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The growing interest in global value chains (GVCs) has been paired with a greater appreciation of the need for better measurement methods, as reflected by recent initiatives from academia and leading international organizations. This research note focuses on one method to measure GVCs that has been recommended in recent scholarly work, namely input–output models, but goes beyond the industry level of analysis by introducing intra-industry firm heterogeneity. Our illustrative application to multinational enterprises (MNEs) versus domestic firms’ participation in GVCs enhances our understanding of their specific role in GVCs and how such engagement varies across countries and industries. While showing that MNEs’ contribution to value-added exports is considerably smaller than what is suggested by traditional trade statistics, our findings also, interestingly, document that the higher import content of exports of MNEs can go hand in hand with the creation of local backward linkages as a function of their much higher specialization in only parts of the production process vis-à-vis domestic firms. By answering relevant questions on MNEs’ engagement in GVCs that have hitherto been impossible to address comprehensibly and in a cross-country comparative setting, this application illustrates how the methodology has great potential for international business research.

This paper investigates the economic impact of landlockedness applying a conditional convergence model. The econometric analysis is carried out for three income groups (high, upper middle, lower middle and low income) following the World Bank classification according to the level of Gross Domestic Product (GDP) per capita at constant 2010 US dollars and the time before and after the global financial crisis (GFC) of 2007/9. It is for the first time that the consequences of landlockedness for economic activity are investigated with respect to income groups and the GFC. The quality of institutions, investment rate, landlockedness, international trading costs and trade openness are used as conditional variables. The time period under investigation is 1995 to 2016. Descriptive analysis reveals the considerable heterogeneity among the growth performance of countries over time, income groups and geographical status. The econometric analysis suggests that especially for low-income countries a minimum quality of institutions is necessary to embark a convergence trajectory. This paper contributes to the debate between geography and institutions as main obstacles for higher economic growth in landlocked countries. 

This paper investigates the economic impact of landlockedness applying a conditional convergence model. The econometric analysis is carried out for three income groups (high, upper middle, lower middle and low income) following the World Bank classification according to the level of Gross Domestic Product (GDP) per capita at constant 2010 US dollars and the time before and after the global financial crisis (GFC) of 2007/9. It is for the first time that the consequences of landlockedness for economic activity are investigated with respect to income groups and the GFC. The quality of institutions, investment rate, landlockedness, international trading costs and trade openness are used as conditional variables. The time period under investigation is 1995 to 2016. Descriptive analysis reveals the considerable heterogeneity among the growth performance of countries over time, income groups and geographical status. The econometric analysis suggests that especially for low-income countries a minimum quality of institutions is necessary to embark a convergence trajectory. This paper contributes to the debate between geography and institutions as main obstacles for higher economic growth in landlocked countries.

This paper updates the OECD International Transport and Insurance Cost (ITIC) of Merchandise Trade database, which covers more than 180 countries and partners, and over 1000 products from 1995 to 2020. Transport and insurance costs, also known as CIF-FOB margins, are estimated using a gravity model. A cross-validation procedure is used to evaluate model performance. In addition to describing the methodology, the paper highlights that transport and insurance costs are declining as a fraction of trade value, but this reduction has been flattening out in more recent years. However, an alternative measure, the explicit CIF-FOB margins per kilogramme imported, suggests that transport and insurance costs have been actually rising since 2002. Both CIF-FOB margins and cost per kilogramme imported show increases in 2020 when compared to 2019. This is robust to corrections for compositional changes. The methodology is used to produce the International Transport and Insurance Costs of Merchandise Trade data base and the data is made publically available on .Stat under the International Trade and Balance of Payments heading.

In light of the need for detailed and timely internationally comparable trade price indices, this paper describes a multi-tiered methodology to mitigate many of the empirical challenges associated with using customs data, to provide more robust estimates of unit value indices (UVIs) by country and product. UVIs are available for both exports and imports, by reporting country and the CPA 2-digit level of classification. Although the approach cannot capture changes in the quality of products nor compositional changes happening at a lower than HS 6-digit classification, the results indicate that at higher levels of aggregation (SITC 1-digit level), estimated UVIs closely follow price changes obtained from other sources. This is observed both for products with significant and rapid quality changes, such as hi-tech products, and for products with a low rate of quality changes, such as commodities, other primary and low-tech goods. Furthermore, products where little quality change occurs over time show similarity between UVIs and price changes from other sources at lower levels of disaggregation. The methodology is used to produce the Merchandise Trade Price Index and the data is made publically available on .Stat under the International Trade and Balance of Payments heading.

