Clarion University Clarion, PA · Clarion University. Clarion, PA. Proceedings of the 2012...

Proceedings of the 2012 Pennsylvania Economic Association Conference

Clarion University Clarion, PA


PROCEEDINGS OF THE PENNSYLVANIA ECONOMIC

ASSOCIATION 2012 CONFERENCE

May 31-June 2, 2012 Clarion University

Clarion, Pennsylvania

William K. Bellinger, Editor Dickinson College

Visit the Pennsylvania Economic Association Home Page at http://aux.edinboro.edu/pea/index.html

http://aux.edinboro.edu/pea/index.html


Pennsylvania Economic Association: 2011-2012

Executive Board

• President: Orhan Kara, West Chester University • President-Designate: Tracy Miller, Grove City College • Vice President, Program: William Bellinger, Dickinson College • Vice President, Publicity: Sandra Trejos, Clarion University • Vice President, Membership: Natalie Reaves, Rowan University • Secretary: Stephanie Brewer, Indiana University of Pennsylvania • Treasurer: Steven Andelin, Penn State - Schuylkill • Co-Editors, Pennsylvania Economic Review: Thomas Tolin & Orhan Kara, West

Chester University • Webmaster: Michael Hannan, Edinboro University of Pennsylvania • Immediate Past President: James Jozefowicz, Indiana University of Pennsylvania

Board of Directors

• Ron Baker, Millersville University • Charles Bennett, Gannon University • Deborah Gougeon, University of Scranton • Kosin Isariyawongse, Edinboro University • John McCollough, Penn State - Lehigh Valley • Brian O'Roark, Robert Morris University • Mark Schweitzer, Federal Reserve Bank of Cleveland • Yaya Sissoko, Indiana University of Pennsylvania • Luke Tilley, Federal Reserve Bank of Philadelphia • Roger White, Franklin and Marshall College

Ex-Officio Directors

• Thomas O. Armstrong, Pennsylvania Department of Community & Economic Development

• Gerald Baumgardner, Pennsylvania College of Technology

• David Culp, Slippery Rock University

• Donald Dale, Muhlenberg College • Robert D'Intino, Rowan

University • James Dunn, Edinboro University • Andrew Economopoulos, Ursinus

College

• Joseph Eisenhauer, Wright State University

• Mark Eschenfelder, Robert Morris University

• Andrew Hill, Federal Reserve Bank of Philadelphia

• Elizabeth Hill, Penn State-Mont Alto

• Mehdi Hojjat, Neuman College • Tahereh Hojjat, DeSales

University • Ioannis N. Kallianiotis,

University of Scranton • Donna Kish-Goodling,

Muhlenberg College

mailto:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected],[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]


• Richard Lang, Federal Reserve Bank of Philadelphia (retired)

• Daniel Y. Lee, Shippensburg University

• Robert Liebler, King's College • Johnnie B. Linn III, Concord

University • Patrick Litzinger, Robert Morris

College • Stanley G. Long, University of

Pittsburgh/Johnstown • Jacquelynne McLellan, Frostburg

State University • Lawrence Moore, Potomac State

College of West Virginia University

• Gayle Morris, Edinboro University

• Heather O'Neill, Ursinus College • Brian O’Roark, Robert Morris

University

• Abdul Pathan, Pennsylvania College of Technology

• William F. Railing, Gettysburg College

• Margarita M. Rose, King's College

• William Sanders, Clarion University

• John A. Sinisi, Penn State University-Schuylkill

• Brian Sloboda, US Postal Service • Kenneth Smith, Millersville

University of Pennsylvania • Lynn Smith, Clarion University • Osman Suliman, Millersville

University • Paul Woodburne, Clarion

University • Bijou Yang-Lester, Drexel

University • David Yerger, Indiana University

of Pennsylvania

mailto:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]


Editor’s Introduction and Acknowledgements

The papers published in this volume were presented at the 2012 Annual Conference of the Pennsylvania Economic Association held at Clarion University of Pennsylvania from May 31 to June 2, 2012. The program lists all scheduled presenters, session chairs and discussants. Only the papers and comments submitted according to the manuscript guidelines are included in the Proceedings. Each research paper listed in the Table of Contents and Author Index can be accessed directly by clicking on the listing. The 2012 Conference was apparently a great success. Participants gathered from across Pennsylvania, several other states, and multiple nations in order to share their research. Faculty, other professionals, and both graduate and undergraduate students participated in the conference. The conference also featured three general presentations; “Stratification Economics” by Dr. Sue Stockly, a presentation on the regional economy by Mark Schweitzer, Research Director at the Federal Reserve Bank of Cleveland, and a session on teaching economics with Excel by Dr. Humberto Barreto. I particularly wish to thank Dr. Sandra Trejos of Clarion University for her time and energy in coordinating all local arrangements. We also owe special thanks to the Federal Reserve Bank of Cleveland and Dr. James Pesek, Dean of the College of Business at Clarion University of Pennsylvania for their support of this conference. Additional thanks go to the PEA board for their advice and effort in making the conference a success. Lastly, thanks to all of the participants who contributed interesting ideas and a friendly atmosphere to the conference.


Table of Contents

Conference Agenda page 1 RISK AVERSION AND BUSINESS CYCLES: AN EMPIRICAL ANALYSIS Cristian Pardo page 16 RESPONSIVENESS OF THE U.S. TRADE FLOWS TO CHANGES IN CHINESE CURRENCY Orhan Kara page 37 RECENT PENNSYLVANIA JOB TRENDS: EFFECTS OF SHALE? (2012) Jay Bryson, Tim Quinlan and Joe Seydl page 48 MULTIGENERATIONAL DISCOUNTING: MERGING INTERGENERATIONAL EQUITY AND INDIVIDUAL TIME PREFERENCE William Bellinger page 55 AID EFFECTIVENESS IN SUB-SAHARAN AFRICA Yaya Sissoko and Niloufer Sohrabji page 66 ECONOMIC ANALYSIS OF ALTERNATIVE WAYS TO REFORM MEDICAL MALPRACTICE Tracy C. Miller page 85 DOES A FIRM’S DIVIDEND INITIATION AFFECT ITS RISK? Henry F. Check, Jr., John S. Walker and Karen L. Randall page 90 THE BUREAU OF MOTOR FUEL TAXES COMPLIANCE STRATEGY: PENNSYLVANIA DEPARTMENT OF REVENUE Thomas O. Armstrong, Daniel Meuser, James Dehnert, and Nic Banting page 101 A PANEL STUDY ANALYSIS OF ECONOMIC GROWTH IN SOUTH EAST ASIA Tai McNaughton page 117 THE DODD-FRANK “WALL STREET REFORM” ACT OF 2010: IS OUR FINANCIAL SYSTEM MORE STABLE NOW? Adora D. Holstein page 125 GOVERNMENT POLICY AND RESULTANT EFFECT ON NICHE INDUSTRIES: THE CASE OF USPS “EVERY DOOR DIRECT MAIL” Brenda Ponsford and William R. Hawkins page 145 FOREIGN AID EFFECTS ON GROWTH IN LATIN AMERICA Tai McNaughton page 148 OFFSETS IN THE DEFENSE TRADE: COUNTERING COMPARATIVE ADVANTAGE INERNATIONAL BUSINESS Brenda Ponsford and William R. Hawkins page 156 ACADEMIC PERFORMANCE IN GRADUATE MANAGERIAL ECONOMICS Rod D. Raehsler page 164 DECOMPOSING RECENT MONEY SUPPLY CHANGES WITH IMPLICATIONS FOR CURRENT FED POLICY Richard Robinson and Marwan El Nasser page 177


WORLD OIL PRICES: ECONOMIC IMPACT AND ECONOMETRIC FORECAST Carrie R. Williams page 187 ADVANTAGEOUS SELECTION IN HEALTH INSURANCE Paul Sangrey page 196 THE EFFECT OF RELIGION AND EMPOWERMENT OF WOMEN ON FERTILITY Denae A. Heath and Cameron D. McConnell page 202 THE EFFECT OF HUMAN DEVELOPMENT LEVEL ON THE RELATIONSHIP BETWEEN ENERGY CONSUMPTION AND ECONOMIC GROWTH: A CHAOS THEORY APPROACH Ezatollah Abbasian and Maysam Nasrindoost page 208 LIVING IN KEYNES’S LONG RUN: THE EFFECTS OF THE OVERUSE OF ECONOMIC STIMULUS David Nugent page 216 DISCUSSANT COMMENT ON LIVING IN KEYNES'S LONG RUN: THE EFFECTS OF THE OVERUSE OF ECONOMIC STIMULUS Michael J. Hannan page 222 KANTIAN MARKETS, BOYCOTTS, AND EFFICIENCY Richard Robinson page 223 THE ECONOMIC IMPACT OF ALVERNIA UNIVERSITY Tufan Tiglioglu, Lisa Cooper, Bari Dzomba, Rachel Gifford, and Joseph Hess page 232 A STUDY OF FACTORS AFFECTING THE ECONOMIC FEASIBILITY OF THE IMPLEMENTATION OF TORREFACTION TECHNOLOGY BY THE PENNSYLVANIA WOOD PELLET INDUSTRY Robert F. Brooker and Harry R. Diz page 243 THE COLLEGE EDUCATED AND THE PUBLIC/PRIVATE SALARY DIFFERENTIAL: CAN OCCUPATION EXPLAIN DIFFERENCES? Mary Ellen Benedict, Michael Bajic, and David McClough page 251

