Seeing Volatility

Published

February 11, 2026

Abstract

Graphs and regressions to measures how consumption responds to different draws

CDFs of Consumption

Note

Graphs here residualize out baseline consumption.

Note

Graphs here also residualize out period effects in addition baseline consumption.

Histograms

Broken down by Category and Draw

Regressions

Risky / Predictable Arm Regressions

Food

Dependent variable: log_food_consumption
Riskyno elw/ LagPredictableno elw/ Lag
(1)(2)(3)(4)(5)(6)
C(draw)[T.H]-0.024*-0.021-0.0220.0020.014-0.020
(0.014)(0.015)(0.015)(0.022)(0.024)(0.024)
C(draw_lag1)[T.H]-0.027*-0.041*
(0.015)(0.024)
C(period)[T.2]-0.272***-0.272***-0.240***-0.240***
(0.025)(0.025)(0.040)(0.039)
C(period)[T.3]-0.383***-0.383***-0.109***-0.360***-0.360***-0.120***
(0.024)(0.024)(0.024)(0.039)(0.039)(0.038)
C(period)[T.4]-0.439***-0.439***-0.169***-0.441***-0.441***-0.202***
(0.025)(0.024)(0.024)(0.039)(0.038)(0.038)
C(period)[T.5]-0.468***-0.468***-0.195***-0.486***-0.486***-0.247***
(0.025)(0.024)(0.024)(0.039)(0.039)(0.038)
C(period)[T.6]-0.198***0.068***-0.177***0.063*
(0.024)(0.024)(0.039)(0.038)
Intercept5.006***5.058***4.757***4.943***4.980***4.758***
(0.076)(0.083)(0.083)(0.114)(0.123)(0.122)
bl_log_food_consumption0.235***0.227***0.233***0.247***0.240***0.243***
(0.011)(0.012)(0.012)(0.017)(0.018)(0.018)
Control Mean6.196.196.196.196.196.19
Observations548745294579224618501907
Note:*p<0.1; **p<0.05; ***p<0.01
Dependent variable: food_purchase_total_99
Riskyno elw/ LagPredictableno elw/ Lag
(1)(2)(3)(4)(5)(6)
C(draw)[T.H]-17.898**-16.643*-17.995**9.13518.6190.713
(8.969)(9.348)(9.144)(14.627)(15.064)(15.539)
C(draw_lag1)[T.H]-5.067-20.304
(9.141)(15.540)
C(period)[T.2]-143.120***-143.564***-144.068***-144.343***
(15.989)(15.136)(26.126)(24.421)
C(period)[T.3]-208.969***-209.320***-64.617***-199.553***-199.700***-55.599**
(15.812)(14.967)(14.471)(25.861)(24.173)(24.279)
C(period)[T.4]-251.515***-251.786***-108.471***-239.326***-239.546***-95.337***
(15.841)(14.996)(14.441)(25.767)(24.085)(24.187)
C(period)[T.5]-265.858***-265.971***-121.907***-281.908***-282.192***-138.292***
(15.934)(15.083)(14.596)(25.975)(24.280)(24.391)
C(period)[T.6]-73.097***63.762***-57.281**86.563***
(15.777)(14.456)(25.645)(24.069)
Intercept547.430***559.236***410.656***541.674***552.639***417.566***
(14.577)(14.333)(14.551)(23.339)(22.640)(24.349)
bl_food_purchase_total_990.144***0.131***0.140***0.145***0.128***0.139***
(0.008)(0.009)(0.008)(0.013)(0.013)(0.013)
Control Mean459.47459.47459.47459.47459.47459.47
Observations548745294579224618501907
Note:*p<0.1; **p<0.05; ***p<0.01
Dependent variable: expenditure_total_food_99
Riskyno elw/ LagPredictableno elw/ Lag
(1)(2)(3)(4)(5)(6)
C(draw)[T.H]-10.370**-9.821*-6.4797.0818.2060.327
(5.250)(5.754)(5.341)(8.013)(8.715)(8.102)
C(draw_lag1)[T.H]5.454-5.809
(5.340)(8.102)
C(period)[T.2]-39.244***-39.243***-45.173***-45.144***
(9.364)(9.319)(14.317)(14.131)
C(period)[T.3]-67.012***-66.999***-27.688***-59.750***-59.752***-14.597
(9.260)(9.214)(8.458)(14.181)(13.996)(12.653)
C(period)[T.4]-70.424***-70.426***-29.561***-95.977***-96.036***-50.760***
(9.272)(9.228)(8.435)(14.130)(13.946)(12.606)
C(period)[T.5]-76.526***-76.511***-37.432***-73.312***-73.373***-28.223**
(9.330)(9.285)(8.529)(14.244)(14.058)(12.713)
C(period)[T.6]-51.576***-11.820-47.951***-2.781
(9.235)(8.443)(14.055)(12.536)
Intercept314.989***313.513***272.069***306.302***308.463***266.725***
(8.131)(8.363)(8.139)(12.219)(12.449)(12.199)
bl_expenditure_total_food_990.084***0.087***0.080***0.088***0.081***0.090***
(0.009)(0.010)(0.009)(0.013)(0.014)(0.013)
Control Mean266.25266.25266.25266.25266.25266.25
Observations545645024555224118451904
Note:*p<0.1; **p<0.05; ***p<0.01

