EUROPEAN COMMISSION. Table A.0.1: List of Developing countries

Transcription

1 APPENDIX A.0. Appendix to Chapter 1 Introduction The table below shows the list of developing countries as defined by the World Bank, namely countries with a per capita Gross National Income (GNI) lower than USD 11,905. Table A.0.1: List of Developing countries Developing Countries (in alphabetical order) Afghanistan Guatemala Panama Albania Guinea Papua New Guinea Algeria Guinea-Bissau Paraguay American Samoa Guyana Peru Angola Haiti Philippines Argentina Honduras Romania* Armenia India Russian Federation Azerbaijan Indonesia Rwanda Bangladesh Iran, Islamic Rep. of Samoa Belarus Iraq Sao Tome and Principe Belize Jamaica Senegal Benin Jordan Serbia Bhutan Kazakhstan Seychelles Bolivia Kenya Sierra Leone Bosnia and Herzegovina Kiribati Solomon Islands Botswana Korea, Democ. P. Rep. of Somalia Brazil Kosovo South Africa Bulgaria* Kyrgyz Republic South Sudan Burkina Faso Lao People's Democ. Rep. Sri Lanka Burundi Lebanon St. Lucia Cambodia Lesotho St. Vincent and the Grenadines Cameroon Liberia Sudan Cape Verde Libya Suriname Central African Republic Macedonia, the F.Y.R. of Swaziland Chad Madagascar Syrian Arab Republic China Malawi Tajikistan Colombia Malaysia Tanzania, United Republic of Comoros Maldives Thailand Congo, Democ. Republic of the Mali Timor-Leste Congo, Rep. Marshall Islands Togo Costa Rica Mauritania Tonga Côte d'ivoire Mauritius Tunisia Cuba Mexico Turkey Djibouti Micronesia, Fed. States of Turkmenistan Dominica Moldova Tuvalu Dominican Republic Mongolia Uganda Ecuador Montenegro Ukraine Egypt, Arab Rep. Morocco Uzbekistan El Salvador Mozambique Vanuatu Eritrea Myanmar Venezuela Ethiopia Namibia Vietnam Fiji Nepal West Bank and Gaza Gabon Nicaragua Yemen Gambia, The Niger Zambia Georgia Nigeria Zimbabwe Ghana Pakistan Grenada Palau Source: The World Bank -199-

2 Note: The above list is valid from 1 January until 31 December It is the list used for all tables in this Appendix and in Chapter 3. *While Bulgaria and Romania are listed as developing countries in the World Bank list they are members of the EU27. In the tables of chapter 3 and the appendix to chapter 3 they are not included with developing countries in the trade of developing countries with the EU. A.1. Appendix to Chapter 3 Evolution of EU-ACP Agricultural Trade International trade statistics of the type appropriate for this evaluation, namely detailed origin destination data for a long enough period, are reported both by the European Union Statistical Office as well as the United Nations (UN). The EU trade data base is called COMEXT while the UN data base is called COMTRADE. COMEXT covers trade data only for the EU member states, is reported in EUR or the ECU before the Euro, and uses the HS (Harmonized System) classification of products. COMTRADE covers all countries of the world, is reported in USD, and is organized according to the so called SITC (Standard International Trade Classification) nomenclature. The underlying data on the basis of which both of these sources are constructed is the same, namely country declarations of trade, but they undergo different types of processing before being incorporated in the respective data bases. There are advantages and disadvantages to both sources and for this evaluation both are used, with the reasons for doing so explained in each case. Another issue that also needs to be clarified is the definition of agri-food products. In this report, the definition of agri-food products based on the HS system is the same one used by the WTO and is given below. HS Code Table A.1.1: Definition of agri-food products according to the WTO Label HS Sections 1 to 24 less fish and fish products as follows 1 LIVE ANIMALS 2 MEAT AND EDIBLE MEAT OFFAL 4 DAIRY PRODUCE; BIRDS' EGGS; NATURAL HONEY; EDIBLE PRODUCTS OF ANIMAL ORIGIN, NOT ELSEWHERE SPECIFIED OR INCLUDED 5 PRODUCTS OF ANIMAL ORIGIN, NOT ELSEWHERE SPECIFIED OR INCLUDED 6 LIVE TREES AND OTHER PLANTS; BULBS, ROOTS AND THE LIKE; CUT FLOWERS AND ORNAMENTAL FOLIAGE 7 EDIBLE VEGETABLES AND CERTAIN ROOTS AND TUBERS 8 EDIBLE FRUIT AND NUTS; PEEL OF CITRUS FRUITS OR MELONS 9 COFFEE, TEA, MATÉ AND SPICES 10 CEREALS 11 PRODUCTS OF THE MILLING INDUSTRY; MALT; STARCHES; INULIN; WHEAT GLUTEN 12 OIL SEEDS AND OLEAGINOUS FRUITS; MISCELLANEOUS GRAINS, SEEDS AND FRUIT; INDUSTRIAL OR MEDICINAL PLANTS; STRAW AND FODDER 13 LAC; GUMS, RESINS AND OTHER VEGETABLE SAPS AND EXTRACTS VEGETABLE PLAITING MATERIALS; VEGETABLE PRODUCTS NOT ELSEWHERE SPECIFIED OR INCLUDED ANIMAL OR VEGETABLE FATS AND OILS AND THEIR CLEAVAGE PRODUCTS; PREPARED EDIBLE FATS; ANIMAL OR VEGETABLE WAXES PREPARATIONS OF MEAT, OF FISH OR OF CRUSTACEANS, MOLLUSCS OR OTHER AQUATIC INVERTEBRATES 17 SUGARS AND SUGAR CONFECTIONERY 18 COCOA AND COCOA PREPARATIONS 19 PREPARATIONS OF CEREALS, FLOUR, STARCH OR MILK; PASTRYCOOKS' PRODUCTS 20 PREPARATIONS OF VEGETABLES, FRUIT, NUTS OR OTHER PARTS OF PLANTS 21 MISCELLANEOUS EDIBLE PREPARATIONS 22 BEVERAGES, SPIRITS AND VINEGAR 23 RESIDUES AND WASTE FROM THE FOOD INDUSTRIES; PREPARED ANIMAL FODDER 24 TOBACCO AND MANUFACTURED TOBACCO SUBSTITUTES -200-

3 Additional products as follows: HS Code (mannitol) HS Code (sorbitol) HS Heading (essential oils) HS Headings to (albuminoidal substances, modified starches, glues) HS Code (finishing agents) HS Code (sorbitol n.e.p.) HS Headings to (hides and skins) HS Heading (raw furskins) HS Headings to (raw silk and silk waste) HS Headings to (wool and animal hair) HS Headings to (raw cotton, waste and cotton carded or combed) HS Heading (raw flax) HS Heading (raw hemp) Source: World Trade Organization (WTO Agreement on Agriculture Annex I) The additional products indicated above have been aggregated for the exposition into one product group, which is designated as OA (Other agriculture). For several analyses in this report not using the HS system for reasons explained in the text, the definition of agri-food products utilized uses the SITC classification, which corresponds most closely to the above official definitions, and is given in table A.1.2. The definitions in table A.1.2 have been utilized in many previous empirical analyses of agri-food trade and hence are appropriate for comparisons with earlier studies. This classification is consistent with both the definition of agri-food products utilized in the Constant Market Share (CMS) analysis, as well as the product disaggregation utilized for the gravity analysis. The Appendix proceeds to list detailed tables on the basis of which the figures of Chapter 3 have been constructed. Table A.1.2: Definition of agri-food products adopted for some of the empirical analyses SITC Code Label 00 Live animals other than animals of SITC code Meat and meat preparations 02 Dairy products and birds' eggs 04 Cereals and cereal preparations 05 Vegetables and fruits 06 Sugar, sugar preparations and honey 07 Coffee, tea, cocoa, spices, and manufactures thereof 08 Feedstuff for animals (excluding unmilled cereals) 09 Miscellaneous edible products and preparations 11 Beverages 12 Tobacco and tobacco manufactures 22 Oil seeds and oleaginous fruits 41 Animal oils and fats 42 Fixed vegetable oils and fats, crude, refined or fractionated 43 Processed Animal and vegetable oils and fats 261 Silk 262 Cotton 263 Jute and other textile based fibres 265 Other vegetable textile fibres Source: Authors designations -201-

4 Table A.1.3: EU imports (current EUR million) of agricultural products from all developing countries EU-12 EU-15 EU-27 HS section ,297 1,554 1,669 2,203 2, , ,218 1, ,644 1,212 1, ,986 2,083 2,888 2, ,457 3,247 4,191 4,829 6,873 7,236 9,815 9, ,774 4,264 5,019 2,870 2,828 2,991 5,224 5, ,072 1,330 3,982 3, ,821 1,739 1,842 3,401 1,411 1,499 2,940 4, ,243 1,528 1,180 2,270 2,336 5,177 5, ,337 1,217 2,056 2,108 3,618 4, , ,259 1,419 1,668 2, ,211 1,218 1,417 1,539 2,399 2,501 3,291 4, ,630 1,530 1,750 2,035 2,556 2,713 3,630 4, , ,759 1,812 2,623 2, ,761 2,059 2,569 3, , ,056 1,084 1,206 1,321 1,896 OA 1,891 1, ,254 1,686 1,988 1,534 1,813 Total 23,454 22,769 28,589 31,250 33,938 36,381 54,856 60,756 Source: Computed by authors using COMEXT data. OA includes all other agricultural products not included in HS chapters

