Seite - (000162) - in Evaluating Climate Change Action for Sustainable Development

land ismuchmore likely tohaveother cropsgrownon it, once soybeanandpaddy rice havebeenharvested. Inowdiscuss theeffectofvariables thatcanbeaffectedbypolicyonagricultural landand intensityof cultivation.Results arepresented in column1,Table8.8 30,31 Results inTable8.8showthata1%decrease in travel time tomarket increases the percentageof agricultural landcultivatedby2.9%points. Populationhasnoeffect on the intensity of cultivation for either group of villages. Short run crop water availability increases the percentage of area cultivated by almost 6 percentage points. Thismay be occurring if short run crops such as soybean andmung bean are grownon intra-marginal lands. Results show that the effects of explanatory variables are different for villages that have no secure property rights (NPR villages). On average NPR villages cultivate land less intensively than APR villages by 71 percentage points. Addi- tionally in NPR villages, there is almost no effect of a change in travel time to market (travel timeestimate forNPRvillages¼0.343 (which is coefficient for log (travel time estimate) ¼ 2.868 þ coefficient (NPR ¼ 1*Log(travel time estimate))¼3.212)¼0.343; z¼0.42; Prob>Chi-square¼0.67). Short runwater availability alsohasnoeffect on intensityof cultivation inNPRvillages (the short run water coefficient in NPR villages ¼ 5.716–4.11¼1.6; Z-statistic ¼ 1.04; Prob>Z¼0.30). Toinvestigate landexpansionasmeasuredbyvillageagricultural land, thesame variables are used to explain the equation asused for agricultural intensity.This is becausevariables that affect intensity of cultivation should also affect landexpan- sion.Results are presented in column2,Table 8.8.32 Results in column (2) show that a 1% increase in village population leads to a 0.4% increase in area devoted to agricultural land in thevillages in the estimation sample.BAACcredit use increases agricultural land by1.1% in these villages.A 1%increaseintravel timetothemarket increases theareaundercultivationinAPR 30Since the intensity of cultivation is measured as a categorical variable, with each value representinganinterval, Iestimate theequationsfor intensityofcultivationusingarandomeffects interval regressionmodel.Similar to theprocedurefollowedfor thecropareaequations, Iestimate a reduced formequationwhereBAACcredit use is endogenous. The results I discuss here use a two-stepvariant of the interval regressionmodel inwhich thefirst step estimates a reduced form model forBAACcredituse,usingarandomeffectsprobitmodel.Column(5) isa two-stepvariant of the random effects interval regression, where the first stage uses a random effects probit equation to estimate themodel forBAACcredit use. Results from the first stage are reported in Table 5.17. 31Thedifferent specifications and sensitivity analyses are presented inPuri 2006. 32I estimate a random effects equation via generalized two stage least squares to estimate the model for agricultural land. The dependent variable is in logs. In Table 5.16 I present only one specification.BAACcredituse instrumentedfor,byusing three identifyinginstruments.Theseare proportion of population with compulsory education, travel time to the district and HYV rice dummy. The results from the first stage random effects equation for BAAC credit use are not shownhere. 146 J. Puri