Author Index page 267

1 Proceedings of the 2012 Pennsylvania Economic Association Conference

Pennsylvania Economic Association

2012 CONFERENCE AGENDA

THURSDAY, May 31, 2012

• 4:00 pm - 9:00 pm Registration (Moore Hall) • 5:00 pm - 8:00 pm Board of Directors Dinner/Meeting

(Eagle Commons 107-108) • 6:00 pm - 10:00 pm Reception (Moore Hall)

FRIDAY, June 1, 2012

• 8:00 am – noon, 2 pm – 4 pm Registration (Still Hall Lobby) • 7:30 am - 10:30 am Continental Breakfast (Still Hall Lobby) • 9:00 am - 10:15 am Concurrent Sessions (Still Hall) • 10:30 am - 11:45 pm Concurrent Sessions (Still Hall) • 12 noon - 1:45 pm Luncheon with Speaker- “Stratification Economics"

Dr. Sue Stockly (Gemmell Complex-Multipurpose Room) • 2:15 pm - 3:30 pm Concurrent Sessions (Still Hall) • 3:45 pm - 4:45 pm Fed Lecture: Mark Schweitzer, Research Director at The Federal

Reserve Bank of Cleveland (Still Hall 112) • 5 pm - 8 pm Fed Sponsored Reception (Still Hall Lobby)

SATURDAY, June 2, 2012

• 7:30 am - 10:30 am Registration & Continental Breakfast (Still Hall Lobby) • 9:00 am - 10:15 am Concurrent Sessions (Still Hall) • 10:30 am - 11:30 am Plenary Session- Teaching Economics with Excel by Dr.

Humberto Barreto (Still Hall 112) • 11:45-12:45 General Membership Meeting (Still Hall 112) • 12:45 am Closing


FRIDAY, June 1, 2012

Conference Registration 8:00 a.m. – noon, 2-4 p.m., Still Hall Lobby

7:30 a.m. – 10:30 a.m. Continental Breakfast(Still Hall Lobby)

Sessions F1: Friday, June 1, 2012, 9:00 a.m. – 10:15 a.m.

Session F1A: Development Economics Location: Still Hall 111

Chair: Orhan Kara, West Chester University The effect of human development level on the relationship between energy consumption and economic growth: a chaos theory approach Ezatollah Abbasian Bu-Ali Sina University

Is Foreign Debt a Threat or a Promise to Least Developed Countries? Evelyn Wamboye Pennsylvania State University

Aid Effectiveness in Sub-Saharan Africa Yaya Sissoko Indiana University of Pennsylvania Niloufer Sohrabji Simmons College

Discussants: Morteza Sameti, University of Isfahan, Iran Kiril Tochkov, Texas Christian University Orhan Kara, West Chester University

Session F1B: Student Session I

Location: Still Hall 102 Chair: Tracy Miller Grove City College

A Dissimilarity of the Federal Reserve and the European Central Bank Mandates and an Investigation of the Zero-Bound Rule during the Recent Global Financial Crisis of 2008 Emily Abbondanza Edinboro University

Industrial Composition of U.S. Counties as a Determent of Income: A Case Study of Pennsylvania Deepra Yusuf Franklin & Marshall College

Advantageous Selection in Health Insurance Paul Sangrey Grove City College

Discussants: Tracy Miller, Grove City College Thomas Armstrong, PA Department of Revenue


Session F1C: Women and Labor Location: Still Hall 202

Chair: Mary Ellen Benedict, Bowling Green University Models for Forecasting Local Employment Trends in Pennsylvania Sandra McPherson Millersville University

Determinants of Youth Unemployment in the UAE Samer Kherfi American University of Sharjah

Informal social networks and household wellbeing in rural Ethiopia Abera Birhanu Demeke University Canada West

Tax Incentives, Education and Migration: The Case of Puerto Rico Carlos Liard Central Connecticut State University

Discussants: Jay Bryson, Wells Fargo Kevin Quinn, Bowling Green State University Mary Ellen Benedict, Bowling Green University

Session F1D: Microeconomics in an International Context Location: Still Hall 203

Chair: Ronald Baker, Millersville University of Pennsylvania Elasticity Estimation for the Turkish Manufacturing Industry Zeynep Deniz Dervisen Kadir Has University

Cournot and Bertrand Competition when Advertising Rotates Demand: The Case of Honda and Scion Kosin Isariyawongse Edinboro University of Pennsylvania

Ecological Efficiency and Economic Development in Latin America SandraTrejos Clarion University of PA

Discussants: Ronald Baker, Millersville University of Pennsylvania Thomas Andrews, West Chester University Soloman Kone, City University of New York

Session F1E: Macroeconomics

Location: Still Hall 205 Chair: Michael Hannon, Edinboro University of Pennsylvania

Risk Aversion and Business Cycles: An Empirical Analysis Cristian Pardo Saint Joseph's University

Using Options to Measure Monetary Policy Credibility Timothy Kearney Misericordia University

The Volcker Rule, Wall Street Reform, and the Subprime Financial Crisis Adora Holstein and Nicole Baird Robert Morris University

Changing Patterns of Credit Usage from the Survey of Consumer Expenditures: An Exploratory Study of Type and Level of Credit Before and After 9/11 Heather Kirkwood-Mazik Clarion University of Pennsylvania


Discussants: Richard Robinson SUNY-Fredonia Shuang Feng Edinboro University of PA Michael Hannan Edinboro University of PA Marwan El Nasser SUNY-Fredonia

Session F1F: The Economics of Education Location: Still Hall 206

Chair: Lynn Smith, Clarion University

What Distinguishes Winners from Losers? An Analysis of School Choice in Massachusetts Soma Ghosh Albright College

Financial Aid, College Tuition and Student Retention Frederick Tannery Slippery Rock University

The Economic Impact of Alvernia University Tufan Tiglioglu Alvernia University

Discussants: Lynn Smith, Clarion University of Pennsylvania Liang Ding, Alvernia University William Bellinger, Dickinson College

Sessions F2: Friday, June 1, 2012 10:30 a.m. – 11:45 a.m.

Session F2A: Health Economics

Location: Still Hall 111 Chair: David McClough, Ohio Northern University

The Effect of Safe Water, Sanitation, and Human Capital on Child Nutrition and Health: A Quantile Regressions Approach Divya Balasubramaniam St. Joseph's University

Economic Analysis of Alternative ways to reform medical malpractice Tracy Miller Grove City College

The Economic Costs of Racial Disparities in Breast Cancer Kemi Oyewole Spelman College

Discussants: Samer Kherfi, American University of Sharjah Charles Telly, SUNY Fredonia David McClough, Ohio Northern University


Session F2B: Student Session II, Empirical Analysis Location: Still Hall 102

Chair: Rod Raehsler Clarion University A Panel Study Analysis of Economic Growth in Southeast Asia McNaughton, Tai Clarion University

The Determinants of Flight Delays Nadejda Sergheeva Villanova University

World oil Prices: Economic Impact and Econometric Forecast Williams, Carrie Clarion University

Discussants: Wenting Yu Texas Christian University Rod Raehsler Clarion University

Session F2C: Sustainability in the Business Curriculum Location: Still Hall 202

Chair: David Culp, Slippery Rock University A Matrix Model for Integrating Sustainability into the Business Curriculum: A Case Study David Culp Slippery Rock University

Green Accounting: Measuring and Reporting the Triple Bottom Line Anna Lusher Slippery Rock University

How a Sustainable Business Accelerator Can Enhance Delivery of Sustainability in the Business Curriculum John Golden Slippery Rock University

Discussants: Robert Leibler, Kings College Robert F. Brooker, Gannon University Steven Andelin, Penn State University-Schuylkill

Session F2D: International Macro Topics Location: Still Hall 203

Chair: Lei Zhang, Edinboro University of PA Convergence and Persistence of Prices within the European Union Olena Ogrokhina University Of Houston

Interest Rates and the Demand for Credit in Ghana Eric Fosu Oteng-Abayie Kwame Nkrumah University

Is Foreign Debt a Threat or a Promise to Least Developed Countries? Evelyn Wamboye Pennsylvania State University

Discussants: Lei Zhang, Edinboro University of PA Cristian Pardo, Saint Joseph's University Xuebing Yang, Penn State University-Altoona


