1st COURSE: DYNAMIC PANEL DATA METHODS |
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7th COURSE: DATA MANAGEMENT AND PANEL DATA MODELS
Table of contents |
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1. Introduction
The aim of this course is to communicate the skills necessary to understand and assess the applications of panel data analysis reported in the Business Economics literature, and to provide skills which could be applied to analyzing a variety of research and policy problems related to Business Economics. The course is intended as an introduction to the issues and opportunities arising when a panel data structure is available. In particular, the course covers the different structures of data and the advantages and limitations of panel data. Additionally, a new approach to modern econometric analysis is provided, highlighting the role of conditional expectations. Both static and dynamic models for panel data analysis are presented, with special attention to choosing the most suitable estimator for each model. As a result, the course focuses on the decisions that the researcher should make instead of the algebraic derivation of the models. Moreover, several cases on how to derive economic models combining panel data and Stata ® are discussed. Finally, the efficient research process using panel data and Stata ® is shown by analyzing a case.
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2. Structure of the Course
PART I. ECONOMETRIC MODELS FOR PANEL DATA |
Lesson 1. |
Estimation Methods: Endogeneity and Instrumental Variables |
1.1. |
Data Structures |
1.2. |
Role of Conditional Expectations in Econometrics |
1.3. |
Linear Regression Framework |
1.4. |
The Endogeneity Problem: Sources and Responses |
1.5. |
Instrumental Variable Estimation |
1.6. |
Generalized Method of Moments |
Lesson 2. |
Introduction and Linear Static Models for Panel Data |
2.1. |
Characterizing Panel Data Methods |
2.2. |
Advantages and Limitations of Panel Data |
2.3. |
Why is the Panel Data Methodology Needed? |
2.4. |
Fixed Effects Models |
2.5. |
Random Effects Models |
2.6. |
Fixed Effects Models versus Random Effects Models |
2.7. |
Limitations of Linear Static Panel Data |
Lesson 3. |
Linear Dynamic Models for Panel Data |
3.1. |
Autoregressive Models |
3.2. |
Models with Predetermined Variables |
3.3. |
Models with Strictly Exogenous Variables |
3.4. |
System GMM |
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3.4.1. |
System GMM for Autoregressive Models |
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3.4.2. |
System GMM for Models with Predetermined Variables |
3.5. |
Specification Tests |
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3.5.1. |
Testing for Residual Serial Correlation |
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3.5.2. |
Testing for Overidentifying Restrictions |
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3.5.3. |
Incremental Sargan Tests |
Lesson 4. |
Nonlinear Panel Data Models |
4.1. |
Introduction to Discrete Response Models |
4.2. |
Fixed Effects Logit |
4.3. |
Random Effects Logit |
4.4. |
Censored Regression Models |
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PART II. PANEL DATA METHODS WITH Stata ® |
Lesson 5. |
Introduction to Data Management with Stata ® |
5.1. |
Basic Concepts |
5.2. |
Format and Content of Data Files |
5.3. |
Data Management |
5.4. |
Stata ® Work Environment: Do Files and Output Files |
5.5. |
Joining Data |
Lesson 6. |
Managing Variables for Research |
6.1. |
Types of Variables: Storage and Displaying Format |
6.2. |
Management of Variables |
6.3. |
Descriptive Analysis |
6.4. |
Creating Variables for Research |
Lesson 7. |
Advanced Operations with Stata ® |
7.1. |
Using Matrices |
7.2. |
Advanced Commands |
7.3. |
Error Messages |
7.4. |
Online Help |
Lesson 8. |
Model Estimation with Stata ® |
8.1. |
Introduction to Model Estimation with Stata ® |
8.2. |
Estimation of Linear Static Models for Panel Data |
8.3. |
Estimation of Linear Dynamic Models for Panel Data |
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8.3.1. |
The Difference GMM Estimator |
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8.3.2. |
The System GMM Estimator |
8.4. |
Estimation of Nonlinear Panel Data Models |
Lesson 9. |
Deriving Economic Models Combining Panel Data and Stata ®: Case Analyses |
9.1. |
Improving Previous Models |
9.2. |
Computing Parameters and Elasticities |
9.3. |
Implementing New Research Strategies |
9.4. |
Obtaining the Optimal Value of Parameters |
Appendix A. |
Panel Data and Publication |
A.1. |
Explaining the Panel Data Methodology in the Paper |
A.2. |
How to Answer Referees' Questions on the Methodology |
A.3. |
Comparison between Estimators |
Lesson 10. |
Efficient Research Process by Using Panel Data and Stata ®: A Case Analysis |
10.1. |
Collecting the Data |
10.2. |
Joining the Data |
10.3. |
Constructing Variables |
10.4. |
Constructing Variables by Using Estimation Results |
10.5. |
Panel Data Structure and Variable Analysis |
10.6. |
Estimation of the Model |
10.7. |
Process of Incorporating New Ideas |
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3. References
Main References
- Arellano, M. (2003): Panel Data Econometrics (Advanced Texts in Econometrics), Oxford University Press.
