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| Academic Year: | 2018/9 |
| Owning Department/School: | Department of Economics |
| Credits: | 6 [equivalent to 12 CATS credits] |
| Notional Study Hours: | 120 |
| Level: | Masters UG & PG (FHEQ level 7) |
| Period: |
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| Assessment Summary: | CW 50%, EX 50% |
| Assessment Detail: |
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| Supplementary Assessment: |
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| Requisites: | Before taking this module you must take ES50060 |
| Description: | Aims: The aim of this unit is to provide students with the knowledge necessary to analyse macro/time series and panel data. Both univariate and multivariate models are considered with and without the stationary assumption. Learning Outcomes: At the end of the unit students should: (1) develop a comprehensive set of tools and techniques for analysing various forms of univariate and multivariate time series models as well as panel data models and for understanding the current literature in applied time series econometrics; (2) survey the current research topics in time series and panel data econometrics and be critically aware of how the theoretical results are used and applied in practice; (3) be able to apply appropriate econometric models to specific research questions. Skills: Ability to develop rigorous arguments through precise use of concepts and mathematical models Ability to select, analyse and present numerical data using econometric packages Ability to select, summarise and synthesise written information from multiple sources Ability to select and use appropriate ideas to produce a coherent response to a pre-set question Comprehensive and scholarly written communication) Concise and effective written communication (e.g. briefings / written exams) Effective oral communication (e.g. lecture question and answer) Ability to formulate a research question, then develop and present an original & coherent answer Ability to produce work to agreed specifications and deadlines Content: The unit begins with stationary univariate models by explaining the theory of difference equations, demonstrating that they are the foundation of all time-series models. The stationary univariate analysis emphasises the ARMA models and Box-Jenkins methodology. The unit focuses on univariate and multivariate models with and without the stationary assumption. Many recent developments in time series analysis including ARIMA models, unit root tests, cointegration/error-correction models, vector autoregressions and TAR, M-TAR models are considered. In addition modern panel data models will also be covered. There will be numerous examples to illustrate the various techniques, many of which concern models of macroeconomics, finance, international trade and agricultural economics. |
| Programme availability: |
ES50051 is Compulsory on the following programmes:Department of Economics
ES50051 is Optional (DEU) on the following programmes:Department of Social & Policy Sciences
ES50051 is Optional on the following programmes:Department of Economics
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Notes:
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