thick description in empirical economics - world...
TRANSCRIPT
-
Thick description in empirical economics
Jonathan Morduch
New York University ABCDE, World Bank
June 20, 2016
-
Thick description: Explains context of behavior, to give it meaning. Observe actions and, from those, piece together meanings Immersive Interpretive [Inductive] (Geertz 1973, Ryle 1971)
-
Paradox of social science
• We are becoming more “scientific” – Causality – Heterogeneity, LATE, the contingency of results – Pre-analysis plans, protocols – “High-altitude data”
• Need complementary data that explains context – Systematic, clear economic definitions – Probe aggregation – Preferences, constraints and mechanisms – “Low-altitude”
-
Opportunity
• Researchers are in the field more than ever • How to best exploit that opportunity?
-
How do you live on
$1.90 a day?
-
The Economist. October 2015. “Poor statistics. The tricky work of measuring falling global poverty. The number of poor people is declining, but the data are fuzzy” http://www.economist.com/news/finance-economics/21673530-number-poor-people-declining-data-are-fuzzy-tricky-work-measuring-falling
-
$2…
Can’t even buy a small coffee
-
If you earn $2 a day, it’s easy to assume…
You live hand-to-mouth
You can’t plan for the future You can’t save
You can’t have much of a
financial life
-
By Daryl Collins, Jonathan Morduch, Stuart Rutherford and Orlanda Ruthven
-
www. USfinancialdiaries.org | ©, 2014
US Financial Diaries
• Jonathan Morduch, Professor of Public Policy and Economics, New York University
• Rachel Schneider, Senior Vice President, Insights and Analytics, Center for Financial Services innovation
Principal Investigators
The US financial diaries were created jointly by the NYU Financial Access Initiative, the Center for Financial Services Innovation, and Bankable Frontier Associates.
-
www. USfinancialdiaries.org | ©, 2014
Support
Leadership support for the project is provided by the Ford Foundation and the Citi Foundation, with additional support
and guidance from the Omidyar Network.
-
U.S. Financial Diaries
PRELIMINARY DATA - DO NOT CITE
-
235 households allowed us to track every dollar they earned, saved, borrowed, shared, and spent for a full year.
Macon and Columbus, August 2013, Photo: Whitten Sabbatini
-
Financial Diaries • Atlanta • Glasgow • Tokyo • NYC, Mississippi, Kentucky, Ohio, California • Indian SME • Bangladesh (Hrisipara) • Myanmar • Kenya • Mexico
• Bankable Frontier Associates • Microfinance Opportunities • Independent researchers
-
Methodology and Data
-
Why digital data aggregation would miss a lot Fed Cash Product Office (April 2014) Diary of Consumer Payment Choice
USFD: 40% on average
USFD: 50% on average
-
Empirical Progression
INCOME ASSETS CASH FLOW
244 Households 316,763 cash flows 100 spending categories 38 income types 69 financial instruments
High-frequency data Households surveyed every 2-4 weeks
US Financial Diaries
-
Village studies • ICRISAT Village-level studies. 6 villages. 1974-85, 2001-4 • Palanpur, 1 village in Uttar Pradesh. 112 households.
1957/58, 1963/64, 1974/5, 1983/84, 2008-10 • Townsend Thai monthly village surveys. 1998 onward
• Insight: agricultural household model • Utility (home-grown good, market good, leisure)
maximized subject to – Cash income constraint – Time constraint – Production function
-
Structure • Corporate financial tools
– Balance sheets – Income statements – Cash flow statements
• Adding up constraint: inflows vs outflows
Krislert Samphantharak and Robert Townsend. 2009. Households as
Corporate Firms: An Analysis of Household Finance Using Integrated Household Surveys and Corporate Financial Accounting. Cambridge [Econometric Society Monographs].