Session F2E: Public Economics Location: Still Hall 205

Chair: Michael Hannan , Edinboro University of PA The Bureau of Motor Fuels Tax Compliance Strategy: Pennsylvania Department of Revenue Thomas Armstrong PA Department of Revenue

Can Responsibility Centered Budgeting Provide Healing from Budget Cuts? Robert Balough Clarion University of PA

Tax Incentives and Capital Spending Revisited Arthur Schiller Casimir Western New England University

Discussants: Heather Kirkwood-Mazik, Clarion University of Pennsylvania Michael Hannan , Edinboro University of PA John Walker, Kutztown University

Session F2F: Miscellaneous Topics Location: Still Hall 206

Chair: Roger White, Franklin and Marshall Does Economic Freedom Mean Freedom to Grow? Ranajoy Ray-Chaudhuri The Ohio State University

Sources and Management of Stress Among Non-Academic Staff in Public Universities in Ghana: The Case of Kwame Nkrumah University of Science and Technology Henry Kofi Mensah Kwame Nkrumah University of Science and Technology

The Reciprocal Relation of Marginal Cost of Public Funds: Inequality Aversion and Economic Growth in Iran Morteza Sameti University of Isfahan, Iran

Estimation Window and the Power of Event Study Liang Ding and Tufan Tiglioglu Alvernia University

Discussants: Roger White, Franklin & Marshall David Nugent, Not Affiliated Ezatollah Abbasian Bu-Ali Sina University Abera Birhanu Demeke , University Canada West


LUNCHEON AND SPEAKER 12:00 Noon – 1:45 P.M.

“Stratification Economics" Dr. Sue Stockly

Gemmell Complex-Multipurpose Room)

Dr. Sue K. Stockly is an Associate Professor of Economics at Eastern New Mexico University. A native New Mexican, she completed a B.A. and an M.B.A. at the College of Santa Fe. She received a Ph.D. in Economics from the University of Texas at Austin in 1999. After working as an associate economist with the RAND Corporation for five years, she returned to New Mexico where she teaches Economics and Business Research Methods. Her current research interests include stratification economics, regional economic development, teaching of economics, and minority student performance in higher education.


Sessions F3: Friday, June 1, 2012 2:15 p.m. – 3:30 p.m.

Student Poster Session: Location: Still Hall Lobby

Nobel Laureate James Meade Kathleen Coen Clarion University

Antoine-Augustin Cournot Matthew Bauer Clarion University

Jeremy Bentham Samantha Myler Clarion University

Session F3A: Resource Economics Location: Still Hall 111

Chair: Sandra McPherson, Millersville University Recent Pennsylvania Job Trends: Effects of Shale? Jay Bryson, Tim Quinlan and Joe Seydl, Wells Fargo

Anthracite Production in Northeast Pennsylvania Steven Andelin Pennsylvania State University

Determinants of Distributed Photovoltaic Installations in the United States Thomas Andrews West Chester University

A study of factors affecting the economic feasibility of the implementation of torre faction technology by the Pennsylvania wood pellet industry Robert F. Brooker Gannon University

Discussants: Sandra McPherson, Millersville University Arthur Schiller Casimir, Western New England University Tufan Tiglioglu, Alvernia University Steven Andelin, Penn State University-Schuylkill

Session F3B: Student Session III

Location: Still Hall 102 Chair: Sandra Trejos, Clarion University

Small Business and the United States Economy: The Key to Job Creation and Growth Miranda Mease Clarion University

Sheltering Our Poor: Natural Disasters and the Economies of Bangladesh and Haiti Mary Jo Milford Clarion University

Militarization and Economic Development in Brazil Braden Picardi Clarion University

Discussants: Sandra Trejos Clarion University Anna Lusher, Slippery Rock University


Session F3C: Economic Education

Location: Still Hall 202 Chair: Abdul Pathan, PA College of Technology

Academic Performance in Graduate Managerial Economics Rod Raehsler Clarion University

An Outline of Some Thoughts on Teaching Money, Banking, and Monetary Economics in Ex-Soviet Countries in Transition Marwan El Nasser SUNY-Fredonia Testing Procedures Robert Liebler King's College

Approaches to Lecture Preparation Presentation and Assessing Student Learning for Economics Abdul Pathan PA College of Technology Discussants: David Culp, Slippery Rock University Robert Balough, Clarion University of PA Soma Ghosh, Albright College John Golden, Slippery Rock University

Session F3D: Microeconomics Location: Still Hall 203

Chair: Kosin Isariyawongse, Edinboro University of Pennsylvania Comparing the effectiveness of leadership gifts and matching funds in the provision of public goods under alternative laboratory methodologies Ronald Baker Millersville University of Pennsylvania

Multigenerational Discounting: Merging Intergenerational Equity and Individual Time Preference William Bellinger Dickinson College

Kantian Markets, Boycotts, and Efficiency Richard Robinson SUNY Fredonia

Discussants: Kosin Isariyawongse, Edinboro University of Pennsylvania Zeynep Deniz Dervisen, Kadir Has University Brenda Ponsford, Clarion University


Session F3E: Miscellaneous Topics Location: Still Hall 205

Chair: Tracy Miller, Grove City College

The College Educated and the Public/Private Salary Differential: Can Occupation Explain Differences? Mary Ellen Benedict and Michael Bajic, Bowling Green State University" David McClough Ohio Northern University

Innovation by London's Water Companies: Internalizing public health externalities Nicola Tynan Dickinson College

Adam Smith on Education Kevin Quinn Bowling Green State University

Smith’s Invisible Hand is Exonerated by Hayek’s Concept in the Fatal Conceit Charles Telly SUNY Fredonia

Discussants: Lynn Smith, Clarion University Tracy Miller, Grove City College Charles Telly, SUNY Fredonia Kevin Quinn, Bowling Green State University

Session F3F: International Economics Location: Still Hall 206

Chair: Kiril Tochkov Texas Christian University Responsiveness of the U.S. Trade Flows to Changes in Chinese Currency Orhan Kara West Chester University

Impact of the Global Financial Crisis the ECOWAS Countries Yaya Sissoko Indiana University of Pennsylvania Soloman Kone City University of New York

The Transforming Dragon: Labor Productivity Change in China's Three Economic Sectors Wenting Yu Texas Christian University

Discussants: Xuebing Yang, Penn State University-Altoona Adora Holstein, Robert Morris University Ranajoy Ray-Chaudhuri, The Ohio State University

3:45 p.m. – 4:45 p.m. Still Hall 112 Presentation on the Regional Economy, Mark Schweitzer, Research Director at the

Federal Reserve Bank of Cleveland

5 –8 P.M. Still Hall Lobby Reception hosted by the Federal Reserve Bank of Cleveland


SATURDAY, June 2, 2012 7:30 – 10:30 A.M. Conference Registration & Continental Breakfast:

Still Hall Lobby ____________________________________________

Sessions S1: Saturday, June 2, 2012 9:00 a.m. – 10:15 a.m.

Session S1A: International Trade

Location: Still Hall 111 Chair: Shuang Feng, Edinboro University of PA

Regional Supplier Associations as the Producer of Transitional Public Goods in Latin America and the Caribbean Sunita Mondal University of Pittsburgh

Losing Comparative Advantage? Calibrating the DFS Model for US Trade, 1970-2008 Roger White Franklin & Marshall College

An Eaton-Kortum Openness Index Xuebing Yang Penn State University at Altoona

Discussants: Ronald Baker, Millersville University of Pennsylvania Orhan Kara, West Chester University Shuang Feng, Edinboro University of PA

Session S1B: Monetary Economics Location: Still Hall 102

Chair: Robert Balough, Clarion University of PA Decomposing Recent Money Supply Changes with Implications for Current Fed Policy Richard Robinson and Marwan El Nasser, SUNY at Fredonia

The Bank Lending Channel: a FAVAR Analysis Lei Zhang Edinboro University of PA

Living in Keynes's Long Run: The Effects of the Overuse of Economic Stimulus David Nugent Not Affiliated

Discussants: Timothy Kearney, Misericordia University Robert Balough, Clarion University of PA Michael Hannan, Edinboro University of PA


Session S1C: Student Session IV Location: Still Hall 202

Chair: Abdul Pathan, Pennsylvania College of Technology Impacts of the Recession on Women: Analysis of a Local Economy Deepra Yusuf Franklin and Marshall College

The Effect of Immigration on State Wages Jennifer Johnson Indiana University of Pennsylvania

Foreign Aid and Its Effect on Human Functioning In Africa Nathan Wolbert Clarion University

Why Do Dragons Breathe Fire? The Economic Growth and Development of Eastern Asia Michael Bartley Clarion University

Discussants: Abdul Pathan, Pennsylvania College of Technology Lynn Smith, Clarion University

Session S1D: Miscellaneous Topics Location: Still Hall 203

Chair: William Bellinger, Dickinson College Government Policy and Resultant Effect on Niche Industries Brenda Ponsford Clarion University William R. Hawkins U.S. House of Representatives

