SlideShare a Scribd company logo

Sujata Visaria: Finding the Diamonds in the Rough - Welfare Comparisons of Two Targeting Mechanisms in Microcredit

•
•
HKUST IEMS
HKUST IEMS

In a HKUST IEMS Academic Seminar, Sujata VIsaria (HKUST) examined the distributive impacts of two alternative approaches to deliver agricultural credit to smallholders: TRAIL (or trader-agent intermediated lending), where local traders recommend village residents for individual liability micro-loans, and GBL (or group-based lending), where households self-select into groups and receive joint liability loans. This is joint work with Pushkar Maitra, Sandip Mitra and Dilip Mookherjee. Find out more about the event at http://iems.ust.hk/trail

Economy & Finance
1 of 76
Download to read offline
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Finding the Diamonds in the Rough The Equity Impacts of Targeting Smallholder Agricultural Credit Pushkar Maitra, Sandip Mitra, Dilip Mookherjee, Sujata Visaria HKUST Institute for Emerging Market Studies 9 March 2017 MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 1 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Targeting Private Benefits MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 2 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Targeting Private Benefits How should governments choose the recipients of private benefits? subsidies: food, fertilizer transfer payments: pensions MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 2 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Targeting Private Benefits How should governments choose the recipients of private benefits? subsidies: food, fertilizer transfer payments: pensions Centralized schemes: lack of information Decentralized schemes: corruption & elite capture MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 2 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Smallholder Agricultural Credit Designing agricultural credit programs for small farmers State-sponsored efforts: poor information leads to high default Microcredit: high repayment, but does not usually target agriculture Can we design a scheme that leverages local information? and avoids problems of elite capture? MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 3 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Agent-intermediated Lending MMMMV (2017) designed an alternative credit delivery mechanism (AIL): MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 4 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Agent-intermediated Lending MMMMV (2017) designed an alternative credit delivery mechanism (AIL): Leverages local information, but differently Individual liability loans Borrowers recommended by a local “agent” embedded in the community Agent incentivized by commissions that depend on repayment MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 4 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Agent-intermediated Lending MMMMV (2017) designed an alternative credit delivery mechanism (AIL): Leverages local information, but differently Individual liability loans Borrowers recommended by a local “agent” embedded in the community Agent incentivized by commissions that depend on repayment Field experiment in 48 villages TRAIL loans had positive significant average impacts on farm value-added: 22% MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 4 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Average Treatment Effects: Farm and Non-Farm Income (Efficiency) MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 5 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion The Mechanism TRAIL agents are more likely to select “able” borrowers high productivity low risk of crop failure MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 6 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion The Mechanism TRAIL agents are more likely to select “able” borrowers high productivity low risk of crop failure Positive impacts are larger for the more able farmers MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 6 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion The Comparison: Group-based Lending Group-based lending involves self-selected borrower groups Joint liability lending Participation does not require recommendation by an agent MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 7 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion The Comparison: Group-based Lending Group-based lending involves self-selected borrower groups Joint liability lending Participation does not require recommendation by an agent Both high and low ability individuals will form groups Because both pay lower interest rates on GBL loans than the status quo MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 7 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion The Comparison: Group-based Lending Group-based lending involves self-selected borrower groups Joint liability lending Participation does not require recommendation by an agent Both high and low ability individuals will form groups Because both pay lower interest rates on GBL loans than the status quo GBL loans had non-significant average impacts on farm value-added MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 7 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Average Treatment Effects: Farm and Non-Farm Income (Efficiency) MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 8 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Research Question: Equity Impacts Previous work examines the relative efficiency impacts Welfare impacts depend on both efficiency and equity impacts MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 9 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Research Question: Equity Impacts Previous work examines the relative efficiency impacts Welfare impacts depend on both efficiency and equity impacts Could GBL dominate TRAIL on equity grounds? MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 9 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Why Worry? MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 10 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Why Worry? MMMMV (2017): 30-40% of the efficiency impact of TRAIL due to borrower selection: TRAIL agents selected borrowers who were more productive Productive borrowers may also be wealthier/higher SES to begin with TRAIL could amplify these differences Efficiency gains, but at the cost of equity? MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 10 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Aggregate Welfare Impacts We estimate the scheme’s impact on aggregate welfare depends on both efficiency and equity By partitioning households by landholding by social group: religion/caste MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 11 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion How we estimate welfare impacts MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 12 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion How we estimate welfare impacts Question: If the scheme was introduced into a village, by how much would the welfare of representative household change? MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 12 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion How we estimate welfare impacts Question: If the scheme was introduced into a village, by how much would the welfare of representative household change? Problem: selection into the scheme was NOT random Average TRAIL borrower NOT representative of population MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 12 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion How we estimate welfare impacts, contd. Question: If the scheme was introduced into a village, by how much would the income of representative household change? MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 13 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion How we estimate welfare impacts, contd. Question: If the scheme was introduced into a village, by how much would the income of representative household change? That depends on: does that household participate in the scheme (pg )? MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 13 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion How we estimate welfare impacts, contd. Question: If the scheme was introduced into a village, by how much would the income of representative household change? That depends on: does that household participate in the scheme (pg )? if it participates, how much does its income change (CTEg )? MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 13 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion How we estimate welfare impacts, contd. Question: If the scheme was introduced into a village, by how much would the income of representative household change? That depends on: does that household participate in the scheme (pg )? if it participates, how much does its income change (CTEg )? Expected income effect for group g = pg × CTEg MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 13 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion How we estimate welfare impacts, contd. Question: If the scheme was introduced into a village, by how much would the income of representative household change? That depends on: does that household participate in the scheme (pg )? if it participates, how much does its income change (CTEg )? Expected income effect for group g = pg × CTEg Use welfare functions to infer welfare effects with different assumptions about inequality aversion MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 13 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion TRAIL Features MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 14 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion TRAIL Features Agent is selected randomly from list of established trader/lenders in any given village MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 14 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion TRAIL Features Agent is selected randomly from list of established trader/lenders in any given village Agent recommends 30 borrowers from among landless or marginal landowners (≤ 1.5 acres) subset of these are chosen randomly to receive offer of TRAIL loans MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 14 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion TRAIL Features Agent is selected randomly from list of established trader/lenders in any given village Agent recommends 30 borrowers from among landless or marginal landowners (≤ 1.5 acres) subset of these are chosen randomly to receive offer of TRAIL loans Agent plays no further role: MFI sets loan terms, directly lends to and collects repayments from borrowers No group meetings, savings requirements or gender restrictions MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 14 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion TRAIL Loan Features Loan interest rate pegged at below average rates on informal credit in the village Dynamic borrower incentives: start with small loans, future credit access grows at fast rate based on current repayment *Loan durations/timing: 4 months, match key-crop cycles *Insurance against covariate (price-yield) risks *Doorstep banking, no bank accounts (*: non-standard) MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 15 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion The Group Based Lending Scheme Same loan features as TRAIL loans, except: 5-member self-formed groups of borrowers joint liability monthly group meetings savings requirements MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 16 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Experimental Setting Two potato-growing districts in a state in eastern India 48 villages randomly assigned to: TRAIL scheme: 24 GBL scheme: 24 Collaborated with a microfinance institution 8 4-month cycles: Sept 2010 - July 2013 MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 17 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Partitions Land class Landless 0-0.5 acres 0.5-1 acre 1-1.5 acres MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 18 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Partitions Land class Landless 0-0.5 acres 0.5-1 acre 1-1.5 acres Social group scheduled castes/scheduled tribes non-Hindus general caste Hindus MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 18 / 50
