Service-Led Economic Development: The Case of India

Proposal Description:

This research project focuses on the role of the service sector in the process of economic development. Services play a large and growing role in both developed and developing countries today. The traditional view is that the expansion of service sector is corollary of development; the main driver are manufacturing and agriculture. In this project we study whether technical progress in the service sector is an important determinant of economic growth and of the improvement in the living conditions of millions of people.

India is a case in point. India has experienced significant growth in the past decades and, like in many other countries, the aggregate employment share in agriculture has declined. However there has been no major increase in the employment share of the manufacturing sector. Rather, the lion’s share of the structural transformation has been the growth of the service sector. Is this development process sustainable?

A problem in assessing the role of the service sector in the development process is that directly measuring service productivity is notoriously difficult. First, it is hard to measure the quality of the services provided. Second, there is a lot of heterogeneity in what is common classified as a service sector. Think of lawyers vs janitorial services.

Our approach is to construct and estimate a structural model using granular data across India on employment shares, skills and prices. The project is thus quite data intensive. We have already collected most of the data so we are now turning mostly to the analysis.

The selected applicants will work under the joint supervision of Professors Michael Peters and Fabrizio Zilibotti and interact frequently with Tianyu Fan, who is a PhD students at the economics department.

Requisite Skills and Qualifications:

We invite application from students with a strong background in economics and statistics. Skills and interests in data collection and econometric analysis are important. Knowledge of Stata and the ability to merge datasets are essential skills (please dwell on this in the application). Other quantitative skills (e.g., programming skills) are appreciated but are not essential. We expect the student to work well in a team.

  • Ziyu Zhu