English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

World Input-Output (I/O) matrices provide the networks of within- andcross-country economic relations. In the context of I/O analysis, themethodology adopted by national statistical offices in data collection raisesthe issue of obtaining reliable data in a timely fashion and it makes thereconstruction of (part of) the I/O matrices of particular interest. In thiswork, we propose a method combining hierarchical clustering and MatrixCompletion (MC) with a LASSO-like nuclear norm penalty, to impute missingentries of a partially unknown I/O matrix. Through simulations based onsynthetic matrices we study the effectiveness of the proposed method to predictmissing values from both previous years data and current data related tocountries similar to the one for which current data are obscured. To show theusefulness of our method, an application based on World Input-Output Database(WIOD) tables - which are an example of industry-by-industry I/O tables - isprovided. Strong similarities in structure between WIOD and other I/O tablesare also found, which make the proposed approach easily generalizable to them.

Hierarchical Clustering and Matrix Completion for the Reconstruction of World Input-Output Tables