5 Table A.1.4: EU imports (current EUR million) of agricultural products from all ACP countries EU-12 EU-15 EU-27 HS section , ,047 1,655 1,690 1,720 2,137 2, ,179 1,647 1, , , ,042 1,097 1,276 1,690 2,261 2,339 3,028 3, OA Total 6,247 5,136 7,598 9,150 9,173 9,415 11,314 13,289 Source: Computed by authors using COMEXT data. OA includes all other agricultural products not included in HS chapters

6 Table A.1. 5: Shares of EU imports of agricultural products from ACP countries (% of EU agricultural imports from all developing countries ) EU-12 EU-15 EU-27 HS section OA Total Source: Computed by authors using COMEXT data. OA includes all other agricultural products not included in HS chapters

7 Table A.1.6: Product composition of EU imports of agricultural products from ACP countries (% of EU agricultural imports from all ACP countries ) EU-12 EU-15 EU-27 HS chapter OA Total Source: Computed by authors using COMEXT data. OA includes all other agricultural products not included in HS chapters Table A.1.7: EU imports (current EUR million) of agricultural products from all ACP-LDC countries EU-12 EU-15 EU-27 HS chapter

8 OA Total 1,373 1,740 1,915 1,265 1,315 1,383 2,004 2,557 Source: Computed by authors using COMEXT data. OA includes all other agricultural products not included in HS chapters Table A.1.8: Shares of EU imports of agricultural products from ACP-LDC countries (% of EU agricultural imports from all ACP countries ) EU-12 EU-15 EU-27 HS chapter OA Total Source: Computed by authors using COMEXT data. OA includes all other agricultural products not included in HS chapters Table A.1.9. EU agricultural imports from the different ACP regional groups in 1990, and 2012 EU-12 shares of agricultural imports from all ACP and regional ACP groups in 1990 CARI- All ACP ECOWAS SADC PIF ESA EAC CEMAC All ACP FORUM EUR HS Chapter % of total EU agricultural imports from all ACP countries million

9 8 1, , , OA Total 6, Product composition of EU-12 agricultural imports from all ACP regional ACP groups in 1990 All ACP CARI- (1 decimal All ACP ECOWAS SADC PIF ESA EAC CEMAC FORUM figure accuracy) EUR HS Chapter % of total EU agricultural imports from each regional group million , , , OA

10 Total 6, EU-12 shares of agricultural imports from all ACP and regional ACP groups in 2012 CARI- All ACP ECOWAS SADC PIF ESA EAC CEMAC All ACP FORUM EUR HS Chapte % of total EU agricultural imports from all ACP countries million , , , , OA Total 13, Product composition of EU-12 agricultural imports from all ACP regional ACP groups in 2012 All ACP CARI- (1 decimal All ACP ECOWAS SADC PIF ESA EAC CEMAC FORUM figure accuracy) EUR HS Chapter % of total EU agricultural imports from each regional group million , ,

11 , , OA Total 13, Source: Own computations from Comext data. OA includes all other agricultural products not included in HS chapters Table A.1.10: Country aggregations of the GTAP 8 data base 126 NOTATION AGGREGATION DEV1 Non ACP developing LDC DEV2 Non ACP developing non LDC ACP1 ACP LDC ACP2 ACP non LDC ROW Rest of World (developed) EU27 EU-27 EU15 The 15 EU members before 2004 EU12N The 12 EU members that joined the EU since 2004 Table A.1.11: Definition of GTAP sectors 127 Number Code Description (Detailed Sector Breakdown) 1 PDR Paddy rice 2 WHT Wheat 3 GRO Cereal grains nec 4 V_F Vegetables, fruit, nuts 5 OSD Oil seeds 6 C_B Sugar cane, sugar beet 7 PFB Plant-based fibres 8 OCR Crops nec 9 CTL Bovine cattle, sheep and goats, horses 10 OAP Animal products nec 11 RMK Raw milk 12 WOL Wool, silk-worm cocoons 126 Note: Croatia which joined the EU in 2013 is not covered in the ensuing analysis and is included in ROW. 127 The GTAP group has gone into great effort to make the production and trade data consistent, with the consequence, however, that there is no one to one correspondence between the agri-food sector listed in table A.1.10 and the HS or SITC chapters defining the agricultural products that were listed in tables A.1.1 and A.1.2 Nevertheless, the nomenclature indicated in table A.1.10 is quite clear and in most cases is compatible with the trade chapters listed in Tables A.1.1 and A

12 13 CMT Bovine meat products 14 OMT Meat products nec 15 VOL Vegetable oils and fats 16 MILLION Dairy products 17 PCR Processed rice 18 SGR Sugar 19 OFD Food products nec 20 B_T Beverages and tobacco products Total All of the above Source: Table A.1.12: Global agricultural product trade pattern Trade values (1997 USD million values) VXWD DEV1 2 DEV2 3 ACP1 4 ACP2 5 ROW 6 EU15 7 EU12N Total 1 DEV ,492 2 DEV2 1,716 36,515 1,011 2,176 47,164 33,052 7, ,547 3 ACP , ,731 6, ,711 4 ACP2 10 2, ,479 5,376 6,057 1,088 14,943 5 ROW 1,241 35, ,572 59,870 28,271 11, ,516 6 EU ,955 2,743 1,667 23, ,763 36, ,952 7 EU12N 18 3, ,325 2,462 9,664 Total 3, ,511 5,163 9, , ,806 60, ,826 Export shares VXWD DEV1 2 DEV2 3 ACP1 4 ACP2 5 ROW 6 EU15 7 EU12N Total 1 DEV DEV ACP ACP ROW EU EU12N Total Import shares VXWD DEV1 2 DEV2 3 ACP1 4 ACP2 5 ROW 6 EU15 7 EU12N Total 1 DEV DEV ACP ACP ROW EU EU12N Total Source: Own calculations from the GTAP 6 data base 128 The source for the 1997 data is GTAP release 6, while for 2011 it is the latest release GTAP 8. For years earlier than 1997 either the data is not available or an aggregation facility is not provided in GTAP -210-

13 Table A.1.13: Global agricultural product trade pattern 2011 Trade values (2004 USD million values) VXWD 1 DEV1 2 DEV2 3 ACP1 4 ACP2 5 ROW 6 EU27 Total 1 DEV1 1,564 4, ,249 8,309 2 DEV2 23, ,220 11,681 14, ,618 87, ,896 3 ACP ,665 1,821 1,593 2,727 5,810 17,779 4 ACP ,654 2,700 7,493 6,390 13,551 37,391 5 ROW 5, ,924 3,535 11, ,144 37, ,699 6 EU27 2,883 61,818 5,889 6,635 60, , ,078 Total 34, ,469 25,779 41, , ,612 1,384,153 Export shares VXWD 1 DEV1 2 DEV2 3 ACP1 4 ACP2 5 ROW 6 EU27 Total 1 DEV DEV ACP ACP ROW EU Total Import shares VXWD 1 DEV1 2 DEV2 3 ACP1 4 ACP2 5 ROW 6 EU27 Total 1 DEV DEV ACP ACP ROW EU Total Source: Own calculations from the GTAP 8 data base -211-

14 DEV1 DEV2 Table A Global agri-food trade with and within the ACP regional groups in 2011 (current USD million) ACP ECOWAS ACP SADC ACP ESA ACP EAC ACP CEMAC ACP PACIFIC ACP CARIB ROW EU27 Total DEV1 1,564 4, ,249 8,309 DEV2 23, ,220 10,345 3,754 3,407 1,962 1, , ,618 87, ,896 ACP ECOWAS 84 4,161 1, ,531 6,509 15,227 ACP SADC 96 2, , ,737 3,956 11,058 ACP ESA 126 2, ,869 8,099 ACP EAC 215 1, ,380 6,201 ACP CEMAC ,189 ACP PACIFIC ,735 ACP CARIB , ,082 2,049 10,662 ROW 5, ,924 5,563 1,175 1, ,371 5, ,144 37, ,699 EU27 2,883 61,818 4,369 1,965 1, , ,895 60, , ,078 Total 34, ,469 27,032 8,330 8,835 3,332 3,250 2,317 14, , ,612 1,384,153 DEV1 DEV2 (Export shares %) ACP ECOWAS ACP SADC ACP ESA ACP EAC ACP CEMAC ACP PACIFIC ACP CARIB ROW EU27 Total DEV DEV ACP ECOWAS ACP SADC ACP ESA ACP EAC ACP CEMAC ACP PACIFIC ACP CARIB ROW EU Total

15 (Import shares %) ACP DEV1 DEV2 ECOWAS ACP SADC ACP ESA ACP EAC ACP ACP ACP ROW EU27 Total CEMAC PACIFIC CARIB DEV DEV ACP ECOWAS ACP SADC ACP ESA ACP EAC ACP CEMAC ACP PACIFIC ACP CARIB ROW EU Total Source: Own estimates from the GTAP 8 database -213-

