Research Proposal

Intro ’Metrics, Spring 2025

Introduction

• This research proposal is a critical component of your final assessment in this semester’s econometrics course. It evaluates your ability to apply econometric methods in research design and demonstrates your practical skills in analyzing real-world data using econometric software.

• The proposal accounts for \(\textcolor{red}{20\%}\) of your total grade. (Grade breakdown: Attendance \(\textcolor{blue}{10\%}\), Assignments \(\textcolor{blue}{30\%}\), Final Exam \(\textcolor{blue}{40\%}\))

• Due to high enrollment this semester, submissions will be completed in research groups. Each group must consist of \(\textcolor{red}{2}\) students and will submit \(\textcolor{red}{1}\) research project. (Please contact the TA or instructor if you need assistance finding a partner)

Submission Deadline

Time	Task
\(\textcolor{pink}{TBA}\)	Submit research proposal via 教学立方

Basic Requirements:

• Use of microdata sets (cross-sectional or panel data structure) is strongly recommended.

• Please utilize either the microdata sets described below or relevant data from reputable online sources. We particularly encourage the use of cleaned datasets from your course assignments.

• Language: Submissions are accepted in either English or Chinese. English submissions may receive 5-10 bonus points based on quality.

  • Length: Minimum **\(\textcolor{blue}{5000}\)** words plus relevant figures and tables, with a minimum of \(\textcolor{blue}{5}\) pages(A4 Size).

Appendix A: Research Proposal Guidelines

A well-developed empirical research proposal should include:

1. Research Motivation

   • Clearly state the research question or problem

   • Explain the theoretical, empirical, and policy significance of your research

2. Literature Review

   • Provide a concise overview of relevant literature and key findings

   • Identify gaps or limitations in existing research

   • Explain how your study builds upon or extends previous work

3. Research Methodology and Key Challenges

   • What are the key variables in your project? What are the independent and dependent variables? What are the main identification challenges? (e.g., non-random sampling, self-selection, or causality issues?)

   • What main empirical research methods do you plan to use to overcome these challenges? (Such as instrumental variables, difference-in-differences, regression discontinuity, etc.) How can these methods address the identification challenges in your research?

4. Data Sources and Types

   • What is the source of the data, what is the unit of analysis? Why is your chosen dataset suitable for this research project, and what are its advantages and limitations?
   1. In terms of data type, which category does it fall into?
   • cross-sectional
   • panel
   • time series

   2. Does the data require processing, such as removing missing values, outliers, or samples that don’t meet certain criteria? For example, in wage studies, samples of non-working individuals are typically excluded.

   3. Which variables in the database correspond to the independent and dependent variables in your research question?

5. Basic Data Description

   • Basic descriptive statistics of the data: fundamental statistical information about your key dependent variables, independent variables, and other control variables (means, variances, maximum and minimum values, etc.)

   • If possible, conduct mean difference analysis between groups (similar to what we did in class), and use scatter plots to examine relationships between dependent and independent variables.

6. Expected Results

   • What are the expected outcomes of this research project?
   • What direct contributions will the results make to research and policy?
   • What are the potential limitations of the research findings? How might these be overcome?

Potential Research Topics

人口与劳动经济学

• 健康和营养方面：比如肥胖、吸烟和喝酒对工资、家庭消费和福利的影响

• 教育和培训：在职培训对城市居民和农民工就业及工资的影响。

• 失业就业研究：“四万亿”投资与就业、“一带一路”策略与就业、工作流动性研究。

• 劳动力市场市场化程度研究

• 农民工工资上涨的原因？劳动力短缺还是制度原因（最低工资制度还是劳动合同法）

• 人口问题：计划生育、二胎的影响

• 新《劳动合同法》、机器人更新换代、产业升级、新冠肺炎疫情的相关影响？

教育经济学

• 城乡中学教育质量的差异？

• “补课”是否有用？

• “快慢班”对学生成绩的影响？

• 家长投入（时间、金钱等方面）对学生学习成绩的影响？

• “重点学校”对学生成绩的影响？

• “教培”行业被整顿对学生成绩的影响

收入分配与不平等

• 工资不平等和收入不平等(比如：高考制度与工资不平等)

• 机会不平等与代际传递

• 比如：户籍制度与机会不平等

• 比如：家庭背景与机会不平等

• 比如：出生地与机会不平等

城乡移民迁移

• 迁移决策的决定：教育、土地、家庭结构及社会网络如何决定移民的决策？

• 对迁移地的影响：比如农民工迁移对当地就业和工资的影响

• 对迁出地的影响：比如农民工迁移对农村收入分配和贫困的影响

腐败经济学

• 反腐运动对家庭消费、奢侈品消费、餐饮消费的影响？

• 被双规的官员的特征(是否有某些决定性的因素决定了容易腐败？比如是否是副职，是否在某些特定部门（财税、建设、交通、还是…）是否有年龄效应（比如59岁），（找到一个影响最大的来研究）腐败的程度是否有差别？

