Assessing the Role of Group Heterogeneity in Community Forest Concessions in Guatemala’s Maya Biosphere Reserve

Lea Fortmann, Brent Sohngen and Douglas Southgate

Article Figures & Data

Figures

Tables

  • TABLE 1

    Overview of the Three Types of Community Forest Concessions

    Concession CategoryConcession NameYear FormedNumber of MembersConcession Area (ha)
    Resident, long-inhabitedCarmelita199712253,797
    Uaxactún200024483,558
    Resident, recently settledSan Miguel1994307,039
    La Pasadita199711018,817
    La Colorada20013927,067
    Cruce a la Colorada20016520,469
    NonresidentSuchitecos (RíoChanchich)1998274,607
    Laborantes (Chosquitán)20007819,390
    San Andrés (AFISAP)200017451,940
    Arbol Verde (Las Ventanas)200136464,973
    El Esfuerzo (Yaloch)20023925,386
    Custosel (La Unión)20029621,176
    • Source: Data from Gómez and Méndez 2007.

  • TABLE 2

    Member Summary Statistics Separated by Concession Group

    VariableNonresidentLong-InhabitedRecently Settled
    Age of head49.647.851.0
    Education of head (years)5.0**4.1**2.5***
    Born in Petén (percent)52***76***29***
    Daily food expendituresa (dollars)11.87**8.777.41
    Annual incomea (dollars)7,928*3,867*2,413**
    Own land (percent)47***76.8**82**
    Personal landholdings (ha)13.8**7.6**48.8***
    Dividend payment (2011 dollars)350***48***0***
    Farmer (percent)34.237.186***
    Forest job (percent)7.9**25.8***1.7**
    Other job (percent)52.6**35.5**10.5***
    Observations1526257
    • Note: Concession membership ranged from 20 members to more than 300. Twenty to twenty-five percent of members were randomly selected for interviews.

    • a Income and food expenditures are converted from quetzales to dollars based on October 2012 exchange rates (when the survey was conducted), Q1.00 = $0.1253 (source: www.freecurrencyrates.com/exchange-rate-history/GTQ-USD/2012). Significant difference from the other two groups based on independent sample t-tests.

    • * Significant at 10%;

    • ** significant at 5%;

    • *** significant at 1%.

  • TABLE 3

    Comparison of Summary Statistics for Three Forest Concession Groups

    VariableNonresidentLong-InhabitedRecently Settled
    Road distance (km)21.48.86.6
    Slope (degrees)3.73.55.0
    Elevation (meters)194226230
    Cleared distancea (kilometers)9.45.71.6
    City distance (kilometers)49.569.551.6
    pH6.87.17.3
    Archeo distanceb (kilometers)21.416.422.7
    Aspect (degrees)175159185
    Village distance (kilometers)25.313.15.1
    • Note: Data are from remote sensing satellite images. Observations are based on 30 m × 30 m parcels of land. See Data section for more details. All of the variables for each concession group are significantly different from the other groups at the 99% level for all covariates.

    • a Cleared distance is the distance to the nearest pixel of land cleared prior to 1990.

    • b Archeo distance is the distance to the nearest Mayan archeological site in the reserve.

  • TABLE 4

    Results of Difference-in-Differences (DID) and Probit Marginal Effects (ME)

    Unmatched (1)Matcheda (2)Matched without 2 km Buffer (3)
    ModelCoeff.Clustered Std. Err.Coeff.Clustered Std. Err.Coeff.Clustered Std. Err.
    All Groups
      DID−0.020.024−0.0420.038−0.0460.037
      Probit ME0.022**0.0110.0040.0080.00980.009
      Observations295,001169,666134,192
      R-squared0.120.150.14
    Nonresident
      DID−0.04**0.02−0.0330.02−0.043**0.02
      Probit ME0.0030.02−0.014**0.007−0.014*0.007
      Observations293,24890,19073,159
      R-squared0.130.470.098
    Long-inhabited
      DID−0.043**0.02−0.050*0.028−0.064*0.033
      Probit ME−0.0180.013−0.022**0.011−0.024**0.012
      Observations294,67994,20484,471
      R-squared0.130.110.12
    Recently settled
      DID0.0260.022−0.078*0.047−0.077***0.019
      Probit ME−0.0010.013−0.040**0.016−0.0150.014
      Observations296,26243,11625,682
      R-squared0.080.250.065
    • Note: Standard errors are clustered at the “concession” region level with 25 clusters for “all groups” and 17 clusters in the subgroups.

