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Time Preference & Cognition Survey 2009 - 2010

Malawi, 2009 - 2010
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Reference ID
MWI_2009-2010_TPCS_v01_M
Producer(s)
Xavier Giné, Jessica Goldberg, Dan Silverman, Dean Yang
Metadata
DDI/XML JSON
Created on
Sep 19, 2018
Last modified
Sep 19, 2018
Page views
15516
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  • Study Description
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  • GGSY_data
  • GGSY_data_long
  • sim_data

Data file: GGSY_data

GGSY_data.dta: This file contains data from an artefactual field experiment in Malawi that measures time preferences and revision behavior. The sample consists of several hundred wife-husband pairs in rural Malawi. Intertemporal choices are elicited by adapting Andreoni and Sprenger's (2012) convex time budget method, with large real stakes (roughly a month's wages). Subjects decide five potential allocations of money to be disbursed at two points, 61 or 91 days, in the future for the corresponding interest rates: 10%, 25%, 50%, 75%, and 100%. A subset of these subjects was revisited some time prior to the first disbursement at t=61 days and given the opportunity to revise their allocation between sooner or later. Dataset contains N=10,710 decisions (i.e., five allocations and associated interest rate for 2,142 subjects in the study).

Cases: 2157
Variables: 398

Variables

respid
Respondent ID
hhid
Household ID
target_lag
Days to first disbursement at revisit (target)
actual_lag
Days to first disbursement at revisit (actual)
v2_mk
Initial sooner allocation (value, MK)
v4_beans
Initial later allocation (beans)
v4_mk
Initial later allocation (value, MK)
v6_mk
Final sooner allocation (MK)
v7_mk
Final later allocation (MK)
b1_1_1
Expenditure in April on food
b1_1_2
Expenditure in May on food
b1_1_3
Expenditure in June on food
b1_1_4
Expenditure in July on food
b1_1_5
Expenditure in August on food
b1_2_1
Expenditure in April on medicine
b1_2_2
Expenditure in May on medicine
b1_2_3
Expenditure in June on medicine
b1_2_4
Expenditure in July on medicine
b1_2_5
Expenditure in August on medicine
b1_3_1
Expenditure in April on school fees
b1_3_2
Expenditure in May on school fees
b1_3_3
Expenditure in June on school fees
b1_3_4
Expenditure in July on school fees
b1_3_5
Expenditure in August on school fees
b1_4_1
Expenditure in April on farm expenditures
b1_4_2
Expenditure in May on farm expenditures
b1_4_3
Expenditure in June on farm expenditures
b1_4_4
Expenditure in july on farm expenditures
b1_4_5
Expenditure in August on farm expenditures
b1_5_1
Expenditure in April on transport
b1_5_2
Expenditure in May on transport
b1_5_3
Expenditure in June on transport
b1_5_4
Expenditure in July on transport
b1_5_5
Expenditure in August on transport
b1_6_1
Expenditure in April on other household items
b1_6_2
Expenditure in May on other household items
b1_6_3
Expenditure in June on other household items
b1_6_4
Expenditure in July on other household items
b1_6_5
Expenditure in August on other household items
b2_1
How many days in April did you have less than 3 meals?
b2_2
How many days in May did you have less than 3 meals?
b2_3
How many days in June did you have less than 3 meals?
b2_4
How many days in July did you have less than 3 meals?
b2_5
How many days in August did you have less than 3 meals?
b3_1
How many days in April did children have less than 3 meals?
b3_2
How many days in May did children have less than 3 meals?
b3_3
How many days in June did children have less than 3 meals?
b3_4
How many days in July did children have less than 3 meals?
b3_5
How many days in August did children have less than 3 meals?