Can a Change in Dividend Policy Affect Risk? John Walker Kutztown University

Offsets in the Defense Trade: Brenda Ponsford Clarion University William R. Hawkins U.S. House of Representatives

Discussants: William Bellinger, Dickinson College Thomas Andrews, West Chester University Nicola Tynan, Dickinson College

Session S1E: Student Session V Location: Still Hall 205

Chair: Yaya Sissoko, Indiana University of PA Promised Land? The Impact of Promise Scholarship Programs on Housing Prices Michael LeGower University of Pittsburgh

Analysis of the Time Series Properties of U.S. Unemployment Kristen Workley Clarion University

Recovery From Current Recession: Is It Different From Previous Recessions? Yang Yang Clarion University


Discussants: Heather Kirkwood-Mazik, Clarion University Yaya Sissoko, Indiana University of PA

Session S1F: Student Session VI (Development) Location: Still Hall 206

Chair: Sandra Trejos Clarion University Religion and Empowerment of Women in Brazil Deane Heath Clarion University

The Effects of Political Stability and Disease in Sub-Saharan Africa Jared Bruce Clarion University

Leadership, Democracy and Economic Development in Africa Chris Myers Clarion University

Foreign Aid Effects on Growth in Latin America McNaughton, Tai Clarion University

Discussants: Sandra Trejos, Clarion University Rod Raehsler, Clarion University

10:30 am - 11:30 am Plenary Session, Still Hall 112 Dr. Humberto Barreto, Teaching Economics with Excel

11:45-12:45 General Membership Meeting Still Hall 112

This Annual Business Meeting of the General Membership of the Pennsylvania Economic Association is open to the entire membership of the PEA, including all registrants at the conference. Door prizes will be awarded.

SATURDAY, June 2, 2012 CLOSING

Program Author & Participant Index

First Name Last Name E-mail Sessions Ezatollah Abbasian [email protected] F1A, F2F Emily Abbondanza [email protected] F1B Steven Andelin [email protected] F2C, F3A Thomas Andrews [email protected] F1D, F3A, S1D Thomas Armstrong [email protected] F1B, F2E Ronald Baker [email protected] F1D, F3D, S1A Divya Balasubramaniam [email protected] F2A Robert Balough [email protected] F2E, F3C, S1B Michael Bartley [email protected] S1C Matthew Bauer [email protected] Poster Sess.


William Bellinger [email protected] F3D, S1D Mary Ellen Benedict [email protected] F1C, F3E Robert Brooker [email protected] F2C, F3A Jared Bruce [email protected] S1F Jay Bryson [email protected] F1C, F3A Arthur Schiller Casimir [email protected] F2E, F3A Kathleen Coen [email protected] Poster Sess. David Culp [email protected] F2C, F3C Abera Birhanu Demeke [email protected] F1C, F2F Zeynep Deniz Dervisen [email protected] F1D, F3D Liang Ding [email protected] F1F, F2F Marwan El Nasser [email protected] F1E, F3C, S1B Shuang Feng [email protected] F1E, S1A Soma Ghosh [email protected] F1F, F3C John Golden [email protected] F2C, F3C Deborah Gougeon [email protected] Michael Hannon [email protected] F1E, F2E, S1B Deane Heath [email protected] S1F Adora Holstein [email protected] F1E, F3F Kosin Isariyawongse [email protected] F1D, F3D Jennifer Johnson [email protected] S1C Orhan Kara [email protected] F1A, F3F, S1A Timothy Kearney [email protected] F1E, S1B Samer Kherfi [email protected] F1C, F2A Heather Kirkwood-Mazik [email protected] F1E, F2E, S1E Soloman Kone [email protected] F1D, F3F Michael LeGower [email protected] S1E Carlos Liard [email protected] F1C, F2D Robert Liebler [email protected] F2C, F3C Anna Lusher [email protected] F2C, F3B David McClough [email protected] F2A, F3E Tai McNaughton [email protected] F2B, F3B Sandra McPherson [email protected] F1C, F3A Miranda Mease [email protected] F3B Henry Kofi Mensah [email protected] F2F Mary Jo Milford [email protected] F3B Tracy Miller [email protected] F1B, F2A, F3E Sunita Mondal [email protected] S1A Chris Myers S1F Samantha Myler [email protected] Poster Sess. David Nugent [email protected] F2F, S1B


Olena Ogrokhina [email protected] F2D Eric Fosu Oteng-Abayie [email protected] F2D Kemi Oyewole [email protected] F2A Cristian Pardo [email protected] F1E, F2D Abdul Pathan [email protected] F3C, S1C Braden Picardi [email protected] F3B Brenda Ponsford [email protected] F3D, S1D Kevin Quinn [email protected] F1C, F2A, F3E Rod Raehsler [email protected] F2B, F3C, S1F Ranajoy Ray-Chaudhuri [email protected] F2F, F3F Richard Robinson [email protected] F1E, F3D, S1B Morteza Sameti [email protected] F1A, F2F Paul Sangrey [email protected] F1B Arthur Casimir Schiller [email protected] F1E, F3A Nadejda Sergheeva [email protected] F2B Joseph Seydl [email protected] F3A Yaya Sissoko [email protected] F1A, F3F, S1E Lynn Smith [email protected] F3E, S1C Frederick Tannery [email protected] S2G Charles Telly [email protected] F2A, F3E Tufan Tiglioglu [email protected] F2F, F3A,F1F Sandra Trejos [email protected] F1D, F3B, S1F Kiril Tochkov [email protected] F1A, F3F Nicola Tynan [email protected] F3E, S1D John Walker [email protected] F2E, S1D Evelyn Wamboye [email protected] F1A, F2D Roger White [email protected] F2F, S1A Carrie Williams [email protected] F2B Nathan Wolbert [email protected] S1C Kristen Workley [email protected] S1E Yang Yang [email protected] S1E Xuebing Yang [email protected] F2D, F3F, S1A Wenting Yu [email protected] F2B, F3F Deepra Yusuf [email protected] F1B, S1C Lei Zhang [email protected] F2D, S1B

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RISK AVERSION AND BUSINESS CYCLES: AN EMPIRICAL ANALYSIS

Cristian Pardo Department of Economics Saint Joseph's University Philadelphia, PA 19131

ABSTRACT

Private entrepreneurs usually lack access to complete risk-pooling for their idiosyncratic risk. Consequently, risk-averse entrepreneurs internalize volatility and demand a private equity premium, which is capable of amplifying business cycles due to its sensitivity to shocks and subsequent impact on investment and output. Therefore, economies with larger private entrepreneurial sectors should present higher volatility. I test this prediction by (1) conducting a reduced-form analysis that shows that volatility is negatively associated with the importance of the corporate vs. privately-held sectors; and (2) estimating the model's structural parameters, where positive risk-aversion coefficients should be found where private entrepreneurs are predominant.

INTRODUCTION Differences in business cycle fluctuations in emerging markets relative to developed economies have been extensively studied by economists. Prasad, Agenor and McDermott (1999), among many others, provide empirical evidence supporting much higher average output volatility in emerging economies than in industrialized economies.1 In the theoretical arena, numerous models rely on financial imperfections as a primary stylized fact to motivate this discussion, where low levels of development in financial markets observed in emerging markets are often cited. For instance, Calvo and Reinhart (2000) and Chang and Velasco (2000) focus on the role of “dollarized liabilities." Namely, due to currency mismatching, real exchange rate depreciations may negatively impact firms' and banks' balance sheets by asymmetrically increasing the value of outstanding debt relative to revenues. Another stylized fact commonly analyzed is the presence of a more important privately-held sector relative to corporations in emerging markets. Market capitalization as a fraction of GDP, for instance, is about 100 percent or more in high-income countries, while 35 percent or less in low and middle-income countries (The World Bank, 2010). The fact that privately-owned firms tend to rely more on debt rather than equity to finance their investments may play an additional role in creating frictions in emerging economies. Bernanke, Gertler and Gilchrist (1999), for example, study the impact of information asymmetries in the borrower-lender relationship. The authors show that the agency problems that arise from

