The Roles of Corporate Governance in Bank Failures During the Recent Financial Crisis. Online Appendix
|
|
- Kevin Dorsey
- 5 years ago
- Views:
Transcription
1 1 The Roles of Corporate Governance in Bank Failures During the Recent Financial Crisis Berger, Allen N. 1 Imbierowicz, Björn 2 Rauch, Christian 3 Online Appendix 1 Corresponding author. University of South Carolina, Moore School of Business, 1014 Greene Street, Columbia, SC, USA, Phone: , Wharton Financial Institutions Center, and European Banking Center, aberger@moore.sc.edu 2 Copenhagen Business School, Finance Department and Center for Financial Frictions (FRIC), Solbjerg Plads 3, 2000 Frederiksberg, Copenhagen, Denmark, bi.fi@cbs.dk 3 University of Oxford, Saïd Business School, Park End Street, Oxford, OX1 1 HP, United Kingdom, christian.rauch@sbs.ox.ac.uk
2 2 Online Appendix Table A1 Addition to Table 5 Regression Results This table reports in Panel A1 and A2, Model I in Panel B, and Panels C and D results from logit regressions of bankruptcy indicators on predictor variables. All variables are defined in Table 1. Robust standard errors are employed and clustered at the bank level. Model II in Panel B shows results of a probit regression model with sample selection following Heckman (1979) and includes standard errors derived via the Huber (1967) White (1980) sandwich estimator, clustered at the bank level. The selection equation is Corporate Governance Data available = α + β 1*ln(Assets) + β 2*(ln(Assets)) 2 + β 3*Real Estate Loans + β 5*Cumulative Operating Income from 2004:Q1- + β 5*Agricultural Loans + β 6*Commercial Loans + β 7*Individual Loans+ β 8*Public Bank + β 9*Multibank Holding Company + β 10*OCC + β 11*FED, where the operating income and the loan variables are employed relative to a bank s total assets and total loans, respectively. We also report the results for the Wald test of no sample selection bias, i.e. the p-value for the null of no correlation between the errors of the selection equation and the regression model. SIFIs (systemically important financial institutions) in Panel C are defined as banks with assets larger than $50bn. in at least one quarter in our time period. The statistical significance of results is indicated by * = 10% level, ** = 5% level and *** = 1% level. Panel A1: Variation of Specifications in Panel A Total Assets ($-Thd.) I II 1 Year 2 Years 1 Year 2 Years Outside Directors CEO Other higher-level Mgmt * 7.044*** ** Lower-level Mgmt ** 2.508*** 4.657*** Outside Directors CEO Other higher-level Mgmt Lower-level Mgmt Other TARP Public Bank 1.689*** 1.565*** 1.911*** Multibank Holding Company Outside Directors/Board Higher-level Mgmt./Board Lower-level Mgmt./Board log(board Size) ** ** Chairman is CEO ** ** * log(assets) ** * ** * * Capital Ratio *** *** 5.737** Total Loans excl. C&D/Assets ** * C&D Loans/Assets 8.054*** *** *** 5.607** 9.473*** *** Loan Concentration ** * ST Deposits/Assets ** ** *** ** Brokered Deposits/Assets E Return on Assets *** *** * *** ** ** Non-perform. Loans/Assets ** * *** *** * Loan Growth *** ** *** * MBS/Assets * Unused Commitm./Assets * *** * Constant *** Observations 5,804 5, ,201 3, Number of Defaults McFadden's adjusted Pseudo R-squared 36.6% 19.1% 47.1% 39.6% 21.9% 53.9%
3 Panel A2: Variation of Specifications in Panel A Total Assets ($-Thd.) Stock & Awards / Total Bonus / Total 3 III IV 1 Year 2 Years 1 Year 2 Years Outside Directors ** CEO Other higher-level Mgmt ** 7.265*** ** 0.791* 7.068*** * Lower-level Mgmt *** 2.440*** 6.172*** 2.790*** 2.105** 9.903** Outside Directors CEO Other higher-level Mgmt Lower-level Mgmt ** Other TARP ** Public Bank 1.737*** 1.623*** 2.343*** ** 3.137*** Multibank Holding Company Variable Variables Outside Directors * CEO Other higher-level Mgmt Lower-level Mgmt ** CEO Other higher-level Mgmt ** * Lower-level Mgmt * *** Outside Directors/Board Higher-level Mgmt./Board *** Lower-level Mgmt./Board log(board Size) ** ** Chairman is CEO ** ** * * ** * log(assets) ** ** * * Capital Ratio *** 5.118* ** Total Loans excl. C&D/Assets * C&D Loans/Assets 4.893** 9.481*** *** *** *** Loan Concentration ST Deposits/Assets *** ** *** Brokered Deposits/Assets ** Return on Assets *** *** * *** ** ** Non-perform. Loans/Assets *** *** *** ** Loan Growth *** *** *** MBS/Assets Unused Commitm./Assets * * ** 9.104** Local Market Power * (Local Market Power) Comps.' Subprime Exposure *** House Price Inflation *** %-Change in GDP *** OCC 1.195** 0.927* FED Constant 3.824*** * Observations 4,201 3, ,290 3, Number of Defaults McFadden's adjusted Pseudo R-squared 38.7% 21.4% 54.5% 41.5% 25.8% 52.3%
4 Panel B: Full Specification of Panel B log ($- Ownership) log ($- Holdings) Stock & Awards / Total Bonus / Total 4 I II Heckman Selection Model 1 Year 2 Years 1 Year 2 Years Outside Directors CEO ** Other higher-level Mgmt * 0.097** 0.719*** 0.027* 0.037** 0.281*** Lower-level Mgmt ** 0.066* 0.128** 0.052** 0.023** 0.015*** Outside Directors 0.284*** 0.263** 0.303* 0.090* 0.110*** CEO * ** Other higher-level Mgmt * Lower-level Mgmt * Other TARP *** Public Bank *** 1.316*** 0.793* 3.072*** Multibank Holding Company 1.312*** 1.153** 5.397*** 0.504** 0.485** 2.293** Variable Variables Outside Directors 2.686* ** 0.843* CEO ** Other higher-level Mgmt Lower-level Mgmt * CEO Other higher-level Mgmt Lower-level Mgmt *** ** Outside Directors/Board Higher-level Mgmt./Board *** *** Lower-level Mgmt./Board log(board Size) * ** Chairman is CEO ** ** ** ** ** ** log(assets) Capital Ratio *** ** ** ** Total Loans excl. C&D/Assets C&D Loans/Assets *** *** *** *** Loan Concentration * ** ST Deposits/Assets *** *** * Brokered Deposits/Assets 5.078** *** Return on Assets *** *** ** * *** Non-perform. Loans/Assets *** *** 6.520* *** Loan Growth *** * *** *** MBS/Assets * Unused Commitm./Assets ** ** Local Market Power ** ** *** * (Local Market Power) ** * 9.604** ** Comps.' Subprime Exposure ** * *** ** House Price Inflation *** * *** * %-Change in GDP *** *** OCC 1.346*** 1.376** 3.205* 0.599*** 0.617*** 1.388** FED ** * Constant * *** Observations 3,290 3, ,586 78,319 4,198 Censored Observations 75,296 75,222 4,006 Uncensored Observations 3,290 3, Number of Defaults McFadden's adj. Pseudo R-squared: Wald test of indep. eqns. (rho = 0): 40.5% 26.8% 52.5% 45.06% 33.73% 56.38%
