Course descriptions

PhD Course on the Economics of Innovation

Here we sketch nine topics / sessions for the course on the economics of innovation. The nine topics are selected on the basis of two criteria. First, they provide a coherent story of the role that innovation plays in economic development, i.e., when seen as a set they provide students with a UNU-MERIT view on ‘innovation’. Second, the topics are chosen for the opportunities they provide for linkages to other research themes in the institute, and, as a logical consequence, to the other PhD courses in the first or second semester.

Each topic, listed below, consists of a number of sub-topics.

We start with the basics: How does innovation interact with the economy? various models of innovation; technological paradigms and trajectories; long waves and (economic) history. Microeconomic principles: equilibrium and optimisation versus disequilibrium and evolution theories.

We turn to the global picture: Economic development and international diffusion of knowledge; structural change and international trade; absorptive capacity and country capabilities; global value chains. Sustainability and energy transitions: large technological systems; transition theory and policy; clean energy and the location of production and consumption.

Innovation systems: Actors and roles: the Community Innovation Survey and firm innovation activities; science, technology and innovation policy; the system of Research and Development (R&D). Localised interaction: University-industry interaction; local economic impact of universities; why innovation clusters; types of local innovation clusters; smart specialisation.

Development or a lack of it: The developmental state: Asian tigers; technology gap model; global value chains. Latin American: the structural model; balance-of-payments restricted growth. Agriculture: the green revolution; diffusion of agricultural knowledge; IPRs. Inclusive innovation: bottom of the pyramid; entrepreneurship and micro credit; sanitation and basic necessities.

Innovation, labour markets and inequality: Development, employment, inequality: empirical regularities; theoretical underpinning. Product and process innovation: effects on employment; general equilibrium and labour supply models; skills biases and structural unemployment. Automation: employment impacts; innovation and (soft) skills. The global picture: trade vs. technology for explaining outsourcing; local labour markets and the China effect. Developing countries: formal and informal sectors and decent employment; international trade and the living wage.

Innovation and the international movement of production factors: Technology-based explanations of trade: basic trade models; extensive and intensive margins; technology gap adjustment theory. Sociology of global value chains. Foreign direct investment and technology spillovers. Economic structure and migration. Technology transfer.

Regions and cities: Geography of innovation: industrialisation and de-industrialisation; economic migration. Inventors and researchers: measuring and explaining output; co-operation networks; migration of high-skilled labour. Cities: Jacobs vs. Marshall externalities; the Triple Helix; academic entrepreneurship.

Public Policy: Indicators for policymaking: the EU scoreboard; Lisbon process. Motivations for policy: market-failure and systems failure; types of policy. Industrial policy: historical experiences and a new fashion.

Sustainability and innovation: Circular economy: engineering and waste; NIMEA accounts; the sharing economy.

PhD Course on Programme and Policy Evaluation

How do we know whether (public) policies or programmes work for development? For example, does business training improve business outcomes? What is the role of networks in adopting new products or technologies? Do R&D subsidies improve private R&D spending? Rigorous evidence on these issues helps to better design and target new programmes and policies.

The main objective of the course is to build problem-solving and research skills for evidence-based interventions and policies, with a focus on developing and transition economies.

Students will learn the basic intuition behind (quasi)-experimental designs including RCTs DID, PSM, IV and review assumptions and criteria for the validity of each of these approaches. Students will gain experience in deciding which approach(es) are most appropriate for a given research question and context. We will draw on several empirical applications in class, and learn about challenges and potential pitfalls in conducting successful impact evaluations in practice. STATA tutorials will help students familiarise themselves with analysing quantitative datasets to assess the impact of a policy or programme using (quasi)experimental methods.

After successful completion of this course students are expected to be able to:

  1. Compare and understand quantitative impact assessment methods;
  2. Analyse and interpret existing impact assessments in relation to theory and policy objectives including the SDGs;
  3. Analyse the quality and appraise the policy implications of impact assessments performed by others;
  4. Design their own impact assessments;
  5. Investigate impact assessment using existing studies and data.