the positive probability of costly default imply that lenders optimally charge entrepreneurs an external finance premium. This premium is endogenous to firms' balance sheet in that a higher reliance on external funds raises the aforementioned agency costs. As business cycles affect entrepreneurs' net worth, the resulting external finance premium is counter-cyclical and may become a mechanism that magnifies the impact of real shocks over time. Pardo (2010) examines additional stylized facts about emerging markets, including that private entrepreneurial activity in particular is also often very volatile. An illustrative example is the Chilean case. While it has boasted one of the most robust financial systems in its region, its economy still reacted strongly to the effects of the Asian crisis of the 1990's. A reason often cited for this response was that the entrepreneurial sector moved quickly from an early-to-mid 1990's boom euphoria to a deep depression in the following years. Evidence like this may make it worthwhile to further examine facts and assumptions about the private entrepreneurial sector. In general, the simplifying assumption of risk neutrality on agents makes sense in some cases. Gale and Hellwig (1985), for instance, point out that “risk neutrality is not an unreasonable assumption to make in the case of investors since it can be justified as a consequence of risk-pooling." That is, by investing large amounts of funds and thus taking advantage of economies of scale, lenders tend to successfully maintain highly diversified portfolios that allow them to significantly reduce the exposure to risk. However, the authors also emphasize the fact that the risk-neutrality assumption “makes less sense in the case of entrepreneurs." As shown by Moskowitz and Vissing-Jørgensen (2002), the high concentration of ownership of privately-held companies and their importance in their owners' portfolios, leave private entrepreneurs highly vulnerable to project-specific, uninsurable risks. That is, the lack of access to complete risk-pooling for their idiosyncratic risks leaves private entrepreneurs with no other option but to internalize the cost of volatility. Therefore, assuming risk neutrality (that is, assuming that risk can be ignored) seems to be a stronger assumption in this case. Pardo (2010) builds on Bernanke et al. (1999) to show that introducing risk aversion among private entrepreneurs modifies the optimal relationship with lenders mainly by


incorporating a private equity premium, or the positive risk premium that risk-averse entrepreneurs demand due to the stochastic nature of the uninsurable part of their investment returns. This premium may lead to further magnifying the aggregate effects of real shocks. The mechanism works as follows: a real shock that decreases entrepreneurial profits and net worth, reduces entrepreneurs' minimum guaranteed level of consumption (the insurable part of the entrepreneur's returns). Consequently, their effective risk aversion and so the private equity premium rise. In response to the increased internal and external costs, entrepreneurs increase the rental rate of capital to final goods firms, producing a contraction in the supply of capital and thus additional impact of shocks on investment and production. Finally, Pardo (2012) extends the previous model into a small open economy framework. In this context, following Chang and Velasco (2000), shocks not only affect entrepreneurs' net worth directly, but also indirectly through the increase in the value of debt following the corresponding real exchange rate adjustment. As wealth falls, the aforementioned private equity premium rises, therefore generating the known amplifying impacts of shocks over time. Consequently, a direct implication of this model is that economies where the private entrepreneurial sector is a relatively important actor in the financial market (for instance, where family-owned businesses are predominant), and therefore the economy as a whole is more vulnerable to uninsurable risk, all else equal, should present higher output volatility than economies where the corporate sector, whose ownership structure is highly diversified at all levels, is more important. Considerable debate has taken place among economists about the role of entrepreneurial activity in affecting economic growth. Arguments about the impact of entrepreneurship on important factors affecting long-run growth often discuss innovation, productivity and knowledge spillovers (van Stel, Carree and Thurik, 2005). Much less attention has been given to the relationship between entrepreneurship and output growth volatility. Apart from Pardo (2012), another exception is Rampini (2004), who provides a theoretical framework in which entrepreneurial activity is procyclical and produces amplification and propagation of shocks. In the empirical arena, however, to the best of my knowledge there have been no studies examining the relationship between the ownership structure of the real sector and output volatility. Entrepreneurial activity is a plausible index of the economic importance of entrepreneurship. The Global Entrepreneurship Monitor (GEM) builds the Total Entrepreneurial Activity rate (TEA), which measures the “relative amount of nascent entrepreneurs and business owners of young firms for a range of countries" (van Stel et al., 2005). Figure 1 illustrates the simple direct (unconditional) correlation between total entrepreneurial activity, as measured by the TEA index, and

output volatility, as measured by the standard deviation of the per capita real GDP growth, for 46 countries. At least as preliminary evidence, there seems to be a positive correlation between those two variables.2 The objective of this paper is to empirically test whether the volatility-inducing frictions that risk aversion introduces are more likely to be present the greater the relative size of the private entrepreneurial sector is. I test this prediction through two alternative approaches. First, I examine the statistical significance of the correlation between GDP growth volatility and the ownership structure of the productive sector through a simple reduced-form analysis. In particular, using international data, I find that output volatility is negatively associated with the relative importance of the corporate sector in the financial market, all else equal. The investment-to-capital ratio (as a measure of financial leverage), indices of financial structure and development plus other measures of cross-country sources of uncertainty are used as control variables. The reduced-form approach's main limitation in this case is that a resulting statistical relationship between output volatility and ownership structure may not provide empirical significance of the magnitude of the impact imposed by private entrepreneurs in promoting sharper business cycle volatility. Consequently, I also conduct a structural analysis through which instead of using a measure of ownership of the real sector as a proxy for the relevance of entrepreneurial risk aversion, I estimate the model's risk-aversion coefficient (γ) that is consistent with an economy's observed fluctuation of output. That is, I estimate the structural parameters of the dynamic model that I introduce in Section 2 using observed data for the model's main variables; namely output, investment and consumption. Intuitively, if an economy is mostly composed of corporations (such as the U.S.) and so the importance of frictions imposed by risk-averse entrepreneurs is relatively small, we should see this economy behave more closely to one with risk neutral agents (that is, the estimated γ should not be significantly different from zero). Conversely, an economy where private entrepreneurs are predominant and so risk aversion is likely to impose stronger impacts, a positive coefficient of risk aversion should be found. The outline of this paper is as follows. The next section describes the dynamic model and its theoretical implications; the following two sections introduce a reduced-form empirical analysis using international data and then conducts a structural empirical analysis of the risk-aversion assumption. The last section 4 provides some concluding remarks. THE SUPPLY OF CAPITAL, AGGREGATE EFFECTS

AND DYNAMICS


The theoretical framework is based on Pardo (2012), who builds upon Cespedes, Chang and Velasco (2004) and Bernanke et al. (1999). In order to focus this paper's attention on the model's empirical implication, which is that GDP growth volatility, all else equal, should be associated with the ownership structure of the productive sector, this section briefly describes the model in which frictions between risk-averse entrepreneurs and lenders may lead to the aforementioned aggregate effects, while leaving further discussion and a more detailed description of the model in 5. The first step is to introduce the context in which an international lender and a domestic borrower optimally interact and, as a consequence of asymmetric information and entrepreneurial risk aversion, a risk premium arises. The contract between entrepreneurs and lenders, which eventually yields the economy's capital supply, involves the following features: (i) entrepreneurs produce capital goods (such as plant and equipment) that domestic firms rent in order to produce final goods; (ii) entrepreneurs (or capitalists) finance their capital investments using both their internal net worth and borrowed funds denominated in foreign currency; (iii) competitive risk-neutral international lenders provide financing to entrepreneurs for which they receive a contracted interest rate; and (iv) the contractual relationship between borrowers and lenders is subject to informational frictions in that the effective profitability of capital production is ex-ante unknown and ex-post observed only by entrepreneurs, unless lenders pay an auditing cost (Townsend, 1979). The optimal contract implies the following equilibrium results: (i) lenders charge a premium that is higher than the opportunity cost of lending due to the agency costs that arise from costly entrepreneurial bankruptcy, denoted the external finance premium; (ii) risk-averse entrepreneurs seek self-insurance against low state of nature; (iii) hedging is incomplete as entrepreneurs optimally and willingly accept some uncertainty in order to maintain some information as private, namely the upper side of the distribution of capital returns; (iv) risk-averse entrepreneurs internalize the utility associated with facing uncertain returns and for which they require a premium on top of the pecuniary borrowing costs, denoted the private equity premium; (v) the capital rental rate that entrepreneurs charge captures both the external finance premium and the private equity premium; (vi) all else equal, a risk-averse entrepreneur requires a higher expected capital return than a risk-neutral entrepreneur, or equivalently, given a capital rental rate, an entrepreneur is willing to supply less capital to final goods firms; and (vii) any drop in entrepreneurial net worth, say as a consequence of an adverse shock, affects both premiums: the external finance premium due to increased agency costs as entrepreneurs rely more on external rather than internal funds, and the private equity

premium, as the entrepreneurs' minimum guaranteed consumption level falls and so their effective level of risk aversion increases. The next step is to introduce the dynamics and aggregate effects of the derived supply of capital in the context of an open economy dynamic general equilibrium framework. The main elements that this model comprises include: (i) the domestic economy produces a final good using labor and capital supplied by workers and entrepreneurs, respectively; (ii) domestic firms maximize profits by optimally choosing capital, labor and output; (iii) the firm optimality conditions yield the economy's demand for capital, which together with the supply of capital, determine the economy's equilibrium capital investment and rental rate; (iv) workers maximize utility over consumption and leisure subject to a budget constraint; (v) the monetary authority uses its policy instruments to maintain the domestic price level constant while letting the exchange rate freely fluctuate; and (vi) the model closes by imposing domestic and external market clearing conditions. The predicted effects of an unexpected shock on the economy are as follows. Say that an unexpected decrease in the foreign demand for domestic goods takes place. The drop in exports produces a decrease in output demand and, in particular, in planned capital investment demand. The corresponding drop in domestic expenditure produces an instantaneous real depreciation of the local currency, which reduces the entrepreneur's net worth by increasing the domestic currency value of debt repayment, which is denominated in foreign currency. As a consequence, both the external finance premium and the private equity premium increase, further impacting planned investment decisions and the real exchange rate. That is, the shock together with entrepreneurial risk aversion should produce a magnified short-term effect on capital investment and output. The predicted implication suggests that business cycles should be more volatile in economies where non-publicly traded private firms are relatively more important than in economies where publicly-traded corporations are relatively more important, all else equal. This result arises from the fact that risk aversion and thus the private equity premium are more relevant to privately-held companies than to, say, corporations, which are usually owned by multiple large investors. Recall that given the observed high concentration of ownership of privately-held companies and their importance in the owners' portfolios, private entrepreneurs become highly vulnerable to project-specific risks and thus are forced to internalize the cost of volatility more (Moskowitz and Vissing-Jørgensen, 2002).

