Quantitative Research Methods in Corporate Finance Exemplified by Stata, Python, and R

Data management concerns collecting, processing, analyzing, organizing, storing, and maintaining the data you collect for a research design. The focus in this chapter is on learning how to use Stata and apply data-management techniques to a provided dataset. No previous knowledge is required for the applications. The chapter goes through the basic operations for data management, including missing-value analysis and outlier analysis. It then covers descriptive statistics (univariate analysis) and bivariate analysis. Finally, it ends by discussing how to merge and append datasets. This chapter is important to proceed with the applications, lab work, and mini case studies in the following chapters, since it is a means to become familiar with the software. Stata codes are provided in the main text. For those who are interested in using Python or R instead, the corresponding code is provided on the online resources page (www.cambridge.org/mavruk).