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Baum, C., M. Schaffer and S. Stillman (2011): "Using Stata for Applied Research: Reviewing its Capabilities", Journal of Economic Surveys, 25 (2), 380-394.
- Bond, S.R. (2002): "Dynamic Panel Data Models: A Guide to Micro Data Methods and Practice". Cemmap Working Paper Series No. CWP09/02, Institute for Fiscal Studies, London.
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Greene, W. (2008): Econometric Analysis (5th Edition), Prentice Hall.
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Petersen, M.A. (2009): "Estimating Standard Errors in Finance Panel Data Sets: Comparing Approaches", The Review of Financial Studies, 22 (1), 436-480.
- Pindado, J. and I. Requejo (2012): "Panel Data: A Methodology for Model Specification and Testing". In Wiley Encyclopedia of Management, 3rd Edition. John Wiley & Sons, Ltd (in press).
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Roodman, D. (2009): "How to do xtabond2: An Introduction to Difference and System GMM in Stata", The Stata Journal, 9 (1), 86-136.
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Roodman, D. (2009): "A Note on the Theme of Too Many Instruments", Oxford Bulletin of Economics and Statistics, 71 (1), 135-158.
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Wooldridge, J.M. (2002): Econometric Analysis of Cross Section and Panel Data, MIT Press.
Additional References
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Ahn, S.C. and P. Schmidt (1995): "Efficient Estimation of Models for Dynamic Panel Data", Journal of Econometrics, 68, 5-28.
- Anderson, T.W. and C. Hsiao (1981): "Estimation of Dynamic Models with Error Components", Journal of the American Statistical Association, 76, 598-606.
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Anderson, T.W. and C. Hsiao (1982): "Formulation and Estimation of Dynamic Models using Panel Data", Journal of Econometrics, 18, 47-82.
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Arellano, M. and O. Bover (1995): "Another Look at the Instrumental Variable Estimation of Error-Components Models", Journal of Econometrics, 68, 29-51.
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Arellano, M. and S. Bond (1991): "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations", Review of Economic Studies, 58, 277-297.
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Baltagi, B.H. (2005): "Econometric Analysis of Panel Data", Wiley.
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Blundell, R.W. and S.R. Bond (1998): "Initial Conditions and Moment Restrictions in Dynamic Panel Data Models", Journal of Econometrics, 87, 115-143.
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Bover, O. and M. Arellano (1997): "Estimating Dynamic Limited Dependent Variable Models from Panel Data", Investigaciones Economicas, 21, 141-165.
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Chamberlain, G. (1980): "Analysis of Covariance with Qualitative Data", Review of Economic Studies, 47, 225-238.
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Chamberlain, G. (1984): "Panel Data". In Griliches, Z. and M.D. Intriligator (comp.), Handbook of Econometrics Vol. 2, North-Holland, Amsterdam.