Non-food Expenditure

High / Low Draw Regressions

Savings (Flow and Stock)

Dependent variable: svg_savings_flow_99
Riskyno elw/ LagPredictableno elw/ Lag
(1)(2)(3)(4)(5)(6)
C(draw)[T.H]5.891-1.6805.67823.01523.97321.835
(12.700)(14.145)(13.010)(19.874)(22.265)(20.033)
C(draw_lag1)[T.H]20.620-15.285
(13.007)(20.028)
C(period)[T.2]-5.511-4.915-21.004-21.042
(22.891)(23.148)(35.952)(36.567)
C(period)[T.3]-38.028*-37.997*-30.693-52.853-53.123-31.000
(22.100)(22.346)(21.106)(34.741)(35.336)(32.112)
C(period)[T.4]5.6095.72613.326-34.382-34.541-12.998
(21.974)(22.221)(20.920)(34.284)(34.870)(31.706)
C(period)[T.5]-1.554-2.014-0.388-19.033-19.3713.199
(22.044)(22.290)(21.064)(34.448)(35.037)(31.850)
C(period)[T.6]55.275**65.703***13.97336.852
(21.972)(21.011)(34.357)(31.771)
Intercept28.37740.217**-25.25843.61349.716*0.876
(17.688)(18.239)(18.840)(27.558)(28.548)(28.831)
bl_svg_savings_flow_99-0.138***-0.165***-0.012-0.129***-0.151***-0.028
(0.014)(0.015)(0.014)(0.022)(0.025)(0.022)
Control Mean-1.79-1.79-1.79-1.79-1.79-1.79
Observations485740074011201616621694
Note:*p<0.1; **p<0.05; ***p<0.01
Dependent variable: svg_current_savings_99
Riskyno elw/ LagPredictableno elw/ Lag
(1)(2)(3)(4)(5)(6)
C(draw)[T.H]-12.763-25.977**-15.5383.08111.1474.389
(11.486)(12.588)(12.350)(18.477)(20.638)(18.861)
C(draw_lag1)[T.H]-8.2436.504
(12.344)(18.860)
C(period)[T.2]4.5575.135-29.133-28.918
(20.474)(20.380)(33.004)(33.454)
C(period)[T.3]-32.035-32.025-38.354**-58.858*-58.766*-29.584
(20.247)(20.153)(19.544)(32.668)(33.114)(29.466)
C(period)[T.4]-38.834*-38.109*-41.430**-80.623**-80.536**-51.391*
(20.286)(20.193)(19.503)(32.550)(32.994)(29.354)
C(period)[T.5]-62.636***-62.757***-66.802***-93.131***-92.930***-63.849**
(20.407)(20.312)(19.713)(32.812)(33.261)(29.602)
C(period)[T.6]-11.109-15.197-60.172*-30.912
(20.204)(19.524)(32.396)(29.211)
Intercept246.169***251.659***255.320***264.034***257.305***233.443***
(16.328)(16.550)(17.204)(26.111)(26.932)(26.218)
bl_svg_current_savings_990.162***0.166***0.164***0.178***0.187***0.170***
(0.011)(0.012)(0.012)(0.019)(0.021)(0.019)
Control Mean270.66270.66270.66270.66270.66270.66
Observations548745294579224618501907
Note:*p<0.1; **p<0.05; ***p<0.01

