africa-latin america article

8/2/2019 Africa-Latin America Article

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Abstract

Since the 1960s, IMT/PIM has formed the central tenant of institutional reform in the

irrigation sector worldwide. Despite the widespread application of IMT as a remedy for

poor systems performance, the actual effectiveness of transfer programs in terms of

improving irrigation, agricultural and management efficiency is still a subject of much

debate. Through the systematic review of 65 case studies of IMT/PIM in Africa and

Latin America, this study identifies important gaps in the literature on management

transfer, in particular the need for higher quality and longer-term impact assessments

of transfer programs to better establish a causal link between IMT intervention and

impact. It also provides insights into the conditions that shape the effectiveness of

institutions for irrigation management . In particular we find that in the African context,

three factors were consistently correlated with successful IMT/PIM, these are credit

and market access, property rights and NGO-donor assisted implementation. In Latin

America, governance issues such as WUA organizational structure and water rights

appear to increase the likelihood of successful management transfer. Thus, our research

suggests that what matters in Africa is not always relevant in Latin America and vice

versa, Even within these regions performance is mixed and impact across various

technical, social, economic and agricultural indicators is highly variable. Moreover, our

analysis suggests that some factors may be so critical to successful transfer, for instance,

the ability to absorb the costs of management that they impact the significance of

others, such as the type and size of scheme. Put simply, no clear, consistent pattern

emerges that offers a recipe for the successful replication of IMT/PIM interventions

elsewhere. Rather our work suggests that irrigation management reform must move

beyond single-policy solutions if it is to address farmers’ development needs.



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Introduction

Since the 1960s, the debate on how to best improve the management of the public

irrigation sector has stagnated. The policy which has ruled irrigation reform discourse

for the past 50 years claims the answer lies in devolving some or all of the management

authority for irrigation systems to organised user groups or Water User Associations

(WUA). This phenomenon is termed Irrigation Management Transfer (IMT) or

Participatory Irrigation Management (PIM) and has been adopted in more than 60

countries around the world (FAO, 2007).

The literature on public sector irrigation reform is replete with case studies of PIM/IMT.

Although individual case studies are an important source of data and analysis on

performance trends at a scheme or country-level it is also useful to situate them in alarger context and differentiate between localised trends and regional/global

developments (Giordano et al. 2010?). This is especially pertinent when single policy

solutions are taken up based on their ‘success’ in particular schemes and transplanted

to a wide range of locations and problems, as has been the case with IMT/PIM

interventions.

In spite of this, very few papers systematically combine and analyse the findings of

IMT/PIM case studies. The value of such systematic review is established in the works

of Petrosino et al. (2001); Farrington (1998, 2003); Welsh and Farrington (2006) and

Van der Knapp et al. (2008) who argue that when done well and with full integrity, they

provide the most reliable and comprehensive statement about what policy

interventions work, under which conditions and why.

This review attempts to partially fill that gap. It draws on the most comprehensive

database of IMT/PIM cases in Africa and Latin America to date and updates the very

limited number of existing reviews on the policy (Vermillion, 1997; FAO, 2007) with

new evidence and methods of analysis. While this paper builds on previous research it

also differs from it in several ways. In particular, with 65 case studies from 20 different

countries it taps into a much larger database and geographical scope than Vermillion or

FAO and is thus amenable to regression analysis.1 Moreover, unlike FAO we analyse

only localised case studies of IMT/PIM and hence are able to capture in-country

variation in terms of IMT/PIM impacts and outcomes.

The results of this review provide insights into the quality of evidence and research

methods used in IMT/PIM impact evaluations. Through the systematic analysis of case

study design we establish that available impact assessments largely fail to causally link

improvements in scheme performance and transfer programs. For this reason, the

actual effectiveness of IMT in terms of improving irrigation, agricultural and

management efficiency remains questionable.

1 FAO’s review (2007) covered only 8 cases from Africa and 7 from Latin America and Vermillion’s

(1997), analyzed only 4 from Africa and 4 from Latin America.



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We also develop and apply a methodology for classifying each of these IMT/PIM case

studies as successful or failed. Performance is measured from several perspectives,

drawing on ten financial, technical, social and agricultural outcome and impact

indicators. Each intervention is assigned a unique score and is ranked in terms of

success or failure. Finally, drawing on these success scores we investigate patterns of

success/failure through a combination of simple correlation, binary logistic regressions

and qualitative comparative analysis. From this we provide empirical support to some

prevalent hypotheses regarding the pre-conditions for successful management transfer.

Without doubt, PIM policy has generated some success stories, particularly in the

dynamic commercial farming sectors of South Africa and Northern Mexico. However,

overall our results show that the outcomes of IMT/PIM in the African and Latin

American regions are mixed and the positive impacts of the devolution program,

ranging from livelihood security to improved technical efficiency, show great variability

across and within locations. This variation, we argue, reflects the ‘difficulty of

transplanting institutions from one context to another’ when local situations vary

significantly in terms of technology, water availability, cropping patterns, market

development, social capital and government policies (Meinzen-Dick, 2007: 15200).

Nowhere is this institutional mismatch and disconnect more pronounced than in the

small-holder irrigation context of Africa. In this context of moderate dynamism and

poverty, interventions in the irrigation sector must move beyond single-policy solutions

and encompass, land reform, market access, and other support services which will help

farmers increase their livelihoods and consequently their ability to absorb the costs and

responsibilities of irrigation management.

Research Questions

Our review considers evidence from 65 case studies of IMT/PIM in Latin America and

Africa to answer the following questions:

1. How well have the impacts and outcomes of IMT/PIM in Africa and LatinAmerica been documented and what have we learnt from those studies?

2. How can we evaluate the impact and outcomes of IMT/PIM and differentiate thesuccessful cases from ‘not so successful’ ones?

3. What are the conditions under which successful or at least promising WUAs inpublic irrigation systems are found? Are those conditions replicable?

The substantive sections of this paper each address one of these research questions.

Methodology

Given the objectives of this paper, a five-stage review process was undertaken. First we

attempted to locate all existing case studies of IMT/PIM by searching academic



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databases and Google and Google Scholar search engines.2 Sources were also identified

from the bibliographies of previous meta-reviews (Vermillion, 1997: Shah 2002; FAO

2007). These searches returned over 2,500 records. However only studies which met

the following criteria were included in our review:

a) Case studies were limited in geographic scope to Africa and Latin America.

b) Records were localized case studies of one or more Water User Association andnot country level studies.

c) Case studies were of publicly owned irrigation systems that were later handedover to the farmers for management either as a decision of the government,

donors or due to the interest of the farmers. This meant we did not include casestudies of farmer managed irrigation systems (FMIS), which, unlike the turnedover or transferred systems of our interest, were built and managed by thefarmers themselves.

d) Case studies were published after 1994. The year 1994 marked a watershed yearin the study of IMT/PIM initiatives. It was in this year that a major conference onPIM/IMT was held at Wuhan, China. Here, more than 100 case studies werepresented and later documented in 2 volumes of conference proceedings. Basedon the assumption that IMT/PIM initiatives in the pre-1994 era were adequatelystudied and documented, we wanted to review only the post-1994 case studiesso as to reduce duplication in results and make our review more up to date andfocused.

e) Case studies were documented in the English language. We include thereferences for papers excluded on this basis so that they may be incorporatedinto future reviews.

After reviewing titles and abstracts, all but 137 case studies were excluded on the basis

of relevance. A further 57 studies were eliminated because they did not contain a

localised intervention. Another 8 sources were eliminated as they did not provide

enough information on the impact and performance of IMT and 7 sources were

eliminated because they were published in languages other than English (French,

Spanish and Japanese). In total, 65 distinct case studies of IMT/PIM were included in

our review.

We made a concerted effort to include as many case studies from as many countries as

possible. To this end we undertook country and schemes specific searches in an attempt

to maximize sample size and country representation; however despite our best efforts

potentially relevant sources were either inaccessible or failed to meet our inclusion

2 The following databases were searched: Water Resources Abstract, CAB Direct, Econ Lit, SociologicalAbstracts, Web of Science, Scopus, World Bank Publications, FAO’s AGRIS database, EnvironmentalSciences and Pollution Management, ProQuest Central, EVA Environmental Abstracts, Ingenta Connect,Ovid Databases, JSTOR, Sage Journals, Science Direct and IWMI’s catalogue.

