Determinants of Beer Consumption Among Lasallian ...

Determinants of Beer Consumption Among Lasallian Students

An Empirical Paper Presented to Dr. Cesar C. Rufino School of Economics De La Salle University – Manila

In partial fulfillment of Course requirements for Introduction to Econometrics 1st Trimester, AY 2013 – 2014

Submitted by: Aaron C. Francisco 11105607 V24 September 6, 2013

Determinants of Beer Consumption Among Lasallian Students

2013

Table of Contents

Introduction …………………………………………………………………………………………………………………. 3 Statement of the Problem ……………………………………………………………………………………………. 5 Objective ……………………………………………………………………………………………………………………… 5 Scope and Limitations ………………………………………………………………………………………………….. 6 Theoretical Framework ………………………………………………………………………………………………… 7 Review of Related Literature ………………………………………………………………………………….……. 7 Operational Framework ………………………………………………………………………………………………13 Assumptions of the Classical Linear Regression Model ……………..………………………13 Variables of the Model ………………………………………………………………………………………14 A-Priori Expectations ……………………………………………………………………………………….. 16 Methodology ……………………………………………………………………………………………………………… 18 Data Gathering………………………………………………………………………………………………… 18 Empirical Procedures ……………………………….……………………………………………………….23 Summary of the Dataset …………….…………………………………….…………………………….. 24 Empirical Testing and Analysis of Results ………………………………………………..…………………. 26 Initial Regression …………………………………………………………………………………………….. 26 Testing for the Overall Significance of the Model ………………………………..…………… 29 Normality Tests of Residuals ……………………………………………………………………………. 29 Multicollinearity ………………………………………………………………………………………………. 31 Heteroscedasticity …………………………………………………………………………………………… 32 Specification Bias ………………………………………………………………………………………….... 34 Corrective Measures and Corrected Model ..………………………………………………....... 35 Conclusion …………………………………………………………………………………………………………………. 36 Appendix ……………………………………………………………………………………………………………………. 38 Bibliography ………………………………………………………………………………………………………………. 41

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Determinants of Beer Consumption Among Lasallian Students

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Background

Introduction Beer was first introduced in the Philippines in 1890 by Don Enrique Ma Barretto de Ycaza who established Southeast Asia‟s first brewery which was named La Fabrica de Cerveza de San Miguel or now known as San Miguel Corporation with Danding Conjuangco as the majority stakeholder. Beer has been in the country for more than 100 years serving the Filipino people (San Miguel, Our History). Asia Brewery, another beer producer and distributor was established in1982 and is owned by Lucio Tan as the majority stakeholder (Asia Brewery, History). Today, the two breweries are competing to gain majority of the market shares in their target market of beer drinkers. Some of the beer labels familiar to the Filipinos are San Miguel Pale Pilsen, San Miguel Light, Red Horse and San Miguel Strong Ice which are the better known San Miguel beer products (San Miguel, San Miguel Beer ) while Beer na Beer, Colt 45, Tanduay Ice and some imported beers are the known Asia Brewery‟s beer products (Asia Brewery, Alcoholic Beverages). The most consumed beer over the last three quarters of 2012 was Red Horse and San Miguel Pale Pilsen (Market Publishers, 2013). Both men and women in the Philippines drink beer. According to World Health Organization‟s report (2011) regarding alcohol consumption, 19.6% of male students and 12.9% of female students drank at least one drink containing alcohol on one or more days in the past 30 days. This implies that students of these ages who are below 18 years old and of both genders have access to alcohol. This shows that the legal ordinances (ex. Republic Act No.9211) are not strictly implemented in prohibiting the sale and consumption of alcohol for minors. Moreover, the recorded adult (ages 15 and 3|Page

Determinants of Beer Consumption Among Lasallian Students

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above) per capita consumption (in litres of pure alcohol) is 4.60 in 2009 in the Philippines. (WHO, Levels of Consumption: Recorded adult per capita consumption, from 1961, Total by country) This indicates a high consumption of alcohol on average in which beer only accounts for 27.83% of the total per capita consumption (in litres of pure alcohol) among adults based on the beer consumption per capita of 1.28. There is an increasing trend of beer consumption per capita (in litres of pure alcohol) in the Philippines from 0.35 in 1961 up to 1.28 in 2009 among adults (WHO, Levels of Consumption: Recorded adult per capita consumption, from 1961, Beer by country). Though the spirits account mostly for alcohol consumption in the Philippines is due to the lower-middle income group. According to the World Bank, beer consumption is the second highest and the most prevalent among students since they just rely on their allowance and beer is cheaper than spirits. But according to the report of the Market Publishers (2013) which was released in August 2013, beer is the most consumed alcoholic beverage in the country in terms of volume. Alcohol (which also includes beer) has been associated as a form of bonding, socializing, and relaxation for people (Labajo). Furthermore, beer makes the drinker enjoy the good moments and forget about their problems as well. As the weekend approaches, some Lasallian students (not all) would hang out with their friends and schoolmates, usually in drinking places located near the premises of the campus such as The Beach parking lot (two blocks away from Razon building), Sherwood (across Andrew Building), Timeout Bar in the University Mall and several others. As soon as it is “Happy Thursday” or the usual last day of the academic week, this signals the time when most students want to distress themselves from problems in

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school, at home or in their love lives by going to the places mentioned above to consume alcoholic drinks. Due to the amount of allowance given to students by their parents or guardians, their choice of alcoholic beverage would be beer because of its lower and affordable price compared to other types of alcoholic drinks. With these in mind, it begs to ask the following questions: “What or who influences students to consume beer?” “Would the location of bars/stores selling beer be a factor of an increase in beer consumption?” “Would the allowance per week play a role in the student‟s beer consumption?” These would be some of the questions to be addressed in this study. Statement of the Problem The researcher has the following questions to answer in writing the paper: What are the explanatory variables/ regressors that would mainly influence the consumption of beer among students? What would be the relationship of the independent variables to the dependent variable in this study? Objective This study aims to infer the relationship between the dependent variable (consumption of beer in one session/sitting) and the independent variables (age, gender, location of bar/store/shop selling beer, brand, price per bottle of beer, influences in drinking beer, allowance, members in the drinking group) among Lasallian (DLSU-Manila) students aged 16-22 through the use of multiple regression analysis.