Total Asset Purchases and Sales

Dependent variable: expenditure_total_nonfood_99
Riskyno elw/ LagPredictableno elw/ Lag
(1)(2)(3)(4)(5)(6)
C(draw)[T.H]1.4171.9612.1811.0936.404-0.150
(5.532)(4.868)(5.991)(8.920)(7.665)(9.769)
C(draw_lag1)[T.H]5.362-2.436
(5.988)(9.770)
C(period)[T.2]-62.543***-62.919***-73.912***-74.019***
(9.883)(7.894)(15.980)(12.442)
C(period)[T.3]-83.731***-83.919***-21.882**-91.776***-91.910***-17.872
(9.763)(7.797)(9.493)(15.797)(12.299)(15.314)
C(period)[T.4]-93.180***-93.376***-30.797***-113.425***-113.548***-39.501***
(9.782)(7.813)(9.473)(15.730)(12.247)(15.247)
C(period)[T.5]-104.607***-104.715***-41.351***-115.313***-115.503***-41.496***
(9.837)(7.856)(9.572)(15.856)(12.345)(15.375)
C(period)[T.6]123.562***185.413***110.061***183.883***
(9.730)(9.471)(15.602)(15.118)
Intercept186.956***197.821***122.413***193.421***198.249***125.567***
(8.142)(6.651)(8.659)(12.952)(10.304)(13.975)
bl_expenditure_total_nonfood_990.084***0.049***0.081***0.115***0.091***0.101***
(0.008)(0.007)(0.009)(0.012)(0.011)(0.013)
Control Mean172.19172.19172.19172.19172.19172.19
Observations547345124571224718451909
Note:*p<0.1; **p<0.05; ***p<0.01
Note

Durable assets include: livestock, land, durable goods and agricultural equipment.

Dependent variable: asset_purchases_99
Riskyno elw/ LagPredictableno elw/ Lag
(1)(2)(3)(4)(5)(6)
C(draw)[T.H]1.966-3.3074.542-8.790-4.777-3.442
(3.740)(3.125)(4.010)(6.526)(6.038)(7.270)
C(draw_lag1)[T.H]1.522-0.183
(4.008)(7.271)
C(period)[T.2]-26.358***-26.126***-9.640-9.605
(6.666)(5.059)(11.655)(9.787)
C(period)[T.3]-31.322***-31.292***-5.813-26.185**-26.204***-16.551
(6.592)(5.003)(6.345)(11.537)(9.687)(11.356)
C(period)[T.4]-37.571***-37.247***-11.232*-36.786***-36.818***-27.186**
(6.605)(5.013)(6.332)(11.495)(9.652)(11.314)
C(period)[T.5]-38.509***-38.536***-12.180*-30.795***-30.787***-21.149*
(6.644)(5.042)(6.400)(11.588)(9.730)(11.409)
C(period)[T.6]58.803***83.927***59.027***68.625***
(6.578)(6.339)(11.441)(11.259)
Intercept56.817***60.701***28.110***59.608***58.539***46.672***
(5.232)(4.032)(5.508)(9.068)(7.736)(9.982)
bl_asset_purchases_990.029**0.0030.032**0.110***0.093***0.123***
(0.012)(0.010)(0.013)(0.018)(0.016)(0.020)
Control Mean50.0050.0050.0050.0050.0050.00
Observations548745294579224618501907
Note:*p<0.1; **p<0.05; ***p<0.01
Note

Durable assets include: livestock, land, durable goods and agricultural equipment.

Dependent variable: asset_sales_99
Riskyno elw/ LagPredictableno elw/ Lag
(1)(2)(3)(4)(5)(6)
C(draw)[T.H]0.0980.275-0.231-3.298-1.895-3.401
(1.613)(1.365)(1.755)(2.757)(2.148)(3.140)
C(draw_lag1)[T.H]-2.022-2.093
(1.755)(3.140)
C(period)[T.2]-1.967-1.960-0.598-0.598
(2.876)(2.211)(4.925)(3.481)
C(period)[T.3]-7.246**-7.201***-5.302*-2.073-2.066-1.506
(2.844)(2.186)(2.778)(4.875)(3.446)(4.905)
C(period)[T.4]-5.837**-5.812***-3.962-1.968-1.972-1.398
(2.850)(2.190)(2.772)(4.857)(3.433)(4.887)
C(period)[T.5]-5.564*-5.525**-3.541-3.185-3.176-2.640
(2.867)(2.203)(2.802)(4.896)(3.461)(4.928)
C(period)[T.6]17.472***19.930***27.779***28.334***
(2.838)(2.775)(4.834)(4.863)
Intercept8.525***8.872***7.979***6.487*6.011**6.902
(2.255)(1.761)(2.406)(3.841)(2.758)(4.309)
bl_asset_sales_990.012*-0.0010.0100.028***0.023***0.030**
(0.007)(0.006)(0.007)(0.011)(0.008)(0.012)
Control Mean10.4210.4210.4210.4210.4210.42
Observations548745294579224618501907
Note:*p<0.1; **p<0.05; ***p<0.01

