Impact of Better Factories Cambodia: Evidence from Factory-Level Empirical Analysis

1. Impact of Better Factories Cambodia:Evidence from Factory-Level Empirical Analysis Raymond Robertson, Macalester College Rajeev Dehejia, Tufts University Drusilla Brown, Tufts University

2. Three Recent Papers • “Public Disclosure, Reputation Sensitivity, and Labor Law Compliance” Raymond Robertson, Rajeev Dehejia, Drusilla Brown, Debra Ang • “Two Steps Forward, One Step Back? Retrogression in Working Conditions: Evidence from Better Factories Cambodia” Drusilla Brown; Rajeev Dehejia; Raymond Robertson • “Working Conditions and Factory Survival” Drusilla Brown; Rajeev Dehejia; Raymond Robertson

3. Changes in Working Conditions

4. Summary of Results • Overall compliance is high and increases consistently • Public Disclosure • BFC originally posted compliance record on the Internet • Ended this policy in Fall of 2006 • Data through 2008 suggest that compliance rates, especially first-time compliance and changes in compliance between first and second visit were much higher during public disclosure period • Retrogression (preliminary) • Retrogression rates are low • Retrogression rates affected by investment costs • Public disclosure may have deterred retrogression

5. “Working Conditions and Factory Survival”: Our Hypothesis • Assuming that managers are optimizing with full information and without perceptions of coordination failures, the regulations imposed by the BFC program could increase the rate of factory failure (closure). • On the other hand, if the measures help the firm, perhaps by increasing worker effort or productivity, then the chances of firm survival may increase. • Bottom line: what changes, if any, have statistically significant effects on the probability of closure?

6. Kaplan-Meier Survival Estimates for Selected Compliance Categories

7. Empirical Strategy: Survival Analysis and Linear Probability Model • Time variable: Visit • Visits occur about every 8-12 months • Assumes that the exposure begins when factories start participating in BFC (obviously contestable) • Treatment: BFC • Problem: Right-hand censoring • Most factories reach end of sample period (2011) without failing • Empirical approach handles this problem • Estimate “conditional compliance rate” for each firm as a summary measure of question-level compliance

8. Cox Estimation of Closure Probabilities • Four specifications: levels, differences, 2nd visit change and 2nd visit indicator • Most controls strongly and consistently significant • Size (initial log employment)  Negative (reduces failure) • Reputation Sensitive Buyer Negative (in ¾) • Crisis control Positive • Ownership country not significant • Most working conditions not significant. • Exceptions: Regular hours (in #2), Payment of Wages (negative in all, sig in #2 and #4) • Address potential multicollinearity with factor analysis

10. Key Findings • Very little, if any, support for argument that improving working conditions increases probability of closure • Factories with higher conditional compliance rates are less likely to close • There is some support for the “efficiency wage” hypothesis in that improvements in some areas reduce the probability of closure

11. Recommendations • Gov’t/NGOs: Continued research is necessary • Measuring productivity directly • Controlling for endogeneity • Buyers/Managers: Consider thinking about HR innovations as another form of technology that might improve factory performance overall. If performance improvements are greater than cost increases, then compliance may increase chance of factory survival.

12. Thank you for your Comments!

13. Data • Monitoring begins in 2001 • In 2008 a team from Macalester coded monitoring reports