dependent vari-

ables and should be addressed in any future work. Another possible explanation could be found in a

more detail look at the production structure of these firms. If it was the case that much of their exported

brew was actually subcontracted to brewers in the consuming country, as is usually the case in Canada,

then a change in exchange rates would have very little effect on the end price or thus demand of that

brewers beer.

Looking now at the second period or recession period results, we once again are presented with re-

sults that are a mix of expected and unexpected. The Asian breweries still display signs of pro-cyclical

behavior with positive coefficients on the Nikkei 225 and the lagged- NYSE Composite. Also positively

significant in the Asian model is the lagged-Yen/USD variable. Together these lags, neither of which was

present in the first period Asian regression, are likely an indicator that the Asian market itself had a slightly

sticky response to the US downturn. As the American markets crashed, the Japanese market briefly held

strong before following suit the transfer of economic turmoil was probably delayed for Asia, and the

Tokyo Stock Exchange specifically. The sign attached to the Yen/USD-lag variable is peculiar in its impli-

cations about the effect that an American financial crisis can have on an Asian brewer. Being positive,


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significant, and greater than one, it means that as the Yen appreciates relative to the USD19 at the start of

the recession, there is a more than proportional drop in value of beer investment values. This would be

startling if it were not for the lagged nature of this variable. Instead of indicating a flight of value from the

beer stock as the Yen initially appreciates (relative to the USD), it illustrates a defensiveness of the stock

once the Yen begins to fall as well a period later. So, when the woes of the Asian currencies begin to

catch up with their American brethren, this positive coefficient signals a noteworthy defense of the stocks

value when the Yen finally does start dropping as well, the values of Sapporo, Kirin, and Asahi are resis-

tant.

Where the Asian breweries showed a delayed response to the United States financial meltdown, the Eu-

ropean ones showed both immediate and lagged significant responses. Also in contrast is the direction of

correlation; in Europe, appreciations in the Euro to the dollar (both today and yesterday) result in large in-

creases in the value of the beer stocks. The betas for Euro/USD and lagged-Euro/USD are -2.77 and

-2.61 respectively. I expect that this result stems from the transfer of investments from USD exchanges to

the Euro as the recession took hold. Investors, losing faith in the USD as a vessel for investment, likely

shifted many of their assets to the European markets for added strength and stability. Quite notably, and

quite significantly20, the recession-period results in Europe indicate a strong counter-cyclical relationship

with the domestic market, or in this case, the MSCI Europe. Countering this result is the persistent pro-

cyclical relationship between the aggregate stock values and the NYSE Composite value. In this second

19 In a recession started in the USA, it is fair to assume that the USD will fall relative to the Yen and other world cur-

rencies, thus causing them to appreciate

20 The p-value of MSCI Europe in period two testing is equal to zero, that is, the resulting coefficient is extremely ro-

bust.


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period, the NYSE Composite coefficient, though still positive, is only about half of what it was in period

one. The highly correlated values of the two western indices together with the overpowering magnitude of

the counter-cyclical MSCI Europe coefficient in the second period, indicates that beer may actually be a

recession-proof investment option in the European market.

V. Conclusion

First and foremost, the results of this analysis robustly support the findings in the literature that, during

normal economic periods, beer is a normal and pro-cyclical good. When we escape from the analysis of

regular business cycles, we encounter statistically significant indicators in each market that point to a cer-

tain response system prevalent in that market. For Europe, beer based investments are highly defensive

and counter-cyclical in the face of a major global recession. With greater density in the data and a more

extensive analytical framework, we would likely come up with a more empirically defensible statement of

European beers level of recession-proof. However, in light of the limitations, it is fair to say that this

model is in support of beer as a recession-proof investment at least in the European case. For Asian

beer investments, a recession does not mean a significant departure from pro-cyclical behavior. Rather,

the stocks are essentially just as pro-cyclical with the market aggregate, only showing their slightly defen-

sive nature through the side avenue of currency devaluation.

In conclusion, I have found that the value of beer-based investments during a recession exhibits heteroge-

neously responsive behavior, dependant on the specific market it resides in. Always pro-cyclical during


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unexceptional economic times, yet defensive or even counter-cyclical during recessions, beer looks to be

a good investment whether rain or shine.

