Transcript Buying Less, but Shopping More: Changes in Consumption
Buying Less, but Shopping More: The Use of Non Market Labor During a Crisis
David McKenzie,
World Bank
Ernesto Schargrodsky,
Di Tella
“Women, the poor, children, the unemployed, etc. would be more willing to spend their time in a queue or otherwise ferreting out rationed goods than would high earning males” (Becker 1965,
A Theory of the Allocation of Time
).
Adjustment to Aggregate Shocks
Reduced set of risk-coping mechanisms Formal and informal credit dries up Rising inflation erodes value of savings Price of assets fall.
group based informal insurance can’t protect against common shocks Unemployment limits use of labor market => Total expenditure falls by as much as income
Alternative Coping Strategies
Reallocate expenditure, spending more on basic foods Take actions to change how much food a given amount of expenditure can buy Spend more time searching Shop at a wider variety of stores Buy lower quality products
Non-Market Use of Labor
When income falls, consumers can substitute goods for time in the production of consumption by increasing the time devoted to shopping and other home production activities.
It has proven difficult, however, to test this implication.
Standard expenditure surveys generally provide little information on shopping consumer behavior.
When expenditure surveys including detailed shopping data exist, they usually have a cross sectional structure with no exogenous source of income variation.
Non-Market Use of Labor
We use high-frequency (10-day) expenditure data from LatinPanel, a market research firm, to analyze shopping behavior during the 2002 Argentine crisis.
The crisis provides a large exogenous shocks to households’ income which allows to identify the causal effect of income on shopping activity.
Preview of results
Consumers are found to shop more days a week at a wider variety of channels during the crisis.
The fall in income explains much of the increase in shopping frequency.
Increased shopping frequency results in lower prices and more priced goods, mitigating up to 40% of the fall in expenditure.
Outline
Macroeconomic Overview Data Basic Facts – changes in expenditure, shopping frequency, stores visited and quality Explaining the increase in shopping frequency Prevalence as a mitigation mechanism Conclusions
The Macro Context
Recession 1998(2)-2001 December 3, 2001:
corralito
deposits – partial freeze on January 6, 2002: govt. votes to end 11 years of convertibility and float the peso Real GDP fell 10.9% in 2002, private real consumption 14.4% Unemployment increases to 21.5% Poverty increases to 37.7%
Exchange Rate
Argentine Peso - U.S. Dollar Exchange Rate 2000-2003 2000 2001 2002 Year and Month 2003 2004
Monthly Inflation Rates 2000 2001 2002 Year and Month CPI Inflation LatinPanel food inflation 2003 Food Inflation 2004
Measure of Liquidity Effect of Corralito
Discount rate offered by exchange houses for exchanging money inside the corralito for cash Corralito Liquidity Premium 2001 2002 Year and Month 2003
Price Dispersion
Average of coefficients of variation for individual products weighted by 2000 expenditure shares Price Dispersion 2000 2001 Year and Month 2002 2003
LatinPanel Data
Market research firm rotating panel of 3000 households nationwide for 2000-02 Purchase diaries kept of expenditure on food, cleaning and beauty products Record day of purchase, amount, units, quality, channel for each 10-day period Two main quality levels for each product: premium and priced goods
Products
Food, cleaning and beauty products with brands Fresh fruit, bread, fresh meat, and meals out not included Mean expenditure shares: Food 76%, cleaning 13%, beauty 11% Calculate that LatinPanel food is about 50% of total food basket, total LP expenditure is around 15% of monthly income Mixture of necessity and luxury items
Ten Channels
Hypermarkets Supermarkets Discounts Wholesalers Drugstores
Kioscos
(candy store)
Almacenes
(small grocery store)
Autoservicios
(self service)
Trueque
(Barter Clubs) Other channels (
Ferias
etc)
Pseudo-panel structure
For confidentiality restrictions LP does not provide data at the individual level, but instead aggregated into pseudo-households Pseudos contain all households with the same demographic and socioeconomic characteristics: Region *Socioeconomic Class * household size * housewife’s age * youngest child age In practice just over 400 pseudos Can also use this structure to match with labor force survey
Income
Labor-force survey (EPH) provides income for matched pseudo-households: available for months of April and September each year only Monthly average wage from Social Security system to extrapolate change in average income between EPH months.
