Rural Development Policies and Sustainable Land Use in the ...

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64 CHAPTER 5 Table 5.5—Continued Incorporate No burning Minimum/zero tillage crop residues Standard Standard Standard Explanatory variable Coefficient error Coefficient error Coefficient error Prior investments on parcel Stone wall 1.08242*** 0.36211 0.24601 0.41272 1.22839*** 0.42266 Live barrier or fence 0.66462** 0.29597 0.81895*** 0.28247 –0.55983* 0.28509 Trees planted –0.77211*** 0.27057 0.83221** 0.32330 –0.39188 0.46935 Land use in 1999 (proportion of parcel area; cf. basic grains) Other annual crops –3.32715*** 1.05913 –1.61588** 0.76402 0.35532 0.61075 Coffee –1.33549*** 0.34968 –1.80552*** 0.40774 –2.11164*** 0.58072 Other perennial crops 0.15966 0.35542 –1.61227*** 0.43222 –1.69658*** 0.63848 Unimproved pasture –0.58040* 0.32005 –1.82105*** 0.48260 –0.64926 0.39474 Improved pasture 0.44644 0.51457 –1.78035*** 0.60140 0.39004 0.58035 Fallow –1.37974*** 0.29793 –0.60730** 0.30670 –1.29574*** 0.32590 Forest –0.37226 0.49586 –1.48522*** 0.52589 –0.89019** 0.43228 Intercept –3.09006*** 0.94312 2.57981*** 0.83330 0.56157 1.28975 Number of observations 776 776 776 Proportion of positive observations 0.3377 0.2321 0.1711 Mean predicted probability of positive 0.3424 0.2419 0.1641 observations Hausman test of exogeneity of livelihood p = 0.9945 p = 1.0000 NE strategies and participation in programs/ organizations (OLS vs. IV linear version of models) Hansen’s J test of overidentifying restrictions p = 0.7624 p = 0.8606 p = 0.6861 in IV linear model Note: NE means the Hausman test could not be computed due to a negative value of the test statistic. *, **, *** mean statistically significant at 10%, 5%, and 1% level, respectively. a Coefficients and standard errors adjusted for sampling weights and stratification, and are robust to heteroskedasticity and non-independence of observations from different parcels from the same household (clustering). productivity were estimated at the plot level, as these data were collected at the smaller plot level. 49 No Burning Many types of factors influence whether no burning is practiced, including livelihood strategy, natural capital, human capital, social capital (participation in programs and organizations), geographic determinants of comparative advantage, parcel characteristics, land tenure, and prior land investments and land use. Among natural capital variables, no burning is more common at higher elevation and where there is more rainfall in the primary (summer) rainy season (primera). The association of no burning with higher rainfall may be related to higher intensity of cultivation in areas of better agroclimatic conditions, which could reduce the need for burning to clear land. Another possible factor may be the increased risk of runoff as a result of higher rainfall, and the concomitant higher potential payoff of no burning. No burning is more common among households for whom migration is important, 49 Recall that a parcel is defined as a contiguous piece of land with a single tenure status, but possibly more than one land use, whereas a plot is a subunit of a parcel that has one land use (e.g., annual or perennial crop production, not both—unless these are planted in a mixed cropping or intercropped system).
ECONOMETRIC RESULTS 65 perhaps because this practice can be labor saving (Deugd 2000). Households pursuing the basic grains/farmworker livelihood strategy are more likely than basic grains farmers to use no burning (and basic grains/livestock/ farmworkers are more likely at the 10 percent level), possibly for the same reason (because households pursuing these livelihood strategies may have higher labor opportunity costs than pure basic grains farmers). No burning is more common in areas having better road access. Higher labor opportunity costs in such areas are likely to play an important role here, as may better access to information about this technology where road access is better. No burning is more common among farmers participating in agricultural extension but, surprisingly, is not significantly affected by whether the household participated in conservation training or extension programs. This suggests that more general agricultural extension programs are providing training on this practice, even if it was not mentioned by survey respondents as a specific emphasis of these programs. No burning is more common on parcels that are on top of a hill than at the bottom, consistent with the earlier result that it is more common at higher altitude. It is more common on farmers’own usufruct land than on borrowed or leased-in parcels, probably because of greater concern on the part of owners about the damage to investments and longer term soil fertility caused by burning. Consistent with this explanation, no burning is more common on parcels where prior investments in stone walls or live fences or barriers exist. However, it is less common on parcels where trees have been planted. This may be because no burning was seen by survey respondents as a specific practice that is associated with basic grains production, because burning is normally used to clear land for basic grains production. Thus, respondents may not have reported using “no burning” as a practice where other land uses such as perennial crops were more