Research Project: Coordinated Case Studies – Innovation for Productivity Growth in Low Income Countries

Innovation and growth

Research

The research component of the project focuses on understanding innovation, its processes and critical factors and conditions for its diffusion and promotion across a particular group of developing countries in Africa and Asia and its consequences for structural economic change, macroeconomic development and poverty reduction. To this end, Tilburg University and its research partners will develop a set of coordinated thematic case studies for ten selected developing countries.

More specifically, the project will empirically evaluate the effects of existing policies and institutions on innovation and productivity in ten countries. In so doing, it will focus on two themes: Innovation Systems and finance for productivity growth.

Research theme 1: Innovation systems

This project aims to understand the process of innovation, the diffusion of technology and productivity growth. Small firms have more difficulty accessing credit markets, face higher capital prices, suffer more from competition from imports, and have more difficulty in obtaining raw materials, whereas large firms are more productive and are more likely to survive in the long term, securing employment and economic growth (Van Biesebroek, 2005). Regional conditions and infrastructures differentially affect levels of innovation and technological and industrial development in developing countries. However, we do not know why most small firms do not grow bigger in developing countries and why medium-sized and large firms have been able to grow. Specifically, using enterprise level surveys we would like to address the following research questions:

  1. What firm-level and regional-level factors (e.g. size, ownership, market orientation, labor skills availability, gender, firm location, ties between public/private sector, role of intermediaries etc.) hinder or foster the engagement of firms in innovative activities?
  2. What firm-level and regional-level factors hinder or foster the extent to which firms can successfully commercialize the outcomes of their innovative activities?
  3. What is the impact of in-house innovation activities versus collaborative innovative activities or technology acquisition activities on the innovative performance of firms in developing countries?
  4. What is the role of economic spillovers within clusters of firms in fostering economic growth and innovation?
  5. What policy interventions can be designed to enhance the innovative performance of firms and the economic growth of regions in developing countries?
  6. What are the most critical barriers to the process of innovation and the diffusion of technology in low income country setting? What policies are most relevant to overcoming these barriers? Some innovation systems are more productive, measured by patent or other innovation measures for a given outlay. Why the difference?
  7. There is a need to look at how to commercialise research. What types of links between the public/private sectors, universities, governments, NGOs and the private sector are more conducive to innovation activity? What is the role of Universities for facilitating/propagating innovation in LICs? What is the role of the private sector?
  8. What is the role of demand side versus supply side policies (e.g. AMC, tax credit on R&D, techno parks, export processing zones, trade preferences) In what sectors/contexts can they be applied? What are the lessons?
  9. What is the role of intermediaries to bring producers and user of innovation/knowledge together? What is the role of technology brokers, for example or other institutional mechanisms to increase such flows?

Research theme 2: Finance for productivity growth

This project particularly focus on the effects of access to finance in determining productivity of Small and Medium Size Enterprises (SMEs) and how constraints to SMEs' investment finance influence the process of macroeconomic development. Two strands of economics literature build upon this empirical observation and aim to understand first, why such productivity differences do exist across firms, and second, what the implications for macroeconomic development are.  Our project in the “finance and productivity” theme aims to contribute to both of these strands of literature.  Specifically, using enterprise level surveys and data from field experiments we would like to address five key questions:

  1. How does the design of formal and informal financial institutions affect firm productivity dispersion across SMEs?
  2. What are the firm level margins that make finance matter for productivity?
  3. What role do observable managerial decisions (e.g. managerial practices, innovation, product market competition, product quality, technology adoption, location of the plant and the trade status) and managerial characteristics (e.g. gender, age, education, behavioural aspects) play in explaining the nexus between financial development and firm productivity?
  4. How does firms' productivity respond to exogenous developments in the financial environment?
  5. What are the macroeconomic implications of such development experiences?

As in the other theme, we acknowledge not only firm heterogeneity within countries, but also across countries. To account for that, once we have addressed the above questions in each of the developing countries of our study, we will do a cross-country comparison which eventually will suggest different policy recommendations depending on the case studied.

As result of the research undertaken, we expect to be able to identify policies and financial products that help ease SMEs’ financing constraints and improve productivity. We hope to especially identify interactions between firm-level characteristics, such as entrepreneurial traits, country-level factors (such as industrial structure, institutional framework etc.) and access to finance.  Policies and financial products comprise specific lending products (maturity, currency, collateral conditions etc.) and extension services (training, business development services, financial literacy).

Research Methodology

The research approach and the collection of extant and extra data has to be considered in the overall approach of the 3 levels of analysis (micro, meso, macro) involving qualitative and quantitative approaches, which we believe is necessary with a view to the policy development ambitions of the project. This approach summarized in Table 1 on the next page.

Bearing this overall strategy in mind, we envisage a data collection strategy including four interrelated steps providing a basis for combining, generating and aggregating data for the three levels of analysis.

  1. Exploration of extant databases in the case countries and multilateral organizations complemented with the qualitative country descriptions with a view to develop a basic understanding of innovation and productivity (TFP) as well as to identify innovation manifestations and the lack of innovation in clusters, sectors and regions in the case countries.
  2. From this analysis a number of regions, clusters, sectors per country will be selected in which a representative sample of firms will be further analysed in-depth through firm-level survey (extra data, combining CIS-type information and information on productivity). This micro analysis involves measurement of firm characteristics, firm-level innovation and productivity (TFP) and external financial and non-financial factors facilitating or hampering innovation (extra data).
  3. Building upon the micro economic analysis of in step 2 we will further validate and refine our understanding through Randomized Controlled Trials (RCTs), where necessary and possible. We expect to organize this in 6 countries (extra data).
  4. Lastly, for interpreting the outcomes into policy recommendations, the project requires a broader understanding of the meso and macro context including policy context, structural change and transformational innovation issues through the exploration of secondary sources (extant data).