Economic growth has been at the core of poverty reduction and the increasing prosperity of individuals as well as countries. Despite growing inequality, between 1980 and 2016, the average income of the bottom 50 per cent of earners nearly doubled. Economic growth also allows the government to marshal additional resources for expanding education, social safety net, healthcare, and support for vulnerable groups. Across the world, the drop of "extreme poverty" by more than half since 1990, from nearly two billion to around 700 million, appears to be largely attributed to sustained economic growth, primarily in China and India, and also in other smaller neighbours like Bangladesh. As economic growth in both India and China is slowing down, there is an apprehension about sustaining this trend of reducing the number of people living in poverty. There appears to be no magic formula for enjoying sustained economic growth, as Nobel Laureates Abhijit V. Banerjee and Esther Duflo stated in a recent op-ed, "There is no clear formula for growth." They indicated further, "Unfortunately, just as economists don't know much about how to make growth happen, they know very little about why some countries, such as Mexico, get stuck in the middle-income trap and why some, such as South Korea, don't." In the absence of a sound theory, how should we plan resource allocation for attaining sustained growth for making a developing country like Bangladesh a high-income country by a certain time frame? Should we wait for luck for an accidental outcome to occur?
It appears that Abhijit V. Banerjee and Esther Duflo are not the first globally renowned economists to highlight such weakness about our competence in designing growth path to guide developing countries to keep growing with the target of reaching high-income state, like those 13 countries among 101 who uplifted from middle-income economies in the 1960s to high-income ones by 2008. In 2006, with the support of $4m budget, World Bank-sponsored growth commission, comprising of 21 world leaders and experts, an 11-member working group and 300 academic experts, worked over two years through 12 workshops and 13 consultations to reach a conclusion: "there are no general principles for growth and that no two instances of economic expansion are quite alike." In commenting on this report in an op-ed, Prof. Rodrik shared the opinion that cookie-cutter policy recommendations unaffected by contextual differences do not work anymore. Studies also report that running cross-country growth regressions during the 1980s and 1990s on growth-related data like education, investment, corruption, inequality, culture, distance from the sea, and so on could not reveal any distinct patterns of helping or hurting growth. It appears that there is an acceptance that there is no known recipe for how to make developing countries enjoy sustained high growth, say 7 percent, over 30 years or so to reach high-income status.
In the absence of an acceptable theory, what should we rely on to allocate resources? Where are those few levers that could be pulled to raise growth? In the absence of theories in engineering a sustained growth path, evidence-based economic policymaking has been surfacing as a viable alternative. One of the approaches of getting those pieces of evidence is 'randomised controlled trial' or RCT. Recent awarding of the Nobel Prize in Economics has underscored the importance of RCT in the development policymaking circle. But it does not offer a strong basis to make decisions in a context or situation, which is not a very close replica of the experiment. Particularly, it becomes quite difficult to apply such an approach to support decisions to harness science and technology in a competitive market economy to drive growth, which is a vital area for developing countries to unlock. Due to the dynamic nature of technology, scale, scope, network externality, and the response of competition, the efficacy of evidence is a function of time. A follower cannot replicate the success of a leader by implementing the same set of actions in deriving economic output from technology innovation potential. Decision-making (whether for policy or investment) to harness the potential of technology innovation in a globally connected competitive market economy requires the simulation of likely unfolding scenarios within a model derived of sound theories. In the absence of interpretation of evidence within applicable theories, decision-making based on evidence derived from a controlled experiment, for instance, runs the risk of making a serious blunder. For example, Bangladesh attempted to replicate IT outsourcing industry of India by following India, but it did not lead to success.
Prof. Solow's growth theory around total factor productivity (TFP) by taking into consideration science and technology producing residual effect does not offer any clear path in designing interventions for taking advantage of technology innovation for opening endless frontier of growth. Rather, it only measures TFP as a residual effect by performing regressional analysis on economic data, without having any clear explanation about the policy lever to be tweaked with. By the way, USA's technology-led growth agenda was formulated by an Electrical Engineering Professor of MIT, Dr. Vannevar Bush. He advised President Roosevelt in 1945 to develop national science foundation (NSF) and other building blocks of USA's science and technology (S&T) ecosystem with a very simple argument: U.S. firms must attain the capability of offering increasingly better products at decreasing cost by leveraging a flow of knowledge distilled from S&T progression for creating economic incentives for both producers and consumers. Since then, economists have been trying to understand the role of S&T policy and investment in economic growth by collecting data and performing regression analysis, which led to Solow's understanding as the residual effect--giving birth to TFP. Although Prof. Romer has succeeded in articulating the role of S&T as an endogenous factor by placing ideas as a key factor for producing wealth out of objects (material, energy, labour, capital, etc.), but his work has not given adequate clarification about the way profitability of non-rivalry power of excludable ideas are being shaped by the response of competition and successive generation of technologies. As a result, Romer's work is not sufficient to read evidence to interpret technology innovation dynamics in a globally connected competitive market. To overcome this limitation, bits and pieces of theories produced by Prof. Clayton, Prof. Schumpeter, Prof. KIM & Mauborgne, Prof. Collins, and Prof. Porter, among others are valuable, but they are not sufficient to guide decisions to open the endless frontier of growth for developing countries like Bangladesh.
For these reasons, there seems to be a necessity of undertaking additional work on strengthening theories, gathering and interpreting evidence within them, and simulating future technology innovation dynamics for offering advice in the policy and investment making circles. Instead of pursuing comprehensive reform for opening endless frontier of growth, it might be wise to have policy experimentation within relatively narrowly targeted initiatives to make progress in generating profitable revenue from S&T ideas in addition to labour and natural resources. Such experimentations should be carefully monitored and evaluated in order to learn which experiments work in the local context, which should gradually lead to a scalable fine-tuned model of guiding developing countries like Bangladesh to make steady progress in gaining snowballing growth momentum from S&T for sustaining long term growth for attaining high-income status.
The writer is an academic and researcher on technology, innovation and policy.
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