Postgraduate Diploma in Survey Data Analysis for Development

Purpose

The primary purpose of the qualification is to train working professionals in the skills required to analyse a diverse set of social surveys. Another purpose is to provide sufficient skills that individuals who want to pursue more advanced research (at a Master's level) will be able to do so.

Rationale

The aim of the qualification is to improve the ability of professionals working in the Labour Statistics, Social Statistics and Economic Statistics divisions of Statistics South Africa to analyse the available micro-data in order to address policy relevant questions. A second aim is to equip graduates who wish to enter into employment in the development field with a set of specialist tools that would enable them to seek employment in development agencies. No existing qualification is focused on the skills required to analyse social survey data. Statistics South Africa has asked the School of Economics to provide training for its staff and the introduction of this qualification is partly a response to the demand for this training.

Recognition of Prior Learning (RPL)

Applicants who do not have a Degree or Advanced Diploma but have at least 5 years working experience in data analysis may be assessed through an entrance examination to determine whether they have the equivalent educational ability and motivation as someone with the Level 7 Exit Level Outcomes.

Entry Requirements

The minimum entry requirement to this qualification is

• A Bachelor's Degree in Statistics, Economics or Demography.

This qualification comprises compulsory modules at Level 7 totalling 120 Credits.

• Cross sectional methods, 16 Credits.
• Panel data methods, 16 Credits.
• Consumption and microeconomic theory, 16 Credits.
• The analysis of Complex Surverys, 14 Credits.
• Welfare Measurement, 14 Credits.
• Applied Labour Economics, 14 Credits.
• Research Project, 30 Credits.

1. Understand key theories in economic development and data analysis.
2. Understand key debates in economic policy.
3. Analyse data emanating from complex social surveys.
4. Think critically about what data would be relevant for particular policy debates.
5. Obtain the necessary data if available, for particular policy debates.
6. Present the data in support of particular positions in a comprehensible way.
7. Analyse African data and South African data in particular to the development challenges facing South Africa in the areas of poverty, income inequality and unemployment.

The following Associated Assessment Criteria will be assessed in an integrated manner across the Exit Level Outcomes

• Use statistical software to calculate appropriate statistics from social survey data (e.g. labour force surveys and living conditions surveys) and present the results to an audience of policy makers as well as other researchers.
• Evaluate what survey data would be relevant to address policy questions.
• Understand the Classical Linear Regression Model, when the assumptions underlying the model are likely to be violated (particularly in the case of measurement error and omitted variable bias) and what this means for analysing their results.
• Understand the theory of instrumental variable estimation.
• Estimate instrumental variable models.
• Understand limited dependent variables models.
• Estimate limited dependent variables models.
• Understand the functions and limitations of survey weights.
• Understand the importance of sampling design and the implication of this for standard errors.
• Understand the foundations of microeconomic theory.
• Understand the foundations of consumption theory.
• Use consumption data to test consumption theory.
• Use panel/longitudinal data and understand the advantages it has over cross sectional data.
• Understand the limitations of panel data, particularly differential attrition.
• Measure income, expenditure, inequality and poverty using survey data.
• Undertake welfare analysis using survey data.
• Understand the limitations of income and expenditure data collected in surveys.

Integrated Assessment

Each course will have at least two formative tests using professional econometric software that will take place during the two week lecture block, followed by one or two formative assignments that will be completed after the two week lecture block. These will together amount to 50% of the final mark. A final summative exam will count towards the other 50% of each course mark.