Comment [SN(1]: In his comments earlier this

year, Mark thought this was not a good reason-

perhaps some more justification that there would

be overlap?



5

criteria. As a result, there are regional biases in the data collected, with some countries

such as South Africa, Mexico and Columbia over-represented and others, such as

Burkina Faso, Chad and Ecuador not accounted for at all.

Second, we coded studies on a range of methodological, descriptive and

outcome/impact related attributes. The purpose of the coding was to make comparable

a number of seemingly diverse and inconsistent results across IMT/PIM case studies.

Coding was based on the Institutional Analysis and Development (IAD) framework

which draws on various disciplines such as political science, economics, anthropology,

game theory and law, to study common property resources (CPR). In short, this

framework analyses the physical attributes of the resource, the community attributes of

the people managing them and the attributes of the institutions that have been formed

to manage the resource (Oakerson 1986). Coding was done to gain insights into the

three core research questions which frame this paper. It enabled us to:

a) Assess the quality and strength of evidence used in case studies. This was done by

identifying and coding the study design and data collection methods used in case

studies. We collated information on case study authors’ methods of analysis;

whether or not they undertook independent verification of outcomes and

impacts and the number of years that elapsed between the IMT/PIM

intervention and the impact assessment. There were 21 methodological

parameters assessed in this study and these were then used to evaluate the

quality of research into IMT/PIM in general. Our list of indicators conforms to

and builds on Vermilion’s (1997) analysis of the evidence on IMT/PIM.

b) Measure IMT/PIM case studies in terms of their outcomes and impacts . We chose

10 indicators of success which closely conform to the definition of successful

IMT/PIM initiatives endorsed by both the International Network on

Participatory Irrigation Management (INPIM, see http://www.inpim.org/ ) and FAO

(2007). We measure the following outcomes: irrigation service fee collection

rates; financial viability of WUA; functional condition of infrastructure (good

maintenance); enhanced equity; reliability and adequate water supply; reduction

in government expenditure after transfer, popular participation and reduction in

disputes (or increase in rule conformance). In addition we measure the following

impacts: crop related impacts (increase in production, yield, cropping intensity)

and livelihoods related impacts (increase in income, employment, wage rates,

reduction in forced out-migration etc.). Table X presents the list of outcome andimpact indicators we used to evaluate success.

c) Identify factors that that influence the success of IMT interventions. To do this we

coded cases on 25 descriptive attributes including their technical specifications

(type of scheme, size, complexity, whether or not it had been rehabilitated);

socio-economic and agricultural characteristics (population served, major crops,

per capita GDP, access to credit, markets, importance of agriculture, social

http://www.inpim.org/






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cohesion, land rights, water rights); and their IMT/PIM experience (level of

transfer, training, political will, legislation, election to WUAs).

Third, to allow for further commentary on the methodological quality of each selected

IMT/PIM case study we developed and applied a modified version the Maryland

Scientific Methods Scale (SMS) which is recommended for systematic reviews by Welsh

and Farrington (2006) and Van der Knapp et al. (2008). This is a five-point scale that

rates the strength of scientific evidence used in impact evaluations, with 1 being the

weakest and 5 the strongest scientific evidence in terms of inferring cause and effect. 3

Given that our sample does not contain a single case study with a traditional SMS score

of 4 or above (i.e. none used an experimental design with statistical control of

extraneous influences on the transfer process) we adapted the scale to better reflect the

actual analytical techniques and evidence used in our source documents. This is because

the nature of PIM/IMT interventions rules out impact assessments by experimental

design (such evaluation research measures change before and after an intervention in

units that are randomly assigned to experimental and control conditions).4 It does not,

however rule out scope for rigor by combining a “before-after” with a “with-without”

comparison. We assigned a rating of one to four based on design robustness, as

described in detail below.

Level 1. Studies which measure the correlation between an intervention and an

indicator of performance at a certain point in time, after the introduction of the

intervention. This design fails to rule out any threat to internal validity and also

fails to establish causal order.

Level 2. Studies which measure the performance before and after the

intervention, without a (comparable) control condition or statistical analysis.


intervention, without a (comparable) control condition but with statistical

analysis.


intervention, and also have a comparable control group (quasi-experimental

design) with statistical analysis.

By grouping case studies according to SMS levels we can distinguish between high and

low quality impact assessments. Given that the primary objective of a systematic review

is to combine the findings of a large number of studies with the aim of drawing credible,

generalizable conclusions about what policy interventions work, where and why,

3 The SMS was designed by Sherman et al, as a tool to evaluate the methodologies for their review of over500 crime prevention interventions for the U.S congress. The scale has since been considered a keyresource for appraising quantitative studies. The five levels are described by Welsh and Farrington(2006).

4 This type of impact assessment is common in the field of public health.



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attribution challenges arise from the inclusion of studies with non-experimental

evaluation designs. Through the SMS we can assign labels of success or failure with

caveats and soften many problems that arise from the presence of low quality studies

(SMS of 2 and below) in a review of this kind. In the end, systematic reviews are only as

robust as the existing evidence on a given intervention enables them to be.

Fourth, we constructed a composite success score (CSS) from the coding of outcome and

impact indicators and use this to differentiate successful cases of IMT from not so

successful ones. This scoring system (CSS) is adapted from Mukherji et al. (2009).5

The CSS draws on the dichotomous coding of outcome and impact indicators (1= if

performance improved; 0= no change in performance or deteriorated) outlined in Table

X and simply involves adding up all positive scores and dividing this sum by themaximum possible score. Here, the challenge was to deal with missing values in each of

the case studies (as the data availability among case studies varied between 4-10

outcome/impact indicators). We decided that whenever data was not available, we

would leave it out from our calculation. For example, if outcome and impact indicators

were available for 8 out of 10 (maximum) possible indicators, then we calculated the

CSS assuming a maximum possible score of 8 (and not 10). If out of these 8 indicators,

four were positive (therefore getting a cumulative score of 4) and 4 were negative or

neutral (getting a cumulative score of 0), our CSS would be 4 out of 8 or 0.5 which can

be converted to 5 on a 10 point scale (see Appendix 7).

Table X : List of outcome and impact indicators used for construction of success sc ores

Sr.No.

Name of the indicator Scoring system Number of cases wherethis indicator was present

(Max=65)

A. Outcome indicators

1. Irrigation service fee collection rate 1= if it has gone up

0= no change or declined

n/a = not available

56

2. Financial viability of WUA 1= if it has improved

0= no change or deteriorated

n/a = not available

59

3. Functional condition of infrastructure 1= if it has improved

0= no change or deterioration

n/a = not available

64

4. Equitable distribution of water 1= if it has gone up


n/a = not available

46

5. Reliability and adequacy in water

distribution

1= if it has gone up

0= no change or declined49

5 For a discussion on the strengths and limitations of this scoring method please refer to Mukherji et al(2009); pp. 13-14.



8

Sr.

No.

Name of the indicator Scoring system Number of cases where

this indicator was present

(Max=65)

n/a = not available

6. Reduction in government

expenditure

1= Yes

0= Otherwise

n/a = not available

30

7. Popular awareness and participation

in WUA activities

1= if it has gone up


n/a = not available

60

8. Reduction in frequency of disputes 1= Yes

0= No or got worsen/a = not available

33

B. Impact indicators

1. Crop related impacts (production,

yields, cropping pattern, cropped

area)

1= If any one of these registered

an increased after transfer

0= Otherwise

n/a= not available

50

2. Livelihoods and household

parameters (income, wage,

employment, poverty reduction,

reduction in forced migration)

1 = if any of these have gone up

after transfer

0=Otherwise

n/a = Not available

39

All cases that got a value of 5 and above in our CSS scale were categorized as effective

and those with scores of 5 and less were categorized as ineffective cases of IMT. While it

may be argued that using a score of 5 as the cut off point is rather arbitrary, we justifyour cut off point on the grounds that varying the cut off point between 5 and 6 (when

5.5 is the mean value on a scale of 0 to 10) does not change the overall number of

successful and failed cases.