EMPIRICAL EVIDENCE:

REDUCED-FORM APPROACH


This model, like others that examine the impact of financial frictions on business cycles, predict that more leveraged economies tend to present stronger business cycle fluctuations, as higher reliance on debt rather than internal wealth translates into a higher external finance premium. In addition, the model in this paper particularly stresses the role played by risk-averse entrepreneurs in that the private equity premium may also be responsible for creating even sharper business cycle fluctuations. This section attempts to empirically test this model's main predictions. In particular, using international data, I look at the reduced-form cross-sectional association between business cycle volatility and the ownership structure of the economy's capital-producing sector, controlling for the financial development, leverage and other sources of uncertainty. Specifically, I test whether business cycle volatility, all else equal, is more pronounced where the privately-owned private sector represents a larger fraction of their economic activity of a country, relative to where the corporate sector predominates. The Data I use the standard deviation of per capita GDP growth to measure business cycle volatility.3 I obtain data for this variable from the International Financial Statistics (IFS) of the International Monetary Fund. To capture leverage, I employ the investment to capital ratio estimated by Albuquerque and Wang (2008) (QK/PN).4 In order to account for the relative importance of the privately-owned sector, I use cross-country data on a financial structure definition constructed by Levine (2002). This measure, called Structure-size (STSIZE), is an index of the relative size of stock markets vs. bank credit to the private sector. The main principle behind this measure is that an economy will have a larger index the greater the importance of the corporate sector relative to the privately-owned sector in its financial structure. Therefore, this model predicts a negative coefficient on this variable. This measure, however, harbors some limitations. For instance, even though this index measures the relative importance of the two markets, it can only serve as a proxy for the relative importance of the flow of new equity and credit to businesses. No clear bias can be ex-ante identified as consequence of this measurement error. In addition, due to its role of facilitating the optimal allocation of funds and risk pooling, the different levels of development of financial markets should in theory imply differences in how risk is managed and diversified, thus also affecting GDP growth volatility. To this goal, I have included an index of financial development as an explanatory variable both by itself and multiplied by the financial structure variables in order to explore an interaction effect. I use as the

index of financial development the ratio of the stock market liquidity to costs in the banking sector as a measure of efficiency in the financial market, as in Levine (2002). Empirically, however, there is no clear evidence of a significant link between financial development and economic growth volatility. Some studies have found that financial development does dampen GDP growth volatility (Wahid and Jalil, 2010; Denizer, Iyigun and Owen, 2002), while others have obtained no robust relationship (Beck, Lundberg and Majnoni, 2006). Consequently, there is no unambiguous ex-ante way that differences in financial development may affect GDP growth volatility in the context of this model. As in previous studies, I control for other cross-country sources of uncertainty. To account for aggregate monetary uncertainty, I use the average inflation rate for the period 1985-2006 (INFAVE) and inflation volatility for the same period (INFSTD). In terms of uncertainty associated with international trade, I use the volatility of the real exchange rate (RERSTD) and the degree of openness of the economy, as measured by the share of the sum of exports and imports to GDP (TRADE). All these series come from either the International Financial Statistics (IFS) of the IMF or the World Development Indicators (WDI) of the World Bank. Finally, in order to account for the uncertainty caused by government institutions, as in Albuquerque and Wang (2008), I employ a measure of government spending volatility (GOVSTD), an index of corruption (CORRUPT) and an index of government stability (GOVSTAB).5 The first series is obtained from the IFS while the last two series come from the International Country Risk Guide (ICRG) of the Political Risk Service Group. Results Table 1 shows the results from estimating the relationship between output growth volatility, firm leverage (QK/PN) and the measure of relative importance of the corporate sector in the financial market (STSIZE), while controlling for different sets of exogenous sources of volatility. In regression (1), I examine the impact of leverage and the relative size of the corporate sector on volatility, initially controlling only for monetary shock variables: the average inflation level (INFAVE) and its volatility (INFSTD). Only the estimated coefficients for the inflation variables have the predicted sign and statistical significance. Regression (2) include the volatility induced by openness to international markets, as captured by the volatility of the real exchange rate (RERSTD) and the trade to GDP ratio (TRADE). Regressions (3) additionally considers the volatility induced by the government. In both regressions (2) and (3), the coefficients for the relative importance of the corporate sector have the expected sign and statistical significance. In regressions (4) and (5), I split the sample in order to track


groups with high and low entrepreneurial importance base on their “Total Entrepreneurial Activity" index (TEA) separately. Results are not unambiguous. While the volatility-reducing impact of the relative importance of the corporate sector is stronger for countries with lower entrepreneurial activity (STSIZE1) than those with higher entrepreneurial activity (STSIZE2), the difference of these values, however, is not statistically significant. The lack of significance maybe partially explained by the low number of observations. Finally, regression (6) considers the impact of differences in financial development and GDP growth volatility across countries, either directly or through its interaction with the financial structure variable. As commonly found in the literature, results do not show evidence of a significant role played by capital markets in affecting growth volatility. The above results suggest that the volatility of GDP growth is indeed negatively associated with the relative importance of the corporate sector in the financial market, holding overall leverage, financial development and other sources of volatility constant. That is, these results are consistent with this model's main prediction that a relatively larger entrepreneurial sector should increase volatility, all else equal.6 In addition, results are also consistent with the more standard prediction that more leverage should significantly increase volatility. The main limitations of the reduced-form approach is that the existence of a statistical relationship between volatility and ownership structure does not indicate how strong the role of entrepreneurial risk aversion is in promoting sharper business cycles fluctuations. This shortcoming can be addressed through a structural empirical analysis.

EMPIRICAL EVIDENCE: STRUCTURAL APPROACH

Given the reduced-form analysis' limitation in providing clear empirical evidence about the magnitude of the role of entrepreneurial risk aversion in affecting business cycles, this section attempts to estimate the coefficient of risk aversion (γ ) that would be consistent with observed fluctuations in output and other variables experienced by individual economies. A positive coefficient would signal that entrepreneurial risk aversion is indeed a necessary feature of the model in order to replicate the observed path of real variables. A coefficient not significantly different from zero, on the other hand, would imply that risk aversion is irrelevant in explaining a country's business cycle. Consequently, the objective of this section is two-fold: (i) to estimate the main structural parameters of the model, in particular the risk-aversion coefficients (γ ) that are consistent with 12 economies' observed paths of real

variables such as output, consumption and investment: Argentina, Brazil, Canada, Chile, France, Germany, Japan, South Korea, Mexico, Thailand, the U.K. and the U.S.7; (ii) to provide cross-country comparisons for consideration. As results in Section 3.1 suggest, the role of risk-averse entrepreneurs in causing sharper business cycle fluctuations is likely to be more significant in economies where the privately-owned private sector represents a relatively larger fraction of the real sector. In contrast, for countries like the U.S., where the corporate sector is more important, we should observe this economy behave more closely to one with risk-neutral agents. Therefore, the null hypotheses are (i) that the estimated risk-aversion coefficient is significantly greater than zero, and (ii) that it is higher for countries in which privately-held economies predominate like, say, Mexico, Chile, Thailand or Korea, when compared to corporate-intensive economies like the U.S. In short, the way this estimation procedure works is the following. The model's non-standard parameters are initially calibrated using observed data on each economy. Calibration details are presented in 7. Subsequently, the mathematical package DYNARE, which is commonly used for simulation and estimation of rational expectation models, solves the dynamic model presented in 5 and obtains the policy function of its choice variables, given the realization of the stochastic shocks and an initial choice of parameters values. Then, using Bayesian methods, the package uses real data in order to estimate the value of select parameters that best match the observed path followed by some of the model's main variables. The following section introduces the dataset and the parameters to be estimated. The Data Besides the risk-aversion coefficient (γ), the parameters I estimate in this section are the share of domestic goods in total expenditure (θ) and the three parameters that are initially obtained through calibration: the default cost rate (μ), the entrepreneurial saving rate (δ) and the variance of capital returns (σω2). Given that the model has three shock parameters (the multifactor productivity parameter, A; the international risk-free rate, ρ; and foreign demand for domestic goods, X), only three data vectors can be used in order to avoid stochastic singularity (Juillard, 2004). As a result, I use time series on real output (Y), consumption (C) and physical capital investment (K) to conduct the estimations.8 Data for France, Germany, Japan and the U.K. come from Eurostat. Data for Brazil, Korea and Mexico were obtained from the IMF's International Financial Statistics (IFS). In addition, I obtain


