Female Spending Female Spending HabitsHabitsArielle PhillipsArielle Phillips&&Kristen YurkavageKristen Yurkavage

22

OverviewOverview Research Planning and Research Planning and

ExplorationExploration– Background of studyBackground of study– HypothesisHypothesis

Data Collection Data Collection and and PreparationPreparation Analysis Analysis andand Interpretation Interpretation

33

BackgroundBackground National Bureau of Economic ResearchNational Bureau of Economic Research

– Private group of economists tracking recessionsPrivate group of economists tracking recessions

December 2007 start of recession with 1.2 December 2007 start of recession with 1.2 jobs cut in first 10 months of 2008jobs cut in first 10 months of 2008

Consider personal income, industrial Consider personal income, industrial production, wholesale and retail sales, and production, wholesale and retail sales, and GDPGDP

44

Background Background continuedcontinued

Downturn in house market widely accepted as Downturn in house market widely accepted as cause of recessioncause of recession– Fall of housing prices since early 2000s cut into new home Fall of housing prices since early 2000s cut into new home

building and home purchasesbuilding and home purchases– Caused steep rise in mortgage foreclosuresCaused steep rise in mortgage foreclosures– Resulted in losses of hundreds of billions of dollars for Resulted in losses of hundreds of billions of dollars for

banksbanks– Lenders tightened creditLenders tightened credit

Financial markets and credit crisis worsened Financial markets and credit crisis worsened during Summer 2008during Summer 2008– Wall Street and Auto Industry bailoutsWall Street and Auto Industry bailouts

Current recession one of the longest economic Current recession one of the longest economic downturns since 1930s Great Depressiondownturns since 1930s Great Depression

Source: Money.cnn.com

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Female’s Affect on EconomyFemale’s Affect on Economy

Prudential’s Prudential’s Financial Experience & Behaviors Financial Experience & Behaviors Among Women Among Women Research StudyResearch Study– 1,250 American women between 25 and 64 years old1,250 American women between 25 and 64 years old– Analyzes financial security, preparedness and challengesAnalyzes financial security, preparedness and challenges

FindingsFindings– 95% involved in financial decision-making in household95% involved in financial decision-making in household

One-quarter are primary financial decision-makersOne-quarter are primary financial decision-makers– 15% of married respondents are primary financial 15% of married respondents are primary financial

decision-makersdecision-makers– 57% have become more cautious with their money due 57% have become more cautious with their money due

to “market plunge”to “market plunge”

Source: Prudential’s Financial Experience & Behaviors Among Women study, 2010

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Data CollectionData Collection HypothesisHypothesis

– Female’s have cut back on spending as a result of Female’s have cut back on spending as a result of recent economic conditions.recent economic conditions.

Target AudienceTarget Audience– Females Females – 18 years old and over18 years old and over

Survey MethodSurvey Method– 15 question survey on SurveyMonkey.com15 question survey on SurveyMonkey.com– Distributed randomly online through e-mail and Distributed randomly online through e-mail and

FacebookFacebook– 76 surveys completed76 surveys completed

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Data PreparationData Preparation Age DistributionAge Distribution

– 30.3% of women were 30.3% of women were between the ages of 18 between the ages of 18 and 28, and 29 and 38and 28, and 29 and 38

– More than half of the More than half of the respondents were under respondents were under 39 years old39 years old

Marital StatusMarital Status– More than half of More than half of

respondents were respondents were marriedmarried

– Approximately 30% of Approximately 30% of respondents were singlerespondents were single

30.3% 30.3%

17.1%

11.8% 10.5%

0

5

10

15

20

25

30

35

18-28 29-38 39-48 49-59 60 andover

18-2829-3839-4849-5960 and over

Marital Status

28.9%

59.2%

7.9%

3.9%

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Single

Married

Divorced

Widowed

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Data Preparation Data Preparation continuedcontinued

Females’ Spending HabitsFemales’ Spending Habits– 80% of women changed 80% of women changed

their spending habits in their spending habits in the last 24 months, 20% the last 24 months, 20% did notdid not

Product ChangeProduct Change– Almost half cut back on Almost half cut back on

Clothing and Accessories Clothing and Accessories (47.6%)(47.6%)