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Lastly, this paper would seek to find out which among the independent variables along with the dummy variables would be the determinants in the students‟ consumption of beer. Scope and Limitations As a whole, this study would distinguish the determinants that affect consumption of beer in one sitting/session among students. The scope of the study encompasses 130 Lasallian students randomly selected who are aged from 16 to 22 years old and who drink beer. The sample size would not be enough to represent the entire Lasallian student population consumption of beer. Collecting at least half of the entire student population responses would best represent the Lasallian‟s consumption of beer but cannot be done due to time constraints. This study considered only those who drink beer and did not include those who do not drink beer because it mainly focuses only on beer drinkers‟ consumption. The factors that are discussed in this study are age, gender, price per bottle of beer, brand, influences in consuming beer, allowance, members in a drinking group and location of bar/store/shop selling beer. It also aims to evaluate the significance of the regressors on the regressand as discussed above. There may be other factors of drinking beer such as sociological background, psychological thinking, family values, alcohol content of the beer and a lot more which could be done for further studies in the consumption of beer but would not be covered by this study. There would be a cross-section data collected primarily by the researcher from the randomly selected respondents through surveys that they answered in order to obtain

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raw data for this study. The data gathered is only received by the researcher and cannot be guaranteed with absolute certainty that it is indeed free from errors and that the respondents answered the survey with candor and honesty. Thus, we can only presume that the data to be used in the study would be accurate and correct. Theoretical Framework The Law of Consumption according to John Maynard Keynes in his 3 assumptions stated in the theory that individuals are predisposed to increase their consumption as their income increases but not as much as the increase in their income (Keynes, 1936). He further stated that income is the main determinant of consumption (not interest rates). Income in this study would be represented by the allowance received by the student. This is applicable to the study because as the student receives a bigger allowance, he/she tends to consume more than usual but not all of it. Those who possess a bigger allowance tend to spend more on consuming a greater number of beer bottles/cans. Also, the law of demand indicates that as the price of the product or service increases, the consumption of that certain good would decrease. This is evident among students since they are price sensitive due to their weekly allowance constraint. Review of Related Literature Consumption of Beer “Beer ranks as the most-consumed alcoholic beverage” (Zimuda, 2011) and has been common in most countries except those that prohibit consumption of alcohol. It is prevalent

among

adults

including

teenagers

since

they

are

exposed

to

bars/shops/stores that sell alcoholic beverages especially beer which is one of the cheapest and affordable for students. Almost every end of the week, students hang out

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together with their friends in places where they usually drink beer and other alcoholic beverages. Given a lot of school work, left and right problems with relationships (family and friends), peer pressure and a lot more other reasons make the student drink beer instead of non-alcoholic beverages( juice, soft drinks, water and coffee). But why is that so? Drinking helps the students forget their problems temporarily. It is the same cycle every week of consuming the same beverage without getting tired of it. Others would say that it is “social drinking”. Mostly, beer drinkers want to enjoy the good moments and 38% look for friendship, 11% for experience and 4% for the brand (SKEMA, 2010). According to Labago, alcohol (which includes beer) has been associated as a form of bonding, socializing, and relaxation for people. Moreover, she mentioned the following reasons for Filipinos to drink: to socialize (45.5%), to distress (23.8%), and to be happy and have pleasure (17.5%). In this light, beer along with other alcohol beverages has been seen more as a benefit rather than as a health risk. Non-poor households are not the only ones who can afford alcohol to consume but also poor households. According to Rufino (2013), the consumption incidence (percentage of total households consuming positive amount of that good) of the nonpoor and poor households for alcoholic beverages is 59.60% and 51.59% respectively. This shows a small disparity of consumption of alcohol between the poor and non-poor. But surprisingly, estimated share of income (percentage of the household‟s income for consuming a certain good) of the poor is 0.90% on alcohol which is bigger than the nonpoor of 0.58% only (Rufino, 2013). This shows that the consumption of alcohol for the poor is bigger because savings is not a priority for them. Therefore, alcohol

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consumption including beer will be common in society as long as there is income generated to buy those goods. Allowance Students receive a fixed amount of money per week for his/her out of pocket expenses for food, transportation, printing/photocopying and a lot more. The allowance is given to the student not just to cover the expenses but also to teach the person to budget and save a portion of their allowance weekly. Nathan Dungan, the president of Share Save Spend, said that “Allowance transfers accountability and responsibility." (Holland, 2013). This shows that the allocation of allowance required proper decision making which can be according to the student‟s needs or his wants. Age Drinking starts mostly at adolescence and as early as 13 years old and continues until the person decides either to stop or just go on drinking for his entire lifetime. The legal drinking age is 18 years old (House, 2003) but the Filipino youth as young as 16 to 17 years old on average already start drinking alcohol (Valbuena, 2002). As the student starts drinking alcohol as early as 13 years old with just a few sips, by the time they reach 17 years old, they tend to consume 6 or more times per month than those who started drinking later in life. This shows that early consumption of beer can lead to harmful effects as the student ages and in the long-run develop alcohol dependency. Members When students are in a group, there exists peer pressure to have fun when they drink beer. It also becomes part of the group‟s hangout ritual which is composed mostly of the student‟s classmates, friends and family members. There is a saying that “the more, the

