Course_ Organizational Behavior组织行为学

Course_ Organizational Behavior组织行为学 Course: Organizational Behavior组织行为学 Instructor: Prof. Johan Coetsee Assistant: Dr. Wenchuan Liu Course Description: Organisationalbehaviour is the study of individuals and groups within an organisational context, and the study of internal processes and practices as they affect individuals and groups. The field of organisationalbehaviour borrows many concepts and methods form the behavioural and social sciences, such as psychology, sociology, political science and anthropology. As a result, issues and topics touching on many academic disciplines may become the subject of study in the field of organisationalbehaviour. The course gradually broadens the level of perspective, starting out with an individual level perspective on motivation, attitudes and stress, proceeding to a group level perspective on group dynamics, teams and leadership, power and politics and culminating in the organisational level perspective on culture and change. The aims of the course are: Top provide students with a broad and critical understanding of current OB theory and research; To provide insights into participants’ own behaviour, motivations, experience of work groups, teams and organisational environments Through cases and classroom experiences, to explore how insight and knowledge can be translated into business problem-solving To prepare students for future roles in which they need to work with individuals and groups in organisations. The course consists of the following 8 Topics: 1. Fundamental concepts and overview of organisationalbehaviour 2. Work motivation, attitudes and stress 3. Groups and group dynamics 4. Working in teams 5. The art and practice of leadership 6. Power and politics in the workplace 7. Organisational culture 8. Leading change The purpose of this course is not just to teach you about the theory behind how organizations and individuals mutually influence one another, but also to help you develop a sophisticated understanding of the motivations that drive people’s behaviour in real organisations, and the skills and confidence to promote your ideas and views within an organisation in the ‘real world’. To accomplish this objective, we will draw on a variety of teaching methods, including lectures, class and group discussion, and case studies. This format means that it is essential that you come to class prepared for discussions, having read and thought about the materials, and willing to participate. 1 / 23 Bio for Instructor: Johan is a faculty member of Newcastle Business School at Northumbria University, United Kingdom. He is an aaccomplished professional with 20 years international experience (South Africa, Ireland, United Kingdom) working in academia and consulting to diverse, global organisations in the areas of Leadership, Organisationalbehaviour, and Human Resource Management. He was awarded a Doctorate in Human Resource Development in 1998 and also holds the following qualifications: Masters of Business Administration, Masters of Commerce degree, B Com degree (Hons). Currently, he is involved in executive education, undergraduate and post-graduate teaching. Before joining NBS, Johan held a number of senior positions in academia and industry. His background is in chemical, manufacturing, banking and organizational development. His main academic interests are in Change management and creating organizational readiness for change. In particular, this professional expertise has been put into practice by designing and delivering executive and master’s level programmes for senior and executive managers from a range of organisations. 2 / 23 Course: Leadership and Change领导力与变革 Instructor: Prof. Patrick C. Flood Assistant: Dr. Wenchuan Liu Course Description: In this course we focus on the role of management and leadership in achieving organizational objectives and profitability. We will show that the senior and middle management have a critical role in this process and in engaging employees during the change process. The course will draw from psychology, sociology, strategy and organizational behaviour and will use experiental methods, case studies and videos as part of the learning process. The experience of participants and their views will be canvassed throughout the course so that it is meaningful to the work context. This course will enable you to lead and to lead change more successfully. Topics to be addressed include: , What is the role of the senior management team and how can we select this team to make it work well for the benefit of the organization and its members? , What do we mean by transformational leadership and what do we need to do to become transformational leaders? , What is our leadership style and how can we manage it? , How can power and politics be managed effectively in organizations and how should you manage your career effectively? , Are their lessons we can learn from sports teams to create high