Abstract
This paper discusses international trade prospects of the main wine-producing countries over different time horizons. Our framework is composed of two approaches and aims at renewing and extending the findings of the existing literature on the dynamics of major wine exporters. Firstly, we apply a Porter’s diamond analysis in order to disentangle competitive advantages in 16 countries from various features of the global wine market. Then, we assess short- and medium-term prospects from the evolution of past trends. Secondly, we use data from a survey of (57) wine experts as a robustness analysis to complete the prospective dimension over the long term. Compared with previous literature (prior to the Covid and Ukraine shocks), our results show that the international competitiveness of countries has significantly changed over the last five years. France and Italy should maintain their leadership, but Spain and Chile are slipping back, while China could collapse. New Zealand could eventually become a major leader. These results indicate that competitive advantages are very dynamic in the wine industry, despite static natural endowments (excluding climate). Investment incentives and innovation should therefore play a key role in the long term in this sector, which is often presented as being driven by tradition and natural factors.
See (Tables A1 and A2, Figures A3 and A4, Tables A5–A7, Figure A8).
Proportion of international trade components at a worldwide scale in 2021.
Countries | Share of exports | Share of imports | Rank exporters | Rank importers |
---|---|---|---|---|
Spain | 0.2412 | 0.0109 | 1 | 10 |
Italy | 0.2266 | 0.0482 | 2 | 6 |
France | 0.1493 | 0.0952 | 3 | 4 |
Chile | 0.0884 | 0.0004 | 4 | 14 |
Australia | 0.0645 | 0.0163 | 5 | 9 |
South Africa | 0.0489 | 0.0004 | 6 | 13 |
Germany | 0.0377 | 0.2383 | 7 | 1 |
Argentina | 0.0341 | 0.0000 | 8 | 16 |
Portugal | 0.0336 | 0.0479 | 9 | 7 |
USA | 0.0333 | 0.2243 | 10 | 2 |
New Zealand | 0.0291 | 0.0066 | 11 | 11 |
Georgia | 0.0082 | 0.0001 | 12 | 15 |
UK | 0.0037 | 0.2128 | 13 | 3 |
Brazil | 0.0008 | 0.0294 | 14 | 8 |
China (HK + Macao) | 0.0004 | 0.0684 | 15 | 5 |
India | 0.0001 | 0.0009 | 16 | 12 |
Proportion of production at a worldwide scale in 2021.
Countries | Share of production | Rank producers |
---|---|---|
Italy | 0.2195 | 1 |
France | 0.1645 | 2 |
Spain | 0.1550 | 3 |
USA | 0.1052 | 4 |
Australia | 0.0647 | 5 |
Chile | 0.0587 | 6 |
Argentina | 0.0545 | 7 |
South Africa | 0.0471 | 8 |
Germany | 0.0382 | 9 |
Portugal | 0.0321 | 10 |
China | 0.0258 | 11 |
Brazil | 0.0128 | 12 |
New Zealand | 0.0116 | 13 |
Georgia | 0.0092 | 14 |
India | 0.0008 | 15 |
United Kingdom | 0.0003 | 16 |

Exported volumes of the main wine-exporting countries, 2011–2022 (in 1,000 hL). Note: Percentage figures represent percentage increases over the 2011–2022 period. (∗) for China, we include Macao and Hong-Kong wine exports. Source: International Organisation of Vine and Wine (OIV).

Global wine exports by main regions (in million hL). Source: Authors’ calculations from OIV data.
Items selected to assess country competitive advantage in the context of Porter’s diamond.
Factor conditions | Market structure |
---|---|
Agricultural area in 1,000 ha, 2019 (FAO) | Average price per litre exported, 2021 (UN Comtrade) |
Vineyard area in 1,000 ha/agricultural land, 2019 (OIV/FAO) | Variation of wine export in value, 1995–2021 (UN Comtrade) |
Variation of vineyard area, 1995–2021 (OIV) | Wine export in volume in 1,000 hL, 2022 (OIV) |
Productivity level: GDP/total hours worked, 2019 (World Bank/OECD) | Variation of wine export in volume, 1995–2022 (OIV) |
Water availability per capita in m3/hab, 2018 (FAO) | Wine exports in million USD/area, 2020 (UN Comtrade/OIV) |
Rainfall/surface area in thousands of square km, 2020 (FAO) | FDI inflows in billion USD/GDP in billion USD, 2019 (OECD and government reports) |
World Risk Index, 2021 (World Risk Index) | Country risk assessment Q4, 2021 (Coface) |
Agriculture area certified organic in % of total area, 2019 (EU website and governmental websites) | Ease of doing business – World bank Score, 2020 (World Bank) |
Shanghai ranking for being in the top 100 in agricultural sciences, 2021 (Shanghai Ranking) | Wine exports – Wine imports in million Euro, 2020 (UN Comtrade, OIV) |
Pesticide used in tonnes/agricultural area, 2019 (FAO) | Government expenditure for agriculture/total government expenditure in million USD, 2019 (FAO) |
|
|
Related industries | Demand conditions |
|
|
Number of WSET delivering places (WSET) | Adjusted net national income per capita in current USD, 2021 (World Bank) |
Grapes – Gross production value in current thousand USD, 2020 (UN Comtrade) | Consumption per capita in litre/year, 2021 (OIV) |
Beer exports/total exports in value, 2021 (UN Comtrade) | Evolution consumption per capita, 1995–2021 (OIV) |
Spirits exports/total exports in value, 2021 (UN Comtrade) | Annual consumption in 1,000 hL, 2021 (OIV) |
Glass exports/Total exports in value, 2020 (UN Comtrade) | Evolution annual consumption, 1995–2021 (OIV) |
Share of agriculture in GDP, 2020 (UN Comtrade and governmental websites) | Wine imports in 1,000 hL, 2021 (OIV) |
Number of unicorns/population, 2020 (Failory/World Bank) | Evolution annual wine imports, 1995–2021 (OIV) |
Number of patent applications/population, 2020 (government reports) | Share of world total wine import, 2021 (UN Comtrade) |
Value-added tax (VAT) on alcohol in % (Anderson, Nelgen, and Pinilla 2017, https://expathub.ge/taxes-in-georgia-country-income-corporate/ for Georgia) |
-
Source: Authors (derived from Porter 1990; Van Rooyen, Esterhuizen, and Stroebel 2011; Bargain et al. 2018).
List of formulae.
For each country, we compute the following indicators: Calculus of the score of each vertex: For k = {Factor conditions, Related industries, Market Structure, Demand conditions} and ‘Serie’ corresponding to the decile score obtained by a country for a respective variable. Calculus of the overall score of Porter’s diamond: Calculus of the score of the survey: With ‘Rating’ being the score attributed for a respective country by a respective number of wine experts. Calculus of the revealed comparative advantage (RCA) for the wine industry: We consider here the share of wine export (p) of a respective country (c) in its total export value compared to the share of wine export for the aggregate of wine exporting countries ( |
Origin of respondents.
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Clustering without factor conditions.
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