HH Characteristics by Land Class Average Landless 0–0.5 acres 0.5–1.0 acres 1.0–1.5 acres (1) (2) (3) (4) (5) Head’s education: primary school or more 0.420 0.211 0.366 0.552 0.654 (0.011) (0.019) (0.017) (0.021) (0.031) Head’s primary occupation: cultivation 0.438 0.057 0.374 0.692 0.726 (0.011) (0.011) (0.017) (0.020) (0.029) Head’s primary occupation: casual labor 0.332 0.673 0.409 0.091 0.043 (0.010) (0.022) (0.017) (0.012) (0.013) Landholding (Acres) 0.464 0.000 0.261 0.755 1.237 (0.009) (0.000) (0.005) (0.006) (0.009) Pucca house 0.273 0.171 0.259 0.324 0.377 (0.010) (0.018) (0.015) (0.020) (0.031) Electrified house 0.750 0.634 0.733 0.824 0.838 (0.010) (0.023) (0.015) (0.016) (0.024) Owns radio/TV/VCR/DVD 0.452 0.325 0.398 0.543 0.636 (0.011) (0.022) (0.017) (0.021) (0.031) Owns motorized vehicle 0.127 0.068 0.073 0.181 0.272 (0.007) (0.012) (0.009) (0.016) (0.029) Owns phone (mobile or landline) 0.591 0.420 0.536 0.712 0.781 (0.011) (0.023) (0.017) (0.019) (0.027) Has savings bank account 0.446 0.250 0.414 0.542 0.667 (0.011) (0.020) (0.017) (0.021) (0.030) Has insurance policy 0.286 0.139 0.247 0.375 0.461 (0.010) (0.016) (0.015) (0.021) (0.032)
HH Characteristics by Social Group Total SC/ST Non-Hindu General (1) (2) (3) (4) Head’s education: primary school or more 0.420 0.222 0.317 0.614 (0.011) (0.015) (0.025) (0.016) Head’s primary occupation: cultivation 0.439 0.284 0.432 0.560 (0.011) (0.017) (0.026) (0.016) Head?s primary occupation: casual labor 0.331 0.562 0.276 0.176 (0.010) (0.018) (0.024) (0.012) Landholding (acres) 0.465 0.293 0.482 0.590 (0.009) (0.013) (0.022) (0.014) Pucca house 0.273 0.112 0.329 0.376 (0.010) (0.012) (0.025) (0.016) Electrified house 0.750 0.604 0.792 0.846 (0.010) (0.018) (0.022) (0.012) Own a radio/ TV/ VCR/ DVD 0.453 0.318 0.387 0.583 (0.011) (0.017) (0.026) (0.016) Owns motorized vehicle 0.126 0.030 0.155 0.189 (0.007) (0.006) (0.019) (0.013) Owns phone (mobile or landline) 0.590 0.413 0.691 0.687 (0.011) (0.018) (0.025) (0.015) Has savings bank account 0.446 0.284 0.408 0.586 (0.011) (0.017) (0.026) (0.016) Has insurance policy 0.287 0.161 0.237 0.403 (0.010) (0.013) (0.023) (0.016)
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Land Class MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 21 / 50
Step 1: Selection Frequencies pg pg = number of g hhs selected total number of g hhs selected = recommended by TRAIL agents self-selected into GBL groups selection = take-up only households with ≤ 1.5 acres of land considered
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Step 1: Selection Frequencies, contd. 0.059 0.073 0.074 0.054 0.068 0.040 0.070 0.032 0.05.1 Landless Land 0-0.5 Land 0.5-1.0 Land 1.0-1.5 TRAIL GBL MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 23 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Selection Frequencies by Land Class the landless have a slightly lower selection frequency in TRAIL than in GBL TRAIL: across land classes, selection frequencies are very similar GBL: selection frequencies fall as landholding increases MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 24 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Step 2: CTEs, by land MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 25 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Step 2: CTEs, by land -20000020000 Landless 0-0.5 acres 0.5-1 acres 1-1.5 acres TRAIL, absolute -20000020000 Landless 0-0.5 acres 0.5-1 acres 1-1.5 acres GBL, absolute Conditional Treatment Effects, by Land MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 25 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Absolute v. Proportional CTEs, by land: TRAIL MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 26 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Absolute v. Proportional CTEs, by land: TRAIL 01000020000 Landless 0-0.5 acres 0.5-1 acres 1-1.5 acres TRAIL, absolute -1012 Landless 0-0.5 acres 0.5-1 acres 1-1.5 acres TRAIL, relative Conditional Treatment Effects, by Land MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 26 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Absolute v. Proportional CTEs, by land: GBL -20000-10000010000 Landless 0-0.5 acres 0.5-1 acres 1-1.5 acres GBL, absolute -.50.511.5 Landless 0-0.5 acres 0.5-1 acres 1-1.5 acres GBL, relative Conditional Treatment Effects, by Land MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 27 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Step 3: Expected treatment effects on income -.010.01.02.03.04.05 ty_g Landless 0-0.5 acres 0.5-1 acres 1-1.5 acres TRAIL, relative -.010.01.02.03.04.05 ty_g Landless 0-0.5 acres 0.5-1 acres 1-1.5 acres GBL, relative Expected Proportional Treatment Effects, by Land MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 28 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Step 4: Change in welfare, θ = 0 MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 29 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Step 4: Change in welfare, θ = 0 -10123 rdw TRAIL GBL theta=0 MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 29 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Step 4: Change in welfare, θ = 1 0.05.1.15.2 rdw TRAIL GBL theta=1 MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 30 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Step 4: Change in welfare, θ = 2 20040060080010001200 rdw TRAIL GBL theta=2 MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 31 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Step 4: Change in welfare, θ = 3 05000001.0e+061.5e+062.0e+06 rdw TRAIL GBL theta=3 MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 32 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Step 4: Change in welfare, θ = 4 01.0e+092.0e+093.0e+09 rdw TRAIL GBL theta=4 MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 33 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Step 4: Change in welfare, θ = 5 01.0e+122.0e+123.0e+124.0e+12 rdw TRAIL GBL theta=5 MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 34 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Social Group MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 35 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Step 1: Selection frequencies 0.073 0.073 0.066 0.050 0.064 0.037 0.05.1 SC/ST Non-Hindu General Probabilities of selection TRAIL GBL MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 36 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Step 2: CTEs, by social group -500005000 SC/ST Non-Hindu General TRAIL, absolute -500005000 SC/ST Non-Hindu General GBL, absolute Conditional Treatment Effects, by Social Group MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 37 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Absolute v. Proportional CTEs, by social group: TRAIL 0500010000 SC/ST Non-Hindu General TRAIL, absolute 0.51 SC/ST Non-Hindu General TRAIL, relative Conditional Treatment Effects, by Social Group MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 38 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Absolute v. Proportional CTEs, by social group: GBL -500005000 SC/ST Non-Hindu General GBL, absolute -.50.5 SC/ST Non-Hindu General GBL, relative Conditional Treatment Effects, by Social Group MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 39 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Step 3: Expected treatment effects, by social group -.010.01.02.03.04.05 ty_g SC/ST Non-Hindu General TRAIL, relative -.010.01.02.03.04.05 ty_g SC/ST Non-Hindu General GBL, relative Expected Proportional Treatment Effects, by Social Group MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 40 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Step 4: Change in welfare, θ = 0 0.005.01.015.02.025 rdw TRAIL GBL theta=0 MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 41 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Step 3: Change in welfare, θ = 4 5.0e+061.0e+071.5e+072.0e+07 rdw TRAIL GBL theta=4 MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 42 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Step 3: Change in welfare, θ = 5 1.0e+092.0e+093.0e+094.0e+095.0e+096.0e+09 rdw TRAIL GBL theta=5 MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 43 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Changes in Inequality θ = 1 θ = 2 θ = 3 θ = 4 θ = 5 (1) (2) (3) (4) (5) Panel A: TRAIL Baseline 0.3249 0.7236 0.8632 0.9051 0.9234 Endline 0.3205 0.7217 0.8630 0.9053 0.9237 Effect on inequality ↓ ↓ ↓ ↑ ↑ Panel B: GBL Baseline 0.3662 0.8139 0.9247 0.9517 0.9625 Endline 0.3594 0.7947 0.9123 0.9431 0.9561 Effect on inequality ↓ ↓ ↓ ↓ ↓ MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 44 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Discussion The evidence that TRAIL was elitist is limited. MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 45 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Discussion The evidence that TRAIL was elitist is limited. Comparing landless borrowers: in TRAIL had lower baseline farm income than in GBL MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 45 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Discussion The evidence that TRAIL was elitist is limited. Comparing landless borrowers: in TRAIL had lower baseline farm income than in GBL In fact, GBL might be keeping out both the high wealth/high status households and the poorest among the low wealth households MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 45 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Selection by TRAIL agent Control 1 households Representative sample Difference Panel A: Bought from agent Landless 0.233 0.280 -0.047 (0.079) (0.092) (0.120) 0–0.5 acres 0.523 0.333 0.190*** (0.048) (0.040) (0.062) 0.5–1 acres 0.339 0.365 -0.026 (0.062) (0.047) (0.078) 1–1.5 acres 0.318 0.488 -0.170 (0.102) (0.079) (0.131) Panel B: Borrowed from agent Landless 0.067 0.167 -0.100 (0.046) (0.078) (0.087) 0–0.5 acres 0.349 0.107 0.241*** (0.046) (0.026) (0.050) 0.5–1 acres 0.233 0.173 0.060 (0.055) (0.037) (0.064) 1–1.5 acres 0.227 0.220 0.008 (0.091) (0.066) (0.112) Panel C: Worked for agent Landless 0.167 0.000 0.167** (0.069) (0.000) (0.078) 0–0.5 acres 0.182 0.083 0.098** (0.037) (0.023) (0.042) 0.5–1 acres 0.133 0.086 0.048 (0.044) (0.027) (0.049) 1–1.5 acres 0.000 0.098 -0.098 (0.000) (0.047) (0.064) Panel D: Same social group as agent Landless 0.353 0.222 0.131 (0.083) (0.082) (0.118) 0–0.5 acres 0.504 0.543 -0.039 (0.047) (0.041) (0.062) 0.5–1 acres 0.672 0.517 0.155** (0.059) (0.047) (0.077) 1–1.5 acres 0.913 0.689 0.224** (0.060) (0.070) (0.107) MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 46 / 50
Social Capital in GBL Groups Total SC/ST Non-Hindu General (1) (2) (3) (4) Invited by group members 0.583 0.536 0.800 0.558 (0.032) (0.048) (0.069) (0.051) Encouraged by officials to join group 0.417 0.464 0.200 0.442 (0.032) (0.048) (0.069) (0.051) Received assistance from others in the group (Cycle 1) 0.248 0.239 0.361 0.216 (0.028) (0.040) (0.081) (0.042) Provided assistance to others in the group (Cycle 1) 0.124 0.080 0.171 0.158 (0.021) (0.026) (0.065) (0.038) Proportion members with same occupation 0.624 0.616 0.598 0.642 (0.015) (0.022) (0.036) (0.023) Proportion members with same education level 0.530 0.520 0.594 0.516 (0.012) (0.019) (0.034) (0.018) Proportion members in same social group 0.522 0.732 0.887 0.192 (0.027) (0.038) (0.044) (0.033) Herfindahl Index by social group 0.762 0.873 0.940 0.593 (0.014) (0.019) (0.024) (0.019) Coefficient of variation of landholding 0.999 1.217 0.975 0.805 (0.035) (0.060) (0.075) (0.044)
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Summary of Results Compare welfare impacts of two alternative credit delivery models TRAIL is not more elitist than GBL MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 48 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Summary of Results Compare welfare impacts of two alternative credit delivery models TRAIL is not more elitist than GBL When partitioning by landholding: TRAIL generates higher average gains and benefits the landless more than GBL As a result it dominates GBL. MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 48 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Summary of Results Compare welfare impacts of two alternative credit delivery models TRAIL is not more elitist than GBL When partitioning by landholding: TRAIL generates higher average gains and benefits the landless more than GBL As a result it dominates GBL. When partitioning by social group: TRAIL: High status group outperforms other groups GBL: Low status groups outperform high status groups Point estimates indicate larger welfare in GBL under high θ But differences are not statistically significant MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 48 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Conclusion Our previous work indicates that TRAIL is superior to GBL from an efficiency standpoint. From an equity standpoint: Clear evidence from land partitioning that it outperforms GBL Less clear evidence from social group partitioning differences depend on θ values lack statistical significance MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 49 / 50
Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Thank you! MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 50 / 50

