Related papers: Learning to Import through Production Networks
Rising economic instability and continuous evolution in international relations demand a self-reliant trade and commodity flow networks at regional scales to efficiently address the growing human needs of a nation. Despite its importance in…
Since 2018, there has been a consistent decline in the distance traveled by U.S. manufacturing imports, reaching a level not observed since 2008. This trend is the result of the substitution away from imports from China and towards imports…
A rich theoretical and empirical literature investigated the link between export diversification and firm performance. Prior theoretical works hinted at the key role of capability accumulation in shaping production activities and…
This paper investigates the causal effect of export intensity on productivity and other firm-level outcomes with a dose-response function. After positing that export intensity acts as a continuous treatment, we investigate counterfactual…
National economies rest on networks of millions of customer-supplier relations. Some companies -- in the case of their default -- can trigger significant cascades of shock in the supply-chain network and are thus systemically risky. Up to…
The vast advances in Machine Learning over the last ten years have been powered by the availability of suitably prepared data for training purposes. The future of ML-enabled enterprise hinges on data. As such, there is already a vibrant…
Production networks constitute the backbone of every economic system. They are inherently fragile as several recent crises clearly highlighted. Estimating the system-wide consequences of local disruptions (systemic risk) requires detailed…
This paper presents a computational evolutionary game model to study and understand fraud dynamics in the consumption tax system. Players are cooperators if they correctly declare their value added tax (VAT), and are defectors otherwise.…
The combination of the network theoretic approach with recently available abundant economic data leads to the development of novel analytic and computational tools for modelling and forecasting key economic indicators. The main idea is to…
Detecting fraud and corruption in public procurement remains a major challenge for governments worldwide. Most research to-date builds on domain-knowledge-based corruption risk indicators of individual contract-level features and some also…
Tourism is a complex dynamic system including multiple actors which are related each other composing an evolving social network. This paper presents a growing bipartite network model that explains the rise of the supply network in a tourism…
Economic growth is often associated with diversification of economic activities. Making a product in a country is dependent on having, and acquiring, the capabilities needed to make the product, making the process path-dependent. We derive…
We analyze the multilayer architecture of the global input-output network using sectoral trade data (WIOD, 2016 release). With a focus on the mesoscale structure and related properties, our multilayer analysis takes into consideration the…
We study spillover effects in corporate toxic emissions using a heterogeneous panel network of U.S. industrial facilities from 2000-2023. Rather than imposing a network structure a priori, we uncover an unobserved web of influence directly…
This paper examines the export promotion of processed foods by a regional economy and regional vitalisation policy. We employ Bertrand models that contain a major home producer and a home producer in a local area. In our model, growth in…
This study examines the network of supply and use of significant innovations across industries in Sweden, 1970-2013. It is found that 30% of innovation patterns can be predicted by network stimulus from backward and forward linkages. The…
Network analysis of inter-industry payment flows reveals structural economic relationships invisible to traditional bilateral measurement approaches, with significant implications for real-time economic monitoring. Analysing 532,346 UK…
Artificial Neural Networks (ANN) which are a branch of artificial intelligence, have shown their high value in lots of applications and are used as a suitable forecasting method. Therefore, this study aims at forecasting imports in OECD…
In economic systems, the mix of products that countries make or export has been shown to be a strong leading indicator of economic growth. Hence, methods to characterize and predict the structure of the network connecting countries to the…
We present a new approach to estimating the interdependence of industries in an economy by applying data science solutions. By exploiting interfirm buyer--seller network data, we show that the problem of estimating the interdependence of…