Performance Outcomes

The WUA reforms in Uzbekistan are an attempt to use local, collaborative institutions to improve both crop productivity and environmental sustainability. To get at policy performance for crops, we used 2001, a year prior to the establishment of any of the WUA institutions, and compared it to 2004, the latest year for which data was available on crop outputs, number of hectare planted, and the costs of crop production. The research team focused primarily on the

Table 16.2 Sources of Data for Framework Variables

Institutional "Functionality" variable

Degree of structure

WUA Chairman surveys/focus group,

cross-checked against WUA

member surveys

WUA meetings frequency

WUA Chairman surveys/focus group,

cross-checked against WUA

member surveys

Involve membership in decision

Participation index from WUA

making?

member surveys

Make and implement "major"

WUA Chairman and WUA Member

decisions?

surveys

Physical wealth-

Land/soil resources

Expert estimates from TIIM/WUA

Chairman surveys/focus group

Water resources, availability of

Volume/precipitation

Expert estimates from TIIM/WUA

Chairman surveys/focus group

Access — location on canal

WUA Chairman surveys/focus group

Economics

Wealth of surrounding area

Expert estimates from TIIM/WUA

Chairman surveys/focus group

Access to "outside" resource

WUA member surveys

Social Capital/Democratization

Social capital—Three trust indexes

WUA member surveys

Egalitarian decision-making index

WUA member surveys

Accountability index

WUA member surveys

two major crops in Uzbekistan, cotton and wheat, with attention given to corn (maize) in two cases. The crop productivity function is developed by first taking the rate of productivity (in centners per hectare)* for 2004 and dividing that rate by the rate of productivity for 2001. This gives a measure of how much crop production increased or decreased on a centner/hectare basis. Second, the cost measure is developed in the same way. The costs of crop production for 2004 are calculated on a cost per centner basis, and this cost function is then compared to 2001's, using division (2004 cost function divided by the 2001 cost function). Third, the increases (or decreases) in crop productivity are then divided by the increases (or decreases) in the cost of production function to arrive at the cumulative productivity measure. Ratings above "one" indicate that a WUA has met the goals of the WUA policy reform for agricultural productivity across all the crops in the survey. Ratings below one signal a decline in productivity. Finally, the cumulative productivity scores are weighted to reflect the dominance

* Centners are the basic measure of weight used in Central Asian agriculture, much like bushels in the U.S.

Table 16.3 Crop Productivity by WUA

WUA Name

RANK

Cumulative Productivitya

Cotton

Wheat

Maize

Aganay

4th

0.86

0.845c

0.874c

N/A

Amir Temur

3rd

1.72

2.477b

1.186c

0.672b

Berdakh

1st

2.49

2.064c

2.914c

N/A

Dnepr Kama

5th

0.77

0.853b

0.647b

N/A

Jambul

6th

0.62

N/A

0.618c

N/A

Oq Oltin

7th

0.60

0.752c

0.442c

N/A

Tulkun

2nd

1.91

1.289b

2.563b

1.769b

a Inflation for 2002 (7.6%) and 2003 (2.8%) is factored into these figures. Source for inflation data is the National Bank of Uzbekistan.

b Sole source of crop planting, production and cost data are the individual WUA farmer /member surveys.

c Crop planting, production and cost data are derived from both the individual WUA farmer/member surveys and the examination of WUA records.

a Inflation for 2002 (7.6%) and 2003 (2.8%) is factored into these figures. Source for inflation data is the National Bank of Uzbekistan.

b Sole source of crop planting, production and cost data are the individual WUA farmer /member surveys.

c Crop planting, production and cost data are derived from both the individual WUA farmer/member surveys and the examination of WUA records.

of cotton and wheat.* (See Appendix A for all planting, harvest, and cost data for each crop and each WUA.)