dC_2
Change in later consumption upon revisiting
dC_1
Change in sooner consumption upon revisiting
revised_pb
revisions present biased
revised_fb
revisions future biased
qualflag
(mean) qualflag
rlspsdiffc_f_soon
(mean) rlspsdiffc_f_soon
imple_rbasis
(mean) imple_rbasis
timeprefA
(mean) timeprefA
commitmentsavings
(mean) commitmentsavings
ordinarysavings
(mean) ordinarysavings
wealth_bline1
(mean) wealth_bline_M
lnwealth_bline_M
Ln(baseline wealth)
z13_day
(mean) z13_day
z13_month
(mean) z13_month
male
Male
numinvillage
(mean) numinvillage
relatives
Number of relatives in the village
havemaize
Have adequate maize
maizemissing
(mean) maizemissing
younger
Less than 35 yrs old
middleage
35-37 yrs old
older
(mean) older
no_school
(mean) no_school
some_primary
Some primary school
primary
Primary school
morethan_primary
More than primary school
wrdrecal_1
Words recalled
wrdrecal_1sq
(mean) wrdrecal_1sq
wrdrecal_2
(mean) wrdrecal_2
wrdrecal_2sq
(mean) wrdrecal_2sq
rm1_correct
(mean) rm1_correct
rm2_correct
(mean) rm2_correct
rm3_correct
(mean) rm3_correct
ravens
Raven's Tests correct
finlit_1
(mean) finlit_1
finlit_dk_1
(mean) finlit_dk_1
finlit_2
(mean) finlit_2
finlit_dk_2
(mean) finlit_dk_2
finlit_3
(mean) finlit_3
finlit_dk_3
(mean) finlit_dk_3
finlit_total
Financial literacy questions correct
finlit_dk_total
(mean) finlit_dk_total
presbias
(mean) presbias
presbias_2
(mean) presbias_2
futurebias
(mean) futurebias
futurebias_2
(mean) futurebias_2
consistent
(mean) consistent
consistent_2
(mean) consistent_2
fracpb
(mean) fracpb
fracfb
(mean) fracfb
fracconsis
(mean) fracconsis
fracpb_2
(mean) fracpb_2
fracfb_2
(mean) fracfb_2
fracconsis_2
(mean) fracconsis_2
havedemos
(mean) havedemos
a1
(mean) a1
a2
(mean) a2
a4
(mean) a4
b1_100
(mean) b1_100
b1_110
(mean) b1_110
b2_100
(mean) b2_100
b2_125
(mean) b2_125
b3_100
(mean) b3_100
b3_150
(mean) b3_150
b4_100
(mean) b4_100
b4_175
(mean) b4_175
b5_100
(mean) b5_100
b5_200
(mean) b5_200
b6_100
(mean) b6_100
b6_110
(mean) b6_110
b7_100
(mean) b7_100
b7_125
(mean) b7_125
b8_100
(mean) b8_100
b8_150
(mean) b8_150
b9_100
(mean) b9_100
b9_175
(mean) b9_175
b10_100
(mean) b10_100
b10_200
(mean) b10_200
improreturn
Implemented interest rate \{.1, .25, .5, .75, 1\}
first_merge
merge variable
deathinfam
Indicator: death in the family
delta_hh_tot_exp
change in total household expenditure
delta_income
Shortfall in expected HH income (MK)
own_transfer_card
indiv own transfer card
own_sooner_tokens
indiv own tokens - sooner
own_later_tokens
indiv own tokens - later
own_sooner_mk
indiv own in mk - sooner
own_later_mk
indiv own in mk - later
spouse_b1_100
(mean) b1_100
spouse_b1_110
(mean) b1_110
spouse_b2_100
(mean) b2_100
spouse_b2_125
(mean) b2_125
spouse_b3_100
(mean) b3_100
spouse_b3_150
(mean) b3_150
spouse_b4_100
(mean) b4_100
spouse_b4_175
(mean) b4_175
spouse_b5_100
(mean) b5_100
spouse_b5_200
(mean) b5_200
spouse_b6_100
(mean) b6_100
spouse_b6_110
(mean) b6_110
spouse_b7_100
(mean) b7_100
spouse_b7_125
(mean) b7_125
spouse_b8_100
(mean) b8_100
spouse_b8_150