Argentinean data from Argentina's Instituto Nacional de Estadística y Censos (INDEC), Chilean data from the Central Bank of Chile, Canadian data from OECD.Stat Extracts, Thailand's data from Office of The National Economic and Social Development Board, Thailand, and U.S. data comes the U.S. Bureau of Economic Analysis (BEA). The frequency of data is quarterly and, in order to facilitate cross-country comparison, the data range from 1995.1 to 2011.4 for all 12 economies. In addition, I use the Hodrick-Prescott filter in order to extract the trend of all series and then transform the series in terms of the percentage deviations from their trends. Priors The structural estimation procedure requires setting prior assumptions for the parameters' distribution, mean and standard deviation. Most of the mean values were obtained or chosen in the calibration procedure presented in 7 (see Table 4 for a summary of results). For the risk-aversion coefficient (γ), for instance, I use the normal distribution around the initially assumed mean value of 2 for all countries. The standard deviation is set high enough in order to allow for higher flexibility in the estimation. For the expenditure share of domestic goods in home consumption parameter (θ), I also assume a normal distribution with a prior mean of 0.6 and standard deviation of 0.3 for all countries.9 Mean and standard deviation values for the remaining variables to be estimated were set according to calibration and specific to each country. The bankruptcy cost parameter (μ) and the variance of capital returns (σω2) were assumed to follow an inverse gamma distribution in order to ensure positive estimates. The standard deviations for these variables were set at values equal to roughly one half of their prior means. Finally, the entrepreneurial saving rate (δ) follows a normal distribution with rather low standard deviations (between 0.05 and 0.1), in order to avoid the possibility of saving rates greater than one. With respect to the shock parameters, I use uniform distribution for their standard deviations (σ) and persistence parameters (φ). Their lower and upper bounds were set loosely equal to 0 and 1, respectively. The first four columns of Table 2 summarize the parameters' prior distribution, mean and standard deviation. Results The last three columns of Table 2 present the parameter estimations computed using the Bayesian method. The first column contains the estimated mean, while the last two show the 5th and 95th percentiles of the posterior distributions. The

bottom of each table contains the value of the marginal likelihood, computed with the Laplace approximation. Turning to the risk-aversion coefficient, as observed in Table 2, while the posterior values for γ are positive for Argentina, Brazil, Canada, Chile, Germany, Korea, Mexico and Thailand, they are not statistically different from zero for the cases of France, Japan, the U.S. and the U.K. One may have not expected Canada and Germany to belong to the group with positive γ parameters; however one may also notice that their values are statistically lower than the values for γ of any country in that group. In general, the fact that the posterior γ is statistically higher for countries like Argentina, Brazil, Chile, Korea, Mexico and Thailand than for Canada, France, Germany, the U.K. and the U.S. suggests that this model requires a higher risk-aversion coefficient in order to explain the responses to shocks followed by some economies than for others. Similarly, one may observe that not all the estimated mean values for γ can be statistically distinguished among countries. For instance, though France presents the lowest mean value for γ, its estimate is not statistically different from those found for Japan, the U.S. or the U.K. Equivalently, though Korea presents the highest mean values for γ, its estimate is not statistically different from those found for Argentina or Brazil. In addition, the estimate of γ for Japan cannot be statistically distinguished from any of the countries in the group of economies with positive γ, except for Korea. The result above supports the idea that entrepreneurial risk neutrality may be an assumption that more closely reassembles economies that are more corporate-intensive than predominantly privately-held. Put differently, entrepreneurial risk aversion is realistic and statistically significant in explaining output fluctuations for economies that are more heavily composed of privately-held firms, but not so much for economies where the corporate sector is relatively more important. That is, these results suggest that risk aversion on the part of entrepreneurs not only makes sense in theory for some economies, but also presents empirical relevance. The values of the other coefficients are mostly close to their corresponding prior values, which came from the calibration procedures described in 7. One exception is the coefficient on the share of domestic goods in consumption (θ), which tends to be greater than the uniformly assumed value of 0.6 for developed countries and lower for less developed countries. This result is consistent with the empirical evidence that bias towards domestic goods weakens in emerging markets relative to developed countries. Wang and Chen (2004) discuss and provide evidence that issues like lack of trust of goods manufactured in developing countries and the


documented consumption home bias among OECD countries are behind this result. With respect to the shock variables, the estimated standard deviations and persistence parameters tend to differ with respect to the shock and across countries. In general, however, shocks are on average stronger in emerging economies than in more advanced economies (as captured by their standard deviations σX, σρ and

σA), however less persistent (as given by their autocorrelation coefficients φX, φρ and

φA. The difference in volatility and persistence of shocks towards stronger but less persistent values for less developed economies is also consistent with previous literature. For instance, Mendoza (1995) finds that terms of trade shocks are on average almost three times more volatile however less persistent in emerging markets relative to developed countries. The parameter μ is one that seemingly departs from previously estimates values. For instance, Bernanke et al. (1999) and Carlstrom and Fuerst (1997) find that for the United States, μ = 0.12 and μ = 0.20, respectively, while I found from both calibration and estimation than its value is considerably lower. One of the factors that may explain this difference is that in both Bernanke et al. (1999) and Carlstrom and Fuerst (1997), μ represents costs of bankruptcy, while in this model μ captures the costs of default. Given that bankruptcy implies default while default does not necessarily imply bankruptcy, it follows that the costs of default should be lower than those of bankruptcy.

CONCLUDING REMARKS Evidence has shown that economies can still respond strongly to shocks even in the absence of noticeable flaws in their financial and/or productive sectors. A possible answer to this apparent puzzle may lie in the role of private entrepreneurs. This sector has evidenced signals of rapid transitions from euphoria during booms to deep depression in even mild recessions in some economies. Consequently, their behavior towards the exposure to risk may be an additional source of amplification of shocks in an economy. Risk aversion on the part of private entrepreneurs implies that entrepreneurs internalize the cost of the uncertainty of their investment returns, for which they require an extra premium: the private equity premium. A microeconomic analysis of the optimal relationship between lenders and entrepreneurs under asymmetric information shows that the rate at which entrepreneurs rent capital to final goods firms (R) incorporates this premium. As a consequence, a positive premium translates into a more constrained capital supply. In addition, this premium may further amplify shocks in general equilibrium. Specifically, entrepreneurial activity

may respond to shocks as changes in net worth would impact their effective level of risk aversion in the opposite direction. The corresponding effect on the private equity premium further impacts the economy's capital supply and thus production. A corollary to this result is the fact that higher output volatility should be more prevalent in countries where private entrepreneurs are likely to be relatively more important actors of an economy. That is, economies with a relatively higher share of privately-held companies, all else equal, should exhibit sharper business cycles than economies with a private sector composed more importantly of publicly traded companies. Put differently, two otherwise similar economies subject to similar real shocks may respond differently to these shocks due to differences in the ownership structure of the real sector. This paper empirically tests the above implication and finds evidence to suggest the hypothesis that risk aversion may matter. I first approach this issue by conducting a simple reduced-form regression analysis to examine the cross-country empirical connection between GDP growth volatility and the general ownership structure of the real sector. Results suggest that a statistically significant relationship exists when controlling for other relevant variables, like financial development, leverage and other cross-country sources of uncertainty. To provide further evidence on the magnitude of the role of entrepreneurial risk aversion in affecting business cycles fluctuations, I also execute an empirical analysis of the structural parameters of the model. In particular, I estimate the risk aversion coefficient that would generate business cycles which best match the observed real fluctuations. Empirical results for 12 countries signal that the risk-aversion assumption is macroeconomically more relevant for small open economies like Argentina, Brazil, Chile, Mexico, Korea and Thailand (which present relatively stronger privately-held sectors) than for Canada, France, Germany, the U.K. and the U.S. (where the corporate sector is relatively more important). In terms of policy implications, improvements in information technology and transparency in the privately-owned sector that could alleviate agency costs may reduce the importance of asymmetric information in generating volatility. In addition, entrepreneurial risk aversion will play a lesser role as more established businesses become public. Therefore, policies encouraging the participation of investors in the ownership of firms, for instance through private equity firms, may help reduce the volatility associated with entrepreneurial risk aversion.


Figure 1: Scatter plot and linear fit of the volatility of GDP growth on total entrepreneurial activity.


