A monetary mechanism for sharing capital: Diamond and Dybvig meet Kiyotaki and Wright

A model is presented in which banks accept deposits of fiat money and intermediate capital. Alt though theories about the coexistence of money and credit are inherently difficult, the model offers a simple explanation for the dual role of financial institutions: Banks are well monitored, and can credibly allow fiat-money withdraws to whom needs its, thus qualifying to become safe brokers of idle capital. The model shares some features with those of Diamond and Dybvig (1983) and Kiyotaki and Wright (1989).

A note on convergence of Peck-Shell and Green-Lin mechanisms in the Diamond-Dybvig model

We study the effects of population size in the Peck-Shell analysis of bank runs. We find that a contract featuring equal-treatment for almost all depositors of the same type approximates the optimum. Because the approximation also satisfies Green-Lin incentive constraints, when the planner discloses positions in the queue, welfare in these alternative specifications are sandwiched. Disclosure, however, it is not needed since our approximating contract is not subject to runs.

A monetary mechanism for sharing capital: Diamond and Dybvig meet Kiyotaki and Wright

Historically, payment systems and capital intermediation interact. Friedman (1959), and many observers of bank instabilities, have ad- vocated separating depositary from credit institutions. His proposal meets today an ever-increasing provision of inside money, and a short- age of monetary models of bank intermediation. In this paper, we eval- uate the proposal from a new angle, with a model in which isolating a safe payments system from commercial intermediation undermines information complementarities in banking activities. Some features of the environment resemble the models in Diamond and Dybvig (1983), and Kiyotaki and Wright (1989).

Cherry picking with synthetic controls

The synthetic control (SC) method has been recently proposed as an alternative method to estimate treatment e ects in comparative case studies. Abadie et al. [2010] and Abadie et al. [2015] argue that one of the advantages of the SC method is that it imposes a data-driven process to select the comparison units, providing more transparency and less discretionary power to the researcher. However, an important limitation of the SC method is that it does not provide clear guidance on the choice of predictor variables used to estimate the SC weights. We show that such lack of speci c guidances provides signi cant opportunities for the researcher to search for speci cations with statistically signi cant results, undermining one of the main advantages of the method. Considering six alternative speci cations commonly used in SC applications, we calculate in Monte Carlo simulations the probability of nding a statistically signi cant result at 5% in at least one speci cation. We nd that this probability can be as high as 13% (23% for a 10% signi cance test) when there are 12 pre-intervention periods and decay slowly with the number of pre-intervention periods. With 230 pre-intervention periods, this probability is still around 10% (18% for a 10% signi cance test). We show that the speci cation that uses the average pre-treatment outcome values to estimate the weights performed particularly bad in our simulations. However, the speci cation-searching problem remains relevant even when we do not consider this speci cation. We also show that this speci cation-searching problem is relevant in simulations with real datasets looking at placebo interventions in the Current Population Survey (CPS). In order to mitigate this problem, we propose a criterion to select among SC di erent speci cations based on the prediction error of each speci cations in placebo estimations