Short courses in Survey Data Analysis for Development

We will be offering the following three courses online in March :
Econometrics: The course covers some foundational statistics that are necessary for going forward. We will cover the classical linear regression model (CLRM) and will discuss inference and estimation using the CLRM, as well as common violations of the CRLM assumptions, particularly endogeneity, heteroscedasticity, non-linear errors and omitted variable bias. Participants will be introduced to binary dependent variable models (Linear probability model, probit, logit) South African survey data will be used throughout to estimate the models covered.

Understanding Complex Social Survey Data: The course will introduce the elements of sample design. It will discuss the use of weights to correct for the survey design as well as other common weight adjustments, e.g. for nonresponse and to “calibrate” the sample to external population totals. We will also consider the importance of taking the sample design into consideration when estimating standard errors, in particular in the case of multi-stage samples. Besides learning a set of tools necessary to get reliable estimates from social surveys we will also develop an appreciation of some of the trade-offs faced by survey organisations in collecting the data.

Understanding Panel Survey Data: The aim of the course is to introduce students to the techniques used in the analysis of “cross-sectional” panel data sets, such as the National Income Dynamics Study (NIDS). The course covers panel data management and descriptive analysis using panel data. The course then covers first differencing, fixed effects and random effects estimators as well as the construction and evaluation of transition matrices. Students will also be introduced to the problem of differential attrition.

Survey Data Analysis for Development Course.

 

Mon, 15 Mar 2021 - 09:00 to Mon, 17 May 2021 - 10:30
Venue: 

Each course will be delivered online over a period of ten weeks with one 1.5 hour lecture and one 1.5 hour Stata practical per week.

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