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H2020

INDLINK Report Summary

Project ID: 661068
Funded under: H2020-EU.1.3.2.

Periodic Reporting for period 1 - INDLINK (Growth and Diversification in the Presence of Industry Linkages)

Reporting period: 2015-04-01 to 2017-03-31

Summary of the context and overall objectives of the project

Countries or regions do not prosper by making more of the same. Instead, the economic growth is often associated with diversification. The diversification process is path-dependent: what a country produces conditions currently what it can produce in the future. The ability to make things evolves by moving from the current set of goods to others that have similar knowledge or physical inputs, which creates linkages between industries. This project investigates the economic consequences of and reasons behind these industry linkages.
Dr. Yıldırım embarked on such a study about understanding the economic growth and diversification process in the presence of many disaggregated and interacting industries, which are the building blocks of a country’s economy. Diversification at this detailed level is not the focus of the leading theories of growth or trade which focus on the relative contributions of core productive factors such as capital, labour, human capital and institutions and technological differences and, hence, the transformation cannot be easily predicted with these models. There is both theoretical and empirical gap in the field of economics to understand diversification and growth process and these questions have momentous societal importance.
This project investigates the industrial patterns of countries in the presence of linkages in four separate but complementary objectives. In the first objective, using the state-of-the art trade models, we show that the industry linkages indeed shape the evolution of comparative advantage and creates a structure. In the second objective, a new trade dataset is created and using this dataset the diversification pattern of countries are related to the country and product level quality measures. In the third objective, temporal aspects of industry spillovers are captured using Diebold-Yilmaz methodology and these spillovers are related to real and knowledge based networks. Separately, we also identified the ecosystem of a product, which facilitates a new product's emergence in a country, from the trade data and showed that it is an important predictor of diversification. Finally, in the fourth objective, effects of one specific type of spillover, namely the Input-Output linkages, on the trading decision and location choice of industries is explored.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

In the first objective, we explored how productivity of countries are shaped by the related industries. According to the Ricardian theory, countries should produce and export relatively more in industries in which they are relatively more productive. We posit that the distribution and transformation of comparative advantage is not random, but rather a path-dependent process, i.e., what a country effectively produces today is an important determinant of which industries it might be productive at tomorrow. We test whether we can predict the productivity levels in an industry from the productivity in related industries by building different measures of relatedness between industries based on Input Output, Labor and Knowledge tables. We then explore whether this structure has a predictive power in determining which industries would grow after North American Free Trade Agreement. In all our tests, we confirm the importance of the structure in comparative advantage patterns of the countries.

In the second objective, we analyze the interaction between the country-level and product level quality indices and the diversification process. To do that, we first created a novel world trade dataset from the raw trade data. We take advantage of the fact that each trade transaction is, in theory, reported twice by the exporter and importing country which helps us estimate reliability of reporting. We implement this procedure to create databases of trade covering more than 50 years, and show how estimates of trade change for countries. Using this new dataset, we then analyzed whether the country level quality parameters have an effect on the export growth at the disaggregated product level. We showed that having higher years of schooling both sped up the overall growth and also helped countries capitalize on the nearby products. But we could not find consistent results when we used the Rule of Law, Democracy level and Control of Corruption. On the product quality side, having more products nearby a product resulted in an increase in the product quality.

In the third objective, using Diebold-Yılmaz methodology we show that the movements in the stock market indicate large amount of spillovers between industries. These spillovers are explained by the Marshallian externalities like input-output relationships, knowledge sharing and labor-pooling, especially during the epochs with no-crisis. Crisis change the fundamental interdependence between industries. This approach bridges the approaches used in the finance literature to industrial growth. We also analyzed the temporal changes in the exports of countries and defined the ecosystem of products, which consists of products facilitating to jump to a new product. We show that the ecosystem is an important predictor of diversification. Network properties of ecosystem reveal important determinants of diversification.

In the fourth objective, we incorporate the input-output linkages to the Ricardian models of trade. We recently witnessed the extreme fragmentation of the supply-chain and countries often push to move up the chain. We explicitly incorporate IO relationships into the trade models and observe that the inclusion of IO linkages forces non-trivial location choices of industries.

All these results will be published as academic papers in high-impact journals and presented in important conferences. There have been significant efforts to reach out to the public and policymakers.

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

All projects listed above are beyond state of the art and have high potential impact and will help us understand development and economic growth. We expect the resultant publications to create interest from both academic community as well as the policymakers and practitioners. In the first objective, we show how comparative advantage evolves within the countries. The main results indicate the path-dependent nature of the economic progress and it gives policy makers novel sets of tools about industrial policy. In the second objective, we created a world trade dataset that covers the period between 1962-2015 and will be widely used. Country-level quality measures have generally been used to track the development at the country level, but here we show that they have an effect at the granular industrial development level as well. We also find that the product quality is affected by the country's presence on the related products. In the third objective, we directly measure spillovers between close to 250 industries using the stock market data and relate this to the real networks. This relationship, however, changes through time and especially hindered during the crisis. In the second part, the ecosystem matrix is a fresh approach to understand product relatedness based on the temporal patterns. In the fourth objective, we incorporate the input-output linkages to the Ricardian models of trade. The field has moved into the direction to models with IO linkages but the effects of these IO linkages on trade patterns have not been studied extensively. Hence, this is a very timely project to pursue with potential to become highly influential in the field.

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