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Flannery, M.J. and K.W. Hankins (2013): “Estimating Dynamic Panel Models in Corporate Finance”, Journal of Corporate Finance, 19, 1-19.
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Giroud, X., H.M. Mueller, A. Stomper and A.Westerkamp (2012): “Snow and Leverage”, Review of Financial Studies, 25 (3), 680-710.
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Doornik, J., M. Arellano and S. Bond (1999): "Panel Data Estimation using DPD for Ox". Working paper Nuffield College, Oxford.
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Hausman, J.A. (1978): "Specification Tests in Econometrics", Econometrica, 46, 1251-1272.
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Hillier, D., J. Pindado, V. de Queiroz and C. de la Torre (2011): "The Impact of Country-level Corporate Governance on Research and Development", Journal of International Business Studies, 42, 76-98.
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Hsiao, C. (1990): Analysis of Panel Data. Cambridge University Press, Cambridge.
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Larcker, D.F. and T.O. Rusticus (2010): "On the Use of Instrumental Variables in Accounting Research", Journal of Accounting and Economics, 49, 186-205.
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Maestro, M and J. Pindado (2005): "Capital Structure and Stock Prices: Additional Evidence", Applied Financial Economics Letters, 1, 355-360.
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Miguel, A. and J. Pindado (2001): "Determinants of Capital Structure: New Evidence from Spanish Panel Data", Journal of Corporate Finance, 7, 77-99.
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Miguel, A., J. Pindado, and C. de la Torre (2004): "Ownership Structure and Firm Value: New Evidence from the Spanish Case", Strategic Management Journal, 25, 1199-1207.
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Miguel, A., J. Pindado and C. de la Torre (2005): "How do Entrenchment and Expropriation Phenomena Affect Control Mechanisms?", Corporate Governance: An International Review, 13, 505-516.
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Mundlak, Y. (1961): "Empirical Production Function Free of Management Bias", Journal of Farm Economics, 43, 44-56.
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Pindado, J., V. de Queiroz and C. de la Torre (2010): "How do Firm Characteristics Influence the Relationship between R&D and Firm Value?", Financial Management, 39 (2), 757-782.
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Pindado, J., I. Requejo and C. de la Torre (2011): "Family Control and Investment-Cash Flow Sensitivity: Empirical Evidence from the Euro Zone", Journal of Corporate Finance, 17 (2), 1389-1409.
- Pindado, J., I. Requejo and C. de la Torre (2012): “Do Family Firms Use Dividend Policy as a Governance Mechanism? Evidence from the Euro Zone”, Corporate Governance: An International Review, 20 (5), 413-431.
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Pindado, J., L. Rodrigues and C. de la Torre (2008): "Estimating Financial Distress Likelihood", Journal of Business Research, 61 (9), 995-1003.
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Pindado, J. and L. Rodrigues (2005): "Determinants of financial distress costs", Financial Markets and Portfolio Management, 19 (4), 343-359.
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Windmeijer, F. (2005): "A Finite Sample Correction for the Variance of Linear Efficient Two-Step GMM Estimators", Journal of Econometrics, 126, 25-51.
- Wintoki, M.B., J.S. Linck and J.M. Netter (2012): “Endogeneity and the Dynamics of Internal Corporate Governance”, Journal of Financial Economics, 105, 581-606.