performance work teams in organizations? , What is the role of the middle manager and how can they manage the leadership team to gain support for their initiatives? , What principles work best in leading and managing change? , How do we engage employees in the change process and communicate effectively with them , What are the most effective change models that we can use and how can we apply them in our daily lives We will begin our course by focusing on the top level of the organization and then through lectures, cases and exercises we will explore how to be an effective middle manager who gains the support of all of his/her employees. The course will be practical in focus and applies theory to the practice of management and leadership Text books: S.J.Carroll and P.C.Flood (2010) Persuasive leadership: Lessons from the Arts, Jossey Bass, California. J.Coetsee and P.C.Flood (2013) Change Lessons from the CEO, Jossey Bass, California. 3 / 23 Bio for Instructor: Patrick C. Flood is Professor of Organizational Behaviour at Dublin City University. He is an expert on organizational behaviour, leadership development and change management. His books include Change lessons from the CEO(Jossey Bass, 2013) (); Persuasive Leadership: Lessons from the Arts (Jossey Bass, 2010), Leadership in Ireland (Blackhall, 2010); Strategy Implementation (Blackwell, 2000), Effective Top Management Teams (Blackhall, 2000) and Managing without Traditional Methods (Addison Wesley, 1996). He is the author of over 100 publications and has published in Strategic Management Journal, Journal of Business Ethics, Human Relations, British Journal of Management, Industrial Relations and Human Resource Management. He has taught on executive and MBA programmes in Australia, China, Ireland, UK, Belgium, Germany, Italy, Netherlands, Poland and the US. He serves as Academic Fellow at the Judge Business School, University of Cambridge, and is currently Visiting Professor at the Northeastern University, China and Capital University of Economics, Beijing. HR magazine ranked Patrick #8 in the 2012 Influential International Thinkers category. He has extensive consulting experience with companies in Europe and the USincluding Pirelli, Adidas and Pernod-Ricart. Flood received his PhD from the London School of Economics (LSE) where he was a British Council Scholar. He did his post doctoral work at London Business School and his Fulbright at University of Maryland at College Park.He has held faculty and visiting appointments at a number of business schools including London Business School, University of Limerick, University of Maryland and the Australian Graduate School of Management. He holds two research excellence and teaching awards. Patrick is an elected Academician of the Academy of Social Sciences (AcSS) and a Fellow of the Royal Society of Arts, UK. 4 / 23 Course: International Finance 国际金融 Instructor: Prof. Yoonbai KIM Assistant:Dr Yu You Course Description: This is a course in international finance and open-economy macroeconomic analysis. Key topics include the determination of exchange rates, the balance of payments, the effects of monetary and fiscal policies in an open economy, and international capital flows. Students will be exposed to key theories and their applications for financial and monetary issues around the world. Among current issues, we will focus on the Eurozone problems, the choice of the exchange rate regime, monetary union, and recurrent financial crises. Text book: “International Finance”, by Keith Pilbeam 2013. Palgrave Macmillan. Bio for Instructor: Yoonbai is a professor of economics at the University of Kentucky. He has also taught at National University of Singapore, Korea and Sogang Universities in Korea, Southern Illinois University, and the American University of Sharjah (U.A.E.). He holds a BA degree in Economics from Seoul National University and a PhD in Economics from Stanford University. Dr. Kim’s research is focused on empirical study of various issues in international macroeconomics including current account adjustment, exchange rate determination, and causes and effects of international capital movement. More recently, he has been studying the exchange rate regime choice and the stabilizing effects of international capital controls. His research has been published in journals including Review of Economics and Statistics, Journal of Business and Economic Statistics, Journal of Money, Credit and Banking, Journal of International Money and Finance, World Development. Dr. Kim served as President of the Korea-America Economic Association in 2009. 