16 Table A.1.15: Total agricultural EU-27 imports (current EUR million) from each ACP country for the years 2010, 2011 and 2012 Country non-ldc ACP countries EU-27 Agricultural Imports ANTIGUA AND BARBUDA BAHAMAS BARBADOS BELIZE BOTSWANA CAMEROON CAPE VERDE CONGO COOK ISLANDS COTE D'IVOIRE 2,256 2,270 2,201 DOMINICA DOMINICAN REPUBLIC FIJI GABON GHANA 1,280 1,601 1,502 GRENADA GUYANA JAMAICA KENYA 1,008 1,105 1,066 MARSHALL ISLANDS MAURITANIA (incl.sp SAH.from 1977) MAURITIUS MICRONESIA, FEDERATED STATES OF NAMIBIA NAURU NIGERIA NIUE PALAU PAPUA NEW GUINEA SEYCHELLES SOUTH AFRICA 2,104 1,981 2,041 ST KITTS AND NEVIS ST LUCIA ST VINCENT AND THE GRENADINES SURINAME SWAZILAND (NGWANE) TONGA TRINIDAD AND TOBAGO ZIMBABWE Total 10,242 10,966 10, non-ldc ACP countries EU-27 Agricultural Imports ANGOLA BENIN BURKINA FASO BURUNDI

17 CENTRAL AFRICAN REPUBLIC CHAD COMOROS CONGO, DEMOCRATIC REPUBLIC OF DJIBOUTI ERITREA ETHIOPIA EQUATORIAL GUINEA GAMBIA GUINEA GUINEA-BISSAU HAITI KIRIBATI LESOTHO LIBERIA MADAGASCAR MALAWI MALI MOZAMBIQUE NIGER RWANDA SAO TOME AND PRINCIPE SAMOA SENEGAL SIERRA LEONE SOLOMON ISLANDS SUDAN TOGO TUVALU UGANDA TANZANIA, UNITED REPUBLIC OF VANUATU ZAMBIA Total 2,205 2,868 2,560 Source: Own calculations from Comext data -215-

18 A.2. Appendix to Chapter 5 Answer to Evaluation Question 1 A.2.1 Agri-food products classification and countries classification used in the gravity model Table A.2.1a: Agri-food products classification used in the gravity model Standard International Trade Classification - SITC Rev. 1 2-digit Product Description 4-digit 2-digit Product Description 4-digit Bovine cattle including buffaloes 0011 Raw sugar, beet & cane 0611 Sheep, lambs and goats 0012 Refined sugar & other prod. of refining, no syrup 0612 Swine 0013 Molasses 0615 Poultry,live 0014 Natural honey 0616 Horses, asses, mules and hinnies 0015 Sugars & syrups n.e.s incl. art. honey & caramel 0619 Live animals chiefly for food, n.e.s Sugar confectionery & other sugar preparations Meat of bovine animals, fresh, chilled or frozen 0111 Coffee, green or roasted 0711 Meat of sheep & goats, fresh, chilled or frozen 0112 Coffee extracts, essences, concentrates 0713 Meat of swine, fresh, chilled or frozen 0113 Cocoa beans, raw or roasted 0721 Poultry, incl. offals ex. liver fresh, chilled, frozen 0114 Cocoa powder, unsweetened 0722 Meat of horses, asses, mules & hinnies, fr.ch.fro Cocoa butter and cocoa paste 0723 Edible offals of animals, fresh, chilled, frozen 0116 Chocolate & other food prep. Of cocoa 0730 Other fresh, chilled, frozen meat & edible offals 0118 Tea 0741 Bacon, ham & other dried, salted, smoked pig meat 0121 Mate 0742 Meat & edible offals, n.e.s. Dried, salted, smoked 0129 Pepper & pimento, whether or not ground 0751 Meat extracts & meat juices 0133 Spices, exc. Pepper & pimento ground or not 0752 Sausages, whether or not in airtight containers Other prepared or preserved meat 0138 Hay & fodder, green or dry Bran, pollard, sharps & other by products 0812 Milk & cream evaporated or condensed 0221 Oil seed cake & meal & other veg. Oil residues 0813 Milk & cream in solid form, blocks or powder 0222 Meat & fish meal, unfit for human consumption 0814 Milk & cream fresh 0223 Food wastes & prepared animal feed, n.e.s Butter Cheese and curd 0240 Lard & other rendered pig & poultry fat 0913 Eggs 0250 Margarine, imitn lard & prepared edible fats n.e.s Food preparations, n.e.s Fish, fresh, chilled or frozen Fish, salted, dried or smoked 0312 Non alcoholic beverages, n.e.s Crustacean & molluscs, fresh, chilled, salted, dried 0313 Wine of fresh grapes including grape must 1121 Fish, in airtight containers 0320 Cider & fermented beverages, n.e.s Beer including ale, stout, porter 1123 Wheat and meslin, unmilled 0410 Distilled alcoholic beverages 1124 Rice in the husk or not, not further prepared 0421 Tobacco, unmanufactured & scrap 1210 Rice, glazed or polished, not further prepared Barley, unmilled 0430 Cigars & cheroots 1221 Maize (corn), unmilled 0440 Cigarettes 1222 Rye, unmilled 0451 Tobacco, manufactured for smoking, chewing snuff 1223 Oats, unmilled Cereals, unmilled, n.e.s 0459 Groundnuts peanuts green, ex. flour and meal 2211 Meal and flour of wheat or of meslin 0460 Copra, ex. flour and meal 2212 Meal & flour of cereals except wheat or meslin 0470 Palm nuts & kernels 2213 Cereal grains, flaked, pearled 0481 Soya beans 2214 Malt including malt flour 0482 Linseed 2215 Macaroni, spaghetti, noodles, vermicelli etc Cotton seed 2216 Bakery products 0484 Castor oil seed 2217 Preparations of cereals, flour & starch for food 0488 Oil seeds, oil nuts & oil kernels, n.e.s Flour & meal of oil seeds, nuts, kernels, fat 2219 Oranges, tangerines and clementines Other citrus fruit 0512 Oils of fish and marine mammals 4111 Bananas including plantains,fresh 0513 Animal oils, fats and greases, excluding lard 4113 Apples, fresh Grapes, fresh 0515 Soya bean oil 4212 Edible nuts, fresh or dried 0517 Cotton seed oil 4213 Fresh fruit, n.e.s 0519 Groundnut /peanut/ oil 4214 Dried fruit, dehydrated artificially 0520 Olive oil 4215 Fruit, fruit peel, preserved by sugar 0532 Sunflower seed oil

19 Table A.2.1b Imports of 4 digit agri-food products into the EU-27 for ( according to SITC classification) SITC 2- digit chapter Product description 4-digit SITC code average EU-27 imports USD million Share of each 4 digit product in its 2-digit chapter (%) 0 Live animals Bovine cattle including buffaloes Sheep, lambs and goats Swine Poultry, live Horses, asses, mules and hinnies Live animals chiefly for food, n.e.s. Total Meat and meat preparations Meat of bovine animals, fresh, chilled or frozen Meat of sheep & goats, fresh, chilled or frozen Meat of swine, fresh, chilled or frozen Poultry, incl. offals ex. liver fresh, chilled, frozen Meat of horses, asses, mules & hinnies, fr.ch.fro Edible offals of animals, fresh, chilled, frozen Other fresh, chilled, frozen meat & edible offals Bacon, ham & other dried, salted, smoked pig meat Meat & edible offals, n.e.s. Dried, salted, smoked Meat extracts & meat juices Sausages, whether or not in airtight containers Other prepared or preserved meat Total Dairy products and birds' eggs Milk & cream evaporated or condensed Milk & cream in solid form, blocks or powder Milk & cream fresh Butter Cheese and curd Eggs Total Cereals and cereal preparations Wheat and meslin, unmilled Rice in the husk or not, not further prepared Rice, glazed or polished, not further prepared Barley, unmilled Maize (corn), unmilled Rye, unmilled Oats, unmilled Cereals, unmilled, n.e.s Meal and flour of wheat or of meslin Meal & flour of cereals except wheat or meslin Cereal grains, flaked, pearled Malt including malt flour Macaroni, spaghetti, noodles, vermicelli etc Bakery products Preparations of cereals, flour & starch for food Total Vegetables and fruit Oranges, tangerines and clementines Other citrus fruit Bananas including plantains,fresh 513 1, Apples, fresh Grapes, fresh