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4. Timetable
Date |
Time |
Lesson |
Lecturer |
Room |
08-07-2013
Monday |
16-20 |
Lesson 1
Lesson 2 |
Julio Pindado |
Room |
09-07-2013
Tuesday |
9-13 |
Lesson 3 (3.1-3.4) |
Julio Pindado |
Room |
09-07-2013
Tuesday |
15-18 |
Lesson 5 (5.1-5.4) |
Ignacio Requejo |
Computer Room |
10-07-2013
Wednesday |
9-11 |
Lesson 3 (3.5)
Lesson 4 |
Julio Pindado |
Room |
10-07-2013
Wednesday |
11-13 |
Lesson 8 (8.1-8.2) |
Julio Pindado |
Computer Room |
10-07-2013
Wednesday |
15-18 |
Lesson 5 (5.5)
Lesson 6 |
Ignacio Requejo |
Computer Room |
11-07-2013
Thursday |
9-13 |
Lesson 8 (8.3-8.4) |
Julio Pindado |
Computer Room |
11-07-2013
Thursday |
15-18 |
Lesson 7 |
Ignacio Requejo |
Computer Room |
12-07-2013
Friday |
9-11 |
Lesson 10 (10.1-10.3) |
Ignacio Requejo |
Computer Room |
12-07-2013
Friday |
11-14 |
Lesson 9
Appendix A
Lesson 10 (10.4-10.7) |
Julio Pindado |
Room |
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5. Brief Biographies
Julio Pindado is Professor of Accounting and Finance at Universidad de Salamanca (Spain) and Professorial Fellow of Accounting and Finance at the Division of Accounting and Finance at Leeds University Business School, University of Leeds (UK). He has published academic peer-reviewed articles on corporate finance and governance in several top journals ranked with a high impact factor in the Journal Citation Report, such as the Strategic Management Journal, Financial Management, Journal of International Business Studies, Journal of Corporate Finance and Corporate Governance: An International Review. Prof. Pindado is Advisory Editor of Frontiers in Finance and Economics, serves as a member of the Editorial Advisory Board of Journal of Financial Regulation and Compliance and Review of Behavioral Finance. Additionally, Prof. Pindado has served as a member of the Board of Directors of the European Financial Management Association (2003-2005). He has also served as instructor at the 2004 and 2007 “Merton H. Miller” Doctoral Seminar, organized by Prof. John Doukas, managing editor of European Financial Management. Prof. Pindado has also been Visiting Fellow at the Institute of Finance and Accounting at the London Business School.
E-mail: pindado@usal.es Web: http://diarium.usal.es/pindado/
Ignacio Requejo is Assistant Professor of Finance at Universidad de Salamanca (Spain). He holds a PhD degree in Business Economics with a “European Distinction” from this university. During his doctoral studies, he has stayed at Saïd Business School (University of Oxford) as a Visiting Doctoral Student and at the Centre for Corporate Governance at London Business School (University of London) as a Visiting Research Assistant. Dr. Requejo’s thesis on family firms was awarded the 2011 Best Doctoral Dissertation Award sponsored by the Family Firm Institute (FFI) and Relative Solutions. His work has been published in top finance and governance journals, including the Journal of Corporate Finance and Corporate Governance: An International Review. He has presented several papers in which the panel data methodology is used in numerous international conferences, including the Financial Management Association (FMA) International Annual Meeting, the European Financial Management Association (EFMA) Annual Conference and the Annual International Family Enterprise Research Academy (IFERA) Conference. He has also presented his work at research seminars held at Saïd Business School, London Business School, Leeds University Business School and University of Strathclyde Business School. Dr. Requejo is Visiting Lecturer at the University of Strathclyde Business School, where he has taught at the M.Sc. Investment & Finance and M.Sc. International Banking & Finance.
E-mail: irequejo@usal.es Web: http://www.irequejo.es/
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6. Academic and Research Awards
Requejo, I.: 2011 Best Doctoral Dissertation Award sponsored by the Family Firm Institute (FFI) and Relative Solutions and awarded at the 2011 FFI Annual Conference held in Boston (US) for the thesis entitled "Corporate Governance in Family Firms: Effects of Family Control on Firm Value and Corporate Financial Decisions".
Pindado, J., Requejo I. and de la Torre, C.: "GEEF" Best Policy-oriented Research Paper Award at the 10th Annual IFERA Conference, which took place between the 6th and the 9th of July 2010 in Lancaster (UK), for the paper "Family control and the investment–cash flow sensitivity: Empirical evidence from the Euro zone".