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merrier” which means that when there are more people or friends involved in a situation, the happier it will be (Free Dictionary, 2002). “The more the merrier” mind set can also refer to the increase in units of consumption in the social setting. This has been true since most mass media especially in commercials show groups of people usually barkada or friends drinking the alcoholic beverage being sold and promoted. Lastly, beer drinking is considered a social activity since drinkers consume with their friends either in a bar or at home. (SKEMA, 2010) Price Different beer brands have different price ranges depending on the dealer or the seller of the alcoholic drinks which can be influenced by the place, foot traffic of consumers, and income group of the people near the store. In economics, consumers are willing to purchase a product when the marginal benefit (or the additional benefit) would be equal to the price of the good. That price of that good is the maximum price or the reservation price that the consumer is willing to pay for a unit of that product. (UCSB) Gender Males consume more beer than females according to the WHO report on alcohol consumption among students. Because of this, “alcohol is the world‟s leading risk factor for death among males aged 15–59” (WHO, Global Status Report on Alcohol and Health, 2011). A study according to the University of Maryland Center for Food, Nutrition and Agriculture Policy (2006) showed that more men drink beer than women and that men drink about five times a month while females drink less than three times a

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month. This is certainly true in Philippine culture where parents tolerate drinking in sons more than daughters. Brand When one consumes a product, he recognizes the brand since he would not normally purchase one whose brand name is not familiar to him. Brand names should reflect the product that the seller is offering to its target market. The factors that influence college students in choosing the brand of beer they consume are the price of the beer and the risk-taking behaviors associated with it. It is said that emotions influence consumption behavior of college students more than the brand of the beer itself (Kim, 2008). Individuals possess collective positive associations with a brand. This is known as brand capital. Higher sales go to firms with higher levels of brand capital because the consumers achieve higher levels of utility (Saffer, 2005). Place The area or site where students drink would show how much they consume. It is typical that college students who engage in moderate to heavy drinking behavior are usually located in bars, parties or clubs. On the other hand, students would drink more lightly in pools, at the beach, at home with the student‟s friends and not in a party. (Kim, 2008). Moreover, most drinkers would drink both at bars (50%) and at home (35%) with friends (SKEMA, 2010). In the Philippine context, even when there is no special occasion, Filipinos drink on the streets, especially in front of their houses with their friends or in convenience stores (Valbuena, 2002).

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Influence People have to be influenced by someone or something for them to decide that they should consume beer. “Alcohol drinking is a big part of the Filipino merry-making activities. Beer is an essential part of fiestas, birthdays, and parties.” (Valbuena, 2002). One of the prevalent forms of influence in consuming beer is mass media. Advertising, promotions and special events have been used to persuade Filipinos to consume more beer. Companies portray drinking alcoholic beverages with positive images like “heroic, attractive, athletic, or successful.” (Valbuena, 2002). Moreover, advertisements are seen in fashion and youth-oriented magazines. High sales of alcohol is achieved through advertisements and because of the creative and catchy forms, it creates a direct link between “alcohol and happiness, sexual conquest, success, and excitement” for the consumer. Lastly, local celebrities, sexy actors and actresses are most commonly used in advertisements to associate it with “thirst quenching, male bonding, friendship and camaraderie, unity, youthfulness and fun”. (Valbuena, 2002) Beer advertisers use different forms of media such as television, radio, print, internet, outdoor signage, commercial jingles, MTV, songs, basketball teams in PBA, Oktoberfest (world‟s largest drinking event on October), sponsorship and gift items. The youth are also influenced in alcohol drinking through these same forms. (Valbuena, 2002) Also according to Valbuena (2002),”the teenagers said their family, friends, and the mass media have influenced them to experiment with drinking alcohol. Underscoring the critical role that the family plays in youth behaviors, young people seem to take their cue from their own parents' attitudes and behavior.” The individuals most likely to drink are 12 | P a g e

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those who: have parents who drink; live apart from parents; whose parents approve of drinking; frequently attend social gatherings; enjoy going to parties, bars and discos; and do not do sports. (Valbuena, 2002) Operational Framework The classical linear regression model (CLRM) with the ordinary least squares (OLS) estimation method would be used in regression analysis. This will provide empirical validation of the theoretical framework of the study. With the application of the OLS estimation method, this will find the significance of the aforementioned regressors (independent variables) on the regressand (dependent variable). Moreover, according to Gujarati and Porter (2009), this method would try to estimate the Population Regression function with a Sample Regression Function so as to minimize error between the independent and dependent variables. The Assumptions of the Classical Linear Framework a. Linear in Parameters b. Zero covariance between disturbance term and independent variables c. Mean value of disturbance term is zero d. Homoscedastic e. No autocorrelation f. No multicollinearity among all independent variables g. Number of observations greater than number of parameters to be estimated h. Sufficient variation in the values of the independent variable (Gujarati & Porter, 2009)

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Variables of the Model Variable List

Variable Labels (both entered in Gretl and Stata)

