Payment technology complementarities and their consequences in the banking sector. (with José Renato Haas Ornelas)

Abstract: 

Can a new payment technology increase the use of other payment methods and enhance banking sector outcomes, such as deposits and loans? Leveraging individual-level banking data in Brazil, we examine the effects of a novel payment technology, Pix, on the utilization of other payment technologies and its impact on both banks and non-bank financial institutions (NBFIs). By comparing exogenous flood events in periods before and after the introduction of Pix, we are able to display the crucial role Pix plays in informal insurance and in promoting the use of financial products. We find that the use of Pix has led to a significant increase in bank deposits, loan activity, and the use of other payment methods, such as card payments, among individuals and firms. Non-bank financial institutions also experience higher account use due to Pix with no evidence of funds flowing from banks directly to them. Contrary to concerns raised by banks and regulators, we show that new payment technologies yield advantages not only for firms and individuals but also for the broader banking and payment industry.

Digital Payments and Monetary Policy Transmission. (with Pauline Liang and Sergey Sarkisyan)

Abstract: 

We examine the impact of digital payments on the transmission of monetary policy by leveraging administrative data on Brazil's Pix, a digital payment system. We find that Pix adoption diminished banks' market power, making them more responsive to changes in policy rates. We estimate a dynamic banking model in which digital payments amplify deposit demand elasticity. Our counterfactual results reveal that digital payments intensify the monetary transmission by reducing banks' market power-banks respond more to policy rate changes, and loans decrease more after monetary policy hikes. We find that digital payments impact monetary transmission primarily through the deposit channel.

The Ripple Effects of Instantaneous Payment Technologies: evidence from Brazil's Pix. (with José Renato Haas Ornelas)

Abstract: 

We assess the impact of digital payment adoption on real economic outcomes by analyzing administrative data on Brazil’s instant payment technology, Pix. Using exogenous flood events from periods before and after Pix's introduction, we investigate its influence on labor market metrics, including job formalization, growth in formal employment, and wage levels. Furthermore, we evaluate Pix's effects on local economic indicators such as municipal GDP and agricultural output. Leveraging data on formal incomes and governmental social program records, we conduct a heterogeneous analysis to explore the differential impact of Pix across income groups. Preliminary results indicate a positive effect of Pix on formal workers' wages, suggesting potential benefits that extend to both workers and municipalities. Further analysis will provide a deeper understanding of payment technologies's full economic implications.

Planning Production and Equipment Qualification under High Process Flexibility. (with Hongmin Li, Woonghee T. Huh, and Naiping Keng)

Abstract: 

We present and solve a joint production and qualification planning problem for a manufacturing environment with high process flexibility. Various factors contribute to the complexity of the problem, one of which is product-machine mapping: Each machine may be qualified to produce multiple products and each product can be produced on multiple machines. To meet a build-plan, the factory needs to not only determine a multi-machine multi-product production schedule that accounts for sequence-dependent setup time, but also a qualification schedule which prescribes whether and when a machine should undergo a qualification process such that it is ready to produce a product. We consider processing characteristics including sequence-dependent setups, job splitting, and machine eligibility in addition to qualification. We formulate the mathematical model as an MILP problem that minimizes the total weighted delay. In this study, we describe two heuristic solution approaches developed for this complex decision setting and the application at Intel. We compare our approach with Intel's current approach which is a spreadsheet-based manual approach that relies on the experience of the factory planner. The results indicate that our approach, which we call the GS approach, dominates in terms of minimizing the delay. Our approach performs well when capacity is tight and additional qualifications are considered while the Intel approach may perform better on reducing the setup and qualification time in certain problem instances, particularly those with loose capacity. As a result, an integrated approach which selects the better solution from both approaches is proposed, which shows significant reduction over the current approach in both the weighted delay and the setup and qualification time.