Loan Payments

Dependent variable: loan_total_payment
Riskyno elw/ LagPredictableno elw/ Lag
(1)(2)(3)(4)(5)(6)
C(draw)[T.H]3.7382.6164.705-7.486-6.223-4.734
(3.375)(3.843)(3.856)(6.400)(7.063)(5.472)
C(draw_lag1)[T.H]0.799-1.798
(3.855)(5.472)
C(period)[T.2]11.057*11.114*-26.214**-26.191**
(6.016)(6.219)(11.431)(11.448)
C(period)[T.3]-4.122-4.107-15.355**-35.716***-35.690***-9.545
(5.949)(6.150)(6.102)(11.316)(11.332)(8.548)
C(period)[T.4]-3.682-3.611-14.843**-32.542***-32.519***-6.388
(5.960)(6.162)(6.089)(11.274)(11.291)(8.516)
C(period)[T.5]-7.627-7.618-18.473***-34.486***-34.459***-8.322
(5.996)(6.199)(6.154)(11.365)(11.382)(8.588)
C(period)[T.6]-6.106-16.755***-23.025**3.104
(5.936)(6.096)(11.221)(8.474)
Intercept17.863***18.259***28.110***53.378***52.497***26.923***
(4.697)(4.927)(5.262)(8.853)(8.995)(7.465)
bl_loan_total_payment0.035***0.043***0.030***0.065**0.078***0.055**
(0.007)(0.008)(0.008)(0.026)(0.028)(0.022)
Control Mean15.3515.3515.3515.3515.3515.35
Observations548745294579224618501907
Note:*p<0.1; **p<0.05; ***p<0.01

Appendix

Mental Health

Dependent variable: gad2_z
Riskyno elw/ LagPredictableno elw/ Lag
(1)(2)(3)(4)(5)(6)
C(draw)[T.H]-0.057**-0.062**-0.054*-0.052-0.053-0.015
(0.027)(0.028)(0.029)(0.042)(0.044)(0.046)
C(draw_lag1)[T.H]-0.0200.058
(0.029)(0.046)
C(period)[T.2]-0.156***-0.156***-0.099-0.099
(0.048)(0.046)(0.075)(0.072)
C(period)[T.3]-0.210***-0.210***-0.042-0.211***-0.211***-0.111
(0.047)(0.046)(0.046)(0.074)(0.071)(0.072)
C(period)[T.4]-0.289***-0.289***-0.138***-0.261***-0.261***-0.161**
(0.047)(0.046)(0.046)(0.074)(0.071)(0.072)
C(period)[T.5]-0.314***-0.314***-0.167***-0.446***-0.446***-0.346***
(0.048)(0.046)(0.047)(0.074)(0.071)(0.073)
C(period)[T.6]0.197***0.344***0.258***0.358***
(0.047)(0.046)(0.073)(0.072)
Intercept-0.034-0.032-0.181***0.0170.016-0.130**
(0.037)(0.036)(0.040)(0.058)(0.056)(0.063)
bl_gad2_z0.099***0.098***0.086***0.123***0.106***0.123***
(0.014)(0.015)(0.015)(0.020)(0.021)(0.022)
Control Mean-0.12-0.12-0.12-0.12-0.12-0.12
Observations547445294567223918501900
Note:*p<0.1; **p<0.05; ***p<0.01
Dependent variable: phq2_z
Riskyno elw/ LagPredictableno elw/ Lag
(1)(2)(3)(4)(5)(6)
C(draw)[T.H]-0.038-0.053**-0.034-0.013-0.0260.022
(0.024)(0.026)(0.026)(0.039)(0.042)(0.043)
C(draw_lag1)[T.H]-0.0130.084*
(0.026)(0.043)
C(period)[T.2]-0.095**-0.095**-0.073-0.073
(0.043)(0.042)(0.070)(0.068)
C(period)[T.3]-0.086**-0.087**0.016-0.141**-0.141**-0.068
(0.043)(0.042)(0.042)(0.069)(0.067)(0.068)
C(period)[T.4]-0.126***-0.125***-0.034-0.146**-0.146**-0.073
(0.043)(0.042)(0.042)(0.069)(0.067)(0.067)
C(period)[T.5]-0.146***-0.147***-0.055-0.255***-0.255***-0.180***
(0.043)(0.042)(0.042)(0.069)(0.068)(0.068)
C(period)[T.6]0.238***0.325***0.261***0.335***
(0.043)(0.042)(0.069)(0.067)
Intercept-0.201***-0.192***-0.288***-0.126**-0.119**-0.259***
(0.034)(0.033)(0.036)(0.054)(0.053)(0.059)
bl_phq2_z0.084***0.070***0.077***0.094***0.083***0.096***
(0.012)(0.013)(0.013)(0.019)(0.021)(0.021)
Control Mean-0.15-0.15-0.15-0.15-0.15-0.15
Observations547445294567223918501900
Note:*p<0.1; **p<0.05; ***p<0.01