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920686299-MIT.Pdf Essays on Banking and Local Credit Markets by Hoai-Luu Q. Nguyen S.B. Economics, Minor in Mathematics, Massachusetts Institute of Technology (2007) Submitted to the Department of Economics in partial fulfillment of the requirements for the degree of MASSACHUSETTS INSTITUTE Doctor of Philosophy OF TECHNOLOLGY at the JUN 09 2015 MASSACHUSETTS INSTITUTE OF TECHNOLOGY LIBRARIES· June 2015 © 2015 Hoai-Luu Q. Nguyen. All rights reserved. The author hereby grants to MIT permission to reproduce and distribute publicly paper and electronic copies of this thesis document in whole or in part. Signature redacted Author .......... y Department of Economics May 15, 2015 Signature redacted Certified by .......................................... Michael Greenstone Milton Friedman Professor of Economics, University of Chicago Signature redacted Thesis Supervisor Certified by ....... Robert M. Townsend Elizabeth & James Killian Professor of Economics Thesis Supervisor Signature------- - redacted Accepted by .. /~ Ricardo J. Caballero Ford International Professor of Economics Chairman, Departmental Committee on Graduate Studies Essays on Banking and Local Credit Markets by Hoai-Luu Q. Nguyen Submitted to the Department of Economics on May 15, 2015, in partial fulfillment of the requirements for the degree of Doctor of Philosophy Abstract This thesis consists of three chapters on banking and local credit markets. The first chapter studies the relationship between bank-specific capital and credit access in a new setting: bank branch closings in markets where the branch network is dense. Existing regulation in the U.S. is targeted toward areas with few branches where closings inhibit physical access to the branch network. I show that, even in crowded markets, closings can have large effects on local credit supply. To generate plausibly exogenous variation in the incidence of closings, I use Census tract level data paired with a novel identification strategy that exploits within-county variation in exposure to post-merger consolidation. This instrument identifies the effect of closings that occur in close proximity to other branches. I find that closings have a prolonged negative impact on credit supply to local small businesses, but only a temporary effect on local mortgage lending. The number of new small business loans is 13% lower for several years, and this decline persists even after the entry of new banks. The decline in lending is highly localized, dissipating 8 miles out, and is concentrated in low-income and high-minority neighborhoods. These results show closings have large effects on local credit supply when lending is information-intensive and lender-specific relationships are difficult to replace. The second chapter (co-authored with Michael Greenstone and Alexandre Mas) estimates the effect of the reduction in credit supply that followed the 2008 financial crisis on the real economy. We predict county lending shocks using variation in pre-crisis bank market shares and estimated bank supply-shifts. Counties with negative predicted shocks experienced declines in small business loan originations, indicating that it is costly for these businesses to find new lenders. Using confidential microdata from the Longitudinal Business Database, we find that the 2007-2009 lending shocks accounted for statistically significant, but economically small, declines in both small firm and overall employment. Predicted lending shocks affected lending but not employment from 1997-2007. The third chapter uses a cash demand framework to model household credit decisions when there are both fixed and marginal costs associated with borrowing. In standard models of credit demand, the price associ­ ated with a loan is simply the interest rate. In reality, however, loan contracts encompass many dimensions that contribute to the effective price a household pays to borrow. Understanding how these other factors influence households' credit decisions is important for evaluating the impact of policy on household credit demand. I show, using data from Thailand, that the cash demand model matches many observed patterns of household behavior while providing a framework for understanding how tradeoffs between different costs drive borrowing decisions. Thesis Supervisor: Michael Greenstone Title: Milton Friedman Professor of Economics, University of Chicago Thesis Supervisor: Robert M. Townsend Title: Elizabeth & James Killian Professor of Economics 3 Contents Acknowledgements 7 List of Tables 9 List of Figures 11 1 Do Bank Branches Still Matter? The Effect of Closings on Local Economic Outcomes 13 1.1 Introduction . 13 1.2 Data 16 1.3 Identification and Empirical Framework 18 1.3.1 External Validity 21 1.4 Results . 21 1.4.1 Exposure to Consolidation and Branch Closings . 