Review of economic and livelihood benefits for ASAP ... · Review of economic and livelihood...

Review of economic and livelihood benefits for ASAP-supported investments

IFAD Technical Report

Keyword: Evaluation, Economic Development, Climate Change, Economics

JEL: O. Economic Development, Innovation, Technological Change, and Growth -> O1 Economic

Development -> O13 Agriculture • Natural Resources • Energy • Environment • Other Primary

Products

AUTHORS (alphabetical order):

Ferrarese C.1, Mazzoli E.2, Rinaldi R.3, 2016. Review of economic and livelihood benefits for ASAP-

supported investments. IFAD Publications, Rome, Italy.

© 2016 by the International Fund for Agricultural Development (IFAD)

The opinions expressed in this document are those of the authors and do not necessarily represent

those of the International Fund for Agricultural Development (IFAD). The designations employed

and the presentation of material in this article do not imply the expression of any opinion

whatsoever on the part of IFAD concerning the legal status of any country, territory, city or area or

of its authorities, or concerning the delimitation of its frontiers or boundaries.

This publication or any part thereof may be reproduced without prior permission from IFAD,

provided that the publication or extract therefrom reproduced is attributed to IFAD and the title of

this publication is stated in any publication and that a copy thereof is sent to IFAD.

1 OpenEconomics - Independent Consultant- corresponding author [email protected] 2 IFAD - Economic and Financial Analysis Specialist 3 Stockholm Environment Institute (Associate) - Junior Researcher


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Abbreviations

ASAP Adaptation for Smallholder Agriculture Programme

BCR Benefit-cost ratio

BT Benefit Transfer

CC Climate Change

CV Contingent Valuation

DfID Department for International Development

ECD Environment and Climate Change Division

EFA Economic and Financial Analysis

EIRR Economic Internal Rate of Return

EV Environmental Valuation

GDP Gross Domestic Product

IFAD International Fund for Agricultural Development

IPCC Intergovernmental Panel on Climate Change

NPV Net Present Value

ODI Overseas Development Institute

PDR Project Design Report

PTA Policy and Technical Advisory Division

VfM Value for Money


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Abstract

In the process of gathering numerical evidences about the economic, social and environmental

benefits induced by the Adaptation for Smallholder Agriculture Programme (ASAP), this work

proposes a technical and empirical review of 32 approved projects under the ASAP. Results are

integrated in the light of data gaps emerged from the original database, especially regarding the

assessment of environmental benefits.

ASAP financing guarantees an average return of $1.77 per dollar invested. Supporting evidences

came also from the analysis of the Economic Internal Rates of Return (EIRR), which reveals that

mean EIRR in each of the IFAD regions ranges between 15% and 35%. At global level, the analysis

suggests that climate change adaptation strategies contribute to GDP growth for about 22% of the

GDP total value that translates in a yearly growth by 1.2%. Expected outcomes vis-à-vis pre-

identified risks and climate variability measured running a Monte Carlo simulations are proved to

remain positive in most of the countries, with few exceptions were climate variability has bigger

effect on final results.

The conclusive part of this study suggests an extension in the scope of the analysis through minor

investments in primary data collection to validate and consolidate technical and empirical reviews.


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Introduction

Since the inception of the Adaptation for Smallholder Agriculture Programme (ASAP) in

September 2012, a total of 36 ASAP-supported projects were approved by the IFAD Executive

Board, committing 100% of its approved finance on supporting the adaptation of poor smallholder

farmers to climate change4 (CC). Currently 15 of these projects have been implemented, disbursing

their first batches of financing and delivering intermediate results5.

An external Progress Review by the Overseas Development Institute (ODI)6 to evaluate the status

of ASAP found that ASAP’s impact has been strong in two areas. Firstly, the internal policy and

project design process within IFAD raised awareness and provided the basis for thorough

mainstreaming of climate change and a more structured approach to integrate the concept of

'resilience' in IFAD investment designs. Secondly, ASAP has created a strong internationally-

recognised brand on climate adaptation for rural smallholder farmers, combining IFAD’s existing

credibility on agriculture with strategic partnerships involving international institutions leading on

climate change in this field.

IFAD and DfID in the UK are now interested to gathering numerical evidences about the economic,

social and environmental benefits leveraged via ASAP projects. While data and partial assessments

are already available in individual project Economic and Financial Analysis (EFA), there seems to

be a lack in reporting expected returns per US dollar spent from the ASAP while providing an

overview of the benefits at country and regional level.

This work proposes, therefore, a review of economic and livelihood benefits for ASAP-supported

investments. This study makes use of the larger sample of ASAP-supported projects, so as to gather

evidences about the quantifiable economic returns and the value for money of the ASAP

programme at a broader global scale. The study also attempts to shed lights on the net incremental

benefits generated at farm/household level, so as on the indirect benefits imputable to ASAP at

different scales (job creation, impact on GDP, second-tier effects). Final results will be then tested

via sensitivity and risk analysis, in order to account for the long-term global outlook on CC.

The approach can be described in five steps as follows:

4 Norman (2015) Food and livelihoods in a changing climate: the role of climate finance for agriculture. 5 Laganda (2016) ASAP Quarterly Newsletter - April 2016. 6 ODI (2015) Adaptation for Smallholder Agriculture Programme (ASAP) - Progress Review.


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I. Formalisation of theoretical concepts. The team identifies and, subsequently, categorises the

socio-economic and environmental benefits pertaining the study database. The screening

criteria to filter the starting sample into smaller samples of ASAP projects are described in

the next chapter.

II. Preliminary review of benefits and costs. Using project design reports and EFA annexes, the

team will extract necessary context information and data to encode (i.e. to collect and store)

costs and benefit details for the initial study sample of the ASAP projects so far approved

into a comprehensive database. A preliminary analysis of those benefits and costs will

measure: i) the value for money of ASAP investments; ii) economic returns on 1 USD dollar

spent on ASAP; iii) macroeconomic impacts and indirect effects of climate change

adaptation strategies; iv) expected outcomes vis-à-vis pre-identified risks and climate

variability.

III. Integrated benefits appraisal. In order to integrate likely data gaps - especially on the

monetary evaluation of environmental benefits - the team will apply Benefit Transfer

technique for a selected number of ASAP project (sample II);

IV. Comprehensive and reviewed benefits appraisal. A mini-Systematic review is performed to

complement benefits data gaps using the most appropriate techniques and values to be

applied for such evaluation.

Figure 1: Diagram of the study

Formalisation of theoretical

concepts

Main Database

(sample I) Preliminary

data analysis

Systematic review

Data collection (EFA documents)

Sub-sample

(sample II)

Reviewed

expected benefits

analysis

Initial expected

benefits appraisal

Zero draft

VS.