5 Panel C1: Robustness Tests Total Assets ($-Thd.) Stock & Awards / Total Bonus / Total 5 II. Excluding Multibank III. Excluding Banks I. Excluding SIFIs Holding Companies which received TARP 1 Year 2 Years 1 Year 2 Years 1 Year 2 Years Outside Directors ** ** ** CEO Other higher-level Mgmt * 6.914*** * 0.312** 8.617*** 1.101** 6.187*** Lower-level Mgmt *** 2.122** *** 4.160*** 1.413** 2.476** 2.300** Outside Directors ** CEO Other higher-level Mgmt Lower-level Mgmt * Other TARP ** * Public Bank ** 4.641*** Multibank Holding Company Variable Variables Outside Directors 2.930* ** 4.073** CEO Other higher-level Mgmt Lower-level Mgmt CEO * *** Other higher-level Mgmt Lower-level Mgmt *** Outside Directors/Board Higher-level Mgmt./Board *** Lower-level Mgmt./Board * ** log(board Size) Chairman is CEO * * * * ** log(assets) * Capital Ratio *** *** ** Total Loans excl. C&D/Assets C&D Loans/Assets *** *** *** *** Loan Concentration ST Deposits/Assets *** *** ** *** * Brokered Deposits/Assets 4.869** * 7.175*** * Return on Assets *** ** *** *** ** ** *** Non-perform. Loans/Assets ** * ** *** Loan Growth *** *** *** MBS/Assets Unused Commitm./Assets ** ** ** * ** Local Market Power * (Local Market Power) Comps.' Subprime Exposure *** *** *** House Price Inflation *** *** *** %-Change in GDP *** *** *** OCC 1.188** 0.947* ** 0.952* 1.239** 1.184** FED ** Constant 8.693* * ** Observations 3,143 2, ,849 2,696 2,162 2,016 McFadden's adj. Pseudo-R2 41.0% 25.2% 53.0% 42.8% 25.3% 38.0% 23.4%
6 Panel C2: Robustness Tests Total Assets ($-Thd.) Stock & Awards / Total Bonus / Total 6 IV. All Commercial Banks V. Parsimonious Model VI. Including Accounting Information from 2004:Q1-1 Year 2 Years 1 Year 2 Years 1 Year 2 Years Outside Directors ** * CEO Other higher-level Mgmt ** 6.793*** *** 0.319* 7.496*** Lower-level Mgmt *** 2.025** 5.592*** 2.346** 2.401** Outside Directors * CEO Other higher-level Mgmt Lower-level Mgmt Other TARP ** ** Public Bank ** 2.598*** * Multibank Holding Company Variable Variables Outside Directors * CEO Other higher-level Mgmt Lower-level Mgmt CEO Other higher-level Mgmt * Lower-level Mgmt *** Outside Directors/Board Higher-level Mgmt./Board 1.072* *** Lower-level Mgmt./Board 1.412* log(board Size) Chairman is CEO ** ** * log(assets) *** *** *** ** *** Capital Ratio *** *** ** *** Total Loans excl. C&D/Assets C&D Loans/Assets 7.906*** 9.635*** *** 3.706*** 8.654*** *** *** Loan Concentration ST Deposits/Assets *** *** *** *** * *** ** Brokered Deposits/Assets * 4.253** * Return on Assets ** ** *** *** ** * *** *** Non-perform. Loans/Assets *** ** ** *** Loan Growth *** 5.495*** *** *** *** MBS/Assets Unused Commitm./Assets 0.562** 0.205** 0.470*** ** ** ** Local Market Power * ** (Local Market Power) ** ** Comps.' Subprime Exposure *** * *** *** *** House Price Inflation *** *** *** *** %-Change in GDP *** *** *** *** OCC 0.586** 0.579*** 0.496* 0.879** 0.678* ** 1.601*** FED Constant 4.381** ** * Observations 39,274 38,576 2,154 3,290 3, ,290 3,097 Number of Defaults McFadden's adj. Pseudo-R2 40.5% 28.2% 41.4% 45.20% 29.80% 60.00% 40.8% 25.9%
7 Panel D: Holdings Normalization and Excluding Variable Stock & Awards / Total Bonus / Total 7 I II 1 Year 2 Years 1 Year 2 Years Outside Directors ** ** CEO Other higher-level Mgmt * 7.516*** ** 1.377** 7.560*** ** Lower-level Mgmt *** 2.019* 9.019** 2.771*** 1.969** 4.317*** Outside Directors CEO Other higher-level Mgmt Lower-level Mgmt Other TARP ** ** Public Bank * 2.265*** * 1.633** Multibank Holding Company Variable Variables Outside Directors 3.065* CEO Other higher-level Mgmt Lower-level Mgmt CEO Other higher-level Mgmt Lower-level Mgmt ** Outside Directors/Board Higher-level Mgmt./Board ** ** Lower-level Mgmt./Board log(board Size) Chairman is CEO * * log(assets) Capital Ratio ** *** Total Loans excl. C&D/Assets C&D Loans/Assets *** *** *** *** Loan Concentration * ST Deposits/Assets *** *** Brokered Deposits/Assets 4.746** ** Return on Assets *** ** * *** ** * Non-perform. Loans/Assets *** ** *** ** Loan Growth *** ** MBS/Assets Unused Commitm./Assets * ** 8.174* ** ** Local Market Power * * (Local Market Power) * Comps.' Subprime Exposure *** *** House Price Inflation *** *** %-Change in GDP *** *** OCC 1.180** 0.894* ** 0.799* 1.336* FED Constant 7.972* * Observations 3,290 3, ,290 3, Number of Defaults McFadden's adj. Pseudo-R2 41.4% 26.0% 51.8% 42.9% 27.5% 52.2%
8 8 Online Appendix Table A2 Addition to Table 7 Regression Results for Accounting Measures of Bank Risk This table reports results for measures of bank risk using data from 2004:Q1 to 2010:Q3. The measures are the capital ratio, non-performing loans to total assets, the return on assets (RoA), all defined as in Table 1, as well as the non-interest income to total assets as reported on the balance sheet and the natural logarithm of the Z- score. The natural logarithm of the Z-score is defined as the sum of the capital ratio and the RoA divided by the standard deviation of the RoA over the previous 8 quarters. All Panels report cross-sectional regression results of risk measures on control variables measured in. To account for potential endogeneity we also show specifications excluding in Panel A the capital ratio, in Panel B Non-perform. Loans/Assets, in Panel C the capital ratio and the return on assets, and in Panel D the return on assets. For the derivation of the respective dependent variables at the bank-level we use the period 2007:Q1 to 2010:Q3 and in Panels B1 and B3 quarterly differences of the Capital Ratio and the natural logarithm of the Z-score, respectively, where all other panels use quarterly data of non-performing loans to total assets, the return on assets and non-interest income to total assets, respectively. For the kurtosis we use the excess kurtosis. Standard errors are robust to heteroscedasticity and statistical significances indicated by * = 10% level, ** = 5% level and *** = 1%.