5 / 23 Course: Quantitative Policy Analysis 量化政策分析 Instructor: Prof. Henry Kinnucan Assistant: Dr. Jing Gao The course aims to develop skills in specifying, simulating, and interpreting economic models, as well as to learn the basics of applied welfare analysis using the equilibrium displacement modeling (EDM) approach. Students who intend to register for this course will have completed one course each in microeconomic theory, mathematical economics, and econometrics. The format of the course will be lectures and labs (see schedule below). Labs will devote to model simulation using Excel. Readings from journals and other sources will be made available as the course unfolds. The course will focus on applied welfare analysis using equilibrium displacement modeling. For isolated market, we will mainly discuss advertising and research, production subsidy, consumption tax and welfare effects of a supply/demand shift in closed economy, and advertising and research, production subsidy, import tariff, export tax, exchange rate pass through, welfare effects of a supply/demand shift in open economy. For multiple markets, we will discuss advertising, tax, Buse elasticity, Armington model, Muth model-primal/dual form, and welfare effects of a supply/demand shift in a vertical/horizontal market. Textbook: Just, R. E., D. L. Hueth, and A. Schmitz. 2004. The Welfare Economics of Public Policy. Cheltenham, UK and Northhampton, MA, USA: Edward Elgar. Lecture/Lab Schedule and Topics Week Lecture 1 Lecture 2 Lab 1 Total Hours 1 Equilibria/Hypotheses/ Applications of EDM - Simulating Closed Introduction to EDM Closed Economy Economy Models (4 hours) (4 hours) (3 hours) 11 Lecture 3 Lecture 4 Lab 2 2 Applications of EDM – Open Open Economy Simulating Open Economy Applications Continued Economy Models (4 hours) (4 hours) (3 hours) 11 Lecture 5 Lecture 6 Lab 3 3 Applications of EDM - Multiple Market Simulating Multiple Multiple Markets Applications Continued Market Models (4 hours) (4 hours) (2 hours) 10 32 6 / 23 Bio for Instructor: Henry Kinnucan is Professor of Economics and Graduate Program Coordinator in the Department of Agricultural Economics and Rural Sociology at Auburn University, USA. He received his B.S. degree from University of Illinois, and M.S. and Ph.D. degrees from University of Minnesota. Professor Kinnucan focuses on Prices, Marketing and Applied Demand Analysis. He has published four books and over one hundred refereed papers in journals including American Journal of Agricultural Economics, Journal of Agricultural Economics, Applied Economics, Agribusiness, European Review of Agricultural Economics, and Journal of Agricultural and Resource Economics. Prof. Kinnucan was awarded the Provost’s Award for Outstanding Contribution to Graduate Studies by Auburn University in 2011 and the Lifetime Achievement Award by the Southern Agricultural Economics Association in 2012. 7 / 23 Course: Advanced Econometrics 高级计量经济学 Instructors: Prof. Qi Li&DrRuixuan Liu Assistant: Dr. Kunpeng Li Course Description: This course will mainly focus on nonparametric/semiparametric methods and their applications in economics. We will show that nonparametric/semiparametric methods can help us solve problems that can be difficulty to handle using conventional parametric approach. Nonparametric methods also have its limitations. We will discuss this as well. Nonparametric methods is a complement, rather than substitute, to the popular parametric methods. We will mainly discuss the nonparametric kernel method with independent data. Other nonparametric methods such as series (spline) method will be briefly discussed. We show that all asymptotic analysis can be extended to cover the weakly dependent data case. Nonparametric estimation with non-stationary data will also be covered (if time permits). We will also discuss a few useful econometric methods (parametric methods) in estimating treatment effects, and in analyzing nonstationary data. At the beginning of the course we will review linear regression models with independent data. We first study the finite sample property of the least squares estimator under some strong assumptions. Then we show that these strong assumptions can be removed provided that one has a relative large sample size. Because when sample size is large, one can reply on laws of large numbers and central limit theorems to derive the distribution of the least squares estimator without imposing strong assumptions. We then discuss some simple regression models with time series data. After that we will move to study nonparametric econometric models. We will also cover many applications of nonparametric/semiparametric methods to economics problems. Text book: “Nonparametric Econometrics: Theory and Practice”, by Li, Q. and Racine, J. 2006. Princeton University Press. 