20 Edible nuts, fresh or dried Fresh fruit, n.e.s Dried fruit, dehydrated artificially Fruit, fruit peel, preserved by sugar Jams, marmalades, fruit jellies Fruit juices & vegetable juices, unfermented Fruit, temporarily preserved Fruit & nuts, prepared or preserved, n.e.s Potatoes, fresh, not including sweet potatoes Beans, peas, lentils & leguminous vegetable. dried Tomatoes, fresh Other fresh vegetables Vegetables, frozen or in temporary preservative Vegetable products, chiefly for human food n.e.s Vegetables, dehydrated excl. leguminous vegetable Flour & flakes of potatoes, fruits, vegetables Vegetables preserved or prepared, n.e.s Total 4, Sugars, sugar preparations and honey Raw sugar, beet & cane Refined sugar & other prod. of refining, no syrup Molasses Natural honey Sugars & syrups n.e.s incl. art. honey & caramel Sugar confectionery & other sugar preparations Total 1, Coffee, tea, cocoa, spices, and manuf. Coffee, green or roasted 711 1, Coffee extracts, essences, concentrates Cocoa beans, raw or roasted 721 4, Cocoa powder, unsweetened Cocoa butter and cocoa paste 723 1, Chocolate & other food prep. Of cocoa Tea Mate Pepper & pimento, whether or not ground Spices, exc. Pepper & pimento ground or not Total 8, Feeding stuff for animals (not unmilled cereals) Hay & fodder, green or dry Bran, pollard, sharps & other by products Oil seed cake & meal & other veg. Oil residues Meat & fish meal, unfit for human consumption Food wastes & prepared animal feed, n.e.s Total Miscellaneous edible products and preparations Lard & other rendered pig & poultry fat Margarine, imitn lard & prepared edible fats n.e.s Food preparations, n.e.s Total Beverages Non alcoholic beverages, n.e.s Wine of fresh grapes including grape must Cider & fermented beverages, n.e.s Beer including ale, stout, porter Distilled alcoholic beverages Tobacco, unmanufactured & scrap Total 1,

21 12 Tobacco and tobacco manufactures Cigars & cheroots Cigarettes Tobacco, manufactured for smoking, chewing snuff Total Oil seeds and oleaginous fruits Groundnuts peanuts green, ex. flour and meal Copra, ex. flour and meal Palm nuts & kernels Soya beans Linseed Cotton seed Castor oil seed Oil seeds, oil nuts & oil kernels, n.e.s Flour & meal of oil seeds, nuts, kernels, fat Total Animal oils and fats Oils of fish and marine mammals Animal oils, fats and greases, excluding lard Total Fixed vegetable fats and oils, crude, refined Soya bean oil Cotton seed oil Groundnut /peanut/ oil Olive oil Sunflower seed oil Rape, colza and mustard oils Linseed oil Palm oil Coconut copra oil Palm kernel oil Castor oil Fixed vegetable oils, n.e.s Total Animal or vegetable fats and oils, processed Anim./veget. oils, boiled, oxidized, dehydrated Hydrogenated oils and fats Acid oils, fatty acids and solid residues Waxes of animal or vegetable origin Total Total average EU-27 imports (USD million) for ,539 Source: Own computations from Comtrade data -219-

22 Table A.2.1c: Countries without any trade preferences during the analysed period that are used as the counterfactual group in the gravity model All period, from 1962 to 2012 No. years from 1962 to 1968/1972 (cont.) No. years from 1962 to 1968/1972 (cont.) No. years Australia * 51 Egypt 9 Canada * 51 El salvador 9 Saint vincent and the grenadines 9 Hong kong * 51 Equatorial guinea 9 Sao tome and principe 9 Japan * 51 Ethiopia 9 Saudi arabia 9 Korea * 51 Fiji 9 Sierra leone 9 Korea, dem. people's republic of 51 Gambia 9 Southern African Customs Union 9 New zealand * 51 Georgia 9 Sri lanka 9 Singapore * 51 Ghana 9 Sudan 9 United states * 51 Grenada 9 Suriname 9 Guatemala 9 Swaziland years, from 1962 to 2003/2009 Guinea 9 Syrian arab republic 9 Albania 47 Guinea-bissau 9 Tajikistan 9 Bosnia and herzegowina 46 Honduras 9 Tanzania 9 Croatia 43 India 9 Thailand 9 Macedonia 42 Indonesia 9 Trinidad and tobago 9 Iran (islamic republic of) 9 Turkmenistan years, from 1962 to 1968/1972 Iraq 9 Uganda 9 Iceland 11 Jamaica 9 Ukraine 9 Norway 11 Jordan 9 Uruguay 9 Switzerland 11 Kazakhstan 9 Uzbekistan 9 Chile 10 Kenya 9 Venezuela 9 Angola 9 Kuwait 9 Viet nam 9 Antigua and barbuda 9 Kyrgyzstan 9 Yemen 9 Argentina 9 Lao people's democratic republic 9 Zambia 9 Armenia 9 Lebanon 9 Zimbabwe 9 Azerbaijan 9 Lesotho 9 Israel 8 Bahamas 9 Liberia 9 Morocco 7 Bahrain 9 Macau 9 Tunisia 7 Bangladesh 9 Malawi 9 Barbados 9 Malaysia 9 2 years, from 1962 to 1963 Belarus 9 Maldives 9 Benin 2 Belize 9 Mauritius 9 Burkina faso 2 Bermuda 9 Mexico 9 Burundi 2 Bhutan 9 Mongolia 9 Cameroon 2 Bolivia 9 Mozambique 9 Central african republic 2 Botswana 9 Namibia 9 Chad 2 Brazil 9 Nepal 9 Congo 2 Brunei darussalam 9 Nigeria 9 Cote d'ivoire 2 Cambodia 9 Oman 9 DR Congo 2 Cape verde 9 Pakistan 9 Gabon 2 China 9 Panama 9 Madagascar 2 Colombia 9 Paraguay 9 Mali 2 Comoros 9 Peru 9 Mauritania 2 Costa rica 9 Philippines 9 Niger 2 Djibouti 9 Qatar 9 Rwanda 2 Dominica 9 Russian federation 9 Senegal 2 Dominican republic 9 Saint kitts and nevis 9 Togo 2 Ecuador 9 Saint lucia 9 Turkey 2 (*) Developed countries excluded in the results reported in last bars of Figure Note: The table reports the countries-years without PTAs, and the corresponding time period for which the respective country entered in the counterfactual. For example Iceland was in the counterfactual from the 1962 until However, it signed a PTA with the EU in Thus, starting from 1973 onward, Iceland belongs to the Other group

23 A.2.2. Econometric results for the tables of section (results from the gravity model approach) Table A.2.2: Trade effect of PTAs in the agri-food sector (see Figure 5.5.2) Source: Own analysis based on data described in the text OLS PPML PPML_1 PPML_2 PPML_2A ACP/GSP/LDC ij *** *** *** *** *** (0.0344) (0.0407) (0.1177) (0.0533) (0.0692) OTHER ij *** *** *** *** *** (0.0455) (0.0509) (0.1471) (0.0635) (0.0810) GDP j *** *** *** *** *** (0.0052) (0.0067) (0.0788) (0.0287) (0.0290) GDP i *** *** *** *** (0.0089) (0.0122) (0.3071) (0.0995) (0.1096) DIST ij *** *** *** *** (0.0209) (0.0274) (0.0665) (0.0905) CONT ij *** *** *** *** (0.1001) (0.0850) (0.0701) (0.1099) LANG ij *** *** *** (0.0851) (0.0688) (0.0668) (0.0653) LANG9 ij *** *** *** *** (0.0829) (0.0678) (0.0655) (0.0610) COL45 ij *** *** *** *** (0.0559) (0.0534) (0.0350) (0.0367) Constant *** *** * (0.2468) (0.3488) (1.5175) (1.7257) No. of obs R-sq Note: *, ** and *** indicate statistically significance at the 10, 5 and 1 % level, respectively. Robust standard errors in parentheses. All regressions include year dummies. The Poisson estimation procedure (PPML) includes bilateral dummies for each importer-exporter combination (PPML_1) or distinct importer and exporter fixed effects (PPML_2). Differently, PPML_2A results refer to a specification that excludes high income countries with no PTA from the sample (see (text)

24 Table A.2.3: Trade effect of different EU PTAs in the agri-food sector (see Figure 5.5.3) Source: Own analysis based on data described in the text PPML_1 PPML_2 PPML_1 PPML_2 (1) (2) (3) (4) GDP j *** *** *** *** (0.0899) (0.0312) (0.0800) (0.0288) GDP i *** *** (0.3081) (0.1001) (0.3077) (0.0997) DIST ij *** *** (0.0663) (0.0666) CONT ij *** *** (0.0697) (0.0702) LANG ij (0.0673) (0.0673) LANG9 ij *** *** (0.0659) (0.0661) COL45 ij *** *** ACP *** *** (0.1985) (0.0898) ACP *** *** (0.1615) (0.0870) ACP *** *** (0.1798) (0.0838) ACP ** *** (0.2134) (0.0956) GSP *** *** (0.1196) (0.0561) GSP *** *** (0.1845) (0.0731) LDC *** *** (0.2324) (0.1081) LDC (0.2244) (0.0916) OTHER *** *** (0.1498) (0.0646) (0.0349) (0.0350) AVG *** *** (0.1143) (0.0508) _cons ** * (1.5438) (1.5221) No. of obs. 76,330 79,962 76,330 79,962 R-Sq Note: *, ** and *** indicate statistically significance at the 10, 5 and 1 % level, respectively. Robust standard errors in parentheses. Columns (1) and (3) report estimates using the Poisson estimation procedure (PPML) that includes bilateral dummies for each importer-exporter combination (PPML_1). Columns (2) and (3) include distinct importer and exporter fixed effects (PPML_2). All regressions include year dummies