Recommended

The Growth of Charitable Estate Planning
The Growth of Charitable Estate PlanningThe Growth of Charitable Estate Planning
The Growth of Charitable Estate Planning
Russell James
 
Charitable Bequest Demographics
Charitable Bequest DemographicsCharitable Bequest Demographics
Charitable Bequest Demographics
Russell James
 
Charitable Bequest Decision-Making
Charitable Bequest Decision-MakingCharitable Bequest Decision-Making
Charitable Bequest Decision-Making
Russell James
 
Inside the mind of the bequest donor
Inside the mind of the bequest donorInside the mind of the bequest donor
Inside the mind of the bequest donor
Russell James
 
Storia dei rolex dal 1912
Storia dei rolex dal 1912Storia dei rolex dal 1912
Storia dei rolex dal 1912
Franco Danese
 
TF.RGO.99
TF.RGO.99TF.RGO.99
TF.RGO.99
Arcee327
 
Risultato 2° Rating menu scolastici 2016_17
Risultato 2° Rating menu scolastici 2016_17Risultato 2° Rating menu scolastici 2016_17
Risultato 2° Rating menu scolastici 2016_17
foodinsider
 
Mukhopadhyay iems leanwashing 02 march2017
Mukhopadhyay iems leanwashing 02 march2017Mukhopadhyay iems leanwashing 02 march2017
Mukhopadhyay iems leanwashing 02 march2017
HKUST IEMS
 

Recommended

The Growth of Charitable Estate Planning
The Growth of Charitable Estate PlanningThe Growth of Charitable Estate Planning
The Growth of Charitable Estate Planning
Russell James
 
Charitable Bequest Demographics
Charitable Bequest DemographicsCharitable Bequest Demographics
Charitable Bequest Demographics
Russell James
 
Charitable Bequest Decision-Making
Charitable Bequest Decision-MakingCharitable Bequest Decision-Making
Charitable Bequest Decision-Making
Russell James
 
Inside the mind of the bequest donor
Inside the mind of the bequest donorInside the mind of the bequest donor
Inside the mind of the bequest donor
Russell James
 
Storia dei rolex dal 1912
Storia dei rolex dal 1912Storia dei rolex dal 1912
Storia dei rolex dal 1912
Franco Danese
 
TF.RGO.99
TF.RGO.99TF.RGO.99
TF.RGO.99
Arcee327
 
Risultato 2° Rating menu scolastici 2016_17
Risultato 2° Rating menu scolastici 2016_17Risultato 2° Rating menu scolastici 2016_17
Risultato 2° Rating menu scolastici 2016_17
foodinsider
 
Mukhopadhyay iems leanwashing 02 march2017
Mukhopadhyay iems leanwashing 02 march2017Mukhopadhyay iems leanwashing 02 march2017
Mukhopadhyay iems leanwashing 02 march2017
HKUST IEMS
 
Devdrv 161206 iBress Datahub APG Round Tables
Devdrv 161206 iBress Datahub APG Round TablesDevdrv 161206 iBress Datahub APG Round Tables
Devdrv 161206 iBress Datahub APG Round Tables
Atomu Hidaka
 
Ramadan & eid candle collection 2017
Ramadan & eid candle collection 2017Ramadan & eid candle collection 2017
Ramadan & eid candle collection 2017
Dennie Wallace
 
TF.RGO.100
TF.RGO.100TF.RGO.100
TF.RGO.100
Arcee327
 
DEBAT: DEL BATXILLERAT A LA UNIVERSITAT
DEBAT: DEL BATXILLERAT A LA UNIVERSITATDEBAT: DEL BATXILLERAT A LA UNIVERSITAT
DEBAT: DEL BATXILLERAT A LA UNIVERSITAT
Estel Paloma
 
TF.RGO.97
TF.RGO.97TF.RGO.97
TF.RGO.97
Arcee327
 
TF.RGO.98
TF.RGO.98TF.RGO.98
TF.RGO.98
Arcee327
 
Tipos de memoria
Tipos de memoriaTipos de memoria
Tipos de memoria
Rayzeraus
 
Case conference orthokorat
Case conference orthokorat Case conference orthokorat
Case conference orthokorat
Mild Chanikarn
 
Curso de Procesado de Fotografía Digital: 3. Selección avanzada en Photoshop
Curso de Procesado de Fotografía Digital: 3. Selección avanzada en PhotoshopCurso de Procesado de Fotografía Digital: 3. Selección avanzada en Photoshop
Curso de Procesado de Fotografía Digital: 3. Selección avanzada en Photoshop
domingo leiva
 
XDi Presentation_Lean UX-Workshop@MCBW2017
XDi Presentation_Lean UX-Workshop@MCBW2017XDi Presentation_Lean UX-Workshop@MCBW2017
XDi Presentation_Lean UX-Workshop@MCBW2017
Stefan Schmitt
 
Albert Park: Economic consequences of demographic changes in emerging markets
Albert Park: Economic consequences of demographic changes in emerging marketsAlbert Park: Economic consequences of demographic changes in emerging markets
Albert Park: Economic consequences of demographic changes in emerging markets
HKUST IEMS
 
Sujata Balasubramanian: Is the PDS Already a Cash Transfer? Rethinking India’...
Sujata Balasubramanian: Is the PDS Already a Cash Transfer? Rethinking India’...Sujata Balasubramanian: Is the PDS Already a Cash Transfer? Rethinking India’...
Sujata Balasubramanian: Is the PDS Already a Cash Transfer? Rethinking India’...
HKUST IEMS
 
Regina Moench-Pfanner - Diets in Transition: Urbanization & Processed Food at...
Regina Moench-Pfanner - Diets in Transition: Urbanization & Processed Food at...Regina Moench-Pfanner - Diets in Transition: Urbanization & Processed Food at...
Regina Moench-Pfanner - Diets in Transition: Urbanization & Processed Food at...
HKUST IEMS
 
China as the World's Technology Leader by Naubahar Sharif
China as the World's Technology Leader by Naubahar Sharif China as the World's Technology Leader by Naubahar Sharif
China as the World's Technology Leader by Naubahar Sharif
HKUST IEMS
 
Registration Status, Occupational Segregation and Rural Migrants in Urban China
Registration Status, Occupational Segregation and Rural Migrants in Urban ChinaRegistration Status, Occupational Segregation and Rural Migrants in Urban China
Registration Status, Occupational Segregation and Rural Migrants in Urban China
HKUST IEMS
 
Piotr Lewandowski - A routine transition? Technology, upskilling, structural ...
Piotr Lewandowski - A routine transition? Technology, upskilling, structural ...Piotr Lewandowski - A routine transition? Technology, upskilling, structural ...
Piotr Lewandowski - A routine transition? Technology, upskilling, structural ...
HKUST IEMS
 
Introducing windows 10 universal driver
Introducing windows 10 universal driverIntroducing windows 10 universal driver
Introducing windows 10 universal driver
Atomu Hidaka
 
6.1 The HEARTH Act: Implications for Rural Communities (Harrison)
6.1 The HEARTH Act: Implications for Rural Communities (Harrison)6.1 The HEARTH Act: Implications for Rural Communities (Harrison)
6.1 The HEARTH Act: Implications for Rural Communities (Harrison)
National Alliance to End Homelessness
 
Alternative Payment Models: The Good, the Bad, and the Ugly
Alternative Payment Models: The Good, the Bad, and the UglyAlternative Payment Models: The Good, the Bad, and the Ugly
Alternative Payment Models: The Good, the Bad, and the Ugly
PYA, P.C.
 
