- UCAS course code
- L900
- UCAS institution code
- M20
Bachelor of Arts (BAEcon)
BAEcon Development Studies
In-depth study into the problems and options faced by the developing world.
- Typical A-level offer: AAA including specific subjects
- Typical contextual A-level offer: ABB including specific subjects
- Refugee/care-experienced offer: BBB including specific subjects
- Typical International Baccalaureate offer: 36 points overall with 6,6,6 at HL, including specific subjects
Fees and funding
Fees
Tuition fees for home students commencing their studies in September 2025 will be £9,535 per annum (subject to Parliamentary approval). Tuition fees for international students will be £29,500 per annum. For general information please see the undergraduate finance pages.
Policy on additional costs
All students should normally be able to complete their programme of study without incurring additional study costs over and above the tuition fee for that programme. Any unavoidable additional compulsory costs totalling more than 1% of the annual home undergraduate fee per annum, regardless of whether the programme in question is undergraduate or postgraduate taught, will be made clear to you at the point of application. Further information can be found in the University's Policy on additional costs incurred by students on undergraduate and postgraduate taught programmes (PDF document, 91KB).
Scholarships/sponsorships
Scholarships and bursaries, including the Manchester Bursary , are available to eligible home/EU students.
Some undergraduate UK students will receive bursaries of up to £2,000 per year, in addition to the government package of maintenance grants.
You can get information and advice on student finance to help you manage your money.
Course unit details:
Topics in Applied Macroeconometrics
Unit code | ECON33021 |
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Credit rating | 20 |
Unit level | Level 3 |
Teaching period(s) | Semester 1 |
Available as a free choice unit? | Yes |
Overview
Students taking this course unit will develop understanding and skills in applying macroeconometric models. They will be able to apply time-series modelling and forecasting techniques and will be able to think in classical as well as Bayesian statistical frameworks. Students will gain an overview of the relevant literature, will develop the ability to critically evaluate such research and to communicate research findings effectively.
Pre/co-requisites
(ECON10072 or ECON20072) and (ECON20110 or ECON20222) and (ECON20532 or ECON20032)
Aims
The course unit aims to:
- Develop students' understanding of various empirical macroeconomic models, estimation techniques, and forecasting methods.
- Provide students with the necessary tools and knowledge to conduct research in macroeconometric topics such as time series analysis, forecasting, Bayesian econometrics, and structural modelling.
- Strengthen students skills in implementing time-series modelling techniques in R.
- Equip students with critical thinking skills, the ability to read relevant literature, and proficiency in communicating research results effectively.
Syllabus
Week 1: Introduction to Macroeconometrics
- Overview of the course and topics to be covered
- The role of econometric methods in macroeconomics
- Review of statistical and econometric concepts
Week 2-3: Time Series Analysis and Forecasting
- Stationary and non-stationary time series models
- ARIMA models and their applications
- Vector autoregressive models and impulse response functions
- Forecast evaluation and model selection
Week 4-5: Bayesian Econometrics
- Introduction to Bayesian inference
- Bayesian regression analysis
- Markov Chain Monte Carlo methods
- Applications to macroeconomic data and models
Week 7-8: Structural Modeling in Macroeconomics
- Dynamic stochastic general equilibrium (DSGE) models
- Estimation and inference in DSGE models
- Applications to monetary and fiscal policy analysis
- Model evaluation and robustness checks
Week 10-11: Empirical Applications in Macroeconometrics
- Case studies and applications of macroeconometric techniques
- Empirical research papers and presentations
- Student research projects and presentations
Week 12: Wrap-up and Review
- Review of key concepts and methods covered in the course
- Final exam review and preparation
Teaching and learning methods
- Synchronous activities (such as Lectures or Review and Q&A sessions, and tutorials), and guided self-study.
- Tutorials will be used to review key points in the lectures, develop technical skills needed to understand the key models and empirical evidence covered in the course, and develop communication skills (oral and written).
Knowledge and understanding
Analyze and apply various econometric techniques to real-world macroeconomic data, including:
- Understand the assumptions underlying different macroeconomic models and econometric methods.
- Evaluate and interpret empirical results from macroeconomic models.
- Apply econometric techniques to macroeconomic data, including time series analysis, forecasting, Bayesian econometrics, and structural modeling.
- Identify appropriate statistical models to address specific economic questions.
Intellectual skills
Develop skills to critically read and review macroeconometric research papers.
Practical skills
Communicate macroeconometric research findings effectively, including:
- Identify relevant literature and datasets for conducting macroeconometric research.
- Perform independent research projects using macroeconomic data and econometric methods.
- Ability to implement empirical methods using the R programming language.
Transferable skills and personal qualities
- Present and communicate research findings effectively through written reports, oral presentations, and visual displays.
- Communication and inter-personal skills required to work as a member of a group.
Assessment methods
Group work assessment - 20%
Computing Test - 10%
Midterm exam 30 minutes - 30%
Exam (End of term) Equivalent of 1.5h on-campus - 40%
Feedback methods
- Class feedback
- Office hours
- Revision sessions
- Discussion boards
Recommended reading
Preliminary Reading List
Textbooks:
- "Bayesian Econometric Methods," by Gary Koop (2003).
- "Bayesian Analysis of DSGE Models," by Edward P. Herbst and Frank Schorfheide (2015).
- "Time Series Analysis," by James D. Hamilton (1994).
- "Time Series Analysis: Forecasting and Control," by George E. P. Box, Gwilym M. Jenkins, and Gregory C. Reinsel (2015).
Papers:
- Bai, J., & Ng, S. (2002). "Determining the number of factors in approximate factor models." Econometrica, 70(1), 191-221.
- Sims, C. A. (1980). "Macroeconomics and reality." Econometrica, 48(1), 1-48.
- Engle, R. F. (1982). "Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation." Econometrica, 50(4), 987-1008.
- Stock, J. H., & Watson, M. W. (1999). "Business cycle fluctuations in US macroeconomic time series." In J. B. Taylor & M. Woodford (Eds.), Handbook of macroeconomics (Vol. 1, pp. 3-64). Elsevier.
No single textbook provides the necessary material for this course. The course itself will be taught using a combination of textbook chapters, elementary journal articles, and working papers. A full reading list with the readings for each topic will be made available at the beginning of the course and through the a Library Reading List.
Study hours
Independent study hours | |
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Independent study | 174 |
Teaching staff
Staff member | Role |
---|---|
Yizhou Kuang | Unit coordinator |
Additional notes
Scheduled activity hours
Staff/student contact (Include lectures, seminars/tutorials/workshops, practicals/laboratory work)
26 (2 hours of lectures – 10 weeks, 6 weeks of tutorials/computer labs)
Private study (Include seminar preparation, presentation preparation and essay preparation)
100
Directed reading
74
Total hours
200
Independent study hours
Private study (Include seminar preparation, presentation preparation and essay preparation)
100
Directed reading
74
Additional notes
Through their pre-requisites students are expected to have good working knowledge of the R programming language.