In short, every case study was scored and ranked on a uniform scale of 0 to 10. In cases

which scored 0, the transfer process produced no positive changes in scheme

performance. In cases that scored 10, the transfer process produced only positive

changes in scheme performance

There are obvious limitations with some of the indicators used it our system of

classification. This is particularly true for the impact indicators. Very often, increase in

crop yields, incomes or area under acreage, even, if it happens after the intervention,

may not be directly attributable to greater farmer involvement in O&M per se. Rather,many factors exogenous to IMT interventions such as, changes in fertilizer application

rates, higher crop prices, rainfall patterns and more favourable market conditions can

affect the performance of irrigated agriculture. Furthermore, it should be pointed out

that investments in farmer management are often part of a wider set of economic and

agricultural interventions, including promoting marketing and micro-credit, high-

yielding seed technology and better on farm management. However, because case

studies do not explicitly examine casual links between IMT interventions and systems



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performance our CSS is forced to draw on these problematic but very well documented

indicators (over 70% of case studies measure success or failure of IMT interventions

based on crop and livelihood related impacts). This may mean that our evaluation of

IMT may appear to be more positive than might actually be the case.

An additional source of bias with our database stems from the fact that these studies are

snapshots of cases at one point in time ranging from 1995 to 2010. In most cases, we do

not have any information on current status of these schemes. It is possible that schemes

classified as success/potential success stories in our analysis might as well have failed

over the years or our failed cases might have turned around and become successful

later on. We do not have the time or the resources needed for verifying the current

status of our case study schemes. In short, this type of review gives expression to static

perspectives: performance is measured at one point in time. However, we recognize

that WUAs may be at different stages of maturity and that IMT interventions are

impacted by spatial and temporal dimensions.

Finally, we drew on simple correlations and regression analysis to identify and

investigate which socio-economic and technical mechanisms appear to be active in

successful management transfer. Given the limited number of case studies from Latin

America (18 in total) our regressions only include data from African case studies. The

dependent and independent variables that we consider for our Logit model are detailed

in Table X.

The dependent variable in our case is dichotomous and takes the value “1” if an IMT

intervention was successful or “0” if failed. On the other hand, we considered severalindependent variables that might influence the probability of successful management

transfer. All are drawn from the list of 25 descriptive indicators coded in step 2. Two

variables were dropped from the regression as they were problematic these are,

‘importance of agriculture in people's livelihood’ and ‘amount of O&M authority

transferred’.

Table X : Description of dependant and independent variables used in the logit model.

Variables Domain

Dependent Variable

SUCCESS Binary dummy variable, where 1 =

successful/potentially successful case of IMT/PIM and 0= failed/potentially failed

cases Independent Variables:

Type of scheme Dummy variable: “scheme_type” where Lift &

pump =1, others =0

Size of scheme Dummy variable: “scheme_size” where

Small=0, Large & Medium=1

Value of crops grown Dummy variable: “crop_value” where low ormixed=0, high=1



10

Type of crops grown Dummy variable: “crop_type where Paddy=0,non paddy and mixed=1

Access to credit/markets/support services Dummy variable: “acess_credit” where low ormixed=0, high=1

Land rights Dummy variable: “landrights” where low ormixed=0, high=1

Implementing Agency Dummy variable: “Implementer” where Donor& NGO assisted or farmers =1, Government=0

By correlating success and failure with individual scheme characteristics, we were not

only able to identify patterns of success but also, test some of the hypotheses put

forward in the literature on the determinants of successful management transfer. Our

regressions do not attribute causality rather we can only comment only on theassociation of variables and rates of success.

1. Review of the Evidence: How well have the impacts and outcomes of IMT/PIM

in Africa and Latin America been documented and what have we learnt from

those studies?

Over a decade ago, Vermillion characterised the literature on the impacts and outcomes

of IMT as a ‘disparate collection of definitions and methodologies from which it is

difficult to deduce general conclusions or policy implications’ (1997: 5). At the heart of

his criticisms were problems of causal attribution which arise as a result of post-hocfallacies, fallacies of induction and short-term impact assessments. Our review,

fourteen years on, is frustrated by these very shortcomings and as such the

generalizations that can be derived from these case studies are very limited. We are

however, able to systematically assess the evidence about the impacts of management

transfer with reference to performance measures and the quality of research methods

used in our case studies.

By grouping case studies according to the Maryland Scientific Methods Scale (SMS) we

show the overwhelming majority of evidence on IMT/PIM in Africa and Latin America,

is of low scientific quality. As Figure X indicates most IMT impact assessments rely

solely on post-impact observations and data (SMS 1) to infer cause and effect.

Assessments which claim interventions produced changes in performance without

providing a reference point for those comparisons are inherently problematic.

Studies that use only the “before and after” or “with or without” methodological design

(SMS 2 and 3) also often fail to establish a causal relationship between IMT intervention

and impacts. Many factors exogenous to IMT such as better farm management, changes

in fertiliser application rates, rainfall patterns, changes in technology or cultivation

practices and more favourable market conditions can affect the performance of



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irrigated agriculture. Moreover, in the majority of available case studies IMT followed or

was part of a wider set of neoliberal economic and agricultural reforms all of which

impact systems performance.

Figure X : IMT case studies according to SMS

We found that only 4 of our case studies (out of 65) used a quasi-experimental design to

assess impact by combining “before after” and “with-without” analysis (SMS level 4).Qualitative review of these high qualitycase studies suggest that it is only possible to

trace certain changes to IMT/PIM policies such as, improvements in management

efficiency, staff accountability and the significant shift in the burden of cost from the

government to farmers. From these high quality studies it is clear that ‘transfer has not

had substantial impacts on the performance of operations and maintenance, or on the

agricultural and economic productivity of irrigated land or water – neither improving

negative performance nor causing detriment where performance is positive’

(Vermillion and Garcés-Restrepo, 1998: 33).

For example, in the rigorous evaluations of Samacá and RUT irrigation systems

(Columbia), performance cross almost all documented impact/outcome indicators,

remained constant or could not be linked to management transfer. In Samacá and RUT

farmers shifted to higher value crops just before transfer and thus, positive post-transfer crop impacts may not be attributable to farmer management. These high

quality impact assessments do not shed light on the factors that increase the probability

of IMT failure, as much as they reinforce arguments about the difficulty of attributing

changes in scheme performance to IMT alone. Indeed, they draw attention to the link

between the quality of design and empirical findings, by reinforcing Rossi’s (1987)

37

1113

4

0

5

10

15

20

25

30

35

40

1 2 3 4

N u m b e r o f C a s e S t u d i e s

Adapted SMS Score



12

‘stainless steel’ law of evaluation which states that the better designed impact

evaluations are, the less effective the interventions or programs seem to be.

It is also worth noting that many of these attribution problems are manifest in case

studies which evaluated rehabilitated schemes. In 31 studies, transfer was accompanied

by physical improvement of the system. In these cases, it is difficult to determine the

extent or degree to which initial positive results, in terms of water delivery and crop

related impacts, are attributable to either farmer management or to systems

rehabilitation. Of the 31 studies which were rehabilitated before or during transfer only

4 were evaluated via with and without comparisons. As a result, case studies authors

made little attempt to disaggregate the effects of rehabilitation and transfer by

comparing systems that were transferred with and without rehabilitation. These

problematic causal links between IMT and changes in scheme performance make it

difficult to draw robust conclusions about the impacts of transfer.

We also assessed case studies according to their use of time series and statistical

analysis. Of the 24 studies which compared performance before and after transfer, only

14 examined data on 5 or more consecutive time periods. Without sufficient time series

analysis it is impossible to firmly establish the timing of impacts, to control for

alternative causes of change and to identify the extent transfer has influenced the

outcome (Vermillion, 1997).

The low rates of quantitative analysis also exacerbate problems of casual attribution.

Only 30 cases used statistical tests compared to 52 studies which quoted descriptive

statistics. Statistical and econometric analyses may help to overcome some of themethodological shortcomings identified in this review. For example, combining with

and without and before and after analyses with difference in difference analysis will

help establish a causal link between intervention and impact. Using other quasi-

experimental methods such as an instrumental variable approach will similarly help in

identifying casual attribution and therefore resolve the most pertinent methodological

weakness in IMT/PIM studies.

Further attribution problems arise from the types and rigour of data collection methods

used by case study authors.



