Antoine Bouet-CEPII

RECHERCHE ET EXPERTISE SUR L’ECONOMIE MONDIALE

Ce que l’on sait, ce que l’on ne sait pas et ce qu’il faut savoir sur le commerce alimentaire informel en Afrique (de l’Ouest) Antoine Bouët (CEPII) SWAC/OECD Experts Meeting: “Intra-regional food trade data in West Africa” 12/13 October in Paris, France

Introduction

• Importance of trade data in agriculture and food – A key input for the balance of payments – A key input for identification of products with comparative advantage – A key input for food safety and the establishment of “food balance sheets” – A key input for the private sector – A key input for academic research

• The African Context – The Malabo declaration – The AfCFTA – Importance of informal trade

Measuring trade in West Africa

• Main databases: • • • • •

COMTRADE BACI FAOSTAT Regional databases (CEDEAO…) Source of data: Customs => National Statistical Institutes

• In (West) Africa: – Informal trade is important • Trade in small quantities • Smuggling • Underinvoicing/misclassification

– Many factors in the African context: costs/benefits of formalization – ECOWAS: weak incentives of customs to record trade - no custom duties

The quality of ‘formal’ databases can be questioned

• Absence of declarations Frequency of declaration of trade flows, COMTRADE, ECOWAS countries from 2010 to 2016 Nigeria Ghana Cote d'Ivoire Mali Senegal Burkina Benin Togo Liberia Guinee Sierra Leone Cape Vert Guinee Bissau Gambie Niger

2010 Y Y Y Y Y Y Y Y

2011 Y Y Y Y Y Y Y Y

2012 Y Y Y Y Y Y Y Y

2013 Y Y Y

Y Y Y Y

2014 Y

2015

Y

Y

Y Y Y Y

Y Y Y Y

Y Y Y Y Y

Y Y Y

Y Y

Y

Y Y

Y

Y

Y

Y

Y Y Y

Y Y

Y Y

Y Y

Y Y

Y Y

Source : Mitaritonna et Traoré, 2017 Note: Y means that data are available

2016 Y Y

How are official databases (e.g. COMTRADE) improved?

• BACI database designed by CEPII from COMTRADE – Procedure that reconciliates mirror flows: declaration of exporting countries and importing countries – Transportation costs are evaluated thanks to a gravity model (proxy of CIF/FOB) – It weighs each declaration by the quality of reporting country according to an econometric procedure

How are official databases (e.g. COMTRADE) improved?

COMTRADE-BACI Comparison Total imports ECOWAS (Millions USD) 160

140 120 100 80 60 40 20 0 2000

2001

2002

2003

2004

2005

2006

2007 Comtrade

2008

2009

2010

2011

Diff BACI

Source : Mitaritonna et Traoré, 2017 Source: BACI et COMTRADE

2012

2013

2014

2015

2016

COMTRADE-BACI Comparison

Intra and extra regional trade – ECOWAS – Imports 2000-2016 Intra_ECOWAS trade (mlns USD) Year 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

Comtrade 2.4 2.0 1.7 3.3 3.2 4.5 4.3 5.9 8.0 3.8 6.2 7.4 8.3 9.2 7.5 4.4 4.3

BACI 2.7 2.7 2.9 4.2 4.6 6.5 6.5 7.4 10.9 6.4 8.6 9.8 11.7 13.9 12.1 7.5 7.0

BACI/Comtrade 1.1 1.3 1.7 1.3 1.4 1.4 1.5 1.2 1.4 1.7 1.4 1.3 1.4 1.5 1.6 1.7 1.6

Source : Mitaritonna et Traoré, 2017 Source: BACI et COMTRADE

Extra_ECOWAS trade (mlns USD) Comtrade 10.9 14.1 15.8 25.1 10.4 16.2 38.9 54.6 55.9 54.9 72.1 94.6 71.1 81.5 73.6 24.8 62.8

BACI 23.1 26.1 28.8 35.6 35.4 43.0 56.7 74.5 92.0 87.7 101.1 131.1 110.5 118.1 121.9 100.2 91.2

BACI/Comtrade 2.1 1.8 1.8 1.4 • 3.4 2.7 • 1.5 1.4 • 1.6 1.6 1.4 1.4 1.6 1.4 1.7 4.0 1.5

- Larger Difference with extraECOWAS trade - Wrong declarations on both sides with intra - Average ratios : 1.90 versus 1.45

Still some limitations…

• Statistical treatment based on mirror flows: limited possibilities • Presence of informal flows • Trade in small quantities • Smuggling • Underinvoicing, misclassification

• Indirect methods of evaluation exist…, but they have their own limitations • National account approach (comparison: production, consumption and recorded trade) • Econometric approach: use of gravity models

What can be done?

