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Organization and Performance of Cotton Sectors in Africa ... - infoDev

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■■works by companies agree<strong>in</strong>g on an open<strong>in</strong>g price, based on a cautious estimate<strong>of</strong> the company’s costs <strong>and</strong> desired pr<strong>of</strong>its, with market competitionthen driv<strong>in</strong>g the price up as the season progresses. The open<strong>in</strong>g price is notheavily affected by the season, but when the harvest is good, the price willbe driven up less than <strong>in</strong> a drought season when companies are desperatefor seed cotton to fulfill contracts. Thus, when one <strong>in</strong> adjustes prices toreflect a good season, the average price received by the top producers (whosell more <strong>of</strong> their product late <strong>in</strong> the season) is lowered by more than theaverage price received by the poorer producers (who are forced to sell much<strong>of</strong> their product as soon as the season opens to meet press<strong>in</strong>g cash needs).In Mozambique, budgets were constructed for four groups <strong>of</strong> farmers. Anationally representative annual household survey allows the distribution<strong>of</strong> cotton yields <strong>in</strong> both 2004/05 (a drought year) <strong>and</strong> 2005/06 (a good ra<strong>in</strong>fallyear) to be exam<strong>in</strong>ed. The national yield spread is roughly mirrored bythe follow<strong>in</strong>g comb<strong>in</strong>ation <strong>of</strong> focus group budgets: 2005/06—group 1 (40percent), group 2 (20 percent), group 4 (40 percent); 2004/05—group 1 (20percent), group 3 (20 percent), group 4 (60 percent). Unlike the case <strong>of</strong> acompetitive cotton sector such as Tanzania’s, however, prices <strong>in</strong> Mozambiquevary less between good <strong>and</strong> bad seasons. This book, therefore, considersjust one scenario (figures 10.5 <strong>and</strong> 10.7), <strong>in</strong> which the balance <strong>of</strong> producersacross groups is assumed to be as follows: group 1 (5 percent), group2 (25 percent), group 3 (30 percent), group 4 (40 percent).In Mali, <strong>in</strong>formation on actual yields for the period 2004 to 2006 <strong>in</strong> the villageswhere focus group discussions were held was available from the localextension agent. The average village-level yield was similar to the averagenational yield (approximately 1,100 kg/ha), but it was higher than theweighted average yield generated by focus group discussions (approximately1,000 kg/ha). For the budgets, therefore, the yields reported by thefocus groups were adjusted upward by 10 percent.Distribution <strong>of</strong> Producers across GroupsFigure 10.5 shows estimates <strong>of</strong> the proportion <strong>of</strong> cotton farmers found with<strong>in</strong>each group. These figures were determ<strong>in</strong>ed <strong>in</strong> a number <strong>of</strong> ways. In Mali,Zambia, <strong>and</strong> Zimbabwe, the numbers were taken from the focus group exercises.In these countries, all farmers from each village were assigned to onegroup or another. The data are thus strictly representative <strong>of</strong> the focus groupvillages <strong>and</strong> at best are only illustrative <strong>of</strong> the country more widely. Yet <strong>in</strong> eachcase, the weighted average yield figures that resulted from these proportionsare plausible <strong>in</strong> light <strong>of</strong> other <strong>in</strong>formation for the country. In Burk<strong>in</strong>a Faso<strong>and</strong> Cameroon, the data were from monitor<strong>in</strong>g reports by SOFITEX <strong>and</strong>SODECOTON, respectively. In Tanzania, the numbers were taken from a 2004cotton farmer survey (Maro <strong>and</strong> Poulton 2005), while those <strong>in</strong> Mozambique136 POULTON, LABASTE, AND BOUGHTON

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