Reshaping the World Development Indicators (WDI) for Panel Data and Seemingly Unrelated Regression Modeling in Stata

The World Bank's World Development Indicators (WDI) compilation is a rich and widely used dataset about development of most economies in the world. However, after obtaining the data from the World Bank’s web site or the WDI CD-ROM, users need to manage or reorganize the data in a certain way for statistical applications. The World Bank has made great strides in rendering WDI in several forms for download. Yet, seemingly unrelated regression analysis, for example, cannot be performed using any of such structures. Reorganizing the data for seemingly unrelated regression analysis as well as renaming the series with meaningful variable names and maintaining the series descriptors as variable labels in the reshaped dataset represent significant data management challenges for the inexperienced Stata users. I will present a new Stata program, wdireshape, which reduces data management time and effort to zero when the ultimate structure is to estimate panel data and seemingly unrelated regression models, or to have a dataset with the countries as rows and the variables for each year as columns. The wdireshape and paverage commands are available for download from the SSC Archive.