Program Evaluations and Randomization

Lecture 9 HSE, 8.12.2014

Dagmara Celik Katreniak

Course Overview

• Part I: Field Experiments – Introduction to Randomized Control Trials (RCTs)

• Why to randomize? • Field versus Lab Experiments

– Experimental Design • Types of designs, designing stages • Implementation of an RCT • Implementation issues (attrition, spillover, selection, …)

– Data Analysis • Treatment effects

Course Overview

• Part II: Topics in Development Economics – Field experiments in health – Field experiments in education – Field experiments in consumer choice – Field experiments in labor economics – Field experiments in microfinance – Field experiments in credit and savings

Outcome • Proposal

– Topic closest to your interest – Literature review – Arguments for the proposed project – Methodology – Sample size and power calculation – Budget – Logistics and Implementation, suggested solutions

for possible implementation issues

Expectations and Evaluation

• Attendance (5% of final score) • Reading list • Quizzes (15% of final score) • Final examination (50% of final score)

– Before midterm 20% and final 30% • Proposal presentation (first draft)

– Individual or in pairs • Proposal (final draft, 30% of final score)

Outline

• Credit and Savings • Microfinance

• Proposal Presentations

• December 15th – final examination

– What to expect?

Poor • Poor have little access to credit • Poor face lots of risk and do not have any insurance • Do poor attempt to save? • How could poor save?

– Keep money “under their pillow” – Bank account – Saving groups (SHGs = self-help groups) – ROSCAs (= rotating saving and credit association) and

ASCAs (=accumulating saving and credit association) – Money guards – Take a loan from microfinance and invest it in a bank – Mobile money – Immediate investment into durable goods

• So why don’t they save? Or how do they save?

Saving • Poor find various ways to save, usually costly or

inefficient

• Would they save more if banks open inexpensive accounts for them? – How would you try to find it out?

Dupas & Robinson: AEJ Applied Economics 2013

• Randomized access to noninterest-bearing bank accounts in Kenya – Offered to market vendors (mostly women) and bicycle

taxi drivers (men) – paid opening-account fees in a village bank, no interest,

but some fee for withdrawals • Administrative data from banks and daily logbooks of

participants • Results:

– Treated market women used accounts actively compared to non-treated women; their savings as well as expenditures increased on average; they increased their investment, too;

• about 2/3 of women deposited money at least once – No significant results for men

Where is the problem coming from?

• Access to the saving products – If it was enough to make the banking account cheaper, the

study of Dupas and Robinson would have higher take up rates and equally distributed among men and women

• Poor’ psychology – Kremer, Robinson and Duflo: western Kenya, fertilizers

• Time inconsistency • Savings and Fertilizer Initiative (SAFI) – voucher purchasing

fertilizer at later time – increase in fertilizer usage by 50% – Similar to the story of street vendors – temptation goods

• Following their consumption patterns they could save 5 rupees a day and not to drink sweet tea .. In 90 days

• Decision making under fMRI scanner (20$ vs. 30$ under different time patterns)

Are poor aware of their inconsistency?

• How to find it out?

• Ask directly people

• Saving brick by brick serves as an example they are • If they are aware, they should be willing to commit or to

pay someone to force them to save – Taking loan from microfinance institution – Financial product designed to commit

Ashraf, Karlan & Yin (QJE 2006)

• “Tying Odysseus to the Mast: Evidence From a Commitment Savings Product in the Philippines”

• commitment savings product • Baseline on existing clients, ½ chosen to be

treated (offer of commitment product) – Out of 710 only 202 accepted the product

• Comparison of saving balances across subjects • Average saving balances increased by 81% after

12 months – Comparison of those assigned to treatment compared

to the control

Where is the problem? • Problem is that not everyone is aware of his self-control

problem; it needs push from inside • Dupas and Robinson (Kenya):

– Offered lockboxes to ROSCA savers which would serve for emergency usages (health-wise)

– They randomly assigned two groups, in the first one key from lockbox was given to ROSCA group members, in the second one to NGO field officers kept it

– People used lockbox more if they had a key from it, they were scared of locked lockbox

• Also, problem is about future expectations • Karlan and Mullainathan – repayment of loans of vendors,

shortly they were in debt again (40% after 10 weeks)

Dupas & Robinson (AER 2013) • “Why Don’t the Poor Save More? Evidence from Health

Savings Experiments” • Provision of saving technologies can increase investment in

preventative health and reduce vulnerability to health shocks – Safe place for money increased health savings by 66 percent

• Design: – Safebox, lockbox, Health Saving Accounts versus health pot – Differ in type and amount of commitment – Earnmaking versus storage versus social commitment

• “existing informal mechanisms in rural Kenya are insufficient” – “introducing a technology as basic as a simple box with a lock

and key allows the average individual to substantially increase her investment in preventative health and to reduce her household’s vulnerability to health shocks.”

Summary

• Poor people have limited access to saving but they want to save as they come up with alternative saving products

• They are time inconsistent • Their behavior is influenced by temptation goods

– Comparison to rich people • On one hand they want flexibility, on the other hand

once they commit (buy bricks) they search for other alternatives if a problem appears

• Only some fraction of poor realizes their problem with self-control

• Hope, optimism and future aspirations and beliefs play role

Risk • Every day component of poor’s life • No assurance of stable salary and regular employment • Vulnerability of poor

• A story of Ibu Tina, Indonesia (Poor Economics, Ch.6)

• Poor verus hedge-fund managers

– Who is worse off? – No hedge-fund manager is liable for 100 percent of his

losses – Poor put all their own capital into business start-up

The life of poor • They run small businesses or farms • Risk

– Weather, agricultural disasters – Health status – Frauds and thieves

– Global economic crisis, WB

– No insurance, no guarantee – No enforceability – High level of corruption

– Psychological effects, stress

• Do we face a poverty trap?