    • a Matched samples are based on nearest-neighbor propensity score matching with Mahalanobis distance metric with calipers set to 0.25 standard deviations taken from the sample with 300,000 observations. Results based on a linear probability model where the dependent variable equals 1 if pixel is deforested, 0 otherwise.

    • * Significant at 10%;

    • ** significant at 5%;

    • *** significant at 1%.

  • TABLE 5

    Average Treatment Effect on the Treated (ATT) Results for Kernel and Bias-Corrected Matching Estimators

    UnmatchedKernelBias-Corrected
    Concession GroupTime PeriodATTStd. Err.ATTStd. Err.ATTStd. Err.
    NonresidentPre−0.0360.002−0.00280.004−0.0130.0006
    Post−0.0700.003−0.0250.009−0.0150.004
    Difference−0.034***0.004−0.022**0.010−0.00150.004
    Long-inhabitedPre−0.0360.002−0.0410.0090.00800.004
    Post−0.0680.003−0.1440.011−0.0770.009
    Difference−0.032***0.004−0.103**0.014−0.085***0.010
    Recently settledPre−0.0190.0020.0130.020.0380.002
    Post0.0680.004−0.0650.034−0.0460.020
    Difference0.087***0.004−0.078**0.039−0.084***0.020
    • Note: Kernel matching performed in Stata Version 12 with “psmatch2” using clustered standard errors. Bias-corrected performed in Stata using the “nnmatch” command. The number of observations for each sample varies but is based on 50,000 total observations in the unmatched sample, then split up into 25,000 each for pre and post samples. The standard errors for kernel results do not take into account estimated propensity scores, but we choose not to bootstrap given the potential for errors (see Abadie et al. 2004; Abadie and Imbens 2006), since these are robustness checks. The bias-corrected ATT estimates do not include clustered standard errors.

    • * Significant at 10%;

    • ** significant at 5%;

    • *** significant at 1%.

  • TABLE 6

    Leakage Estimates for Buffer for Recently Settled Concessions

    2 km Buffer5 km Buffer10 km Buffer
    ModelUnmatchedMatchedUnmatchedMatchedUnmatchedMatched
    OLS0.0890.1450.078−0.0570.0570.039
    Robust Std. Err.(0.004)***(0.008)***(0.003)***(0.009)***(0.004)***(0.014)***
    Clustered Std. Err.(0.031)***(0.003)***(0.027)***(0.005)***(−0.054)(0.055)
    Kernel0.068***−0.13***−0.0004
    Std. Err.(0.018)(0.013)(0.036)
    Observations96,8997,23097,7565,58298,0145,004
    R-squared0.190.280.160.290.150.17
    • Note: Matched results are based on nearest-neighbor matching without replacement with Malahanobis distance metrics. Matching was done in R using “MatchIt” (Ho et al. 2011). Kernel results are from Stata Version 12 using “psmatch2.” Standard errors are in parentheses. Dependent variable is binary, equal to 1 if observation is within the designated buffer zone. OLS, ordinary least squares.

    • * Significant at 10%;

    • ** significant at 5%;

    • *** significant at 1%. Significance designations based on clustered standard errors.