Consumption of beer in one sitting/session

lncmb

Allowance received by the student

lnall

Age of the student

age

Number of members in the student‟s drinking group The student‟s willingness to pay for a bottle/can of beer Gender of the student drinking beer

mem

Brand of the beer

br

Place of drinking beer

pl

Influences on student to drink beer

inf

pr gen

Description of the variables 1. Consumption of Beer This is the dependent variable of the model. This represents the number of beer bottles/cans that are consumed by a Lasallian beer drinker in one sitting/session. This variable is subject to change depending on the different factors/ independent variables as mentioned in the model. 2. Allowance This independent variable represents the weekly allowance received from his or her parents. This will affect the decision of the Lasallian student in consuming a certain number of bottles/cans of beer. 14 | P a g e

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3. Age This independent variable represents the age of the Lasallian beer drinker. The age range of the respondents would be between 16 years old and 22 years old. This variable will affect the consumption of beer bottles of the Lasallian. 4. Members This independent variable represents number of people usually in the student‟s drinking group. The difference of count in a drinking group will surely affect the number of bottles the student will consume. 5. Price This independent variable represents the student‟s willingness to pay on how much he/she wants for a bottle/can of beer. 6. Gender This dummy variable represents the sex or gender of the student drinking beer. If the student‟s gender is male, the variable value will be 1 and 0 otherwise. 7. Brand This dummy variable represents the student‟s choice of brand of beer he or she prefers to consume. If the student is choosy of the brand of beer he/she consumes, the variable value will be 1 and 0 otherwise. 8. Place This dummy variable represents the place for drinking beer and whether or not the student‟s consumption of beer increases if there is one near the campus. If the students‟ consumption of beer increases when the bar/store/shop

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that sells beer is near the school premise, the variable value will be 1 and 0 otherwise. 9. Influence This dummy variable represents the influence which makes the student consume beer. If the influence comes from the student‟s family and/or friends, the variable value will be 0 and if the influence comes from the mass media (advertisements, promotions etc.), the variable value will be 1. A-Priori Expectations The dependent variable of the model is lncmb as shown. The table below shows the a-priori expectations of the independent variables on the dependent variable. An a-priori expectation shows the relationship of the two variables either having a positive or negative relationship. Regressors

Algebraic Sign

A-priori Expectations

lnall

Positive

age

Positive

mem

Negative

An increase in the allowance of the student would also increase their consumption according to the Law of Consumption. As the student starts drinking alcohol as early as 13 years old with just a few sips, by the time they reach 17 years old, they tend to consume 6 or more times per month than those who just drank later in life (Hingson, Heeren, & Winter, 2006). When there are more people in a drinking group, the consumption of the student decreases because they tend to socialize more 16 | P a g e

Determinants of Beer Consumption Among Lasallian Students

Pr

Negative

gen

Positive

Br

Positive

Pl

Positive

inf

Positive

2013

rather than drinking beer when alone since they are either lonely or depressed. As the price of the beer increases, the consumption of beer decreases according to the Law of Demand. Due to allowance constraints, students are price-sensitive when buying certain goods/commodities. Males consume more beer than females according to the WHO report on alcohol consumption among students. Because of that, “alcohol is the world‟s leading risk factor for death among males aged 15–59” (WHO, Global Status Report on Alcohol and Health, 2011) When the student is more familiar with the beer brand, he/she tends to drink more since they enjoy the taste and the feeling that the beer has on them. When the place of the bar/store/shop selling beer is near the school, it encourages them to go to those areas because it is convenient for them and they can also hang out with their friends and classmates after school. This makes students consume more beer when the location is near the campus. When mass media influences the student to drink beer, it makes the student drink but only a few indicated this while most 17 | P a g e

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drank because of family and/or friends.

their

Methodology Data Gathering The data was obtained through an online survey which was given to De La Salle University – Manila students. A sample size of 130 students was taken to discover what the determinants or factors are that influence Lasallians to consume beer. The survey can be answered in a few minutes and all the questions regarding the factors are asked from the survey. A screenshot of the online survey

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Presentation of Data The data acquired from the online survey: Age 17 17 20 19 18 20 16 19 21 19 19 19 19 18 18 19 21 19 19 20 17 20 20 21 19 18 20 20 20 19 17 20 20 18 19

Gen 0 1 0 1 0 1 1 0 1 0 0 1 1 1 0 1 1 1 0 1 1 0 1 1 0 1 1 1 0 0 1 1 0 0 1

All 1000 500 1500 1000 1500 1250 1500 2000 500 700 1000 500 900 2500 1000 1800 1500 1500 1500 1000 1000 1500 5000 1000 1200 2000 1000 2500 500 1000 2500 1000 1500 1000 1000

Pr 40 200 35 50 50 100 70 40 10 60 100 80 50 150 30 70 500 50 50 30 30 100 40 30 35 30 30 40 100 45 250 200 50 50 150

Br 1 1 1 1 1 1 0 1 0 1 1 0 1 1 1 0 1 0 0 1 1 1 1 1 0 1 1 1 1 1 0 0 1 1 1

CMB 2 2 3 1 3 3 6 2 6 2 1 1 2 2 3 3 5 1 1 3 3 4 3 2 1 2 2 2 1 2 6 3 6 2 6

Mem 4 5 5 6 4 4 5 8 20 10 3 4 5 5 5 8 20 10 2 5 5 8 5 6 2 5 6 4 3 6 7 5 3 3 6

Pl 0 1 1 0 1 0 0 1 0 0 0 0 0 0 1 1 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 1 1 1

Inf 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 20 | P a g e

Determinants of Beer Consumption Among Lasallian Students 19 19 21 22 17 18 18 20 19 17 20 19 21 20 18 21 20 18 19 20 19 18 18 18 21 18 19 17 18 20 19 19 17 17 19 19 18 19 19

