ECON 6102 Advanced Macroeconomic Analysis Course Outline Semester 2, 2012 Part A: Course-Specific Information Students are also expected to have read and be familiar with Part B Supplement to All Course Outlines. This contains Policies on Student Responsibilities and Support, Including Special Consideration, Plagiarism and Key Dates.

Table of Contents COURSE OUTLINE

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STAFF CONTACT DETAILS

1.1 Communications with staff 1.2 Pitstop 2

COURSE DETAILS

2.1 Teaching Times and Locations 2.2 Units of Credit 2.3 Summary of Course 2.4 Aims and Relationship to Other Courses 2.5 Student Learning Outcomes 3

LEARNING AND TEACHING ACTIVITIES

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3.1 Approach to Learning and Teaching in the Course 3.2 Learning Activities and Teaching Strategies

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ASSESSMENT

4.1 Formal Requirements 4.2 Assessment Details 4.3 Tutorial Participation (if relevant/desired) 4.4 Midsession Exam (if required/desired) 4.5 In-tutorial Tests (if required/desired) 4.6 Tutorial discussion questions (if required/desired) 4.6.1 Submission Procedure 4.6.2

Late Submission

4.7 Assignment (if required/desired) 4.7.1 Submission Procedure for Assignment 4.7.2

Late Submission of Assignment

4.8 Final Exam Format 4.9 Quality Assurance

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COURSE EVALUATION AND DEVELOPMENT

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COURSE RESOURCES

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COURSE SCHEDULE

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7.1 Lecture Schedule 7.2 Tutorial Schedule

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1 STAFF CONTACT DETAILS The Lecturers for this course are: Geni Dechter (Lecturer-in-charge) Lecturer: Weeks 1-8 Room 442c ASB Building Phone No: 9385 7478 Email: [email protected] Consultation Times – by appointment Alexandre Dmitriev Lecturer: Weeks 9-12 Room Q3117 Phone No: 9385 3351 Email: [email protected] Consultation Times – by appointment

1.1

Communications with staff

Email is the recommended means of initial communication with the teaching staff for this course. You should feel free to approach your lecturer about any academic matter. The information concerning administrative matters may also be obtained from the School of Economics Office, level 4, ASB building.

2 COURSE DETAILS 2.1

Teaching Times and Locations

Lectures:

2.2

Tuesdays

13:00 – 16:00 ASB 119

Units of Credit

Units of Credit: 6

2.3

Summary of Course

The goal of the first 8 weeks of the course is to provide methodological tools for advanced research in macroeconomics. The emphasis is on theory, although data guides the theoretical explorations. We build entirely on models with microfoundations, i.e., models where behaviour is derived from basic assumptions on consumers’ preferences, production technologies, information, and so on. We will study two alternative ways of solving dynamic optimization problems: using sequential methods and using recursive methods. Sequential methods involve maximizing over sequences. Recursive methods – also labeled dynamic programming methods – use functional equations. The second part of the course will further extend the dynamic general equilibrium models and also introduce practical solution methods. We will learn problem solving and numerical techniques and apply them to the particular topic of discussion. In particular, we will computationally solve one sector growth models using Matlab. In each topic and models introduced, we will emphasize the basic structure of these models and their applications.

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2.4

Aims and Relationship to Other Courses

The course aims to provide benefits to students in terms of: • •

The ability to use advanced economic tools in addressing economic policy questions; An understanding of the different ways in which economic policy issues can be tackled and the way in which economic policies affect economic performance;

This course is a 2nd part of the graduate course on advanced macroeconomics. It will build on the material that was taught in macroeconomic analysis (ECON6002). You must have completed ECON6002 with satisfactory grades or have completed equivalent course material.

2.5

Student Learning Outcomes

On completion of the course, students should be able to: 1. Identify and explain the assumptions and structure of standard models in macroeconomics 2. Analyze and critically manipulate these models 3. Apply the models to interpret and analyze problems in macroeconomics 4. Recognize and assess numerical tools to solve rational expectation models and analyse their quantitative prediction 5. Construct economic arguments in terms of the above concepts, and present their arguments Graduate Attributes This course contributes to your development of the following Australian School of Business Graduate Attributes, which are the qualities, skills and understandings we want you to have by the completion of your degree. Learning Outcomes 1, 2, 3, 4 1, 2, 3, 4 5 1, 2, 3, 4 1, 2, 3, 4 1, 2, 3, 4

ASB Graduate Attributes Critical thinking and problem solving Communication Teamwork and leadership Social, ethical and global perspectives In-depth engagement with relevant knowledge Professional skills

Attribute No. 1 2 3 4 disciplinary 5 6

3 LEARNING AND TEACHING ACTIVITIES 3.1

Approach to Learning and Teaching in the Course

The philosophy underpinning this course and its Teaching and Learning Strategies are based on “Guidelines on Learning that Inform Teaching at UNSW. These guidelines may be viewed at: www.guidelinesonlearning.unsw.edu.au. Specifically, the lectures, tutorials and assessment have been designed to appropriately challenge students and support the achievement of the desired learning outcomes. A climate of inquiry and

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dialogue is encouraged between students and teachers and among students (in and out of class). The lecturers and tutors aim to provide meaningful and timely feedback to students to improve learning outcome. An effective learning strategy (on which the course materials are based) is the following: 1. Prior to attending a lecture, download the lecture notes, read them and the relevant material from the textbook, bring the notes with you to the lecture. 2. Attend the lecture. The relevant material from the textbook forms the basis for the lecture. Key concepts will be emphasised and demonstrated through worked examples. 3. Assignments: do not be discouraged if you cannot answer all of the questions as some questions are more difficult than others. Attempting the assigned questions will provide a self-test of your understanding of particular topics and identify those topics which may require further attention.