Pindado, J., Requejo I. and de la Torre, C.: "University of Alberta" Best Family Business Research Paper Award at the 8th Annual IFERA Conference, which took place between the 2nd and the 5th of July 2008 in Breukelen (The Netherlands), for the paper "Ownership concentration and firm value: Evidence from Western European family firms".
Requejo, I.: Award for the Best Paper presented at the I International Accounting & Finance Doctoral Symposium, which took place on the 16th and 17th of April 2008 in Prato (Italy), for the paper "The effect of family control on corporate performance".
Pindado, J. and de la Torre, C.: Award for the Best Paper published in the European Financial Management Journal in 2006 for the paper "The Role of Investment, Financing and Dividend Decisions in Explaining Corporate Ownership Structure: Empirical Evidence from Spain".
Pindado, J. and Rodrigues, L.: Award for the Best Paper published in the Financial Markets and Portfolio Management Journal in 2005 for the paper "Determinants of financial distress costs".
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7. Publications using the Panel Data Methodology
Pindado, J. and Requejo, I. "Panel data: a methodology for model specification and testing", in Finance volume of Wiley Encyclopedia of Management, (in press).
Bastos, R. and Pindado, J., "Trade Credit during a Financial Crisis: A Panel Data Analysis", Journal of Business Research, 2013, Vol. 66, pp. 614-620.
Pindado, J., Requejo, I. and de la Torre, C., “Do family firms use dividend policy as a governance mechanism? Evidence from the Euro Zone”, Corporate Governance: An International Review, 2012, Vol. 20, No. 5, pp. 413-431.
Pindado, J., Requejo, I. and de la Torre, C., "Family control and investment–cash flow sensitivity: Empirical evidence from the Euro zone", Journal of Corporate Finance, 2011, Vol. 17, No. 2, pp. 1389-1409.
Hillier, D., Pindado, J., de Queiroz, V. and de la Torre, C., "The Impact of Country-level Corporate Governance on Research and Development", Journal of International Business Studies, 2011, Vol. 42, No. 1, pp. 76-98.
Pindado, J. and de la Torre, C., "Capital structure: new evidence from the ownership structure", International Review of Finance, 2011, Vol. 11, No. 2, pp. 213-226.
Pindado, J., de Queiroz, V. and de la Torre, C., "How do Firm Characteristics Influence the Relationship between R&D and Firm Value?", Financial Management, 2010, Vol. 39, No. 2, pp. 757-782.
Pindado, J. and de la Torre, C., "The Effect of Ownership Structure on Underinvestment and Overinvestment: Empirical Evidence from Spain", Accounting & Finance, 2009, Vol. 49, No. 2, pp. 363-383.
Bastos, R. and Pindado, J., "Trade credit, creditor protection and accounting standards: evidence from an international sample", Revista de Economia Financiera, 2009, No. 17, pp. 10-33.
Pindado, J., Rodrigues, L. and de la Torre, C., "How do insolvency codes affect a firm's investment?", International Review of Law and Economics, 2008, Vol. 28, pp. 227-238.
Pindado, J. and de la Torre, C., "Financial Decisions as Determinants of Ownership Structure: Evidence from Spanish Family Controlled Firms", Managerial Finance, 2008, Vol. 34, No. 12, pp. 868-885.
Pindado, J., Rodrigues, L. and de la Torre, C., "Estimating Financial Distress Likelihood", Journal of Business Research, 2008, Vol. 61, No. 9, pp. 995-1003.
Bastos, R. and Pindado, J., "An agency model to explain trade credit policy and empirical evidence", Applied Economics, 2007, Vol. 39, No. 2, pp. 2631-2642.
Pindado, J. and de la Torre, C., "The Role of Investment, Financing and Dividend Decisions in Explaining Corporate Ownership Structure: Empirical Evidence from Spain", European Financial Management, 2006, Vol. 12, No. 5, pp. 661-687.
