Orbis Historical Data Processing Manual provides detailed instructions for processing historical data from Bureau van Dijk's Orbis database. It covers system requirements, folder structures, and specific processing steps for firm description, financial, and ownership data. Designed for researchers and analysts, this manual guides users through using Stata for efficient data management. Key topics include data chunking, merging techniques, and cleaning procedures, ensuring accurate and streamlined analysis of firm-level data. Ideal for users handling large datasets in economic and financial research.
Key Points
Outlines system requirements for processing Orbis historical data using Stata.
Describes folder structures for organizing firm description, financial, and ownership data.
Includes step-by-step instructions for data chunking and merging in Stata.
Provides guidelines for cleaning and managing large datasets effectively.
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What are the key steps for processing firm description data?
Processing firm description data involves unzipping RAR files, saving them in designated folders, and using Stata to import and clean the data. Users should identify and handle multiple entries per firm ID by prioritizing incorporation addresses and standardizing formats. The manual recommends breaking large text files into smaller chunks to facilitate easier handling and analysis. Finally, users can merge the cleaned data into a final dataset for further analysis.
How does the manual recommend handling financial data?
The manual suggests processing financial data by breaking down large files into smaller, manageable pieces, especially for extensive datasets like the Industry - Global financials. Each piece can be imported into Stata, corrected for discrepancies in country codes, and saved by country for streamlined analysis. This method ensures that users can efficiently manage and analyze financial information across various firms and countries.
What is the purpose of the Ownership data section?
The Ownership data section details the relationships between firms and their shareholders, providing insights into ownership structures. It includes specific files that outline various types of ownership links, such as domestic and global ultimate owners. The manual guides users through processing these links, ensuring accurate representation of ownership dynamics in the data. This information is crucial for understanding corporate governance and financial networks.
What are the recommended practices for data cleaning in Stata?
Recommended practices for data cleaning in Stata include dropping unnecessary variables, standardizing formats, and ensuring that each dataset has a consistent structure. The manual emphasizes the importance of handling missing values and duplicates effectively. Users are encouraged to implement specific commands to streamline the cleaning process, which can significantly reduce file sizes and enhance the quality of the analysis.
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