(mean) b8_150
spouse_b9_100
(mean) b9_100
spouse_b9_175
(mean) b9_175
spouse_b10_100
(mean) b10_100
spouse_b10_200
(mean) b10_200
spouse_qualflag
(mean) qualflag
spouse_timeprefA
(mean) timeprefA
spouse_wealth_bline
(mean) wealth_bline_M
spouse_frac_posdcs
(mean) frac_posdcs
spouse_relatives
(mean) relatives
spouse_havemaize
(mean) havemaize
spouse_young
(mean) younger
spouse_middleage
(mean) middleage
spouse_some_primary
(mean) some_primary
spouse_primary
(mean) primary
spouse_morethan_primary
(mean) morethan_primary
spouse_wrdrecal_1
(mean) wrdrecal_1
spouse_ravens
(mean) ravens
spouse_finlit_total
(mean) finlit_total
spouse_presbias
(mean) presbias
spouse_presbias_2
(mean) presbias_2
spouse_futurebias
(mean) futurebias
spouse_futurebias_2
(mean) futurebias_2
spouse_consistent
(mean) consistent
spouse_consistent_2
(mean) consistent_2
spouse_fracpb
(mean) fracpb
spouse_fracfb
(mean) fracfb
spouse_fracconsis
(mean) fracconsis
spouse_fracpb_2
(mean) fracpb_2
spouse_fracconsis_2
(mean) fracconsis_2
spouse_transfer_card
spouse's transfer card
spouse_sooner_tokens
spouse's tokens - sooner
spouse_later_tokens
spouse's tokens - later
spouse_sooner_mk
spouse's in mk - sooner
spouse_later_mk
spouse's in mk - later
gap_tokens
gap in tokens
gap_mk
gap in mk
which_svy
which surveys
strat
Randomization Strat var
d_fixdepoOIBM_sr
[HS14d]0/1: fixed deposit account at OIBM
d_fixdepoOth
[HS14]0/1: Any fixed deposit account, non-OIBM
d_fixdepoAll
[HS14]0/1: Any fixed deposit account, any bank
treatment
Treatment Group
tr_tot_EL
[TR](MK)Total transfers received
TRb0t99tr_tot_EL
[TR](MK)Total transfers received;TRIM(0&99)
tr_totPRE_EL
[TR](MK)transfers received, big gift<=Oct09
TRb0t99tr_totPRE_EL
[TR](MK)transfers received, big gift<=Oct09;TRIM(0&99);
ts_tot_EL
[TR](MK)Total transfers sent
ts_totPRE_EL
[TR](MK)transfers sent, big gift<=Oct09
TRb0t99ts_totPRE_EL
[TR](MK)transfers sent, big gift<=Oct09;TRIM(0&99);
abrlspsdiffc_f_soon
abrlspsdiffc_f_soon
spsdiffpos
spsdiffpos
pos_abrlspsdiffc_f_soon
pos_abrlspsdiffc_f_soon
actual_lag_squared
actual lag squared
pblag_interaction
pb lag interaction
net_transfers
net transfers
ini_pb_sim
ini_pb_sim
fracpbothersim
fracpbothersim
club_reg_no
club registration number
respid_num
Commitment Savings respondent ID / Revising Commitment HH ID
d_maleRC
0/1:male RC voucher holder
d_sooner
0/1:treatment=tmrw/1month (vs 2m/3m)
intrate
treatment:interest rate offered
ureaperacre
urea per acre
spousebias_sooner_mk
spouse bias sooner in mk
spousebias_all_sooner
spouse bias - sooner
spousebias_nonimp
Spouse minus own allocation to sooner (MK)
spousebias_near
spouse bias - near
spousebias_far
spouse bias - far
spousebias_imp
spouse bias imp
spousebias_nonimpfar
spouse bias non-imp far
treatment_1
1 treatment
treatment_2
2 treatment
treatment_3
3 treatment
treatment_4
4 treatment
treatment_5
5 treatment
treatment_6
6 treatment
c_delta_soon10
Difference between Soon and Far:MK in two months, for r=0.1
c_delta_soon25
Difference between Soon and Far:MK in two months, for r=0.25
c_delta_soon50