Using the SNACC Linking Project to Impute Medicaid in the Current Population ...
Using the SNACC Linking Project to Impute Medicaid in the Current Population ...Using the SNACC Linking Project to Impute Medicaid in the Current Population ...
Using the SNACC Linking Project to Impute Medicaid in the Current Population ...
soder145
 
hr_2022_Employee_Engagement_Trends_Report.pptx
hr_2022_Employee_Engagement_Trends_Report.pptxhr_2022_Employee_Engagement_Trends_Report.pptx
hr_2022_Employee_Engagement_Trends_Report.pptx
Dr. Rajkumar V P
 
Data Day 2012_Henderson_Using Indicators-A Primer
Data Day 2012_Henderson_Using Indicators-A PrimerData Day 2012_Henderson_Using Indicators-A Primer
Data Day 2012_Henderson_Using Indicators-A Primer
Metropolitan Area Planning Council
 

More Related Content

Viewers also liked

Sujata Balasubramanian: Is the PDS Already a Cash Transfer? Rethinking India’...
Sujata Balasubramanian: Is the PDS Already a Cash Transfer? Rethinking India’...Sujata Balasubramanian: Is the PDS Already a Cash Transfer? Rethinking India’...
Sujata Balasubramanian: Is the PDS Already a Cash Transfer? Rethinking India’...
HKUST IEMS
 
Regina Moench-Pfanner - Diets in Transition: Urbanization & Processed Food at...
Regina Moench-Pfanner - Diets in Transition: Urbanization & Processed Food at...Regina Moench-Pfanner - Diets in Transition: Urbanization & Processed Food at...
Regina Moench-Pfanner - Diets in Transition: Urbanization & Processed Food at...
HKUST IEMS
 
Registration Status, Occupational Segregation and Rural Migrants in Urban China
Registration Status, Occupational Segregation and Rural Migrants in Urban ChinaRegistration Status, Occupational Segregation and Rural Migrants in Urban China
Registration Status, Occupational Segregation and Rural Migrants in Urban China
HKUST IEMS
 
Piotr Lewandowski - A routine transition? Technology, upskilling, structural ...
Piotr Lewandowski - A routine transition? Technology, upskilling, structural ...Piotr Lewandowski - A routine transition? Technology, upskilling, structural ...
Piotr Lewandowski - A routine transition? Technology, upskilling, structural ...
HKUST IEMS
 

Viewers also liked (17)

Devdrv 161206 iBress Datahub APG Round Tables
Devdrv 161206 iBress Datahub APG Round TablesDevdrv 161206 iBress Datahub APG Round Tables
Devdrv 161206 iBress Datahub APG Round Tables
 
Ramadan & eid candle collection 2017
Ramadan & eid candle collection 2017Ramadan & eid candle collection 2017
Ramadan & eid candle collection 2017
 
TF.RGO.100
TF.RGO.100TF.RGO.100
TF.RGO.100
 
DEBAT: DEL BATXILLERAT A LA UNIVERSITAT
DEBAT: DEL BATXILLERAT A LA UNIVERSITATDEBAT: DEL BATXILLERAT A LA UNIVERSITAT
DEBAT: DEL BATXILLERAT A LA UNIVERSITAT
 
TF.RGO.97
TF.RGO.97TF.RGO.97
TF.RGO.97
 
TF.RGO.98
TF.RGO.98TF.RGO.98
TF.RGO.98
 
Tipos de memoria
Tipos de memoriaTipos de memoria
Tipos de memoria
 
Case conference orthokorat
Case conference orthokorat Case conference orthokorat
Case conference orthokorat
 
Curso de Procesado de Fotografía Digital: 3. Selección avanzada en Photoshop
Curso de Procesado de Fotografía Digital: 3. Selección avanzada en PhotoshopCurso de Procesado de Fotografía Digital: 3. Selección avanzada en Photoshop
Curso de Procesado de Fotografía Digital: 3. Selección avanzada en Photoshop
 
XDi Presentation_Lean UX-Workshop@MCBW2017
XDi Presentation_Lean UX-Workshop@MCBW2017XDi Presentation_Lean UX-Workshop@MCBW2017
XDi Presentation_Lean UX-Workshop@MCBW2017
 
Albert Park: Economic consequences of demographic changes in emerging markets
Albert Park: Economic consequences of demographic changes in emerging marketsAlbert Park: Economic consequences of demographic changes in emerging markets
Albert Park: Economic consequences of demographic changes in emerging markets
 
Sujata Balasubramanian: Is the PDS Already a Cash Transfer? Rethinking India’...
Sujata Balasubramanian: Is the PDS Already a Cash Transfer? Rethinking India’...Sujata Balasubramanian: Is the PDS Already a Cash Transfer? Rethinking India’...
Sujata Balasubramanian: Is the PDS Already a Cash Transfer? Rethinking India’...
 
Regina Moench-Pfanner - Diets in Transition: Urbanization & Processed Food at...
Regina Moench-Pfanner - Diets in Transition: Urbanization & Processed Food at...Regina Moench-Pfanner - Diets in Transition: Urbanization & Processed Food at...
Regina Moench-Pfanner - Diets in Transition: Urbanization & Processed Food at...
 
China as the World's Technology Leader by Naubahar Sharif
China as the World's Technology Leader by Naubahar Sharif China as the World's Technology Leader by Naubahar Sharif
China as the World's Technology Leader by Naubahar Sharif
 
Registration Status, Occupational Segregation and Rural Migrants in Urban China
Registration Status, Occupational Segregation and Rural Migrants in Urban ChinaRegistration Status, Occupational Segregation and Rural Migrants in Urban China
Registration Status, Occupational Segregation and Rural Migrants in Urban China
 
Piotr Lewandowski - A routine transition? Technology, upskilling, structural ...
Piotr Lewandowski - A routine transition? Technology, upskilling, structural ...Piotr Lewandowski - A routine transition? Technology, upskilling, structural ...
Piotr Lewandowski - A routine transition? Technology, upskilling, structural ...
 
Introducing windows 10 universal driver
Introducing windows 10 universal driverIntroducing windows 10 universal driver
Introducing windows 10 universal driver
 

Similar to Sujata Visaria: Finding the Diamonds in the Rough - Welfare Comparisons of Two Targeting Mechanisms in Microcredit

Relationship of agricultural credit with agricultural growth and economic dev...
Relationship of agricultural credit with agricultural growth and economic dev...Relationship of agricultural credit with agricultural growth and economic dev...
Relationship of agricultural credit with agricultural growth and economic dev...
RashidLatief3
 

Similar to Sujata Visaria: Finding the Diamonds in the Rough - Welfare Comparisons of Two Targeting Mechanisms in Microcredit (9)

6.1 The HEARTH Act: Implications for Rural Communities (Harrison)
6.1 The HEARTH Act: Implications for Rural Communities (Harrison)6.1 The HEARTH Act: Implications for Rural Communities (Harrison)
6.1 The HEARTH Act: Implications for Rural Communities (Harrison)
 
Alternative Payment Models: The Good, the Bad, and the Ugly
Alternative Payment Models: The Good, the Bad, and the UglyAlternative Payment Models: The Good, the Bad, and the Ugly
Alternative Payment Models: The Good, the Bad, and the Ugly
 
Using the SNACC Linking Project to Impute Medicaid in the Current Population ...
Using the SNACC Linking Project to Impute Medicaid in the Current Population ...Using the SNACC Linking Project to Impute Medicaid in the Current Population ...
Using the SNACC Linking Project to Impute Medicaid in the Current Population ...
 
hr_2022_Employee_Engagement_Trends_Report.pptx
hr_2022_Employee_Engagement_Trends_Report.pptxhr_2022_Employee_Engagement_Trends_Report.pptx
hr_2022_Employee_Engagement_Trends_Report.pptx
 
Data Day 2012_Henderson_Using Indicators-A Primer
Data Day 2012_Henderson_Using Indicators-A PrimerData Day 2012_Henderson_Using Indicators-A Primer
Data Day 2012_Henderson_Using Indicators-A Primer
 
How We Fund Local Government: Michigan's Local Leaders See Need for Reform
How We Fund Local Government: Michigan's Local Leaders See Need for ReformHow We Fund Local Government: Michigan's Local Leaders See Need for Reform
How We Fund Local Government: Michigan's Local Leaders See Need for Reform
 
Relationship of agricultural credit with agricultural growth and economic dev...
Relationship of agricultural credit with agricultural growth and economic dev...Relationship of agricultural credit with agricultural growth and economic dev...
Relationship of agricultural credit with agricultural growth and economic dev...
 
Workshop 1: Social Care Community of Practice
Workshop 1: Social Care Community of PracticeWorkshop 1: Social Care Community of Practice
Workshop 1: Social Care Community of Practice
 
Place Matters Cds Conference Presentation July 2009
Place Matters Cds Conference Presentation July 2009Place Matters Cds Conference Presentation July 2009
Place Matters Cds Conference Presentation July 2009
 

More from HKUST IEMS

China’s New Anti Poverty Strategy
China’s New Anti Poverty StrategyChina’s New Anti Poverty Strategy
China’s New Anti Poverty Strategy
HKUST IEMS
 

More from HKUST IEMS (20)

Grid-Scale Energy Storage and Electric Vehicles: The Risks of Technology Lock...
Grid-Scale Energy Storage and Electric Vehicles: The Risks of Technology Lock...Grid-Scale Energy Storage and Electric Vehicles: The Risks of Technology Lock...
Grid-Scale Energy Storage and Electric Vehicles: The Risks of Technology Lock...
 
Financial Inclusion and Contract Terms
Financial Inclusion and Contract Terms Financial Inclusion and Contract Terms
Financial Inclusion and Contract Terms
 
Enforcing Regulation under Illicit Adaptation
Enforcing Regulation under Illicit Adaptation Enforcing Regulation under Illicit Adaptation
Enforcing Regulation under Illicit Adaptation
 
Demography Meets Psephology: the Impact of Changing Age Structure on Democrat...
Demography Meets Psephology: the Impact of Changing Age Structure on Democrat...Demography Meets Psephology: the Impact of Changing Age Structure on Democrat...
Demography Meets Psephology: the Impact of Changing Age Structure on Democrat...
 