• Direct methods of evaluation are needed – More or less complete surveys – Only a few in West Africa: CILSS, ECENE (2010, 2011), Benin and Nigeria – Very interesting survey in Uganda since 2005 (BoU+UBOS)

Studies measuring ICBT in Africa (Source : Bouët, Pace and Glauber, 2018)

Country / region at origin

Name of the initiative

Operated by

Funded by

Borders covered

Years covered

Products covered

Type of ICBT

Survey

Uganda

ICBT Survey

Uganda Bureau of Statistics

Bank of Uganda

Uganda with South Sudan, Congo RD, Rwanda, Tanzania and Kenya

2005-2017

All goods

ICBT Def. A

Survey

Rwanda

ICBT Survey in Rwanda

National Bank of Rwanda, National Institute of Statistics of Rwanda

Government of Rwanda

Rwanda with Burundi, DR Congo, Tanzania and Uganda

2009-2017

All goods

ICBT Def. A

Interviews

DR Congo

Timber Trade in Africa’s Great Lakes

South African Institute of International Affairs

na

DR Congo with Uganda, Burundi, Tanzania and Kenya (through Uganda)

November 2010February 2012

timber

ICBT Def. A

Survey

Benin

ECENE

Benin INSAE

Ministere du Developpement, de l'Analyse Economique et de la Prospective du Benin et Delegation de l'UE au Benin

Benin with Togo, Nigeria, Niger and Burkina

2010 / 2011

all merchandises

ICBT Def. B

Estimation

The Gambia/Senegal

Golub and Mbaye (2009)

World Bank

The World Bank, Agence Francaise du Dévelopement (AFD)

The Gambia with Senegal

2006

Agricultural (unprocessed and processed) goods

ICBT Def. B

Survey

Namibia

Informal CrossBorder Trade Survey (ICBTS)

Namibia Statistics Agency

Bank of Namibia - Namibia Ministry of Finance

Namibia with Angola, South Africa and Zambia

2014-2015

all merchandises

ICBT Def. A

Survey

Cameroon

Cameroon Ministry of Agriculture and Rural Development

Cameroon Ministry of Agriculture and Rural Development

Cameroon with Central African Republic, Chad, Gabon, Congo and Equatorial Guinea

2008

agricultural and horticultural commodities

ICBT Def. A

Type of study

Studies measuring ICBT in Africa (Source : Bouët, Pace and Glauber, 2018)

Type of study

Country / region at origin

Name of the initiative

Meta-Survey

Eastern Africa

East Africa Crossborder Trade

Meta-Survey

Eastern and Southern Africa

Informal Cross-border Trade In Eastern And Southern Africa

Survey

Southern Africa

Cross-border Food Trade Monitoring Initiative

Survey

Kenya

Informal Cross-border Trade Survey

Survey

Tanzania

Survey

Eastern and Southern Africa

Ackello-Ogutu (1996)

Operated by

Funded by

Data provided by the EAGC, USAID, FAO, FEWSNet, Ministère FEWS NET, FAO, NBR and des Affaires Étrangères de la WFP France

Borders covered

ICBT between Tanzania, Burundi, Rwanda, Uganda, Kenya, Somalia, Djibouti, Ethiopia, Sudan, and South Sudan and DRC

Years covered

Products covered

Type of ICBT

2010-2014

Staple food commodities: Maize grain, Rice grain, Maize and wheat flour, Beans and pulses, Cassava, Onions, Tomatoes, Live bovine animals, Milk and cream, Bovine meat, Fish and crustaceans

ICBT Def. A

USAID, ILRI, ReSAKSS

ICBT between Burundi, Democratic Republic of Congo, Djibouti, Ethiopia, Kenya, Malawi, Rwanda, Uganda, Tanzania, Zambia and South Sudan

ACTESA

ACTESA, WFP, FEWSNET

ICBT between Malawi, Mozambique, Zimbabwe and Zambia.