9 Panel A: Capital Ratio Dependent Variable from 2007:Q1 to 2010:Q3 Mean St. Dev. Skew Kurtosis Minimum Independent Variables I II III IV V VI VII VIII IX X Total Assets ($-Thd.) 9 Outside Directors ** ** ** CEO Other higher-level Mgmt *** *** * * 7.502*** 7.711*** ** * Lower-level Mgmt * * Outside Directors CEO Other higher-level Mgmt Lower-level Mgmt * 0.984* Other Public Bank ** *** * Multibank Holding Company ** *** 0.003** 0.004** * ** * ** *** Outside Directors/Board 0.059** Higher-level Mgmt./Board ** 0.003* 0.004** ** 1.912** * ** Lower-level Mgmt./Board * * log(board Size) * Chairman is CEO ** 0.653** log(assets) 0.007*** 0.010*** * 0.277* Capital Ratio *** 0.041*** ** *** Total Loans excl. C&D/Assets * * C&D Loans/Assets *** ** 0.013** 0.011** * *** ** Loan Concentration ST Deposits/Assets Brokered Deposits/Assets Return on Assets 0.649** *** *** Non-perform. Loans/Assets Loan Growth ** ** MBS/Assets ** ** Unused Commitm./Assets Local Market Power ** ** * 0.086** (Local Market Power) * 0.046* * Comps.' Subprime Exposure ** House Price Inflation * %-Change in GDP OCC FED * 0.002** * * Constant *** ** ** Observations Adjusted R-Squared
10 10 Panel B: Non-performing Loans / Total Assets Dependent Variable from 2007:Q1 to 2010:Q3 Mean St. Dev. Skew Kurtosis Maximum Independent Variables I II III IV V VI VII VIII IX X Total Assets ($-Thd.) Outside Directors 0.370*** 0.373*** 0.019*** 0.019*** *** 0.056*** CEO * * Other higher-level Mgmt ** 0.768*** 0.050** 0.050** * 0.107* Lower-level Mgmt * 1.559* Outside Directors *** 2.299*** 4.360*** 4.389*** CEO Other higher-level Mgmt Lower-level Mgmt ** 0.621** Other Public Bank ** 0.003** ** 0.009** Multibank Holding Company * 0.014* Outside Directors/Board Higher-level Mgmt./Board Lower-level Mgmt./Board log(board Size) Chairman is CEO log(assets) Capital Ratio 0.940*** 0.919*** 0.088*** 0.088*** *** 0.214*** Total Loans excl. C&D/Assets ** C&D Loans/Assets 1.171*** 1.226*** 0.114*** 0.115*** * *** 0.310*** Loan Concentration ST Deposits/Assets * 0.015* ** 0.047** Brokered Deposits/Assets Return on Assets * ** ** ** ** Non-perform. Loans/Assets 6.337** ** Loan Growth MBS/Assets Unused Commitm./Assets Local Market Power (Local Market Power) Comps.' Subprime Exposure * * House Price Inflation * * %-Change in GDP OCC * 0.009* FED Constant *** 4.682*** Observations Adjusted R-Squared
11 11 Panel C: Ln(Z-Score) Dependent Variable from 2007:Q1 to 2010:Q3 Mean St. Dev. Skew Kurtosis Minimum Independent Variables I II III IV V VI VII VIII IX X Total Assets ($-Thd.) Outside Directors * * CEO * * Other higher-level Mgmt Lower-level Mgmt * * * 0.570** Outside Directors 0.164** 0.180** * ** * 0.293** 0.074* 0.082* CEO * Other higher-level Mgmt Lower-level Mgmt Other Public Bank Multibank Holding Company Outside Directors/Board *** 1.885*** Higher-level Mgmt./Board *** *** 0.203** 0.181* ** ** Lower-level Mgmt./Board log(board Size) Chairman is CEO * 0.323* log(assets) Capital Ratio * Total Loans excl. C&D/Assets C&D Loans/Assets *** *** 1.016*** 0.837*** * *** *** Loan Concentration ** ** ST Deposits/Assets ** * Brokered Deposits/Assets Return on Assets *** *** * *** Non-perform. Loans/Assets * Loan Growth * 0.581* 0.915** ** 3.693** ** MBS/Assets ** ** 1.369* 1.448* Unused Commitm./Assets Local Market Power (Local Market Power) Comps.' Subprime Exposure House Price Inflation %-Change in GDP OCC ** ** ** ** FED *** ** 0.120** 0.109** * * 0.820* ** ** Constant ** 6.900** Observations Adjusted R-Squared
12 12 Panel D: Return on Assets Dependent Variable from 2007:Q1 to 2010:Q3 Mean St. Dev. Skew Kurtosis Minimum Independent Variables I II III IV V VI VII VIII IX X Total Assets ($-Thd.) Outside Directors CEO Other higher-level Mgmt *** *** 0.036** 0.036** ** ** 2.854* 2.872* ** *** Lower-level Mgmt Outside Directors ** 0.017** * CEO Other higher-level Mgmt Lower-level Mgmt * * Other Public Bank ** ** 0.002* 0.002* * * Multibank Holding Company Outside Directors/Board Higher-level Mgmt./Board * * Lower-level Mgmt./Board log(board Size) Chairman is CEO ** * 0.264* 0.281** * 0.009* log(assets) Capital Ratio *** *** 0.075** 0.074** ** ** 7.179* 7.228* *** *** Total Loans excl. C&D/Assets C&D Loans/Assets *** *** 0.042*** 0.043*** ** ** *** *** Loan Concentration ST Deposits/Assets Brokered Deposits/Assets Return on Assets 3.840*** Non-perform. Loans/Assets * * Loan Growth MBS/Assets Unused Commitm./Assets * 0.006* * Local Market Power (Local Market Power) Comps.' Subprime Exposure House Price Inflation %-Change in GDP ** ** OCC * FED ** * * Constant * 4.693* Observations Adjusted R-Squared
13 13 Panel E: Non-Interest Income / Total Assets Mean St. Dev. Skew Kurtosis Minimum Independent Variables I II III IV V Outside Directors * * CEO Other higher-level Mgmt * Lower-level Mgmt ** 0.093** Total Assets ($-Thd.) Outside Directors * CEO Other higher-level Mgmt Lower-level Mgmt ** ** Other Public Bank Multibank Holding Company 0.025* Outside Directors/Board ** ** Higher-level Mgmt./Board * *** Lower-level Mgmt./Board * log(board Size) ** * Chairman is CEO * log(assets) 0.011*** * Capital Ratio Total Loans excl. C&D/Assets *** * C&D Loans/Assets *** * * *** Loan Concentration ST Deposits/Assets Brokered Deposits/Assets Return on Assets 1.867* 0.223* ** Non-perform. Loans/Assets * Loan Growth MBS/Assets *** * * Unused Commitm./Assets Local Market Power (Local Market Power) Comps.' Subprime Exposure House Price Inflation %-Change in GDP OCC ** ** FED Constant 0.171** 0.011** ** Observations Adjusted R-Squared
Analyzing the Determinants of Project Success: A Probit Regression Approach