I

II


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This report will collect and present all the findings developed throughout the above-depicted

activities, describing the review exercise undertaken and presenting the economic and livelihood

benefits achieved through ASAP-supported investments in the considered samples.

Chapter 1: Formalisation of theoretical concepts

Prior to collecting data and the analysis of this work, it is necessary to clarify some of the

terminology and the methodology that is going to be used in this work.

Firstly, we need to explain what do we mean by “socio-economic” and “environmental” benefits.

The former consists in the impacts that a rural development project has on community, social and

economic well-being, which can be expressed not only in quantitative7 but also qualitative terms8.

The latter consists of positive or mitigating consequences that result from the implementation of

activities within each component of the IFAD projects. Similarly to socio-economic benefits, also

environmental benefits can be usually observed at design stage but are seldom reported or

quantified in monetary terms.

To this purpose, this work will attempt to provide a more accurate estimation of the benefits

deriving from ASAP-supported investment, integrating the existing data gap on socio-economic and

environmental benefits emerged after a preliminary review of projects implemented with an ASAP

component. The focus is specifically on the quantification of environmental benefits sometimes re-

assessed using the most appropriate techniques and tools, so as to provide an economic value to

environmental amenities also called Environmental Valuation9.

Finally, it is worth noting that the information collected to undertake the review of ASAP-supported

projects was gathered by analysing the Project Design Documents (PDRs) in their final version, as

well as annexes, Working Papers and EFA calculation spreadsheets of each programme. In case of

discrepancies and heterogeneous values across different versions of documents, preference has been

given to the latest version of the PDR that has been approved for implementation.

7 Edwards (2000) provides as examples changes in community demographics, housing, employment and income,

market effects, public services, and aesthetic qualities of the community. Other examples in Zeppel (2006), Feldmann

(2005), IFAD (2012). 8 In the documentation that we consulted for this work, also the words ‘quantifiable’ and ‘unquantifiable’ are also used

to indicate these two concepts. 9 Environmental Evaluation of a programme or a project corresponds to the process of estimating and evaluating short-

term and long-term impacts at a significant scale on the environment where the project is implemented. This differs

from the concept of Environmental Valuation used in this work which is the process of allocating on environmental

goods and services a monetary value due to a lack of easily observable market prices (Dixon, 2008).


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Description of samples

Sample I

The starting sample (Sample I) is formed by ASAP-supported projects that have been approved

and/or implemented within the last six years (2010-2015). The lack of data for four ASAP-

supported projects have reduced the initial sample size of 36 projects to 3210. Using PDRs and EFA

annexes, the team extracted necessary context information and data to encode (i.e. to collect and

store) into a comprehensive database that constitutes Sample I. This database collects socio-

economic and environmental benefits assessed at the design stage on a yearly basis and per

component discounted to the 2015 USD value; both for the project and for the ASAP financed part

of the project.

As per its mandate, IFAD operates in the rural areas of low-income countries, engaging with

farmers living in very different environmental, socioeconomic and cultural contexts. Jointly with

the ASAP, IFAD has intervened in the following regions: Asia and the Pacific (APR), East and

Southern Africa (ESA), Latin America and the Caribbean (LAC), Near East and North Africa

(NEN), and West Central Africa (WCA). In the stratification of the projects sample used for this

work, we preserved this geographical diversity also to allow any conclusion to not being distorted

by possible regional peculiarities (countries in green - Figure 2).

Figure 2: Geographical distribution of projects and programmes approved with ASAP component

10 See Annex I for the full list of projects with title, as well as country and region of the intervention.


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Despite on average each region is represented equally, Table 1 and Figure 3 show that the highest

number of projects are implemented in the ESA and WCA region (25%), while NEN region follows

with 19% and finally APR and LAC region (16%)11.

Figure 3: Percentage of the geographic distribution of the IFAD/ASAP-supported investments

included in sample I

Similarly, the distribution of ASAP financial allocation in projects reviewed ranges from $32.1

million (13%) of the LAC region to the $63.9 million (26%) of the WCA region, as shown in the

table below.

Table 1: Financial contribution by region (2010 - 2015) - Sample I

Region Total contribution of projects with

ASAP component (2015 USD)

ASAP financial allocation in projects

reviewed (2015 USD)

APR $189,958,728 $52,016,121

ESA $632,346,000 $61,831,425

NEN $327,781,783 $34,999,520

WCA $615,990,900 $63,943,750

LAC $175,503,341 $32,128,823

Total $1,941,580,752 $244,919,639

We have also collected information regarding the number of smallholders directly impacted by

projects activities that have an ASAP component, and number of people who directly benefit of

project activities. ASAP-supported investments have benefitted more than 8.5 million people, with

11 The exact figures are WCA and ESA 25.0%, NEN 18.8% and 15.6% for LAC and APR regions. Rounding of values

explains the slight discrepancy in percentages of Figure 3.


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almost three million beneficiaries in the WCA region, and more than 1.4 million in the ESA, APR

and NEN regions; while about six per cent of the direct beneficiaries in the LAC region (Table 2).

Table 2: Beneficiaries by region (2010 - 2015) - Sample I

Region Smallholders directly impacted

by project activities Direct beneficiaries of projects

APR 468 695 1 600 300

ESA 376 450 1 987 834

NEN 271 400 1 486 900

WCA 496 007 2 980 962

LAC 120 300 477 200

Total 1 732 852 8 533 194

In terms of projects’ implementation, it is interesting to note that 91 % of them have an

implementation period between five to seven years. As many as 41 % have a seven years

implementation period and no one is above nine years. The total life period considered in projects’

EFAs is usually ten or twenty years. In our samples 78% has a 20-year term, while 13% of only ten

years. Only three per cent of the projects is analysed with a time horizon of 30 years.

Sample II

As explained in the introductory chapter, for a selected number of ASAP projects (Sample II) the

team undertook an Environmental Valuation exercise in order to assess missing benefits. In

reviewing the calculation of benefits sourced in the final design reports and EFA annexes, we have

identified a pool of potential candidates to constitute Sample II. Based on project selection criteria,

a total of ten projects are filtered out to form Sample II. Similarly to Sample I, the geographical

representation is equally distributed across IFAD regions. Two countries per each working region

have been selected to be part of the sample. The full list of these projects is available in Annex II.

