Engel’s law in the commodity composition of exports

Different shares of distinct commodity sectors in production, trade, and consumption illustrate how resources and capital are allocated and invested. Economic progress has been claimed to change the share distribution in a universal manner as exemplified by the Engel’s law for the household expenditure and the shift from primary to manufacturing and service sector in the three sector model. Searching for large-scale quantitative evidence of such correlation, we analyze the gross-domestic product (GDP) and international trade data based on the standard international trade classification (SITC) in the period 1962 to 2000. Three categories, among ten in the SITC, are found to have their export shares significantly correlated with the GDP over countries and time; The machinery category has positive and food and crude materials have negative correlations. The export shares of commodity categories of a country are related to its GDP by a power-law with the exponents characterizing the GDP-elasticity of their export shares. The distance between two countries in terms of their export portfolios is measured to identify several clusters of countries sharing similar portfolios in 1962 and 2000. We show that the countries whose GDP is increased significantly in the period are likely to transit to the clusters displaying large share of the machinery category.

Export Specialization of India with Top Five Agricultural Economies: An Application of RCA and RSCA

The paper attempts to determine Revealed Comparative Advantage (RCA) and Revealed Symmetric Comparative Advantage (RSCA) of Indian agriculture sector with respect to top five agriculture exporting countries viz; USA, UK, UAE, Singapore and China. The study evaluates the structure of comparative advantage from 1995-2017. Data as per the Standard International Trade Classification (SITC-1) is used to compute RCA and RSCA index. The indices reveals the comparative advantage in case of majority of commodities like fish, fish preparations, fruits, vegetables, sugar, sugar preparations, miscellaneous food products, wood, lumber and cork. Increasing world demand for exports trailed by the competitiveness of Indian exports has played an important role in export performance.

Przewaga komparatywna krajów Andyjskiego Wspólnego Rynku (CAN) w międzynarodowym handlu towarami z Mercosur

Celem artykułu jest określenie przewag komparatywnych w handlu towarowym czterech krajów ugrupowania CAN nad pięcioma krajami ugrupowania Mercosur w latach 2007–2017. W tym celu zastosowano wskaźnik ujawnionych przewag komparatywnych Balassy oraz klasyfikację towarów SITC (standard international trade classification). Badanie poprzedzono omówieniem międzynarodowych obrotów towarowych CAN z Mercosur. Przeprowadzone badanie ujawniło przewagę komparatywną CAN w następujących segmentach klasyfikacji towarowej SITC: trzecim (surowce mineralne, smary i podobne materiały), ósmym (inne wyroby przemysłowe) oraz dziewiątym (inne wyroby niesklasyfikowane). Szczególnie wysoką wartość RCA w latach 2007–2017 odnotowano w przypadku segmentu trzeciego. Świadczy to o dużym znaczeniu towarów przemysłu wydobywczego dla gospodarek narodowych należących do CAN.

Physical and Monetary Methods for Estimating the Hidden Trade of Materials

The hidden trade of a material (e.g., aluminum) refers to the trade of that material embedded in final products (e.g., automobiles). There are two methods for estimating the hidden trade amount of materials: (1) the physical method relies on the physical trade data (measured by physical units) in which products are categorized according to the standard international trade classification codes or the harmonized system codes; and (2) the monetary method relies on the monetary trade data (measured by monetary units) in which products are categorized in accordance to the sectors of an input–output (IO) table. Information on material concentrations in products can be relatively quickly estimated by an IO-based model in the monetary method, but will have to be collected from various sources with intensive time cost in the physical method. Exemplified by the U.S. hidden trade of aluminum, iron, and copper in 2007, this study attempts to compare the two methods. We find that, despite the unavoidable but reasonable differences in the amounts of three metals trade, the results generated by the two methods are consistent with each other pretty well for final products at the level of end-use product groups (e.g., total transportation facilities). However, the comparison for specific products (e.g., automobiles) is challenging or does not generate consistent enough results. We suggest that similar estimations be done for more materials, more countries/territories, and different years, to gain experience, reduce estimation time and costs, and increase the knowledge base on metal flows in society.

Competitiveness as the Ability to Adjust: the EU–10 Exports Structure and Its Convergence to the German Pattern

Competitiveness of a nation is associated with a set of characteristics that enable structural adjustment to global technological trends, and as a consequence, a rise in the living standard of its citizens. For catching-up economies, GDP convergence towards the most developed economies, constituting their developmental goal, relies upon its ability to shift production and exports structure towards specialization based on knowledge and innovation. Thus, in this paper, competitiveness is evaluated through structural adjustments of exports, and for catching-up economies (the EU–10 states) it may be understood as the ability to close the structural gap to the most developed countries (here: the strongest EU member economy: Germany). We analyse the evolution of the EU–10 nations’ exports specialization in the years 2000 and 2014, checking whether the convergence towards the German exports pattern can be observed, and which of the analysed economies shows the best ability to shift its exports structure towards high-tech specialization. We look additionally at exports structures in 2004 (the year of EU-accession of eight out of 10 countries in the sample) and in 2009 (world trade collapse during the economic crisis). The analysis is based on the Revealed Comparative Advantage (RCA) concept by Balassa (1965). We use the UN Trade Statistics data in the Standard International Trade Classification (SITC), Rev. 4. Commodity groups are classified following the methodology developed by Wysokińska (1997, p. 18).

Exportações baianas: especialização e desempenho no período 2003-2015

As exportações favorecem o crescimento econômico, o desenvolvimento empresarial, a inovação, a criação de emprego e a competitividade. A Bahia é a maior economia do Nordeste, com grande representatividade no comércio externo da região, exportando e importando produtos de classes setoriais distintas, dos primários àqueles com tecnologia de ponta. Nessa perspectiva, o objetivo deste artigo é analisar a especialização e o desempenho das exportações baianas por meio de índices de competitividade. Realizou-se a classificação da pauta exportadora por meio do Standard International Trade Classification (SITC), metodologia adotada pela ONU com o intuito de resumir todos os produtos em nove categorias ou grupamentos setoriais. A especialização das exportações baianas baseia-se em produtos químicos e derivados, combustíveis e lubrificantes e artigos manufaturados com pouca agregação de valor e/ou pouca densidade tecnológica. Ademais, a pauta de exportação baiana não é concentrada.

Estimation of export specialization: Lithuanian case

This paper investigates the nature and pattern of export specialization in Lithuania. The aim of this paper is to estimate the nature and pattern of Lithuanian export specialization under the existing conditions. Seeking to define the nature and pattern of export specialization, the basic methods of export specialization measurement and the nature and pattern of export specialization in trade between Lithuania and the EU are determined. For measurement of the pattern of export specialization in Lithuania two approaches are adopted. The index of export specialization is used to determine the pattern of comparative advantage. Secondly, trade dissimilarity index is used to predict structural changes in Lithuanian exports. Using these methods of measurement and standard international trade classification (SITC), the nature and pattern of Lithuanian export specialization was determined. It was found that the biggest flows from Lithuania to the EU are in the following groups: food, drink and tobacco; raw materials; mineral fuels, lubricants and related materials. These calculation results show the main directions of nature and pattern of export specialization. This research could be useful for preparing and forecasting the possibilities of Lithuanian export development.