Bibliography


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1. Cook, Philip J. and Michael J Moore (2002), The Economics Of Alcohol Abuse And Alcohol-Con-

trol Policies, Health Affairs, 21 (2), 120-133

2. Krger, Niclas A. and Mikael Svensson (2008), Good Times Are Drinking Times: Empirical Evi-

dence on Business Cycles and Alcohol Sales in Sweden 1861-2000, rebro University, Working

Paper Series, Paper no.2

3. Bentzen, Jan and Valdemar Smith (2004), Are the fluctuations in alcohol pro- or counter-cyclical?

Empirical evidence from the Scandinavian countries using long-run time series data, VDQS

Qenometri XI Conference in Dijon.

4. Freeman, Donald G. (2009), Beer in Good Times and Bad: A U.S. State-Level Analysis of Eco-

nomic Conditions and Alcohol Consumption, Beeronomics Conference, May 2009.


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Appendix

Table of Contents

I. Basic Statistics

a. European Nominal

b. European Normalized

c. Asian Nominal

d. Asian Normalized

II. Graphs

a. European Market Graph

b. Asian Market Graph

III. Regression Equations


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a. Asian Model- First Period

b. Asian Model- Second Period

c. European Model- First Period

d. European Model- Second Period

IV. Regression Results

a. European Regression Results

i. AB-Inbev, July 2005 Aug 2007

ii. Heineken N.V., July 2005 Aug 2007

iii. SABMiller, July 2005 Aug 2007

iv. Aggregate, July 2005 Aug 2007

v. AB-Inbev, Sept 2007 Feb 2010

vi. Heineken N.V., Sept 2007 Feb 2010

vii. SABMiller, Sept 2007 Feb 2010

viii.Aggregate, Sept 2007 Feb 2010


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b. Asian Regression Results

i. Sapporo, July 2005 Aug 2007

ii. Asahi, July 2005 Aug 2007

iii. Kirin, July 2005 Aug 2007


v. Sapporo, Sept 2007 Feb 2010

vi. Asahi, Sept 2007 Feb 2010

vii. Kirin, Sept 2007 Feb 2010

viii. Aggregate, Sept 2007 Feb 2010

V. Summary Results


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I. Basic Statistics

a. European Nominal


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b. European Normalized

c. Asian Nominal

d. Asian Normalized


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II. Graphs

a. European Market Graph

b.

Asian Market Graph


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III. Regression Equations

a. Asian Model- First Period

i. Yt = 0(Nikkei 225)t + 1(NYSE Comp.)t + 2(Yen/USD)t + t

b. Asian Model- Second Period

i. Yt = 0(Nikkei 225)t + 1(Nikkei 225)t-1 + 2(NYSE Comp.)t +

3(NYSE Comp.)t-1 + 4(Yen/USD)t + 5(Yen/USD)t-1 + t

c. European Model- First Period

i. Yt = 0(MSCI Europe)t + 1(NYSE Comp.)t + 2(Euro/USD)t +

3(Euro/USD)t-1 + t

d. European Model- Second Period

i. Yt = 0(MSCI Europe )t + 1(NYSE Comp.)t + 2(Euro/USD)t +

3(Euro/USD)t-1 + t


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IV. Regression Results

a. European Results:

i. AB-Inbev, July 2005 Aug 2007


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ii. Heineken N.V., July 2005 Aug 2007

iii. SABMiller, July 2005 Aug 2007


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v. AB-Inbev, Sept 2007 Feb 2010


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vi. Heineken N.V., Sept 2007 Feb 2010


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vii. SABMiller, Sept 2007 Feb 2010


b. Asian Regression Results


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i. Sapporo, July 2005 Aug 2007

ii. Asahi, July 2005 Aug 2007


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8

iii. Kirin, July 2005 Aug 2007



35/36

1

v. Sapporo, Sept 2007 Feb 2010

vi. Asahi, Sept 2007 Feb 2010


36/36

vii. Kirin, Sept 2007 Feb 2010


V. Summary Results

economics 490 beer and recessions

Documents