-
Tracking the “Modes” of Payments
Jan received a paycheck and cashed it the same day Richard received wages onto prepaid card EBT card balance increased automatically Paid rent Paid vehicle loan, rent-to-own, recreation, alcohol Bought food, gasoline, clothing, cigarettes
$470
$800
$317
-$625
-$461
-$212
First Weekend
in June 1st-3rd
Received child care payment and cashed it Bought food Paid for vehicle maintenance Bought gasoline, food Bought clothing
$270
-$110
-$477
-$37 -$10
First Full Week
(Mon 4th –Sun 10th)
Jan received a paycheck and cashed it the same day Richard received wages onto prepaid card Paid loan, utilities Paid loan, insurance, bought food, prescription drugs
$781 $722
-$749
-$611
Second Week
Received money from mother Bought cigarettes, gasoline Bought food, housekeeping supplies
$30
-$23 -$56
Third Week
Received money from friend $30 Fourth Week
Household Example: “Jan and Richard” from June 1 to June 30 Amount
-
Margin of error US Financial Diaries
0%
20%
40%
60%
80%
100%
120%
140%
1 6 11 16 21 26Interview Number
67%
12%
Margin of error
Missing outflows + inflows divided by total outflows
It took 6 interviews (3+ months) to bring margin of error down substantially
-
$0$500
$1,000$1,500$2,000$2,500$3,000$3,500
25thPercentile
Median 75thPercentile
Income Distributions Earlier and Later in the Study
Initial QuestionnairesEnd-of-Study Cash Flow…
Precision over time
25%-37% increase
-
$0.78 per person per day
x 2.67 = $PPP 2.08 per person per day
-
Microfinance savings account
Saving with a moneyguard
Home savings
Life insurance
Remittance to home village
Loans to others
Cash in hand
Microfinance loan
Interest free loan from neighbor
Wage advance
Savings held for neighbors
Shopkeeper credit
Rent arrears
-
Volatility
-
www. USfinancialdiaries.org | ©, 2014
$2 a day is just an average…… Seasonal variations in monthly income
$0
$20
$40
$60
$80
$100
$120
$140
$160
$180
$200
Aug Sept Oct Nov Dec Jan Feb Mar Apr May June July Aug
Traders
Small Farmers
Appendix Figure A.1
-0.726398441
-0.9199011636
-3.4291159702
-0.6103714945
-1.5955796526
-0.3834176526
-0.0545323493
-0.3044022478
-0.0817491755
-0.2180559357
-0.2964965682
-0.0637464449
-0.3225552049
0.0124516578
0.0810273982
-0.0076981393
-0.0197246812
0.0301176016
0.019425984
-0.0819182362
0.0480258092
-0.1001486823
0.0264796019
0.0891200749
0.1569383251
0.1090021209
0.1094809482
0.4836879491
0.7164715026
0.3333333333
After about 6 interviews, the margin of error of data collection decreases to an average of 6%.
Number of interviews
Figure 5.3
End-DecEnd-Dec
JanJan
FebFeb
MarMar
AprApr
MayMay
JunJun
JulJul
AugAug
SepSep
OctOct
NovNov
DecDec
But saving at the ASCA savings rate of 30% per month gives you a return of 734% over the year, or $1322!
Principal
Interest
Principal
Interest
100
0
200
30
300
99
400
218.7
500
404.31
600
675.603
700
1058.2839
800
1585.76907
900
2301.499791
1000
3261.9497283
1100
4540.53464679
1200
6232.695040827
1300
8462.5035530751
Figure 5.2
End-DecEnd-Dec
JanJan
FebFeb
MarMar
AprApr
MayMay
JunJun
JulJul
AugAug
SepSep
OctOct
NovNov
DecDec
Adding $15 per month at 6% per annum would give you a return of 15% or $26
Interest
Principal
Principal
Interest
100
0
200
0.5
300
1.5025
400
3.0100125
500
5.0250625625
600
7.5501878753
700
10.5879388147
800
14.1408785088
900
18.2115829013
1000
22.8026408158
1100
27.9166540199
1200
33.55623729
1300
39.7240184764
Figure 5.1
2
4
5
6
7
8
10
11
12
13
15
16
18
19
22
25
26
30
31
33
35
36
37
41
47
51
52
65
70
79
80
84
90
131
199
202
236
Days
Term for which loans are quoted
3.6242977306
1.5533008589
3.8989627457
0.6
0.690803232
1.088955762
0.7248595461
0.3294816119
0.75
0.3719709711
0.4103656748
0.4530372163
0.4841154824
0.3947368421
0.4991255506
0.3369316877
0.2389693629
0
0.3129686178
0.1769202652
0.1775200982
0.1343228507
0.1385030216
0.1145700612
0.1028855877
0.079935232
0.0929927428
0.1398190386
0.1035513637
0.1224753916
0.0829875341
0.0719769528
0.0833333333
0.0501594781
0.0408640499
-0.0020922023
0.0563555595
Figure 4.2
-31
-31
-3193
-31
-31
-3193
Each month each member gives $31
And then receives $93 when it's her "turn"
And then the cycle repeats again….