Table 3: Financial contribution by region (2010 - 2015) - Sample II

Region Total contribution of projects with

ASAP component (2015 USD)

ASAP financial allocation in projects

reviewed (2015 USD)

APR $56,496,200 $19,999,000

ESA $181,000,000 $16,000,000

NEN $52,839,444 $15,995,520

WCA $174,900,000 $16,994,750

LAC $82,678,000 $18,000,108

Total $547,913,444 $86,989,378


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Table 4: Beneficiaries by region (2010 - 2015) - Sample II

Region Smallholders directly impacted

by project activities

Direct beneficiaries of projects

APR 157 700 630 000

ESA 157 000 942 000

NEN 110 300 755 300

WCA 149 000 783 000

LAC 72 000 344 000

Total 644 000 3 454 300

Chapter 2: Preliminary review of benefits and costs

The results of the analysis conducted using Sample I database are presented in the following

sections. Firstly, we comment on the Value for Money (VfM) of the ASAP-supported investments

through the appraisal of benefit-cost ratios (BCR), Net Present Values (NPV) and Economic

Internal Rate of Return (EIRR). It follows an investigation about the macroeconomic impacts and

indirect effects of climate change adaptation strategies. A sensitivity analysis on expected outcomes

vis-à-vis pre-identified risks and climate variability concludes the preliminary review.

2.1. Value for money on ASAP-supported investments

Four elements can define the VfM of an investment: Economy, Efficiency, Effectiveness and

Equity. Economy implicates that inputs are at sufficient quality and appropriate cost. ‘How well’

inputs are converted into outputs is the efficiency; while effectiveness relates to ‘how well’ outputs

achieve a desired outcome (Barr and Christie, 2015; Jayasuriya, 2013). Many development agencies

and organisation include some or all of these elements in their definition in applying the VfM

concept to their work. Under this work, the DfID approach to VfM is adopted. Based on the first

three Es, but with the need to include Equity considerations throughout, VfM is “about maximising

the impact of each £ spent to improve poor people’s lives” (DfID, 2011 - pp. 2).

2.1.1. Benefit to Cost Ratio (BCR)

A first method identified to evaluate VfM of ASAP contribution, applying DfID definition, is the

BCR of ASAP-supported investments. BCR is a synthetic evaluation criterion of the acceptability


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and - under specific and limited circumstances - preferability of a project12. The indicator is

calculated as the ratio of project benefits over project costs13. According to this criterion, a project is

worth the investment when BCR is greater than one.

This ratio owns some operational advantages and disadvantages to be taken into consideration.

Indeed, its application has a relevant inconvenience due to the high sensitivity of results to the cost

and benefit values included in the assessment of the ratio and it cannot be used as for the ranking of

projects. On a brighter note though, it would provide an initial idea about project feasibility and a

robust proxy measure of the returns generated by each dollar invested in the project. Hence, this

indicator is used so as to determine value contribution of ASAP component to the overall project

value.

Results of the BCR analysis are presented in Figure 4. As shown in the leftward box-plot, for a

dollar spent in a project or programme that has an ASAP component, expected benefits will be

$1.59 and on average equals to $2.06; with a minimum BCR of $ 1.05, and maximum of $ 6.53 and

$ 6.49. Therefore, for every dollar invested in IFAD programmes, a net worth of $ 0.59 to $ 1.06

on average is generated and redistributed to project beneficiaries. Two of the ratios above 6.0

dollars – respectively calculated in the Bolivia14 and Nicaragua15 project - were considered outlier

and therefore excluded by the box plot16. On the right side of the graph, the BCR for each ASAP

component are represented as single entries as well as grouped in the box plot.

For ASAP alone, the median and average values are equal to $ 1.76 and $ 2.26 respectively, with

minimum value being $ 1.05 and maximum $ 7.21. The latter – as in the previous case – has been

considered as extreme value. The BCR review of the 32 ASAP-supported investments suggests

that investments are worth the costs and ASAP components slightly outperform the overall

investment in terms of worth generation and redistribution capacity.

12 See Hanley (1993) for more information. 13 This indicator should be calculated using the present values of both benefits and costs, discounted at an appropriate

discount rate. This indicator should be used jointly with others as, when used alone, it may give incorrect ranking

among independent projects and cannot be used for choosing among mutually exclusive alternatives. 14 ACCESSOS programme 15 Adapting to Markets and Climate Change Programme 16 Standard Deviation = 1.28; Variance = 1.64; Standard Error = 0.23.


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Figure 4: BCR for Sample I17

As already partially emerged in the description of results, the aggregation of BCR does not come

without bias, such as the geographical distribution and the nature of values considered for the

analysis. Indeed, the assessment of benefits, especially the environmental ones, does not apply a

standardised methodology across the several programmes hence the comparison across

programmes, countries and regions could not be considered as technically valid. This is partially the

explanation of the existence of extreme values, which can also be explained with the challenge in

monetising those ASAP-related impacts such as capacity building, inclusion of climate change

adaptation strategies in the local and national institutions where the projects and programmes are

implemented, the increased awareness of climate change impacts on local communities, etc.

However, this exercise allowed us to conclude that ASAP components are expected to provide

benefits up to seven times the amount of costs, with the majority of those (first to third quartile)

ranging from $1.44 to $2.63 with an average BCR of $2.26. For every dollar spent in ASAP

actions, the net worth redistributed to each project beneficiary ranges from $ 0.44 to $ 1.63.

Figure 5: BCR for ASAP components (yellow) and BCR for overall programmes (green)

17 Distribution of all points is shown on the left, while right hand scatter plot does not include extreme points.


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A regional representation of results, such as in Figure 6, provides a more detailed overview of the

VfM that each area of intervention can offer. Using as reference the ratios presented in the previous

figure, this chart denotes the same results

but with a regional view.

The LAC region in green shows values

that span from a BCR of $1.45 in the

Ecuador ASAP component to the $7.21 in

Nicaragua. The region in blue (NEN)

collects ratios between the $1.32 of

Djibouti to the Morocco’s project $2.27.

In the bottom left of the chart, the WCA

regional ratios are collected with figures

stretching from the Ivory Coast $1.25 to

the $4.14 of Liberia. The APR region is

represented in the bottom centre of the

chart with the BCR of the analysed countries scoping from $1.47 in Nepal to the $4.59 observed in

Cambodia. Finally, in the right-corner Rwanda $1.05 and Tanzanian $3.68 tidemark the BCRs of

the ESA region.

2.1.2. Net Present Value

Another key indicator for the assessment of the VfM of the ASAP-supported investments consists

of the Net Present Value (NPV) of socio-economic and environmental benefits, net of the project or

programme economic costs. The NPV is a profitability indicator, which synthesizes the net project

worth generated once all operating inputs and production factors have been repaid. The project

would be worth the investment when the NPV is greater than zero.

Similarly to the previous section, Figure 7 shows in a box-plot the range of values that characterises

the sample of 32 projects that include an ASAP component.

Figure 6: BCR for ASAP components divided by regions


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Figure 7: Box plot with NPV of ASAP benefits and costs in 2015 USD18

The average NPV of the benefits in the sample is of $ 12.7 million with first and third quartile equal

to $ 5.7 million and $ 16.1 million. These values are higher than what shown on the right side box

plot collecting the NPV of ASAP component’s costs that averages to $ 5.9 million, with first and

third quartile being equal to $ 3.3 and $ 6.2 million respectively. In other words, ASAP components

completely offset their costs and still contribute to value generation for about $ 6.8 million on

average.