25 Table A.2.4: The trade effects of the EU PTAs: PPML_2 regression results with exporters, importers and years fixed effects (see Figure 5.5.4) LIVE MEAT AND MEAT PREPARATIO CEREALS AND CEREALS FEEDING VEGETABLES SUGAR AND COFFEE, TEE STUFF FOR MISCELLANE OUS EDIBLE ANIMAL OIL VEGETABLE ANIMAL OR VEG OIL AND FAT ANIMALS N DAIRY FISH PREP. AND FRUITS SUGAR PREP COCOA ANIMALS PROD BEVERAGE TOBACCO OIL SEED AND FAT OIL AND FAT PROCESSED TOTFOOD (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15) (16) (17) GDPj 0.69*** *** 0.73*** 0.24*** 0.57*** 0.70*** 1.25*** 1.16*** 0.71*** 0.59*** 0.91*** 1.23*** 1.20*** 1.11*** *** (0.25) (0.11) (0.25) (0.06) (0.11) (0.04) (0.07) (0.05) (0.09) (0.09) (0.16) (0.08) (0.09) (0.23) (0.10) (0.15) (0.0287) GDPi 0.92*** 1.46*** *** *** *** 0.74*** 1.66*** -1.20*** *** 1.82*** 2.45*** *** (0.26) (0.34) (0.50) (0.17) (0.29) (0.14) (0.25) (0.19) (0.21) (0.20) (0.34) (0.25) (0.34) (0.57) (0.33) (0.43) (0.0995) DISTij -0.97*** -0.52** -0.58*** -1.67*** -0.42* -1.11*** -1.36*** *** -0.54*** -0.81*** -0.28* -1.09*** 0.40* -1.97*** *** (0.27) (0.24) (0.14) (0.06) (0.24) (0.07) (0.13) (0.19) (0.11) (0.08) (0.11) (0.15) (0.19) (0.23) (0.13) (0.34) (0.0665) CONTij 0.98*** 2.80*** 1.34*** 1.30*** 1.34*** 0.49*** 1.12*** *** 1.26*** 1.23*** 0.55** 1.26*** 3.10*** 0.98*** 2.70*** *** (0.26) (0.29) (0.13) (0.12) (0.17) (0.09) (0.15) (0.15) (0.19) (0.08) (0.13) (0.24) (0.26) (0.26) (0.21) (0.32) (0.0701) LANGij 2.42*** *** 0.89*** 0.41** -0.34*** *** 0.41*** 0.40*** 0.67*** -0.53*** 0.34** -1.17*** (0.28) (0.17) (0.28) (0.08) (0.19) (0.05) (0.14) (0.08) (0.15) (0.11) (0.17) (0.13) (0.14) (0.19) (0.16) (0.29) (0.0668) LANG9ij -0.94*** 0.81*** 0.58** -0.25*** *** 0.74*** 0.68*** * 0.74*** *** 0.55*** *** (0.36) (0.17) (0.28) (0.08) (0.19) (0.05) (0.14) (0.08) (0.15) (0.10) (0.17) (0.11) (0.15) (0.22) (0.16) (0.29) (0.0655) COL45ij * -2.99*** 0.39*** 1.67*** 1.34*** 1.39*** 0.81*** 0.88*** 0.89*** *** 1.39*** 1.89*** 0.54*** 0.40*** *** (0.26) (0.14) (0.21) (0.05) (0.10) (0.05) (0.09) (0.05) (0.08) (0.07) (0.16) (0.10) (0.11) (0.28) (0.09) (0.13) (0.0350) ACP/LDC/GSP -2.18*** *** 0.94*** -0.37** 0.17** 1.00*** 0.24*** 0.48*** *** 1.14*** ** 1.20*** 0.69*** *** (0.40) (0.22) (0.34) (0.12) (0.17) (0.08) (0.31) (0.08) (0.10) (0.20) (0.19) (0.10) (0.15) (0.23) (0.17) (0.18) (0.0533) OTHER -1.00*** 1.15*** *** 1.36*** 0.29*** 0.90*** 0.66*** *** -0.36** 1.08*** 0.41** 0.70*** 1.08*** *** (0.24) (0.22) (0.19) (0.11) (0.17) (0.10) (0.33) (0.11) (0.10) (0.16) (0.18) (0.12) (0.18) (0.14) (0.21) (0.17) (0.0635) Constant ** ** 10.06*** *** *** *** 17.04*** *** *** *** * (5.06) (4.97) (7.25) (2.15) (4.74) (1.87) (3.70) (3.33) (3.12) (2.73) (5.14) (3.49) (4.17) (6.57) (4.48) (5.81) (1.5175) No. of obs R-Sq Source: Own analysis based on data described in the text Note: *, ** and *** indicate statistically significance at the 10, 5 and 1 % level, respectively. Robust standard errors in parentheses. All Columns report estimates obtained using the Poisson estimation procedure (PPML) that includes distinct importer and exporter fixed effects (PPML_2) and year dummies

26 Table A.2.5: The trade effects of the EU PTAs: PPML_1 regression results with importer-exporter bilateral dummies and year dummies (see Figure 5.5.5) LIVE MEAT AND MEAT CEREALS AND FEEDING VEGETABLES SUGAR AND COFFEE, TEE STUFF FOR MISCELLANE OUS EDIBLE ANIMAL OIL VEGETABLE ANIMAL OR VEG OIL AND FAT ANIMALS PREPARATION DAIRY FISH CEREALS PREP. AND FRUITS SUGAR PREP COCOA ANIMALS PROD BEVERAGE TOBACCO OIL SEED AND FAT OIL AND FAT PROCESSED (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15) (16) GDPj 0.84* *** 0.74** *** 0.66*** 1.24*** 1.20*** 0.69** 0.56*** 0.80*** 1.22*** 0.93*** 1.11*** (0.48) (0.31) (0.39) (0.16) (0.34) (0.13) (0.11) (0.13) (0.25) (0.23) (0.30) (0.21) (0.22) (0.47) (0.23) (0.29) GDPi 0.96** ** * *** *** 1.47** 2.47*** (0.39) (1.03) (1.95) (0.34) (0.73) (0.39) (0.46) (0.49) (0.54) (0.48) (0.58) (0.78) (1.12) (1.44) (0.64) (0.92) ACP -2.66*** 1.99** -1.44* 1.88*** * 0.81*** *** -1.63*** -2.18** 0.89*** (0.58) (0.84) (0.77) (0.37) (0.38) (0.39) (0.31) (0.26) (0.42) (0.49) (0.38) (0.30) (0.39) (0.88) (0.28) (0.48) LDC -3.26*** *** * 1.26*** *** 1.71** *** -2.81*** -1.49* -1.08** -1.19** (0.76) (1.00) (0.96) (0.38) (0.44) (0.41) (0.35) (0.32) (0.50) (0.74) (0.65) (0.37) (0.43) (0.83) (0.46) (0.60) GSP -1.72*** ** 0.80*** -0.54* *** *** 0.83*** *** 0.58 (0.54) (0.52) (0.67) (0.27) (0.28) (0.14) (0.25) (0.22) (0.29) (0.35) (0.18) (0.24) (0.36) (0.54) (0.23) (0.43) OTHER -0.96*** 1.06** *** 1.29*** *** *** -0.61*** 0.91*** (0.36) (0.52) (0.45) (0.25) (0.31) (0.18) (0.28) (0.32) (0.32) (0.21) (0.19) (0.31) (0.41) (0.34) (0.37) (0.40) No. of obs Source: Own analysis based on data described in the text Note: *, ** and *** indicate statistically significance at the 10, 5 and 1 % level, respectively. Robust standard errors in parentheses. All Columns report estimates obtained using the Poisson estimation procedure (PPML) that includes bilateral dummies for each importer-exporter combination (PPML_1) and year dummies