8 / 23 Bio for Instructor: Qi Li is a professor at the International School of Economics & Management at the Capital University of Business and Economics, and the Hugh Roy Cullen Professor in Liberal Arts at Texas A&M University. Professor Li serves as an associate editor of six international journals including Journal of Econometrics, Economics Letters and Econometric Reviews. He also served in the past as a co-editor of (United Kingdom Royal Economic Society's) Econometrics Journal, and an associated for Econometric Theory and Journal of Nonparametric Statistics. Professor Qi Li's main research field is econometrics, including nonparametric econometrics, panel data method and non-stationary data analysis. Professor Li has published n 120 papers in international economics and statistical journals, including Econometrica, American Economic Reviews, Journal of Econometrics, Journal of Economic Theory, Review of Economics and Statistics, International Economic Reviews, Games and Economic Behavior, Journal of Business and Economic Statistics, Econometric Theory, Journal of American Statistical Association and Annals of Statistics. He also published a book (co-authored with Jeffrey S. Racine) entitled ``Nonparametric Econometrics: Theory and Practice'' by the Princeton University Press. 9 / 23 Course: Bayesian Econometrics贝叶斯计量经济学 Instructor: Prof. Richard Startz Assistant:Dr Sui Luo Course Description: This course provides an introduction to Bayesian econometrics. The Bayesian approach to econometrics provides an alternative estimation framework to the classical, or frequentist, approach for many statistical problems. Bayesian approaches offer several advantages. In theory, the most important advantage is that Bayesian estimates lead to proper probability statements for making decisions in ways that classical methods often do not. In practice, the most important advantage may be that Bayesian estimation can be implemented by straightforward computer simulation techniques in situations where classical maximization techniques are difficult. In many situations Bayesian techniques offer the additional advantage of providing a method for incorporating prior information into the statistical analysis. The course is organized around the standard econometric toolkit: linear regression and its extensions. We take familiar ideas and use them as a basis for introducing Bayesian techniques that have more general applicability. In addition to linear regression models, we will consider models of autocorrelation and heteroskedasticity and nonlinear regression models. The majority of the course focuses on algorithms for Bayesian computation, including Gibbs sampling, Metropolis-Hastings algorithm, and techniques for computing the marginal likelihood. Students considering the course should be familiar with the basic linear regression model, the basics of probability theory (marginal, conditional, and joint distributions), and have some experience with programming (or be willing to learn programming as it is introduced in the course.) Textbook: Bayesian Econometrics, by Gary Koop, Wiley, 2003. 10 / 23 Bio for Instructor: Richard Startz is Professor of Economics at the University of California, Santa Barbara, where he also holds an appointment as Professor of Statistics. He previously taught for many years at the University of Washington, and has also taught at the Wharton School, UC San Diego, Princeton, and the Stanford business school. Prof. Startz is the author of numerous articles on econometric methodology and empirical macroeconomics. His work includes well-known papers on weak instruments, models of interest rate yield curves, and methodological work on ARMA models. In addition to journal articles, Prof. Startz is coauthor (with RudigerDornbusch and Stanley Fischer) of the widely used textbook Macroeconomics. His most recent book, Profit of Education, discusses reforms of the K-12 education system centered on teacher pay. Prof. Startz is also author of three books on aspects of personal computing, including most recently EViews Illustrated. 11 / 23 Course: Production Efficiency: Methods and Applications生产效率:方法与应用 Instructor: Prof. Hung-Jen Wang Assistant: Dr. Yu-Fan Huang Course Description: This course will introduce the fundamental empirical methods of the production efficiency analysis. The targeting audients are graduate students and perhaps well- trained undergraduate students. Basic understandings of Econometrics and Microeconomics are advised. The main empirical model, the stochastic frontier model, was first proposed in the context of production function estimation to account for the effect of technical inefficiency. The inefficiency causes actual output to fall below the potential level (that is, the production frontier) and also raises production cost above the minimum level (that is, the cost frontier). Recent applications of the model are found in many fields of study including labour, finance, and economic growth. In these applications, the observed outcome (of wages, investment, and so on) is modelled as being deviating from a frontier level in one direction owing to factors such as information asymmetry. Generally speaking, the basic stochastic frontier model is a regression model with special specification of the error term. Therefore, students with fundamental knowledge of the linear regression model will be able to grasp the idea of the stochastic frontier model easily. In additional to introducing methodological issues, many empirical examples will also be illustrated and discussed in a hope that students will be able to implement the stochastic frontier model in other applicable cases. Textbook A Practitioner's Guide to Stochastic Frontier Analysis, by Hung-Jen Wang, SubalKumbhakar and Alan Horncastle, Cambridge University Press (Forthcoming). 