Poor Economics, p.139

The Hedge How would you spread the risk? How would you try to insure against risks?

• Try to work more – Negative impact in isolated areas

• Diversification of your portfolio of activities – Agricultural and nonagricultural activities – But conservative with respect to experimenting

• Multiple plots within village • Renting some land (cost-sharing in good/bad times) • Short-term migration for work of some family members • Inter-village marriages • The number of children • What are the disadvantages? Are there other ways?

Community life • Extended families, neighbors, communities, religion

meetings, etc. • All represent “an insurance target” unless all are hurt • Informal insurance (a form of solidarity)

– Christopher Udry (The review of Economic Studies 1994) – Nigeria – Not perfect – After shock people despite the solidarity decrease their

consumption (in the presence of perfect insurance this should not happen)

– Fafchamps and Lund, Philippines – informal contracts work only if the shock is not caused by health shock

• Why?

• Reciprocity? Or moral obligation?

Insurance Companies for poor? • Formal insurance non-existing or rare

– Health insurance – Insurance against bad weather – Insurance against livestock death, etc.

• Since poor face lots of risk, they should be willing to pay risk premium and get insured - true?

• Problems with formal insurance – Moral hazard – Adverse Selection – Outright fraud (example: insurance against cattle death)

– The insurance companies do not want only sick to be in

their portfolio

Micro Insurance?

• Micro Health Insurance – SKS Microfinance, India – Compulsory insurance for microcredit customers – Over time – compulsory for renewals, then voluntary – People not willing to get insurance

• Micro Against-Weather Insurance – Robert Townsend, India – Very low take-up rate (higher for door-to-door product

sellers)

• Why low take-up rate?

Why poor do not want Insurance?

• Government’s fault? – Non functioning markets – In case of disasters – help from governments

• Insufficient

• Low understanding of insurance

• Insurance only against catastrophic scenarios

• Lack of trust, lack of credibility

• Time inconsistency

Summary

• Poor bear high levels of risk • But the take up rate of insurance products is low • Possible reasons are not:

– Lack of knowledge or understanding – Humanitarian aid

• Possible reasons are: – Lack of trust and/or credibility – Time inconsistency

• Role for government – Should step in to help insurance market to

emerge

Lending to the poor

• Suppose you are a street vendor and you do not have cash to buy fruits you want to sell during a day

• You can have a loan from the wholesaler • Banerjee and Duflo (PE, Ch.7) observed in India: • You would buy fruits for 1000 rupees (15.78 USD) in the

morning • You would have to repay 1046.9 rupees on average back • What do you think about it? • It means that there is 4.69% interest rate DAILY!

• If poor would not have to repay loans, they could expand • Why don’t they borrow money from banks?

Official Lending Institutions • Banks

– There is no scarcity of banks • Robin Burgess and Rohini Pande, a study in India • Problems with high default rates, lending driven by

political priorities (before election), money in hands of “local elites”

• Short term effect – positive on the poverty, but in long term

– It is very costly • Interest can vary from 40 – 200 per cent per year (PE,

p.160) – The poorer you are, the more you are going to pay

• Why?

Official Lending Institutions

• Problems with poor – High default rates (informal lending low, formal lending

high due to long enforceability of credit contracts) – Collaterals needed – Poor are costly (monitoring represent fixed costs no matter

what is the size of loan in the end = information constraint) – Segmentation (official lending institutions prefer to lend to

people they trust and whom they know)

Why high interest rates for poor? • Monopoly of the lender (or monopolistic competition)

• Lender’s risk – Absence of legal enforcement – High default risk – For lenders extra costs of monitoring and enforcement and

therefore they have high information and administration costs – Some costs fixed, some scale with the loan size – Multiplier effect

• Arbitrage by lender – Borrow cheap, lend further for higher rate

• So how to lend to poor?

Microfinance • Spadana

– Padmaja Reddy – She started from 1 loan to one ragpicker in 1997 to

4.2milion loan clients with portfolio of 42 billion ruppes in 2010

– Simple idea – small loan for poor for reasonable interest

• Microfinance, Grameen Bank (the bank for the poor) – Muhammad Yunus (Nobel Peace Prize winner, 2006) – Since 1970s – The main idea is not to make money out of poor but to

help them to make money and be financially stable

• Why didn’t street lenders lower their interest to fight?

Microfinance • Typically, it involves loans to a group of people, which solves

the problem of knowing the customer well • Uses information from inside of the community • Members are liable for each other’s loans • If default – future lending cut off • Simplicity, loan collector does not need high skills • Limited flexibility and short repayment horizon

– Fixed amount of repaying each week on a weekly meeting • Cost of lending much smaller compared to official lending

institutions but still high • Zero tolerance for failure

Banerjee et al. (SSRN 2013) • The miracle of microfinance; India • Slums randomized into opening a branch of a microfinance

institution (Spadana) • 15 – 18 months later

– households were 8.8 percentage points more likely to have a microcredit loan

– No more likely to start new business (instead they invested into their existing businesses)

– No effect on average monthly expenditure per capita – Expenditures on durable goods increased, on temptation goods

declined • 3 – 4 years later

– Probability of borrowing the same – Households in treatment slums borrowed for longer and larger

amounts

Thank you for your attention

… and please evaluate the course