Linking Poor Rural Households to Microfinance and Markets in Ethiopia

Total Page:16

File Type:pdf, Size:1020Kb

Linking Poor Rural Households to Microfinance and Markets in Ethiopia Linking Poor Rural Households to Microfinance and Markets in Ethiopia Baseline and Mid-term Assessment of the PSNP Plus Project in Doba March 2010 John Burns Solomon Bogale Gezu Bekele Table of Contents SUMMARY ................................................................................................................................... 7 1. INTRODUCTION .................................................................................................................. 9 1.1 PSNP Plus Project Background....................................................................................... 9 1.2 Linking Poor Rural Households to Microfinance and Markets in Ethiopia ............... 11 2 THE PSNP PLUS PROJECT .................................................................................................. 11 2.1 PSNP Plus Overview....................................................................................................... 11 2.2 LIS Overview.................................................................................................................... 12 2.2 Overview of PSNP Plus Project Activities in Doba ...................................................... 13 2.2.1 Study Area General Characteristics ........................................................................... 13 2.2.2 Microfinance Linkage Component .............................................................................. 13 2.2.3 Village Saving and Lending Associations................................................................... 14 2.2.4 Market Linkage Component ....................................................................................... 15 2.3 Research Questions ....................................................................................................... 17 3. ASSESSMENT METHODOLOGY ......................................................................................... 17 3.1 LIS Approach................................................................................................................... 17 3.2 Overview of Methods and Indicators ............................................................................ 19 3.3 Indicator Selection .......................................................................................................... 19 3.4 Sampling .......................................................................................................................... 19 3.4.1 Method and Size......................................................................................................... 19 3.4.2 Study Locations........................................................................................................ 20 3.5 Data Collection Methods ............................................................................................. 22 3.5.1 Household Interviews ................................................................................................. 22 3.5.2 Focus Group Methods ................................................................................................ 23 3.6 Pre-Testing ...................................................................................................................... 23 3.7 Triangulation ................................................................................................................... 24 3.8 Data Analysis................................................................................................................... 24 3.9.1 Analysis of VSLA and Non-VSLA Comparison Groups ........................................... 24 4 RESULTS ................................................................................................................................ 26 4.1 PSNP Plus in the Context of Other Programs in Doba................................................ 26 4.2 Project Status at the time of the Assessment .......................................................... 27 4.3 Community Characteristics ........................................................................................... 29 4.3 Characteristics and Background Data on sampled PSNP Plus Households ............ 30 4.4 Income.............................................................................................................................. 31 4.4.1 Sources of Income...................................................................................................... 31 4.4.2 Livestock Sales........................................................................................................... 31 4.4.3 Crop Sales.................................................................................................................. 31 4.5 Expenditure ..................................................................................................................... 32 4.6 Asset Levels and Changes............................................................................................. 