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

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88 CHAPTER 5 and wage labor. Nevertheless, simple analysis of descriptive statistics (results not reported) shows that the value of production per manzana is higher on perennial than annual plots, owing to the higher prices of perennial crops. Predicted Impacts of Changes in Selected Explanatory Variables To better assess the magnitude of impacts (as opposed to just their direction and statistical significance) of particular factors on livelihood strategies, land management practices, input use, productivity, and household income, we present results of simulations of these impacts based upon the regression results presented earlier. In the simulations, we calculate the direct effect of changes in particular explanatory variables upon the dependent variables by altering the value of the explanatory variable (e.g., increasing population density by 1 percent) for each observation and predicting new values of the dependent variable based on the regression coefficients. For many dependent variables, the impacts of a change in a particular explanatory variable may come via multiple “channels.” For example, an increase in road density can affect the value of crop yield by affecting households’ choice of livelihood strategy, land management practices, labor, and purchased input use, as well as by possibly affecting local prices and hence the value of yields directly, independently of quantitative changes in yields. These indirect effects are estimated by predicting the effects of the change in the explanatory variable on all of these intermediate dependent variables, and then using these values to predict the value of crop yield. Combining the effects of these indirect and direct effects results in an estimate of the total impact of the change, which may be helpful to policymakers and others interested in our results. 60 For our simulations, we focus on the impacts of changes in several policy-relevant variables that are found to have statistically significant impacts on at least one of our main response or outcome variables (livelihood strategy, land management, crop productivity, income): population density, road density, market access, amount of land owned, value of machinery and equipment owned, value of livestock owned, and median level of schooling of household members. For all of the simulations, we estimated the percent change in the dependent variables associated with a 1 percent increase in the explanatory variable. 61 Our simulation estimates for these variables thus represent response or impact elasticities. The results of the simulations are presented in Table 5.11. We discuss these by type of explanatory factor, focusing on results that are based on statistically significant regression coefficients and that are relatively large in quantitative terms. Land Owned Increased land ownership is predicted to increase pursuit of livelihood strategies involving livestock (livestock production and basic grains/livestock/farmworker), and reduce pursuit of the basic grains/farmworker strategy. Greater land ownership is predicted to reduce perennial crop yields significantly (elasticity = –0.21). This result suggests that increased allocation of land to smaller farms could result in increased average crop 60 See Nkonya et al. (2004) for a detailed explanation of the simulation approach. 61 When the dependent variable took on discrete values such as the livelihood strategy or use of land management practices or purchased inputs, the simulation results predict the percentage change in the probability of one of these discrete values occurring. For example, if the probability of a particular livelihood strategy increased from 0.1 to 0.15, that represents a 50 percent increase in probability. For the market access variable which is measured in terms of travel time to the nearest market, we simulated a reduction.
Table 5.11 Simulation results—Percentage change in selected variables Population Market Owned Machinery/ Livestock Median density Road density access land equipment value value education Variable increased 1% increased 1% increased 1% increased 1% increased 1% increased 1% increased 1% Livelihood strategies Livestock 0.03 –0.45 –0.35* 0.12*** –0.04 Coffee –0.55*** 1.50** –0.11 –0.11 –0.43 Basic grains 0.48 –0.95 0.42 –0.06 –0.07 Basic grains/farmworkers 0.14 0.73** –0.02 –0.19* –0.36 Basic grains/livestock/farmworkers –0.26*** –0.04 –0.01 0.12*** 0.42 Land management No burning –0.05 0.78*** –0.06 0.01 0.01 –0.06 –0.13* Minimum/zero tillage –0.07 –0.81** 0.35* –0.02 –0.05** –0.05 0.06 Incorporation of crop residues –0.18* 0.69*** 0.05 –0.04* –0.01 –0.08 0.31 External inputs Fertilizer 0.18*** 0.24*** –0.03 0.02 0.01 –0.05** 0.09* Herbicides –0.11 0.19 –0.16* 0.04 –0.04** 0.02 –0.01 Insecticides –0.09 –0.08 0.27 0.01 0.01 0.18*** –0.04 Labor inputs Family labor –0.03 0.16** 0.05 0.00 –0.02* –0.02* –0.01 Wage labor 0.20* 0.05 0.04 –0.05 0.10*** 0.16*** 0.05 Value of annual crop yield Total effect 0.03 0.15 0.01 0.00 0.00 0.00 0.06 Value of perennial crop yield Direct effect 0.00 0.83*** 0.32* –0.24*** 0.00 0.09*** 0.34*** Total effect 0.13 R 0.72 0.39 –0.21 R 0.05 R 0.09 0.13 R Income/capita Direct effect 0.07 –0.21 –0.07 0.00 0.13*** –0.04 0.12 Total effect 0.08 –0.11 –0.16 –0.02 0.13 –0.04 0.04 Notes: R means that the total impact estimated in the reduced form regressions in Tables 5.8 and 5.9 are the same sign and statistically significant at the 10% level. *, **, *** mean that the regression coefficient upon which the estimated direct effect is based is statistically significant at the 10%, 5%, or 1% level, respectively. ECONOMETRIC RESULTS 89
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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
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14 CHAPTER 2 Table 2.3 Yield of pri
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16 CHAPTER 2 Table 2.7 Intersectora
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18 CHAPTER 2 Figure 2.2 Terms of tr
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CHAPTER 3 Methods and Models In thi
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22 CHAPTER 3 Figure 3.1 Sustainable
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24 CHAPTER 3 financial organization
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26 CHAPTER 3 decide the number of c
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28 CHAPTER 3 The reduced form versi
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30 CHAPTER 3 Table 3.1 Variables in
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32 CHAPTER 3 of years of formal sch
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34 CHAPTER 3 Key socioeconomic elem
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36 CHAPTER 3 although we report the
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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 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 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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