EC3065 Business Statistics Project by vei21189


									                 Department of Economics

        Business Statistics Project

Academic Year: 2008-09                   Lectures:        4
Year:            3                       Seminars:        0
Credits:         15                      Private Study:   108.5
Semester:        2                       Total Hours:     112.5
Prerequisites:   EC3063

Lecturer:        Professor W. Charemza
This module develops specific skills in applied research in economics and business statistics by
means of independent computer-based project work. The module provides experience in
quantitative analysis and forecasting which will be particularly useful for those students who which
to pursue a career in business research and statistical forecasting, or for those in managerial
positions who need to make use of or evaluate sets of forecasts. Students will make an oral
presentation of what they intend to do at the beginning of the second semester.

Lectures at the start of the semester will discuss structure the project and are designed in order to
help the students to choose a specific topic and schedule their work in time. Later the students will
have the opportunity to discuss their progress with the module leader on individual basis.

Typical students will be able to use modern time series packages for the estimation and forecasting
of MARIMA models, (currently STATA9) and for the estimation of non-linear models for long-run
forecasting (currently MICROFIT 4.0). General transferable skills in data collection, data
presentation, report writing and oral presentation will be developed. Students will demonstrate
subject specific skills relating to model estimation, model choice and statistical testing and
At the end of the module a typical student will be able to:
       Competently apply the time series forecasting knowledge for producing and evaluating
       industry specific or related forecasts.
       Apply transferable skills in data collection, Internet literature search, descriptive data
       analysis, report writing and oral presentation
       Demonstrate subject specific skills relating to forecast evaluation, selection, and
       interpretation of the results

There will be one two-hour lecture explaining the organisation of the course in the first week of
Spring Term. There will be also another two-hour lecture given by the MediaCom senior
econometrician (see below). Students will be entitled to a half-hour meeting with Professor
Charemza at the start of the project to discuss their intended project.

The attainment of the intended learning outcomes will be assessed through a written report (with
90% weight) and oral presentation (10% weight). For oral presentation date and place - see 3rd year
Notice Board).
Plagiarism is regarded as a serious offence and is always heavily penalised. In the unlikely case that
plagiarism is suspected, you may be asked to defend the project as your own work in an oral
examination. In case where the plagiarism is confirmed, the most likely outcome is that the author

will be penalised by a zero mark for the entire module.       However,     more    severe   penalties,
including expulsion, cannot be ruled out.

MediaCom Economics Prize
MediaCom, a company which utilises both econometric modelling and time series forecasting as
part of its operations, has agreed to award an annual prize of £50 to the BSc student that produces
the best final year computer-based project in either EC3064 or EC3065. All students following the
BSc (Econ), BSc Business Economics and BSc Financial Economics programmes in 2008/09 will
be eligible for this prize following the midsummer 2009 examinations. The ‘best project’ will be
decided by the Board of Examiners for Economics which includes the external examiners. The
recommendation will be sent to Faculty Board so that the prize can be awarded at the degree
ceremony. This venture with MediaCom has come about through discussions with a former BSc
student who now works for that company as a senior econometrican.
Additionally and separately from the MediaCom Economics Prize, MediaCom are prepared to offer
a job interview to the winner of the prize if that student so wishes, and may also offer other
interviews to students (up to 5 in number) who have also performed well in the project.
A student will need to indicate to us by the signing of a form their agreement that a copy of their
project may be seen by MediaCom. This is so that students can be short listed by MediaCom for
giving a short (10 minutes) presentation on their project to MediaCom here in the department at
Leicester. The presentations will be judged by MediaCom on their criteria of delivery, interpretation
of results and relevance to the commercial world. Following these presentations and MediaCom’s
inspection of the selected projects, job interviews may follow with the company at a later date.
MediaCom will give the lecture for both EC3064 and EC3065 on Friday 20 February, 10.00-12.00
in AC LG017. They will discuss the use of econometrics and statistics in the real world and the use
that their company makes of these areas.
Organisation Details

You should choose the subject of your project and register it with Professor Charemza by the 13th of
February, by e-mail. Such e-mail must be sent from your own University of Leicester address and
have, in the subject line the text ‘EC3064’. The final submission date for the project is Monday 11 th
May. Late submission (unless in exceptional circumstances and with prior agreement) will be
penalised by 5 marks for each day (or part of a day) by which the project is late.