34 4.6.1 Land............................................................................................................................ 34 4.6.2 Livestock..................................................................................................................... 34 4.6.3 Productive Assets (Tools)........................................................................................... 35 4.7 Savings and Loans ......................................................................................................... 38 4.8 Comparison Between VSLA and Non-VSLA Households ........................................... 41 5. DISCUSSION ......................................................................................................................... 43 Longitudinal Impact Study of the PSNP Plus Program Baseline Assessment in Doba Woreda 5.1 Assessment Constraints and Methodological Limitations ......................................... 43 5.1.1 Timing......................................................................................................................... 43 5.1.2 Attribution ................................................................................................................... 44 5.1.3 Indicators .................................................................................................................... 45 5.1.4 Sampling Challenges.................................................................................................. 46 5.1.5 Selection and Respondent Bias ................................................................................. 46 5.1.6 Secondary data limitations ......................................................................................... 46 5.1.7 Other Challenges........................................................................................................ 47 5.2 Community Wealth Indicators ....................................................................................... 47 5.2.1 Livestock..................................................................................................................... 47 5.2.2 Land............................................................................................................................ 48 5.2.3 Cash Crops and Honey Production ............................................................................ 48 5.2.4 Dwellings and Household Items ................................................................................. 48 5.2.5 Food Security Duration............................................................................................... 49 5.3 Factors Affecting Food Security and Asset Accumulation......................................... 49 5.3.1 Rain Failure and Pests ............................................................................................... 49 5.3.2 Livestock Disease....................................................................................................... 50 5.3.3 Food Prices ................................................................................................................ 50 5.3.4 Education Expenses................................................................................................... 50 5.3.5 Lack of Employment Opportunities and Land Division ............................................... 51 5.3.6 Medical Expenses ...................................................................................................... 51 5.3.7 Household Responses to Food Insecurity.................................................................. 51 5.4 Income Sources .............................................................................................................. 52 5.4.1 Cash Crops................................................................................................................. 52 5.4.2 Livestock Production and Trade ................................................................................. 52 5.4.3 PSNP Employment..................................................................................................... 53 5.4.4 Petty Trade and Other Income Generating Activities ................................................. 53 5.4.5 Informal Employment and Firewood Sales................................................................. 53 5.5 Expenditure ..................................................................................................................... 54 5.6 Assets and Asset Changes ............................................................................................ 54 5.6.1 Land Holdings............................................................................................................
Recommended publications
  • Ethiopia: 2015 HRF Projects Map (As of 31 December 2015)