0 1 1 1 1 1 0 0 1 0 1 0 1 0 0 0 1 1 0 1 1 0 1 0 1 1 0 1 0 1 1 0 0 1 1 1 1 1 1

1500 1000 1500 2500 1250 1200 2500 800 2000 3000 1000 1500 2000 2000 2000 1000 1750 2000 1500 1500 1000 3500 1000 1000 3000 1200 1000 2100 600 2000 600 1500 3750 2000 3000 3000 1500 1500 750

20 50 200 50 50 100 100 100 30 60 30 70 80 100 50 50 45 40 50 100 50 50 30 35 50 30 40 80 40 50 150 20 100 35 85 50 30 50 40

0 1 1 1 1 1 1 1 0 1 1 1 1 0 0 1 1 1 1 1 1 0 0 1 1 1 0 1 0 1 0 1 1 0 1 0 1 1 1

1 6 2 4 3 2 1 2 4 2 4 2 2 2 1 2 4 4 5 5 2 2 2 4 6 3 1 1 5 3 3 1 2 3 3 6 1 5 4

4 5 4 5 4 8 5 6 5 5 4 5 5 8 6 7 5 6 10 11 7 9 4 6 10 5 5 10 4 5 3 10 6 5 5 6 5 5 3

0 0 1 0 0 0 0 0 0 1 0 0 0 1 1 0 0 1 1 0 0 1 1 1 1 0 0 0 1 1 0 0 1 1 0 1 0 1 1

2013 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 21 | P a g e

Determinants of Beer Consumption Among Lasallian Students 19 20 19 20 21 20 18 18 18 17 20 20 19 18 19 21 18 20 20 18 20 20 19 18 17 18 19 19 19 19 20 19 19 18 20 18 19 19 20

1 1 1 0 0 0 0 1 1 1 1 0 0 1 1 1 0 1 1 0 0 1 0 1 1 1 0 1 1 1 0 1 1 1 0 0 1 1 1

1500 1000 2000 1000 5000 800 1200 1500 4000 1750 1500 2000 1800 5000 3250 1000 1500 600 4000 2000 2000 2000 1500 500 1500 2500 1000 2500 2000 1500 1500 1500 1500 1000 2000 1000 1000 2500 1000

50 20 50 30 50 30 40 25 500 100 50 25 30 25 100 40 50 30 50 30 40 500 100 30 35 20 50 100 500 40 50 25 50 50 30 100 30 50 45

1 0 1 1 1 1 1 1 1 0 1 1 0 0 1 1 1 1 1 1 0 1 0 1 0 1 0 1 1 1 1 1 1 1 1 1 1 0 1

2 2 6 3 4 2 1 1 3 6 6 2 2 3 6 1 1 5 5 3 2 2 1 5 1 6 1 2 3 3 2 1 6 1 2 1 4 2 3

10 5 4 7 5 5 6 2 5 2 9 5 3 10 6 10 5 5 6 5 5 5 10 8 4 6 3 3 5 5 4 8 10 8 5 5 6 6 5

1 0 0 0 0 1 1 0 0 0 0 1 1 0 1 0 1 1 1 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1

2013 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 22 | P a g e

Determinants of Beer Consumption Among Lasallian Students 18 19 20 22 19 20 20 20 22 22 20 19 20 20 18 21 16

1 0 1 1 1 0 0 1 1 1 1 1 1 1 0 0 1

4000 2000 1500 2000 1000 2000 2500 2000 1500 1000 1500 1600 1000 1200 1500 1300 2500

50 250 30 50 80 70 70 35 50 300 50 100 20 25 50 50 300

1 1 0 1 1 1 1 1 1 0 0 1 1 0 1 1 1

1 2 4 6 4 5 4 3 6 6 2 3 3 5 1 5 6

10 6 6 4 5 5 5 5 8 25 10 5 10 3 5 6 2

0 0 0 0 0 0 1 1 1 1 0 1 0 0 0 0 0

2013 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1

130 respondents from different batches, different colleges and only those who drink beer were able to give their preferences on consumption of beer. Empirical Procedures For this study, the researcher would utilize two statistical and econometric softwares namely Stata 12 and Gretl to verify the relationship of the independent and dependent variables and to summarize the data gathered. These will aid in the interpretation and analysis of the data in making sure that any violations on the assumptions of the Ordinary Least Squares (OLS) in the model might have aroused. These violations will make the estimators dwindle and would not be the Best Linear Unbiased Estimators (BLUE). Also, the researcher has to check any violations particularly concerning Multicollinearity and Heteroscedasticity since it is a cross-section data in which the

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softwares can detect and provide remedial measures if such violations do exist in the model. Moreover, misspecifications especially omitted variables bias would be checked as well. Lastly, the researcher would also look at the overall significance of the model and individual significance of each independent variable to the dependent variable. Lastly, the relationship of the regressand and the regressors based on the results from the softwares would be provided. Summary of the Dataset Table 1: Data Summary Variables

Observations

Mean

Minimum

Maximum

.9300519

Standard Deviation .5980901

cmb (in log form) all (in log form) Age

130

0

1.791759

130

7.309092

.4967824

6.214608

8.517193

130

19.06923

1.214821

16

22

Pr

130

75.65385

91.52082

10

500

Mem

130

6.069231

3.218619

2

25

Gen

130

.6307692

.4844634

0

1

Br

130

.7461538

.4368942

0

1

Pl

130

.3461538

.4775834

0

1

Inf

130

.0307692

.1733599

0

1

Based on the 130 observations, we can conclude that the average consumption of beer among Lasallians would be 2.992308 ~ 3 bottles of beer in one sitting/session taking into consideration the standard deviation of 1.658879. The least consumption of beer bottle would be 1bottle of beer and the most consumption would be 6 bottles of 24 | P a g e