2.2. Economic returns on ASAP-supported investments

Another profitability indicator used to measure project worth is the Economic Internal Rate of

Return (EIRR). Typically the internal rate of return is the interest rate (or opportunity cost of

capital) that would reduce to zero the net cash flows of the project. A project is worth the

investment when its EIRR is greater than the cost of capital.

Figure 8 shows the results in terms of EIRR re-calculated in our sample I. These results are based

on a new elaboration of original EFA using a standard base year (2015) for all projects. In 25% of

the cases the EIRR is three times greater than the discount rate. These results also depend on the

inclusion in the ASAP activities of all, or most, project beneficiaries.

18 Distribution of all points is shown on the left, while right hand scatter plot does not include extreme points.


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Figure 8: EIRR for countries with ASAP component against the average discount rate (10%)19

Aggregating projects by the main five regions where IFAD operates, the EIRR values obtained are

always higher than the average value of the discount rate equals to 10%20 (Figure 9).

Figure 9: EIRR average values by region

19 Benin not included. 20 Discount rates used in the analysis ranged between 4.3% and 12.7%


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ESA and APR regions present the best average results, having EIRR values greater than 30%. The

lowest aggregate result is observed in the NEN region; however this remains well above the

discount rate threshold.

2.3. Macroeconomic impacts and indirect effects of climate change adaptation strategies

To measure programmes impacts on a larger scale, and to frame their effects within the

macroeconomic context of the several countries under analysis, we have also analysed the ratio

between costs and benefits in relation to the changes in the GDP of the area of intervention

following the implementation of such ASAP-supported actions. The rationale of such assessment

stands in the fact that countries with ASAP-supported interventions are enlisted in the second half

of the World ranking in terms of GDP per-capita; with eight out of the thirty-two countries21

actually positioned in the last percentile of the GDP ranking22. In particular, Ecuador can be

considered as the wealthiest country within the sample in terms of per-capita GDP ranking 101th,

while Malawi is positioned at the bottom (ranked 190th).

The value of GDP in the programme area has been estimated as the per-capita GDP23 multiplied by

the number of direct beneficiaries for the project. This value is compared against project economic

costs actualised to 2015 USD amounts, ASAP economic costs and the socio-economic benefits

(further split into Socio-economic benefits, ASAP socio-economic benefits and Total Benefits).

Only eight projects out of the entire sample have included environmental benefits in the analysis

and those few have been attributed to ASAP programme.

Figure 10 depicts the contribution of each cost/benefit category to the regional GDP. The latter has

been computed taking into consideration rural livelihoods and poverty aspects of IFAD’s target

groups. Final results represent aggregate figures to be considered over the lifetime of the investment

(i.e. 15-20 years).

The assessment proves IFAD programme to induce changes at macroeconomic level, therefore

contributing to GDP growth in all five regions. Total effects tend to be more pronounced in the

WCA region where yet a larger envelope has been invested over the last five years. Less

pronounced effects – yet positive – are witness in the APR region where total investments costs

have been reasonably lower than elsewhere. Nonetheless, investment net contribution to GDP

growth ranges between 25% and 48%, reaching up a net yearly contribution of 1.2% - 2.4%. As for

the impacts attributable to ASAP, the APR region shows a higher leverage capacity with respect to

21 Gambia, Liberia, Madagascar, Malawi, Mozambique, Niger, Rwanda, Uganda 22 Source: http://unstats.un.org/unsd/snaama/dnllist.asp 23 Ibid.

http://unstats.un.org/unsd/snaama/dnllist.asp


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other regions. The ASAP programme makes up 3% to 10% of the total GDP generable over 20

years and contributes to wealth generation for about 0.2% to 0.5% annually.

Figure 10: Project and ASAP costs and benefits as percentage of the GDP in the region

Figure 11 is a country-by-country elaboration of the regional results just presented. The graph

shows that ASAP net contribution to GDP growth is overall largely positive. On average ASAP

contributes to countries’ GDP growth for about 7% of its total value, with an average annual

impact of roughly 0.3%. Despite overall positive results, it is worth noticing that countries

registering lower values often lacked of numerical evidences about ASAP expected benefits or

environmental benefits directly attributable to ASAP.

Figure 11: ASAP contribution to GDP growth


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2.4. Expected outcomes vis-à-vis ASAP pre-identified risks and climate variability

When estimating the expected outcomes deriving from the successful implementation of projects or

programmes with an ASAP component, it is necessary to take into consideration internal risks

linked to the technical implementation of interventions, or external factors such as the climate

variability. It is, therefore, necessary to evaluate effects that such risks and climate variability can

potentially have on the expected outcomes.

To this purpose, in order to factor in climate change externalities, we estimated changes in yields

and fall in benefits accordingly to likelihood of occurrence and variation in crop production under

long-term CC scenarios for each region. Source of scenarios is the report by IPCC Working Group

II: Impacts, Adaptation and Vulnerability24. Using the IPCC scenarios described in the box below,

we estimated for each region a probability distribution function and key parameters - i.e. mean and

standard deviation - to be linked to the socio-economic benefits expected by the programme.

Box 1: Regional simulation assumptions used for the analysis

● Sub Saharan Africa: Production benefit are linked to a normal distribution

function with mean equal to base scenario and standard deviation equal to 40% of

mean;

● North Africa: Production benefit related to a normal distribution function with

mean equal to base scenario and standard deviation equal to 35% of mean,

truncated at right of mean value;

● Asia: production benefit with a normal distribution with mean equal to base

scenario and standard deviation equal to 31% of mean, truncated at right of mean

value;

● Central and South America Production benefit with a normal distribution function

with mean equal to base scenario and standard deviation equal to 27% of mean,

truncated at right of mean value

Project impacts were assessed using the Monte Carlo simulation analysis25, which is a particularly

useful method for the enhancement of analysis’ robustness and reliability when facing uncertainty

around key project variables. In particular, uncertainty may hinge upon project estimates – caused

by a lack of reliable data regarding benefits and costs estimation – or more generally around the

24 See the report: http://www.ipcc.ch/ipccreports/tar/wg2/index.htm

25 Monte Carlo analysis technique consists in a randomization of key project variables accordingly to probability

functions attached to these variables. Through a mathematical algorithm, project outcomes are presented as a

distribution of possible results within a defined range of values.

http://www.ipcc.ch/ipccreports/tar/wg2/index.htm


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existence of externalities and intangible effects (climate variability, carbon emission, pollution, etc.)

somewhat disregarded from the EFA.