12 / 23 Bio for Instructor: Hung-Jen Wang is a professor at the Department of Economics, National Taiwan University. Before he joined National Taiwan University, he was a research fellow at the Institute of Economics, Academia Sinica. Professor Wang currently serves as an associate editor of the Journal of Productivity Analysis and the Empirical Economics. He also served in the past as co-editor of the Academia Economic Papers and associated editor of the Taiwan Economics Review. He is now the president of the Taiwan Econometric Society. Professor Wang’s research interests lie in the fields of the productivity and efficiency analysis, investment, monetary policy. He published many papers in leading journals, e.g., Journal of Econometrics, Journal of Business and Economic Statistics,Journal of Money, Credit, and Banking, Economics Letters, Journal of Productivity Analysis, etc. He has been working on a textbook titled “A Practitioner's Guide to Stochastic Frontier Analysis”, which will be published in the near future. 13 / 23 Course: Business Research Methods 管理研究方法 Instructor: Dr. SatyaChattopadhyay Assistant:DrGuangqianPeng Course Description: Research Methods is studied as the basis for business decision making, for analysis of alternatives, and for evaluation of strategies through systematic gathering of information and evidence. The foundations and methodology of research, including behavioral sciences and multivariate analysis, are discussed. Research projects are conducted by the class participants and research applications to real life problems are exemplified. Good management is about making good decisions. Managers faced with business problems must make every effort to make good decisions. A structured relationship between management problems, decision problems and research problems is the basis of the course. Management problems have to be formulated as decision problems. Decision problems in turn lead to research problems. The course focuses on how to support good decision-making, specifically in the context of business management. Building on models of decision-making covered in previous courses, a systematic approach to decision support is provided by initially focusing on the choice of the appropriate model to fit the decision environment. The focus of the course then shifts to the process of defining the variables specified by the model chosen, and a systematic process of gathering reliable and valid data for those variables, and their appropriate analysis in order to provide decision support for the original marketing management problem. The course also uses SPSS software platform for collection and analysis of data used for decision support. Each day students are required to read the assigned material and go over the lecture notes and powerpoint slides provided, in order to gain a solid grasp of the content material for the section of the course being covered. Any questions about the material or needed amplification on relevant issues should be raised in class Students will engage in the class discussion to demonstrate their ability to examine marketing research issues with a holistic focus. The students also complete the individual assignment (s) to demonstrate mastery of the content material. There are two mid-term examinations that the students will complete to demonstrate their grasp of concepts learned. Students will complete data analysis exercises using SPSS 14 / 23 Bio for Instructor: Dr. Chattopadhyay teaches Marketing Management, International Marketing, and Marketing Research at the Arthur J. Kania School of Management at the University of Scranton where he has won awards for his research, contribution in development of technology curriculum and his leadership in international education. Dr. Chattopadhyay is Honorary Professor of Management of The Academy of Management of Kyrgyz Republic. In addition, he has been Visiting Professor of Marketing at the French Ecole Superior du Commerce et Management (ESCEM) in France, Peking University's China Center for Economic Research, Remnin Business School of Renmin University of China, Capital University of Economics and Business in Beijing, and Kyiv Mohyla Business School at Kyiv Mohyla Academy, Ukraine. Dr. Chattopadhyay was awarded the Fulbright Senior Scholar Fellowship by the U.S. Department of State in 1999 and 2004. Dr. Chattopadhyay has published regularly in academic journals and made numerous scholarly presentations at international conferences and institutions of higher learning. In addition to his teaching and research, Dr. Chattopadhyay is active in international aid projects