环境与健康

• 空气、水污染的原因：与交通、工业之间的关系

• 空气、水污染的治理与经济发展

• 空气、水污染对居民健康、劳动生产率、消费、幸福感等方面的影响

Note: The topics listed above represent just a small sample of possible research areas. Each suggested topic has been selected because of available data sources and existing literature foundations. I strongly encourage you to explore topics that align with your personal interests - after all, passion is the best teacher! I look forward to seeing your creative and well-researched proposals.

Appendix B: Important Microdata Database Summary

1. Household Survey

• China Household Income Project Survey (CHIPs): China Household Income Project Survey (CHIPs)

-    Responsible Institution: Beijing Normal University China Income Distribution Research Institute
-    Data Structure: Multi-year Cross-Sectional Data
-    Year: 1988, 1995, 1999, 2002, 2007, 2008, 2013, 2018
-    Coverage: Urban, Rural, and Urban-Rural Migrant Families (Starting from 2002)
-    Main Variables: 1) Individual: Basic Information, Work Information, and Income, etc.; 2) Family: Income, Consumption, Assets, and Living Conditions, etc. 3) Community (Village) Level Information.

• China Family Panel Survey (CFPS): China Family Panel Survey (CFPS)

-    Responsible Institution: Peking University Social Science Survey Center
-    Data Structure: Multi-year Panel Data
-    Year: 2010, 2012, 2014, 2016, 2018, 2020
-    Coverage: Urban and Rural Areas
-    Main Variables: 1) Individual: Basic Information, Work, Income, Health Information; 2) Family: Income, Consumption, Assets, and Living Conditions; 3) Community Information

• China Health and Retirement Longitudinal Study: China Health and Retirement Longitudinal Study

-    Responsible Institution: Peking University China Economic Research Center
-    Data Structure: Multi-year Panel Data
-    Year: 2011, 2013, 2014, 2015, 2018, 2020
-    Coverage: Urban and Rural Areas with **45 Years Old or Older Adults**
-    Main Variables: Very Detailed Personal and Family Information Including Very Detailed Personal Health Information

• China-Indonesia Urban-Rural Migrant Survey: Rural to Urban Migration in China (RUMiC)

-    Responsible Institution: Australian National University, IZA, and Beijing Normal University (Now Replaced by Jinan University)
-    Data Structure: Multi-year Panel Data
-    Year: 2008-2017 (Currently Only Available for 2008-2009)
-    Coverage: Urban, Rural, and Urban-Rural Migrants
-    Main Variables: 1) Individual: Basic Information, Work Information, and Income, etc.; 2) Family: Income, Consumption, Assets, and Living Conditions, etc.

• China General Social Survey (CGSS): China General Social Survey (CGSS)

-    Responsible Institution: China Survey and Data Center, Renmin University of China
-    Data Structure: Multi-year Cross-Sectional Data
-    Year: 2003, 2005, 2006, 2008, 2010, 2011, 2012, 2013
-    Coverage: Urban and Rural Areas
-    Main Variables: 1) Individual: Basic Information, Work, and Income Information, Mainly Collected Values (Including Attitudes and Views on Many Social Issues), 2) Family Structure and Conditions Information, 3) Community Information

• China Labor Dynamics Survey (CLDS)

• China Health and Nutrition Survey (CHNS)

• China Family Finance Survey (CHFS)

• China Basic Education Tracking Survey (CEPS)

• Gansu Basic Education Survey

• China Urban Household Survey (UHS)

• Agricultural Fixed Observation Point Household Survey

• Dynamic Monitoring Data of Floating Population

• Dynamic Monitoring Data of Poverty Population

2. Enterprise Survey

• China Industrial Enterprise Database

• China Customs Import and Export Data

• Listed Company Data (Wan De/Guotai Junan Database)

3. Various Statistical Yearbooks

• County Statistical Yearbook

• Urban Statistical Yearbook

• Provincial Statistical Yearbook

4. Other Network Big Data

• Environmental Data (Ministry of Environmental Protection: Air, Water, and Soil)

• Various Official Data (Province, City, and County)

• Douban, Maoyan, and Yi’en Network Movie Data

• Sports Website Sports Event Data

• Real Estate Data (Lianjia)

• Land Utilization Data (National Land Remote Sensing Data)

• Light Data (NASA)

• JD.com, Tmall, Amazon, and Taobao

• Ctrip Ticket and Hotel Price Data