13

Figure X : Data collection methods used in IMT case studies

In particular, Figure X suggests several common tendencies. First, 94% of case studiesrely on secondary sources, including data collected by irrigation agencies, government

departments and/or other scholars. Second, less than half (41%) of the studies which

conducted farmer interviews selected participants through systematic, random

sampling methods. As a result, the conclusions drawn and perspectives expressed on

the basis of farmer interviews may not represent the general perception or actual

performance of the transferred unit. Finally, out of 65 cases we found that only 13

evaluations undertook independent measurements of water distribution operations and

only 17 involved the direct inspection of scheme infrastructure. Taken together, these

flaws suggest that in many cases, authors may have either overestimated or

underestimated performance levels in their studies. For example, before and after

analyses which depend on data from government sources may be biased in the

reporting of pre-transfer performance levels leading to an underestimation of post-transfer impacts.6 Similarly, interviews or surveys which only report the perspectives of

upstream farmers or WUA leaders may risk overestimating positive changes in terms of

water distribution and equity. In short, our analysis indicates that most studies failed to

adequately verify their conclusions about the outcomes and impacts of IMT.

6 For a detailed discussion of this see: Vermillion (1997).

51

40

46

19

31

1317

19

32

0

10

20

30

40

50

60

S e c o n d a r y d a t a f r o m

a g e n c y / g o v e r n m e n t

d e p a r t m e n t s

L i t e r a t u r e

R e v i e w / S y n t h e s i s o f

d a t a f r o m o t h e r s t u d i e s

F a r m e r I n t e r v i e w s

S y s t e m a t i c S a m p l i n g

S t a k e h o l d e r

p e r s p e c t i v e s

D i r e c t m e a s u r m e n t o f

o p e r a t i o n s

D i r e c t i n s p e c t i o n o f

s t r u c t u r e s

A n e c t o d a l e v i d e n c e /

f i e l d o b s e r v a t i o n s

I n d e p e n d e n t

m e a s u r e m e n t o f

o u t c o m e s &

i m p a c t s ?

N

u m b e r o f C a s e S t u d i e s

Indicators



14

Our case studies also varied in terms of the number of years that had elapsed between

the transfer process and the impact assessment/documentation carried out by authors

(we refer to this as the period of evaluation). For the purpose of our review we

categorized case studies as either, short term (3 or less years) medium term (4-10

years) or long term (over 10 years) studies.

Although our adapted SMS ranking does not explicitly address the period of evaluation

as a scoring criteria, our data reveals a clear relationship between short-term impact

assessments and low overall methodological quality. All short-term studies scored a

SMS of 1, suggesting that 3 years is not enough time to fully understand the outcomes

and impacts of IMT. Problems of casual attribution, discussed above, are also more

pronounced in short-term impact assessments, especially when the transfer process is

accompanied by the rehabilitation of physical infrastructure, which often produces

immediate improvements to the technical efficiency of the system.

The methodological quality of medium and long-term studies varies significantly. 31

medium and long-term studies were categorised as SMS 1 or 2 due to their low overall

methodological quality. This is hardly surprising given that only 22 (out of 46) long and

medium-term studies used time series analysis and actual drew upon long term data.

Thus, period of evaluation is not a clear cut measure of methodological quality. Long

and medium term studies do however, have the potential to contribute new and useful

insights into our understanding of IMT/PIM impacts and if integrated with more

systematic research methods, to permit conclusions about the conditions under which

transfer programs could be expected to succeed or not.

Taken together, our review and analysis of IMT case studies reveals that data on the

impact and outcomes of management transfer is weak in terms of rigor and method.

Having said that, case studies do include a range of perspectives on the impacts of

management transfer and some results are independently verified. Ultimately, these

studies are the only available sources of information on the impact of IMT/PIM and we

rely solely on the information contained therein to construct our CSS and to evaluate

and classify each of the projects as successful or failed interventions.

2. Definition of success: How can we evaluate the impact and outcomes of

IMT/PIM and differentiate the successful cases from ‘not so successful’ ones?

One of the main objectives of this review is to evaluate the overall impact and

effectiveness of IMT/PIM interventions in Africa and Latin America. To do this, we first

needed to define what constitutes a successful IMT/PIM intervention. In the literature

(for example, FAO, 2007; Tang, 1992; INPIM website) IMT success is defined as multi-

dimensional. We found that except for Tang (1992), who defined success in terms of

only two indicators namely, rule conformance and good maintenance, most others,



15

including our case study authors, defined success based on a number of outcome and

impact related indicators.

On the whole, the performance criteria used by case study authors to evaluate success

are quite diverse. Studies in Latin America emphasised financial viability and improved

water supply while the most common performance indicators in African case studies

were functional condition of infrastructure and popular awareness and participation.

On average, CSS was calculated on the basis of 6 criteria and none of the case studies

contained data on all 10 impact and outcome indicators. This stems from a lack of

consensus on what constitutes successful transfer in the literature. As Mukherji et al .

(2009) argue, definitions of success are often informed by authors’ disciplinary

background. Social scientists for instance, ‘define success in terms of popular,

community participation, while water resource scientists would define success in terms

of better water control of delivery schedules’ (Mukherji et al: 18).

A single indicator, such as increased reliability of water supply or crop productivity may

highlight particular aspects of an IMT intervention but taken alone does not allow us to

comment on the overall impact of management transfer or to examine trade-offs

between key performance measures. For example, changes in short-term productivity

versus long-term reliability and adequacy of supply (Vermillion, 1997).

For this reason our system of classification (CSS) measures success from several

perspectives, drawing on ten financial, technical, social and agricultural outcome and

impact indicators. Theoretically, successfully transferred systems should show a

marked improvement in systems performance because users receive adequate and reliable supply of water at reasonable and affordable costs over a sufficiently long period

of time enabling them to increase their crop production, productivity and incomes. This

definition of success integrates technical, financial and agricultural outcomes over the

long-term.

Figure X: Distribution of successful and failed IMT interventions in Africa and Latin

America (one map)

What are the chances that our method and success scores may misclassify the actual

outcome of an IMT intervention? To ensure the robustness of our system of

classification we compare our success scores with our evidence base. For this purpose

we documented authors’ classifications of success or failure; when authors did not give

an explicit opinion on the success or failure of the initiative we coded it is inconclusive.

Table 2 compares our success ratings based on CSS, with those of the authors. We find

that none of the cases where authors have declared a case to be a failure, turned out to

be successful according to our success scores, showing, there is not a single example of a

failed case, mistakenly coded as a successful one by us. Similarly, we find that only one

case study which the author declared to be successful turned out to be a failed case in



16

our scoring system. There were 23 cases where the authors had not given any firm

verdict on the outcome of IMT and which we classified as inconclusive. Of these, 66%

turned out to be failed according to our CSS, which is not surprising given our way of

calculating CSS involves multiple indicators, while case study authors often declare an

intervention to be successful based on one or few indicators.

Table 2: Comparison of author’s evaluation of success with our Composite Success

Score

Evaluation according to CSS

E v a l u a t i o n a

c c o r d i n g

t o c

a s e s

t u d y

a u t h o r s

Categories Successful Failed Total

Successful cases 15 1 16

Failed cases 0 26 26

Inconclusive cases 7 16 23

Total 22

(34%)

43

(66%)

65

(100%)

It is important to note however, that the high level of consistency between our

classifications of success and failure does not confirm the robustness of the evidence

itself. Given that we did not have the resources to verify the accuracy of the data and

conclusions drawn by case study authors via field research, our system of classification

instead distinguishes between ‘high’ and ‘low’ quality studies. In doing so we

acknowledge that many changes in scheme performance may have been misclassified

(by case study authors) due to methodological shortcomings.

3. Review of IMT/PIM interventions: What are the conditions under which

successful or at least promising WUAs in public irrigation systems are found?

Are those conditions replicable?

A primary aim of this review is to gain insights into how effective IMT interventions

work (or why they fail). To this end, we examined the relationship between a range of

descriptive attributes and rates of successful management transfer. By correlating

success and failure with individual scheme characteristics, we were not only able to



17

identify patterns of success but also, test some of the hypotheses put forward in the

literature on the determinants of successful management transfer. However, due to the

poor methodological quality of the majority of studies in the field, it is not possible to

make definitive conclusions about what matters and why in successful IMT

interventions. As a result some of the key arguments of the paper remain hypotheses

rather than conclusions and must be verified with extensive and robust field research

and analysis. However, a central argument of this paper – that imposing ‘blue-print,’

one-size fits all institutional models will not fix the complex and diverse management

problems of irrigation systems – remains a robust conclusion.