Current and Projected Elderly Populations of East Asia and Implications for E...
Current and Projected Elderly Populations of East Asia and Implications for E...Current and Projected Elderly Populations of East Asia and Implications for E...
Current and Projected Elderly Populations of East Asia and Implications for E...
 
Determinants of Changing Demographic Structure in Asia
Determinants of Changing Demographic Structure in AsiaDeterminants of Changing Demographic Structure in Asia
Determinants of Changing Demographic Structure in Asia
 
Perceiving Truth and Ceasing Doubts
Perceiving Truth and Ceasing DoubtsPerceiving Truth and Ceasing Doubts
Perceiving Truth and Ceasing Doubts
 
The Belt and Road: From Vision to Reality
The Belt and Road: From Vision to RealityThe Belt and Road: From Vision to Reality
The Belt and Road: From Vision to Reality
 
What to buy when the American Dream fails?
What to buy when the American Dream fails? What to buy when the American Dream fails?
What to buy when the American Dream fails?
 
The United States Turns Inward
The United States Turns InwardThe United States Turns Inward
The United States Turns Inward
 
Intellectual Property-Related Trade Preferential Trade Agreements and the Com...
Intellectual Property-Related Trade Preferential Trade Agreements and the Com...Intellectual Property-Related Trade Preferential Trade Agreements and the Com...
Intellectual Property-Related Trade Preferential Trade Agreements and the Com...
 
Targeting of Local Government Programs and Voting Patterns in West Bengal
Targeting of Local Government Programs and Voting Patterns in West BengalTargeting of Local Government Programs and Voting Patterns in West Bengal
Targeting of Local Government Programs and Voting Patterns in West Bengal
 
State Absenteeism in India's Reverse Migration?
State Absenteeism in India's Reverse Migration?State Absenteeism in India's Reverse Migration?
State Absenteeism in India's Reverse Migration?
 
State Absenteeism in India's Reverse Migration? A Comparison with the Chinese...
State Absenteeism in India's Reverse Migration? A Comparison with the Chinese...State Absenteeism in India's Reverse Migration? A Comparison with the Chinese...
State Absenteeism in India's Reverse Migration? A Comparison with the Chinese...
 
Abhiroop Mukherjee - Roads and Loans
Abhiroop Mukherjee - Roads and LoansAbhiroop Mukherjee - Roads and Loans
Abhiroop Mukherjee - Roads and Loans
 
Martin Kanz - Moral Incentives in Credit Card Debt Repayment
Martin Kanz - Moral Incentives in Credit Card Debt Repayment Martin Kanz - Moral Incentives in Credit Card Debt Repayment
Martin Kanz - Moral Incentives in Credit Card Debt Repayment
 
Real Business Cycles in Emerging Economies
Real Business Cycles in Emerging EconomiesReal Business Cycles in Emerging Economies
Real Business Cycles in Emerging Economies
 
China’s New Anti Poverty Strategy
China’s New Anti Poverty StrategyChina’s New Anti Poverty Strategy
China’s New Anti Poverty Strategy
 
China Employer-Employee Survey Report (June 2017) - English Version
China Employer-Employee Survey Report (June 2017) - English VersionChina Employer-Employee Survey Report (June 2017) - English Version
China Employer-Employee Survey Report (June 2017) - English Version
 
中国企业-劳动力匹配调查 报告 (2017年6月）简体中文版
中国企业-劳动力匹配调查 报告 (2017年6月）简体中文版中国企业-劳动力匹配调查 报告 (2017年6月）简体中文版
中国企业-劳动力匹配调查 报告 (2017年6月）简体中文版
 

Recently uploaded

VIP Independent Call Girls in Bandra West 🌹 9920725232 ( Call Me ) Mumbai Esc...
VIP Independent Call Girls in Bandra West 🌹 9920725232 ( Call Me ) Mumbai Esc...VIP Independent Call Girls in Bandra West 🌹 9920725232 ( Call Me ) Mumbai Esc...
VIP Independent Call Girls in Bandra West 🌹 9920725232 ( Call Me ) Mumbai Esc...
dipikadinghjn ( Why You Choose Us? ) Escorts
 
Navi Mumbai Cooperetive Housewife Call Girls-9833754194-Natural Panvel Enjoye...
Navi Mumbai Cooperetive Housewife Call Girls-9833754194-Natural Panvel Enjoye...Navi Mumbai Cooperetive Housewife Call Girls-9833754194-Natural Panvel Enjoye...
Navi Mumbai Cooperetive Housewife Call Girls-9833754194-Natural Panvel Enjoye...
priyasharma62062
 
(Vedika) Low Rate Call Girls in Pune Call Now 8250077686 Pune Escorts 24x7
(Vedika) Low Rate Call Girls in Pune Call Now 8250077686 Pune Escorts 24x7(Vedika) Low Rate Call Girls in Pune Call Now 8250077686 Pune Escorts 24x7
(Vedika) Low Rate Call Girls in Pune Call Now 8250077686 Pune Escorts 24x7
Call Girls in Nagpur High Profile Call Girls
 
VIP Kalyan Call Girls 🌐 9920725232 🌐 Make Your Dreams Come True With Mumbai E...
VIP Kalyan Call Girls 🌐 9920725232 🌐 Make Your Dreams Come True With Mumbai E...VIP Kalyan Call Girls 🌐 9920725232 🌐 Make Your Dreams Come True With Mumbai E...
VIP Kalyan Call Girls 🌐 9920725232 🌐 Make Your Dreams Come True With Mumbai E...
roshnidevijkn ( Why You Choose Us? ) Escorts
 
Best VIP Call Girls Morni Hills Just Click Me 6367492432
Best VIP Call Girls Morni Hills Just Click Me 6367492432Best VIP Call Girls Morni Hills Just Click Me 6367492432
Best VIP Call Girls Morni Hills Just Click Me 6367492432
motiram463
 
Vasai-Virar High Profile Model Call Girls📞9833754194-Nalasopara Satisfy Call ...
Vasai-Virar High Profile Model Call Girls📞9833754194-Nalasopara Satisfy Call ...Vasai-Virar High Profile Model Call Girls📞9833754194-Nalasopara Satisfy Call ...
Vasai-Virar High Profile Model Call Girls📞9833754194-Nalasopara Satisfy Call ...
priyasharma62062
 
Airport Road Best Experience Call Girls Number-📞📞9833754194 Santacruz MOst Es...
Airport Road Best Experience Call Girls Number-📞📞9833754194 Santacruz MOst Es...Airport Road Best Experience Call Girls Number-📞📞9833754194 Santacruz MOst Es...
Airport Road Best Experience Call Girls Number-📞📞9833754194 Santacruz MOst Es...
priyasharma62062
 
Call Girls Banaswadi Just Call 👗 7737669865 👗 Top Class Call Girl Service Ban...
Call Girls Banaswadi Just Call 👗 7737669865 👗 Top Class Call Girl Service Ban...Call Girls Banaswadi Just Call 👗 7737669865 👗 Top Class Call Girl Service Ban...
Call Girls Banaswadi Just Call 👗 7737669865 👗 Top Class Call Girl Service Ban...
amitlee9823
 
Call Girls Koregaon Park Call Me 7737669865 Budget Friendly No Advance Booking
Call Girls Koregaon Park Call Me 7737669865 Budget Friendly No Advance BookingCall Girls Koregaon Park Call Me 7737669865 Budget Friendly No Advance Booking
Call Girls Koregaon Park Call Me 7737669865 Budget Friendly No Advance Booking
roncy bisnoi
 
Call Girls Service Pune ₹7.5k Pick Up & Drop With Cash Payment 9352852248 Cal...
Call Girls Service Pune ₹7.5k Pick Up & Drop With Cash Payment 9352852248 Cal...Call Girls Service Pune ₹7.5k Pick Up & Drop With Cash Payment 9352852248 Cal...
Call Girls Service Pune ₹7.5k Pick Up & Drop With Cash Payment 9352852248 Cal...
roshnidevijkn ( Why You Choose Us? ) Escorts
 
falcon-invoice-discounting-unlocking-prime-investment-opportunities
falcon-invoice-discounting-unlocking-prime-investment-opportunitiesfalcon-invoice-discounting-unlocking-prime-investment-opportunities
falcon-invoice-discounting-unlocking-prime-investment-opportunities
Falcon Invoice Discounting
 
(INDIRA) Call Girl Mumbai Call Now 8250077686 Mumbai Escorts 24x7
(INDIRA) Call Girl Mumbai Call Now 8250077686 Mumbai Escorts 24x7(INDIRA) Call Girl Mumbai Call Now 8250077686 Mumbai Escorts 24x7
(INDIRA) Call Girl Mumbai Call Now 8250077686 Mumbai Escorts 24x7
Call Girls in Nagpur High Profile Call Girls
 

Recently uploaded (20)

VIP Independent Call Girls in Bandra West 🌹 9920725232 ( Call Me ) Mumbai Esc...
VIP Independent Call Girls in Bandra West 🌹 9920725232 ( Call Me ) Mumbai Esc...VIP Independent Call Girls in Bandra West 🌹 9920725232 ( Call Me ) Mumbai Esc...
VIP Independent Call Girls in Bandra West 🌹 9920725232 ( Call Me ) Mumbai Esc...
 
