PP413      Half Unit
Growth Diagnostics in Development: Theory and Practice

This information is for the 2021/22 session.

Teacher responsible

Dr. Miguel Angel Santos


This course is available on the Double Master of Public Administration (LSE-Columbia), Double Master of Public Administration (LSE-University of Toronto), MPA Dual Degree (LSE and Columbia), MPA Dual Degree (LSE and Hertie), MPA Dual Degree (LSE and NUS), MPA Dual Degree (LSE and Sciences Po), MPA Dual Degree (LSE and Tokyo), Master of Public Administration and Master of Public Policy. This course is available with permission as an outside option to students on other programmes where regulations permit.


Introductory Microeconomics

Introduction to Econometrics (experience in STATA, R or Python)

Course content

The course enables students to deploy a variety of analytical tools to process and interpret the data and formulate a coherent diagnostic narrative that can make sense of simultaneous observations about growth and social outcomes within a particular context. It covers the theory and practice of the Economic Complexity and Growth Diagnostics frameworks, drawing on empirical research, case studies, and real world-data to a) map place-specific opportunities for productive diversification, b) identify the most binding constraints preventing them from materializing, and c) formulating data-driven policy strategies to overcome them.

The course covers a range of topics in development economics. It begins with an overview of Malthusian dynamics, the Great Acceleration and modern growth models, emphasizing the role of productivity and technology. The course then explores Hidalgo and Hausmann’s (2009) Economic Complexity framework, which takes stock of place-specific productive capabilities and defines a roadmap to potential diversification opportunities that can be tapped by redeploying them, thereby reducing coordination problems that surround the process of self-discovery and structural transformation. The course also reviews Hausmann, Rodrik and Velasco’s (2008) Growth Diagnostic framework, a methodology for identifying the most binding constraints to an objective function (i.e. growth, diversification, private investment). Taken together, Economic Complexity and Growth Diagnostics form an innovative conceptual framework that allows policymakers and policy practitioners to focus limited resources on the most impactful issues.

Students will learn to use data-driven tools such as the Atlas of Economic Complexity to map potential avenues for productive diversification and deploy the four diagnostic principles of Growth Diagnostics to identify the most significant constraints preventing them from materializing. The principles of differential diagnostics are illustrated with practical examples that showcase their deployment to test for binding constraints across relevant production factors, such as finance, human capital, infrastructure, market failures (coordination and information externalities), government failures (taxation, regulations, property rights, and corruption) and macroeconomic risks.

The course concludes with several lectures on policy formulation and implementation. There will be a session on building the state capability needed to mobilise and implement reforms using Andres, Pritchett and Woolcock’s (2012) Problem-Driven Iterative Adaptation approach. Students are expected to implement class concepts, methodologies and frameworks on a country of their choosing through a series of hands-on problem sets that develop incremental research outputs that are then used for the final Growth Diagnostics country report and presentation.


30 hours of lectures in the LT.

The course will have two x 90 minute ‘Harvard’ style lecture/seminars per week.

Formative coursework

Students will be expected to produce 1 essay in the LT.

Short pre-class assignments

Indicative reading

  • Galor, Oded, and David N. Weil (1999). From Malthusian Stagnation to Modern Growth. American Economic Review 89, no. 2.
  • Pritchett, L. (1997) Divergence, Big Time. The Journal of Economics Perspectives 11, No. 3.
  • Hidalgo, C., and Hausmann, R. (2009). The building blocks of economic complexity. Proceedings of the National Academy of Sciences, 106(26), 10570-10575.
  • Hausmann, R., Rodrik, D, and Velasco, A. (2008). Growth diagnostics, in Stiglitz, J. and Serra, N. The Washington Consensus Reconsidered: Towards a new global governance. Oxford University Press.
  • Hausmann, R., Pietrobelli, C., and Santos, M.A. Place-specific Determinants of Income Gaps: New Sub-National Evidence from Mexico (forthcoming in the Journal of Business Research).
  • Hani, F., and Santos, M.A. (2021). Testing for Human Capital as a Binding Constraint (forthcoming in Cambridge University Press)
  • Besley, T., and Persson, T. (2011). Pillars of Prosperity: The Political Economics of Development Clusters , The Yrjö Jahnsson Lectures, Princeton University Press 2011.
  • Andrews, M., Pritchett. L., Woolcock, M. (2012). Escaping Capability Traps through Problem-Driven Iterative Adaptation (PDIA). Center for Global Development, Working Paper 299.
  • Crespi, G., Fernández-Arias, E., Stein, E. (2014). Rethinking Productive Development. Inter-American Development Bank, Washington DC.
  • Collier, P. (2018). The future of capitalism: Facing the new anxieties. Harper Collins Publishers, New York. Chapter 7: The geographic divide: Booming metropolis, broken cities.


Group project (50%) in the LT and ST.
Problem sets (20%), problem sets (20%) and class participation (10%) in the LT.

Course selection videos

Some departments have produced short videos to introduce their courses. Please refer to the course selection videos index page for further information.

Important information in response to COVID-19

Please note that during 2021/22 academic year some variation to teaching and learning activities may be required to respond to changes in public health advice and/or to account for the differing needs of students in attendance on campus and those who might be studying online. For example, this may involve changes to the mode of teaching delivery and/or the format or weighting of assessments. Changes will only be made if required and students will be notified about any changes to teaching or assessment plans at the earliest opportunity.

Key facts

Department: School of Public Policy

Total students 2020/21: Unavailable

Average class size 2020/21: Unavailable

Controlled access 2020/21: No

Value: Half Unit

Guidelines for interpreting course guide information

Personal development skills

  • Team working
  • Problem solving
  • Application of information skills
  • Communication
  • Application of numeracy skills