2011-2017

Food products

ICBT Def. A

KNBS

KNBS

Kenya’s ICBT with Uganda, Tanzania, Somali and Ethiopia

2nd quarter of 2011

all merchandise

ICBT Def. A

USAID Africa Bureau

USAID

Tanzania's ICBT with Kenya, Malawi, Zambia, DR Congo, and Uganda

1995-96

all merchandise

ICBT Def. A

USAID

Kenya-Uganda border; Tanzania with Malawi, Zambia, Congo RD and Uganda; Malawi with Mozambique, Tanzania and Zambia; Mozambique with South Africa, Swaziland, Malawi, Zimbabwe, Zambia and Tanzania

1994-95

Some agricultural food products and some manufactured goods

ICBT Def. A

secondary data on ICBT in ESA region collected by UBOS, EAGC, FEWS NET and ACTESA.

Technoserve, Kenya

Studies measuring ICBT in Africa (Source : Bouët, Pace and Glauber, 2018)

Type of study

Country / region at origin

Name of the initiative

Operated by

Econometrics of mirror trade data

Kenya, Mauritius and Nigeria

Bouet and Roy (2010)

IFPRI

Econometrics of mirror trade data

75 countries

Jean and Mitaritonna (2010)

CEPII

Econometrics of mirror trade data

Mozambique

Von Dunem and Arndt (2009)

Econometrics of mirror trade data

Kenya/Tanzania vs.

Kenya/UK

Levin and Windell (2014)

Funded by

European Commission

SIDA-U-Forsk

Borders covered

Years covered

Products covered

Type of ICBT

Kenya, Mauritius and Nigeria

2001, 2004

all goods

ICBT Def. C

Burundi, Cameroon, Gabon, Kenya, Madagascar, Malawi, Mauritania, Mauritius, Morocco, Seychelles, Tanzania, Tunisia

2001, 2004

all goods

ICBT Def. C

Mozambique

2003

all goods

ICBT Def. C

Kenya/Tanzania

2000

all goods

ICBT Def. C

The CILSS approach

– Methodology: • Based on APEX organizations • Enumerators collect data on agri. trade along trade corridors and main marketplaces • Key partners: ACTOAH/CILSS – IFPRI - USAID

– CILSS has also collected data on ‘tracasseries administratives’ • road harassment by police, gendarmerie, city officials, sanitary inspectors, custom officers…

• Data on bribes and wasted time

– Beyond the collection of data • More information on prices and quantities available for the private sector • Improving national and regional policies

The CILSS approach

• Advantages: • Daily flows • No need for time extrapolation • APEX organizations have an extensive knowledge of what happens • APEX organizations facilitate the collection of data by transporters

• Limitations : • All products are not covered • Limited collection concerning the West and East Basins • Limited collection concerning certain modes of transports (sea, laguna) • Systematic data quality control are being implemented

Comparison CILSS/COMTRADE

Bilateral Flows in 2016 for maize, in thousands of USD UN COMTRADE Burkina Benin

Ghana

CILSS Mali

0.54

Burkina

38.41

Cote d’iv.

Ghana Mali Nigeria Togo

58.39

Total

59.68

36.609

81.27

Niger

Togo

2845.58

1.34

848.16

Burkina

3.947 13.77

Cote d’iv.

Ghana Mali Nigeria Togo Total

134.32 36.61

Source: COMTRADE and CILSS Exporter in row - Importer in column

Benin

31.99

0.74 0.55 727.92

Burkina

3029.63

1.34

Ghana

Mali

1440.85

Niger

Togo

8.91 900.64

48.03

7761.08

45.88

3254.73 2204.47

24.48

4990.69

65.06 626.38

0.04

679.92

154.74

7579.98

1079.85

5285.00 5038.72

13746.43

45.92

Integrating CILSS data into official data: challenges to be met

• CILSS has already improved many aspects concerning collection techniques – Flows are now recorded according to international norms (HS-NTS nomenclature, choice of units)

– double accounting issue

• Extension of geographic and product coverage • Institutional arrangements between actors (CILSS-WAEMU-ECOWASINS-IFPRI)

Role of IFPRI

• Participation of private sector • Participation of IFPRI – Quality control – Documentation of databases – Communication activities on obstacles to regional trade – Evaluating the impact of road harassment – Identification at a disaggregated level of the location of major food security and nutrition bottlenecks

Conclusion

• Integration of CILSS data into Nat’l Statist’ Institutes databases in progress • CILSS-IFPRI-USAID: successful initiative

• Important for statistical issues but also for food safety • Can it be improved? And implemented at the continental level?