Degree of commercialisation: Success as a function of access to support services and

crop value

A core objective of IMT was to make irrigation schemes financially self-sufficient

however as argued by Veldwisch (2006), this objective has an implicit bias towards

commercialisation. In order for farmers to absorb O&M expenses the costs of self-

management must be a small proportion of their income (Vermillion, 1997; Shah et al

2002). Put simply, irrigated agriculture must produce enough economic benefits to

cover the economic and financial expense of farmer management. Often this requires

commercialisation.

To investigate the relationship (if any) between commercialisation and successful

management transfer we systematically documented farmers’ access to credit/markets

and crop value. Our results suggest that when output marketing systems are strong and

well developed and farmers have access to credit the chances of successful IMT increasesignificantly in African schemes. According to our system of classification, of those

African schemes with no or low access to input and output markets 92 % are failures. In

contrast, high access to credit and support services did not appear to have a strong

relationship with successful management transfer in Latin America. Rather, the highest

rates of success in the region were found in schemes where the degree of

commercialisation is varied (i.e. schemes served both commercial farms and emerging

or subsistence farmers). Indeed, our sample suggests that intra-scheme inequity in

terms of access to credit does not impede successful transfer in Latin America.

The divergent result in Africa and Latin America on this front may be the result of biases

in the literature. Of the African case studies which house both commercial and

historically disadvantaged farmers (HDF’s), 8 centred upon the perspectives of HDF’s

and as such there was greater emphasis on the legacies of historical inequity and their

continued influence in scheme performance. In Latin American case studies there is less

stress placed on the bifurcated structure of irrigated agriculture. Indeed, even though,

there are clear class divisions in the agricultural sectors of Mexico and Colombia and

these are often perpetuated in the structure and composition of WUAs, these

perspectives are rarely taken up by case study authors in their assessments of IMT

impacts.



18

The evidence from both Latin America and Africa also suggests that in most cases,

cultivating high value crops does not greatly increase the probability of success. Rather

in both regions, it appears that diversifying cropping systems (which include both high

and low value crops) are most positively correlated with successful management

transfer. Having said that, rates of failure in schemes which cultivate low value crops

were consistently high: at 91 % in Africa and 75% in Latin America.

Taken together, our evidence suggests that the relationship between commercialisation

and successful management transfer is mixed. It is important to consider these results

in context; in many small-holder African schemes the enabling environment for

commercialisation is often not in place, this is in part due to poor support services,

inaccessible and unaffordable credit, unreliable markets and poor marketing skills. In

the White Nile Pump Schemes (Sudan), for example, repressive state regulation of

cotton and wheat production (the dominant crops on the schemes) and poorly

developed private markets are a critical factor underpinning the sub-optimal

performance of these schemes (Samad et al. 1995). Similarly, in the Sepeteri and Itoikin

schemes of Nigeria, farmers associated the high risks of irrigated agriculture with low

credit availability and market access (Olubode-Awosola et al., 2005).

Moreover, prior to transfer small-holder irrigated farming in Africa was a highly capital-

intensive activity. Indeed, many small-holder schemes were only made financially viable

as the result of large government subsidies. As a result, the expectation that farmers are

capable of absorbing the costs of self-management (when these costs were a source of

budget deficits for many governments) is paradoxical unless it is accompanied by a

significant improvement in farmers’ livelihoods.

Capacity: Success as a function of pre-existing Farmers Organisations

In both Africa and Latin America, schemes that had farmer’s organizations prior to

transfer appear to succeed more often that those without. However, in the literature the

relationship between pre-existing organizations and successful management transfer is

not clear cut; sometimes WUAs were built on existing organizations (Mexico, white

commercial sector in South Africa, Dominican Republic), and sometimes they neglected

them all together (Mali). Moreover, even when pre-existing organizations become the

basis of WUAs, they sometimes reinforce pre-transfer power hierarchies and social

inequality. In Mexico for example, the IMT program was developed on an alreadyexisting, strong organizational base: the ejidos and the organizations of private growers.

However, more than ten years after the transfer process, ejido farmers continue to

complain that they lack the financial and political muscle to check the influence of large

landowners over the decision-making process (Wilder & Romero Lankao, 2006).

In spite of the post-transfer politicization of WUAs, the results of our study suggests that

pre-existing organizational strength, which we regard as a proxy f or farmers’



19

management capacity, impacts the likelihood of successful transfer. Moreover, we

argue that the high rate of failure among studies which did not have any pre-existing

organisations, 89%, reflects enduring capacity deficits especially in African small-holder

schemes. Indeed, in many cases, farmers were entirely excluded from management

decisions and often were dependant upon the central agency for farm management and

support services. For example, in the Sepeteri scheme (Nigeria) and Hindustan

Irrigation System (South Africa), the agency applied a strict system of management

under which the farmers and very little freedom of choice or control in crop

management, marketing, land tenure and other economically significant aspects of

irrigated agriculture (Olubode-Awosola et al, 2005; Tren and Schur, 2000). Ultimately,

farmers were responsible for little more than weeding and applying fertilizers to their

plots.

More broadly, the ‘capacity deficit’ or ‘dependency syndrome’ which is characteristic of

some African case studies highlights important contradictions in IMT policy. The way in

which the farmer participation concept has been applied in many locations often

implies that WUAs are designed to replace the government agency in scheme

management, at least at the tertiary level. However, in cases where farmers were

previously excluded from management decisions and where local leadership and

organisation have been crippled for decades, it is unrealistic to expect a culture of

collective management to take hold (Mukherji et al. 2009; Shah, 2002).

IMT interventions where there has been a long history of donor involvement are

similarly paradoxical. In the Musengezi schemes in Zimbabwe for example, farmers

viewed the turnover experiment as a game of finding the right savior to bail them out onoperation and maintenance costs. Horticultural companies, international donors and

politicians took turns in picking up the tab.7 As Bolding et al. (2003) suggest, farmers

internalized the idea that both the state and donor are responsible for bankrolling

cultivation and maintenance.

Stakes: success as a function of property rights and the importance of irrigated

agriculture

IMT/PIM policy was built upon the assumption that as farmers have the largest stake in

irrigation schemes, they have more incentive than a government agency to manage

these systems efficiently and sustainably. While this line of reasoning is suggestive, it presupposes that farmers are a homogenous group with harmonious interests. The

evidence from our review indicates that the stakes farmers have in scheme

management, which we measured by the importance of irrigated agriculture to

livelihoods and property rights, varies considerably across and within locations.

7 Farmers were not passive recipients of aid but rather exploited political competition in the area to settletheir debts and keep the scheme operational. See: Bolding et al. (2003): 197.



20

Our results indicate that in Africa the greater the importance of irrigated agriculture in

people’s livelihoods the greater the likelihood of success. According to our system of

classification 63% of schemes which were cultivated and managed by full-time farmers

succeded. This suggests that when farmers derive a substantial proportion of their

livelihoods from irrigated agriculture it builds their stake in self management and

increases the likelihood that they will commit time and resources to it .

The 100 % rate of failure among schemes where irrigated agriculture is not central to

livelihoods, also raises questions about the compatibility of IMT and part-time farming.

In many smallholder schemes, farmers depend on a variety of sources to earn a

livelihood, such as pensions, livestock and jobs in urban centres. In Strydkraal,

Krokodilheuvel, Wonderboom and Veeplaats (South Africa), for example, it is common

for men to work in mines, as farm labour for commercial farmers and in cities while

women cultivate the plots. For a majority of households in these schemes, off farm

income (pensions, labour, wages etc.) exceeds farm income.8 Farmers’ who derive their

incomes from diverse sources have a reduced stake in managing the system. The high

degree of failure among this group suggests this has important flow on effects in terms

of the time and resources that are committed to cultivation and scheme management.

Latin American case studies only offer fragmentary data on the importance of

agriculture in the livelihoods and farmers (only 33% of studies had data on this

indicator) and hence we could not use this information for analysis.