A probability function based on the most probable value has been assumed for each of the variables

that are deemed to be critically important for the outcomes of the project and/or for different

combinations of such variables. Monte Carlo simulation would then allow for interaction and

randomization of these variable until defining a range of plausible values associated to the level of

probability to which the estimate is accurate (confidence level). The analysis is carried out

analysing the EIRR of ASAP component.

The following figures (Figure 12 to Figure 16) show set of EIRR values of the ASAP components

and their likelihood of occurrence, once allowing for changes in main variables and the climate

scenario.

WCA region presents positive and robust results with the set of EIRR values all above the discount

rate of 10%. The base case value for

the EIRR is 28% while the mean value

would attain 16%. The probability for

the rate of return of falling below 14%

is minimal as the 90% of probability

the EIRR would range between 14.8%

and 17.4%.

In APR region the base case value of the EIRR is 35%. After the simulation, this value would get to

a mean value of 26% and it is not

expected to exceed 23% or 29%,

respectively the minimum and

maximum values within likely

outcomes. Results in the region are

therefore proved to be resilient to key

changes among project variables.

Figure 12: ASAP expected EIRR for the WCA region

Figure 13: ASAP expected EIRR in APR region


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In the ESA region, the base case value of EIRR is 32%. Once allowing for climate change

variability, hence decrease in yields and

productivity, the EIRR would fall to an

average value of 22%. Further, under no

circumstances final results are going to

be affected negatively by the changing

climate scenario, as also proven by the

threshold values of 18% and 26%,

respectively the minimum and maximum

outcomes experienced during the trials.

Slightly lower and still positive are results from the LAC region. The average expected EIRR is

23% but under climate change

simulations the mean value decreased

to 16%, with a lowest set to 13%.

Under the latter case, the mean value

despite being very close, it is still

above the threshold discount rate

(10%).

Finally, in the NEN region the base value of EIRR is 18%. Under the Monte Carlo simulation test

the mean value of the rate of return decreases

to 11%. Only in this region a change in key

variables and the internalisation of climate

variability and risks would result in an EIRR

equal to 9%, hence lower than the discount rate.

Figure 14: ASAP expected EIRR in the ESA region

Figure 15: ASAP expected EIRR in the LAC region

Figure 16: ASAP expected EIRR in the NEN region


- 20 -

An overview of Monte Carlo simulation results is provided in the following figure and table.

Figure 17: EIRR values, extremes and variability by region

For each region, the table below presents the base EIRR as well as mean, minimum and maximum

values, with 90% confidence interval shown in the last column on the right.

Table 5: Summary of Monte Carlo simulation results

Region Base EIRR (%) Mean EIRR (%) Min. EIRR

(%) Max EIRR (%) 90% confidence interval

WCA 28 16 13 19 14.8 – 17.4

APR 35 26 23 29 24.4 – 27.1

ESA 32 22 18 26 20.3 – 23.3

LAC 23 16 13 18 14.8 – 16.7

NEN 18 11 9 13 10.5 – 11.5


- 21 -

Chapter 3: Mini-systematic review to complement data

The data extrapolation process, necessary for the creation of the database used to undertake the

analysis results presented in the previous chapter, revealed the existence of so-called data gaps in

the estimation of benefits - mostly the environmental ones. To address this gap, a smaller sample

(Sample II) composed by ten projects, two from each IFAD region, have been selected. For each of

them, we identified the potential socio-economic and environmental benefits that could be

estimated in addition to those already assessed at the project design stage within the economic and

financial analysis (Table 6)

Table 6: Benefits estimated for Sample II to integrate the ASAP review database

Country IFAD Environmental benefits estimated Benefits not estimated in this review

Bolivia LAC (i) Implementation of activities specifically related to CC

adaptation such as soil conservation / water savings that

improve agricultural production locally. (ii) Harvest loss

reduction of loss due to climatic natural disasters through

EWS (iii) reduction in the fuelwood consumption by households

Empowering of households and other local

people involved in ASAP participatory

consultations and reference studies

Djibouti NEN Preservation of biodiversity especially marine species -

Ghana WCA Economic value of more efficient water use in water

management schemes, also in commercial value chains

-

Ivory Coast WCA (i) Reforestation; (ii) Adapting cultivation techniques to soil

degradation levels

-

Kenya ESA Environmental protection due to soil, water and environment conservation technologies

Social benefits in terms of food security and nutrition at the household scale, as some of

the production is used for household’s self-

consumption

Kyrgyzstan NEN (i) Increased area of land saved and land reclaimed; (ii) Increased value of nutrient recovery in the soil; and (iii)

increased moisture availability, water infiltration and

improved water quality in pastures through water supply and water harvesting structures.

-

Laos APR Introducing updated methods and technologies (mainly water

management and irrigation) that will upgrade the basis for

environmental-friendly and climate-oriented production.

The support to the technical line agencies

will improve the effectiveness of technical

services, including training on the good practices and CC adapted approaches.

Madagascar ESA Water savings from the irrigation schemes: (i) realize new

potential areas in irrigated areas, (ii) rehabilitation of existing

schemes to restore or improve and expand the water control, and (iii) develop perimeters spate (PEC: Périmètre

d'épandage de crues)

-

Nepal APR (i) Watershed development to agricultural development (ii)

intensification of terrace risers and bunds with forage plantations minimize surface runoff and soil erosion; (iii)

Collection of animal manure urine and its utilization for crop

production and in the preparation of bio-pesticides will minimize GHG emissions

Alternative income generating opportunities

for the poor have not been quantified in the economic analysis


- 22 -

Nicaragua LAC Environmental impact in economic terms of using sustainable

agricultural techniques, such as the use of "microryza" instead of chemical-based manure

-

A text analysis revealed that the integration of environmental benefits should be the preferred one.

In particular, focusing on three main thematic areas: carbon sequestration and biodiversity, soil

conservation and enhancement, water efficiencies and water quality / irrigation ameliorations. The

following step was the identification of the most appropriate techniques and methods to assess such

environmental benefits, as well as the average values extrapolated from a systematic review of the

literature, as well as past and current research work developed under IFAD stream of funding26. The

resulting techniques and methods, as well as values that they produced were applied to the

population constituting Sample II and a new analysis undertaken, similar to the previous chapter in

order to obtain a more comprehensive review of the benefits that ASAP-support investments

generate.

The Systematic Review (SR) is a methodology that synthesises existing evidence - mainly academic

literature but also other official publications, such as reports by globally recognised institutions and

organisations - following rigorous and objective guidelines under the fundamental principle of

transparency and independency applied throughout the process. This evidence-based framework

allows reaching robust and as extensive as possible conclusions on a specific research question in a

standardised manner (Collaboration for Environmental Evidence, 2013; Pullin and Stewart, 2006).