Cybersecurity Threats in Financial Services Protection.pptx
Cybersecurity Threats in Financial Services Protection.pptxCybersecurity Threats in Financial Services Protection.pptx
Cybersecurity Threats in Financial Services Protection.pptx
 
Navi Mumbai Cooperetive Housewife Call Girls-9833754194-Natural Panvel Enjoye...
Navi Mumbai Cooperetive Housewife Call Girls-9833754194-Natural Panvel Enjoye...Navi Mumbai Cooperetive Housewife Call Girls-9833754194-Natural Panvel Enjoye...
Navi Mumbai Cooperetive Housewife Call Girls-9833754194-Natural Panvel Enjoye...
 
(Vedika) Low Rate Call Girls in Pune Call Now 8250077686 Pune Escorts 24x7
(Vedika) Low Rate Call Girls in Pune Call Now 8250077686 Pune Escorts 24x7(Vedika) Low Rate Call Girls in Pune Call Now 8250077686 Pune Escorts 24x7
(Vedika) Low Rate Call Girls in Pune Call Now 8250077686 Pune Escorts 24x7
 
VIP Kalyan Call Girls 🌐 9920725232 🌐 Make Your Dreams Come True With Mumbai E...
VIP Kalyan Call Girls 🌐 9920725232 🌐 Make Your Dreams Come True With Mumbai E...VIP Kalyan Call Girls 🌐 9920725232 🌐 Make Your Dreams Come True With Mumbai E...
VIP Kalyan Call Girls 🌐 9920725232 🌐 Make Your Dreams Come True With Mumbai E...
 
Best VIP Call Girls Morni Hills Just Click Me 6367492432
Best VIP Call Girls Morni Hills Just Click Me 6367492432Best VIP Call Girls Morni Hills Just Click Me 6367492432
Best VIP Call Girls Morni Hills Just Click Me 6367492432
 
Vasai-Virar High Profile Model Call Girls📞9833754194-Nalasopara Satisfy Call ...
Vasai-Virar High Profile Model Call Girls📞9833754194-Nalasopara Satisfy Call ...Vasai-Virar High Profile Model Call Girls📞9833754194-Nalasopara Satisfy Call ...
Vasai-Virar High Profile Model Call Girls📞9833754194-Nalasopara Satisfy Call ...
 
Strategic Resources May 2024 Corporate Presentation
Strategic Resources May 2024 Corporate PresentationStrategic Resources May 2024 Corporate Presentation
Strategic Resources May 2024 Corporate Presentation
 
Airport Road Best Experience Call Girls Number-📞📞9833754194 Santacruz MOst Es...
Airport Road Best Experience Call Girls Number-📞📞9833754194 Santacruz MOst Es...Airport Road Best Experience Call Girls Number-📞📞9833754194 Santacruz MOst Es...
Airport Road Best Experience Call Girls Number-📞📞9833754194 Santacruz MOst Es...
 
Call Girls Banaswadi Just Call 👗 7737669865 👗 Top Class Call Girl Service Ban...
Call Girls Banaswadi Just Call 👗 7737669865 👗 Top Class Call Girl Service Ban...Call Girls Banaswadi Just Call 👗 7737669865 👗 Top Class Call Girl Service Ban...
Call Girls Banaswadi Just Call 👗 7737669865 👗 Top Class Call Girl Service Ban...
 
Diva-Thane European Call Girls Number-9833754194-Diva Busty Professional Call...
Diva-Thane European Call Girls Number-9833754194-Diva Busty Professional Call...Diva-Thane European Call Girls Number-9833754194-Diva Busty Professional Call...
Diva-Thane European Call Girls Number-9833754194-Diva Busty Professional Call...
 
Call Girls Koregaon Park Call Me 7737669865 Budget Friendly No Advance Booking
Call Girls Koregaon Park Call Me 7737669865 Budget Friendly No Advance BookingCall Girls Koregaon Park Call Me 7737669865 Budget Friendly No Advance Booking
Call Girls Koregaon Park Call Me 7737669865 Budget Friendly No Advance Booking
 
Call Girls Service Pune ₹7.5k Pick Up & Drop With Cash Payment 9352852248 Cal...
Call Girls Service Pune ₹7.5k Pick Up & Drop With Cash Payment 9352852248 Cal...Call Girls Service Pune ₹7.5k Pick Up & Drop With Cash Payment 9352852248 Cal...
Call Girls Service Pune ₹7.5k Pick Up & Drop With Cash Payment 9352852248 Cal...
 
W.D. Gann Theory Complete Information.pdf
W.D. Gann Theory Complete Information.pdfW.D. Gann Theory Complete Information.pdf
W.D. Gann Theory Complete Information.pdf
 
Q1 2024 Conference Call Presentation vF.pdf
Q1 2024 Conference Call Presentation vF.pdfQ1 2024 Conference Call Presentation vF.pdf
Q1 2024 Conference Call Presentation vF.pdf
 
Mira Road Memorable Call Grls Number-9833754194-Bhayandar Speciallty Call Gir...
Mira Road Memorable Call Grls Number-9833754194-Bhayandar Speciallty Call Gir...Mira Road Memorable Call Grls Number-9833754194-Bhayandar Speciallty Call Gir...
Mira Road Memorable Call Grls Number-9833754194-Bhayandar Speciallty Call Gir...
 
Stock Market Brief Deck (Under Pressure).pdf
Stock Market Brief Deck (Under Pressure).pdfStock Market Brief Deck (Under Pressure).pdf
Stock Market Brief Deck (Under Pressure).pdf
 
falcon-invoice-discounting-unlocking-prime-investment-opportunities
falcon-invoice-discounting-unlocking-prime-investment-opportunitiesfalcon-invoice-discounting-unlocking-prime-investment-opportunities
falcon-invoice-discounting-unlocking-prime-investment-opportunities
 
(INDIRA) Call Girl Mumbai Call Now 8250077686 Mumbai Escorts 24x7
(INDIRA) Call Girl Mumbai Call Now 8250077686 Mumbai Escorts 24x7(INDIRA) Call Girl Mumbai Call Now 8250077686 Mumbai Escorts 24x7
(INDIRA) Call Girl Mumbai Call Now 8250077686 Mumbai Escorts 24x7
 
Kopar Khairane Russian Call Girls Number-9833754194-Navi Mumbai Fantastic Unl...
Kopar Khairane Russian Call Girls Number-9833754194-Navi Mumbai Fantastic Unl...Kopar Khairane Russian Call Girls Number-9833754194-Navi Mumbai Fantastic Unl...
Kopar Khairane Russian Call Girls Number-9833754194-Navi Mumbai Fantastic Unl...
 

Sujata Visaria: Finding the Diamonds in the Rough - Welfare Comparisons of Two Targeting Mechanisms in Microcredit