Project Details
Your project should contain the following elements. Each element will carry a fixed share of the
marks, given in brackets.
1.   The project report should begin with an executive summary, giving the main features and
      conclusions of the study in not more than 300 words. You should pay careful attention to the
      clarity of this summary. [10%]
2      This should be followed by a brief, but competent, description of the market you choose to
       analyse, paying particular attention to its institutional characteristics, constraints and
       characteristics of demand. If necessary, you have to recall and reference to the relevant
       economic theory and/or to other, similar, forecasting results. [10%]
3    You need to discuss the properties of data that you have collected to undertake your study,
      including any problems in coverage and any adjustments you have made to the data set. In
      particular, definition of data have to be given and, inf necessary, explained and any
      shortcomings and deficiencies of data should be noticed and acknowledged. This could

          include, for instance, the splicing together           of series measured from different base
          values, conversion of nominal series to ‘real’ values, measurement problems, interpolations,
          reliability and completeness of data sets, etc.). Also, basic time series properties (stationarity
          of data, outliers, structural breaks, etc.) should be identified. [20%]
4        You have to demonstrate the ability to choose an appropriate forecasting method(s) relevant
          to the problem you choose to analyse, justify its usefulness, discuss its advantages,
          drawbacks and constraints. The method of analysis you have chosen to address your
          particular problem should be justified in relation both to the data set used and to the problem
          selected. [10%]
    5.   The main section of the project will be your use of your selected statistical model(s) to the
          problem you have chosen. Each step in your modelling strategy should be clearly identified
          and the main results summarized here in form of graphs and tables. Forecasting of of real
          life data is always difficult and rarely leads to positive results; it is therefore important that
          you are able to look critically at their results and are able to identify drawbacks and
          shortcomings of your findings. You are encouraged to apply more than one forecasting
          method and produce an (optimal) combined forecast. The forecast accuracy has to be
          evaluated and commented upon. Also the analysis of forecasts uncertainties, in forms of
          intervals and densities might improve the quality of this section [40%]
6        The project should always be completed by appropriate conclusions. These conclusions
          should relate to (i) the technique (its peculiarities, drawbacks, advantages, etc) and (ii)
          accuracy of the forecast. Special emphasis should be put on transparency and clarity of
          conclusions. [10%]

Length of Project
No more than 30 pages excluding appendices. Appendices should contain full sets of original data,
full data sources and relevant computer output.
The following text contain chapters giving useful advice on the presentation and completion of
G. Koop (2004), Analysing economic data, 2nd Edition, Wiley.
Organisation Details
You should choose the subject of your project and register it with Professor Charemza by the 13th of
February, by e-mail. Such e-mail must be sent from your own University of Leicester address and
have, in the subject line the text ‘EC3065’. The final submission date for the project is Monday 11th
May. Late submission (unless in exceptional circumstances and with prior agreement) will be
penalised by 5 marks for each day (or part of a day) by which the project is late.

References to books and articles should be given in the full form in the bibliography, as in the
following examples, with only the author’s name and year of publication given in the appropriate
place in the text. The following examples would be referred to in the text as Charemza and
Deadman (1997), Hildreth and Pudney (1999), Lee, Pesaran and Smith (1997), Soper (1997) and
Office for National Statistics (1999).

The choice of topic
Usually, a title of your project will be like ‘Analysis of forecasts of Y in X in the period Z’, where Y
denotes the market, or observable fact you intend to forecast, X denotes the country or region and Z
the period of forecast.
e.g. ‘Analysis of forecasts of package holidays sales in the UK in the period 2005-2007’
                  so that Y= ‘package holidays sales’, X = UK and Z = 2005-2007
Other possible choice of Y’s :
               house prices
               commodity prices (e.g. oil prices)
               electricity consumption
               car accident fatalities
               crime statistics (e.g. homicide rates)
               rate of inflation
               interest rates
               sales of particular products
               traffic growth
               football ticket sales

Of course, you are not limited to these, as you may come up with your own topic or idea. A choice
of interesting and nontrivial (and of, course, well motivated) topic might positively contribute to
your mark.


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