Cost effective panel data collection

Context and primary motivation for the study

The urban literature on developing country cities is still growing. One of the major constraints, however, is access to good quality data. Existing data sources are often costly or difficult to get, frequently do not measure prices, are not individual specific, do not allow for tracking of individuals, and are available infrequently and sporadically.  As a result of this, predictions about the impacts of projects, such as transportation infrastructure, or policy changes in urban contexts are often based on models that have to infer key prices from location choices and must be calibrated to data that is up to 10 years old.  Further, evaluations of projects are not able to make use of modern identification techniques such as synthetic controls which require long panels.

 Non-technical summary of the study design and methodology

This Kampala based study will pilot methods for collecting low-cost, high-frequency panel survey data that improves on existing data sources in three ways:

1. The data will provide information about prices, namely consumer prices, wages, and rents, at the individual and location level;
2. The data will allow for the creation of commuting flows at the individual or group level;
3. The data will allow for tracking of people when they move as well as places over time.