Difference between Soon and Far:MK in two months, for r=0.50
c_delta_soon75
Difference between Soon and Far:MK in two months, for r=0.75
c_delta_soon100
Difference between Soon and Far:MK in two months, for r=1.00
pb_all
pb all
pb_nonimp
pb non-imp
pb_imp
pb imp
fracpb_imp
Indicator of Present Bias for Implemented Interest Rate
fracpb_2_imp
frac pb 2, imp
target_lag_2_6
Indicator: days to first disbursement (targeted) $\leq 6$
target_lag_7_11
target lag 7-11
target_lag_12_16
target lag 12-16
hh_tot_bank_bline
HH total bank-BL
hh_cash_bline
HH case-BL
exp_income_bline
exp income-BL
exp_revenue_bline
exp rev-BL
sell_items_bline
from selling items-BL
sell_animals_bline
from selling animals-BL
wealth_bline
Baseline wealth (100s of MK)
younger_female
(mean) younger
middleage_female
(mean) middleage
a1_female
(mean) a1
younger_male
(mean) younger
middleage_male
(mean) middleage
a1_male
(mean) a1
spouse_age_n
spouse age
own_sooner_far_imp
own_sooner_far_imp
dC_1_new
dummy C1 1
d_C1test
dummy C1 1
indicator_pb_2_10
indicator present bias 2, int. rate=0.10
indicator_pb_2_25
indicator present bias 2, int. rate=0.25
indicator_pb_2_50
indicator present bias 2, int. rate=0.50
indicator_pb_2_75
indicator present bias 2, int. rate=0.75
indicator_pb_2_100
indicator present bias 2, int. rate=1.0
fracpb_2_nonimp
Fraction present-biased, non-implemented interest rates
indicator_fb_2_10
indicator future bias 2, int. rate=0.10
indicator_fb_2_25
indicator future bias 2, int. rate=0.25
indicator_fb_2_50
indicator future bias 2, int. rate=0.50
indicator_fb_2_75
indicator future bias 2, int. rate=0.75
indicator_fb_2_100
indicator future bias 2, int. rate=1.0
fracfb_2_nonimp
Fraction future-biased, non-implemented interest rates
indicator_pb_10
indicator present bias, int. rate=0.10
indicator_pb_25
indicator present bias, int. rate=0.25
indicator_pb_50
indicator present bias, int. rate=0.50
indicator_pb_75
indicator present bias, int. rate=0.75
indicator_pb_100
indicator present bias, int. rate=1.0
fracpb_nonimp
Fraction of Present Bias for Non-Implemented Interest Rate
spousebias_nonimp_wt
spouse's bias, non-imp, wt
pb_all_wt
present bias - wt
pb_nonimp_wt
present bias, non-imp, wt
fracpb_2_wt
frac pb, wt
fracpb_2_nonimp_wt
frac pb 2, non-imp, wt
improreturn10
improreturn .10
improreturn25
improreturn .25
improreturn50
improreturn .50
improreturn75
improreturn .75
improreturn100
improreturn 1.0
spouse_sooner_nonimpfar
spouse_sooner_nonimpfar
own_sooner_nonimpfar
own_sooner_nonimpfar
spouse_sooner_far_imp
spouse_sooner_far_imp
indicator_sb_near_10
indicator: sb near, 0.10
indicator_sb_near_25
indicator: sb near, 0.25
indicator_sb_near_50
indicator: sb near, 0.50
indicator_sb_near_75
indicator: sb near, 0.75
indicator_sb_near_100
indicator: sb near, 1.0
indicator_sb_far_10
indicator: sb far, 0.10
indicator_sb_far_25
indicator: sb far, 0.25
indicator_sb_far_50
indicator: sb far, 0.50
indicator_sb_far_75
indicator: sb far, 0.75
indicator_sb_far_100
indicator: sb far, 1.0
Total: 398
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