involving quality management and enterprise management technology with USAID, USIA, Swiss Development Corporation, Eurasia Foundation and the World Bank, in Vietnam, Kyrgyzstan, Slovakia, Kazakhstan, and Republic of Georgia. In addition to his duties as Associate Professor of Marketing at the University of Scranton, Dr. Chattopadhyay is also the Director for the Hong Kong MBA program Director of International Initiatives for the Kania School of Management. Dr. Chattopadhyay is married, with two daughters: 11 and 18. He holds an undergraduate degree in Mechanical Engineering and MBA in Marketing and Operations Management from Jadavpur University and Indian Institute of Management in Kolkata, India, respectively. His Ph.D. is in Marketing, from Virginia Tech. 15 / 23 Course: 会计理论专题 Instructor: Prof. Zhijun Lin Assistant: Course Description: 从理论分析角度讲述财务会计的主要实务及发展, 內容包括: 1)财务会计概念框架及其作用; 2)会计准则及其制订, 3)会计计量理论和资产计价, 4)收益概念与收益确定, 5)财务 报告 软件系统测试报告下载sgs报告如何下载关于路面塌陷情况报告535n,sgs报告怎么下载竣工报告下载 与信息报露的发展; 6)国际间会计与报告趋同, 等. 海外会计专业大多有开设会计理论相关课程。 Bio for Instructor: 林志军教授，男，1985年获得厦门大学经济学博士学位(中国第一位经济学及会计学博士) 。1983年—1988年执教于厦门大学，1988年—1990年先后于美国斯坦福大学和伊利诺大学任访问学者，1990年一1995年执教于加拿大Lethbridge大学管理学院。现为香港浸会大学会计系系主任、教授，美国会计学会(AAA)、国际会计教育与研究学会(IAAER)、加拿大会计学会(cAAA)、北美中国会计教授会等学会成员，同时是美国注册会计师协会(AIcPA)、中国注册会计师协会(CICPA)成员。1982年以来，先后在中、美、加、英、日等国发表中、英文学术论文50余篇，出版会计专业著作、译著和教材14部。 16 / 23 Course: Intermediate Data Analysis中间数据分析 Instructor: Professor Guo Yi Assistant:Dr Pei Yanbo Course Description: In this course, four generic problems will be discussed, including repeated measures analysis, ordinary least squares regression, logistic regression analysis and time-to-event analysis. The three latter problems will be illustrated with a real data set and three reports will be produced that simulate writing a paper for publication. Such reports will rely heavily on use of statistical software STATA and will follow the usual outline for article publication, namely, introduction and motivation, materials and methods and results of the study, discussion and conclusions. This course is open for first year graduate students, and junior or senior undergraduate students with some basic knowledge in statistics. Bio for Instructor: Guo Yi, PhD is an Assistant Professor in Department of Health Outcomes and Policy in College of Medicine at University of Florida. Professor Guo graduated from Division of Biostatistics, College of Public Health at the Ohio State University in 2010. His research areas include power and sample size analysis for multilevel and longitudinal data, linear models, cancer registry data analysis, etc. He has published more than ten original research articles in high impact peer-reviewed scientific journals. Professor Guo is an investigator on three major research grants from National Institute of Health (NIH); the total amount of the grants is close to 10,000,000 dollars. Professor Guo is also the director of the Statistics and Data Coordinating Center of NIH’s Center for Research to Reduce Disparities in Oral Health. 17 / 23 Course: Game Theoretic Decision Making决策模型 Instructor: Prof. Zhijun Wu Assistant:DrLan Zhang Course Description: This course introduces modern theory and methods on continuous and discrete optimization and game theoretic decision making. The continuous optimization part includes the steepest descent method, conjugate gradient method, and Newton's method for unconstrained optimization, and the necessary and sufficient conditions for constrained optimization and their applications to linear, quadratic, and convex programming. The discrete optimization part includes the combinatorial and integer programming methods for solving the maximum spanning tree problem, optimal matching problem, and network flow problem. The game theory part reviews classical methods for computing Nash equilibrium such as the Snow-Shapley method, Lemke-Howson method, and quadratic programming method. Applications of these subjects in engineering, scientific, and economic computing will also be discussed. Bio for Instructor: Zhijun Wu is a full professor in the Department of Mathematics at Iowa State University, USA. He has a Bachelor degree in Computer Science from Huazhong University of Science and Technology, China and a PhD degree in Computational and Applied Mathematics from Rice University, USA. His research field is in Continuous and Discrete Optimization, Game Theory, and Applications. He did postdoctoral research in Cornell University and Argonne National Lab., USA. He joined the faculty of Iowa State University in 2000, where he has taught Numerical Analysis, Continuous Optimization, and Discrete Optimization.He has directed 12 PhD students and published ~50 papers in top scientific journals. 