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

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62 CHAPTER 5 the basic grains/livestock/farmworker strategy. For households pursuing off-farm employment, farm equipment may yield high returns by enabling them to spare labor for more remunerative off-farm opportunities, as well as possibly contributing to agricultural employment opportunities off their own farm (i.e., if the household members use their own equipment when working for other farmers). For households pursuing coffee production, ownership of equipment such as a sprayer is likely quite important to the profitability of the enterprise. Our results concerning the determinants of the value of perennial crop production (Table 5.9, discussed below), which show large impacts of external inputs such as fertilizer, pesticides, and herbicides on perennial production, support the argument that equipment to apply such inputs is a profitable investment in coffee production. Machinery and equipment appear to be much less remunerative for households pursuing basic grains or livestock production only. In the model with interaction terms, we find that agricultural training has a significant positive association with incomes for basic grains only producers (incomes per capita of basic grains producers are 1779 Lempiras higher among those who have received training), though the effect is smaller than in Table 5.3 and only weakly statistically significant. We find a very large and strongly significant positive association of training with incomes of livestock producers (+10,447 Lempiras with training). Again, it is hard to believe that training could have such a large impact on these producers’ incomes, and these results are not robust in a median regression version of the model. 47 Thus, if there are positive impacts of agricultural training programs, these positive impacts are greatest for livestock producers. Adoption of Sustainable Land Management Practices The determinants of land management practices are shown in Table 5.5. Three practices are analyzed—use of no burning, zero or minimum tillage, and incorporation of crop residues. Other land practices, including use of mulching, manure, and others, were not sufficiently common to permit reliable estimation of the parameters of the probit model specified in equation (4) in Chapter 3. 48 The regressions are estimated using parcel-level data, because this is the level at which data on these land management practices were collected. Subsequent regressions on external input use, labor use, and crop 47 In the median regression version of the model with interactions, the coefficients of agricultural training and training interacted with livelihood strategies were statistically insignificant. The only statistically significant coefficient in that regression was the interaction of equipment/machinery ownership with the basic grains/farmworker livelihood strategy, for which the coefficient was positive and of similar magnitude to that reported in Table 5.3. Thus we have confidence that the returns to equipment and machinery are substantially higher for households in the basic grains/farmworker category, but less confidence in the other interaction results. These regression results are available from the authors on request. 48 With a relatively small number of positive observations of the dependent variable and many dummy variables in a probit model, it often occurs that the dependent variable is always zero or always positive for one of the values of a given dummy variable. In this case, the model cannot be estimated with that explanatory variable included, and the STATA software automatically drops that variable and the observations for which the response is perfectly predicted by the dummy variable, and re-estimates a smaller version of the model. Effectively the model is deterministic for some observations, so a smaller stochastic model is estimated. This procedure resulted in a large number of dropped observations in the regressions for mulching and manure. Although these regressions are not reported, they are still used to determine predicted values of the probability of use of these practices, which are used as instrumental variables in the IV estimation of equation (1) in Chapter 3 (and discussed in section 5.6 below). Some of the predictions from such models are deterministic (i.e., for the observations that were dropped based on certain values of the dummy variables in the full model). The results of these regressions are available on request.
