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ECM605: Econometrics 2

澳门六合彩开奖记录

ECM605: Econometrics 2

Module code: ECM605

Module provider: Economics; School of Philosophy, Politics and Economics

Credits: 20

Level: Postgraduate Masters

When you'll be taught: Semester 2

Module convenor: Dr Shixuan Wang, email: shixuan.wang@reading.ac.uk

Pre-requisite module(s):

Co-requisite module(s): IN THE SAME YEAR AS TAKING THIS MODULE YOU MUST TAKE ECM604 OR TAKE ECM651 (Compulsory)

Pre-requisite or Co-requisite module(s):

Module(s) excluded:

Placement information: NA

Academic year: 2024/5

Available to visiting students: Yes

Talis reading list: Yes

Last updated: 13 August 2024

Overview

Module aims and purpose

This module will teach students about advanced econometric methods in time series and panel data, and empirical applications of those in macroeconomics and finance. The module is designed as two parts: the first part will focus on time series data, while the second part will deal with panel data. Each topic will be demonstrated by a mixture of 1) econometric method, 2) Monte Carlo simulations, and 3) real world applications. In addition, students will develop their econometric software skills with an introduction to R during the computer workshops.

The aim of this module is to provide students with a more extensive knowledge and understanding of econometrics in both time series and panel data, especially applying the techniques for research. Additionally, the module will teach students how to implement those econometric techniques, using R.

Module learning outcomes

By the end of the module, it is expected that students will be able to:

  1. Understand the special econometrics techniques in time series and panel data;
  2. Implement and apply those econometric methods using R;
  3. Read relevant academic papers and understand the suitability of the methods employed.

Module content

Time series topics may include autoregressive moving-average models, unit root/stationarity tests, model selection and diagnostics, forecasting, and cointegration.

Panel data topics may include pooled regression, fixed effects model, random effects model, and difference-in-differences model.

Structure

Teaching and learning methods

Teaching will be a combination of lectures and computer classes.

Study hours

At least 30 hours of scheduled teaching and learning activities will be delivered in person, with the remaining hours for scheduled and self-scheduled teaching and learning activities delivered either in person or online. You will receive further details about how these hours will be delivered before the start of the module.


聽Scheduled teaching and learning activities 聽Semester 1 聽Semester 2 听厂耻尘尘别谤
Lectures 20
Seminars
Tutorials 8
Project Supervision
Demonstrations
Practical classes and workshops
Supervised time in studio / workshop
Scheduled revision sessions 2
Feedback meetings with staff
Fieldwork
External visits
Work-based learning


聽Self-scheduled teaching and learning activities 聽Semester 1 聽Semester 2 听厂耻尘尘别谤
Directed viewing of video materials/screencasts 10
Participation in discussion boards/other discussions
Feedback meetings with staff
Other
Other (details)


聽Placement and study abroad 聽Semester 1 聽Semester 2 听厂耻尘尘别谤
Placement
Study abroad

Please note that the hours listed above are for guidance purposes only.

聽Independent study hours 聽Semester 1 聽Semester 2 听厂耻尘尘别谤
Independent study hours 160

Please note the independent study hours above are notional numbers of hours; each student will approach studying in different ways. We would advise you to reflect on your learning and the number of hours you are allocating to these tasks.

Semester 1 The hours in this column may include hours during the Christmas holiday period.

Semester 2 The hours in this column may include hours during the Easter holiday period.

Summer The hours in this column will take place during the summer holidays and may be at the start and/or end of the module.

Assessment

Requirements for a pass

Students need to achieve an overall module mark of 50% to pass this module.

Summative assessment

Type of assessment Detail of assessment % contribution towards module mark Size of assessment Submission date Additional information
In-person written examination Exam 60 2 hours Semester 2, Assessment Period
Set exercise Project 40

Penalties for late submission of summative assessment

The Support Centres will apply the following penalties for work submitted late:

Assessments with numerical marks

  • where the piece of work is submitted after the original deadline (or any formally agreed extension to the deadline): 10% of the total marks available for that piece of work will be deducted from the mark for each working day (or part thereof) following the deadline up to a total of three working days;
  • the mark awarded due to the imposition of the penalty shall not fall below the threshold pass mark, namely 40% in the case of modules at Levels 4-6 (i.e. undergraduate modules for Parts 1-3) and 50% in the case of Level 7 modules offered as part of an Integrated Masters or taught postgraduate degree programme;
  • where the piece of work is awarded a mark below the threshold pass mark prior to any penalty being imposed, and is submitted up to three working days after the original deadline (or any formally agreed extension to the deadline), no penalty shall be imposed;
  • where the piece of work is submitted more than three working days after the original deadline (or any formally agreed extension to the deadline): a mark of zero will be recorded.

Assessments marked Pass/Fail

  • where the piece of work is submitted within three working days of the deadline (or any formally agreed extension of the deadline): no penalty will be applied;
  • where the piece of work is submitted more than three working days after the original deadline (or any formally agreed extension of the deadline): a grade of Fail will be awarded.

The University policy statement on penalties for late submission can be found at: /cqsd/-/media/project/functions/cqsd/documents/qap/penaltiesforlatesubmission.pdf

You are strongly advised to ensure that coursework is submitted by the relevant deadline. You should note that it is advisable to submit work in an unfinished state rather than to fail to submit any work.

Formative assessment

Formative assessment is any task or activity which creates feedback (or feedforward) for you about your learning, but which does not contribute towards your overall module mark.

Reassessment

Type of reassessment Detail of reassessment % contribution towards module mark Size of reassessment Submission date Additional information
In-person written examination Exam 100 During the University resit period

Additional costs

Item Additional information Cost
Computers and devices with a particular specification
Printing and binding
Required textbooks
Specialist clothing, footwear, or headgear
Specialist equipment or materials
Travel, accommodation, and subsistence

THE INFORMATION CONTAINED IN THIS MODULE DESCRIPTION DOES NOT FORM ANY PART OF A STUDENT'S CONTRACT.

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