Monitoring Corruption: Evidence from a Experiment in Indonesia

1. Monitoring Corruption: Evidence from a Experiment in Indonesia Benjamin Olken

2. Motivation • Corruption is a significant problem in developing countries • Mauro (1995) • Moral issues • How does one best reduce corruption? • Combination of monitoring and punishments • Becker and Stigler (1974) • May simply transfer corruption • Increase grassroots participation • Community members may have better incentives than higher-level officials (Stiglitz 2002)

3. Measure • How do we measure corruption? • Traditionally measured perception of corruption • Mauro (1995), Lambsdorff (2003), Rose-Ackerman (2004) • Direct measure • Randomized field experiment with 608 Indonesian village road projects • Engineers dug core samples in road to estimate the amount of materials used • Local suppliers were surveyed to estimate prices • Villagers were interviewed to determine the wages paid • Missing Expenditures = (Reported Spendings – Cost to Build)

4. Approach • Top-down monitoring • Audits • Control: 4% chance of audit • Treatment: 100% chance of audit • Grassroots • 2 treatments • 1) Sent invitations for “accountability meetings” • 2) Invitations + Anonymous comment forms • Distribution • 1) Schools • 2) Neighborhood heads

6. Difficulties • Identification • Audit treatment may affect neighboring villages • Solution: • Randomization for audit clustered by subdistrict • Invitations and comment forms done village by village • Stratification • Estimate of amount of materials used in road may be smaller than the actual amount used • Loss ratio: average percentage of materials lost as a result of normal construction processes and measurement error • Captured in constant term of regression

7. Estimating Equation (OLS) PercentMissingijk = α1 + α2Auditjk + α3Invitationsijk + α4InvitationsandCommentsijk + εijk i represents a village j represents a subdistrict k represents a stratum of the audits

8. Findings for Audit Experiment • % of Expenditures Missing • Control: 27.7% • Audit (across all specifications): ~19% • This is a 30% reduction • Do these effects represent a reduction in corruption? • Replacing incompetent builders with more skilled workers? • Olken measured the more inexpensive aspects of construction quality (shape of the rocks, grade of the road, etc.) • Controlled for these quality measures • Did not change results of the regression

9. More Questions • Do these effects reflect more careful accounting by villages in response to the audits? • Calculate • 1) difference between estimated actual expenditures and planned expenditures • 2) difference between reported actual expenditures and planned expenditures • Results: effect due to changes in actual expenditures and not better accounting (although not statistically significant)

11. Grassroots Corruption Monitoring • Participation Experiments • Invitations led to 40% increase in attendance at meetings (increase was slightly smaller for the invitations + comments treatment) • About 30% of comment forms were filled out and returned • Quite successful • Average number of people who spoke at meetings increased by ~10%

12. Effect on Missing Expenditures • Overall missing expenditures decreased minimally (less than one percent) • Substantial decreases in missing labor expenditures (14-22%) • No change in missing materials expenditures (possibly slight increase) • Why? 2 main possibilities: • Easier for villagers to observe wages than quantity of materials used • Workers focused on private interests • Comment form treatment was only effective when distributed through schools

13. Cost-Benefit • Audits were substantially cost effective • Net social benefits: $250 per village • This is for a system that shifted from a 4% to 100% audit probability • If the response of corruption to audit probability is concave, then we could attain higher net social benefit with a 50% or even 25% audit probability • Invitations/Comments not cost effective • Olken’s Cost-Benefit analysis is speculative • Assumes that rents from corruption are all used during the village head’s political campaign

14. Conclusions • Increasing the probability of an audit to 100% reduced missing expenditures by 30% • This decrease was not larger because audits do not always detect corruption, impose punishment • Increasing grassroots participation can reduce missing expenditures under certain circumstances • Distribution via schools • Freeriding can be a problem

15. Discussant: Critique • Is it plausible? • Cost-Benefit Analysis: Yes • Limitations of the experiment? • We only see short-run effects • What does this imply?

16. Questions Left Unanswered • Generalizability? • Will these results hold for cultures with different social mores? • Long-run impact • How will long-term auditing affect who decides to become involved in project management? • Will it affect reelection probabilities for local officials? • What other effects will reduced corruption have? • Reduced campaign expenditures?

17. Possible Improvements • Repeat experiment with different audit probabilities • Could yield higher social benefits • Continue experiment for several periods to determine long-term impact