Business Forecasting and Data Analysis 代写

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  • Business Forecasting and Data Analysis
    Coursework Assignment no. 2
    Management Practices and Sales
    Submission of this assignment will take place via Moodle. On the Unit’s Moodle web page there
    are two inboxes related to Assignment 2. In the first (i.e. the SPSS Report Inbox) you have to
    upload your report (maximum 2000 words excluding graphs and tables and any appendices). In
    the second (i.e. the SPSS Calculations Inbox) you have to submit your EViews file comprising
    your calculations (you are allowed to upload only 1 EViews file).
    Submission will open on the 29 th of February 2016 at 9am and will close on Friday the 11 th of
    March 2016 at 11.55pm.
    Working must be on an individual basis. Plagiarism through 'borrowing' of files from others is a
    disciplinary offence. Similarly, you should not 'lend' your work to others, or you may be accused
    of plagiarism yourself. As stated in the unit outline, this assignment counts for 50% of the marks
    in this unit.
    The Software
    SPSS is the required software for undertaking this assignment.
    Background
    Why do management practices differ between firms? Will changing a management practice have
    any effect on sales and/or profits? These are the relevant questions for business that have
    previously been examined using small case studies. More recently, a more systematic way of
    looking at this has been suggested, enabling cross-country comparisons to be made. This
    assignment will ask you to examine how management practices differ between types of firm and
    whether there is a link to sales. You will be required to produce a report on this, using data from
    businesses in one country.
    Management Practices
    You might expect how you run your business to be associated with the success of the business.
    Clearly, there are many different aspects to managing a business and it is difficult to collect data
    on such practices in a way which is helpful, yet a survey has recently been developed to help
    collect data about management practices on a consistent basis. Initial work was confined to just a
    few countries, but the questionnaire has now been refined and analysis extended to many
    countries around the world. Known as the World Management Survey, managers and bosses can
    benchmark their manufacturing firm, hospital, school, or retail outlet against others in their
    country, industry or size class. In the course of their research, Nicholas Bloom and John Van
    Reenen, amongst others, have made their data available through the (US) National Bureau of
    Economic Research and you will be using one of these datasets. Your work will not require you
    to collect further data - all data needed is provided in the SPSS file you can download.
    Essential Reading
    The ideas behind some of the investigation you are required to undertake are based on parts of
    the paper written by Nicholas Bloom and John Van Reenen - "Why do Management Practices
    Differ across Firms and Countries", Journal of Economic Perspectives (2010), pages 203-224.
    This is available on-line to students of the University via the usual channels and is also online at
    WMS HERE, and it is strongly recommended that you read this paper. Other interesting papers
    using the same survey ideas include this one and this one.
    The data
    Between 2003 and 2008 surveys were undertaken in a large sample of medium-sized firms (100
    to 5000 employees). In addition to collecting routine accounting data on sales etc., interviews
    with managers were also carried out to glean information about management practices. These
    questions were in 3 broad areas: "Monitoring: How well do companies monitor what goes on
    inside their firms and use this for continuous improvement; Target setting: Do companies set the
    right targets, track the right outcomes, and take appropriate action if the two are inconsistent?
    Incentives: Are companies promoting and rewarding employees based on performance, and
    trying to hire and keep their best employees?". Across the three categories 18 questions were
    asked, each one scoring from 1 ("worst practice") to 5 ("best practice"). Further information
    about the questions is given in the paper referred to above.
    You will be allocated the data for all firms sampled in a particular country and you are not
    permitted to change this (see the relevant excel file). Once you know the country for which you
    will undertake your analysis, you can download the data directly from Moodle.
    The variables available to you are described below. This is a subset of those used in the
    Bloom/Van Reenen paper and due to various simplifications you should not expect to match the
    results of the paper exactly. A fuller description of the data and its sources etc. is provided there.