Property rights (both land and water) also provide important security and incentives

for farmers to invest in irrigation management. Insecure tenure, lack of crop choice,

rigid rental markets and the inability to offer land as collateral for obtaining credit,limits the time, materials and cash farmers are willing to commit to long term

development investments on their land (let alone in the scheme as a whole). Moreover,

insecure land rights restrict the incentive/ability for uninterested farmers to sell out,

and interested and capable ones to expand their holdings (Shah et al., 2002). For

example, in the small-holder pump schemes of Saga, Kourani-Baria I and II (Niger) the

precise ownership rights of irrigated lands remains unclear as scheme members cannot

sell their land (even if they wish to) but may be evicted from their land (against their

will) by the Water User Association (Abernethy et al, 2000). The issue of uncertain land

tenure arrangements also assumes a gendered dimension in Veeplaats irrigation

scheme (South Africa). Kamara et al (2002) note that well over 50% of farmers

currently cultivating plots (mostly women) do not have the Permission to Occupy (PTO)

registered in their name. Rather, titles are mostly in the names of men, creatingdisincentives for the actual farmers (women) on the scheme.

In Latin America land tenure is not a major institutional issue, indeed all of the schemes

in our sample had either high or mixed degrees of land rights and neither had a

significant relationship with success rates in the region. As a result many of the

8 For detailed analysis see: A.B. Kamara et al. (2002): 820.



21

challenges posed by insecure land rights in Africa (documented above) do not appear to

be relevant in the Latin American context. However, our results indicate that water

rights do appear to impact the extent to which farmers are willing to invest in collective

action for irrigation management (see Figure 17). Of the case studies which had clearly

defined water rights, almost 60% were from Mexico, and all successful cases (in Latin

America) with comprehensive rights were Mexican (thus our results on this front are

skewed by a regional bias and may also reflect other factors unique to the Mexican

case).

Indeed, our results on a number of indicators are biased by the strong representation of

Mexican schemes. As a result, it is difficult to tease out which factors matter most and

why. We can only assume that several factors may have influenced these positive

results. First, Mexico’s IMT program was initially concentrated in the large, commercial

areas of the North and Northwest where the concept of turnover had strong local

support. Five (out of a possible six) cases in our study were drawn from these areas and

thus our results from the country have a strong regional bias . Second, the IMT program

had high level political commitment (from the Office of the President), and as a result,

turnover was preceded by legislation (the national water law) which established water

rights and the legal status of WUAs. Finally, the speed and success of IMT in Mexico can

partly be explained by the high degree of social organization within the irrigation sector

prior to transfer. As mentioned earlier, users were mainly organized through the ejido,

production cooperatives, and farmer unions. WUAs were built upon these traditional

organizational lines and thus harnessed existing social capital or patterns of

cooperation. Most of these factors were highly correlated with successful transfer in

Latin American schemes (see Table 3). Only 45% of African case studies had data on

this indicator and thus comparative analysis on this front is not possible.

Taken together our results suggest that when farmers are heavily invested in scheme

management, either through property rights or because they derive their main source of

livelihoods from the scheme, the likelihood of successful transfer is high.

Process: Success as a function of implementing agency and level of transfer

As argued by Shah et al. (2002), the overwhelming majority of the literature on

IMT/PIM assumes that successful management transfer to user organizations is in

principle viable provided the ‘process’ is right (Vermillion 1996; Fredericksen and Vissia1998; FAO, 2007). Drawing on our rich database we were able to test this hypothesis by

analysing the relationship between the method and extent of devolution and rates of

successful management transfer.

Our results indicate that chances of success are significantly higher when NGOs or

donors assist the implementation of IMT/PIM policies. This finding was consistent



22

across Africa and Latin America (and Asia).9 For instance, in the case of a pilot WUA

within the Gezira Scheme (Sudan), farmers benefited from extensive donor and

government funds and intensive capacity building by national consultants and

international organisations such as, FAO and the World Bank . It is important to note

that the areas chosen as pilot sites for IMT are by no means representative of irrigation

farming communities in Africa as a whole. For example, farmers identified for the pilot

project in Gezira had well defined land rights; were located in proximity to trainers and

consultants (Sudan Gezira Board headquarters), and had above average levels of

education. In addition the pilot site was identified based on high average production

levels (prior to transfer, the average yield of the pilot site was 16% above the scheme

average), adequate water supply, and absence of socio-economic constraints (Hussein,

2006).

As part of the project, farmers were trained for 3 hours a week throughout the season

on maintenance of minor canals, water management and to some extent in matters such

as cropping systems, animal husbandry, marketing and accounts keeping. Training also

stressed equity in distribution along minor canals. At the field level, over 900 training

sessions were held through 12 Farmers Field Schools (FFS). FAO also established a

Revolving Fund in the first season ($15,000) which was used to procure fertilizers and

seeds. Abdelhadi et al. (2004), further attributes the success of the Gezira pilot project

to farmers’ accumulated ‘experience in technology transfer.’ Put simply, farmers in pilot

areas had prior training through the auspices of another project (Integrated Pest

Management Research and Training Centre (IPMRTC) and FAO had been training

farmers in the project area through field schools since 1993).

In contexts such as these, it is very likely that NGO assisted implementation produced

favourable outcomes, especially vis-a-vis comparable schemes who did not benefit from

similar long-term investments in capacity building. However, many factors that shaped

the success of this particular case have their roots in pre-transfer processes and trends.

Thus, similar results cannot be expected in other blocks of the same scheme (the

majority of which do not share these traits) let alone in entirely different systems which

are costly to run, suffer from technical problems, dilapidated infrastructure and

poverty, have lower productivity levels and are unable to collect adequate irrigation

fees from farmers to cover O&M.

Moreover, because the pilot experience was so process intensive it difficult and costly to

replicate on a mass scale. More broadly, NGO involvement in IMT/PIM implementation

has been highly localized and rarely produces reform beyond a very local scale

(Shashidharan 2000). Finally, in our sample the majority of the NGO assisted case

studies were short-term impact assessments and therefore may not capture the actual

management capacities of farmers or the sustainability of NGO-donor investments in

capacity building etc.

9 See Mukherji et al, (2009).



23

In Latin America, there was also a 100 per cent success rate amongst IMT programs

initiated by farmers. However, the four studies in question (Coello Irrigation District,

Saldana Irrigation District, A.U.P.A Culiacancito WUA and Productores Agrícolas

Asociados, A.C WUA) are exceptional cases in which existing farmer cooperatives were

well organized and were motivated by a strong belief that they could administer

schemes more efficiently than the government. Indeed in Coello and Saldana (Colombia)

high de facto farmer participation in irrigation management existed prior to transfer

and the schemes were already highly profitable. Both cases are from a relatively

prosperous farming area, where agriculture and agro-business are the mainstream of

the local economy. In short, these case studies share the ‘double coincidence of need

and capacity’.

The extent of devolution varies significantly across and within locations as do the roles

of farmers and irrigation agencies in O&M. Our sample contains a mix of IMT models, in

which either total or partial management authority is devolved at one of the following

hydraulic levels: headworks, subsystem, main/branch or distributary. Our results show

that the hydraulic level transferred does not have any bearing on success rates but

partial O&M transfer is more likely to succeed that total O&M transfer. This is consistent

with earlier findings that suggest continued agency involvement in O&M is sometimes

necessary, especially in contexts where there is a significant capacity shortfall. On the

whole however, it is difficult to make clear distinctions between farmer and agency

management in many post-transfer systems. Rather, in cases of total O&M transfer, the

agency is still involved in systems management at higher hydraulic levels (our sample,

includes only one case in which management of headworks were transferred to

farmers). According to Aw and Diemer (2005), many of the inefficiencies of farmer

management at the distributary level can be traced to main system managers, who fail

to deliver reliable water supplies in predictable schedules at the outlets. In such cases,

power continues to be vested outside WUAs, technically in the main system and

institutionally with the Irrigation Agency (Narain, 2008).

So while one to one correlation indicates that the ‘right process’ is an important factor

determining success, it may not be sufficient to explain performance outcomes,

especially in the African small-holder context. Our results suggest that the relationship

between ‘process’ and successful transfer is mediated by other factors. In the small-

holder schemes of Africa, for example, irrigated farming faces an ‘entire complex of

constraints’ which prevents effective farmer management (many discussed above, such

as market access, property rights and low incomes and productivity).10 Indeed, in manycase studies, income per household remains too low to meet all subsistence

requirements let alone generate the surplus needed for development (Shah et al. 2002).