2016 Annual Evaluation Review, Linked Document D 1 Analyzing the Determinants of Project Success: A Probit Regression Approach 1. This regression analysis aims to ascertain the factors that determine development
More information1. Logit and Linear Probability Models
INTERNET APPENDIX 1. Logit and Linear Probability Models Table 1 Leverage and the Likelihood of a Union Strike (Logit Models) This table presents estimation results of logit models of union strikes during
More informationInternet Appendix to Credit Default Swaps, Exacting Creditors and Corporate Liquidity Management
Internet Appendix to Credit Default Swaps, Exacting Creditors and Corporate Liquidity Management (not to be included for publication) Table A1 Probability of Credit Default Swaps Trading This table presents
More informationARCH Models and Financial Applications
Christian Gourieroux ARCH Models and Financial Applications With 26 Figures Springer Contents 1 Introduction 1 1.1 The Development of ARCH Models 1 1.2 Book Content 4 2 Linear and Nonlinear Processes 5
More informationEC327: Limited Dependent Variables and Sample Selection Binomial probit: probit
EC327: Limited Dependent Variables and Sample Selection Binomial probit: probit. summarize work age married children education Variable Obs Mean Std. Dev. Min Max work 2000.6715.4697852 0 1 age 2000 36.208
More informationThe Role of Credit Ratings in the. Dynamic Tradeoff Model. Viktoriya Staneva*
The Role of Credit Ratings in the Dynamic Tradeoff Model Viktoriya Staneva* This study examines what costs and benefits of debt are most important to the determination of the optimal capital structure.
More informationQuantitative Techniques Term 2
Quantitative Techniques Term 2 Laboratory 7 2 March 2006 Overview The objective of this lab is to: Estimate a cost function for a panel of firms; Calculate returns to scale; Introduce the command cluster
More informationStronger Risk Controls, Lower Risk: Evidence from U.S. Bank Holding Companies
Stronger Risk Controls, Lower Risk: Evidence from U.S. Bank Holding Companies Andrew Ellul 1 Vijay Yerramilli 2 1 Kelley School of Business, Indiana University 2 C. T. Bauer College of Business, University
More informationCitation for published version (APA): Shehzad, C. T. (2009). Panel studies on bank risks and crises Groningen: University of Groningen
University of Groningen Panel studies on bank risks and crises Shehzad, Choudhry Tanveer IMPORTANT NOTE: You are advised to consult the publisher's version (publisher's PDF) if you wish to cite from it.
More informationStronger Risk Controls, Lower Risk: Evidence from U.S. Bank Holding Companies
Stronger Risk Controls, Lower Risk: Evidence from U.S. Bank Holding Companies Andrew Ellul 1 Vijay Yerramilli 2 1 Kelley School of Business, Indiana University 2 C. T. Bauer College of Business, University
More informationLong and Short Run Correlation Risk in Stock Returns
Long and Short Run Correlation Risk in Stock Returns Discussion by Ric Colacito Econometric Society Winter Meetings, Denver, 1/2011 1 / 10 Contribution 1 Background: market variance risk premium predicts
More informationImport Competition and Household Debt
Import Competition and Household Debt Barrot (MIT) Plosser (NY Fed) Loualiche (MIT) Sauvagnat (Bocconi) USC Spring 2017 The views expressed in this paper are those of the authors and do not necessarily
More informationONLINE APPENDIX: INTERNAL SOCIAL CAPITAL AND THE ATTRACTION OF EARLY CONTRIBUTIONS IN CROWDFUNDING
ONLINE APPENDIX: INTERNAL SOCIAL CAPITAL AND THE ATTRACTION OF EARLY CONTRIBUTIONS IN CROWDFUNDING Massimo G. Colombo Chiara Franzoni Cristina Rossi-Lamastra School of Management, Politecnico di Milano,
More informationBanking sector concentration, competition, and financial stability: The case of the Baltic countries. Juan Carlos Cuestas
Banking sector concentration, competition, and financial stability: The case of the Baltic countries Juan Carlos Cuestas Eesti Pank, Estonia (with Yannick Lucotte & Nicolas Reigl) Prishtina, 14th November
More informationSources of Financing in Different Forms of Corporate Liquidity and the Performance of M&As
Sources of Financing in Different Forms of Corporate Liquidity and the Performance of M&As Zhenxu Tong * University of Exeter Jian Liu ** University of Exeter This draft: August 2016 Abstract We examine
More informationCHAPTER 11 Regression with a Binary Dependent Variable. Kazu Matsuda IBEC PHBU 430 Econometrics
CHAPTER 11 Regression with a Binary Dependent Variable Kazu Matsuda IBEC PHBU 430 Econometrics Mortgage Application Example Two people, identical but for their race, walk into a bank and apply for a mortgage,
More informationAdditional Case Study One: Risk Analysis of Home Purchase
Additional Case Study One: Risk Analysis of Home Purchase This case study focuses on assessing the risk of housing investment. The key point is that standard deviation and covariance analysis can be effectively
More informationData Appendix. A.1. The 2007 survey
Data Appendix A.1. The 2007 survey The survey data used draw on a sample of Italian clients of a large Italian bank. The survey was conducted between June and September 2007 and elicited detailed financial
More informationPhd Program in Transportation. Transport Demand Modeling. Session 11
Phd Program in Transportation Transport Demand Modeling João de Abreu e Silva Session 11 Binary and Ordered Choice Models Phd in Transportation / Transport Demand Modelling 1/26 Heterocedasticity Homoscedasticity
