What determines contribution to a common fund for upkeep of water infrastructures? Evidence from experimental game in Coastal Bangladesh

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Presented by Marie-Charlotte Buisson, on the 31st of May, 2013, from the Challenge Program on Water and Food, G3.

Presented by Marie-Charlotte Buisson, on the 31st of May, 2013, from the Challenge Program on Water and Food, G3.

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  • For this purpose, WMOs are required to create a maintenance fund and collect contribution from its members.  
  • For this purpose, WMOs are required to create a maintenance fund and collect contribution from its members.  

Transcript

  • 1. 31 May 2013 Marie-Charlotte Buisson, Arijit Das, Aditi Mukherji What determines contribution to a common fund for upkeep of water infrastructures? Evidence from experimental game in Coastal Bangladesh
  • 2. INTRODUCTION • Embankments constructed by the Government of Bangladesh (GoB) across the entire coastal zone in the 1960s and 1970s. • 1st objective: Protection for tidal surge, flood, natural calamity • 2nd objective: Increasing agricultural productivity
  • 3. INTRODUCTION • Operation and maintenance of the infrastructures is the key challenge to ensure the sustainability of the system. • GoB requires local communities to organize themselves into Water Management Organizations (WMOs) and contribute towards minor maintenance of water infrastructure. • National Water Policy of 1999 (MoWR, 1999) • Guidelines for Participatory Water Management, (MoWR, 2001). RESEARCH PURPOSE To understand the factors that help or impede collection of voluntary maintenance funds from members of WMOs. POLICY PURPOSE Improve water governance and the maintenance of the infrastructure for enhancing the productive uses of land and water resources.  Some communities have been able to come together and collect fund for maintenance, while majority have not been able to do so. Why?
  • 4. CONTENT 1.Motivation and background 2. Methodology 3. Descriptive statistics 4. Regression analysis and results 5. Concluding remarks, recommendations
  • 5. MOTIVATION AND BACKGROUND Water policy in Bangladesh Before 60s 60s – 80s • Protection by temporary and seasonal earthen. • Maintenance by the landlords (zamindars). • Voluntary labour from their tenants. • Coastal Embankment Project (CEP) • No mention of participatory water management. • BWDB ‘khalashis’ responsible for managing and maintaining coastal embankments. 80s • Involvement of communities in design and implementation of projects introduced. • Financial contribution towards maintenance not required. • Late 1980s, entry of LGED in the water sector. • Community contribution towards maintenance tested for the first time. • Realization that regular upkeep of infrastructure is the Achilles heel of entire infrastructure investments. • GoB enunciated community participation as its core principle of water management through its NWP (MoWR, 1999) and GPWM (MoWR, 2001). • Requirement of financial contribution by the community for maintenance. 90s
  • 6. MOTIVATION AND BACKGROUND Maintenance situation Perception of the infrastructures condition • 20% of the households consider the gates as being in good condition. • 15% of the households consider the canals as being in good condition. Contributions • Both for LGED and BWDB data shows that maintenance funds always fall to answer to the requirements. • 91% of the household did not contribute to maintain the gates in 2012. • 95 % of the household did not contribute to maintain the canals in 2012. 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 Very bad canal condition Very bad gate condition
  • 7. MOTIVATION AND BACKGROUND Institutional differences • Theoretical and empirical research shows the importance of institutions in forging cooperative outcomes (Bardhan, 2005; Agrawal, 2001; North, 1990). • Importance of institution in sustainable management of common property resources (Wade, 1988; Ostrom, 1990; Baland and Platteau, 1996). • Entered the water sector in 1980s, culture of community participation was already well entrenched. • Small Scale Water Resources Sector Development Project (SSWRDSP), phase I in 1994, now phases III and IV, funding support until 2017. • WMCAs registered with the cooperative department. • Communities contribute 4% of the capital cost of physical infrastructure. • Maintenance funds , yearly audit statements. • NGOs and extension agencies for implementing community participation • Declining field presence. • WMGs or WMAs registered as rural cooperatives since 2008. • No contribution of the WMO required at initial stage. • Encouragement of the WMO for starting maintenance fund and collecting subscriptions. BWDBLGED
  • 8. METHODOLOGY Public good game Purpose of the game • Designing a fictive situation to reproduce “real life” • Understanding the determinants of contribution to maintain a public good. • Understanding the behaviours: from cooperation to free-riding Sample • Game played 18 times: - Polder 3, polder 30, polder 31 - Latabunia, Jabusha, Bagachra-Badurgachra • 5 players per game  90 players • 30 rounds per game  2700 decisions
  • 9. • Each player has to decide the allocation of a cash amount (20, 35/10) among a common fund and private fund. • The incentive for contributing in the common fund is that if the fund reaches a certain threshold (50 or 95), a payment is added (25 or 75). • The common pool is then distributed between the players.  The rules vary from one session to another to reflect real life conditions. METHODOLOGY Procedure of the game TREATMENTS C T1 T2 T3 T4 Information No Yes Yes Yes Yes Initial cash = = = ≠ ≠ Gains distribution = = ≠ = ≠ Threshold 50 50 50 50 50
  • 10. DESCRIPTIVE STATISTICS Average contribution per round Control Treatment 1 Treatment 2 Treatment 3 Treatment 4 8 101214 0 5 10 15 20 25 Rounds