27 Table A.2.6: The trade effects of the EU PTAs: PPML_2 regression results with exporters, importers and years fixed effects (see Figure 5.5.5) LIVE MEAT AND MEAT CEREALS AND FEEDING VEGETABLES SUGAR AND COFFEE, TEE STUFF FOR MISCELLANE OUS EDIBLE ANIMAL OIL VEGETABLE ANIMAL OR VEG OIL AND FAT ANIMALS PREPARATION DAIRY FISH CEREALS PREP. AND FRUITS SUGAR PREP COCOA ANIMALS PROD BEVERAGE TOBACCO OIL SEED AND FAT OIL AND FAT PROCESSED (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15) (16) GDP j 0.69*** *** 0.74*** 0.24*** 0.56*** 0.70*** 1.23*** 1.16*** 0.72*** 0.58*** 0.87*** 1.23*** 0.97*** 1.09*** (0.25) (0.11) (0.25) (0.06) (0.11) (0.04) (0.07) (0.05) (0.09) (0.09) (0.16) (0.08) (0.09) (0.23) (0.10) (0.15) GDP i 0.92*** 1.46*** *** *** *** 0.73*** 1.66*** -1.19*** *** 1.83*** 2.44*** (0.26) (0.34) (0.50) (0.17) (0.29) (0.14) (0.25) (0.19) (0.21) (0.20) (0.34) (0.25) (0.34) (0.57) (0.32) (0.43) DIST ij -0.97*** -0.52** -0.58*** -1.67*** -0.41* -1.11*** -1.36*** *** -0.54*** -0.81*** -0.27* -1.10*** 0.40* -2.00*** 0.11 (0.27) (0.24) (0.14) (0.06) (0.24) (0.07) (0.13) (0.19) (0.11) (0.08) (0.11) (0.15) (0.19) (0.23) (0.13) (0.34) CONT ij 0.98*** 2.80*** 1.34*** 1.30*** 1.34*** 0.49*** 1.12*** *** 1.26*** 1.23*** 0.56** 1.24*** 3.10*** 0.95*** 2.70*** (0.26) (0.29) (0.13) (0.12) (0.17) (0.09) (0.15) (0.15) (0.19) (0.08) (0.13) (0.24) (0.26) (0.26) (0.21) (0.32) LANG ij 2.42*** *** 0.89*** 0.40** -0.34*** *** 0.41*** 0.40*** 0.67*** -0.54*** 0.35** -1.17*** (0.28) (0.17) (0.28) (0.08) (0.19) (0.05) (0.14) (0.08) (0.16) (0.11) (0.17) (0.13) (0.14) (0.19) (0.17) (0.29) LANG9 ij -0.94*** 0.80*** 0.58** -0.25*** *** 0.74*** 0.68*** * 0.75*** *** 0.49*** 0.40 (0.36) (0.17) (0.28) (0.08) (0.19) (0.05) (0.14) (0.08) (0.15) (0.10) (0.17) (0.10) (0.15) (0.22) (0.16) (0.29) COL45 ij *** 0.39*** 1.67*** 1.34*** 1.40*** 0.81*** 0.87*** 0.89*** *** 1.41*** 1.90*** 0.54*** 0.40*** (0.26) (0.14) (0.21) (0.05) (0.10) (0.05) (0.09) (0.05) (0.08) (0.07) (0.16) (0.10) (0.12) (0.28) (0.08) (0.13) ACP -2.87*** 2.15*** -1.28*** 2.06*** 0.60** 0.68*** 1.25*** 0.44*** *** *** -1.48*** -1.18** 0.98*** (0.41) (0.32) (0.36) (0.18) (0.24) (0.17) (0.32) (0.11) (0.18) (0.27) (0.28) (0.15) (0.19) (0.50) (0.29) (0.25) LDC -3.25*** *** 1.90*** *** 1.82*** *** 1.99*** *** -2.60*** *** -1.28*** (0.50) (0.36) (0.46) (0.18) (0.28) (0.18) (0.35) (0.13) (0.22) (0.49) (0.52) (0.16) (0.21) (0.51) (0.33) (0.29) GSP -2.17*** *** 0.88*** -0.39** 0.16** 0.95*** *** *** 0.97*** ** 1.01*** 0.71*** (0.41) (0.22) (0.34) (0.12) (0.17) (0.08) (0.31) (0.09) (0.10) (0.20) (0.19) (0.10) (0.14) (0.23) (0.16) (0.18) OTHER -1.00*** 1.14*** *** 1.36*** 0.28*** 0.90*** 0.60*** *** -0.37** 1.04*** 0.49*** 0.70*** 0.81*** (0.24) (0.22) (0.19) (0.11) (0.17) (0.10) (0.33) (0.11) (0.10) (0.16) (0.18) (0.12) (0.18) (0.14) (0.20) (0.17) Constant ** -9.11* * 9.97*** *** *** *** 16.52*** *** *** *** (5.06) (4.98) (7.27) (2.16) (4.75) (1.88) (3.69) (3.33) (3.12) (2.75) (5.19) (3.46) (4.17) (6.57) (4.37) (5.82) No. of obs R-Sq Source: Own analysis based on data described in the text Note: *, ** and *** indicate statistically significance at the 10, 5 and 1 % level, respectively. Robust standard errors in parentheses. All Columns report estimates obtained using the Poisson estimation procedure (PPML) that includes distinct importer and exporter fixed effects (PPML_2) and year dummies

28 Table A.2.7: The trade effects of the EU PTA: PPML_1 regression results with importer-exporter bilateral dummies and year dummies (see Figure 5.5.5) LIVE MEAT AND MEAT PREPARATIO CEREALS AND CEREALS FEEDING VEGETABLES SUGAR AND COFFEE, TEE STUFF FOR MISCELLANE OUS EDIBLE ANIMAL OIL VEGETABLE ANIMAL OR VEG OIL AND FAT TOTFOOD ANIMALS N DAIRY FISH PREP. AND FRUITS SUGAR PREP COCOA ANIMALS PROD BEVERAGE TOBACCO OIL SEED AND FAT OIL AND FAT PROCESSED (EXCL.FISH) (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15) (16) (17) GDP j *** *** 0.65*** 1.27*** 1.20*** 0.76** 0.57*** 0.84*** 1.24*** 1.15*** 1.16*** *** (0.47) (0.32) (0.42) (0.16) (0.37) (0.13) (0.11) (0.13) (0.25) (0.23) (0.31) (0.21) (0.22) (0.47) (0.27) (0.29) (0.0800) GDP i 0.96** ** * *** *** 1.77** 2.49*** (0.40) (1.03) (1.94) (0.35) (0.75) (0.39) (0.45) (0.50) (0.54) (0.48) (0.58) (0.79) (1.12) (1.45) (0.71) (0.93) (0.3077) AVG -1.07*** *** *** *** -0.66*** 1.00*** *** *** (0.36) (0.41) (0.45) (0.25) (0.39) (0.14) (0.25) (0.21) (0.27) (0.20) (0.18) (0.22) (0.38) (0.34) (0.23) (0.36) (0.1143) No. of obs Source: Own analysis based on data described in the text Note: *, ** and *** indicate statistically significance at the 10, 5 and 1 % level, respectively. Robust standard errors in parentheses. All Columns report estimates obtained using the Poisson estimation procedure (PPML) that includes bilateral dummies for each importer-exporter combination (PPML_1) and year dummies

29 Table A.2.8: The trade effects of the EU PTA: PPML_2 regression results with exporters, importers and years fixed effects (see Figure 5.5.5) MEAT AND MEAT PREPARATIO N DAIRY FISH Source: Own analysis based on data described in the text ANIMAL OR VEG OIL AND FAT PROCESSED CEREALS AND FEEDING MISCELLANE LIVE ANIMALS CEREALS PREP. VEGETABLES AND FRUITS SUGAR AND SUGAR PREP COFFEE, TEE COCOA STUFF FOR ANIMALS OUS EDIBLE PROD BEVERAGE TOBACCO OIL SEED ANIMAL OIL AND FAT VEGETABLE OIL AND FAT TOTFOOD (EXCL.FISH) (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15) (16) (17) GDP j 0.58** *** 0.60*** 0.24*** 0.57*** 0.69*** 1.27*** 1.16*** 0.78*** 0.59*** 0.91*** 1.24*** 1.20*** 1.16*** *** (0.26) (0.11) (0.25) (0.06) (0.10) (0.04) (0.07) (0.05) (0.09) (0.09) (0.17) (0.08) (0.09) (0.23) (0.10) (0.15) (0.0288) GDP i 0.92*** 1.47*** *** *** *** 0.74*** 1.67*** -1.19*** *** 1.82*** 2.45*** *** (0.26) (0.34) (0.50) (0.17) (0.30) (0.14) (0.25) (0.19) (0.21) (0.20) (0.34) (0.25) (0.34) (0.57) (0.33) (0.43) (0.0997) DIST ij -0.97*** -0.53** -0.58*** -1.67*** -0.42* -1.11*** -1.36*** *** -0.54*** -0.81*** -0.28* -1.10*** 0.40* -1.96*** *** (0.27) (0.24) (0.14) (0.06) (0.24) (0.07) (0.13) (0.19) (0.11) (0.08) (0.11) (0.15) (0.19) (0.23) (0.13) (0.34) (0.0666) CONT ij 0.97*** 2.83*** 1.34*** 1.30*** 1.31*** 0.49*** 1.12*** *** 1.26*** 1.23*** 0.56** 1.26*** 3.10*** 0.98*** 2.70*** *** (0.25) (0.29) (0.13) (0.12) (0.17) (0.09) (0.15) (0.15) (0.19) (0.08) (0.13) (0.24) (0.26) (0.26) (0.21) (0.32) (0.0702) LANG ij 2.41*** *** 0.89*** 0.42** -0.34*** *** 0.41*** 0.40*** 0.68*** -0.53*** 0.34** -1.17*** (0.28) (0.17) (0.28) (0.08) (0.19) (0.05) (0.14) (0.08) (0.15) (0.11) (0.17) (0.13) (0.14) (0.19) (0.16) (0.29) (0.0673) LANG9 ij -0.92** 0.80*** 0.59** -0.25*** *** 0.74*** 0.68*** * 0.74*** *** 0.55*** *** (0.36) (0.17) (0.28) (0.08) (0.19) (0.05) (0.14) (0.08) (0.15) (0.11) (0.17) (0.11) (0.15) (0.22) (0.16) (0.29) (0.0661) COL45 ij * -3.04*** 0.39*** 1.64*** 1.34*** 1.40*** 0.81*** 0.88*** 0.89*** *** 1.39*** 1.89*** 0.54*** 0.40*** *** (0.26) (0.14) (0.21) (0.05) (0.10) (0.05) (0.09) (0.05) (0.08) (0.07) (0.16) (0.10) (0.11) (0.28) (0.09) (0.13) (0.0350) AVG -1.13*** *** *** 0.92*** 0.32*** 0.33*** 0.92*** -0.42** 1.12*** *** 1.18*** *** (0.23) (0.18) (0.19) (0.11) (0.16) (0.08) (0.33) (0.09) (0.09) (0.16) (0.18) (0.09) (0.15) (0.15) (0.16) (0.16) (0.0508) _cons ** ** 10.16*** *** *** *** 17.03*** *** *** *** * (5.20) (4.99) (7.30) (2.15) (4.87) (1.87) (3.69) (3.34) (3.12) (2.74) (5.16) (3.49) (4.17) (6.59) (4.48) (5.81) (1.5221) No. of obs R-Sq Note: *, ** and *** indicate statistically significance at the 10, 5 and 1 % level, respectively. Robust standard errors in parentheses. All Columns report estimates obtained using the Poisson estimation procedure (PPML) that includes distinct importer and exporter fixed effects (PPML_2) and year dummies

