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Daniel L. Nielson Brigham Young University Michael J. Tierney College of William and Mary

Principals and Interests: Collective Principals and Environmental Lending at Multilateral Development Banks. Daniel L. Nielson Brigham Young University Michael J. Tierney College of William and Mary. Empirical Puzzle. Trends Member governments grow more environmentalist after early-1970s

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Daniel L. Nielson Brigham Young University Michael J. Tierney College of William and Mary

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  1. Principals and Interests: Collective Principals and Environmental Lending at Multilateral Development Banks Daniel L. NielsonBrigham Young University Michael J. TierneyCollege of William and Mary

  2. Empirical Puzzle • Trends • Member governments grow more environmentalist after early-1970s • MDBs largely ignore environment until late-1980s • Late-1980s through 1990s – Big increase in MDB environmental lending • Gaps • How can we explain delay and eventual adoption of an environmental agenda? • How can we explain timing of adoption across different MDBs?

  3. IR Theory and IOs • Neorealism and Neoliberalism deny IO agency • Constructivism suggests abdication • Agency theory resolves gaps • IOs are independent actors • Member states conceived as principals of IOs • Our distinction: collective principal • Principals’ converging preferences guide agents • Principals’ coordination problems enable agency slack

  4. X Agent X XYZ Agent Y Agent Z Most IOs Modeling Collective Delegation • Which type of principal? Single Principal Collective Principal Multiple Principals

  5. Two Stages of Delegation at MDBs: Asian Development Bank

  6. X Policy Outcome Policy Outcome Y Z Collective Principal with Majority Vote X 0% 25% 50% 75% 100% Proportion of Environmental Loans Observational Equivalence X Y Multiple Principals, Independent Action Z X 0% 25% 50% 75% 100% Proportion of Environmental Loans Collective vs. Multiple Principals, Stage 1

  7. Policy Outcome X Y Z Collective Principal with Majority Vote X 0% 25% 50% 75% 100% Proportion of Environmental Loans Divergent Expectations Policy Outcome? X Multiple Principals, Independent Action Y Z 0% 25% 50% 75% 100% Proportion of Environmental Loans Collective vs. Multiple Principals, Stage 2

  8. What Causes IO Agents to Change Behavior? • Hypothesis: • As the policy preferences of collective principals shift toward environmental concerns • MDB Environmental loans will increase • MDB Neutral loans will increase • MDB Dirty loans will decrease

  9. Imputing & Aggregating Preferences (IVs) • Imputing Preferences • Infer preferences from behavior – revealed preferences • Use policy outcomes as proxies for preferences • Environmental Policy Index • Environmental Foreign Aid • Aggregating Preferences • Examine states’ preference distribution • Predict voting coalitions • Weight state’s influence by degree it proves “pivotal” to potential coalitions

  10. Data on Dependent Variable • More than 7,500 individual development loans • World Bank (IBRD & IDA) • African Development Bank & Fund • Asian Development Bank • Inter-American Development Bank • Islamic Development • Coded all loans on five-point environmental scale • Dirty Strictly Defined: direct negative impact (i.e., logging) • Dirty Broadly Defined: moderate but negative (agriculture) • Neutral: no immediate impact (education, telecomm.) • Environmental Broadly Defined: preventative (nuclear safety) • Environmental Strictly Defined: direct (pollution control, biodiversity protection)

  11. MDB Environmental Lending

  12. Environmental Policy Preferences - Policy Index

  13. Variables of Interest • Dependent Variable: Environmental Impact • 1=DSD, 2=DBD, 3=N, 4=EBD, 5=ESD • Key Indep. Variable: Environmental Preferences • Measured 3 ways: • Environmental Policy Index • Environmental Foreign Aid / Total Aid • Environmental + Neutral Aid / Total Aid • Controls • Organic Water Pollution, (De)forestation, Threatened Birds, Sanitation, Infant Mortality, Fertility Rate, Agricultural Value Added, CITES Commitments, GDP Per Capita, ln(GDP), ln(Population), Domestic Savings, Exports, Vehicles, Protected Land

  14. Ordered Logit Regression ResultsDep. Var.: Environmental Impact

  15. Results Summary • Environmental Preferences: • Positive and Significant (beyond .001 level) • Substantively Important • +1 stdev (.12 to .16) for Environmental Preferences  •  4.6% to 8.3% in probability of Dirty project •  2.5% to 4.9% in probability of Neutral project •  1.6% to 3.4% in probability of Environmental project • Controls: mixed to weak • Only Savings and (De)Forestation performed consistently • Others significant in 2 specifications: • GDP per capita, Agriculture Value Added, Threatened Birds, Sanitation, and Protected Land

  16. Conclusion • Collective delegation can work • In (Most) Difficult Context • International Anarchy • Extreme Preference Heterogeneity • Many Actors (up to 180) • More work to • Other specifications of preferences • Further robustness checks

  17. Extra Slide Pivotal-Weighted Preferences

  18. Pivotal-Weighted Preferences Potential Pivotal CoalitionsPlayers ABC A or C ABCD None ABCDE None BCD B or D BCDE B

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