More informationMethods for A Time Series Approach to Estimating Excess Mortality Rates in Puerto Rico, Post Maria 1 Menzie Chinn 2 August 10, 2018 Procedure:
Methods for A Time Series Approach to Estimating Excess Mortality Rates in Puerto Rico, Post Maria 1 Menzie Chinn 2 August 10, 2018 Procedure: Estimate relationship between mortality as recorded and population
More informationThe Run for Safety: Financial Fragility and Deposit Insurance
The Run for Safety: Financial Fragility and Deposit Insurance Rajkamal Iyer- Imperial College, CEPR Thais Jensen- Univ of Copenhagen Niels Johannesen- Univ of Copenhagen Adam Sheridan- Univ of Copenhagen
More informationRETURNS AND VOLATILITY SPILLOVERS IN BRIC (BRAZIL, RUSSIA, INDIA, CHINA), EUROPE AND USA
RETURNS AND VOLATILITY SPILLOVERS IN BRIC (BRAZIL, RUSSIA, INDIA, CHINA), EUROPE AND USA Burhan F. Yavas, College of Business Administrations and Public Policy California State University Dominguez Hills
More informationVolume 37, Issue 2. Relation between Executive Compensation and Performance: Evidence from Japanese Shinkin Banks
Volume 37, Issue 2 Relation between Executive Compensation and Performance: Evidence from Japanese Shinkin Banks Hideaki Sakawa Graduate School of Economics, Nagoya City University Naoki Watanabel Graduate
More informationLiquidity Risk and Bank Stock Returns. June 16, 2017
Liquidity Risk and Bank Stock Returns Yasser Boualam (UNC) Anna Cororaton (UPenn) June 16, 2017 1 / 20 Motivation Recent financial crisis has highlighted liquidity mismatch on bank balance sheets Run on
More informationPASS Sample Size Software
Chapter 850 Introduction Cox proportional hazards regression models the relationship between the hazard function λ( t X ) time and k covariates using the following formula λ log λ ( t X ) ( t) 0 = β1 X1
More informationAppendixes Appendix 1 Data of Dependent Variables and Independent Variables Period
Appendixes Appendix 1 Data of Dependent Variables and Independent Variables Period 1-15 1 ROA INF KURS FG January 1,3,7 9 -,19 February 1,79,5 95 3,1 March 1,3,7 91,95 April 1,79,1 919,71 May 1,99,7 955
More informationFinancial Development and Economic Growth at Different Income Levels
1 Financial Development and Economic Growth at Different Income Levels Cody Kallen Washington University in St. Louis Honors Thesis in Economics Abstract This paper examines the effects of financial development
More informationSmall Sample Performance of Instrumental Variables Probit Estimators: A Monte Carlo Investigation
Small Sample Performance of Instrumental Variables Probit : A Monte Carlo Investigation July 31, 2008 LIML Newey Small Sample Performance? Goals Equations Regressors and Errors Parameters Reduced Form
More informationTable I Descriptive Statistics This table shows the breakdown of the eligible funds as at May 2011. AUM refers to assets under management. Panel A: Fund Breakdown Fund Count Vintage count Avg AUM US$ MM
More informationCorrecting for Survival Effects in Cross Section Wage Equations Using NBA Data
Correcting for Survival Effects in Cross Section Wage Equations Using NBA Data by Peter A Groothuis Professor Appalachian State University Boone, NC and James Richard Hill Professor Central Michigan University
More informationThe Reliability of Voluntary Disclosures: Evidence from Hedge Funds Internet Appendix
The Reliability of Voluntary Disclosures: Evidence from Hedge Funds Internet Appendix Appendix A The Consolidated Hedge Fund Database...2 Appendix B Strategy Mappings...3 Table A.1 Listing of Vintage Dates...4
More informationEmpirical Asset Pricing for Tactical Asset Allocation
Introduction Process Model Conclusion Department of Finance The University of Connecticut School of Business stephen.r.rush@gmail.com May 10, 2012 Background Portfolio Managers Want to justify fees with
More informationSTA 4504/5503 Sample questions for exam True-False questions.
STA 4504/5503 Sample questions for exam 2 1. True-False questions. (a) For General Social Survey data on Y = political ideology (categories liberal, moderate, conservative), X 1 = gender (1 = female, 0
More informationSupplemental Table I. WTO impact by industry
Supplemental Table I. WTO impact by industry This table presents the influence of WTO accessions on each three-digit NAICS code based industry for the manufacturing sector. The WTO impact is estimated
More informationAcemoglu, et al (2008) cast doubt on the robustness of the cross-country empirical relationship between income and democracy. They demonstrate that
Acemoglu, et al (2008) cast doubt on the robustness of the cross-country empirical relationship between income and democracy. They demonstrate that the strong positive correlation between income and democracy
More informationForecastability of petroleum investments on the NCS. Lorentzen & Osmundsen Petroleum investment 1 / 14
Forecastability of petroleum investments on the NCS Sindre Lorentzen University of Stavanger Norway - 4036 Stavanger sindre.lorentzen@uis.no Petter Osmundsen University of Stavanger Norway - 4036 Stavanger
More informationChapter 4 Level of Volatility in the Indian Stock Market
Chapter 4 Level of Volatility in the Indian Stock Market Measurement of volatility is an important issue in financial econometrics. The main reason for the prominent role that volatility plays in financial
More informationInternet Appendix: High Frequency Trading and Extreme Price Movements
Internet Appendix: High Frequency Trading and Extreme Price Movements This appendix includes two parts. First, it reports the results from the sample of EPMs defined as the 99.9 th percentile of raw returns.