    VARIABLE NAME Description
    SALES Sales (in US dollars)
    EMP The number of employees
    HOURST Average weekly hours worked per employee
    CAPITAL Total company fixed assets (US dollars)
    TYPEOWN
    Type of ownership. (Coded as 1:5+ Shareholders; 2:Family, external CEO; 3:Family,
    family CEO; 4:Founder; 5:Other types). Family ownership means second or later
    generation
    MNE
    Business Forecasting and Data Analysis 代写
    Type of multinational (Coded as 1:Foreign multinational; 2:Domestic multinational;
    3:Not a multinational)
    MON1 to MON6 Scores on each of the 6 aspects of 'monitoring'
    TARG1 to TARG5 Scores on each of the 5 aspects of 'target setting'
    INCENT1 to
    INCENT 7
    Scores on each of the 7 aspects of 'incentives'
    MANTIME The number of years the manager interviewed has been employed by the company
    SIC US Industry code Standard Industrial Classification 
    YEAR The year the company data refer to (2003 to 2008)
    RELIABILITY
    An assessment by the interviewer of the reliability of the information (scores are from
    4 to 10)
    COMPANY_ID An identification number for each company
    CTRY Country name
    Bloom and Van Reenen used data for all countries at once, to estimate a pooled data model. As
    you only have one country's data, you cannot attempt this, but for professional empirical work, it
    is sensible to make use of all the data available. Similarly, you should treat each observation as
    independent from the rest, although in fact many firms appear more than once in your data set
    (ie. have data for several years.)
    What you are required to do
    You should write a report (relating to the country you have been allocated) which considers (i)
    whether management practices (i.e scores) vary according to type of firm and (ii) whether there
    is a link between management scores and sales. The items listed below should form the basis for
    your line of investigation (using SPSS) and report. Your report should include commentary and
    discussion interpreting your results. Where new variables have been created or existing ones
    recoded, you should explain what has been done. Make sure your tables are self-
    explanatory. You should also provide a short conclusion summarising your findings. [Note that
    a proper academic paper would include a review of relevant literature - this is not required in the
    assignment]. You should pay some attention to the presentation and formatting of your report,
    which should be sufficient for an 'internal' report, but there is no need to go to extraordinary
    lengths to obtain publishable quality output. Charts should have titles and be suitably labelled.
    Essentials you must include
    1. A suitable chart showing the distribution of the overall mean management score, if all 18
    aspects (questions) are treated equally.
    2. Suitable charts illustrating any variations in the overall mean management score according to (i)
    whether the firm is a multinational or not; (ii) type of ownership; (iii) size of firm (as measured
    by the total weekly labour hours across all employees, i.e. EMP*HOURST).
    3. Suitable statistical tests to examine whether there are variations in the overall mean
    management score according to (i) whether the firm is a multinational or not; (ii) type of
    ownership; (iii) size of firm. Remember to review any assumptions that might be needed for
    these tests.
    4. The results of an estimated multivariate regression model to consider whether management
    scores (and other variables) might explain variations in sales across firms. The model should
    have 'Sales' as dependent variable and you should incorporate the following explanatory
    variables
    a. The total weekly labour hours across all employees
    b. The overall mean management score, if all 18 aspects are treated equally
    c. The total company fixed assets
    d. A dummy variable for whether the company is owned by the founder, or not.
    Ensure that you carefully interpret the SPSS output from your multiple regression,
    including the Adjusted R-squared, the signs of the coefficents, and the Sig. values.
    5. A look at the residuals from your regression to see if they satisfy the usual assumptions.
    6. A prediction from your regression of sales for a firm with 15000 weekly labour hours, a mean
    management score of 3.5, total company assets of 30,000 dollars and which is not owned by the
    founder.
    7. An estimate of the effect on sales of increasing the mean management score from 2.5 to 4.0
    Extensions to enhance your investigation (and improve your mark)
    1. Amend your model of sales to see the effect of dividing up management scores into the three
    broad categories.
    2. Consideration of whether being a multi-national (and whether this is a domestic multinational
    or a foreign multinational) might also help to predict total sales.
    3. Amend your model of sales to see whether the effect of management score on sales might be
    non-linear.
    4. Consideration of whether your model of sales has changed during the years in which the data
    was collected (i.e there is a different intercept each year).
    5. Amend your model of sales to see whether all of sales, labour-hours and capital might better be
    expressed in natural logarithms.
    6. Any other enhancements to your model.
    GOOD LUCK

    Business Forecasting and Data Analysis 代写