Figure 4.1
-9
-9
-9
-9
-9
-9
-9
-9
-9
-9
-999
Every month each member contributes $9
On the final month, the members split the accumulated funds and each receive $99
Figure 2.3
3/20/20043/20/2004
3/26/20043/26/2004
4/2/20044/2/2004
4/8/20044/8/2004
4/16/20044/16/2004
4/23/20044/23/2004
4/30/20044/30/2004
5/8/20045/8/2004
5/15/20045/15/2004
5/21/20045/21/2004
5/29/20045/29/2004
6/4/20046/4/2004
6/11/20046/11/2004
6/17/20046/17/2004
6/24/20046/24/2004
7/2/20047/2/2004
7/9/20047/9/2004
7/23/20047/23/2004
7/30/20047/30/2004
8/6/20048/6/2004
8/13/20048/13/2004
8/20/20048/20/2004
8/27/20048/27/2004
9/4/20049/4/2004
9/10/20049/10/2004
9/17/20049/17/2004
9/25/20049/25/2004
10/2/200410/2/2004
10/9/200410/9/2004
10/16/200410/16/2004
10/22/200410/22/2004
10/30/200410/30/2004
11/6/200411/6/2004
11/12/200411/12/2004
11/19/200411/19/2004
11/27/200411/27/2004
Used money lender loan
Used savings club payout
Revenues plus credit collections
Inventory purchase and expenses
60
53.8461538462
46.9230769231
35.3846153846
46.1538461538
33.8461538462
43.0769230769
27.6923076923
35.3846153846
22.3076923077
60
33.8461538462
46.1538461538
26.1538461538
62.4615384615
35.3846153846
73.8461538462
49.5384615385
78.4615384615
41.5384615385
86.1538461538
51.5384615385
43.0769230769
24
69.2307692308
40
20
10.1538461538
18.4615384615
13.8461538462
23.8461538462
15.3846153846
29.2307692308
9.6923076923
55.3846153846
32.3076923077
21.5384615385
24.6153846154
41.5384615385
24
35.3846153846
30.1538461538
38.4615384615
26.1538461538
36.9230769231
40
63.0769230769
32.3076923077
69.2307692308
50.7692307692
61.5384615385
36.9230769231
70.6923076923
43.6153846154
69.6153846154
43.6153846154
48.0769230769
30.7692307692
87
63.6923076923
71.8461538462
53.3846153846
80.3076923077
38
96.4615384615
52.3846153846
97
50.8461538462
45.6923076923
40.0769230769
97.5384615385
76
Figure 2.2
AugAug
SeptSept
OctOct
NovNov
DecDec
JanJan
FebFeb
MarMar
AprApr
MayMay
JuneJune
JulyJuly
AugAug
&A
Page &P
Small farmers
Traders
25.2522796353
23.094224924
21.8054711246
17.3556231003
10.5410334347
15.7142857143
15.6291793313
57.2188449848
56.7933130699
16.4133738602
23.5319148936
34.4224924012
41.7933130699
46.3404255319
22.641337386
175.0607902736
42.8145896657
135.2127659574
66.2613981763
100.1215805471
79.2978723404
74.8176291793
8.9969604863
10.3951367781
42.1854103343
13.358662614
Figure 2.1
Definition 1: Regular wagesDefinition 1: Regular wages0.1428571429
Definition 2: Regular Wages + Casual WorkDefinition 2: Regular Wages + Casual Work0.4395604396
Definition 3: Regular Wages + Casual Work + Self EmployedDefinition 3: Regular Wages + Casual Work + Self Employed0.8571428571
South Africa
Bangladesh
India
0.4214876033
0.1590909091
0.5592286501
0.3818181818
0.6391184573
0.6909090909
-
www. USfinancialdiaries.org | ©, 2014
