| CODE | INS5014 | |||||||||
| TITLE | Applied IRM Research Techniques | |||||||||
| UM LEVEL | 05 - Postgraduate Modular Diploma or Degree Course | |||||||||
| MQF LEVEL | 7 | |||||||||
| ECTS CREDITS | 5 | |||||||||
| DEPARTMENT | Insurance and Risk Management | |||||||||
| DESCRIPTION | This study-unit will provide students with a detailed treatment of some of the most salient methodological tools used by leading researchers today within the fields of risk management and insurance. The focus will be on various qualitative and quantitative methods that students may find useful both as part of their dissertations as well as in the pursuit of their future careers. The study-unit will be divided into two main parts, namely qualitative and quantitative research methods. The qualitative methods section will deal with the latest developments and ongoing debates within the field, including focus group analysis, content analysis, triangulation and thematic analysis, as well as the factors to consider when structuring interviews and group discussions. The quantitative section will start off with a quick review of key concepts from mathematics and statistics, before moving on to a selection of topics relevant to risk management and insurance, including stationarity, cointegration analysis and error correction models, volatility modelling (GARCH models), panel data models and forecasting. A strong emphasis will be placed on the underlying intuition behind each tool, and on how they can be used to tackle real-world issues in risk management. The module will also include practical sessions illustrating the concepts learned using the Stata software package, which will further assist students in undertaking their own research. Study-unit Aims: a) To familiarise students with the key qualitative and quantitative methods used in modern-day research in Insurance, risk management and related fields; b) To familiarise students with the intuitions, assumptions and rationale behind each tool; c) To demonstrate the use of methodology tools in independent research and future careers. Learning Outcomes: 1. Knowledge & Understanding By the end of the study-unit the student will be able to: i) Identify and conduct core qualitative and quantitative methods that are used within the Insurance and risk management, including thematic analysis, parametric and non-parametric statistical tests and regression analysis; ii) Define the various research philosophies that exist, and in particular the applicability of each one to different research scenarios; iii) Employ these research tools as part of their own research within Insurance and risk management fields of study. 2. Skills By the end of the study-unit the student will be able to: i) Employ research skills in order to undertake more sophisticated independent research within the field; ii) Identify, interpret and employ the latest empirical literature in Insurance and risk management published in leading academic journals, and be able to explain these concepts in a cogent and professional manner via both written and oral means; iii) Employ the tools learned as part of their future professional careers. Main Text/s and any supplementary readings: Main Texts Yin, R. K., (2013). Case study research: Design and methods. Sage publications. Greene, W.H., (2011). Econometric Analysis, 7th Edition. Pearson Education. Angrist, J. D., & Pischke, J. S., (2008). Mostly harmless econometrics: An empiricist's companion. Princeton university press. Heeringa, S. G., West, B. T., & Berglund, P. A., (2010). Applied survey data analysis. CRC Press. |
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| STUDY-UNIT TYPE | Lecture | |||||||||
| METHOD OF ASSESSMENT |
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| LECTURER/S | Sharon Seychell Jonathan Spiteri (Co-ord.) Mark Lawrence Mario Zammit |
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The University makes every effort to ensure that the published Courses Plans, Programmes of Study and Study-Unit information are complete and up-to-date at the time of publication. The University reserves the right to make changes in case errors are detected after publication.
The availability of optional units may be subject to timetabling constraints. Units not attracting a sufficient number of registrations may be withdrawn without notice. It should be noted that all the information in the description above applies to study-units available during the academic year 2023/4. It may be subject to change in subsequent years. |
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