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Short note about DCPAE courses

08 June 2023

Johnson Kansiime, one of our PhD students at RuWell, has actively pursued several capacity-building and learning activities over the past few months. He has diligently participated in three courses: Advanced Applied Econometrics I, offered by the University of Hohenheim in Stuttgart; Introduction to Geographical Information Systems and Spatial Data Analysis, offered by our institution, IAMO; and the High-Quality Research Data course, also provided by IAMO. These courses have significantly enhanced Johnson's understanding of the respective thematic areas.  

Whilst the course, high-quality research data covered the fundamentals of data preparation, cleaning, handling missing data, and ensuring the representativeness of various data samples, the Advanced Applied Econometrics I course particularly emphasized the foundations of statistical inference and the application of various linear panel data models, such as pooled OLS, fixed effects within models, random effects models, fixed effects and random effects with the Mundlak approach, linear panel data models with instrumental variable (IV) regression, and mixed effects models. Special attention was given to understanding the conditions under which these models are appropriate and unbiased, thus enabling researchers to make informed choices in selecting the appropriate model for different circumstances. 

The most recent course, Introduction to Geographical Information Systems, has equipped Johnson with vital skills for effectively presenting geospatial data in scientific papers through the use of self-developed maps. The course also addressed the challenge of accounting for geospatial similarities in various study units in a sample, which can introduce bias when using traditional econometric models that do not cater for geospatial patterns. This challenge can be addressed through the utilization of spatial econometric models and the estimation of geospatial parameters like Moran's I, among others. Additionally, the course provided valuable knowledge on leveraging data hidden in digital aerial photographs (rasters) and other remote sensing features to derive important variables that may not be readily available from certain secondary data sources. The Doctoral Certificate Programme Courses are an integral part of the IAMO graduate school, and they play a key role in enhancing the capacity of PhD students to ably conduct scientific investigations.