Pumza, South Africa
Net cash flows, aggregated weekly, US$
-
www. USfinancialdiaries.org | ©, 2014
The challenge of living on $2 a day is that $2 a day is just an average
-$10
$0
$10
$20
$30
$40
$50
-
www. USfinancialdiaries.org | ©, 2014
Spikes and Dips
-
www. USfinancialdiaries.org | ©, 2014
Few families have steady income
Average Income
+ 25%
- 25%
-
Average Income
- 25%
+ 25%
Five spikes/dips per year on average US Financial Diaries
2.7 Spikes
2.7 Dips
-
Self-reported month to month income variability SHED - Federal Reserve, 2013 Survey of Household Economics and Decisionmaking (7/14)
0%
10%
20%
30%
40%
Under $25,000 $25,000-$49,999 $50,000-$74,999 $75,000-$99,999 $100,000 orHigher
Perc
ent o
f Hou
seho
lds
Annual Income
“Some unusually high or low months”
“Often varies quite a bit from one month to the next”
SHED: Implemented in 9/2013. Nationally-representative sample. Online panel of 50,000 individuals sampled randomly. 6,912 asked to take the survey. About 60% (4,134) agreed. Quick survey (19 minutes median time)
-
Q: Which of the following is more important to you?
A. Financial Stability B. Moving up the income ladder
-
Portfolios of the Poor: The triple whammy
Low incomes
Irregular and unpredictable incomes
Lack of financial tools
-
Poverty
-
Volatility in Palanpur Poverty assessed in different ways
Apparent Prosperity
Current income
Permanent income
Regular job 24% 13% 30%
Agricultural laborer 76 64 59
Landless 70 44 55
Nicholas Stern and Peter Lanjouw. 1991. “Poverty in Palanpur.” World Bank Economic Review 5(1): 23-55. Table 4, p 38.
-
Poverty is often a condition of volatility (With opportunities
And challenges)
-
Charles Booth, Poverty Map of London, late 19th c
Dark Blue
Casual earnings: "very poor" (below 18s. per week for a moderate family). The labourers do not get as much as three days work a week, but it is doubtful if many could or would work full time for long together if they had the opportunity. Class B is not one in which men are born and live and die so much as a deposit of those who from mental, moral and physical reasons are incapable of better work.
Light Blue
Intermittent earnings. 18s to 21s per week for a moderate family. The victims of competition and on them falls with particular severity the weight of recurrent depressions of trade. Labourers, poorer artisans and street sellers. This irregularity of employment may show itself in the week or in the year: stevedores and waterside porters may secure only one of two days' work in a week, whereas labourers in the building trades may get only eight or nine months in a year.
-
Most of the volatility is within job US Financial Diaries
-
0
100
200
300
400
500
600
700
800
900
1000Janice's bi-weekly paychecks
Janice is not poor on average, but, based on income, she is poor 5 months of the year.