    Ethiopia: 2015 HRF projects map (as of 31 December 2015) Countrywide intervention ERITREA Legend UNICEF - Nutrition - $999,753 Concern☃ - VSF-G ☈ ! Refugee camp WFP - Nutrition (CSB) - $1.5m National capital Shimelba Red Sea SUDAN Regional intervention International boundary Hitsa!ts Dalul UNICEF - Health - $1.0m ! !Hitsats ! ! Undetermined boundary ! ! SCI Tigray, Afar, Amhara, Oromia, Kelete Berahile ☃☉ May-Ayni Kola ! Somali, Gambella, SNPR & NRC - ☉ Ts!elemti Temben Awelallo Lake IRC - ★ ! ☄ ! ♫ Tanqua ! SUDAN ! ! ! Dire Dawa Adi Harush ! Enderta Abergele ! Ab Ala Afdera Project woredas Tselemt ! NRC - Debark GAA - ☇ ! WFP (UNHAS) - Coordination ☈ Abergele! Erebti ☋☉ Plan Int. - ACF - ☃ Dabat Sahla ☃Megale Bidu and Support Service - $740,703 Janamora Wegera! Clusters/Activities ! Ziquala Somali region Sekota ! ! Concern - SCI Teru ! Agriculture CRS - Agriculture/Seed - $2,5m ☃ ☃ Kurri ! Dehana ! ☋ ! Gaz Alamata ! Elidar GAA - ☋ Amhara,Ormia and SNNP regions ! ☃☉ Gonder Zuria Gibla ! Gulf of ! Education Plan Int. - Ebenat Kobo SCI☃☉ ☃ ! Gidan ☄ Lasta ! Aden CARE - Lay Guba ! Ewa ! ☃ ! Meket Lafto Gayint ! Food security & livelihood WV - ☃ Dubti ☈ ☉ ! Tach Habru Chifra SCI - ☃ Delanta ! ! - Tigray Region, Eastern Zone, Kelete Awelall, ! Gayint IMC - ☃ Health ☉ Simada Southern Zone, Alamata and Enderta woredas ! ! Mile DJIBOUTI ☊ Mekdela ! Bati Enbise SCI- Nutrition ! Argoba ☃☉ WV - ☃ Sar Midir Legambo ☃ ! Oxfam GB - Enarj ! ☉ ! ! Ayisha Non Food Items - Amhara region, North Gonder (Gonder Zuria), Enawga ! Antsokiya Dalfagi ! ! ! Concern
    [Show full text]
  • 73-84 Association of Arabica Coffee Quality Attributes with Selected So
    East African Journal of Sciences (2015) Volume 9 (2) 73-84 Association of Arabica Coffee Quality Attributes with Selected Soil Chemical Properties Adugnaw Mintesnot1*, Nigussie Dechassa2,and Ali Mohammed1 1Jimma University, Department of Horticulture, P. O. Box 307, Jimma, Ethiopia 2Haramaya University, Department of Plant Sciences, P. O. Box 138, Dire Dawa, Ethiopia Abstract: Coffee (Coffea arabica L.) bean quality attributes differ based on the origin of the produce. Several agro-ecological conditions influence coffee bean quality attributes. Soil chemical properties may be some of the factors affecting the quality attributes. However, no study has so far been conducted to elucidate the association of coffee bean qualities with soil chemical properties in both major and minor coffee growing regions of Ethiopia. Thus, this research was conducted with the objective of establishing association of chemical soil properties with coffee cup quality attributes. Coffee beans as well as soil samples from which the beans originated were subjected to chemical analysis. The coffee beans and the corresponding soil samples originated from large scale coffee plantations (Bebeka, Gemadro and Goma), districts from southwestern major coffee growing region (Gore, Jimma, Lemkefa), West (Gimbi), East (Badano, Chiro, Darolebu, Habro and Melkabelo), South (Yirgacheffe) and northwestern minor coffee growing districts (Ankasha, Bure, Mecha and Jabi). The soil samples were collected from the depth of 0 - 50 cm near the coffee trunks and samples of ripe coffee cherries were picked up from the trees during the 2010/11 harvest season. Selected chemical properties of the soil, namely, available potassium, cation exchange capacity, exchangeable acidity, exchangeable bases, available micronutrients, available phosphorus, total nitrogen, soil pH, electrical conductivity, and percent organic carbon were determined from 53 soil samples in Jimma University soil laboratory and Wolkitie Soil Testing and Soil Fertility Improvement Centre using the established procedures.
    [Show full text]
  • Floristic Composition and Carbon Pools Along Altitudinal Gradient: the Case of Gara–Muktar Forest, West Hararghe Zone, Eastern Ethiopia
    Forestry Research and Engineering: International Journal Research Article Open Access Floristic composition and carbon pools along altitudinal gradient: the case of gara–muktar forest, west hararghe zone, eastern Ethiopia Abstract Volume 4 Issue 1 - 2020 Forests play vital role in combating climate change through carbon sequestration in the Asaminew Wodajo,1 Mehari A Tesfaye,2 atmosphere and serving as a carbon sink in the form of carbon pool systems of forest 3 ecosystems. The species composition and carbon stock in the different carbon pools Muktar Mohammed 1Bonga Agricultural Research Centre, Ethiopia, and analysis of the influence of the environmental gradients were studied by systematic 2Central Ethiopia Environment and Forest Research, Ethiopia sampling method collecting data in thirty-six quadrant plots of 20x20m each distributed 3Oda Bultum Universities, Ethiopia along transect lines. Diameter at breast ≥5cm and total height measured for each tree in the main plot. Above and below ground biomass was estimated using allometric equation, Correspondence: Mehari Alebachew Tesfaye, Central Ethiopia while the litter carbon was estimated by taking 50% of dry biomass as carbon. Soil sample Environment and Forest Research Centre box 30708, Addis was collected using auguring method and analyzed following Walkley-Black method, Ababa, Ethiopia, Tele +251911356756, while bulk density was performed using core sampling method. The data was analyzed Email was performed using one way ANOVA of R software. The carbon stocks in aboveground, belowground, litter biomass and soil organic carbon showed distinct variation along Received: November 27, 2020 | Published: February 28, 2020 environmental gradients. The aboveground and below ground carbon stock was showed a decreasing trend along with increasing altitude, while soil organic carbon and liter carbon showed increasing trend along with increasing in altitude.