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beer. There are no outliers (unusual or untypical observations) under cmb since the range of values is small. The average age of the respondents would be 19.06923 ~ 19 years old. The age range would be 16 years old as the minimum and 22 years old as the maximum. On top of that, the average weekly allowance of a Lasallian student would be Php 1,691.154 with a standard deviation of 908.1343. Having a large standard deviation shows that the data is widely spread out over a large extend of values with a student having a minimum allowance of Php 500 while the maximum allowance would be Php 5,000. The average members in a group would be 5.923077 ~ 6 members in a drinking group. The minimum members in a group would be 2 and the maximum would be 25 members. Moreover, the average price a student is willing to pay for a bottle of beer is 75.65385 with a standard deviation of 89.41322 which is large due to the range of values. Again, the large standard deviation shows that the data is widely spread out from the mean in which the minimum willingness to pay is Php 10 and the maximum willingness to pay is Php P500. Lastly, the remaining variables which are brand, gender, influence and place are dummy or qualitative variables. All of those indicator variables have a minimum of 0 and maximum of 1 due to the survey questions. Gender and brand are nearer 1 which indicates that there more male respondents than female respondents and students are more particular on the brand of the beer they consume. On the other hand, students do not consume more beer whenever the bar/shop/store is nearer the school premise since the mean is nearer 0. Lastly, influence on students to drink beer is mostly attributed from their friends and family members rather than from mass media such as

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advertisements and promotions. This is seen since the mean is closer to 0. Only a few indicated that they were influenced by mass media to consume beer. This is a cross-section study of consumption of beer among Lasallian students with the semi-logarithmic model specification or the population regression function (PRF) as shown in the following: + Empirical Testing and Analysis of Results Initial Regression The initial regression of the model with the aid of Gretl, the following results: Table 2: Initial OLS Regression of model1:

1

For GRETL Results, see Appendix

Therefore, the Sample Regression Function or the estimated model with the estimated coefficients presented is: 26 | P a g e

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+ In determining the strength and power of the model, we have to look at the Rsquared or the goodness of fit of the model. If the R-squared is bigger, the stronger the model is. The R-squared of the model is 0.3086 which 30.86% of the model explains the reality. Despite being less than 50%, it cannot be considered as insignificant. Also, the researcher failed to look at the price discrimination between brands of beer sold in different establishments around the school. Maybe considering other factors that influences the model can be considered and the sample size can be increased for the model to have more explanatory power since it does not show so much about the consumption of beer among Lasallians. Lastly, the adjusted R-squared defined as the adjusted coefficient of determination is a better basis since it decreases biases and not so high as compared to the original R-squared. Thus, the adjusted R-squared of the model is 0.2610 or 26.10% in which the model is not that befitting in explaining the data. In determining the validity of the model, one has to look at the probability values of the independent variables. According to Gujarati (2009), the p-value is defined as the lowest significance level at which at null hypothesis can be rejected or the exact probability of committing a Type I error (rejecting the true hypothesis). For an independent variable to considered statistically significant and have significance in describing the dependent variable, the p-value < the critical region of 0.05. Now, in the regression results, four out of eight independent variables (three are dummy variables) allowing with its p-value are significant in the 15 level of significance in which are the following: age (0.002), gen (0.000), pl (0.001) and inf (0.001). Note that the constant is 27 | P a g e

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significant at the 5% level of significance. Age, Gender, Place and Influence have significant impact on the consumption of beer among Lasallian students. The other variables are not statistically significant because their p-values are greater than 0.05. In addition, we have to look at the coefficients of the independent variables. First, for every 1 peso increase in the student‟s allowance, there is an increase of 10.31949% in the consumption of beer, ceteris paribus and its coefficient is consistent with our a-priori expectation of a positive relationship. Next, as the student gets older by 1 year, there is an increase of 12.62259% in the consumption of beer, ceteris paribus and its coefficient is consistent with our a-priori expectation of a positive relationship. If there is additional one member to the drinking group, there is a decrease of 0.20008% of consumption of beer, ceteris paribus and its coefficient is consistent with out a-priori expectation of a negative relationship. If there is an increase of 1 peso in the price of the bottle of beer, there is a resulting increase of 0.04821% in the beer consumption, ceteris paribus and the coefficient which is not consistent with our a-priori expectation of negative relationship but instead showed a positive relationship. If the brand of the beer matters to the drinker (with the value of 1), there would be a 95.5377% increase in beer consumption, ceteris paribus and its coefficient is consistent with our a-priori expectation of a positive relationship. If the gender of the student is male (with the value of 1), there would be a 37.76193% increase in consumption of beer, ceteris paribus and its coefficient is consistent with our a-priori expectation of a positive relationship. If the establishment is nearer the school (with the value of 1), there would be a 34.27332% increase in beer consumption, ceteris paribus and its coefficient is consistent with our apriori expectation of a positive relationship. Lastly, if the influence comes from the

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family and/or friends, there would be an increase of 97.10448% of consumption in beer, ceteris paribus and its coefficient is consistent with our a-priori expectation of a positive relationship. The model cannot be fully accepted unless there would a series of tests to find out if the model has violated certain assumptions of the CLRM in order to make the model the Best Linear Unbiased Estimators. Testing for the Overall Significance of the Model The ANOVA or the Analysis of Variance would be used in testing the overall significance of the model if the p-value is less than 0.05. This test suggests that the model is overall significant.