– Entertainment- 33.3%Entertainment- 33.3%– Home and Auto- 15.9%Home and Auto- 15.9%

Changed Spending Habits

80.0%

20.0%

YES NO

Most Affected Product Categories

47.6%33.3%

0.0% 3.2%15.9%

0%

20%

40%

60%

80%

100%

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Summary GraphSummary Graph Products and Services that females will not Products and Services that females will not

compromisecompromise

0

5

10

15

20

25

Car Appliances andElectronics

Clothing andAccessories

GroceryProducts

(coffee, babyproducts)

Beauty Health /Medication

Entertainment Other (wine,cigarettes,

heating oil, etc)

1010

Do most females surveyed Do most females surveyed purchase generic products?purchase generic products?

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Summary GraphSummary Graph Generic Products PurchasedGeneric Products Purchased

1212

Summary GraphSummary Graph Generic PreferencesGeneric Preferences

1313

Do at least half of the Do at least half of the females surveyed use females surveyed use

coupons?coupons?

1414

Summary GraphSummary Graph Coupon UsageCoupon Usage

1515

Summary GraphSummary Graph Coupon PreferencesCoupon Preferences

1616

Does marital status affect Does marital status affect spending habits?spending habits?

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How do the females surveyed How do the females surveyed compare to Prudential’s Research compare to Prudential’s Research

Study?Study?

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Does salary affect generic product Does salary affect generic product purchases?purchases? Simple Linear RegressionSimple Linear Regression Y VariableY Variable

– Generic Product PurchaseGeneric Product Purchase 0= No0= No 1= Yes1= Yes

X VariableX Variable– SalarySalary

1= Under 20K1= Under 20K 2= $20,001-40,0002= $20,001-40,000 3= $40,001-60,0003= $40,001-60,000 4= $60,001-80,0004= $60,001-80,000 5= $80,001-100,0005= $80,001-100,000 6= Over $100,0006= Over $100,000

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Salary DataSalary Data

X VariableX Variable

2020

Scatter PlotScatter PlotSalary vs. Generic PurchasesSalary vs. Generic Purchases

-1.2

-0.7

-0.2

0.3

0.8

1.3

0 2 4 6 8

Salary

Gen

eric

Pur

chas

e

Generic Purchase

Predicted GenericPurchase

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Linear Regression Linear Regression SummarySummary Correlation Coefficient= 46%Correlation Coefficient= 46% R2= .2136R2= .2136 Standard Error= .3070Standard Error= .3070 Slope= -.1105Slope= -.1105 Intercept= 1.2087Intercept= 1.2087 P-Value= .00008P-Value= .00008 T Obs= -4.2T Obs= -4.2

There is a negative relationship between the There is a negative relationship between the variables, reject the Null.variables, reject the Null.

As females’ salaries increase, generic product As females’ salaries increase, generic product purchasing decreases.purchasing decreases.

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ConclusionsConclusions Hypothesis #1Hypothesis #1

– More than 75% of females purchase generic products.More than 75% of females purchase generic products. Hypothesis #2Hypothesis #2

– More than half of the survey respondents use coupons.More than half of the survey respondents use coupons. Hypothesis #3Hypothesis #3

– Married females are more likely to alter their spending Married females are more likely to alter their spending habits.habits.

Hypothesis #4Hypothesis #4– In comparison to Prudential’s Research Study, the survey In comparison to Prudential’s Research Study, the survey

results showed an increased change in spending habits.results showed an increased change in spending habits. Hypothesis #5Hypothesis #5

– As females’ salaries increase, generic product As females’ salaries increase, generic product purchasing decreases.purchasing decreases.

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RecommendationsRecommendations Gather more data from the 60+ populationGather more data from the 60+ population Revising survey software to require all Revising survey software to require all

questions to be completedquestions to be completed Collect more specific dataCollect more specific data Gather information from wider Gather information from wider

demographicdemographic– AgeAge– LocationLocation– Income RangeIncome Range

Compare female to male spending habitsCompare female to male spending habits

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Thank You!Thank You!

Questions?Questions?