Technological specialisation and productivity divergence in the age of digitalisation, automation and AI

This research project will apply novel theoretical and empirical approaches to the study of technological progress, addressing a key question for contemporary international economic research: to what extent has the digital revolution contributed to the changes in global productivity distribution and leader-follower relations? We focus on growth and productivity channels. Hence, the main objective of the proposed research is two-fold: (1) to re-examine the dynamics of technological specialisation accompanying economic growth under rapid development of digitalisation, automation and artificial intelligence (AI); and (2) to empirically quantify the effects of technological progress in digital technologies (AI in particular) in terms of its contribution to productivity growth and shifts in worldwide productivity distribution. Our study can be located within various areas of economic research: the technological aspects of economic growth and development, international economics, and industrial relations. The empirical analysis will be performed at several levels, using recently released data at country, regional, industry and firm level and the latest methodological developments in the measurement of digital technological progress (described in detail in Sections 3 and 4). It will be complemented by theoretical investigation using selected formal models of technological progress and economic growth. The research strategy will be consistent with the emphasis on the highest quality of research - in line with the strategy of the Gdansk University of Technology as a leading research university. Successful research funding will enable the participation of the Gdansk University of Technology, as a project leader, in policy-oriented discourse on the productivity effects of technological progress. The project will be realized in international cooperation (Italy, Germany).

project webpage

Details

Financial Program Name:

OPUS

Organization:

Narodowe Centrum Nauki (NCN) (National Science Centre)

Agreement:

UMO-2020/37/B/HS4/01302 z dnia 2021-02-01

Realisation period:

2021-02-01 - 2025-01-31

Project manager:

dr hab. inż. Aleksandra Parteka

Team members:

Principal investigator dr hab. inż. Aleksandra Parteka
investigator dr Aleksandra Kordalska
young scholar Zuzanna Helena Zarach
investigator Jakub Growiec

Realised in:

Katedra Ekonomii

Project's value:

722 280.00 PLN

Request type:

National Research Programmes

Domestic:

Domestic project

Verified by:

No verification

Referenced datasets

dataset Data accompanying the paper: "Productivity effects of trade in natural resources – comparison with mechanisms of technological specialization" (Zarach and Parteka, The World Economy, 2023)

Papers associated with that project

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total: 6

Year 2024

How digital technology affects working conditions in globally fragmented production chains: Evidence from Europe
Publication
- TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE - Year 2024
This paper uses a sample of over 9 million workers from 22 European countries to study the intertwined relationship between digital technology, cross-border production links and working conditions. We compare the social consequences of technological change exhibited by three types of innovation: computerisation (software), automation (robots) and artificial intelligence (AI). To fully quantify work-related wellbeing, we propose...

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Year 2023

Artificial intelligence and productivity: global evidence from AI patent and bibliometric data .
Publication
- A. Parteka
- A. Kordalska
- TECHNOVATION - Year 2023
In this paper we analyse the relationship between technological innovation in the artificial intelligence (AI) domain and macroeconomic productivity. We embed recently released data on patents and publications related to AI in an augmented model of productivity growth, which we estimate for the OECD countries and compare to an extended sample including non-OECD countries. Our estimates provide evidence in favour of the modern...

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Artificial intelligence and productivity: global evidence from AI patent and bibliometric data
Publication
- A. Parteka
- A. Kordalska
- TECHNOVATION - Year 2023
In this paper we analyse the relationship between technological innovation in the artificial intelligence (AI) domain and macroeconomic productivity. We embed recently released data on patents and publications related to AI in an augmented model of productivity growth, which we estimate for the OECD countries and compare to an extended sample including non-OECD countries. Our estimates provide evidence in favour of the modern productivity...

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Export diversification and dependence on natural resources
Publication
- Z. H. Zarach
- A. Parteka
- ECONOMIC MODELLING - Year 2023
Low export diversification is a risk-augmenting factor for many countries dependent on natural resources. The literature tends to focus on the growth effects of resource dependence (‘resource curse’ debate) while not much is known on how it affects the variety of non-resource exports. To quantify this effect we decompose the relative Theil index using product-level export data from 160 countries over the time period 1996–2018....

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Joint foreign ownership and global value chains effects on productivity: a comparison of firms from Poland and Germany
Publication
- International Journal of Emerging Markets - Year 2023
Purpose The study aims to examine the joint effects of foreign ownership (FO) and involvement in global value chains (GVCs) on the productivity performance of firms from a catching-up country (Poland) and a leader economy (Germany). Design/methodology/approach The authors use micro-level data on firms combined with several sector-level GVC participation measures. The authors investigate whether the link between productivity and...

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Productivity effects of trade in natural resources—comparison with mechanisms of technological specialisation
Publication
- Z. H. Zarach
- A. Parteka
- WORLD ECONOMY - Year 2023
This paper compares two alternative growth paths, assessing the effects on productivity of specialisation in natural resources (NR) and in technologically advanced products. The empirical analysis exploits product-level export data for 109 developing and 51 developed economies over the period 1996–2018. We document two distinct types of specialisation, based on exports either of natural resources or of technological products, and...

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