In practical terms, the application of this methodology consisted in the identification of an evidence

need, in our case common techniques and methods to adopt when calculating environmental

benefits related to biodiversity, soil and water preservation and directly attributable to ASAP related

activities. Once investigation questions are identified and the research strategy planned, the review

is conducted. This implies identifying keywords and main research tools to use for the review

purpose. Figure 18 shows the number of results obtained for each combination of keywords in

Google Scholar for each of the main area of interest.

26 For example, the "EFA and Environment methodological review", or the current “Learning Alliance” work by CIAT

and Duft University on developing a tool for the appraisal of costs and benefits for Integrated Agricultural System, the

former, and Climate Smart Agriculture, the latter.


- 23 -

Figure 18: Queries results in Google Scholar

Two additional sources of data were the Environmental Valuation Reference Inventory (EVRI)27

and the Web of Science Service for UK Education28, using the same combination of keywords.

Contingent Valuation (CV) is the most commonly used technique to evaluate environmental

amenities in the literature, according to our SR exercise. It is often employed in the economic

assessment of environmental benefits deriving from activities concerning biodiversity (Christie et

al., 2006; Ingraham and Foster, 2008; Loomis and White, 1996; Loureiro and Ojea, 2008;

Richardson and Loomis, 2009). It is a survey-based methodology through which various

hypothetical scenarios are presented to the individual in order to compute the access fees that

maximize financial revenues from visitors. A range of values for each of the use and/or non-use

values of environmental amenities are the results deriving from this methodology which requires

primary data collection.

Alternatively, whenever a collection of primary data is not possible, the Benefit Transfer (BT)

technique is used. It consists in monetary estimation of ecosystem services by utilizing information

included in the literature about economic assessments endeavoured in similar settings (Liu et al.,

2011; Bateman et al., 2011; Colombo et al., 2007; Shrestha et al., 2007).

The SR also supported us in the identification of average values to apply the BT for Sample II

assessing environmental benefits not originally assessed in the first place, as per table above

presented at the beginning of this chapter (Table 6).

27 https://www.evri.ca/ available in English, French and Spanish. 28 http://wok.mimas.ac.uk/

https://www.evri.ca/

http://wok.mimas.ac.uk/


- 24 -

3.1 Biodiversity (and carbon sequestration)

The evidence-based review for techniques and values to estimate environmental and socio-

economic benefits related to biodiversity preservation also provided considerable information on

carbon sequestration, both in technical and monetary level.

According to the literature explored, in Latin and South America carbon savings from conservation

of already existing forests ranges on average from 3.15 to 8.67 tons of CO2eq Ha-1 year -1. At a

global scale, an average of 125 to 150 tCO2eq Ha-1 year -1 can be expected; as shown in Table 7.

For the integrated appraisal of benefits in Sample II, the average value of 6.67 t CO2eq Ha-1 year -1

is selected. The rationale behind the exclusion of the values deriving from global studies stays in the

rather too heterogeneous array of values behind these estimates.

Table 7: Carbon savings from conservation of already existing forests (tCO2-eq/Ha/yr)

The review also provided further indications on the yearly price per ton of CO2 equivalent that

should be considered in the economic estimations. As shown Table 8, the average price in the

studies that coincidentally took all place in the LAC region, is of about $2.54. However, for the

appraisal of benefits, we decided to use the average value commonly used in EFA’s estimations of

$4 per ton of CO2-eq for all programmes under analysis.

Table 8: Carbon price (2015 USD/tCO2-eq/yr)


- 25 -

As expected, the wide range of definitions for biodiversity and the approaches used to determine the

economic value was reflected in the results of the systematic review.

Table 9: Biodiversity species evaluation (2015 USD/Ha/yr)

Interestingly, the average yearly economic value of $239.95 per Ha of project area dedicated to

conservation and preservation of biodiversity is almost identical to the average Total Economic

Value that the systematic review revealed to be for forestry services, which equals $235.54/Ha/yr.

3.2 Soil and water

Those ASAP activities implemented towards soil conservation and enhancement, or water savings

measures and water quality amelioration are valued using the yearly average worth of $116.33/Ha.

This value derives from the combination of several studies that reported such amount to quantify in

monetary terms watershed protection, flood-control, soil-erosion control and protection of fishing

grounds (Gössling, 1999; Ruitenbeek, 1989; Adger et al., 1995; Pimentel et al., 1995).

In the case of water-only activities, the quantification of correlated benefits will be undertaken

using the average value of $30.00/Ha that emerged from a study by Bishop and Pagiola (2012)

regarding the Payment of Ecosystem Services for water provision in Costa Rica.


- 26 -

Chapter 4: Revised benefits appraisal

Once the most adequate techniques were identified for the assessment of benefits neglected in the

original calculations, these were applied to Sample II. In particular, in applying the BT to Sample II

we firstly used average values obtained in the benefits and costs calculations undertaken by other

ASAP-supported investments and later then we used the average values that emerged from the SR

exercise. In this chapter, we present mainly the results from the analysis of revised benefits on

Sample II using BT with values from SR, which are indicated in figures and tables with the “post-

SR” labelling. Figures obtained applying BT on Sample II with values from other projects are

instead labelled as “pre-SR”.

4.1. Value for money on ASAP-supported investments (Sample II)

The two figures below report the BCR and the NPV values for whole sample of 32 projects but for

those countries selected as part of Sample II, the environmental benefits have been assessed

applying the BT technique.

The results of the BCR analysis in Figure 19 shows that in programmes including ASAP

components, expected benefits will roughly double the costs and on average the BCR would be 2.47

with a minimum ratio equals to 1.05. For every dollar invested, the project is expected to generate

and redistribute to project beneficiary an extra worth that ranges between $ 0.60 (first quartile)

and $ 1.66 (third quartile) with an average return of $1.47 per dollar invested. In comparison with

the initially assessed values, the expected generation and redistribution to project beneficiaries after

the SR is 12% higher. Values for the ASAP component alone are also higher than the initial Sample

I, after the SR exercise. Once the revised benefits are included in the analysis the average ratio

value for the ASAP component is 2.77, and potential returns for every dollar invested in the

ASAP shift upward between $0.59 - $1.96 with an average value of $1.76 per dollar invested.


- 27 -

Figure 19: BCR of programmes and ASAP components in sample II (pre / post SR)

Similarly, the NPVs for the ASAP substantially benefitted from the SR and the inclusion of further

estimates to the calculation. The average NPVs for the BCR after the SR is $ 8.8 million with an

average increase of 14% - with respect to the pre-SR scenario - for programmes implemented over

5 to 7 years and benefits sprawling upon a 20 years period. The first and third quartile equals $ 2.4

million and $ 13.3 million respectively (Figure 20). Cumulatively, the ASAP guarantees a net

wealth creation of $ 274 million as a counterweight to the $ 200 million granted worldwide.