18 / 23 Course:Statistical Methods in Financial Economics金融经济学中的统计方法简介 Instructor: Prof. ChuanshuJi Assistant: Dr. Lili Ma Course Description: This course provides an introduction to statistical methods commonly applied to financial economics. The required mathematical and theoretical background varies based on the needs of undergraduate and graduate students. Course materials will be uploaded to the website, including lecture notes, references and problem sets. A final exam will be given at the end. A tentative list of topics: , interest rate , mean variance analysis , stock data analysis , CAPM and risk decomposition , forward and futures , options, binomial tree pricing , physical and risk neutral probability measures , Black-Scholes formula , fixed-income markets, term structure models , pricing bond derivatives , hedging , volatility modeling: historical, implied, ARCH/GARCH , general equilibrium, absolute/relative asset pricing, etc. , market microstructure: transaction costs, asymmetric information, intra-day data analysis , Monte Carlo simulation methods and applications in financial economics 19 / 23 Bio for Instructor: Department of Statistics and Operations Research, University of North Carolina, Chapel Hill, NC27599-3260, USA; Email: cji@email.unc.edu. Education: Columbia Univ. (Statistics): M.A. 1982, M.Ph. 1986, Ph.D. 1988 (Advisor: Steven P. Lalley)Tsinghua Univ., Beijing (Mathematics): B.S. 1981. Employment:7/95 { present: Associate Professor of Statistics & OR, UNC-Chapel Hill; 7/88 { 6/95: Assistant Professor of Statistics and Mathematics, UNC-Chapel Hill; 8/92 { 12/92: Visiting Assistant Professor, Division of Applied Mathematics, Brown University. Current Research Interests:financial economics, probability approximations in asset pricing, interest rate derivatives for termstructure models, risk management, calibration of stochastic volatility models, market microstructure models with transaction costs and asymmetric information, Monte carlomethodology. Doctoral Students: 14 graduated and 5 currently at UNC-Chapel Hill. Master's Students: more than 30 supervised. Selected Publications Related to Current Research Projects:[1] Cheng, A., Gallant, A.R., Ji, C. and Lee, B. (2008). A Gaussian approximation scheme forcomputation of option prices in stochastic volatility models. Journal of Econometrics 146,44-58.[2] Ji, C. (2007). Inference and computation for stochastic volatility models related to optionpricing. Asymptotic Theory in Probability and Statistics with Applications (edited by T.L.Lai, L. Qian and Q.-M. Shao), 461-483. Zhejiang Univ. Press.[3] Yoon, J., Renault, E. and Ji, C. (2013). Conditional Monte Carlo for option pricing viageneralized Black-Scholes.Submitted to Journal of Econometrics.[4] Xu, B. and Ji, C. (2013). Option pricing in stochastic volatility random field models for theterm structure of interest rates.Submitted to Journal of Derivatives.[5] Liu, F. and Ji, C. (2013). Extensions of Kyle's model and related Bayesian inference. To besubmitted. 20 / 23 课程,高等財務會計研究 授课老师,金成隆教授 助教,张悦 课程描述, 本課程的目的,是從理論與實證兩個角度,介紹會計資訊在資本市場中所扮演的角色。包括資訊觀點與衡量觀點。其次,也從契約角度探討會計資訊的功能,包括獎籌契約與債務契約。第三,探討盈餘質量的問題,含盈餘管理、預期管理、以及語調或文字管理,第四,介紹分析師的中介角色,包括使用何種資訊形成分析師預測與推荐、分析師報告的價值、各種分析師,型的形成原因以及對於研究報告價值的影響、市場對於分析師報告的效,性、分 可以幫助學員了解會計析師本身處,資,的效,性、分析師是否獨,等。透過本課程,希望 理論的發展趨勢、有助學者發覺新的研究議題。 金成隆教授简介, ,成,Chen-Lung Chin 特聘教授兼系主任 Department of Accounting College of Commerce, National Chengchi University NO.64, Sec.2, ZhiNan Rd.,Wenshan District, Taipei City 11605, Taiwan (R.O.C) (Office) 886-2-29393091 ext. 81115 21 / 23 (E-mail) kim@nccu.edu.tw Education: MBA: National Chengchi University 1986 Ph.D : National Chengchi University 1996 Visiting Scholar, University of Oregon, 2008/8~2009/7. Working Experiences Professor, Department of Accounting, National Chengchi University 2001-to date Chairperson, Department of Accounting, National Chung Cheng University 1999‐2001 Associate Professor, National Changhua University of Education 1997‐1999 Lecture, Accounting Department, Ming Chuan University 1988‐1996 Securities and Future Bureau (similar to US SEC). 1986‐1987 Journal Editor : Chief Editor / Associate Editor of International Journal of Accounting Studies (The best Accounting Journal in Taiwan, TSSCI; only one Accounting TSSCI in Taiwan) ~ 2001‐to date Member of Editorial Board of “Taiwan Accounting Review” Member of Editorial Board of “Commerce & Management Quarterly”. Journal Reviewers / Honor: (1) Ad Hoc reviewers of The Accounting Review, Review of Accounting Studies, etc. (2) Best paper of “Taiwan Accounting Association”, 2008. (3) Best paper of “Journal of Management, 2001, 2010. (Chinese Management Association) (4) 國,政治大學研究優,獎, 2008, 2009, 2010, 2011. (5) 國,政治大學會計系傑出研究獎 (多,至今). (6) 國科會甲種研究獎,(多,) (7) 國,政治大學商學院教學優, Professional certification and 22 / 23 membership Certificated Public Accountant, Taiwan, 1990.American Accounting Association, since 2004. Research Interest: Financial Accounting: Financial Disclosure, earnings management, financial analysts Project of National Science Council (NSC) Professor Chen-Lung Chin has 31 projects funded by National Science Council from 1986. (NSC: the main government unit that grant research fund) 23 / 23