-
Sometimes poor
xcz
permanent income = x, consumption = c
Not poor Not poor
Not poor
Episodic poverty, transient poverty, poverty spells
Poor
Poor
Poor
-
91%
Sometimes poor % of USFD households with annual income above the (supplemental) poverty line that spent 1+ month with income under the poverty line
53
100%
200%
97%
65%
43%
150%
4 months 1.5 months
3 months
-
Chronic and Episodic poverty, 2009-11 Ashley Edwards. “Dynamics of Economic Well-Being: Poverty, 2009–2011” US Census Bureau. January 2014
29%
45% 9%
3%
90 million 10 million
-
Spell duration, 2009-11 Ashley Edwards. “Dynamics of Economic Well-Being: Poverty, 2009–2011” US Census Bureau. January 2014
-
Smoothing
-
Friedman: Permanent Income Little effect of stimulus
Save
Dis-save Income
Spending
-
Dynamic stochastic consumption, saving/consumption choice
+∑
−
=
−1
00)()1(max
T
tt
t CUE δ
0>tCtt
ttttt
IYA
rCYAA
∈≥
+−+=+
,0
)1)((:tosubject
1
-
Euler equation Along the optimal path, the marginal value of financial wealth = marginal
utility of consumption
)1/(])1)(([)(
1 δ++= + trCU'ECU'
tt
t
1212 )1/(])1)(([ δ++= + trCU'E tt
120120 )1/(])1)(([ δ++= + trCU'E tt
Next month
Next year
Next decade
Households may be smoothing on some margins but not on others
-
Soon Now Later
-
Saving for
Later
Overspending now
Saving for
Soon
-
Most savings are spent soon US Financial Diaries
85%
7% 5% 3%
44%
17% 16% 23%
0%10%20%30%40%50%60%70%80%90%
-
Microfinance savings account
Saving with a moneyguard
Home savings
Life insurance
Remittance to home village
Loans to others
Cash in hand
Microfinance loan
Interest free loan from neighbor
Wage advance
Savings held for neighbors
Shopkeeper credit
Rent arrears
-
From Portfolios of the Poor (2009) 3 needs that drive much of the financial activity: 1. Managing basics: Cash-flow management to transform irregular
income flows into a dependable resource to meet daily needs
2. Coping with risk: Dealing with the emergencies that can derail families with little in reserve
3. Raising lump sums: Seizing opportunities and paying for big-ticket expenses by accumulating usefully large sums of money
-
Final thoughts
• Not an argument to abandon science, or that qualitative work should be considered more scientific than it is.
• Argument: data collection and qualitative work as theory-building
• Argument: much research is increasingly narrowly scientific but not broadly scientific
• Big data needs little data
Thick description �in empirical economics�Slide Number 2Slide Number 3Paradox of social scienceOpportunitySlide Number 9Slide Number 10$2…If you earn $2 a day, it’s easy to assume…By Daryl Collins, Jonathan Morduch, �Stuart Rutherford and Orlanda Ruthven US Financial DiariesSupportU.S. Financial Diaries235 households allowed us to track every dollar they earned, saved, borrowed, shared, and spent for a full year.Financial DiariesSlide Number 19Why digital data aggregation would miss a lot�Fed Cash Product Office (April 2014)�Diary of Consumer Payment ChoiceEmpirical ProgressionVillage studiesStructureTracking the “Modes” of PaymentsMargin of error�US Financial DiariesPrecision over timeSlide Number 31Slide Number 32Slide Number 33$2 a day is just an average……�Slide Number 36Slide Number 37Spikes and DipsFew families have steady incomeFive spikes/dips per year on average� US Financial Diaries�Self-reported month to month income variability�SHED - Federal Reserve, 2013 Survey of Household Economics and Decisionmaking (7/14)Slide Number 42Portfolios of the Poor:�The triple whammySlide Number 44Volatility in Palanpur�Poverty assessed in different waysSlide Number 46Slide Number 47Slide Number 48Slide Number 49Most of the volatility is within job�US Financial DiariesSlide Number 51Sometimes poorSometimes poor�% of USFD households with annual income above the (supplemental) poverty line that spent 1+ month with income under the poverty lineChronic and Episodic poverty, 2009-11�Ashley Edwards. “Dynamics of Economic Well-Being: Poverty, 2009–2011” US Census Bureau. January 2014Spell duration, 2009-11�Ashley Edwards. “Dynamics of Economic Well-Being: Poverty, 2009–2011” US Census Bureau. January 2014Slide Number 70Friedman: Permanent Income�Little effect of stimulusDynamic stochastic consumption, saving/consumption choiceEuler equation�Along the optimal path, the marginal value of financial wealth = marginal utility of consumptionSlide Number 81Slide Number 82Most savings are spent soon�US Financial DiariesSlide Number 89From Portfolios of the Poor (2009)Final thoughts