Figure 20:NPV for programmes and ASAP components in sample II (pre / post SR)


- 28 -

4.2. Economic returns on ASAP-supported investments (Sample II)

The same analysis performed for Sample I measuring the profitability indicator in terms of the

EIRR was retaken for Sample II. Figure 21 shows programme results that are based on a new

elaboration of original EFA using a standard base year (2015) for all projects. A general increase of

EIRR values can be observed with a growth rate that ranges between the 6% observed in the Ghana

project and 290% on Djibouti. Nonetheless, some of the results would need to be further validated

with field visits - particularly Bolivia and Djibouti – considering the remarkable increase detected.

Finally The EIRR for Kenya in the post SR could not be calculated due to the absence of a

mathematical condition about the existence of negative values in the net stream of benefits in the

post SR exercise.

Figure 21: Average EIRR in sample II projects29

4.3. Macroeconomic impacts and indirect effects of climate change adaptation strategies

(Sample II)

As in the previous analysis, the new sample derived with the SR and the revised benefits in sample

II are now used to measure the macroeconomic impacts and indirect effects of ASAP intervention

and CC adaptation strategy. This time results are presented within the countries exclusively for

those countries included into sample II.

Figure 22 provides a global perspective of expenses and revenues contribution relatively to the

country GDP per capita. Overall, Laos, Nicaragua and Ivory Coast are those country registering the

highest gross contribution to the GDP over the lifetime period of the programmes (20 years). This

29 Benin not included


- 29 -

time, the inclusion of the environmental benefits calculated thanks to the SR would in general

increase programmes’ contribution to GDP growth. The highest contribution attributable to the

environmental benefits are registered in Laos and Djibouti where somehow, programme activities

and literature review allowed for a more comprehensive understanding of environmental upsides

related to CC adaptation activities. Differently, where results are minimal there is space for a more

thorough and ad-hoc investigation as the SR has provided marginal evidence on the environmental

benefits related to some activities. Where properly estimated and substantiated by facts,

environmental benefits – hence ASAP relevance – remarkably increase the effectiveness and

contribution of ASAP investments to farmers livelihoods.

Figure 22: Programmes and ASAP categories’ values as percentage of GDP in the area of

intervention

Considering ASAP components alone, most countries have benefitted by the literature review and

the inclusion of environmental benefits, while few others have been slightly downgraded

(Nicaragua) to more conservative levels.

In particular, Djibouti, Kenya and Laos present the highest values of ASAP contribution to the GDP

growth with an increase of 36%, 33%, 21% respectively compared to the base case. After

environmental externalities are taken into account, ASAP contribution to GDP growth averages

the 22% of its total value - roughly the 1.2 % yearly – marking a notable increase with respect the

7% and the 0.3 % of the base case contribution.


- 30 -

Figure 23: ASAP contribution to GDP growth in the area of intervention

4.4. Expected outcomes vis-à-vis ASAP pre-identified risks and climate variability (Sample II)

The revision of the expected benefits has the main consequence of reducing the volatility and the

likelihood of some risks thus decreasing the width of the probability distributions with respect to

possible outcomes of IFAD - ASAP programmes.

Figure 23 presents the probability distribution and frequency of NPVs results under pre-identified

risks and climate variability, for the ASAP component alone (top graph) and the whole programme

(bottom graph). Generally, programmes tend to remain viable even in light of the changes brought

into the analysis. The majority of the curves’ bells and peaks are indeed centred in the right hand

side area of the graphs towards higher and more profitable results. Some other are instead more at

risk (Ghana, Ivory Coast, and Madagascar) as larger parts of the frequency bells crosses the zero

and extend towards more negative values. Despite an overall increase in programmes’ expected

results after the SR excise., this analysis proves that few of these countries are still at steak of the

climate variability and other risks. A successful implementation of programme activities and a

close monitoring of key variables are deemed necessary to reduce to the maximum extend the

likelihood of negative NPVs.


- 31 -

Figure 24: ASAP NPV (top) and whole programmes NPV (bottom) probability distribution

Conclusive remarks on accountability framework of economic and livelihood benefits for

ASAP-supported investments

This work presented a review of economic and livelihood benefits aimed at quantifying the socio-

economic and environmental benefits attributable to ASAP investments. In particular, the team

investigated a sample of 32 approved projects since 2010 which included ASAP components so as

to measure: i) the value for money of ASAP, ii) the economic returns on 1 USD dollar spent on

ASAP, iii) the macroeconomic impacts and indirect effects of climate change adaptation strategies,

and finally iv) the expected outcomes vis-à-vis pre-identified risks and climate variability. These

results are integrated in the light of data gaps, which appeared a relevant issue to overcome for the

calculation of environmental benefits.


- 32 -

A preliminary analysis of the whole sample confirmed the ASAP-support investments are

characterised by value for money with economic returns on each dollar invested in agriculture

smallholders adaptation to climate change. On average, for a project that is implemented between 5

to 7 years and undertaking an economic and financial analysis over a period of 20 years, for every

dollar invested, the project is expected to generate and redistribute to project beneficiary an extra

worth that ranges between $ 0.44 to $ 1.63 on average. A “representative” project with ASAP

component completely offsets its costs and still contributes to value generation for about $ 0.35

million on average on a yearly basis (NPV of $ 6.8 million).

A more in-depth analysis where data gaps about environmental benefit have been addressed via the

SR and BT techniques further validated the preliminary findings and has shown an increase of

roughly the 12% with respect to initially values. Once the revised benefits are included in the

analysis, the average ratio value for the ASAP component reaches 2.77, and potential returns for

every dollar invested in the ASAP shift upward between $0.59 - $1.96 with an average value of

$1.77 per dollar invested. Similarly, the NPVs for the ASAP substantially benefitted from the SR

and the inclusion of further estimates to the calculation. The average NPVs after the SR is $ 8.8

million with an average increase of 14% - with respect to the pre-SR scenario. Every year the ASAP

would redistribute the equivalent of $ 0.45 million while cumulatively guaranteeing a net wealth

creation of $ 274 million as a counterweight to the $ 200 million granted worldwide.

To estimate the macroeconomics impact of projects and programmes with an ASAP component, we

have analysed the ratio between costs and benefits in relation to the changes in the GDP of the area

of intervention. It was shown that on average the socio-economic benefits generated by the

implementation of such interventions correspond to half of the GDP estimated in the target areas.

ASAP alone – once environmental externalities are taken into account – would contribute the 22%

of the GDP total value over the 20 years’ time period, being responsible for the 1.2% of value added

formation in the area of intervention.

Finally, programmes’ results are tested to climate variability as predicted by the IPCC group by

estimating the changes in probability of crop production under long-term climate scenarios for

different regions. Generally, the analysis showed positive indicators for most countries, with some

proving resilience in spite of the changes and few others put at steak by the climate variability. A

successful implementation of programme activities and a close monitoring of key variables are

deemed necessary to reduce to the maximum extend the likelihood of negative NPVs.