Normality Test of Residuals One of the assumptions of the CLRM is that stochastic disturbance term or the error term is normally distributed. Through the histogram and Doorkin-Hansen test, we would find out if the OLS is normally distributed then it would show that the error term is normally distributed. The null hypothesis is that the error term is normally distributed while on the other hand that the alternative hypothesis is that the error term is not normally distributed.

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Histogram(informal testing)

Doorkin – Hansen test(formal testing)

Since both tests show that the p-value is 0.31053 which is greater than 0.05, we accept the null hypothesis that the error term is normally distributed thus the OLS estimators are normally distributed as well.

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Multicollinearity Multicollinearity is defined as the “existence of a „perfect‟, or exact, linear relationship among some or all explanatory variables of the regression model.” (Gujarati & Porter, 2009). There are different levels of multicollinearity which are perfect, tolerable and dangerous. According to Blanchard (1967), “Multicollinearity is God‟s will and not a problem with OLS or statistical technique in general.” Thus, it is common in economic models and it is inevitable in regression analysis. Although this would not violate the assumption of BLUE, it will lead to large variances and covariance making precise estimation harder. Moreover, the OLS estimators and their standard errors are easily affected with minor changes in the data. If multicollinearity is not addressed, the results would show trifling p-values of the t-statistics despite have a high R2 and large standard errors (Gujarati & Porter, 2009). One of the best indicators in discovering the existence of multicollinearity in the model is through the Variance Inflating Factor (VIF). This is where the “speed” of the variances and covariance can be seen and shows how the variance of an estimator is inflated. According to Gujarati (2009), multicollinearity exists if the mean VIF is greater than 10 showing a presence of severe multicollinearity in the model. On top of that, if the mean VIF is less than 10, there is an existence of tolerable multicollinearity.

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With the use of Stata1, the results are the following:

As seen in the results, the mean VIF is 1.10 which shows tolerable multicollinearity and it is less than 10. Although the model has a presence of tolerable multicollinearity, the researcher shall not do anything about and accept it as it is because its presence is unavoidable. Heteroscedasticity One of the assumptions of CLRM is that the model should be homoscedastic or the equal spread of variance. The tests would find out if there is a violation of homoscedasticity whenever there is a heteroscedastic in the model or unequal spread of variance. This is endemic in cross-section data rather than time-series data. When this violation is not addressed, the OLS would not be the Best Linear Unbiased Estimator since the estimation of standard errors is wrong and the values of the Rsquared and t-ratio would be approximated mistakenly. Lastly, efficiency is lacking in the model. The researcher would only use two tests which are Breusch-Pagan-Godfrey and the White‟s Test.

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With the aid of Stata1, the results are the following:

The null hypothesis is that there is presence of heteroscedastic)

while

the

alternative

hypothesis

homoscedasticity (not

indicates

that

there

is

heteroscedascity in the model. Since the p-value is 0.1015 which is greater than 0.05, we must accept the null hypothesis. Therefore, the model does not exhibit any heteroscedasticity. The White‟s Test is the most powerful and reliable test for Heteroscedascity. If heteroscedasticity exists in the model, there is a ready correction which is the Robust Option that can fix the problem of heteroscedasticity. The null and alternative hypotheses of the White‟s Test are similar to Breusch-Pagan-Godfrey test. With the use of Stata1, the following results are:

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Since the p-value is 0.0709 which is greater than 0.05, we must accept the null hypothesis. Therefore, the model does not exhibit any heteroscedasticity. All the tests have similar results that we should accept the null hypothesis of homoscedascity in our model and it did not pose any problem of heteroscedascity. Therefore, there is no existence of unequal variances of errors and it has followed the homoscedastic assumption in CLRM. Specification Bias According to Gujarati (2009), if the model is not specified correctly, there is model specification error or specification bias. This is a violation on one of the assumptions of CLRM that the regression model is correctly specified when it comes to analysis. The two most common are the omitted variable bias (omitting a relevant variable) and wrong functional form (incorrect functional form used for the model). This can lead to OLS estimators not to be BLUE due to bias and inconsistency as well as leading to inference breakdown. The RESET (Ramsey Regression Equation Specification Error Test) Test would be used to know the specification of the model. Running the test in Gretl, the following results are:

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The p-value is equal to 0.305 which is greater than 0.05. This means that we should accept the null hypothesis of no specification bias. Using Stata, the model would be tested to know if there is omitted variable bias. The following results are:

Since the p-value is greater than 0.05, then the model is not suffering from omitted variable bias. Corrective Measures and Corrected Model Based on the tests done, there is tolerable multicollinearity, no heteroscedasticity and no mis-specification existing in the model. But it best to find alternative models which can improve the significance of the model. Since there are no violations, there is no need of correcting or changing the model. Therefore the final regression model is: + The final regression model with the following estimates:

+

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Conclusion The objective of the study was to ascertain the determinants of beer consumption among Lasallians. The semi-logarithmic model with eight independent variables namely allowance, age, members, price, gender, brand, place and influence which were tested on the dependent variable, consumption of beer. Based on the empirical testing, the positive determinants were age, place, gender and influence and the rest were not determinants of beer consumption among Lasallians. As expected, age, place and gender positively determined consumption because of the legal and cultural settings that the students find themselves in. The average age of the respondents was 19 years old which is above the legal drinking age (18 yrs old). Meanwhile, males are really expected and tolerated to drink more than females by their parents if not by society in general. Place as a determinant was also expected because of the convenience and time-saving factor it provided. The nearer the place, the more time and the more beers one can consume. There is no time wasted in travelling to the bar or shop. On the other hand, the researcher was surprised at the seemingly diminished role of mass media advertising in directly influencing the consumption of beer. Personal influences through their family and friends were consciously attributed by the respondents as the main factor of influence. It seems that word of mouth and modeling are much more powerful influences in beer consumption of Lasallians. The model was tested for presence of multicollinearity, heteroscedasticity, model specification bias and checked its significance with the use of Gretl and Stata. Autocorrelation test was not done because it does not exist in cross-section data. Thus,