Compte tenu de la nécessité de disposer d'indices des prix du commerce détaillés et actualisés, comparables au niveau international, cet article décrit une méthodologie a plusieurs niveaux permettant d'atténuer bon nombre des difficultés empiriques liées a l'utilisation des données douanieres, afin de fournir des estimations plus robustes des indices de valeur unitaire (IVU) par pays et par produit. Les indices IVU sont disponibles pour les exportations et les importations, par pays déclarant et par niveau de classification a deux chiffres de la CPA. Bien que l'approche ne puisse pas capturer les changements de qualité des produits ni les changements de composition a un niveau plus fin de désagrégation que la décomposition HS a six chiffres, les résultats indiquent qu'a des niveaux d'agrégation plus élevés (niveau a un chiffre de la CTCI), les IVU estimés suivent de pres les changements de prix obtenus a partir d'autres sources. Ceci est observé a la fois pour les produits dont la qualité change de maniere significative et rapide, tels que les produits a haute technologie, ainsi que pour les produits dont la qualité change peu, tels que les produits de base, les autres produits primaires et les produits a faible technologie. En outre, les produits dont la qualité change peu au fil du temps présentent des similitudes entre les indices IVU et les variations de prix provenant d'autres sources a des niveaux de désagrégation inférieurs. La méthodologie discutée est utilisée pour produire l'indice des prix du commerce des marchandises et les données sont rendues publiques sur .Stat sous la rubrique Commerce international et balance des paiements.

The economic disadvantage of landlocked countries is well established in the literature (Faye et al, 2004). This paper investigates the economicimpact of landlockedness on convergence. The econometric analysis is carried out for three income groups and the time before and after the global financial crisis (GFC) of 2007/9. The quality of institutions, investment rate, landlockedness, international trading costs and trade openness are used as conditional variables. The time period under investigation is 1996 to 2016. This paper contributes to the debate between geography (Sachs, 2003) and institutions (Rodrik et al, 2004) as main obstacles for higher economic growth in landlocked countries.

Although the costs associated with the international transport and insurance of merchandise trade are an important determinant of the volume and geography of international trade, remarkably little (official) data exist. Combining the largest and most detailed cross-country sample of official national statistics on explicit CIF-FOB margins to date with estimates from an econometric gravity model, and using a novel approach to pool product codes across HS vintages, this paper presents the new OECD Database on International Transport and Insurance Costs (ITIC) that aims to fill this gap, and describes the methodology used in its construction. The database details the bilateral, product level international trade and insurance costs for more than 180 countries and partners, over 1 000 individual products, for the 1995-2014 time period, and provides an important new tool to further our understanding of global value chains, whilst also forming an important statistical input to the development of coherent and balanced bilateral trade statistics and to the TiVA database. In particular the database provides potential new insights on how distance, natural barriers such as mountain ranges, and inadequate infrastructure, shape regional (and global) value chains.

High concentrations of organic aerosol (OA) occur in Asian countries, leading to great health burdens. Clean air actions have resulted in significant emission reductions of air pollutants in China. However, long-term nation-wide trends in OA and their causes remain unknown. Here, we present both observational and model evidence demonstrating widespread decreases with a greater reduction in primary OA than in secondary OA (SOA) in China during the period of 2013 to 2020. Most of the decline is attributed to reduced residential fuel burning while the interannual variability in SOA may have been driven by meteorological variations. We find contrasting effects of reducing NO x and SO 2 on SOA production which may have led to slight overall increases in SOA. Our findings highlight the importance of clean energy replacements in multiple sectors on achieving air-quality targets because of high OA precursor emissions and fluctuating chemical and meteorological conditions. Clean air actions affect air quality greatly. Here, the authors report widespread decreases in organic aerosol (OA) in China from 2013 to 2020 with primary OA decreasing more than secondary OA. However, further reductions are challenging.

Increasing evidence implicates the tumor microbiota as a factor that can influence cancer progression. In patients with colorectal cancer (CRC), we found that pre-resection antibiotics targeting anaerobic bacteria substantially improved disease-free survival by 25.5%. For mouse studies, we designed an antibiotic silver-tinidazole complex encapsulated in liposomes (LipoAgTNZ) to eliminate tumor-associated bacteria in the primary tumor and liver metastases without causing gut microbiome dysbiosis. Mouse CRC models colonized by tumor-promoting bacteria ( Fusobacterium nucleatum spp.) or probiotics ( Escherichia coli Nissle spp.) responded to LipoAgTNZ therapy, which enabled more than 70% long-term survival in two F. nucleatum -infected CRC models. The antibiotic treatment generated microbial neoantigens that elicited anti-tumor CD8 + T cells. Heterologous and homologous bacterial epitopes contributed to the immunogenicity, priming T cells to recognize both infected and uninfected tumors. Our strategy targets tumor-associated bacteria to elicit anti-tumoral immunity, paving the way for microbiome–immunotherapy interventions. Killing bacteria in tumors boosts survival in a mouse model of colon cancer.