PhD Course on the Governance of Development as a Complex Social System

This course offers an introduction to the study of governance of development as a complex social system. The approach of complex social systems emphasises the emergence, evolution and adaptation of constellations created by social structures, agents and interaction dynamics among them. This approach aims at comprehending the heterogeneity of arrangements, relations and causalities shaping developmental trajectories at sub-national, national, transnational and international levels. By adopting this perspective the course will analyse the evolution of key priorities, tendencies and dilemmas of development in academic debates as well as in policy practice. Therefore, it also introduces governance challenges faced during the processes of steering and coordination of development. Finally, the course analyses how these dynamics inform the governance of public policy areas by analysing governance principles and policy tools. It involves the understanding of policy tools choices in addressing different public policy challenges and tasks.

Following this basic approach, the course encompasses examples from different policy areas, including innovation systems, health, energy and environment, political regimes in the broader context of development. The course will also illustrate how the basic concepts and analytical perspectives on complexity of development can be captured by different methods and tools of analysis (e.g. system dynamics modelling, network analysis, qualitative comparative analysis or Q-methodology). However, it will not be a training in research methods.

This course will contribute to the general objectives of the PhD Programme in two aspects. Firstly, it structures and extends participants’ knowledge about development and its governance dynamics. Secondly, it enhances students’ capacity to analyse policy problems in the context of complex social systems in an ordered and focused approach. The objectives are accomplished through:

  • The mapping and classification of the main elements of the governance of development as a complex social system;
  • The advanced understanding of analytical concepts illustrated by examples from different policy areas;
  • Critical and innovative engagement with the academic debates about the governance of development.


PhD Course on Leveraging Technology and Innovation for the Sustainable Development Goals (SDGs)

In this course, we will study the evolutionary processes that are pushing the knowledge frontiers of science, generating new technology and other forms of innovation and impacting economic development. In particular, we will examine the pathways by which new technology and innovation are contributing to the attainment of the Sustainable Development Goals (SDGs).  Such an enquiry is important, because for certain problems there are no technological solutions at present (i.e. there is a need for innovation), or there are multiple solutions (i.e. choices need to be made) or a solution design for one SDG can pose short-term or long-term risks for the attainment of another (i.e. trade-offs need to be weighed). In this context, governance is key to harnessing the potential of science, technology and innovation for societal welfare. For good governance vis-à-vis technology and innovation, we need to understand the dynamics of actor-group interactions within innovation systems and the possible impact of regulation and incentive design on systemic outcomes.  The challenges being faced by middle and low income countries for the attainment of all the SDGs will be covered through the following lectures. The seminal articles will be covered in the lectures and students will be asked to present case studies. The 17 SDGs will be covered in the student presentations.

PhD Course on (Socio-) Economic Development

The course provides a broad overview of (macro-) economic development. In particular, the course aims to provide students – in an integrated framework – with knowledge on three particular dimensions of economic development: the empirical analysis of (country) development experiences; the theory of economic development; and major issues in development economics.

The course will begin with a discussion of: what is meant by economic (and social) development; how we measure economic and social development (including and beyond per capita GDP); and how difficult the process of development is (based upon a discussion of very long-run data and examples of the few countries that have been able to develop in the more recent past). In the introduction we will further discuss convergence and divergence as well as the role of the Sustainable Development Goals (SDGs) as a means of framing the discussion of development.

The remainder of the course will be organised around particular determinants of economic development. These include:

  • Technology and innovation;
  • International trade and globalisation;
  • Industry and structural change;
  • The deep determinants of development (Geography and Institutions);
  • Human Capital; and
  • Urbanisation and internal migration.

During the discussion of each of these topics emphasis will be placed on identifying and understanding both relevant development theories and empirical evidence and country experiences. In addition to obtaining an understanding of the major issues of development at the macro level, the course will therefore also provide a broad overview of different development theories and an understanding of relevant empirical approaches to address the causes of development at the aggregate level. While much of the discussion of these topics will be on economic indicators such as income per capita, time will be spent identifying impacts on broader social indicators of development, most notably inequality and poverty, with the role of policy in influencing these outcomes also introduced.