30 Table A.2.9: PTAs effect on Extensive Margin of Trade: SSTW regression results (see Figure 5.5.6) Source: Own analysis based on data described in the text Extensive N. Lines Extensive N. Lines Margin Margin GDP j 0.36*** 0.38*** 0.30*** 0.33*** (0.01) (0.01) (0.01) (0.01) GDP i 0.41*** 0.21*** 0.37*** 0.18*** (0.04) (0.03) (0.04) (0.03) DIST ij -1.04*** -0.98*** -1.05*** -1.01*** (0.03) (0.02) (0.03) (0.02) CONT ij 0.60*** 0.66*** 0.62*** 0.69*** (0.08) (0.05) (0.08) (0.05) LANG ij *** *** (0.03) (0.02) (0.03) (0.02) LANG9 ij 0.35*** 0.25*** 0.36*** 0.25*** (0.03) (0.02) (0.03) (0.02) COL45 ij 0.66*** 0.51*** 0.65*** 0.50*** (0.03) (0.02) (0.03) (0.02) COLONY ij 0.19*** 0.22*** 0.19*** 0.22*** AVG 0.29*** 0.21*** (0.03) (0.02) (0.03) (0.02) (0.03) (0.02) ACP1 0.40*** 0.41*** (0.04) (0.03) ACP2 0.22*** 0.10*** (0.04) (0.03) ACP (0.04) (0.03) ACP4-0.23*** -0.21*** (0.04) (0.04) GSP ** (0.03) (0.03) GSP *** (0.04) (0.03) LDC1 0.10* -0.22*** (0.05) (0.04) LDC2-0.36*** -0.34*** (0.04) (0.04) OTHER 0.31*** 0.17*** (0.04) (0.03) Constant -1.34** -0.82* (0.58) (0.44) (0.58) (0.45) No. of obs. 76,330 76,330 76,330 76,330 Note: *, ** and *** indicate statistically significance at the 10, 5 and 1 % level, respectively. Robust standard errors in parentheses. The extensive margin is measured both as weighted count of the exported products or as simple count of product lines exported. All the results are based on the Santos Silva, Tenreyro and Wey (2014) estimation procedure, that corrects for the double bounds of the dependent variables

31 Table A.2.10: PTAs effect on Extensive Margin and Trade: PPML_2 regression results (see Figures and 5.5.7) Source: Own analysis based on data described in the text Trade Extensive Trade Extensive Value Margin Value Margin GDP j 0.63*** 0.24*** 0.60*** 0.20*** (0.03) (0.01) (0.03) (0.01) GDP i 0.48*** 0.31*** 0.45*** 0.31*** (0.10) (0.03) (0.10) (0.03) DIST ij -0.76*** -0.63*** -0.76*** -0.63*** (0.07) (0.02) (0.07) (0.02) CONT ij 0.87*** 0.06** 0.87*** 0.07** (0.07) (0.03) (0.07) (0.03) LANG ij (0.07) (0.02) (0.07) (0.02) LANG9 ij 0.71*** 0.19*** 0.71*** 0.19*** (0.07) (0.02) (0.07) (0.02) COL45 ij 0.89*** 0.54*** 0.88*** 0.52*** (0.05) (0.02) (0.05) (0.02) COLONY ij *** *** AVG 0.52*** 0.18*** (0.05) (0.02) (0.04) (0.01) (0.04) (0.01) ACP1 0.64*** 0.32*** (0.09) (0.03) ACP2 0.74*** 0.18*** (0.09) (0.03) ACP3 0.65*** 0.08*** (0.08) (0.03) ACP4 0.53*** -0.08*** (0.10) (0.03) GSP 0.37*** 0.02 (0.06) (0.02) GSP+ 0.53*** 0.02 (0.07) (0.02) LDC1 0.76*** 0.11*** (0.11) (0.04) LDC *** (0.09) (0.03) OTHER 0.76*** 0.21*** (0.06) (0.02) Constant 2.80* -2.22*** 3.62** -1.52*** (1.53) (0.41) (1.55) (0.41) No. of obs. 79,962 76,330 79,962 76,330 R-sq Note: *, ** and *** indicate statistically significance at the 10, 5 and 1 % level, respectively. Robust standard errors in parentheses. All Columns report estimates obtained using the Poisson estimation procedure (PPML) that includes distinct importer and exporter fixed effects (PPML_2) and year dummies

32 Table A.2.11: Gravity regressions with quality of institution variables Dependent variable : trade value (1) (2) (3) (4) (5) GDP j *** *** *** *** *** (0.0307) (0.0313) (0.0312) (0.0313) (0.0319) GDP i *** *** *** *** *** (0.1006) (0.1006) (0.1007) (0.1006) (0.1007) DIST ij *** *** *** *** *** (0.0671) (0.0671) (0.0685) (0.0671) (0.0685) CONT ij *** *** *** *** *** (0.0700) (0.0700) (0.0696) (0.0700) (0.0696) LANG ij ** ** (0.0678) (0.0678) (0.0672) (0.0678) (0.0672) LANG9 ij *** *** *** *** *** (0.0664) (0.0664) (0.0661) (0.0664) (0.0661) COL45 ij *** *** *** *** *** (0.0355) (0.0355) (0.0351) (0.0355) (0.0351) PTA *** *** *** *** *** (0.0523) (0.0524) (0.0526) (0.0524) (0.0526) AUTOC ij Source: Own analysis based on data described in the text (0.0007) (0.0071) DURABILITY ij *** *** (0.0004) (0.0004) POLCOMP ij (0.0006) (0.0064) _cons (1.5120) (1.5120) (1.5153) (1.5127) (1.5241) No. of obs. 67,184 67,184 67,184 67,184 67,184 R-Sq Note: *, ** and *** indicate statistically significance at the 10, 5 and 1 % level, respectively. Robust standard errors in parentheses. All Columns report estimates obtained using the Poisson estimation procedure (PPML) that includes distinct importer and exporter fixed effects (PPML_2) and year dummies

33 A.2.3. The effect of PTAs on the price and quality of exported agri-food products: Technical discussion (refer to figures 5.5.8, and ) Understanding the extent to which the preferential trade agreements have contributed to the increase of the quality of exported goods is of vital importance. This is because there is growing theoretical and empirical evidence showing that the quality of exported goods matter for the export performance and economic development (see Khandelwal, 2010; Rodrik and Hausmann, 2011). In this section we present and discuss the empirical evidence related to this relevant issue. In particular, our purpose is to test whether being a member of a PTA with the EU has affected the pattern of trade concerning the quality of exported agri-food products. Our main goal is to use as proxy for quality, both the unit value (price) obtained from trade data, as normally done by previous literature, as well as a direct measure of quality inferred following the approach of Khandelwal, Schott and Wei (2013). The starting point of our analysis is the empirical specification presented in section (equation 10), that we reproduce below for exposition clarity: 129 y ijk,t = β ln dist ij + γ ln Tadv ijk,t + δpta ij,t + θ ln Tadv ijk,t PTA ij,t + μx ijk,t + ε ijk,t where y ijk,t represents the dependent variable and accounts, either for the log of free on board (FOB) price (unit value) or the (log) estimated quality of product k exported from country i (an ACP or another country) to country j (in this case an EU country) at time t. Moreover because the price of the exported products can be decomposed into the price-adjustedquality and the quality components, we obtain this pure price effect by subtracting from the log unit values the estimated quality term (which is already in log) 130. This allows us to disentangle the effect due to the price-adjusted quality rather than the quality component, in order to assess the contribution of these two components to the gross price term. Before beginning the results discussion, we summarize the key theoretical expectations from the estimation of the relation (1). From this perspective, the empirical analysis can be thought of as a three step procedure. In a first step, we regress our dependent variables on the (log) of the ad valorem tariffs and on the (log) of the bilateral distances. In this respect, we test whether an increase in tariffs has an effect on the price and/or the quality of the exported products. Assuming that price and quality are positively correlated, the expectation is that θ < 0. Indeed, when the tariff is ad valorem, namely increasing with the value of the good, it represents a disincentive for firms to export higher quality goods (Hummels and Skiba, 2004). Differently, considering distance, because transport costs are per unit (Hummels, 1999) our expectation is that β > 0, namely goods with higher unit value (higher price) should be exported in more distant countries, because for this goods the incidence of (per unit) transport costs is lower. This positive prediction represents the so called Alchian and Allen effect, who argue that goods of higher quality, been more expensive, should be exported in more distant countries, in order to offset higher trade costs. Yet, this relation is normally estimated using price as proxy for quality. Instead, the novelty here is to disentangle the effect of these two components. If a one to one relation between price and quality does not hold, as could be indeed the case, then the Alchian and Allen effect has to be verified especially for the price component, but less so for the quality component. In a second step, we add to the specification the PTA dummy, which takes the value of 1 if a country has a PTA with the EU, and 0 otherwise. 131 In this way we can test whether, countries with a preferential trade agreement, on average, export higher quality (or priced) product to the EU with respect to other countries, after controlling for tariff, distance as well as countries and sectoral heterogeneity. As a final step, the interaction between the ad valorem tariffs variable and the PTA dummy is added to the specification. Differently from the previous step, where we assess an average PTA effect on quality (or price), this approach allows us to estimate the effect of an increase (or decrease) of tariffs 129 Note that this analysis considers only the extra-eu trade. Hence, only products exported to the EU15 from non EU countries are considered. 130 Indeed, by construction, prices are the sum of the quality and price-adjusted quality components (see Section for details). 131 Given the period considered in the analysis (2001, 2004, and 2007), our PTA dummy considers the following preferential trade agreements reported in Table 5.5.3: ACP3, GSP, GSP+, LDC1 and LDC2 (EBA)