21 1.4.2 Closings and Local Credit Supply 22 1.4.2.1 Alternative Explanations 24 1.4.2.2 Varying the Size of the Local Banking Market 25 1.4.3 Heterogeneity Across Borrowers 25 1.4.4 Geographic Spillovers 27 1.4.5 Real Economic Effects 27 1.5 Welfare Implications 29 1.6 Conclusion 31 Figures 33 Tables . 39 4 2 Do Credit Market Shocks Affect the Real Economy? Quasi-Experimental Evidence from the Great Recession and 'Normal' Economic Times 46 2.1 Introduction . 46 2.2 Background . 49 2.3 Data Sources 50 2. 4 Research Design 52 2.4.1 Isolating Supply Shocks in Lending . 52 2.4.2 Summary of the Predicted Supply Shock . 54 2.5 Econometric Models and Results ........ 55 2.5.1 The Relationship Between the Predicted Lending Shock and Actual Loan Originations 55 2.5.2 The Relationship Between the Predicted Lending Shocks and Economic Activity Dur- ing the Great Recession . 58 2.5.2.1 Small Standalone Firms . 58 2.5.2.2 Small Establishments in Multi-Unit Firms 58 2.5.2.3 County-Level Economic Outcomes ..... 59 2.5.3 The Role of Small Business Loans in "Normal" Economic Times. 60 2.6 Interpretation 61 2. 7 Conclusion 63 Figures 65 Tables . 68 3 Credit is Cash: A Model of Household Borrowing 77 3.1 Introduction . 77 3.2 Household Credit in Thailand 79 3.2.1 Data ..... 79 3.2.2 Loan Products 80 3.2.3 Household Borrowing Patterns 82 3.3 Credit Demand as Cash Demand 83 3.3.1 Model .......... 84 5 3.3.2 Simulations 87 3.4 Discrete Choice 88 3.5 Conclusion 90 Figures 91 Tables . 94 References 99 Appendices for Chapter 1 106 Appendix Figures 112 Appendix Tables 115 Appendices for Chapter 2 121 Appendix Figures 125 Appendix Tables 127 6 Acknowledgements One of the greatest pleasures of finishing my Ph.D. is having the opportunity to acknowledge and give thanks to all the individuals who helped me along the way. I have been extremely touched and humbled by their support, and I hope I am able to do them justice in these few paragraphs. I have had many occasions to be thankful that Michael Greenstone was the thesis writers' registration officer in my third year. I used his initial flicker of interest in my research as fodder for so many meetings that he was eventually forced to ask if he had become my advisor. Michael has been a mentor in the truest sense of the word, and I am especially grateful that he steered me firmly back on track the spring before my job market year. I would be in a very different place were it not for him. Rob Townsend reached out to me while I was still a prospective student, and has guided me with the same warmth and generosity ever since. His encouragement and enthusiasm gave me the confidence I needed when starting on my own work, and yet he never shied from challenging me to go in directions I would not have otherwise considered. Our conversations have been an invaluable part of my time at MIT. I am also deeply indebted to the rest of the MIT Economics faculty, whose dedication to supporting their graduate students is truly unrivaled. I am especially thankful to the development faculty, who continued to welcome me as part of their community even as my research drifted farther and farther afield. I particularly thank Abhijit Banerjee, whose comments during my seminars always baffled me until I'd had sufficient time to think about them and realize that he was right, and Ben Olken, especially for his support during my job market year. When I returned to MIT for grad school, everyone told me that the biggest benefit would be my peer group. However, it is only now, at the end, that I am able to step back and truly appreciate how lucky I've been to be a part of this community. The students I've met here have been simultaneously the most brilliant and the most humble individuals I've had the privilege to work with. While I am grateful to many, three deserve special mention. Adrien Auclert and I cemented our friendship over long sessions at the squash courts, which provided a much-needed break and a chance to vent about the stresses of grad school. He was also unfailingly generous with his time and expertise on the numerous occasions I was instructed to "write a model" and had no idea where to begin. Adam Sacarny and I share the bond unique to New York Fed RAs who are scheduled for their pre-employment drug screening on the same day. He has been extremely tolerant of my continued promise to invite him over for pho... someday. Finally, Manasi Deshpande was the first person I met from our cohort and she has been my strongest support ever since. For me, she is the one person who best epitomizes that combination of brilliance and graciousness, and I cannot imagine what grad school would have been without her. The MIT Economics department is much more than just its faculty and students, and I am very thankful to the support staff who power it everyday.
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