US-China Tech Decoupling Increases Willingness to Share Personal Data in China

by Yong Suk Lee, Benjamin Larsen, Jingxi Wu

This is a document with information and instruction for data reuse in the paper US-China Tech Decoupling Increases Willingness to Share Personal Data in China submitted to the PNAS Nexus.

Information of corresponding author:

Yong Suk Lee Assistant Professor of Technology, Economy, and Global Affairs, University of Notre Dame, Keough School of Global Affairs 3171 Jenkins Nanovic Hall, Notre Dame, Indiana 46556, USA

Repository supporter: Binh Le

1. GENERAL INFORMATION

1.1 Date of data collection:

09 October 2021 - 07 December 2021

1.2 Geographic location of data collection:

We commissioned the survey firm Qualtrics to conduct the survey on a representative sample of the Chinese internet population. We collected responses that were distributed across China’s provinces.

1.3 Language of the survey:

Simplied Chinese

2. DATA AND FILE OVERVIEW

Data reference: This folder includes information helpful to understand the dataset, including:

• Survey
• Codebooks for both raw and clean datasets
• Datasets: raw and clean

Code file: This folder includes all the code files:

• Code to clean data
• Code to produce tables and figures as presented in the paper

2.1 Survey:

A translated version of the survey to English

2.2 Codebooks:

• Code book for raw data: List and description of all variables in the raw data file. Date updated: April 05, 2023
• Code book for clean data: List and description of all variables in the clean data file. Date updated: April 05, 2023

2.3 Data

• Raw data: File updated on Jun 23, 2022
• Clean data: File updated on July 10, 2022

2.4 Code files

• Figure 1: File updated on May 5, 2023
• Figure 2: File updated on May 5, 2023
• Figure 3: File updated on May 5, 2023
• Figure 4: File updated on May 5, 2023
• Figure 5: File updated on May 5, 2023
• Figure 6: File updated on May 5, 2023
• Tables: Code files for Table 1 and Table 2. File updated on May 5, 2023

Software Implementation

This paper uses R version 4.2.2 to generate the results. However, it could be adapted to use with other softwares or other versions of R. For more information, please refer to The Comprehensive R Archive Network