Business PhD

This module covers:

• philosophical foundations of research – ontology and epistemology
• critical issues relating to the conduct, context and impact of research

This module considers in detail 'academic practice’. It explores the underlying practices that support academic research, and developing academic citizenship, broadly speaking, involves ‘being an academic’ and ‘reflecting on being an academic’ in a challenging yet supportive environment.

It will:

• explore academic practices (critiquing, synthesising, presenting, reflecting)
• expose you to academic practices, encouraging engagement in the intellectual life of the school and participation with the wider faculty outside your supervisory team
• challenge you to ‘practice’ your academic practice, with your peers, and within the wider academic community of the school

The module introduces qualitative and quantitative research designs covering a range of data collection techniques. The module introduces you to the use, interpretation and presentation of an appropriate selection of techniques for the analysis of interview data, and other qualitative data sources.

In terms of quantitative research designs, the module covers measurement issues - validity and reliability issues, descriptive analysis and techniques to test for differences and for relationships.

50% advanced qualitative research methods, covering key aspects of qualitative data collection, management and analysis. Potential topics include:

• Handling Data for Qualitative Analysis
• Coding and Categorisation
• Qualitative Data Analysis
• Grounded Theory
• Narrative Analysis

50% advanced quantitative research methods, including:

• Factor Analysis
• Reliability Analysis
• Multivariate Regression Analysis
• Moderation and Mediation Effects
• Partial Least Squares Modelling
• Experimental Design and Testing

This module covers:

• philosophical foundations of research – ontology and epistemology
• critical issues relating to the conduct, context and impact of research

This module considers in detail three key, interrelated components that constitute the academic research process (i.e., becoming an academic researcher); substance, technique, and context.

• Substance: students will assimilate theoretical building blocks of academic argumentation specific to Business and Society research, equipping them to judge the potential value of new research in the field.
• Technique: students will apprehend and mobilise specific academic techniques such types and styles of questioning, conversation ‘linking’, the role of a discussant and following-up activities.
• Context: students will gain an appreciation of the dynamic and political nature of research dissemination environments and recognise the role of seminars in network building and academic citizenship.

The module introduces qualitative and quantitative research designs covering a range of data collection techniques. The module introduces you to the use, interpretation and presentation of an appropriate selection of techniques for the analysis of interview data, and other qualitative data sources.

In terms of quantitative research designs, the module covers measurement issues - validity and reliability issues, descriptive analysis and techniques to test for differences and for relationships.

50% advanced qualitative research methods, covering key aspects of qualitative data collection, management and analysis. Potential topics include:

• Handling Data for Qualitative Analysis
• Coding and Categorisation
• Qualitative Data Analysis
• Grounded Theory
• Narrative Analysis

50% advanced quantitative research methods, including:

• Factor Analysis
• Reliability Analysis
• Multivariate Regression Analysis
• Moderation and Mediation Effects
• Partial Least Squares Modelling
• Experimental Design and Testing

This module covers:

• philosophical foundations of research – ontology and epistemology
• critical issues relating to the conduct, context and impact of research

This module covers:

• building time series models
• forecasting time series
• modelling volatility
• multivariate time series analysis
• instrumental variables and GMM estimation
• panel data analysis
• discrete choices models
• limited dependent variables models
• conducting empirical econometric research

This module covers:

• corporate financing and investment decisions
• takeovers and mergers and acquisitions
• board structure and corporate governance
• the role of asymmetric Information and agency costs in corporate finance
• asset pricing models and the valuation of securities
• measuring portfolio performance
• market microstructure
• behavioural Finance

This module covers:

• multivariate time series models
• matching techniques
• difference-in-differences
• regression discontinuity design
• event studies

This module covers:

• philosophical foundations of research – ontology and epistemology
• critical issues relating to the conduct, context and impact of research

This module covers:

• building time series models
• forecasting time series
• modelling volatility
• multivariate time series analysis
• instrumental variables and GMM estimation
• panel data analysis
• discrete choices models
• limited dependent variables models
• conducting empirical econometric research

This module covers:

• multivariate time series models
• matching techniques
• difference-in-differences
• regression discontinuity design
• event studies

This module covers the following:

• Dynamic general equilibrium models: Focus: How the time path of consumption, and saving, is determined by optimising agents and firms that interact on competitive markets
• Growth in dynamic general equilibrium: Focus: The Solow model and the data, and the role played by accumulation of knowledge (endogenous innovation) in explaining long run growth
• Growth and Inequality: Focus on the two major changes in the economic landscape over the past 40 years, particularly the US and the UK: Increase in household income inequality and slowdown in aggregate growth
• Real Business Cycles (RBC): Focus: How the RBC approach account for business cycle fluctuations, and what links short run fluctuations and growth processes

This module examines central theoretical aspects from modern microeconomic theory, paying particular emphasis on game theory, imperfect competition and incomplete information.