  • 1. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Finding the Diamonds in the Rough The Equity Impacts of Targeting Smallholder Agricultural Credit Pushkar Maitra, Sandip Mitra, Dilip Mookherjee, Sujata Visaria HKUST Institute for Emerging Market Studies 9 March 2017 MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 1 / 50
  • 2. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Targeting Private Benefits MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 2 / 50
  • 3. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Targeting Private Benefits How should governments choose the recipients of private benefits? subsidies: food, fertilizer transfer payments: pensions MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 2 / 50
  • 4. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Targeting Private Benefits How should governments choose the recipients of private benefits? subsidies: food, fertilizer transfer payments: pensions Centralized schemes: lack of information Decentralized schemes: corruption & elite capture MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 2 / 50
  • 5. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Smallholder Agricultural Credit Designing agricultural credit programs for small farmers State-sponsored efforts: poor information leads to high default Microcredit: high repayment, but does not usually target agriculture Can we design a scheme that leverages local information? and avoids problems of elite capture? MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 3 / 50
  • 6. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Agent-intermediated Lending MMMMV (2017) designed an alternative credit delivery mechanism (AIL): MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 4 / 50
  • 7. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Agent-intermediated Lending MMMMV (2017) designed an alternative credit delivery mechanism (AIL): Leverages local information, but differently Individual liability loans Borrowers recommended by a local “agent” embedded in the community Agent incentivized by commissions that depend on repayment MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 4 / 50
  • 8. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Agent-intermediated Lending MMMMV (2017) designed an alternative credit delivery mechanism (AIL): Leverages local information, but differently Individual liability loans Borrowers recommended by a local “agent” embedded in the community Agent incentivized by commissions that depend on repayment Field experiment in 48 villages TRAIL loans had positive significant average impacts on farm value-added: 22% MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 4 / 50
  • 9. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Average Treatment Effects: Farm and Non-Farm Income (Efficiency) MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 5 / 50
  • 10. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion The Mechanism TRAIL agents are more likely to select “able” borrowers high productivity low risk of crop failure MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 6 / 50
  • 11. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion The Mechanism TRAIL agents are more likely to select “able” borrowers high productivity low risk of crop failure Positive impacts are larger for the more able farmers MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 6 / 50
  • 12. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion The Comparison: Group-based Lending Group-based lending involves self-selected borrower groups Joint liability lending Participation does not require recommendation by an agent MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 7 / 50
  • 13. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion The Comparison: Group-based Lending Group-based lending involves self-selected borrower groups Joint liability lending Participation does not require recommendation by an agent Both high and low ability individuals will form groups Because both pay lower interest rates on GBL loans than the status quo MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 7 / 50
  • 14. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion The Comparison: Group-based Lending Group-based lending involves self-selected borrower groups Joint liability lending Participation does not require recommendation by an agent Both high and low ability individuals will form groups Because both pay lower interest rates on GBL loans than the status quo GBL loans had non-significant average impacts on farm value-added MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 7 / 50
  • 15. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Average Treatment Effects: Farm and Non-Farm Income (Efficiency) MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 8 / 50
  • 16. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Research Question: Equity Impacts Previous work examines the relative efficiency impacts Welfare impacts depend on both efficiency and equity impacts MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 9 / 50
  • 17. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Research Question: Equity Impacts Previous work examines the relative efficiency impacts Welfare impacts depend on both efficiency and equity impacts Could GBL dominate TRAIL on equity grounds? MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 9 / 50
  • 18. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Why Worry? MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 10 / 50
  • 19. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Why Worry? MMMMV (2017): 30-40% of the efficiency impact of TRAIL due to borrower selection: TRAIL agents selected borrowers who were more productive Productive borrowers may also be wealthier/higher SES to begin with TRAIL could amplify these differences Efficiency gains, but at the cost of equity? MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 10 / 50
  • 20. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Aggregate Welfare Impacts We estimate the scheme’s impact on aggregate welfare depends on both efficiency and equity By partitioning households by landholding by social group: religion/caste MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 11 / 50
  • 21. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion How we estimate welfare impacts MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 12 / 50
  • 22. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion How we estimate welfare impacts Question: If the scheme was introduced into a village, by how much would the welfare of representative household change? MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 12 / 50
  • 23. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion How we estimate welfare impacts Question: If the scheme was introduced into a village, by how much would the welfare of representative household change? Problem: selection into the scheme was NOT random Average TRAIL borrower NOT representative of population MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 12 / 50
  • 24. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion How we estimate welfare impacts, contd. Question: If the scheme was introduced into a village, by how much would the income of representative household change? MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 13 / 50
  • 25. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion How we estimate welfare impacts, contd. Question: If the scheme was introduced into a village, by how much would the income of representative household change? That depends on: does that household participate in the scheme (pg )? MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 13 / 50
  • 26. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion How we estimate welfare impacts, contd. Question: If the scheme was introduced into a village, by how much would the income of representative household change? That depends on: does that household participate in the scheme (pg )? if it participates, how much does its income change (CTEg )? MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 13 / 50
  • 27. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion How we estimate welfare impacts, contd. Question: If the scheme was introduced into a village, by how much would the income of representative household change? That depends on: does that household participate in the scheme (pg )? if it participates, how much does its income change (CTEg )? Expected income effect for group g = pg × CTEg MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 13 / 50
  • 28. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion How we estimate welfare impacts, contd. Question: If the scheme was introduced into a village, by how much would the income of representative household change? That depends on: does that household participate in the scheme (pg )? if it participates, how much does its income change (CTEg )? Expected income effect for group g = pg × CTEg Use welfare functions to infer welfare effects with different assumptions about inequality aversion MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 13 / 50
  • 29. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion TRAIL Features MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 14 / 50
  • 30. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion TRAIL Features Agent is selected randomly from list of established trader/lenders in any given village MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 14 / 50
  • 31. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion TRAIL Features Agent is selected randomly from list of established trader/lenders in any given village Agent recommends 30 borrowers from among landless or marginal landowners (≤ 1.5 acres) subset of these are chosen randomly to receive offer of TRAIL loans MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 14 / 50
  • 32. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion TRAIL Features Agent is selected randomly from list of established trader/lenders in any given village Agent recommends 30 borrowers from among landless or marginal landowners (≤ 1.5 acres) subset of these are chosen randomly to receive offer of TRAIL loans Agent plays no further role: MFI sets loan terms, directly lends to and collects repayments from borrowers No group meetings, savings requirements or gender restrictions MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 14 / 50
  • 33. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion TRAIL Loan Features Loan interest rate pegged at below average rates on informal credit in the village Dynamic borrower incentives: start with small loans, future credit access grows at fast rate based on current repayment *Loan durations/timing: 4 months, match key-crop cycles *Insurance against covariate (price-yield) risks *Doorstep banking, no bank accounts (*: non-standard) MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 15 / 50
  • 34. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion The Group Based Lending Scheme Same loan features as TRAIL loans, except: 5-member self-formed groups of borrowers joint liability monthly group meetings savings requirements MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 16 / 50
  • 35. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Experimental Setting Two potato-growing districts in a state in eastern India 48 villages randomly assigned to: TRAIL scheme: 24 GBL scheme: 24 Collaborated with a microfinance institution 8 4-month cycles: Sept 2010 - July 2013 MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 17 / 50
  • 36. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Partitions Land class Landless 0-0.5 acres 0.5-1 acre 1-1.5 acres MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 18 / 50
  • 37. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Partitions Land class Landless 0-0.5 acres 0.5-1 acre 1-1.5 acres Social group scheduled castes/scheduled tribes non-Hindus general caste Hindus MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 18 / 50
  • 38. HH Characteristics by Land Class Average Landless 0–0.5 acres 0.5–1.0 acres 1.0–1.5 acres (1) (2) (3) (4) (5) Head’s education: primary school or more 0.420 0.211 0.366 0.552 0.654 (0.011) (0.019) (0.017) (0.021) (0.031) Head’s primary occupation: cultivation 0.438 0.057 0.374 0.692 0.726 (0.011) (0.011) (0.017) (0.020) (0.029) Head’s primary occupation: casual labor 0.332 0.673 0.409 0.091 0.043 (0.010) (0.022) (0.017) (0.012) (0.013) Landholding (Acres) 0.464 0.000 0.261 0.755 1.237 (0.009) (0.000) (0.005) (0.006) (0.009) Pucca house 0.273 0.171 0.259 0.324 0.377 (0.010) (0.018) (0.015) (0.020) (0.031) Electrified house 0.750 0.634 0.733 0.824 0.838 (0.010) (0.023) (0.015) (0.016) (0.024) Owns radio/TV/VCR/DVD 0.452 0.325 0.398 0.543 0.636 (0.011) (0.022) (0.017) (0.021) (0.031) Owns motorized vehicle 0.127 0.068 0.073 0.181 0.272 (0.007) (0.012) (0.009) (0.016) (0.029) Owns phone (mobile or landline) 0.591 0.420 0.536 0.712 0.781 (0.011) (0.023) (0.017) (0.019) (0.027) Has savings bank account 0.446 0.250 0.414 0.542 0.667 (0.011) (0.020) (0.017) (0.021) (0.030) Has insurance policy 0.286 0.139 0.247 0.375 0.461 (0.010) (0.016) (0.015) (0.021) (0.032)