3.2

Learning Activities and Teaching Strategies

The examinable content of the course is defined by the material covered in lectures, tutorials and problem sets. Lectures The purpose of lectures is to provide a logical structure for the topics that make up the course, to emphasise the important concepts and methods of each topic, and to provide relevant examples to which the concepts and methods are applied. As not all topics will be presented extensively, students should refer to the textbook for further details and be sure to attempt the tutorial exercises. Out-of-Class Study While students may have preferred individual learning strategies, it is important to note that most learning will be achieved outside of class time. Lectures can only provide a structure to assist your study, and tutorial time is limited.

4 ASSESSMENT 4.1

Formal Requirements

To be eligible for a passing grade in this course, students must: • Achieve a composite mark of at least 50 per cent; AND • Satisfactorily complete all assessment tasks or submit appropriate documentation relating to your failure to complete a task to the Lecturer in Charge. .

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4.2

Assessment Details

Assessment Task

Weight

Learning Outcomes assessed

ASB Graduate Attributes assessed

Length

Due Date

Assignments (first 8 weeks)

15%

1,2,3,4,5

1,2,3,4,5,6

2 weeks

See Below

Presentation

20%

1,2,3,4,5

1,2,3,4,5,6

Assignments (last 4 weeks)

15%

1,2,3,4,5

1,2,3,4,5,6

2 weeks

See Below

Final Exam (first 8 weeks)

50%

1,2,3,4,5

1,2,4,5,6

2 hours

See Below

See Below

Assignments Students will be given various assignments including computer simulation projects and class presentations. For each assignment, students will be given at least two weeks to complete and submit their final output. In the tutorial sessions, we will go over the assignments. Students may be asked to present their assignments during the tutorial. Presentations Each student will choose a paper from the reading group to present in class. The presentation will take 30 minutes. The evaluation will be based on the quality of presentation and ability to answer questions. Presentation schedule will be set up during the first week of the semester.

The final examination Final exam will be held in the University examination period and will be at least 2 hours long, or will be taken separately in an extra class time. Further information on the content of the Final Exam will be provided towards the end of session. The examination period for Semester 2, 2012, falls between 26 October and 13 November.

4.3

Quality Assurance

The ASB is actively monitoring student learning and quality of the student experience in all its programs. A random selection of completed assessment tasks may be used for quality assurance, such as to determine the extent to which program learning goals are being achieved. The information is required for accreditation purposes, and aggregated findings will be used to inform changes aimed at improving the quality of ASB programs. All material used for such processes will be treated as confidential and will not be related to course grades.

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5 COURSE EVALUATION AND DEVELOPMENT Each year feedback is sought from students and other stakeholders about the courses offered in the School and continual improvements are made based on this feedback. UNSW's Course and Teaching Evaluation and Improvement (CATEI) Process is one of the ways in which student evaluative feedback is gathered. You are strongly encouraged to take part in the feedback process.

6 COURSE RESOURCES The website for this course is on UNSW Blackboard at: http://lms-blackboard.telt.unsw.edu.au/webapps/portal/frameset.jsp There is no prescribed textbook for this course. Students may find the following graduate textbooks useful for some parts of the course. • • • • •

Lecture notes by Per Krussel (PK) – available on Blackboard Lars Ljungqvist and Thomas J. Sargent, Recursive Macroeconomics Theory, 2nd edition, The MIT Press (2000) Acemoglu, Daron. 2009. Introduction to Modern Economic Growth (Princeton University Press) Nancy L. Stokey and Robert E. Lucas, with Edward C. Prescott, Recursive Methods in Economic Dynamics, Harvard University Press (1989) See attached reading list

7 COURSE SCHEDULE 7.1

Lecture Schedule

Lectures start in Week 1and finish in Week 12 (Last lecture - October 11, 2011). Note that the mid-session break is during 5-9 September. Weeks 1-2: Dynamic Optimization: Sequential methods, Dynamic programming 1. PK lecture notes, chapters 1, 2 and 3 2. Ljungqvist and Sargent, Chapters 1, 3 Week 3: Competitive Equilibrium in Dynamic Models 1. PK lecture notes, chapter 5 2. Ljungqvist and Sargent, Chapters 3-5 Week 4-5: General equilibrium under uncertainty 1. PK lecture notes, chapter 6 2. Ljungqvist and Sargent, Chapters 3-5 Week 6: Aggregation, Aggregate Shocks and Distributional Issues 1. PK lecture notes, chapter 7