ECONOMETRIC RESULTS 63 Table 5.5 Determinants of land management practices (probit regressions) a Incorporate No burning Minimum/zero tillage crop residues Standard Standard Standard Explanatory variable Coefficient error Coefficient error Coefficient error Livelihood strategy (cf. basic grains farmers) Livestock producer 0.15738 0.38872 –0.15527 0.41943 –0.43337 0.49689 Coffee producer –0.35487 0.38024 –0.73369 0.45014 –1.28124*** 0.49666 Basic grains/farmworker 0.78447** 0.30482 –1.12176*** 0.34645 –0.53155 0.38804 Basic grains/livestock/farmworker 0.50630* 0.29471 –0.62714* 0.36177 –0.31616 0.37204 Natural capital Altitude 0.00030*** 0.00010 –0.00009 0.00008 0.00012 0.00012 Summer rainfall 0.00103*** 0.00038 –0.00173*** 0.00045 0.00115* 0.00061 Rainfall deficit in secondary season 0.00225 0.00292 –0.00364** 0.00184 –0.01211*** 0.00462 Soil fertility –0.00019 0.00014 0.00012 0.00013 –0.00055*** 0.00019 Owned land 0.00251 0.00539 –0.00801 0.00566 –0.02065* 0.01055 Physical capital Value of machinery and equipment 0.00000 0.00001 –0.00002** 0.00001 0.00000 0.00001 Value of livestock –0.00001 0.00000 –0.00001 0.00000 –0.00001 0.00001 Human capital Median years of schooling –0.08699* 0.04756 –0.00228 0.04719 0.03489 0.07323 Household size –0.02897 0.03625 0.03212 0.03475 –0.14574*** 0.05228 Dependency ratio 0.16564 0.15702 0.06804 0.15746 –0.51304** 0.24315 Female-headed household 0.13520 0.41749 –0.53418 0.38125 0.96794** 0.43695 Percentage of female adults –0.14056 0.67252 –0.08206 0.67728 –0.88524 0.92686 Age of household head 0.00872 0.00693 0.00382 0.00632 –0.00097 0.00886 Migration index 1.66290*** 0.48703 0.45864 0.38737 0.73742 0.56510 Geographic determinants of comparative advantage Market access 0.01110 0.02158 –0.04532** 0.02099 0.01773 0.02513 Road density 0.24360*** 0.06445 –0.18260** 0.07627 0.36662*** 0.08917 Population density –0.00084 0.00077 –0.00107 0.00111 –0.00244* 0.00126 Participation in programs and organizations Conservation training 0.24561 0.28844 0.91708*** 0.25133 0.27376 0.34648 Agricultural training 0.47078 0.42046 –0.68528** 0.34801 –1.98802*** 0.64474 Conservation extension -0.33692 0.42501 –0.47262 0.31764 1.26840*** 0.44800 Agricultural extension 0.86464** 0.38445 0.83674** 0.36259 2.19605*** 0.43258 Producers’/campesino organization 0.09204 0.37328 0.23775 0.35666 –1.59090** 0.63683 Rural bank/caja rural 0.31194 0.30474 –0.83068** 0.34971 –1.80687*** 0.41727 NGO program –0.16339 0.33625 0.30088 0.27397 1.50439*** 0.48059 Parcel characteristics Area of parcel (mz) 0.00803* 0.00458 0.01253 0.00921 0.02927*** 0.00957 Travel time from parcel to residence (minutes) 0.00294* 0.00172 –0.00202 0.00235 –0.00525 0.00352 Travel time from parcel to road (minutes) –0.00327 0.00481 –0.01164* 0.00700 0.00246 0.00512 Position on hill (cf. bottom) Top of hill 1.12731*** 0.40867 –1.29756** 0.59294 0.19879 0.61334 Hillside 0.14117 0.23112 0.11731 0.23401 0.68288*** 0.25952 Slope (cf. flat) Moderate slope 0.19763 0.25252 –0.11885 0.26331 –0.80551*** 0.27468 Steep slope –0.22478 0.31361 0.46503 0.32946 –1.33237*** 0.41959 Land tenure Percentage of land with title –0.14375 0.36723 0.39666 0.43907 –0.79819 0.58310 Plot tenure (cf. usufruct ownership) Full title –0.14709 0.27352 –0.16568 0.40627 0.17501 0.52359 Occupied communal land 0.10696 0.38146 0.28144 0.47464 –0.38417 0.52371 Borrowed plot –1.06753*** 0.27888 0.11227 0.27148 –0.29208 0.32117 Rented or sharecropped –0.87832*** 0.32504 –0.05103 0.31612 –0.20013 0.32900 (continued)
Page 1 and 2:
Rural Development Policies and Sust
Page 3 and 4:
Contents List of Tables iv List of
Page 5 and 6:
TABLES v 5.6 Determinants of extern
Page 7 and 8:
Boxes 1.1 Defining “Hillsides,”
Page 9 and 10:
Acknowledgments The authors acknowl
Page 11:
SUMMARY xi the adoption of sustaina
Page 14 and 15:
2 CHAPTER 1 Box 1.1 Defining “Hil
Page 16 and 17:
4 CHAPTER 1 will allow Honduras to
Page 18 and 19:
6 CHAPTER 1 In addition to providin
Page 20 and 21:
8 CHAPTER 1 econometric analysis to
Page 22 and 23:
10 CHAPTER 2 1998 and the coffee cr
Page 24 and 25: 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 76 and 77: 64 CHAPTER 5 Table 5.5—Continued
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 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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