    [Show full text]
  • 11 HS 000 ETH 013013 A4.Pdf (English)
    ETHIOPIA:Humanitarian Concern Areas Map (as of 04 February 2013) Eritrea > !ª !ª> Note: The following newly created woreda boundaries are not Tahtay !ª E available in the geo-database; hence not represented in this Nutrition Hotspot Priority Laelay Erob R R !ª Adiyabo Mereb Ahferom !ª Tahtay Gulomekeda !ª I E map regardless of their nutrition hot spot priority 1 & 2: Adiyabo Leke T D Adiyabo Adwa Saesie Dalul Priority one Asgede Tahtay R S Kafta Werei Tsaedaemba E E Priority 1: Dawa Sarar (Bale zone), Goro Dola (Guji zone), Abichu Tsimbila Maychew !ª A Humera Leke Hawzen Berahle A Niya( North Showa zone) and Burka Dintu (West Hararge Priority two > T I GR AY > Koneba Central Berahle zone) of Oromia region, Mekoy (Nuer zone) of Gambella Western Naeder Kola Ke>lete Awelallo Priority three Tselemti Adet Temben region, Kersadula and Raso (Afder zone), Ararso, Birkod, Tanqua > Enderta !ª Daror and Yo'ale (Degahabour zone), Kubi (Fik zone), Addi Tselemt Zone 2 No Priority given Arekay Abergele Southern Ab Ala Afdera Mersin (Korahe zone), Dhekasuftu and Mubarek (Liben Beyeda Saharti Erebti Debark Hintalo !ª zone), Hadigala (Shinille zone) and Daratole (Warder Abergele Samre > Megale Erebti Bidu Wejirat zone) of Somali region. Dabat Janamora > Bidu International Boundary Alaje Raya North Lay Sahla Azebo > Wegera Endamehoni > > Priority 2: Saba Boru (Guji zone) of Oromia region and Ber'ano Regional Boundary Gonder Armacho Ziquala > A FA R !ª East Sekota Raya Yalo Teru (Gode zone) and Tulu Guled (Jijiga zone) of Somali region. Ofla Kurri Belesa
    [Show full text]
  • A Behavioural Perspective Choice and Force – the Former Always Being More Resilient, Truthful and Apt for a Democratic System Like Ours
    216 Somasekhar Sundaresan The central bank, which is the regulator, placed itself in the shoes of the regulated, taking decisions that they ought to take. Such a policy change led to undermining the sovereignty of the governance mechanisms of the bank – with the supervisor and regulator taking the 27 decisions for the supervised and the regulated. The actions were still those of the bank, but the actual decision was being taken outside the bank. Lessons in regulation of conduct have been learnt and this has presented a great opportunity to learn about the core difference between The Code: A Behavioural Perspective choice and force – the former always being more resilient, truthful and apt for a democratic system like ours. Anuradha Guru1 Finally, there is still one question that remains at large – does the Code have any preference between liquidation and resolution? Many legal and judicial minds tend to take an approach that liquidation is avoidable and that one must do the most to make resolution work. There is nothing in the Code to make any expression of such a preference. The choice between “Law is defined as a task of social engineering designed to eliminate friction and waste in the resolution and liquidation is a sovereign right of the CoC. They can choose in their wisdom to satisfaction of unlimited human interests and demands out of a limited store of goods in existence.” liquidate a company once they form a view that the CD is a basket case. The SC has upheld such Roscoe Pound2 sovereignty of the CoC. ccording to Marxist theory,3 the legal system of a society constitutes one of the However, in cases where the resolution plan does go through, obviating liquidation, components of its 'superstructure' being influenced and in-turn influencing the base when there is a challenge to the terms of the resolution, the question rears its head again.