When it comes to cumulative crop agricultural productivity, three WUAs show strong gains—Berdakh with a score of 2.49, Tulkun with a score of 1.91, and Amir Temur, which scores a 1.72 (see Table 16.3). Yet the other four WUAs suffer productivity declines, with Aganay, in the Tashkent region, showing a slight decline all the way down to Oq Oltin, in the Fergana Valley, where the decline is significant, particularly for wheat.

To understand the picture better requires digging into some of the specifics of each case. For example, many of the cases showed large to massive increases of hectares planted, even to the point of quintupling the planting area for cotton in Aganay, Amir Temur, Berdakh, and two other cases (see Appendix I). This suggests that the WUA reforms were responsible, at least in part, for unleashing latent farming demand in which additional opportunities for planting crops afforded by the reforms were fully embraced by Uzbek farmers. Thus, while productivity declined in some WUAs, overall WUA farmers were in a better position because the added increases in planted areas more than made up for the losses in per hectare production rates. A generous reading of such an outcome might claim that what appears to be a lack of success in meeting the WUA reform "productivity" goal, i.e., less efficiency, simply masks the larger picture, which is that of more economically successful WUA farming enterprises. At the same time, in the case of Jambul, Tashkent region, the original wheat production rate was high (relative to other Uzbek WUAs) and increased by 25% from 2001 to 2004. The overall cumulative productivity number, however, showed a decline because these farmers, much more so than others, experienced trouble keeping their

* Cotton and wheat are factored together at 90% of total crop production for each WUA. Added crops, if any, are weighted at 10% of total production. If there are no other crops than cotton and wheat, then their combined weighted score equals 100%.

production costs under control. Their costs for producing the wheat more than doubled. Further, the Aganay case started with high levels of productivity for both cotton and wheat relative to other WUAs, and while suffering a slight productivity decline (0.86), still maintained levels of production per hectare that were second only to Amir Temur in cotton production and much higher than other WUAs for wheat (the next closest WUA produced at a rate fully 18% less). The Fergana Valley WUA, Oq Oltin was in a similar situation—the WUA farmers were already quite productive in 2001 and so, while their productivity did slide significantly due to increasing costs, they were still producing more crops/hectare for both wheat and cotton in 2004 than the base year of 2001, and more crops/hectare than four of the seven surveyed WUAs in 2004. The Aganay and Oq Oltin outcomes may suggest that high performing agricultural areas prior to the reforms had the least to gain from any institutional changes, especially in the case of Oq Oltin, where the farming tradition extends back several thousand years. They know how to farm, regardless of whatever institution is organizing their efforts (Table 16.3).

WUA performance in the area of environmental sustainability is the other public policy outcome of interest to the Uzbek government and to this research. Farmer/members were asked a series of questions after being read the following statement: "My next questions concern environmental sustainability. As you no doubt know, the idea of environmental sustainability is that decisions taken today will maintain or promote a healthy natural environment both now and into the future." By asking three questions specific to environmental quality in the areas of the overall natural environment, the quality of water resources, and the quality of land resources, we established that the perceived overall trend in environmental conditions for all seven "WUAs was positive from 2001 to 2004. Each question asked the farmer/members whether each particular item had (a) improved a great deal, (b) improved a little bit, (c) stayed the same, (d) become a little bit worse, or (e) become a lot worse.* The composite scores for these three questions showed that even in the weakest scoring WUA, Dnepr Kama, over half (55.5%) of the respondents perceived positive improvements (improved a great deal or improved a little bit) for environmental sustainability, while the strongest score of 72% came from the Oq Oltin WUA. This means that, generally speaking, the environmental goals of the legislation are being met in these seven cases.