In situations such as these the method and extent of devolution do not address the true

10 Shah et al. refer to these constraints as downward ratchets or multiple constraints which disable poorpeople “like movements down past a cog which are difficult or impossible to reverse, making poor people

permanently poorer.” (Chambers 1983: 115).



24

causes of sub-optimal performance. This requires support systems that extend beyond

irrigation and which significantly enhance farmers’ livelihoods.

Technical Specifications: Success as a function of the size of system and type of

scheme

A common assumption underpinning the literature on common pool resources (CPR) is

that small sized systems with well defined boundaries are more amenable to

cooperative management.11 This idea draws strength from the endurance of many

traditional self-governed irrigation systems (FMIS) which are well bounded in terms of

both physical infrastructure and scheme membership. However, our results indicate

that irrigation systems which were constructed and formerly managed by the state do

not conform to the hypothesis put forward in CPR literature. On the contrary, in our

sample the likelihood of success does not vary much according to size, if anything

smaller systems are slightly more likely to fail. According to our system of classification,

small and medium-large systems in Africa had failure rates of 85% and 58%

respectively.

In particular, cooperative farmer management has failed to make a mark in small‐holder

farming contexts of Africa. This inconsistency stems from fundamental differences in

the socio-technical conditions and organisational characteristics of WUAs vis-à-vis

farmer organisation under FMIS. As Mukherji et al (2009) argue the ‘farmerparticipation concept’ and ‘culture of irrigation’ common to FMIS is not easily

reproduced in government management systems. This is because there are significant

differences of design and socio-technical complexity between government systems and

FMIS. Indeed, in Africa many irrigation sites were designed based on politico-social

rather than technical rationales (i.e. African irrigation schemes provided the means to

realize food self sufficiency and/or a policy of segregated development, with much less

attention paid to their commercial viability). In addition, small-holder farming in Africa

under agency-management was highly mechanized. The ARDC in South Africa for

example, used heavy equipment for ploughing, land preparation, spraying and

harvesting (Shah et al. 2002). The transfer to farmer management has significantly

increased the cost of hiring farm equipment which has reduced the profitability and

increased the risks of small-holder farming. Thus, the poor design of the majority of smallholder schemes exposes a central contradiction in IMT policy: farmers are now

being called upon to manage expensive and complex outfits that were never meant to be

run by farmers.

11 Refer to: Agrawal (2001); Wade (1988); Ostrom (1990) and Baland and Platteau (1996).



25

The mismatch between IMT models and farmers’ managerial and financial capacities

appears to have serious implications for rates and success and failure, especially in the

African context. For instance, the high rate of failure among African pump schemes,

82%, in our sample is largely due to the high cost of energy (following the removal of

government subsides) and pump maintenance or repair. In an analysis of four

smallholder pump schemes in Niger, Shah et al. (2002) note that turned over pump

schemes almost always leave farmers in the red as net income is 20-25 per cent of gross

income and irrigation fees are as high as 15-20 per cent of gross income. Similarly, in

Senegal Valley’s small-scale schemes, rundown pumps coupled with high energy and

maintenance costs have resulted in the suboptimal performance of pump schemes

(Wester et al, 1995).12 In particular, higher input prices and the greater complexity of

dry season irrigation after management transfer in the Doue Region, lead farmers toalter their cultivation patterns and focus on wet season crops. In short, low farm

productivity and income prevents many African smallholders from taking advantage of

the managerial advantages and better water control offered by high cost pump schemes.

In Latin American pump schemes, high energy and maintenance costs have also led to

sub-optimal results across key performance indicators. In the case of Roldanillo-Union-

Toro (RUT), for instance, the total cost of irrigation is relatively high due to two-stage

pumping. The financial viability of the scheme, prior to transfer, was assured by large

government subsidies which covered 60-80% of total costs. When the government

eliminated subsidies to the agriculture sector and halted its expenditures for O&M in

the scheme, farmers struggled to absorb the high pumping costs involved in irrigated

farming. As Vermillion and Garcés-Restrepo note, ‘over 6 years after transfer, total

farmer payments declined in real terms by 22 per cent, from US$83 to US$65 per

hectare by 1995. This was due to both a decline in fee-collection rate, from above 90 per

cent before transfer to less than 70 per cent by 1995 and a reduction in the amount of

water delivered per hectare’ (1998: 13). The decline of RUT’s financial solvency appears

to be attributable to its high cost and the sudden loss of substantial subsidies from the

government.

Samacá irrigation district (Columbia) followed a similar trajectory post-transfer. It was

also a high-cost system previously sustained by generous government subsidies, which

witnessed substantial cuts in O&M expenditure and declines in irrigation fee collection

rates following IMT. In contrast, low cost Rio Recio was able to sustain financial

solvency for the first 5 years after transfer and dramatically increase fee collection

rates. The O&M budget remained at virtually the same pre-transfer level for severalyears after transfer.

Qualitative review of failed cases suggests that if a scheme is financially viable prior to

transfer, it is likely to financially viable following transfer. If however, pre-transfer

12 Farmers had to travel 350km to Saint -Louis or 650km to Dakar to obtain spare parts needed for pumprepair.



26

viability depends of significant government inputs, then farmers must be able to absorb

the costs of irrigated farming by cross-subsidising irrigation costs.13

Table X: Frequency distribution of descriptive indicators

DESCRIPTIVE INDICATOR

AFRICA LATIN AMERICA

% of data available % of data available

Type of scheme 98 100

Size of scheme 97 100

Scheme complexity 85 94

Age of the scheme 70 67

Crop systems (high/low value) 88 89

Crop Systems (Paddy/non Paddy) 97 94

Population served by the scheme 65 44

Physical water scarcity 80 100

GDP/capita (PPP US$) 100 100

Access to support services 83 72 Importance of agriculture in people'slivelihood 87 33

Social cohesion 55 44

Well defined water rights 45 94

Land rights 83 89

Average size of land holding 68 33 Year of transfer/formation of WUA/initiation of PIM 82 89

Highest hydraulic level transferred 70 72

Amount of O&M authority transferred 98 100

Implementer 100 100

Rehabilitation before or during transfer 68 72

Training and capacity building 58 61 Farmer's organization created beforethe transfer 73 100

Strong political will 52 83 Supporting legislation before thetransfer 47 83

WUA Chairman are elected 75 94

13 This was done in Coello, Colombia by diversifying revenue sources after transfer, including equipment rental, interest from small loans, provision of fertilizers and agro-chemicals etc.). See: Garcés-Restrepoand Johnson III (1997).



27



28

Table X: Contextual factors correlated with successful IMT/PIM

AFRICA

TYPE OF SCHEME SIZE OF SCHEME SCHEME

COMPLEXITY CROP SYSTEMS CROP VALUE

Diversion Pump

and Lift Storage Mixed Small Medium

and Large Simple Complex Paddy Non-

Paddy High Low Mixed

Percentagesuccessful

Percentage FailedTotal number of cases

PHYSICAL WATER

SCARCITY

ACCESS TO SUPPORT

SERVICES

IMPORTANCE OF

AGRICULTURE IN PEOPLE'S

LIVELIHOOD

WELL DEFINED

WATER RIGHTS LAND RIGHTS

High Low Mixed High Low Mixed High Low Mixed High Low High Low Mixed





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AFRICA

HIGHEST HYDRAULIC LEVEL TRANSFERRED

AMOUNT OF

O&M

AUTHORITY

TRANSFERRED

IMPLEMENTER REHAB TRAINING

Headworks Main/Branch Subsystems Distributary

Partial Total Donor/NGOAssisted

Gov Farmers Yes No Yes No


Percentage Failed

Total number of cases

FARMER'S ORGANIZATION

CREATED BEFORE THE

TRANSFER

STRONG POLITICAL WILL

SUPPORTING LEGISLATION

BEFORE THE TRANSFER WUA CHAIRMAN ARE ELECTED

YesNo Yes No Yes No Yes Low





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Table 5: Logit estimates (40 observations from Africa); Dependant v ariable: SUCCESS

Logit estimates Number of obs = 40LR chi2(7) = 36.09Prob > chi2 = 0.0000

Log likelihood = -9.2293616 Pseudo R2 = 0.6616

------------------------------------------------------------------------------success_sc~s | Coef. Std. Err. z P>|z| [95% Conf. Interval]-------------+----------------------------------------------------------------scheme_type | .816976 1.934049 0.42 0.673 -2.97369 4.607642scheme_size | -.4322562 1.705611 -0.25 0.800 -3.775192 2.910679crop_value | .2825835 1.659349 0.17 0.865 -2.96968 3.534847crop_type | 1.388716 1.904762 0.73 0.466 -2.344549 5.121981

acess_credit | 3.29745 1.813107 1.82* 0.069 -.256174 6.851074landrights | 3.437275 1.529967 2.25* 0.025 .4385957 6.435954Implementer | 4.084172 2.312326 1.77* 0.077 -.4479038 8.616248

_cons | -7.047084 3.61534 -1.95* 0.051 -14.13302 .038852------------------------------------------------------------------------------

From this model, we comment only on the variables that are significant. In this case,

high access to credit/markets, well defined land rights and NGO-assisted

implementation are significant at 10% levels. The model correctly predicts in 92% of

cases.