    [Show full text]
  • Running Head: SELF-SERVING ATTRIBUTIONS in SPORT
    This article is downloaded from http://researchoutput.csu.edu.au It is the paper published as: Author: L. J. Aldridge and M. Rabiul Islam Title: Cultural differences in athlete attributions for success and failure: The sports pages revisited. Journal: International Journal of Psychology ISSN: 0020-7594 Year: 2012 Volume: 47 Issue: 1 Pages: 67-75 Abstract: Self-serving biases in attribution, while found with relative consistency in research with Western samples, have rarely been found in Japanese samples typically recruited for research. However, research conducted with Japanese participants to date has tended to use forced choice and/or reactive paradigms, with school or university students, focusing mainly on academic performance or arbitrary and/or researcher-selected tasks. This archival study explored whether self-serving attributional biases would be shown in the real-life attributions for sporting performance made by elite Olympic athletes from Japan and Australia. Attributions (N = 216) were extracted from the sports pages of Japanese and Australian newspapers and rated by Australian judges for locus and controllability. It was hypothesised that Australian, but not Japanese, athletes would show self-serving biases such that they attributed wins to causes more internal and controllable than the causes to which they attributed losses. Contrary to predictions, self-serving biases were shown to at least some extent by athletes of both nationalities. Both Australian and Japanese men attributed wins to causes more internal than those to which they attributed losses. Women, however, attributed wins and losses to causes that did not differ significantly in terms of locus. All athletes tended to attribute wins to causes that were more controllable than the causes to which losses were attributed.
    [Show full text]
  • Oromia Region Administrative Map(As of 27 March 2013)
    ETHIOPIA: Oromia Region Administrative Map (as of 27 March 2013) Amhara Gundo Meskel ! Amuru Dera Kelo ! Agemsa BENISHANGUL ! Jangir Ibantu ! ! Filikilik Hidabu GUMUZ Kiremu ! ! Wara AMHARA Haro ! Obera Jarte Gosha Dire ! ! Abote ! Tsiyon Jars!o ! Ejere Limu Ayana ! Kiremu Alibo ! Jardega Hose Tulu Miki Haro ! ! Kokofe Ababo Mana Mendi ! Gebre ! Gida ! Guracha ! ! Degem AFAR ! Gelila SomHbo oro Abay ! ! Sibu Kiltu Kewo Kere ! Biriti Degem DIRE DAWA Ayana ! ! Fiche Benguwa Chomen Dobi Abuna Ali ! K! ara ! Kuyu Debre Tsige ! Toba Guduru Dedu ! Doro ! ! Achane G/Be!ret Minare Debre ! Mendida Shambu Daleti ! Libanos Weberi Abe Chulute! Jemo ! Abichuna Kombolcha West Limu Hor!o ! Meta Yaya Gota Dongoro Kombolcha Ginde Kachisi Lefo ! Muke Turi Melka Chinaksen ! Gne'a ! N!ejo Fincha!-a Kembolcha R!obi ! Adda Gulele Rafu Jarso ! ! ! Wuchale ! Nopa ! Beret Mekoda Muger ! ! Wellega Nejo ! Goro Kulubi ! ! Funyan Debeka Boji Shikute Berga Jida ! Kombolcha Kober Guto Guduru ! !Duber Water Kersa Haro Jarso ! ! Debra ! ! Bira Gudetu ! Bila Seyo Chobi Kembibit Gutu Che!lenko ! ! Welenkombi Gorfo ! ! Begi Jarso Dirmeji Gida Bila Jimma ! Ketket Mulo ! Kersa Maya Bila Gola ! ! ! Sheno ! Kobo Alem Kondole ! ! Bicho ! Deder Gursum Muklemi Hena Sibu ! Chancho Wenoda ! Mieso Doba Kurfa Maya Beg!i Deboko ! Rare Mida ! Goja Shino Inchini Sululta Aleltu Babile Jimma Mulo ! Meta Guliso Golo Sire Hunde! Deder Chele ! Tobi Lalo ! Mekenejo Bitile ! Kegn Aleltu ! Tulo ! Harawacha ! ! ! ! Rob G! obu Genete ! Ifata Jeldu Lafto Girawa ! Gawo Inango ! Sendafa Mieso Hirna