important, even if they were not using burning. Consistent with this, we find that no burning is more common where basic grains are a larger component of the prior land use than for most other land uses. Zero/Minimum Tillage Use of zero or minimum tillage is affected by many of the same factors as no burning, though not always in the same way. It is less common among basic grains/farmworkers and (weakly significantly) among basic grains/livestock/farmworkers than among farmers pursuing basic grains production as their sole livelihood strategy. This is likely because this technology is labor intensive (Schipper et al. 2005) and because households pursuing these other livelihoods likely have higher labor opportunity costs than basic grains farmers. Use of zero or minimum tillage is less common where there is more rainfall in the summer, but also less common where there is more of a rainfall deficit in the second season. Where there is more summer rainfall, weeds are likely to be a greater problem, making it more difficult for farmers to do without tillage. The negative association of zero/minimum tillage with the rainfall deficit in the second season is puzzling. Perhaps in areas where moisture deficit is severe, there is less need to be concerned about weeds, so farmers may use neither tillage nor specific zero or minimum tillage methods of weed control (which require labor and/or herbicides). In results discussed later, we find that both herbicide use and hired labor are lower in areas with greater moisture deficits, consistent with this explanation. Not surprisingly, use of zero/minimum tillage is less likely among households that own more machinery and equipment, since some of their equipment is used for tillage. We find no effect of any of the human capital variables on use of zero/minimum tillage, suggesting that human capital constraints are not binding for this type of technology. Use of zero/minimum tillage is less likely in areas further from an urban market and in areas of higher road density. These findings are somewhat contradictory. They reflect the fact that market and road access can have
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Rural Development Policies and Sust
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Contents List of Tables iv List of
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TABLES v 5.6 Determinants of extern
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Boxes 1.1 Defining “Hillsides,”
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Acknowledgments The authors acknowl
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SUMMARY xi the adoption of sustaina
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2 CHAPTER 1 Box 1.1 Defining “Hil
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4 CHAPTER 1 will allow Honduras to
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6 CHAPTER 1 In addition to providin
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8 CHAPTER 1 econometric analysis to
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10 CHAPTER 2 1998 and the coffee cr
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12 CHAPTER 2 Box 2.1 Land Issues in
Page 26 and 27: 14 CHAPTER 2 Table 2.3 Yield of pri
Page 28 and 29: 16 CHAPTER 2 Table 2.7 Intersectora
Page 30 and 31: 18 CHAPTER 2 Figure 2.2 Terms of tr
Page 32 and 33: CHAPTER 3 Methods and Models In thi
Page 34 and 35: 22 CHAPTER 3 Figure 3.1 Sustainable
Page 36 and 37: 24 CHAPTER 3 financial organization
Page 38 and 39: 26 CHAPTER 3 decide the number of c
Page 40 and 41: 28 CHAPTER 3 The reduced form versi
Page 42 and 43: 30 CHAPTER 3 Table 3.1 Variables in
Page 44 and 45: 32 CHAPTER 3 of years of formal sch
Page 46 and 47: 34 CHAPTER 3 Key socioeconomic elem
Page 48 and 49: 36 CHAPTER 3 although we report the
Page 50 and 51: 38 CHAPTER 4 Table 4.1 Natural capi
Page 52 and 53: 40 CHAPTER 4 Box 4.1 Remittances Re
Page 54 and 55: 42 CHAPTER 4 Table 4.6 Access to pu
Page 56 and 57: 44 CHAPTER 4 strategy (clusters 1 a
Page 58 and 59: Table 4.8 Mean household net income
Page 60 and 61: 48 CHAPTER 4 Table 4.9 Summary stat
Page 62 and 63: 50 CHAPTER 4 Box 4.2 Gender in the
Page 64 and 65: 52 CHAPTER 5 The socioeconomic expl
Page 66 and 67: 54 CHAPTER 5 explanatory variables
Page 68 and 69: 56 CHAPTER 5 technology training) a
Page 70 and 71: 58 CHAPTER 5 Table 5.3 Determinants
Page 74 and 75: 62 CHAPTER 5 the basic grains/lives
Page 78 and 79: 66 CHAPTER 5 ambiguous effects, dep
Page 82 and 83: 70 CHAPTER 5 more livestock focus m
Page 86 and 87: 74 CHAPTER 5 Geographic determinant
Page 88 and 89: 76 CHAPTER 5 Table 5.8—Continued
Page 90 and 91: 78 CHAPTER 5 Table 5.9—Continued
Page 92 and 93: 80 CHAPTER 5 when they purchase it
Page 94 and 95: 82 CHAPTER 5 Table 5.10 Summary of
Page 96 and 97: 84 CHAPTER 5 able to compensate for
Page 98 and 99: 86 CHAPTER 5 On the other hand, edu
Page 100 and 101: 88 CHAPTER 5 and wage labor. Nevert
Page 102 and 103: 90 CHAPTER 5 productivity. 62 Incre
Page 104 and 105: CHAPTER 6 Summary of Findings, Conc
Page 106 and 107: 94 CHAPTER 6 zero/minimum tillage,
Page 108 and 109: 96 CHAPTER 6 Develop and promote yi
Page 110 and 111: 98 REFERENCES Boucher, S., B. Barha
Page 112 and 113: 100 REFERENCES Hornby, A. S. 1974.
Page 114 and 115: 102 REFERENCES Pino, H. N., P. Jim
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