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Quantifying Central Committee: Approach and Applications. Victor Shih Department of Political Science, Northwestern University Wei Shan Department of Political Science, Duke University Mingxing Liu Peking University, Central Finance and Economic University.
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Quantifying Central Committee: Approach and Applications Victor Shih Department of Political Science, Northwestern University Wei Shan Department of Political Science, Duke University Mingxing Liu Peking University, Central Finance and Economic University
Data: Central Committee (CC) Database • The data quantify all the available biographical information of CC and Alternate CC members from 1921 to 2007 • Each observation (row) represents one CC member • Columns keep track of all the basic demographic variables: birth year, gender, education level…etc. • Additional columns record positions held, start year, and end year (Adolph 2003) • This creates a large database, but one can make logical statements to identify a number of sub-populations among CC members.
A Look at the Original Data Chair, Mass Organization Member, secretariat Member, CAC Vice-secretary, CAC
Some Problems and Solutions • Coding Errors • Solution: Hire Two Coders to Code the Entire Database Separately • Pre-1949 Positions Unclear, except for Party • Solution: develop a detailed picture of the evolution of the Red Army and party before 1949 (on-going) • Bureaucracies Shift Too much • Solution: “Successor Principle” with some caveats • Too Many Positions in the Bureaucracy (below ministerial level) • Solution: All positions are pegged to ministries, provinces, MR, branches of PLA • Overall, new information can easily be incorporated by adding more columns
Factional Influence Indicators (with Shan and Liu) • We record the share of CC members with birth, education, or work ties with a PSC member. • Sounds simple, but it requires highly complex logical statements to derive an annual indicator because we need to: • Select people who are CC members in a particular year AND • Select those with birth and education ties with the PSC member OR • Those who have worked at a particular danwei at the same time that the PSC member worked there
Do the data accord with intuition? Hua Guofeng versus Hu Yaobang
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