The Rise of Unskilled Poor Mega-Cities in Developing Countries [Research Assistantship]

Department: Economics and International Affairs (ESIA)
Professor Remi Jedwab
The Project: I’m a specialist of urban issues in developing countries. In various papers, I have studied the causes and consequences of fast urbanization in Africa, focusing on demographic and economic factors. You can find my research here: http://home.gwu.edu/~jedwab/

I would like to keep working on this topic, and I hope that you are also interested in the topic, and the following project.

Urbanization and economic development have been coupled throughout history. However, post-war developing countries have urbanized in a fundamentally different manner than the historical experience of developed countries. The post-war period has witnessed the rise of poor mega-cities in developing nations. Kinshasa, Karachi, and Lagos comprise some of the largest agglomerations on the planet today. The prevalence of poor mega-cities today counters historical experience. In the 19th century, the largest agglomerations in the world were exclusively located in the most advanced economies (e.g. London, New York, and Paris). The mega-cities of today’s developing world are also unlike their historical counterparts in that their massive size does not indicate higher living standards. Developing countries today are urbanizing into poor mega-cities that appear unable to capitalize on the externalities of their rich-country peers.

Our aim in this project (my co-author is Dietrich Vollrath from the University of Houston) is to document the rise of these poor mega-cities, exhibit their structural features, and explain why they differ from the historical experience of urbanization and rapid economic growth. In particular, we will use various historical and contemporary sources to recreate the “skill” structure (education and occupation) of today’s 300 largest cities over the past 30-200 years (depending on data availability), in order to show that many cities of today’s developing world are not particularly skill-intensive (think of Dhaka, Kabul, Kinshasa, Nairobi, Ho Chi Minh City, etc., where most people have petty jobs in the service sector), unlike most cities of the Industrial Revolution era (in the UK, the US, France, etc.) and most cities of today’s “successful” developing countries (China, India). In other words, many mega-cities in poor countries only create jobs in low-skill sectors, which challenges the theory that cities necessarily act as centers of human capital accumulation and promote knowledge spillovers. Using economic theory and descriptive evidence, we will investigate how various demographic (e.g., high fertility rates) and economic (e.g., a specialization in natural resource exports) factors may explain the disconnect between urbanization, human capital accumulation and development.

The results of this research will develop the understanding of the factors underlying urbanization in developing countries and the factors affecting urbanization’s contribution to development outcomes. This research will be useful to economists, geographers and historians, as well as to organizations that advise governments on urban policy. Specifically, we will present some of these results at the 2016 World Bank-GWU Urbanization and Poverty Reduction Conference (Theme: “Sustainable Urbanization”) and in the 2016 African Economic Outlook (Theme: “Sustainable Cities)” published by the African Bank of Development (AfDB), the Organisation for Economic Co-operation and Development (OECD) and the United Nations Development Programme (UNDP).

Tasks: You will be the one collecting the data for us. In particular, you will use various historical and contemporary sources to recreate the “skill” structure (education and occupation) of today’s 300 largest cities over the past 30-200 years (depending on data availability). (1) We will first identify the 300 largest cities that will comprise our sample. (2) You will use two main sources of data to recreate the skill structure of each city (using various decompositions of skills: based on education, based on technical occupations, etc.) for as many different years as possible as far back as 1800 when possible. The three main sources that we will use are:

  • Demographic and Health Surveys Stat compiler http://www.statcompiler.com/ This compiler is very to use, so the skill structures of each city-year observation can easily be generated and then pasted into an excel file
  • IPUMS International (Census Data): https://international.ipums.org/international/samples.shtml
    This website also has a data compiler, so the skill structures can easily be generated and then pasted into an excel file
  • IPUMS Usa (Census Data for the US from 1850 to date) https://usa.ipums.org/usa/
    This website also has a data compiler, so the skill structures can easily be generated and then pasted into an excel file

We will also various (historical or contemporary) population census reports available online to complete the data set.

Once we have the data for as many city-year observations, we will be able to analyze how the distribution of skills has evolved over time between the cities of today’s developed countries when they were still developing countries, and also how the distributions vary across space today between the successful and the unsuccessful developing countries. As such, in terms of tasks, you will mostly use these online stat compilers and excel, and help me find more sources available on the internet.

I also have a couple more projects on urbanization, natural resource exports, ethnic politics, Sub-Saharan Africa, etc. for which I may also sometimes need help. I would then also ask you to help me with some tasks, depending on the progress you’re making on the main project.

Time Commitment/ Credits: 7-9 hours per week; 3 credits
Contact Email: jedwab@gwu.edu
To Apply: I’m flexible, but I’m looking for either 7-9 hours or 4-6 hours a week (Students seeking three credit hours should expect to dedicate an average of six to nine hours a week. Students seeking two credit hours should expect four to six hours a week). I’m rather indifferent.

Please send me a CV with a short paragraph on why you’re interested in the project. It’s not the first time I supervise undergraduate students from the University Honors Program, and I have had in the past good students as well as bad students. I would like someone who is very committed (because it is costly to train someone), and that I would also mentor (I could write your letters of recommendation, eventually help you get admitted to a master’s program or get a job in development, etc.). This past year, one of my students from the Honors Program obtained a grant of $1500 from GWU thanks to me, whereas I found a short-term consultancy at the World Bank for another student. In other words, if you work well, I will help you as much as I can.