Following this, the marginal effects model was also estimated. This model shows how

much the probability of success changes when various independent variables change

from 0 to 1

Table 6: Marginal effects model

Marginal effects after logity = Pr(success_scores) (predict)

= .21811936------------------------------------------------------------------------------variable | dy/dx Std. Err. z P>|z| [ 95% C.I. ] X---------+--------------------------------------------------------------------schem~pe*| .1423305 .34043 0.42 0.676 -.524898 .809559 .45schem~ze*| -.0701373 .26589 -0.26 0.792 -.591271 .450996 .3crop_v~e*| .0512344 .3079 0.17 0.868 -.552248 .654717 .1crop_t~e*| .1767934 .20553 0.86 0.390 -.226038 .579625 .85acess_~t*| .6516267 .24434 2.67* 0.008 .172736 1.13052 .275landri~s*| .6210161 .22622 2.75* 0.006 .177633 1.0644 .4implemen*| .647597 .22287 2.91* 0.004 .210779 1.08442 .5------------------------------------------------------------------------------

(*) dy/dx is for discrete change of dummy variable from 0 to 1

The marginal effects model shows that for a discrete change in type of scheme from 0 to

1, the probability of success increases by 0.14 units. For discrete changes in access to

credit, landrights and implementing agency from 0 to 1 (i.e. from low to high; or from

government to donor-NGO assisted) the probability of success increases by more than

0.62 units and this is significant at 1%.

We also predicted the logs odds ratio, our results are given below.



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Table 7: Logs odds ratio



------------------------------------------------------------------------------success_sc~s | Odds Ratio Std. Err. z P>|z| [95% Conf. Interval]-------------+----------------------------------------------------------------scheme_type | 2.263644 4.377999 0.42 0.673 .0511143 100.2475scheme_size | .6490431 1.107015 -0.25 0.800 .0229327 18.36927crop_value | 1.326553 2.201213 0.17 0.865 .0513197 34.28978crop_type | 4.009698 7.63752 0.73 0.466 .0958905 167.6671

acess_credit | 27.04359 49.03291 1.82 0.069 .7740073 944.8949landrights | 31.10209 47.58516 2.25 0.025 1.550528 623.8777implementer | 59.39275 137.3354 1.77 0.077 .6389662 5520.634

------------------------------------------------------------------------------

This model shows that for one unit increase (or in this case, a change from 0 to 1) in

type of scheme, the odds of success increase by a factor of 2.26. For a change in

implementer (from 0 to 1) that is from government to NGO assisted, the odds of success

increase by a factor of 59.39.

Lastly, we ran a simple test to see if the model is specified correctly. Through this test

we can determine if any other significant variable has been left out of our analysis.

Table 8: Link test



------------------------------------------------------------------------------success_sc~s | Coef. Std. Err. z P>|z| [95% Conf. Interval]-------------+----------------------------------------------------------------

_hat | .9941093 .352405 2.82 0.005 .3034082 1.68481_hatsq | -.0130492 .1252164 -0.10 0.917 -.2584688 .2323703_cons | .0449714 .7504288 0.06 0.952 -1.425842 1.515785

------------------------------------------------------------------------------

The results show that the model is correctly specified in the sense that no variable

which can significantly influence the probabilities has been left out. This is because the

“_hat ” is significant but ‘_hatsq’ is not significant. This is an indication of correct model

specification.

From this analysis three factors consistently appear to influence the probability of successful management transfer in Africa, these are high access to credit/markets, well

defined land rights and NGO assisted implementation. The other variables do not

appear to be significant.

***********************



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Taken together, our analysis suggests that the results of management transfer, across

and within Latin America and Africa, are mixed. In the African context, schemes which

have high access to credit/markets, large stakes in irrigated agriculture, and which

benefited from a NGO-Donor assisted implementation process are most amenable to

successful management transfer. In Latin America, water rights, farmers’ organisational

capacity and political commitment at the highest levels of government were all

positively correlated with success. Thus, our analysis makes plain that what matters in

Africa is not always relevant in Latin America and vice versa. It also suggests that some

factors may be so critical to successful transfer (i.e. the ability to absorb the costs of

management) that they impact the significance of others (i.e. type and size of scheme).

Moreover, our results indicate that there is great variation in terms of the maturity and

functionality of schemes earmarked for IMT/PIM interventions. Different phases of

political, administrative and institutional development shape the maturity and

functionality of WUAs, which in turn determines the modes and outcomes of PIM that

are realistic at the present moment. It follows then that there is not a sole IMT/PIM

model that can be replicated across locations and that context shapes the scope for

change and as a result institutions that are effective in some places (Northern Mexico)

cannot be transplanted or socially engineered in another environment (smallholder

irrigation sectors of Africa) with the same outcome. In the case of the latter it may be

neither necessary nor possible to create and sustain formal local organisations focused

on irrigation management, such as WUAs. Rather as Srivastava and Brewer argue ‘in

societies characterised by diversified livelihoods and marginally profitable irrigated

agriculture, it may not be worthwhile for farmers to invest heavily in management

associations’ (1994:15). In such contexts, adapting existing multipurpose local

organisations, like village based administrative units, Farmers Organisations or

traditional water operators to manage irrigation may be the more sustainable and

effective option.

Conclusions

The lessons that emerge from our review are multi-fold. First, although the literature on

IMT/PIM is extensive, the evidence linking improvements in scheme performance to

management transfer is far from compelling. Our study highlights important limitations

of existing impact assessments, particularly their heavy reliance on post-intervention

data to infer cause and effect. It also highlights the value of high quality studies (with

both a strong comparison group and pre-and post-intervention data) and long-termimpact assessments for making credible, generalizable conclusions about what works,

where and why.

We also contribute new insights into which socio-economic and technical mechanisms

appear to be active in successful management transfer. In both qualitative and

quantitative review of African case studies three factors were consistently correlated

with successful IMT/PIM, these are credit and market access, property rights and NGO-



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donor assisted implementation. In Latin America, governance issues such as

organizational structure and water rights increased the likelihood of successful

management transfer. Our research suggests that at least in the African context, the IMT

process needs to be accompanied by greater interventions, relating to land reform,

market access, and other support services which will help farmers increase their

livelihoods and consequently their ability to absorb the costs and responsibilities of

management.

Our analysis also indicates that management transfer, in itself, rarely produces

significant changes in the quality of financial management or technical efficiency. In the

dynamic agrarian sectors of Africa and Latin America the transition to famer

management was smooth, effortless and in many cases merely formalised the status

quo.14 In the overwhelming majority of systems however, transfer takes place in a

context of moderate dynamism and poverty.15 Here, the causes of sub-optimal scheme

performance rarely lie in the degree or intensity of farmer participation but rather,

reflect design flaws, problems of market access and property rights, land

fragmentation, the low profitability and productivity of irrigated agriculture, unstable

water supply and unequal water distribution. Unless, the actual causes of poor

performance are understood and addressed reform of the public irrigation sector will

remain only a piecemeal affair, as it has been so far

14 Examples include Coello and Saldana (Colombia), A.U.P.A Culiacancito WUA and Productores AgrícolasAsociados, A.C WUA (Mexico) and the white, commercial farms of South Africa and Zambia)15 Examples include most African small holder schemes , Maria La Baja (Columbia) Yaque del NorteProject (Dominican Republic)

africa-latin america article

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