module specification

This module provides a foundation in statistical methods and analysis and focuses on econometrics. It examines the theory and application of the Classical Linear Regression Model (CLRM), providing a firm grounding in the theory of Ordinary Least Squares (OLS) and an appreciation of its limitations. It provides a theoretical understanding of the causes, consequences and detection of, and remedies for, the violation of the assumptions of the classical linear regression model.  It develops knowledge and skills to use standard statistical/econometric software packages (e.g. EViews) and apply techniques to economics, finance and banking problems and models.

The module provides students with the knowledge and skills to evaluate empirical work within economics, finance and banking.

A range of transferable and subject specific skills are developed, in particular: self- assessment and reflection; peer assessment; written; IT; subject research; problem solving; data and quantitative analysis; analytical and critical thinking.

Equality is promoted by treating everyone with equal dignity and worth, while also raising aspirations and supporting achievement for people with diverse requirements, entitlements and background.

LO1

Review of statistics:  probability distributions, sampling theory, estimation, confidence intervals, hypothesis testing and applications to economic, finance and banking.
Correlation and regression analysis: applications to economics and finance.
Introduction to Econometrics: economic theory versus empirical methods
The Classical Linear Regression Model: assumptions, specification, estimation and hypothesis-testing.

LO2

Violations of the assumptions of the classical linear regression model. Causes, consequences, tests and solutions for regression problems such as multicollinearity and heteroscedasticity.
Functional form and dummy variables.
Evaluation of regression models.

LO3

Use IT to access sources of relevant economic and financial information. Development of intermediate-level knowledge of spreadsheets, using workbooks and solving problems by analysing data.
Producing, interpreting and explaining the output of dedicated econometric software (e.g. EViews).

Learning consists of ‘formal’ classroom learning directed by the teaching team, and reflective independent learning. The formal learning involves lectures, seminars and computer-based exercises that may use software (e.g. EViews), while the independent learning includes reading of the course material, and working on weekly exercises.

The module is delivered in a three-hour session each week which comprises a two-hour lecture, and a one-hour seminar. The two-hour lecture introduces students to key concepts. Seminars enable students to gain a deeper understanding of the key concepts and present their solutions to the problems set and raise questions on the lecture material. Using computers, students undertake empirical analysis using IT software. The seminars provide opportunities for active and reflective learning, and also formative feedback. The virtual learning environment (WebLearn) supports relevant module learning and teaching materials such as lecture notes, seminar materials, IT exercises, past exam papers, coursework brief, module handbook, EViews videos and other learning materials.

All activities provide students with knowledge and understanding of statistics and econometrics. The weekly exercises give students diverse skills as working independently, problem solving, writing concisely and clearly, retrieving secondary data from various online sources and describing and exploring them using econometric software and spreadsheets.

Professional and transferable skills are developed in lectures and seminars, and through independent directed learning and assessment. Skills development is enhanced through working cooperatively solving economic problems.

On successful completion of this module students will be able to:

1. Demonstrate a broad knowledge and a systematic understanding of statistics; correlation and simple regression analysis; hypothesis testing and application to economics, finance and banking.
2. Identify and find solutions to regression problems, conduct appropriate econometric tests and evaluate regression models.
3. Analyse and interpret data and explain multiple regression results.

Reading List Talis Link:

https://bblearn.londonmet.ac.uk/webapps/blackboard/content/launchLink.jsp?course_id=_45667_1&tool_id=_2924_1&tool_type=TOOL&mode=cpview&mode=reset

Core Textbook:

Asteriou, D and Hall S G (2016). Applied econometrics, 3rd ed., Palgrave Macmillan
     [This is an E-BOOK. Hard copies are available at Holloway Road 330.015195 AST]

Additional Textbooks:

Barrow, M. (2017) Statistics for economics, accounting and business studies, 7th
     ed., FT Prentice Hall. [This is an E-BOOK. Hard copies available at Holloway Road 519.502433 BAR]

Bradley, T. (2007). Essential statistics for economics, business and management, John Wiley & Sons Ltd. [Hard copies available at Holloway Road 519.5 BRA]

Dougherty, C. (2016). Introduction to econometrics, 5th edition, Oxford.
    [Hard copies available at Holloway Road 330.015195 DOU ]
   
Gujarati, D. N. (2015). Econometrics by example, 2nd ed., Palgrave MacMillan
     [This is an E-BOOK. Hard copies available at Holloway Road 330.015195 GUJ]

Gujarati, D.N. and Porter D. (2010). Essentials of econometrics, 4th ed., McGraw
     Hill. [Hard copies available at Holloway Road 330.015195 GUJ]

Gujarati, D.N. and Porter D. (2014). Basic econometrics, 6th ed., McGraw Hill
     [Hard copies available at Holloway Road 330.015195 GUJ]

Oakshott, Les (2016). Essential quantitative methods for business, management
     and finance, 6th ed. Palgrave Macmillan. [This is an E-Book. Hard copies are available at Holloway Road 658.0015195]

Waters, Donald (2011) Quantitative methods for business, 5th ed., FT Prentice Hall,
    [This is an E-BOOK]

Wooldridge, J. M. (2016). Introduction to econometrics, 4th ed., South Western
      College Publishing. [This is an E-BOOK. Hard copies are available at Holloway Road
      330.015195  WOO]