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Applied Empirical Accounting and Finance

Module description

BEAM078 aims to equip students with the knowledge and abilities in order to undertake applied empirical research. During this module students will be introduced to various statistical techniques which are common within the accounting discipline and will be provided with coded STATA examples, tasks and relevant reading material.

The latter part of the module introduces students to the practical process of collecting data from database resources whilst using this data to create and test empirical models using STATA software. Combining knowledge and understanding from the first part of the module with larger worked-examples from the latter part, students will be able to independently conduct empirical research and apply the necessary statistical techniques.

This module prepares you for the dissertation stage (or equivalent) of the Accounting and Finance MSc  and other equivalent programs -  where you are required to conduct empirical analysis based upon a particular research question. This module will provide the basic skills and knowledge-set required to perform this task. More broadly, the course will help you later in your career to perform independent empirical research as well as to be able to read and understand published academic research in Accounting and Finance disciplines. 

Module aims - intentions of the module

The module objectives are fourfold:

1. Equip students with the basic statistics and econometrics knowledge in order to undertake independent empirical research projects.
2. Understand and critique published research in the fields of Accounting and Finance
3. Provide students with the ability to access and retrieve data; create and manage large datasets.
4. Understand and apply basic methodological skills to be able to conduct and understand qualitative research in Accounting and Finance.

Intended Learning Outcomes (ILOs)

ILO: Module-specific skills

On successfully completing the module you will be able to...

• 1. recognise the usage and context of contemporary accounting research;
• 2. distinguish between quantitative and qualitative research processes and techniques
• 3. recognise the theory and rationale behind various analysis and research methods;
• 4. identify practical issues and limitations surrounding research projects;
• 5. identify, critique and develop research papers and research methodology
• 6. interpret and apply data sources, statistics, and relevant;

ILO: Discipline-specific skills

On successfully completing the module you will be able to...

• 7. critically evaluate techniques and methodology used within accounting research;
• 8. identify research questions and opportunities for new and exciting disciplinary research;
• 9. bring together, summarise and critique a rounded body of independently sourced material.

ILO: Personal and key skills

On successfully completing the module you will be able to...

• 10. demonstrate key skills in analytical practices including data handling and statistical techniques;
• 11. demonstrate effective use of learning resources and independent research skills;
• 12. pursue and deliver on a sustained program of individual work successfully;
• 13. complete multistage tasks within a defined period whilst assisted by supervision.

Syllabus plan

• • Week 1 – Introduction, Basic Statistics, Distributions
  • Week 2 – Inference and Hypothesis Testing
  • Week 3 – OLS Regression
  • Week 4 – Dummy Variables
  • Week 5 – Journals, Referencing and Assignment Preparation
  • Week 6 – Reading Week (no classes)
  • Week 7 – Binary Choice Models
  • Week 8 – Testing Model Accuracies
  • Week 9 – Stata Practice
  • Week 10 – Data Collection
  • Week 11 – Stata Focus

Learning activities and teaching methods (given in hours of study time)

Details of learning activities and teaching methods

Formative assessment

Summative assessment (% of credit)

Details of summative assessment

Details of re-assessment (where required by referral or deferral)

Re-assessment notes

Re-assessed assignments will be capped at 50%.

Indicative learning resources - Basic reading

Lectures: face-face and online via pre-recorded videos

ELE – Link

Required reading:  lecture notes and academic papers provided

eLibrary and electronic databases

Additional suggested reading::

DeFusco, R.A., McLeavey, D.W., Pinto, J.E. Runcle, D.E. and Anson, M.J.P (2016), Quantitative Investment Analysis (3rd ed.). John Wiley & Sons.

Indicative learning resources - Web based and electronic resources

ELE – https://vle.exeter.ac.uk/

Key words search

Applied Empirical Accounting Finance STATA Statistics Research