More informationThe current study builds on previous research to estimate the regional gap in
Summary 1 The current study builds on previous research to estimate the regional gap in state funding assistance between municipalities in South NJ compared to similar municipalities in Central and North
More informationDeterminants of Revenue Generation Capacity in the Economy of Pakistan
2014, TextRoad Publication ISSN 2090-4304 Journal of Basic and Applied Scientific Research www.textroad.com Determinants of Revenue Generation Capacity in the Economy of Pakistan Khurram Ejaz Chandia 1,
More informationTable IA.1 CEO Pay-Size Elasticity and Increased Labor Demand Panel A: IPOs Scaled by Full Sample Industry Average
Table IA.1 CEO Pay-Size Elasticity and Increased Labor Demand Panel A: IPOs Scaled by Industry Average (1) (2) (3) (4) (5) Ln(Market Value) 0.423 0.419 0.423 0.423 0.255 (33.29) (30.84) (33.29) (33.29)
More informationGGraph. Males Only. Premium. Experience. GGraph. Gender. 1 0: R 2 Linear = : R 2 Linear = Page 1
GGraph 9 Gender : R Linear =.43 : R Linear =.769 8 7 6 5 4 3 5 5 Males Only GGraph Page R Linear =.43 R Loess 9 8 7 6 5 4 5 5 Explore Case Processing Summary Cases Valid Missing Total N Percent N Percent
More informationEconometric Methods for Valuation Analysis
Econometric Methods for Valuation Analysis Margarita Genius Dept of Economics M. Genius (Univ. of Crete) Econometric Methods for Valuation Analysis Cagliari, 2017 1 / 25 Outline We will consider econometric
More informationFinal Exam, section 1. Thursday, May hour, 30 minutes
San Francisco State University Michael Bar ECON 312 Spring 2018 Final Exam, section 1 Thursday, May 17 1 hour, 30 minutes Name: Instructions 1. This is closed book, closed notes exam. 2. You can use one
More informationAppendix A (Pornprasertmanit & Little, in press) Mathematical Proof
Appendix A (Pornprasertmanit & Little, in press) Mathematical Proof Definition We begin by defining notations that are needed for later sections. First, we define moment as the mean of a random variable
More informationa. Explain why the coefficients change in the observed direction when switching from OLS to Tobit estimation.
1. Using data from IRS Form 5500 filings by U.S. pension plans, I estimated a model of contributions to pension plans as ln(1 + c i ) = α 0 + U i α 1 + PD i α 2 + e i Where the subscript i indicates the
More informationReview questions for Multinomial Logit/Probit, Tobit, Heckit, Quantile Regressions
1. I estimated a multinomial logit model of employment behavior using data from the 2006 Current Population Survey. The three possible outcomes for a person are employed (outcome=1), unemployed (outcome=2)
More informationIn Search of Distress Risk
In Search of Distress Risk John Y. Campbell, Jens Hilscher, and Jan Szilagyi Presentation to Third Credit Risk Conference: Recent Advances in Credit Risk Research New York, 16 May 2006 What is financial
More informationOnline Appendix to R&D and the Incentives from Merger and Acquisition Activity *
Online Appendix to R&D and the Incentives from Merger and Acquisition Activity * Index Section 1: High bargaining power of the small firm Page 1 Section 2: Analysis of Multiple Small Firms and 1 Large
More informationGlobal Retail Lending in the Aftermath of the US Financial Crisis: Distinguishing between Supply and Demand Effects
Global Retail Lending in the Aftermath of the US Financial Crisis: Distinguishing between Supply and Demand Effects Manju Puri (Duke) Jörg Rocholl (ESMT) Sascha Steffen (Mannheim) 3rd Unicredit Group Conference
More informationMarket-based vs. accounting-based performance of banks in Asian emerging markets
Asian Journal of Business Research ISSN 1178-8933 Special Issue 2013 DOI 10.14707/ajbr.130014 Market-based vs. accounting-based performance of banks in Asian emerging markets Li Li School of Business,
More informationLAMPIRAN. Lampiran I
67 LAMPIRAN Lampiran I Data Volume Impor Jagung Indonesia, Harga Impor Jagung, Produksi Jagung Nasional, Nilai Tukar Rupiah/USD, Produk Domestik Bruto (PDB) per kapita Tahun Y X1 X2 X3 X4 1995 969193.394
More informationThe Effect of Lease Accounting on Credit Rating and Cost of Debt: Evidence from Firms in Korea
$ social sciences Article The Effect of Lease Accounting on Credit Rating and Cost of Debt: Evidence from Firms in Korea Younghee Park 1 and Kyunga Na 2, * 1 School of Smart Business, Yeungjin University,
More informationOil Price Effects on Exchange Rate and Price Level: The Case of South Korea
Oil Price Effects on Exchange Rate and Price Level: The Case of South Korea Mirzosaid SULTONOV 東北公益文科大学総合研究論集第 34 号抜刷 2018 年 7 月 30 日発行 研究論文 Oil Price Effects on Exchange Rate and Price Level: The Case
More informationDividend Payout and Executive Compensation: Theory and evidence from New Zealand
Dividend Payout and Executive Compensation: Theory and evidence from New Zealand Warwick Anderson University of Canterbury, Christchurch, New Zealand Nalinaksha Bhattacharyya University of Alaska Anchorage,
More informationThe histogram should resemble the uniform density, the mean should be close to 0.5, and the standard deviation should be close to 1/ 12 =
Chapter 19 Monte Carlo Valuation Question 19.1 The histogram should resemble the uniform density, the mean should be close to.5, and the standard deviation should be close to 1/ 1 =.887. Question 19. The
More informationInvestment Platforms Market Study Interim Report: Annex 7 Fund Discounts and Promotions
MS17/1.2: Annex 7 Market Study Investment Platforms Market Study Interim Report: Annex 7 Fund Discounts and Promotions July 2018 Annex 7: Introduction 1. There are several ways in which investment platforms
More informationDiscrete Choice Modeling William Greene Stern School of Business, New York University. Lab Session 2 Binary Choice Modeling with Panel Data
Discrete Choice Modeling William Greene Stern School of Business, New York University Lab Session 2 Binary Choice Modeling with Panel Data This assignment will extend the models of binary choice and ordered
More informationAPPENDIX FOR FIVE FACTS ABOUT BELIEFS AND PORTFOLIOS
APPENDIX FOR FIVE FACTS ABOUT BELIEFS AND PORTFOLIOS Stefano Giglio Matteo Maggiori Johannes Stroebel Steve Utkus A.1 RESPONSE RATES We next provide more details on the response rates to the GMS-Vanguard