Buying Less
Real LatinPanel total expenditure fell 10.6% between 2001 and 2002 (after 2.5% fall between 2000 and 2001) Quantity falls for all food (apart from yerba mate and pasta) and for all cleaning and beauty products Expenditure on premium products fell 17.6% Expenditure on priced goods rose 2%
Shopping more days
Mean days each household spent shopping per 10 day period 2001-2002 2001 2001.5
2002 Year All goods Nonpremium Goods 2002.5
Premium Goods 2003
Shopping in more places
Mean number of channels shopped per household each 10 day period 2000 2001 Year All goods Priced Brand Goods 2002 Premium Goods 2003
Measuring shopping frequency
Channel-days
: sum of the number of days spent shopping at each of the ten channels in the 10-day period Average pseudo-household spent 6.28 channel-days per 10-day period in 2001 and 6.71 in 2002 (7% increase)
TABLE 3: CHANGES IN SHOPPING FREQUENCY 2001-2002
Channel-Days Shopped at per 10-day period 2001 2002 All Households by Income Quartile Households Lowest 2nd 3rd Highest 6.28
6.71** 6.04
6.68** 6.56
7.07** 6.14
6.64** 5.97
6.66** Channel-Days Shopped per Real Peso Spent 2001 2002 0.24
0.28** 0.29
0.35** 0.26
0.31** 0.21
0.26** 0.16
0.20**
Empirical Questions
1.
2.
3.
Do people shop more as a response to falling incomes?
Or is shopping more just another cost of the crisis, reflecting increases in liquidity constraints, inflation, or price dispersion?
If this is a mitigation mechanism, how important is it?
The Income Effect (Cross-section)
On the one hand, falling income lowers the opportunity cost of time, increasing shopping.
On the other hand, falling income reduces consumption and the gains from shopping.
Cross-sectional analysis
: look at relationship between income and shopping frequency in 2001, prior to the crisis.
Non-parametrics: Freq = f(Labor Income) Semi-parametrics: control also for quantities
Nonparametrics: Shopping Frequency against Income 3 4 5 6 Real Log monthly income 7 8
Semiparametrics: Shopping Frequency against Income controlling for quantity purchased 3 4 5 6 Real Log monthly income 7 8
The Income Effect Over Time
Look at changes in income and shopping frequency for pseudos over time Control for pseudo-household fixed effects to capture time-invariant determinants of shopping frequency
Shopping Freq h
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t
log
income h
,
t
Z t
X h
,
t
j
37 1
j q j
,
h
h
h
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t
TABLE 4: DETERMINANTS OF SHOPPING FREQUENCY 2001-02
Dependent Variable: Shopping Frequency (Channel-days shopped at per 10 day period) Fitted EPH log real labor income Corralito premium Food CPI inflation Aggregate price dispersion across channels (3) -0.730
(12.53)** (4) -0.586
(9.18)** 0.004
(1.14) 0.043
(9.52)** -1.099
(2.55)* Product quantity effects Pseudo-household fixed effects yes yes yes yes
Other crisis effects
Corralito
: restricts cash on hand, reducing liquidity Expect this to cause people to shop more frequently buying fewer items each time
Inflation
erodes nominal balances, causing consumers to lower their reservation prices and increase shopping.