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there were no violations in the Classical Linear Regression Model assumptions. No corrective model was done since the model overall had no violations in CLRM. The recommendations for future researchers are to look for other independent variables such as drinking patterns of parents, family values, alcohol content of the beer and a lot more factors which can be considered. Sample size can be increased to further represent Lasallian population. An interesting future research would be to focus on the true role or influence of mass media advertising versus personal influences to consume beer. It is unconceivable that the beer industry allocates so much on their advertising budget to increase sales and not know that their consumers do not consider advertising as an influence in their demand or consumption of beer.

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Appendix STATA: Summary of Data

GRETL: Initial Regression of the model

Legend: * - significant at 10% level; ** - significant at 5% level; *** - significant at 1% level

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GRETL: VIF Test for Multicollinearity Test

GRETL: Breusch-Pagan-Godfrey test for Heteroscedasticity

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GRETL: White‟s test for Heteroscedasticity

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Bibliography Asia Brewery, C. (n.d.). Alcoholic Beverages. Retrieved August 30, 2013, from Asia Brewery Corporation: http://asiabrewery.com/alcoholic-beverages/ Asia Brewery, C. (n.d.). History. Retrieved August 30, 2013, from Asia Brewery: http://asiabrewery.com/history.php Blanchard, O. (1967). Comment. Journal of Business and Economic Statistics , 449 451. Free Dictionary, b. F. (2002). McGraw-Hill Dictionary of American Idioms and Phrasal Verbs. New York: The McGraw-Hill Companies, Inc. Gujarati, D., & Porter, D. (2009). Basic Econometrics. New York: McGraw Hill International. Hingson, R. W., Heeren, T., & Winter, M. R. (2006). Age at Drinking Onset and Alcohol Dependence: Age at Onset, Duration, and Severity. Archives of Pediatrics & Adolescent Medicine , 739-746. Holland, K. (2013, August 6). How an allowance can pay for itself. Retrieved September 2, 2013, from CNBC: Personal Finance: http://www.cnbc.com/id/100903856 House, o. R. (2003). Republic Act No. 9211. Quezon City: Congress of the Philippines. Keynes, J. M. (1936). General Thoery on Employment, Interest and Money. London: Macmillan. Kim, H. (2008). Influential Factors on Brand Choice and Consumption Behaviors An Exploratory Study of College Students and Beer. Gainesville: University of Florida. Labajo, M. V. (n.d.). THE FILIPINO AS THE QUINTESSENIAL DRINKER: A Study of Alcohol Drinking Patterns Among Filipinos. Retrieved August 24, 2013, from Harm Reduction International: http://www.ihra.net/files/2010/05/02/Presentation_23rd_M10_Labajo.pdf Market Publishers, D. (2013). Philippines Beer Market Insights 2013. London: Canadean. Rufino, C. (2013). Consumption Pattern of Poor Households in Metro Manila - A Microeconometric Evaluation. DLSU Business & Economics Review , 10 - 24. Saffer, H. (2005, September 5). Alcohol Advertising and Youth. Retrieved September 5, 2013, from College Drinking - Changing the Culture: http://www.collegedrinkingprevention.gov/supportingresearch/journal/saffer.aspx 41 | P a g e

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San Miguel, C. (n.d.). Our History. Retrieved August 30, 2013, from San Miguel Corporation: http://www.sanmiguel.com.ph/company/page/806/Our_History.html San Miguel, C. (n.d.). San Miguel Beer . Retrieved August 30, 2013, from San Miguel Corporation: http://www.sanmiguelbeer.com.ph/home.php SKEMA. (2010, March). Brand Management: US Beer Market. Retrieved September 3, 2013, from Slideshare: http://www.slideshare.net/Robin.G/brand-management-us-beermarket UCSB. Consumer Surplus and Welfare Measurement. Santa Barbara: UC Santa Barbara. University of Maryland Center for Food, N. a. (2006, October 10). Science Behind Health Benefits of Moderate Beer Consumption. Retrieved September 2, 2013, from Physorg: http://phys.org/news79728415.html Valbuena, 2002, J. P. (n.d.). Alcohol and media - the situation in the Philippines. Retrieved August 24, 2013, from Asia Pacific Alcohol Policy Alliance: http://apapaonline.org/data/National_Data/Philippines/Alcohol_Media_Philippines.pdf WHO. (2011). Global Status Report on Alcohol and Health. Geneva: World Health Organization. WHO. (n.d.). Levels of Consumption: Recorded adult per capita consumption, from 1961, Beer by country. Retrieved August 24, 2013, from World Health Organization: Global Health Observatory Data Repository: http://apps.who.int/gho/data/node.main.A1026?lang=en WHO. (n.d.). Levels of Consumption: Recorded adult per capita consumption, from 1961, Total by country. Retrieved August 24, 2013, from World Health Organization: Global Health Observatory Data Repository: http://apps.who.int/gho/data/node.main.A1025?lang=en Zimuda, N. (2011, June 27). Bottom's Up! A Look at America's Drinking Habits. Retrieved September 2, 2013, from Advertising Age: http://adage.com/article/news/consumers-drink-soft-drinks-water-beer/228422/

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