Pindado, J., Rodrigues, L. and de la Torre, C., "How does financial distress affect small firms' financial structure?", Small Business Economics: An International Journal, 2006, Vol. 26, No. 4, pp. 377-391.
Pindado, J. and Rodrigues, L., "Determinants of financial distress costs", Financial Markets and Portfolio Management, 2005, Vol. 19, No. 4, pp. 343-359.
Miguel, A., Pindado, J. and de la Torre, C., "How do entrenchment and expropriation phenomena affect control mechanisms?", Corporate Governance: An International Review, 2005, Vol. 13, No. 4, pp. 505-516.
Maestro, M. and Pindado, J., "Capital structure and stock prices: Additional evidence", Applied Financial Economics Letters, 2005, Vol. 1, No. 6, pp. 355-360.
Lozano, B., Miguel, A. and Pindado, J., "Dividend policy in regulated firms: An analysis from two agency problems", Eurasian Review of Economics and Finance, 2005, Vol. 1, No. 1, pp. 9-22.
Miguel, A., Pindado, J. and de la Torre, C., "Ownership structure and firm value: New evidence from Spain", Strategic Management Journal, 2004, Vol. 25, No. 12, pp. 1119-1207.
Pindado, J. and de la Torre, C., "Why is ownership endogenous?", Applied Economics Letters, 2004, Vol. 11, No. 14, pp. 901-904.
Morgado, A. and Pindado, J., "The underinvestment and overinvestment hypotheses: An analysis using panel data", European Financial Management, 2003, Vol. 9, No. 2, pp. 163-177.
Del Brío, E., Miguel, A. and Pindado, J., "Investment and firm value: An analysis using panel data", Applied Financial Economics, 2003, Vol.13, No. 12, pp. 893-903.
Miguel, A. and Pindado, J., "Investment decisions: Lessons from Spanish firms", The International Journal of Finance, 2003, Vol. 15, No. 1, pp. 2537-2556.
Miguel, A. and Pindado, J., "Determinants of capital structure: New evidence from Spanish panel data", Journal of Corporate Finance, 2001, Vol. 7, No. 1, pp. 77-99.
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8. Registration
To register send an email to the Director of the course (Prof. Julio Pindado E-mail: pindado@usal.es) with the following information by April 26th:
- Name and Surname
- Research Interests
- Country
- Brief Curriculum Vitae
To guarantee the quality of the course, only a maximum of 20 students will be accepted. The brief CV sent with your registration details will be the main acceptance criterion. Acceptance to the course will be communicated by May 3rd.
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9. Participation Fee
The registration fee for the course is EUR 300 and includes the course materials. Apart from a binder with the contents covered in the course, a CD will be provided with the Stata files (.do, .dta and .log) that will be used during the classes. The fee also includes a welcome coffee the first day of the course and a farewell lunch that will take place on Friday, 12th July 2013 at Apartahotel Hall88:
www.exehall88apartahotel.com/Salamanca
For those accepted to the course, details on the method of payment will be provided upon notification of acceptance.
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EXPERIENCE FROM PAST ALUMNI |
2012 Course
Fabian Bernhard INSEEC – Grande École de Commerce (France)
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"I enjoyed the course on "Data Management and Panel Data Models" as it offered a valuable mix between the theoretical background on panel data analysis techniques with its practical application in the computer lab. Although the course was primarily focused on research in the field of finance and accounting, the instructors did a great job answering questions regarding the application of the presented methods to other / related fields. It is recommended to bring sound knowledge of statistics, but experience with STATA is not necessary as the instructors provided patiently an introduction to this software. Overall, I have to say it was a great experience learning about panel data from two knowledgeable researchers. They presented many examples from their own research which made the learning experience even more interesting. The course was well organized, and the social events were much fun. And also the city of Salamanca was worth the trip. "
Carlo Raimondo Università di Bologna (Italy)
"The main problem in most econometric classes I attended before participating in this course was the difficulty to reconcile theory and practice. And this is precisely what the course taught by Prof. Pindado and Dr. Requejo solves. For each econometric estimation method presented, they discussed both the theoretical basis and the implementation strategy. This allows participants to better understand the reasons at the basis of each estimation procedure and the underlying assumptions and at the same time to learn how to apply and use them in their own research projects. To this main point, I would add a very interesting program, very good professors' teaching skills and a suitable environment. I strongly advise this course!"