    [Show full text]
  • Risk Map Assessment
    Risk Map Assessment A Socio-Economic Study on Vulnerable Children and Adolescents In West Hararge Zone Chiro and Gemechis Woredas Comitato Internazionale per lo Sviluppo dei Popoli (CISP) (International Committee for the Development of Peoples) In the framework of the Italian Cooperation Programme in support of vulnerable children and adolescents in Ethiopia Research Team Desta Ayode Azmeraw Belay Mekdes G/Tinsaye Addis Ababa, June 2006 Risk Map Assessment Table of content Page Acknowledgement ----------------------------------------------------------- i List of Acronyms ------------------------------------------------------------ ii List of Tables and Charts --------------------------------------------------- iii Executive Summary --------------------------------------------------------- 1 Part One; Background ---------------------------------------------- 4 1.1 Introduction------------------------------------------------------------------ 4 1.2 Policy and Legal Framework----------------------------------------------- 5 1.3 Background of the Study--------------------------------------------------- 6 1.4 Objectives of the Study---------------------------------------------- ------ 6 1.5 Overview of the Study Area----------------------------------------- ------ 7 1.6 Structure of the Report----------------------------------------------------- 8 Part Two: Methodology------------------------------------------- 9 2.1 Instruments-------------------------------------------------------------------- 9 2.2 Selection of the Study Sites-------------------------------------------------
    [Show full text]
  • Evaluation of Improved Napier Cultivars As Livestock Feed Under Farmers Conditions in West Hararghe Zone, Oromia Region, Ethiopia
    Animal and Veterinary Sciences 2021; 9(1): 5-15 http://www.sciencepublishinggroup.com/j/avs doi: 10.11648/j.avs.20210901.12 ISSN: 2328-5842 (Print); ISSN: 2328-5850 (Online) Evaluation of Improved Napier Cultivars as Livestock Feed Under Farmers Conditions in West Hararghe Zone, Oromia Region, Ethiopia Tamrat Dinkale1, *, Tessema Zewdu2, Meseret Girma2 1Oromia Agricultural Research Institute, Mechara Agricultural Research Center, Mechara, Ethiopia 2Department of Animal Sciences and Range, Haramaya University, Dire Dewa, Ethiopia Email address: *Corresponding author To cite this article: Tamrat Dinkale, Tessema Zewdu, Meseret Girma. Evaluation of Improved Napier Cultivars as Livestock Feed Under Farmers Conditions in West Hararghe Zone, Oromia Region, Ethiopia. Animal and Veterinary Sciences. Vol. 9, No. 1, 2021, pp. 5-15. doi: 10.11648/j.avs.20210901.12 Received: November 6, 2020; Accepted: December 16, 2020; Published: January 30, 2021 Abstract: This study was conducted to evaluate the forage production and farmers preference as livestock feed under farmer’s conditions in West Hararghe Zone of Oromia region, Ethiopia. Four improved Napier grass cultivars (ILRI cultivar number: 16801, 16800, 16798, and 16840) and local check were planted in a Randomized Complete Block Design (RCBD) with six replications during the main cropping season of 2018/19. The dry matter (DM) yield, fresh biomass yield, plant height, leaf length and leaf-stem ratio and other agronomic data were measured at harvest. Farmers preference of the Napier grass cultivars as livestock feed was collected through visual and hand evaluation of the multiple ranking criteria of the cultivars based on phonological nature. The results shows that, ILRI cultivar no.