34 separately for countries with and without a PTA or, put differently, to understand if the PTA effect on quality (price) is conditional on the level of tariffs. Table A.2.12 reports the results of the empirical analysis. The first three columns display the results of regressing our dependent variables (price, quality and price-adjusted-quality) on the (log) of the ad valorem tariffs and on the (log) of the bilateral distances. As said before, (fob) prices are decomposed in their quality and price-adjusted-quality components. The former captures the contribution of the quality component to the relationship under analysis, while the latter captures the contribution given by the pure price component. The results in column 1 show that the (fob) price of products exported to the EU is positively and significantly related to the bilateral distance. Looking to the results in columns 2 and 3, where the price is decomposed in the quality and in the price-adjusted-quality components respectively, it emerges that the result outlined in column 1 is almost entirely due to the price-adjusted-quality component. 132 Thus, in line with our a-priori expectation the relationship between the price of the exported products and the distance of the destination markets, is almost entirely captured by the pure-price component. Differently, the coefficient of the distance when the quality is the dependent variable, even if positive, is several orders of magnitude lower than the one in column1, and not statistically significant. It is possible to assess the contribution of the quality and the price-adjustedquality components, just by dividing the coefficients reported in columns 2 and 3, respectively, by the one of column 1, yielding 5% (0.0103/0.201) for the former and 95% (0.191/0.201) for the latter. This result represents a confirmation of the Alchian and Allen effect, namely that higher priced products are exported to more distant countries in order to offset the high transport costs. As a corollary, the quality component, which captures everything except the price of a product, is not significantly related to the distance of the destination market. Consistent with expectation, there exists a negative relationship between the price of the exported products and the ad valorem tariff (see column 1). The economic magnitude of the effect suggests that a 10 percentage points increase in tariffs leads to a decrease of the export price of about 0.56%. Looking at the coefficient of the ad valorem tariff in columns 2 and 3, it comes out that, in contrast to what previously emerged with the distance, the quality component seems to largely explain the relationship between the price of the exported products and the ad valorem tariff. Indeed, the quality of the exported products is negatively and significantly related to the ad valorem tariff, while the relationship with the price-adjusted-quality component is very weak and not significant. The rationale for this finding is that when tariffs are lowered the final prices for the consumer will be lower, leading to a gain in market share of the affected products. Indeed, by definition, the main determinant of our quality measure is market share. The results in columns 4 to 9 constitute the core of this analysis. As shown in column 4, introducing the PTA dummy, it emerges that, on average, after controlling for the bilateral distance and the level of tariff, countries with a PTA with the EU tend to export products of lower price. The result is remarkable in terms of magnitude. Indeed, a preferential trade agreement with the EU leads, on average, to export products at prices that are about 15% lower than that from other countries, ceteris paribus. However, and interesting, when the quality component is considered (see Column 5), the results suggest that to be into a PTA does not have any significant effect on the quality of exported product. By contrast, as emerges from column (6), it is the pure price component of the price, that captures the negative effect of PTA on the price of the exported products. From these results it clearly emerges that the negative relationship between export prices and the PTA dummy is entirely captured by the price-adjusted-quality component. As a consequence, this analysis produces evidence that preferential trade agreements seem to affect mostly the price component of the exported products, allowing countries with a PTA to export, on average, products at lower price than other countries, but not of different level of quality, ceteris paribus. Finally, columns 7 to 9 show the results of adding to the specification the interaction term between the PTA dummy and the ad valorem tariff. These results allow one to produce separate elasticities of our dependent variables to ad valorem tariffs, for countries with and without a PTA. As shown in column 7, and in particular by the computed elasticities at the bottom of the table, countries in PTAs with the EU exhibit a negative elasticity of price to tariff. However, when we consider the same elasticity for no PTA countries, it turns out to be positive although very low, suggesting that the price of developed countries exports to the EU is not sensitive to a change in tariff. 132 Note that, the coefficient of the distance in column 1 represents the algebraic sum of the two distance coefficients when the quality and the price-adjusted-quality are considered separately

35 Interesting, this overall effect, when decomposed to its component, goes in a totally different direction when PTA and no PTA countries are considered. For the former, the negative price elasticity, is mainly due to the pure price component that account for 65% of the overall effect, while the quality one only 35%. Instead, considering no PTA countries, the very low (positive) price elasticity to tariff is the results of a counterbalancing effect. Indeed, while the quality elasticity to tariff in negative and of relevant magnitude, the opposite happens when the pure price component is considered. Taken together, these effects show, for PTA countries that an increase in the preference margin main lead to export of higher quality products at higher prices. On the other hand, for no PTA countries a reduction of EU tariffs leads them to export higher quality product but at lower prices. Table A.2.12: The PTA effect on the price, quality and price adjusted for quality of the exported products (1) (2) (3) (4) (5) (6) (7) (8) (9) Price Adj. Price Adj. Price Adj. (ln) Price (ln) Quality (ln) Price (ln) Quality (ln) Price (ln) Quality Quality Quality Quality (ln) Distance 0.232*** *** 0.232*** *** 0.232*** *** ( ) ( ) (0.0110) ( ) ( ) (0.0110) ( ) ( ) (0.0110) (ln) Tariff ** *** * *** *** 0.201*** (0.0277) (0.0246) (0.0311) (0.0281) (0.0249) (0.0315) (0.0401) (0.0358) (0.0438) Dummy PTA *** *** *** *** (0.0304) (0.0344) (0.0396) (0.0306) (0.0345) (0.0397) Dummy PTA * (ln) Tariff *** 0.134*** *** (0.0430) (0.0371) (0.0469) Importer FE Yes Yes Yes Yes Yes Yes Yes Yes Yes Exporter FE Yes Yes Yes Yes Yes Yes Yes Yes Yes Product (hs 6-digit) FE Yes Yes Yes Yes Yes Yes Yes Yes Yes Year FE Yes Yes Yes Yes Yes Yes Yes Yes Yes Elasticities to 10% increase in tariffs PTA = PTA = N R-sq Note: The table reports estimation results of equation 1. *, ** and *** indicate statistically significance at the 10, 5 and 1 % level, respectively. See text for details

36 A.2.4 The effect of PTAs on the price and quality of exported agri-food products: Additional results at product level Figure A.2.13: Price, price-adjusted-quality and quality elasticities to tariffs for PTA vs. no PTA countries Meat and meat preparation Note: the figure reports the elasticity of price, price-adjusted quality and quality to tariffs of products exported to the EU. PTA countries are the ACP, LDC and GSP. Figure A.2.14: Price, price-adjusted-quality and quality elasticities to tariffs for PTA vs. no PTA countries Cereals and cereal preparation Note: the figure reports the elasticity of price, price-adjusted quality and quality to tariffs of products exported to the EU. PTA countries are the ACP, LDC and GSP

37 Figure A.2.15: Price, price-adjusted-quality and quality elasticities to tariffs for PTA vs. no PTA countries Vegetables and fruits Note: the figure reports the elasticity of price, price-adjusted quality and quality to tariffs of products exported to the EU. PTA countries are the ACP, LDC and GSP. Figure A.2.16: Price, price-adjusted-quality and quality elasticities to tariffs for PTA vs. no PTA countries Sugar and sugar preparation Note: the figure reports the elasticity of price, price-adjusted quality and quality to tariffs of products exported to the EU. PTA countries are the ACP, LDC and GSP

38 Figure A.2.17: Price, price-adjusted-quality and quality elasticities to tariffs for PTA vs. no PTA countries Fixed vegetables fats and oils Note: the figure reports the elasticity of price, price-adjusted quality and quality to tariffs of products exported to the EU. PTA countries are the ACP, LDC and GSP