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2. Aiyagari, Rao, (1994). "Uninsured Idiosyncratic Risk and Aggregate Saving," Quarterly Journal of Economics, 109(3), pp. 659-84. 3. Per Krusell and Anthony A. Smith, Jr. (1998). “Income and Wealth Heterogeneity in the Macroeconomy,” Journal of Political Economy, Vol. 106, No. 5 (October 1998), pp. 867-896 Week 7: Real business cycle models 1. PK lecture notes, chapter 12 2. Finn Kydland and Edward C. Prescott, “Time to Build and Aggregate Fluctuations,” Econometrica, 1982. 3. John Long and Charles Plosser, “Real Business Cycles”, Journal of Political Economy, 1983. 4. Prescott, Edward, “Theory Ahead of Business Cycle Measurement,” CarnegieRochester Conference on Public Policy, Autumn 1986, 25, pp. 1 1-44. 5. Robert King, Charles Plosser and Sergio T. Rebelo, “Production, Growth and Business Cycles, I. The Basic Neoclassical Model,” Journal of Monetary Economics, 21, no. 2/3 (May 1988): 195-232. Week 8: From theory to practice: Introduction to Matlab 1. 2. -

Lecture notes Online resources: math.ucsd.edu/~driver/21d-s99/matlab-primer.html www.math.toronto.edu/mpugh/primer.pdf

Week 9: A Primer on Asset Pricing: the Lucas tree model; the Equity premium puzzle; the risk free rate puzzle. 1. Lecture Notes 2. Cochrane, John H. (2005) Asset Pricing, revised ed. (Princeton, NJ and Oxford, UK: Princeton University Press). Chapter 1 and 2. 3. Lucas, R. E. (1978) “Asset Prices in an Exchange Economy”, Econometrica 46(6), 1429–45 4. Kocherlakota, Narayana R. (1996) "The Equity Premium: It's Still a Puzzle," Journal of Economic Literature, vol. 34(1), 42-71. 5. Mehra, Rajnish (2003) “The Equity Premium: Why Is It a Puzzle?” Financial Analysts Journal, January/February 2003, 54-69. 6. Mehra, R. and E. Prescott (2008) “The Equity Premium: ABCs” in Merha, R. and E. Prescott (eds.) Handbook of the Equity Risk Premium. Weeks 10-11. Calibrating and Solving Stochastic Dynamic General Equilibrium Models. 1. Lecture Notes 2. Cooley, T., (1997) "Calibrated Models," Oxford Review of Economic Policy, vol. 13(3), 55-69. 3. Heer and Maussner (2005) Chapter 3 4. Marcet A. and G. Lorenzoni, (1999) “The Parameterized Expectation Approach: Some Practical Issues.” in: R. Marimon and A. Scott, Editors, Computational

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5.

6. 7.

8.

Methods for Study of Dynamic Economies, Oxford University Press, New York, pp. 143–171. Den Haan, Wouter J & Marcet, Albert, (1990) ”Solving the Stochastic Growth Model by Parameterized Expectations”, Journal of Business & Economic Statistics, Vol.8, 31-34. Den Haan, Wouter J & Marcet, Albert (1994) "Accuracy in Simulations," Review of Economic Studies, vol. 61(1), 3-17. Duffy, J. and P. D. McNelis, (2001) “Approximating and Simulating the Stochastic Growth model: Parameterized Expectations, Neural Networks, and the Genetic Algorithm” Journal of Economic Dynamics & Control, Vol.25, 1273– 1303. Maliar, L. and S. Maliar, (2003) ‘Parameterized Expectations Algorithm and the Moving Bounds’, Journal of Business & Economic Statistics, Vol.21, No.1, 8892.

Week 11-12. International Business Cycles: more puzzles and potential solutions 1. Lecture Notes 2. Backus, David K., Kehoe, Patrick J., and Kydland, Finn E. "International Real Business Cycles." Journal of Political Economy, 1992, 100(4), pp. 745-75. 3. Kollmann, R., (1996) "Incomplete asset markets and the cross-country consumption correlation puzzle," Journal of Economic Dynamics and Control, vol. 20(5), 945-961. 4. Patrick J. Kehoe & Fabrizio Perri, (2002) "International Business Cycles with Endogenous Incomplete Markets," Econometrica, 70(3), pp. 907-928. 5. Crucini, Mario (2006) “International Real Business Cycles.” Vanderbilt Economics Working Paper No. 06-W17 6. David Backus & Patrick J. Kehoe & Finn E. Kydland, (1993) "International Business Cycles: Theory and Evidence," NBER Working Papers 4493. 7. Boileau, M. & Normandin, M., (2008) "Closing international real business cycle models with restricted financial markets," Journal of International Money and Finance, vol. 27(5), 733-756. Heathcote, Jonathan & Perri, Fabrizio, (2002) "Financial autarky and international business cycles," Journal of Monetary Economics, 49(3), 601-627.

Reading list (papers to present): Coming soon..

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