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India, the world’s leading rice exporter, banned the export of non-Basmati white rice, accounting for 25% of its total exports (or 10% of the global rice trade). The ban aims to ensure availability to domestic Indian consumers and reduce domestic market prices, impacting global rice market accessibility, consumers, and producers across twelve regions. The study utilized the global simulation model (GSIM) to analyze the effects of trade restrictions on industries. The model uses national product differentiation to assess trade policy changes at global, regional, or national scales. It examined importer and exporter effects on trade values, tariff revenues, exporter surplus, and importer surplus. It found that India’s Voluntary Export Restraint (VER) ban on non-Basmati rice resulted in a higher local price and a negative global net welfare impact of USD 1.7 billion. The losses decreased to USD 1.4 billion when importing countries responded by reducing rice import tariffs by 25% and USD 1.1 billion when importing countries reduced tariffs by 75%. Sub-Saharan Africa, the Middle East, North Africa, and the Gulf Cooperation Council regions were most affected. The study also found minimal impact on consumer surplus in India due to inelastic rice demand.

The world economy has witnessed a rise use of antidumping (AD) and countervailing (CV) duties in recent years. Using a computable partial equilibrium model, this article simulates the economic and welfare impacts of the US's AD/CV duties on photovoltaic (PV) products imported from China and Taiwan China in 2015. The result shows that the AD/CV duties have significant trade destruction and trade diversion effects, relatively moderate trade deflection and depression effects. In the context of globalization, the AD/CV duties have limited remedial effect on the US PV industry, but the United States bears the biggest welfare loss for its AD/CV duties.

This article illustrates a unified conceptual approach to metadata, whereby metadata describing the information content and structure of data and those describing the statistical process are managed jointly with metadata arising from administrative and support activities. Many different actors may benefit from this approach: internal users who are given the option to reuse information; internal management that is supported in the decision-making process, process industrialisation and standardisation as well as performance assessment; external users who are provided with data and process-related metadata as well as quality measures to retrieve data and use them properly. In the article, a general model useful for metadata representation is illustrated and its application presented. Relationships to existing frameworks and standards are also discussed and enhancements proposed.