Yet these results are not necessarily tied to the formation and practices of the WUAs. The more important policy question is whether, from the perspective of the farmer/members, the new WUAs are either promoting or deterring environmental sustainability. We assessed the effects of the WUAs using the following question and response set:

* We asked these questions for the purpose of establishing overall trends and to give us a better perspective for interpreting the results from the "WUA formation and practices" question. For example, we wanted to make sure that if the farmer/members believed strongly that WUAs were contributing to an improved ability to achieve environmental sustainability, yet the local environment in a particular case was getting much worse, then we would know that any positive effects of the new WUAs would be largely meaningless from the perspective of overall environmental sustainability.

Table 16.4 WUA Environmental Sustainability Scores

Rank

Environmental Sustainability Score

Positive

Negative

No Effect

Don't Know

Aganay

5

0.592

43.2

4.1

25.7

27.0

Amir Temur

7

0.364

26.1

2.2

43.5

28.3

Berdakh

2

0.875

56.8

2.7

5.4

35.1

Dnepr Kama

3

0.691

50.7

0.0

22.7

26.7

Jambul

4

0.689

55.4

5.4

19.6

19.6

Oq Oltin (Fergana)

1

0.939

43.8

0.0

2.7

53.4

Tulkun

6

0.411

25.9

0.0

37.0

37.0

Q82. What has been the effect of the formation and practices of the WUA on environmental sustainability in your area? Would you say a.

□ Positive effect or a

□ Negative effect

□ No effect (volunteered)

Table 16.4 shows that three of the seven WUAs—Berdakh, Jambul, and Dnepr Kama—had more than an absolute majority of respondents giving the WUAs a "positive effects" score, while only four WUAs scored any negative responses, with all such scores at extremely low levels (from 2.2 to 5.4%). We extrapolated from these results to develop an "environmental sustainability" score and rank for each WUAs by focusing on only those farmer/members able to make an active assessment—members who felt they knew enough to respond—of the impact of their WUA on environmental sustainability (i.e., we excluded those who responded "Don't Know"). The outcome scores reflect the number, or percentage, of respondents crediting their WUA with a "positive effect" in relation to the total number, or percentage, of "active" respondents scoring their WUAs as having a "positive," "negative," or "no effect" on sustainability. For example, 56.8% of all respondents in Berdakh gave their WUA a positive score, out of a total of 64.9% of active respondents. This translates into an environmental sustainability score of 87.5%, the second strongest sustainability score among the seven cases (Table 16.4).

In order to set up the comparative analysis between the institutional functionality, physical wealth, and informal institutional frameworks, we combined the agricultural productivity and environmental sustainability scores into a single measure giving each score equal weight.* (See Table 16.5.) The single measure is comprised of the sustainability scores in their present form (a 0-1 scale) and the productivity scores after being standardized to the

* Others may think that the two measures deserve different weightings. We chose equal weighting given that the Uzbek legislation was intent on achieving both outcomes simultaneously.

Table 16.5 WUA Policy Performance Scores and Ranks

Agricultural Productivity Score

Environmental Sustainability Score

Total Score

Final Rank

Aganay

0.324

0.592

0.916

7th

Amir Temur

0.647

0.364

1.011

4th

Berdakh

0.939

0.875

1.814

1st

Dnepr Kama

0.291

0.690

0.981

5th

Jambul

0.233

0.689

0.922

6th

Oq Oltin

0.225

0.940

1.165

2nd

Tulkun

0.720

0.411

1.132

3rd

same zero to one scale.* The two scores were then added for the final combined measure and ranking (see Table 16.5). Unsurprisingly, Berdakh ranked first overall given strong scores for both the environment and crop productivity (1.814 out of a possible 2), and Aganay, with relatively weak scores on both counts, especially for crop productivity, ranked last among the seven WUAs. Oq Oltin in the Fergana Valley ended up in second place given their extremely strong environmental sustainability score and despite productivity scores that actually reflected declining productivity from 2001 to 2004. Tulkun, with a third place rank, reversed the Oq Oltin situation, scoring well for productivity, yet with a relatively low environmental score—reflecting the fact that the most Tulkun farmer/members do not believe the WUA is having a positive effect on environmental sustainability.

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