Causal Strategic Inference in Networked Microfinance Economies
Performing interventions is a major challenge in economic policy-making. We propose causal strategic inference as a framework for conducting interventions and apply it to large, networked microfinance economies. The basic solution platform consists of modeling a microfinance market as a networked economy, learning the parameters of the model from the real-world microfinance data, and designing algorithms for various causal questions. For a special case of our model, we show that an equilibrium point always exists and that the equilibrium interest rates are unique. For the general case, we give a constructive proof of the existence of an equilibrium point. Our empirical study is based on the microfinance data from Bangladesh and Bolivia, which we use to first learn our models. We show that causal strategic inference can assist policy-makers by evaluating the outcomes of various types of interventions, such as removing a loss-making bank from the market, imposing an interest rate cap, and subsidizing banks.
SUMMARY:  This paper presents a model for analyzing policy decisions, particularly ones that require some causal knowledge, in microfinance markets.  The model is justified by several studies, and analyzed to show the existence of equilibrium prices.  A computational framework is then presented to compute an equilibrium and learn the parameters of the model from real micofinance data.  Finally, the authors leverage the framework to provide answers to several policy questions.CRITIQUE:  By all metrics, this is a good paper.  It is clear, well-motivated, well-supported by analysis and data, introduces novel techniques, and has a potential for impact.  I point out a few specific problems below, and I do wonder whether this is a good fit for NIPS, but defer to more senior members for the latter.SUGGESTION:  The assumption that MFIs are non-profits is crucial to the entire analysis, yet in my mind is a source for some of the more interesting questions.  At the very least, it would be interesting to note what changes when MFIs are profit seeking, either analytically or empirically.  Specifically, could the social welfare actually increase if MFIs were even slightly profit seeking, and therefore requiring fewer subsidies over time?  It seems that if you expanded your model slightly you might be able to answer this question.SPECIFIC COMMENTS:page 2:. "[13] and joint-liability contracts would mitigate the risks of adverse selection [13]" -- odd to cite [13] twice in the same sentence. "study of causality" -- this term is not really defined, and to many people may seem extremely vague (i.e. all of science); even though you very nicely explain everything in the appendix, it might go a long way to describe the scope of "causality" here. "Put differently, what would be a game-theoretic analog of the do operation [21, p. 23] used for surgeries in probabilistic settings?" -- This sentence is somewhat meaningless unless you know the reference; please clarify the contextpage 3:. "subset of the village"[s]. "interest rate at which MFI i gives loan" -- the phrase "gives loan" seemed odd to me. "max_{r_i} 1" -- this is jarring without an explicit reassurance that you indeed intended max 1. "each MFI i is optimizing (P_M)" -- add "the left-hand side of" (one cannot optimize an inequality)page 4:. "we model the village side as non-corporate agents." -- Where does this come up in the model?. Property 3.2. -- Interpret this for us in words. "trivial allocations" -- Again, remind us what x is by saying why this would be trivialpage 5:. "that a more restricted case" -- this sentence has a bug. "Change ri as described later." -- Cite a specific equation number so the reader isn't left looking for where you fill this in (it's not obvious)page 6:. "Our model computes lower equilibrium interest rate"