More informationSTATISTICAL METHODS FOR CATEGORICAL DATA ANALYSIS
STATISTICAL METHODS FOR CATEGORICAL DATA ANALYSIS Daniel A. Powers Department of Sociology University of Texas at Austin YuXie Department of Sociology University of Michigan ACADEMIC PRESS An Imprint of
More informationtm / / / / / / / / / / / / Statistics/Data Analysis User: Klick Project: Limited Dependent Variables{space -6}
PS 4 Monday August 16 01:00:42 2010 Page 1 tm / / / / / / / / / / / / Statistics/Data Analysis User: Klick Project: Limited Dependent Variables{space -6} log: C:\web\PS4log.smcl log type: smcl opened on:
More informationRisk-Adjusted Futures and Intermeeting Moves
issn 1936-5330 Risk-Adjusted Futures and Intermeeting Moves Brent Bundick Federal Reserve Bank of Kansas City First Version: October 2007 This Version: June 2008 RWP 07-08 Abstract Piazzesi and Swanson
More informationAppendix. Table A.1 (Part A) The Author(s) 2015 G. Chakrabarti and C. Sen, Green Investing, SpringerBriefs in Finance, DOI /
Appendix Table A.1 (Part A) Dependent variable: probability of crisis (own) Method: ML binary probit (quadratic hill climbing) Included observations: 47 after adjustments Convergence achieved after 6 iterations
More informationGARCH Models. Instructor: G. William Schwert
APS 425 Fall 2015 GARCH Models Instructor: G. William Schwert 585-275-2470 schwert@schwert.ssb.rochester.edu Autocorrelated Heteroskedasticity Suppose you have regression residuals Mean = 0, not autocorrelated
More informationHow exogenous is exogenous income? A longitudinal study of lottery winners in the UK
How exogenous is exogenous income? A longitudinal study of lottery winners in the UK Dita Eckardt London School of Economics Nattavudh Powdthavee CEP, London School of Economics and MIASER, University
More informationTHE IMPACT OF BANKING RISKS ON THE CAPITAL OF COMMERCIAL BANKS IN LIBYA
THE IMPACT OF BANKING RISKS ON THE CAPITAL OF COMMERCIAL BANKS IN LIBYA Azeddin ARAB Kastamonu University, Turkey, Institute for Social Sciences, Department of Business Abstract: The objective of this
More informationYour Name (Please print) Did you agree to take the optional portion of the final exam Yes No. Directions
Your Name (Please print) Did you agree to take the optional portion of the final exam Yes No (Your online answer will be used to verify your response.) Directions There are two parts to the final exam.
More informationThe impact of CDS trading on the bond market: Evidence from Asia
Capital Market Research Forum 9/2554 By Dr. Ilhyock Shim Senior Economist Representative Office for Asia and the Pacific Bank for International Settlements 7 September 2011 The impact of CDS trading on
More informationOn-line Appendix: The Mutual Fund Holdings Database
Unexploited Gains from International Diversification: Patterns of Portfolio Holdings around the World Tatiana Didier, Roberto Rigobon, and Sergio L. Schmukler Review of Economics and Statistics, forthcoming
More informationInternet Appendix for: Change You Can Believe In? Hedge Fund Data Revisions
Internet Appendix for: Change You Can Believe In? Hedge Fund Data Revisions Andrew J. Patton, Tarun Ramadorai, Michael P. Streatfield 22 March 2013 Appendix A The Consolidated Hedge Fund Database... 2
More informationDoes Uniqueness in Banking Matter?
Does Uniqueness in Banking Matter? Frank Hong Liu a, Lars Norden b, and Fabrizio Spargoli c a Adam Smith Business School, University of Glasgow, UK b Brazilian School of Public and Business Administration,
More informationTransfer Pricing by Multinational Firms: New Evidence from Foreign Firm Ownership
Transfer Pricing by Multinational Firms: New Evidence from Foreign Firm Ownership Anca Cristea University of Oregon Daniel X. Nguyen University of Copenhagen Rocky Mountain Empirical Trade 16-18 May, 2014
More informationAppendix A. Mathematical Appendix
Appendix A. Mathematical Appendix Denote by Λ t the Lagrange multiplier attached to the capital accumulation equation. The optimal policy is characterized by the first order conditions: (1 α)a t K t α
More informationToo Big to Fail: Discussion of Quantifying Subsidies for SIFIs. Philip E. Strahan, Boston College & NBER. Minneapolis Fed.
Too Big to Fail: Discussion of Quantifying Subsidies for SIFIs Philip E. Strahan, Boston College & NBER Minneapolis Fed November 13 Distortions for TBTF borrowers Debt is too cheap for TBTF firms and not
More informationImpact of credit risk (NPLs) and capital on liquidity risk of Malaysian banks
Available online at www.icas.my International Conference on Accounting Studies (ICAS) 2015 Impact of credit risk (NPLs) and capital on liquidity risk of Malaysian banks Azlan Ali, Yaman Hajja *, Hafezali
More informationAnalysis of Microdata
Rainer Winkelmann Stefan Boes Analysis of Microdata Second Edition 4u Springer 1 Introduction 1 1.1 What Are Microdata? 1 1.2 Types of Microdata 4 1.2.1 Qualitative Data 4 1.2.2 Quantitative Data 6 1.3
More informationStock price synchronicity and the role of analyst: Do analysts generate firm-specific vs. market-wide information?
Stock price synchronicity and the role of analyst: Do analysts generate firm-specific vs. market-wide information? Yongsik Kim * Abstract This paper provides empirical evidence that analysts generate firm-specific
More informationIn Debt and Approaching Retirement: Claim Social Security or Work Longer?
AEA Papers and Proceedings 2018, 108: 401 406 https://doi.org/10.1257/pandp.20181116 In Debt and Approaching Retirement: Claim Social Security or Work Longer? By Barbara A. Butrica and Nadia S. Karamcheva*
More informationFAMILY OWNERSHIP CONCENTRATION AND FIRM PERFORMANCE: ARE SHAREHOLDERS REALLY BETTER OFF? Rama Seth IIM Calcutta
FAMILY OWNERSHIP CONCENTRATION AND FIRM PERFORMANCE: ARE SHAREHOLDERS REALLY BETTER OFF? Rama Seth IIM Calcutta INTRODUCTION The share of family firms contribution to global GDP is estimated to be in the
More informationFinancial Econometrics Jeffrey R. Russell. Midterm 2014 Suggested Solutions. TA: B. B. Deng
Financial Econometrics Jeffrey R. Russell Midterm 2014 Suggested Solutions TA: B. B. Deng Unless otherwise stated, e t is iid N(0,s 2 ) 1. (12 points) Consider the three series y1, y2, y3, and y4. Match
More informationDoes Competition in Banking explains Systemic Banking Crises?