    [Show full text]
  • Partial List of Mass Execution of Oromos and Other Nation And
    Udenrigsudvalget 2013-14 URU Alm.del Bilag 174 Offentligt Partial list of Mass execution of Oromos and other nation and nationalities of Ethiopia (Documented by Oromo Liberation Front Information and Research Unit, March 2014) Injustice anywhere is injustice everywhere!!! Ethiopia is one of the Countries at Genocide Risk in accordance with Genocide Watch’s Report released on March 12, 2013. •Genocide Watch considers Ethiopia to have already reached Stage 7, genocidal massacres, against many of its peoples, including the Anuak, Ogadeni, Oromo and Omo tribes. •We recommend that the United States government immediately cease all military assistance to the Ethiopian Peoples Defense Forces. We also recommend strong diplomatic protests to the Meles Zenawi regime against massive violations of human rights in Ethiopia Article 281 of the Ethiopian Penal Code : Genocide; Crimes against Humanity Whosoever, with intent to destroy, in whole or in part, a national, ethnic, racial, religious or political group, organizes, orders or engages in, be it in time of war or in time of peace: (a) killings, bodily harm or serious injury to the physical or mental health of members of the group, in any way whatsoever; or (b) measures to prevent the propagation or continued survival of its members or their progeny; or (c) the compulsory movement or dispersion of peoples or children, or their placing under living conditions calculated to result in their death or disappearance, is punishable with rigorous imprisonment from five years to life, or, in cases of exceptional
    [Show full text]
  • Ethiopia Humanitarian Situation Report
    UNICEF ETHIOPIA HUMANITARIAN SITUATION REPORT ETHIOPIA Humanitarian Situation Report SitRep # 5 - Reporting Period May 2019 SITUATION IN NUMBERS Highlights 4.89 million # of children in need of humanitarian Failed spring rains this year in parts of Afar, Amhara, Oromia and Somali regions have renewed concerns about another drought affecting children, assistance (Ethiopia Humanitarian Needs Overview 2019) further compounding vulnerabilities in regions already suffering from chronic food insecurity, prolonged and complex population displacements, and increased risks to outbreaks of cholera and measles. These regions 8.86 million also have over-stretched health care systems, poor access to water, and # of people in need recurrent outbreaks of preventable diseases. (Ethiopia Humanitarian Needs Overview 2019) As of April 2019, UNICEF has supported the screening and admission of 110,826 children under the age of five for severe acute malnutrition (SAM) 3.19 million treatment and the numbers are expected to grow with the projected Internally displaced persons in Ethiopia drought in the country. (Ethiopia Humanitarian Needs Overview 2019) UNICEF Ethiopia urgently requires US$ 5.4 million to replenish its nutrition commodities pipeline for the expected surge in severe acute malnutrition 919,938 (SAM) in 2019. In addition, US$ 2.45 million is required to rehabilitate 35 Registered refugees and asylum seekers in water schemes and provide durable safe water and sanitation for the most Ethiopia vulnerable children, including displaced children,
    [Show full text]
  • Pastoral Areas Nutrition Update Transportation
    Food and Livelihood Security Update – Pastoral Areas The latest update by the Somali Region Disaster Prevention and Preparedness Bureau (DPPB) and Save the Children UK reports a slight improvement in the food security situation in the region due to good performance of the deyr rains, increased demand for livestock exports and ongoing relief food distributions. The terms of trade for pastoralists have improved in all major markets (Jijiga, Fik and Kebridehar) due to increased livestock demand from Gulf countries ahead of the upcoming Muslim holy pilgrimage (Haj). The deyr rains have also significantly replenished water sources in Gode, Afder, Liben, Degehabur and Fik zones, bringing emergency water tankering interventions to an end. In Korahe, Warder and parts of Shinile zones, however, serious water shortages persist. In Afar, the latest DPPB/Save the Children UK report recommends close monitoring of the food security situation in the region due to the recurrent dry spells and absence of recovery periods between them, which have exhausted the coping strategies of the pastoralist population. Livestock herd sizes, the number of milking animals and productivity have been significantly reduced, especially in terms of cattle. The report further indicates that the terms of trade for pastoralists have not improved due to low livestock prices and increased cereal prices. A joint Government and NGO rapid assessment conducted in Borena zone (Oromia) from 24 to 27 October has found the food and nutritional security of communities in all woredas to be of concern due to the poor performance of the current hagaya rains, coming on top of the previous poor ganna (mid-March to May) harvest.
    [Show full text]