Name File Type Size Last Modified
aggregate.dta application/x-stata 391.9 KB 09/07/2020 03:58:PM text/x-stata-syntax 14.5 KB 09/23/2020 07:26:PM
codebook.txt text/plain 4.1 KB 09/23/2020 07:24:PM
file description.txt text/plain 883 bytes 09/23/2020 07:20:PM
nationalranking12.dta application/x-stata 286.2 KB 09/23/2020 07:23:PM
outcomes12.dta application/x-stata 402.9 KB 09/07/2020 03:35:PM
outcomes13.dta application/x-stata 171.5 KB 09/07/2020 06:54:AM
strategies12.dta application/x-stata 424.6 KB 09/07/2020 06:54:AM
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Project Citation: 

Chen, Yan, Jiang, Ming, and Kesten, Onur. Data and Code for: An Empirical Evaluation of Chinese College Admissions Reforms Through A Natural Experiment. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2020-09-28.

Project Description

Summary:  View help for Summary This repository contains datasets and analysis code accompanying the paper "An Empirical Evaluation of Chinese College Admissions Reforms Through A Natural Experiment" by Chen, Jiang, and Kesten. The datasets contain the college admission data for a county in China's Sichuan Province for year 2008 and 2009. These include students' submitted rank-ordered lists of colleges and admission results. All variables are recoded to remove any identifiable information (including college and high school code). The analysis code can be used to replicate the tables and figures in the paper.
Funding Sources:  View help for Funding Sources National Science Foundation (SES-0720943); National Science Foundation (SES-0962492); National Natural Science Foundation of China (71703038)

Scope of Project

Subject Terms:  View help for Subject Terms economics; college admission; matching
Geographic Coverage:  View help for Geographic Coverage China
Time Period(s):  View help for Time Period(s) 2008 – 2009
Collection Date(s):  View help for Collection Date(s) 2014 – 2017
Universe:  View help for Universe High school seniors in a county in Sichuan Province in China.
Data Type(s):  View help for Data Type(s) observational data; program source code


Unit(s) of Observation:  View help for Unit(s) of Observation Individual applicant
Geographic Unit:  View help for Geographic Unit Sichuan Province, China

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