  • 11. DESCRIPTIVE STATISTICS Information effect Control No information Treatment 1 Information T-test of differences (p-value) Individual variables Individual contributions 11.448 9.442 (0.000) Individual gains 26.117 22.702 (0.000) Group variable Proportion of rounds with success 0.744 0.533 (0.003) Contribution standard deviation, within group 5.009 4.174 (0.020) Control Round 5 No information Treatment 1 Round 6 Information Individual variables Individual contributions 12.277 10.233 Individual gains 27.666 22.488
  • 12. DESCRIPTIVE STATISTICS Unequal gain distribution effect Treatment 1 Equal gains distribution Treatment 2 Proportional gains distribution T-test of differences (p-value) Individual variables Individual contributions 9.442 13.224 (0.000) Individual gains 22.702 27.842 (0.000) Group variable Proportion of rounds with success 0. 533 0.777 (0.000) Contribution standard deviation, within group 4.174 4.005 (0.640) Equal Endow ment
  • 13. DESCRIPTIVE STATISTICS Inequalities in endowments effect Equal Endow ment Treatment 1 Equal endowments Treatment 3 Unequal endowments T-test of differences (p-value) Individual variables Individual contributions 9.442 10.208 (0.156) Individual gains 22.702 24.602 (0.010) Group variable Proportion of rounds with success 0.533 0.611 (0.294) Amount collected in the collective fund 47.211 51.044 (0.274) Contribution standard deviation, within group 4.174 8.394 (0.000)
  • 14. REGRESSION ANALYSIS Model Equal Endow ment Individual contribution Individual earning Round characteristics • Game-rules variables • Past events from the game (success, contributions, earning) Group characteristics • Number of relatives and friends • Heterogeneity of the group (sex, religion, wealth) • Institutional context Individual characteristics • Age, sex, religion • Level of education • Main source of income, land size • Participation and contribution • Model estimated by OLS • Clustering at individual level for taking care of unobserved characteristics of the individual.
  • 15. REGRESSION ANALYSIS Estimation strategy Equal Endow ment Robustness Panel analysis, with individual fixed effects Consistency of the results Learning effect Each player learns from the game, from the group he plays with and this learning also depend from his own background. • Individual, group level • age, sex, education • clustering at individual level • Game level: • continuous variable, number of round already played by the member • Game events from the 2 previous rounds: contribution, earning, failure
  • 16. REGRESSION ANALYSIS Game variables - Results Equal Endow ment VARIABLES (1) OLS (3) OLS Individual contribution Individual earning Initial endowment 0.566*** 0.963*** (0.0348) (0.0270) Information -1.851*** -3.754*** (0.449) (0.871) Inequalities in endowments -2.497*** -3.400** (0.753) (1.425) Unequal sharing of the pot 1.204** 1.270 (0.508) (0.901) Previous round unsuccessful 0.249*** 0.423*** (0.0747) (0.144) Round, learning effect -6.277*** -7.717*** (0.559) (0.668) Observations 2,250 2,250 R-squared 0.523 0.473 • Information has a negative and significant effect on the individual contribution as well as on the earning • Endowment heterogeneity in the game design has a significant negative influence on the individual earning and contribution. • Proportional distribution of the common fund has a significant and positive effect on the contributions.
  • 17. REGRESSION ANALYSIS Individual variables - Results Equal Endow ment VARIABLES (1) OLS (3) OLS Individual contribution Individual earning Main income from agriculture 2.364** -2.223** (0.955) (0.895) Main income from aquaculture 2.753*** -1.500* (0.917) (0.846) Sex, men -0.516 0.244 (0.988) (0.750) Religion, Muslim 3.768*** -1.711** (0.898) (0.833) Age 0.0539* 0.0312 (0.0321) (0.0336) Education level 0.319*** -0.0843 (0.101) (0.0812) WMCA, WMO member 0.683 -1.541** (0.678) (0.662) Contribution in maintenance fund -0.497 -1.400 (0.881) (0.976) Land size -0.00208** 0.00162 (0.000942) (0.00131) Observations 2,250 2,250 R-squared 0.523 0.473 Players are drawing most of their income from agriculture or aquaculture they are contributing more to the common fund. Age as well as the highest level of education achieved determine positively and significantly the individual contribution.
  • 18. REGRESSION ANALYSIS Group variables - Results Equal Endow ment VARIABLES (1) OLS (3) OLS Individual contribution Individual earning LGED sub-project 2.376*** 2.637*** (0.876) (0.831) Number of relative in the group -1.073** 0.641 (0.418) (0.475) Number of close friend in the group -0.312 0.718 (0.405) (0.450) Same religion within the group 0.767 -0.304 (0.902) (0.841) Standard deviation of land size 0.00177 0.00189 (0.00141) (0.00132) Group of men 0.765 1.452* (0.781) (0.731) Constant -7.898*** 7.467*** (2.250) (2.264) Observations 2,250 2,250 R-squared 0.523 0.473 • Group composition in terms of gender, religion or wealth doesn’t have any significant effect on the individual contribution. • The more a player is surrounded by relatives in his group, the less he contributes. • Players from LGED villages are contributing higher amounts in the common fund than other players whatever are the individual, group and game characteristics.
  • 19. CONCLUSION Main results and recommendations Equal Endow ment 1. Principal users and beneficiaries of the infrastructures should be targeted first for contributing. 2. Homogeneous groups would contribute more and maintain their infrastructure better. • But: How to create homogeneous groups in heterogeneous villages? • Solution: Membership conditions • Ex: In some WMOs, only landowners can be members. 3. Contributions are higher when there are related benefits. • But: In reality, benefits are not related to the contributions. • Solution: Introducing benefits for members, even if not related to water • Ex: In some WMOs, access to micro-credit for members, fishing rights… 4. Strong institutions support individual contributions for maintenance. • Institutions created by the community itself • Involvement at the early stage of the project, create an ownership, a willingness (and ability) to cooperate in the future.
  • 20. Thank you Your questions, comments and suggestions are welcome!