  • 39. HH Characteristics by Social Group Total SC/ST Non-Hindu General (1) (2) (3) (4) Head’s education: primary school or more 0.420 0.222 0.317 0.614 (0.011) (0.015) (0.025) (0.016) Head’s primary occupation: cultivation 0.439 0.284 0.432 0.560 (0.011) (0.017) (0.026) (0.016) Head?s primary occupation: casual labor 0.331 0.562 0.276 0.176 (0.010) (0.018) (0.024) (0.012) Landholding (acres) 0.465 0.293 0.482 0.590 (0.009) (0.013) (0.022) (0.014) Pucca house 0.273 0.112 0.329 0.376 (0.010) (0.012) (0.025) (0.016) Electrified house 0.750 0.604 0.792 0.846 (0.010) (0.018) (0.022) (0.012) Own a radio/ TV/ VCR/ DVD 0.453 0.318 0.387 0.583 (0.011) (0.017) (0.026) (0.016) Owns motorized vehicle 0.126 0.030 0.155 0.189 (0.007) (0.006) (0.019) (0.013) Owns phone (mobile or landline) 0.590 0.413 0.691 0.687 (0.011) (0.018) (0.025) (0.015) Has savings bank account 0.446 0.284 0.408 0.586 (0.011) (0.017) (0.026) (0.016) Has insurance policy 0.287 0.161 0.237 0.403 (0.010) (0.013) (0.023) (0.016)
  • 40. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Land Class MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 21 / 50
  • 41. Step 1: Selection Frequencies pg pg = number of g hhs selected total number of g hhs selected = recommended by TRAIL agents self-selected into GBL groups selection = take-up only households with ≤ 1.5 acres of land considered
  • 42. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Step 1: Selection Frequencies, contd. 0.059 0.073 0.074 0.054 0.068 0.040 0.070 0.032 0.05.1 Landless Land 0-0.5 Land 0.5-1.0 Land 1.0-1.5 TRAIL GBL MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 23 / 50
  • 43. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Selection Frequencies by Land Class the landless have a slightly lower selection frequency in TRAIL than in GBL TRAIL: across land classes, selection frequencies are very similar GBL: selection frequencies fall as landholding increases MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 24 / 50
  • 44. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Step 2: CTEs, by land MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 25 / 50
  • 45. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Step 2: CTEs, by land -20000020000 Landless 0-0.5 acres 0.5-1 acres 1-1.5 acres TRAIL, absolute -20000020000 Landless 0-0.5 acres 0.5-1 acres 1-1.5 acres GBL, absolute Conditional Treatment Effects, by Land MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 25 / 50
  • 46. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Absolute v. Proportional CTEs, by land: TRAIL MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 26 / 50
  • 47. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Absolute v. Proportional CTEs, by land: TRAIL 01000020000 Landless 0-0.5 acres 0.5-1 acres 1-1.5 acres TRAIL, absolute -1012 Landless 0-0.5 acres 0.5-1 acres 1-1.5 acres TRAIL, relative Conditional Treatment Effects, by Land MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 26 / 50
  • 48. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Absolute v. Proportional CTEs, by land: GBL -20000-10000010000 Landless 0-0.5 acres 0.5-1 acres 1-1.5 acres GBL, absolute -.50.511.5 Landless 0-0.5 acres 0.5-1 acres 1-1.5 acres GBL, relative Conditional Treatment Effects, by Land MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 27 / 50
  • 49. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Step 3: Expected treatment effects on income -.010.01.02.03.04.05 ty_g Landless 0-0.5 acres 0.5-1 acres 1-1.5 acres TRAIL, relative -.010.01.02.03.04.05 ty_g Landless 0-0.5 acres 0.5-1 acres 1-1.5 acres GBL, relative Expected Proportional Treatment Effects, by Land MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 28 / 50
  • 50. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Step 4: Change in welfare, θ = 0 MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 29 / 50
  • 51. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Step 4: Change in welfare, θ = 0 -10123 rdw TRAIL GBL theta=0 MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 29 / 50
  • 52. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Step 4: Change in welfare, θ = 1 0.05.1.15.2 rdw TRAIL GBL theta=1 MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 30 / 50
  • 53. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Step 4: Change in welfare, θ = 2 20040060080010001200 rdw TRAIL GBL theta=2 MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 31 / 50
  • 54. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Step 4: Change in welfare, θ = 3 05000001.0e+061.5e+062.0e+06 rdw TRAIL GBL theta=3 MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 32 / 50
  • 55. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Step 4: Change in welfare, θ = 4 01.0e+092.0e+093.0e+09 rdw TRAIL GBL theta=4 MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 33 / 50
  • 56. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Step 4: Change in welfare, θ = 5 01.0e+122.0e+123.0e+124.0e+12 rdw TRAIL GBL theta=5 MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 34 / 50
  • 57. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Social Group MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 35 / 50
  • 58. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Step 1: Selection frequencies 0.073 0.073 0.066 0.050 0.064 0.037 0.05.1 SC/ST Non-Hindu General Probabilities of selection TRAIL GBL MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 36 / 50
  • 59. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Step 2: CTEs, by social group -500005000 SC/ST Non-Hindu General TRAIL, absolute -500005000 SC/ST Non-Hindu General GBL, absolute Conditional Treatment Effects, by Social Group MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 37 / 50
  • 60. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Absolute v. Proportional CTEs, by social group: TRAIL 0500010000 SC/ST Non-Hindu General TRAIL, absolute 0.51 SC/ST Non-Hindu General TRAIL, relative Conditional Treatment Effects, by Social Group MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 38 / 50
  • 61. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Absolute v. Proportional CTEs, by social group: GBL -500005000 SC/ST Non-Hindu General GBL, absolute -.50.5 SC/ST Non-Hindu General GBL, relative Conditional Treatment Effects, by Social Group MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 39 / 50
  • 62. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Step 3: Expected treatment effects, by social group -.010.01.02.03.04.05 ty_g SC/ST Non-Hindu General TRAIL, relative -.010.01.02.03.04.05 ty_g SC/ST Non-Hindu General GBL, relative Expected Proportional Treatment Effects, by Social Group MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 40 / 50
  • 63. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Step 4: Change in welfare, θ = 0 0.005.01.015.02.025 rdw TRAIL GBL theta=0 MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 41 / 50
  • 64. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Step 3: Change in welfare, θ = 4 5.0e+061.0e+071.5e+072.0e+07 rdw TRAIL GBL theta=4 MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 42 / 50
  • 65. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Step 3: Change in welfare, θ = 5 1.0e+092.0e+093.0e+094.0e+095.0e+096.0e+09 rdw TRAIL GBL theta=5 MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 43 / 50
  • 66. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Changes in Inequality θ = 1 θ = 2 θ = 3 θ = 4 θ = 5 (1) (2) (3) (4) (5) Panel A: TRAIL Baseline 0.3249 0.7236 0.8632 0.9051 0.9234 Endline 0.3205 0.7217 0.8630 0.9053 0.9237 Effect on inequality ↓ ↓ ↓ ↑ ↑ Panel B: GBL Baseline 0.3662 0.8139 0.9247 0.9517 0.9625 Endline 0.3594 0.7947 0.9123 0.9431 0.9561 Effect on inequality ↓ ↓ ↓ ↓ ↓ MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 44 / 50
  • 67. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Discussion The evidence that TRAIL was elitist is limited. MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 45 / 50
  • 68. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Discussion The evidence that TRAIL was elitist is limited. Comparing landless borrowers: in TRAIL had lower baseline farm income than in GBL MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 45 / 50
  • 69. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Discussion The evidence that TRAIL was elitist is limited. Comparing landless borrowers: in TRAIL had lower baseline farm income than in GBL In fact, GBL might be keeping out both the high wealth/high status households and the poorest among the low wealth households MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 45 / 50
  • 70. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Selection by TRAIL agent Control 1 households Representative sample Difference Panel A: Bought from agent Landless 0.233 0.280 -0.047 (0.079) (0.092) (0.120) 0–0.5 acres 0.523 0.333 0.190*** (0.048) (0.040) (0.062) 0.5–1 acres 0.339 0.365 -0.026 (0.062) (0.047) (0.078) 1–1.5 acres 0.318 0.488 -0.170 (0.102) (0.079) (0.131) Panel B: Borrowed from agent Landless 0.067 0.167 -0.100 (0.046) (0.078) (0.087) 0–0.5 acres 0.349 0.107 0.241*** (0.046) (0.026) (0.050) 0.5–1 acres 0.233 0.173 0.060 (0.055) (0.037) (0.064) 1–1.5 acres 0.227 0.220 0.008 (0.091) (0.066) (0.112) Panel C: Worked for agent Landless 0.167 0.000 0.167** (0.069) (0.000) (0.078) 0–0.5 acres 0.182 0.083 0.098** (0.037) (0.023) (0.042) 0.5–1 acres 0.133 0.086 0.048 (0.044) (0.027) (0.049) 1–1.5 acres 0.000 0.098 -0.098 (0.000) (0.047) (0.064) Panel D: Same social group as agent Landless 0.353 0.222 0.131 (0.083) (0.082) (0.118) 0–0.5 acres 0.504 0.543 -0.039 (0.047) (0.041) (0.062) 0.5–1 acres 0.672 0.517 0.155** (0.059) (0.047) (0.077) 1–1.5 acres 0.913 0.689 0.224** (0.060) (0.070) (0.107) MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 46 / 50
  • 71. Social Capital in GBL Groups Total SC/ST Non-Hindu General (1) (2) (3) (4) Invited by group members 0.583 0.536 0.800 0.558 (0.032) (0.048) (0.069) (0.051) Encouraged by officials to join group 0.417 0.464 0.200 0.442 (0.032) (0.048) (0.069) (0.051) Received assistance from others in the group (Cycle 1) 0.248 0.239 0.361 0.216 (0.028) (0.040) (0.081) (0.042) Provided assistance to others in the group (Cycle 1) 0.124 0.080 0.171 0.158 (0.021) (0.026) (0.065) (0.038) Proportion members with same occupation 0.624 0.616 0.598 0.642 (0.015) (0.022) (0.036) (0.023) Proportion members with same education level 0.530 0.520 0.594 0.516 (0.012) (0.019) (0.034) (0.018) Proportion members in same social group 0.522 0.732 0.887 0.192 (0.027) (0.038) (0.044) (0.033) Herfindahl Index by social group 0.762 0.873 0.940 0.593 (0.014) (0.019) (0.024) (0.019) Coefficient of variation of landholding 0.999 1.217 0.975 0.805 (0.035) (0.060) (0.075) (0.044)
  • 72. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Summary of Results Compare welfare impacts of two alternative credit delivery models TRAIL is not more elitist than GBL MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 48 / 50
  • 73. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Summary of Results Compare welfare impacts of two alternative credit delivery models TRAIL is not more elitist than GBL When partitioning by landholding: TRAIL generates higher average gains and benefits the landless more than GBL As a result it dominates GBL. MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 48 / 50
  • 74. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Summary of Results Compare welfare impacts of two alternative credit delivery models TRAIL is not more elitist than GBL When partitioning by landholding: TRAIL generates higher average gains and benefits the landless more than GBL As a result it dominates GBL. When partitioning by social group: TRAIL: High status group outperforms other groups GBL: Low status groups outperform high status groups Point estimates indicate larger welfare in GBL under high θ But differences are not statistically significant MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 48 / 50
  • 75. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Conclusion Our previous work indicates that TRAIL is superior to GBL from an efficiency standpoint. From an equity standpoint: Clear evidence from land partitioning that it outperforms GBL Less clear evidence from social group partitioning differences depend on θ values lack statistical significance MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 49 / 50
  • 76. Equity Impacts of Targeting Credit MMMV Motivation Equity Impacts TRAIL & GBL Partitions Results Land Social Group Inequality Mechanisms Conclusion Thank you! MMMV (Mar 2017) Equity Impacts of Targeting Credit Mar 2017 50 / 50