Does Competition in Banking explains Systemic Banking Crises? Abstract: This paper examines the relation between competition in the banking sector and the financial stability on country level. Compared
More informationMANAGEMENT SCIENCE doi /mnsc ec
MANAGEMENT SCIENCE doi 10.1287/mnsc.1100.1159ec e-companion ONLY AVAILABLE IN ELECTRONIC FORM informs 2010 INFORMS Electronic Companion Quality Management and Job Quality: How the ISO 9001 Standard for
More informationInvestment, Financial Frictions and the Dynamic Effects of Monetary Policy
Investment, Financial Frictions and the Dynamic Effects of Monetary Policy James Cloyne Clodo Ferreira Maren Froemel Paolo Surico UC, Davis Bank of Spain London Business School & BoE ESCB Research Cluster
More informationOWNERSHIP STRUCTURE, CORPORATE PERFORMANCE AND FAILURE: EVIDENCE FROM PANEL DATA OF EMERGING MARKET THE CASE OF JORDAN
OWNERSHIP STRUCTURE, CORPORATE PERFORMANCE AND FAILURE: EVIDENCE FROM PANEL DATA OF EMERGING MARKET THE CASE OF JORDAN Rami Zeitun* Abstract This study investigate performance and failure in a panel estimation
More informationInput Tariffs, Speed of Contract Enforcement, and the Productivity of Firms in India
Input Tariffs, Speed of Contract Enforcement, and the Productivity of Firms in India Reshad N Ahsan University of Melbourne December, 2011 Reshad N Ahsan (University of Melbourne) December 2011 1 / 25
More informationFinal Exam, section 1. Tuesday, December hour, 30 minutes
San Francisco State University Michael Bar ECON 312 Fall 2018 Final Exam, section 1 Tuesday, December 18 1 hour, 30 minutes Name: Instructions 1. This is closed book, closed notes exam. 2. You can use
More informationDOES COMPENSATION AFFECT BANK PROFITABILITY? EVIDENCE FROM US BANKS
DOES COMPENSATION AFFECT BANK PROFITABILITY? EVIDENCE FROM US BANKS by PENGRU DONG Bachelor of Management and Organizational Studies University of Western Ontario, 2017 and NANXI ZHAO Bachelor of Commerce
More informationTable 1a (Robustness) Event study of stock returns surrounding announcements of Fortune ranking scores
Table 1a (Robustness) Event study of stock returns surrounding announcements of Fortune ranking scores This table presents cumulative abnormal returns (CARs) calculated over various intervals surrounding
More informationLiquidity in the Foreign Exchange Market: Measurement, Commonality, and Risk Premiums - Supplemental Appendix
Liquidity in the Foreign Exchange Market: Measurement, Commonality, and Risk Premiums - Supplemental Appendix Loriano Mancini Angelo Ranaldo Jan Wrampelmeyer Swiss Finance Institute Swiss National Bank
More informationCredit-Induced Boom and Bust
Credit-Induced Boom and Bust Marco Di Maggio (Columbia) and Amir Kermani (UC Berkeley) 10th CSEF-IGIER Symposium on Economics and Institutions June 25, 2014 Prof. Marco Di Maggio 1 Motivation The Great
More informationThe data definition file provided by the authors is reproduced below: Obs: 1500 home sales in Stockton, CA from Oct 1, 1996 to Nov 30, 1998
Economics 312 Sample Project Report Jeffrey Parker Introduction This project is based on Exercise 2.12 on page 81 of the Hill, Griffiths, and Lim text. It examines how the sale price of houses in Stockton,
More informationTHE PERSISTENCE OF UNEMPLOYMENT AMONG AUSTRALIAN MALES
THE PERSISTENCE OF UNEMPLOYMENT AMONG AUSTRALIAN MALES Abstract The persistence of unemployment for Australian men is investigated using the Household Income and Labour Dynamics Australia panel data for
More informationMonetary Economics Measuring Asset Returns. Gerald P. Dwyer Fall 2015
Monetary Economics Measuring Asset Returns Gerald P. Dwyer Fall 2015 WSJ Readings Readings this lecture, Cuthbertson Ch. 9 Readings next lecture, Cuthbertson, Chs. 10 13 Measuring Asset Returns Outline
More information(iii) Under equal cluster sampling, show that ( ) notations. (d) Attempt any four of the following:
Central University of Rajasthan Department of Statistics M.Sc./M.A. Statistics (Actuarial)-IV Semester End of Semester Examination, May-2012 MSTA 401: Sampling Techniques and Econometric Methods Max. Marks:
More informationVolatility Analysis of Nepalese Stock Market
The Journal of Nepalese Business Studies Vol. V No. 1 Dec. 008 Volatility Analysis of Nepalese Stock Market Surya Bahadur G.C. Abstract Modeling and forecasting volatility of capital markets has been important
More informationQuantitative Methods
THE ASSOCIATION OF BUSINESS EXECUTIVES DIPLOMA PART 2 QM Quantitative Methods afternoon 26 May 2004 1 Time allowed: 3 hours. 2 Answer any FOUR questions. 3 All questions carry 25 marks. Marks for subdivisions
More informationWe follow Agarwal, Driscoll, and Laibson (2012; henceforth, ADL) to estimate the optimal, (X2)
Online appendix: Optimal refinancing rate We follow Agarwal, Driscoll, and Laibson (2012; henceforth, ADL) to estimate the optimal refinance rate or, equivalently, the optimal refi rate differential. In
More informationFinancial Derivatives at Community Banks
Financial Derivatives at Community Banks Xuan (Shelly) Shen Quantitative Analyst, Regions Bank Valentina Hartarska Professor, Dept. Ag. Econ. & RS and Dept. of Finance, Auburn University Key Empirical
More informationStock Market Cross-Sectional Skewness and Business Cycle Fluctuations 1
Stock Market Cross-Sectional Skewness and Business Cycle Fluctuations 1 Ninth BIS CCA Research Conference Rio de Janeiro June 2018 1 Previously presented as Cross-Section Skewness, Business Cycle Fluctuations
More informationThis paper examines how different types of interactions with U.S. markets by non-u.s. firms are associated
Published online ahead of print July 19, 2013 MANAGEMENT SCIENCE Articles in Advance, pp. 1 22 ISSN 0025-1909 (print) ISSN 1526-5501 (online) http://dx.doi.org/10.1287/mnsc.2013.1714 2013 INFORMS Which
More information