Instructions:
You are required to carry out a firm-level analysis explaining firm-level outcomes based on
information available from the Orbis database,
. For example, you could investigate how various firm characteristics affect firm performance.
You need to design an empirical (evidence-based) methodology by extracting, preparing, presenting, describing and analysing the data. You should then provide a written report of the findings, discussing in the report how qualitative methods could be used to support or expand the research study.
Requirements:
(1) Data used in this report will be secondary data.
(2) You must submit a written report by the deadline, which should include:
• A title page and table of contents
• A one page ‘executive summary’.
In the summary, you can introduce the research topic, provide the main objectives, highlight the main findings, and preview the potential contributions to knowledge of your report (about 250 words)
• Methodology.
This part should include an explanation of the empirical model and a justification for the choice of dependent and independent variables (about 250 words
• A description of the data and associated summary statistics.
Summary statistics tables, graphs and correlation/regression analyses should all be created, reproduced in the report and explained (about 500 words)
• A discussion about the results from the statistical analysis, e.g. which firm characteristics are significantly associated with firm performance, are there any new finding if you compare two groups of firms, are the results consistent when you use different variables?
(about 500)
• A discussion about how qualitative methods could be used to support or expand this research agenda, which methods would you apply, how would you go about the arrangements, why would you choose these methods, and what exactly would you hope to learn from them that you cannot find out from your quantitative data analysis?
(about 250 words)
• Conclusion (about 250 words)
(3) The data should be analysed using a variety of statistical techniques such as:
• Graphs/figures (such as pie chart, histogram, scatterplot, etc.)
• Summary/descriptive statistics
• Preliminary data analysis
• Correlation and regression analysis
(4) Guidance:
• You need to provide a justification for the choice of firm predictor/outcome variable(s) and any other key constructs included in your analysis.
• A number of firm characteristics might influence the outcome variable, and you will need to provide a justification for the choices of variables included in your analysis.
• You need to include the analysis based on the whole firm sample. In addition to that, you also need to include any subsample analyses that you think might be useful.
• If you decide to compare two groups of firms, you need to show your workings and provide some justifications as to why you chose them.
For example, if you want to compare foreign firms with domestic firms, you can describe the differences in firm characteristics between these two firm groups and discuss the existing literature about the differences between two groups of firms.
• You should check the multicollinearity of explanatory variables.
• Explanatory notes are required for every table, graph and figure. Do not just cross-reference them and expect the marker to interpret your findings.
• The report should be no longer than 2000 words, excluding the bibliography, graphs and
figures, appendices and footnotes.
Credit will be given for:
presentation and style; the quality of the methodology and sophistication of the statistical analyses; the discussion of the statistical results and the appropriateness of the conclusions; the discussion of how qualitative methods would enhance and/or support the quantitative research; and overall coherence and consistency
• There is no guarantee that all or any of your statistical tests will reveal significant effects, but note that marks are not awarded for obtaining significant results, only for carrying out the analyses properly and interpreting the results correctly.
• The main statistical results must be summarised and included in the written report.
• As the requirement is for a report, academic sources can be cited/referenced using Harvard Referencing Style or footnotes.
The data should be analysed using a variety of statistical techniques, which may include some or all of the following:
Illustrations such as contingency tables, pie charts, histograms, box plots and scatterplots
Preliminary analysis such as data reliability checks, factor analysis, missing values, parametric assumptions, multicollinearity
Summary or descriptive statistics such as measures of central tendency (location) and dispersion (spread), including skewness and kurtosis
Univariate, bivariate and multi-variate analysis including correlation and regression
Hypothesis testing to assess the nature and statistical significance of relationships and differences between variables
Explanatory notes are required for every table, graph and figure. Do not just cross-reference them and expect the marker to interpret your findings.
The main statistical results must be summarised, illustrated and clearly explained in the written report
You need to provide a justification for the choice of firm outcome variables and any other key constructs included in your analyses. A number of firm characteristics might influence the outcome variable, so you will also need to provide a justification for the choice of predictor variables included in your analyses.
As the requirement is for a report, academic sources can be identified using citation and references in Harvard Referencing Style, or by using footnotes, but not both!
If you compare two groups of firms, you need to provide some justifications as to why you chose them.
For example, if you want to compare foreign firms with domestic firms, you can describe the differences in firm characteristics between these two firm groups and discuss the existing literature about the differences between two groups of firms.
The highest scores are likely to be associated with the most sophisticated analyses (e.g. correlation and regression) but good scores can still be obtained for very good use of descriptive statistics .
Last Completed Projects
| topic title | academic level | Writer | delivered |
|---|