Despite the evidence provided that ASAP-supported investments generate relevant economic and

livelihood benefits, a major challenge in performing this review has been the quantity and quality


- 33 -

data available to create the database used as input of our analysis. Furthermore, to validate and

consolidate results presented in the previous paragraph, it is strongly suggested to conduct a CV. It

is, therefore, suggested to compose a third sample with at least 2 virtuous ASAP project, whose

implementation is in an advanced state. For this sample, field visits should be arranged to collect

standardised evidences about ASAP impacts, consolidating the soundness of the results, i.e. their

scientific robustness. Furthermore, running a CV can be considered as the first step towards what

seems to be a necessary effort by analysts in estimating environmental benefits that are directly

generated by ASAP-supported investments, as well as review how valuations are undertaken in the

project cycle with follow up in mid-term and end-of-project.

To this purpose, it is suggested to conduct reviews of benefits generated by ASAP-supported

investments on a regular temporal basis. This has the twofold advantage of providing accountability

information to donors about the actions initiated by IFAD, as well as creating organisation know-

how as per the assessment of economic and financial feasibility of projects and programmes

towards a standardised manner of undertaking such task. Corollary to this, it is the creation of a

common database owned and managed by IFAD in which all information gathered, used and

generated within the EFA process, is stored in an organisational repository that will contribute

towards the efficiency and efficacy amelioration of investments supporting adaptation for

smallholder agriculture to incumbent challenges of climate change impacts.


- 34 -

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Annex I: ASAP-supported investments for Sample I

The 32 ASAP-supported investments that have been included in the initial sample of this work are

reported in the table below. Project names are presented in the original language of preparation to

safeguard the meaning of project’s acronym.

COUNTRY REGION TITLE STATUS30

Benin WCA Projet d'Appui au Développement du Maraîchage au Bénin (PADMAR) Approved

Bhutan APR Commercial Agriculture and Resilient Livelihoods Enhancement Programme

(CARLEP) Approved

Bolivia LAC Programa de Adaptación para la Agricultura en Pequeña Escala (ACCESOS) Implementation

Cambodia APR Agricultural Services Programme for Innovations, Resilience and Extension (ASPIRE) Implementation

Chad WCA Projet d'Amélioration de la Résilience des Systèmes

Agricoles au Tchad (PARSAT)

Implementation

Djibouti NEN Programme to Reduce Vulnerability in Coastal Fishing Aras Implementation

Ecuador LAC Proyecto de Fortalecimiento de los Actores Rurales de la Economía Popular y Solidaria Approved

Egypt NEN Sustainable Agriculture Investments and Livelihoods (SAIL) Implementation

El Salvador LAC Rural Adelante - Programa Nacional de Transformación Económica Rural Approved

Gambia WCA National agricultural land and water management development project (NEMA) Approved

Ghana WCA Ghana Agriculture Sector Investment Programme (GASIP) Implementation

Ivory Coast WCA Projet d'Appui à la Production Agricole et à la commercialisation (PROPACOM) +

PROPACOM Extension Ouest

Implementation

Kenya ESA Climate Resilient Agricultural Livelihoods Programme (KCEP-CRAL) -> KCALP Implementation

Kyrgyzstan NEN Livestock and Market Development Programme II Implementation

Laos APR Adaptation to Climate Change in Southern Laos (ACCSL) Implementation

Lesotho ESA Wool and Mohair Production Project (WAMPP) Implementation

Liberia WCA Tree Crop Extension Project (TCEP) Approved

Madagascar ESA Project to Support Development in the Menabe and Melaky Regions - AD2M-Phase II Implementation

Malawi ESA Programme for Rural Irrigation Development (PRIDE) Approved

Morocco NEN Programme de Developpement Rural des Zones de Montagne (PDRZM) Implementation

Mozambique ESA Pro-Poor Value Chain Development Project in the Maputo and Limpopo Corridors (PROSUL)

Implementation

Nepal APR Adaptation for Smallholders in the Hilly Areas (ASHA) Implementation

Nicaragua LAC Adapting to changing markets and the effects of climate change Implementation

Niger WCA Programme de Promotion de l'Agriculture Familiale dans les régions de Maradi,

Tahoua et Zinder (PRODAF)

Implementation

Nigeria WCA Climate Change Adaptation and Agribusiness Support Programme (CASP) Implementation

30 As of December 2015


- 37 -

Paraguay LAC Project for Family and Indigenous Production Approved

Rwanda ESA Post-harvest and Agribusiness Support Project (PASP)

Implementation

Sudan NEN Livestock Marketing and Resilience Programme Implementation

Tajikistan NEN Livestock and Pasture Development II (LPDP II) Approved

Tanzania ESA Bagamoyo Sugar Outgrower and Community Development Programme (BSIASCDP) Approved

Uganda ESA Programme for the Restoration of Livelihoods in the Northern Region (PRELNOR) Implementation

Viet Nam APR Adaptation to Climate Change in the Mekong River Delta Region (AMD) Implementation

Annex II: ASAP-supported investments for Sample II

The following 10 countries were selected for Sample II

Country Region Environmental benefits estimated

Bolivia LAC (i) Implementation of activities specifically related to CC adaptation such as soil conservation / water

savings that improve agricultural production locally. (ii) Harvest loss reduction of loss due to climatic natural disasters through EWS (iii) reduction in the fuelwood consumption by households

Djibouti NEN Preservation of biodiversity especially marine species

Ghana WCA Economic value of more efficient water use in water management schemes, also in commercial value

chains

Ivory Coast WCA (i) Reforestation; (ii) Adapting cultivation techniques to soil degradation levels

Kenya ESA Environmental protection due to soil, water and environment conservation technologies

Kyrgyzstan NEN (i) Increased area of land saved and land reclaimed; (ii) Increased value of nutrient recovery in the soil;

and (iii) increased moisture availability, water infiltration and improved water quality in pastures through

water supply and water harvesting structures.

Laos APR Introducing updated methods and technologies (mainly water management and irrigation) that will

upgrade the basis for environmental-friendly and climate-oriented production.

Madagascar ESA Water savings from the irrigation schemes: (i) realize new potential areas in irrigated areas, (ii)

rehabilitation of existing schemes to restore or improve and expand the water control, and (iii) develop perimeters spate (PEC: Périmètre d'épandage de crues)

Nepal APR (i) Watershed development to agricultural development (ii) intensification of terrace risers and bunds with forage plantations minimize surface runoff and soil erosion; (iii) Collection of animal manure urine and its

utilization for crop production and in the preparation of bio-pesticides will minimize GHG emissions

Nicaragua LAC Environmental impact in economic terms of using sustainable agricultural techniques, such as the use of

"microryza" instead of chemical-based manure

Review of economic and livelihood benefits for ASAP ... · Review of economic and livelihood...

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