Valentina Tarkovska Dublin Institute of Technology (Ireland)
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"The course is a real eye opener! Being developed by the high calibre academics, it is perfectly designed and extremely well taught. Starting with the intuitive explanation of fundamental principles in panel data analysis, Professor Pindado taught us when, where, and how to use the most sophisticated estimation techniques. Static, dynamic, and non-linear models were explained by using carefully selected examples from the Business Economics literature. The use of very good real-life examples always facilitates understanding, contributes to the rapid absorption of the material, and makes this course unique. The comprehensive STATA training organised by Dr. Requejo cannot be underestimated as well. It is an important part of the course - inspiring for the beginners and hugely beneficial for the experienced STATA users. Prof. Pindado and Dr. Requejo share their knowledge and expertise by demonstrating how to develop panel data models in STATA with special attention being paid to the selection of the estimator for each model, interpretation of results, and robustness tests. All participants receive excellent course material including examples of datasets and STATA codes which can be applied immediately. Upon completion of this workshop, I improved my own empirical paper significantly, as I became familiar with the principle, and had been equipped with all necessary tools. It was great to be able to learn panel data management techniques in one of the oldest Universities on the Globe in the beautiful Salamanca, with its own unique traditions, fantastic food, and difficult-to-resist shopping! I would strongly recommend this course for PhD students and early career researches who plan to use panel data in the future."
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2011 Course
Thomas Kaspereit Universität Oldenburg (Germany)
"The (panel data) course was divided into two closely related but distinct parts: A theoretical part that introduces the participants into advanced methods in panel data analysis, and a practical part that was an introduction of the STATA software. Both parts were extremely helpful, because the methods that were taught are the gold standard in panel data analysis. I recommend every researcher with solid knowledge about statistics and interest in learning STATA to attend this course. The organization is perfect, the atmosphere very familiar, the application process uncomplicated, and the outcome outrageous."
Mª Pilar Velasco González University of Valladolid (Spain)
"It seems to me a useful course because panel data methodology is widespread in business research. Data management is another important feature of the course. Both aspects of the course have come up to my expectations. When I finished the course – especially the data management lessons with STATA – I only felt a little upset because… I realized I could have done the same work faster! So, I'm willing to apply it in my next research works."
Kwong Yew (Rand) Low University of Queensland (Australia)
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"I found the GMM course very useful, interesting and applicable for all researchers in the areas of accounting and finance. Prof. Pindado created the right balance of theory and application such that we understood the benefits and superiority over other cross-sectional and time-series frameworks and also its limitations. Individuals unfamiliar with Stata are not disadvantaged as Dr. Requejo and Dr. De La Torre taught the class the basics of using Stata and useful tips and tools from their experience. The program included more advanced Stata material and the best sites/forums to search for help in the future when required. Any participant of this course virtually has no impediments not to use the GMM methodology as Prof. Pindado provides the GMM Stata code, example datasets and expected results. Prof. Pindado walks you through the entire process of loading the data, applying the functions and interpretation of results. I highly recommend this course to PhD students and early career researchers who wish to use GMM in their research as they will be able to apply the principles, tools and technology immediately upon completion of the workshop. Salamanca is a beautiful city with the 3rd oldest university in the world and an abundance of cultural and historical heritage to engage any visitor. I have to admit, one of the factors that led to my application to the workshop was the opportunity to visit Salamanca itself."
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