Inflation generally accompanied by
Price Dispersion
Consumers will want to hold a lower stock of knowledge about prices May need to increase or decrease search to hold this smaller stock of information
Aggregate time trends
Add time effects Allow effect of inflation, price dispersion, and corralito to differ by household Construct pseudo-household CPI and price dispersion Interact Corralito with credit card ownership
TABLE 5: ROBUSTNESS OF SHOPPING FREQUENCY REGRESSIONS
Dependent Variables: Channel-days shopped at per 10 day period (Columns 1-6), Channel-days per real peso per 10 day period (Column 7) (4) (5) (6) Fitted EPH log real labor income Corralito premium Food CPI inflation Aggregate price dispersion across channels -0.237
(2.83)** -0.238
(2.84)** -0.558
(8.67)** 0.002
(0.56) 0.043
(9.30)** -1.328
(3.03)** Corralito premium*credit card ownership Pseudo-level inflation Pseudo-level price dispersion 0.009
(0.84) 0.035
(1.16) 0.477
(0.32) Total household labor hours worked Constant 6.132
(12.28)** 4.379
(8.56)** -0.005
(1.54) 7.554
(19.87)** (7) -0.030
(9.46)** -0.001
(6.48)** 0.004
(20.43)** 0.005
(0.22) 0.392
(20.92)** Pseudo-household fixed effects Time effects Product quantity effects yes yes yes yes yes yes yes no yes yes no no
How prevalent is this for crisis mitigation?
One of the most prevalent mechanisms 66% households use it.
60%-80% of households use different consumption strategies.
Instead, 13% use labor market, and between 2 and 11% use formal or informal credit, although adjustments in the labor and credit market have received much more attention in the literature.
TABLE 7: PREVALENCE OF USE OF DIFFERENT ADJUSTMENT MECHANISMS
Adjustment Mechanism All Percentage of Households using: Lowest 2nd Income Quintile 3rd 4th
Shopping Frequency from LatinPanel database
Increase in days Increase in channels Increase in channel-days 61.6
75.8
66.0
60.3
72.6
61.6
56.3
71.8
63.4
61.3
80.0
65.3
61.6
79.5
65.8
Highest 66.2
74.3
71.6
World Bank Survey on Crisis Coping Strategies:
Consumption Strategies
Reduced quantity of food Substituted for cheaper food Reduced consumption of non-food items Substituted non-food items for cheaper items Increased home production
Labor Market Strategies
Adding new workers to labor market Working more hours
Financial Strategies
Selling assets Using savings Borrowing from banks Borrowing from friends and family Purchase with delayed payment 74.9
92.3
81.0
83.2
61.1
12.9
13.7
3.3
4.8
1.8
11.3
8.0
90.4
97.6
90.5
89.5
64.4
28.0
11.4
5.9
2.8
0.9
21.2
14.6
83.1
95.4
87.7
89.3
73.0
16.8
15.6
3.7
3.5
3.6
15.7
13.1
73.2
92.5
81.5
80.4
62.6
12.2
16.3
3.3
4.0
1.8
10.6
9.5
69.0
91.5
76.8
80.2
52.5
6.2
11.5
2.7
8.0
0.6
5.8
2.3
59.1
84.8
68.3
76.6
43.2
1.4
13.4
1.1
5.6
2.0
3.0
0.7
Why shop more?
To search out lower prices for the same products ln
price i
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q
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t
,
h
i
,
q
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t
Channelday s t
,
h
h
i
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q
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t
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h
Instrument channel-days with EPH income
Results
Shopping one more channel-day results in a 18% fall in the price of same product, along with 2% saving from switching to cheaper brands Crisis is estimated to increase channel-days by 0.20, so estimated 4% saving in price Expenditure fell 10%, so shopping increase mitigates approximately 40% of fall in expenditure through cheaper prices.
Conclusions
Argentine consumers increased their shopping frequency as means of coping with the crisis Showed a mitigation mechanism that standard income and expenditure surveys provide little information about Mechanism is used by many households and has significant effects In the presence of aggregate shocks which prevent households from taking their labor to the labor market, non-market uses of labor like searching for better prices provide an alternate way for households to smooth consumption.