Table 1: OLS Estimates of Standard Deviation of Per Capita Real GDP Growth

Variable (1) (2) (3) (4) (5) (6) QK/PN -6.1030 3.1022** 4.700** 5.6532 5.9117* 3.9861**

12.065 1.2218 1.5297 2.2419 3.0158 1.9727 STSIZE -0.0514 -0.0093** -0.0108** -0.0144** 0.0501 0.0038 0.0038 0.0066 STSIZE1 -0.0131** 0.0048 STSIZE2 -0.0093 0.0093 INFSTD 0.2770** 0.7893** 0.7535** 0.6324** 1.3930** 0.7349** 0.0402 0.0461 0.0550 0.1135 0.8700 0.0857 INFAVE 1.2297** 0.0836 0.2753** 0.5384 -0.1047 0.3201* 0.1012 0.1019 0.1336 0.3169 0.8218 0.1899 RERSTD 0.0003 0.0004 0.0017 0.001 0.0004 0.0009 0.0009 0.0014 0.0018 0.0009 TRADE 0.0002* 0.0002* 0.0002* 3.6E-6 0.0002* 0.0001 0.0001 0.0001 0.0004 0.0001 GOVSTAB 0.0026 -0.0192 0.0145 0.0005 0.0055 0.0099 0.0103 0.0070 GOVSTD -0.3378 -0.5655 0.3571 -0.2655 0.3256 0.3433 1.7343 0.3712 CORRUPT 0.0075 0.0200* 0.0025 0.0073 0.0050 0.0083 0.0102 0.0053 FDEV 0.0033 0.0051 STSIZE*FDEV 0.0021

0.0050 Intercept 0.6140 -0.3378** -0.5652** -0.5677** -0.7808** -0.4800** 1.3061 0.1250 0.1656 0.2325 0.3421 0.2197 # of Obs. 34 28 28 14 14 28 Adjusted R2 0.9939 0.9822 0.9835 0.9955 0.7044 0.9820

Notes: Variables are the capital to net worth ratio (QK/PN), the measure of the relative importance of the corporate sector (STSIZE), the volatility of inflation (INFSTD), average inflation (INFAVE), the volatility of the real exchange rate (RERSTD), trade openness (TRADE), an index of government stability (GOVSTAB), the volatility of real government spending (GOVSTD), the degree of corruption (CORRUPT), and an index of efficiency of the domestic financial market (FDEV). Numbers below the coefficient estimates correspond to the standard errors.


Table 2: Bayesian Estimation ARGENTINA

Prior Posterior

Parameter Distrib. Mean Std. dev Mean Confidence interval γ normal 2 2 2.7859 1.9004 3.9440

σ2ω inv gamma 0.009 0.0044 0.0077 0.0049 0.0102 μ inv gamma 0.028 0.014 0.0274 0.0187 0.0340 δ gamma 0.947 0.05 0.8431 0.7976 0.8924 θ normal 0.6 0.05 0.6684 0.6423 0.7063

φX uniform 0.5 0.2887 0.6522 0.6098 0.6873 φA uniform 0.5 0.2887 0.1455 0.0232 0.2810 φρ uniform 0.5 0.2887 0.2809 0.0790 0.4858 σX uniform 0.5 0.2887 0.2919 0.2578 0.3435 σA uniform 0.5 0.2887 0.0586 0.0516 0.0663 σρ uniform 0.5 0.2887 0.0151 0.0133 0.0167

Marginal Likelihood: 345.39

BRAZIL

Prior Posterior





CANADA

Prior Posterior






CHILE

Prior Posterior





FRANCE

Prior Posterior

Parameter Distrib. Mean Std. dev Mean Confidence interval γ normal 2 4 -0.2102 -0.5691 0.0535




GERMANY

Prior Posterior






JAPAN

Prior Posterior

Parameter Distrib. Mean Std. dev Mean Confidence interval γ normal 2 4 0.9690 -0.4808 2.2994




KOREA

Prior Posterior





MEXICO

Prior Posterior






THAILAND

Prior Posterior





U.K.

Prior Posterior

Parameter Distrib. Mean Std. dev Mean Confidence interval γ normal 2 4 -0.0299 -0.8155 0.9308




U.S.

Prior Posterior

Parameter Distrib. Mean Std. dev Mean Confidence interval γ normal 2 3 -0.1481 -1.0452 0.4725 μ inv gamma 0.02 0.0101 0.0159 0.0125 0.0200

σ2ω inv gamma 0.005 0.0024 0.0039 0.0035 0.0046 δ gamma 0.948 0.05 0.9711 0.9511 1.0020

φA uniform 0.5 0.2887 0.0028 0.0001 0.0050 σA uniform 0.5 0.2887 0.0075 0.0039 0.0124

Marginal Likelihood: 190.14 Note: Dependent variables: Y, K and C. The intervals correspond to the 5th and 95th percentiles of the posterior distributions.


Table 3: Calibration Parameter Values and Sources

Country Parameter Value Sources Argentina Default probability 3% Lizarazo (2011) Argentina Risk premium 2.85% Ministerio de Economia (Argentina); Glen and Mondragon-Velez (2011) Argentina Capital to net worth ratio 1.646 Cespedes, Gonzalez and Molina (2010) Brazil Default probability 4% Souza-Sobrinho (2010) Brazil Risk premium 36.62% World Development Indicators (WDI) Brazil Capital to net worth ratio 2.7 Terra (2009) Canada Default probability 7% Aretz and Pope (2007) Canada Risk premium 1.521% World Development Indicators (WDI) Canada Capital to net worth ratio 1.463 Goyal and Wang (2011)

Chile Default probability 9% Calvo, Drexler, Flores and Pacheco (2009) Chile Risk premium 2.12% Central Bank of Chile Chile Capital to net worth ratio 1.612 Fernandez (2005) France Default probability 6% Aretz and Pope (2007) France Risk premium 3.145% World Development Indicators (WDI) France Capital to net worth ratio 1.818 Mefteh and Oliver (2007) Germany Default probability 9% Aretz and Pope (2007) Germany Risk premium 6.727% World Development Indicators (WDI) Germany Capital to net worth ratio 1.314 Niu (2009) Japan Default probability 4% Aretz and Pope (2007) Japan Risk premium 2.13% World Development Indicators (WDI) Japan Capital to net worth ratio 1.481 Bartram, Brown and Fehle (2009) Korea Default probability 2.72% Gertler, Gilchrist and Natalucci (2007) Korea Risk premium 3.5% Gertler et al. (2007) Korea Capital to net worth ratio 2.1 Gertler et al. (2007) Mexico Default probability 4.74% Rocha and Garcia (2004) Mexico Risk premium 1.747% World Development Indicators (WDI) Mexico Capital to net worth ratio 1.424 Cespedes et al. (2010) Thailand Default probability 8.7% Sandstrom (2006) Thailand Risk premium 5.369% World Development Indicators (WDI) Thailand Capital to net worth ratio 1.988 Chorruk and Worthington (2010) U.K. Default probability 3% Aretz and Pope (2007) U.K. Risk premium 1.499% UK Debt Management Offfice; Bank of England U.K. Capital to net worth ratio 1.202 Niu (2009) U.S. Default probability 2% Bernanke et al. (1999); Fisher (1998) U.S. Risk premium 2% Bernanke et al. (1999) U.S. Capital to net worth ratio 2 Bernanke et al. (1999)


Table 4: Calibration.

Common Parameters Parameter Description Value

α share of capital to output 0.35 γ coefficient of risk aversion 2 β discount factor 0.99 Υ labor supply elasticity parameter 4/3 θ domestic goods to total expenditure ratio 0.6

Country Parameters

Country Parameter Description Argentina Brazil Canada Chile

µ default cost rate 0.0285 0.7750 0.0127 0.0185 δ entrepreneur saving rate 0.9471 0.5205 0.9698 0.9594

σω volatility 0.0936 0.2350 0.0876 0.0842 Country France Germany Japan Korea


σω volatility 0.0980 0.2039 0.0875 0.0916 Country Mexico Thailand U.K. U.S.


σω volatility 0.0781 0.1193 0.0814 0.0705

Table 5: Implied steady state values Parameter Description Value Argentina Brazil Canada Chile

κ capital to net worth ratio 1.647 2.694 1.437 1.617 H(ŵ) default rate 2.999% 4.017% 6.923% 7.93%

R − (1 + ρ) overall risk premium 2.849% 36.603% 1.537% 2.14% QK/Y capital to output ratio 33.70% 25.50% 34.13% 33.94% QC/Y consumption to output ratio 65.00% 65.00% 65.00% 65.0% SX/Y exports to output ratio 40.78% 45.70% 40.52% 40.64%

x insurance rate 476.38% 43.62% 88.32% 83.88% France Germany Japan Korea

κ capital to net worth ratio 1.860 1.306 1.463 2.1 H(ŵ) default rate 6.053% 8

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