  • TABLE A1

    Logit Results from Estimating Propensity Scores for Matching

    NonresidentLong-InhabitedRecently Inhabited
    VariableOdds RatioClustered Std. Err.Odds RatioClustered Std. Err.Odds RatioClustered Std. Err.
    Distance to road1.410.209**0.830.132.130.56***
    Distance to road21.000.0050.990.0050.970.008***
    Distance to major city0.910.0764.741.44***2.340.745***
    Distance to major city21.000.00060.990.002***1.000.004
    Elevation1.000.00451.030.009***1.020.008***
    Slope (degrees)1.050.02***1.040.016**1.060.015***
    Distance to cleared parcel2.080.28***1.620.314 **0.400.13***
    Distance to cleared parcel20.970.97***0.970.009***0.930.07
    Distance to nearest village1.350.106***0.620.106***0.330.22*
    Distance to nearest village21.000.0016**1.000.0031.040.04
    Distance to archeo site0.970.0241.160.083**0.470.04***
    pH2.320.40***0.630.102***0.950.61
    Aspect1.000.0021.000.0002***1.000.0002
    West (dummy)424.5642***0.250.25
    Constant2.2e–65.2e–6***2.6e–232.7e–22***8.2e–78.9e–6
    Observations293,248294,208232,984
    Pseudo R20.58280.77940.8384
    Log likelihood−78,344.1−41,589.9−25,643
    • Note: Logit results from Stata Version 12. The nonresident observations include 19 clusters, long-inhabited 15 clusters, and the recently settled 7 clusters (since only western concessions and controls are included).

    • * Significant at 10%;

    • ** significant at 5%;

    • *** significant at 1%.

  • TABLE A2

    Comparison of Balance between Matched Data Sets

    NonResidentLong-InhabitedRecently Inhabited
    UnmatchedMatchedUnmatchedMatchedUnmatchedMatched
    VariableMean Diff.eQQ Med.aMean Diff.eQQ Med.aMean Diff.eQQ Med.aMean Diff.eQQ Med.aMean Diff.eQQ Med.aMean Diff.eQQ Med.a
    Distance to road6.866.751.811.72−5.716.82−0.030.67−8.938.131.061.45
    Distance to city−23.4824.92−0.966.60−3.4823.165.9619.98−14.9821.955.206.86
    Distance to village6.626.520.882.65−5.606.60−0.990.90−9.6610.110.480.81
    Distance to village2305.9217.732.0671.17−231.9262.1−40.1021.99−240.3200.012.315.74
    Distance to clearing1.902.10−0.591.36−1.801.34−0.140.56−8.6810.670.860.19
    Distance to clearing218.6919.14−19.2427.82−46.5213.78−5.323.91−152.4133.17.370.38
    Distance to archeo site−0.865.22−1.892.01−5.853.27−0.972.943.645.53−3.192.87
    Aspect12.8810.011.014.40−2.606.34−0.361.3020.2714.04−4.024.07
    pH0.340.360.100.050.550.50−0.090.000.510.36−0.130
    Elevation29.9048.2512.2211.0062.1469.00−4.2936.0029.9335.0014.716
    Slope (degrees)0.570.87−0.360.000.380.46−0.110.002.201.90−1.861.97
    West (location dummy)−0.290.290.000.00−0.160.160.000.000.320.000.000.00
    Observations293,24890,190294,20894,204296,26243,116
    • Note: Matching methods for all three data sets are nearest neighbor without replacement, with Mahalanobis distance metric for select variables.

    • a Median values for the quantile-quantile (QQ) plot differences are used for all ordinal covariates and the mean is used for categorical covariates (west). Matching is conducted in R using “Matchit” (Ho et al. 2011).

  • TABLE A3

    Panel Test for Parallel Trends in Deforestation Preconcession Policy

    Recently SettledLong-InhabitedNonresident
    VariableCoeff.Std. Err.Coeff.Std. Err.Coeff.Std. Err.
    Control0.0040.0070.0130.0080.0070.005
    Year 90_93−0.003**0.001−0.0008*0.0004−0.00002**0.00001
    Year 93_95−0.002**0.001−0.0008*0.00040.000000.00000
    Control*90_93−0.0040.005−0.0100.007−0.0050.003
    Control*93_95−0.0030.004−0.0030.002−0.0040.003
    Constant0.007**0.0030.0008*0.00040.00007**0.00003
    Observations129,099282,537270,564
    Groups43,03394,17990,188
    • Note: Results based on a random effects linear probability model with panel data from three preconcession periods: 1990–1993, 1993–1995, and 1995–1997. Each pixel was coded as 1 if it experienced deforestation during that period, and then remained 1 for all subsequent periods. Results based on a linear probability model where the dependent variable equals 1 if pixel is deforested, 0 otherwise.

    • * Significant at 10%;

    • ** significant at 5%;

    • *** significant at 1%.

  • TABLE A4

    Test for Unobserved Bias Using the Mantel-Haenszel Test Statistic

    NonresidentLong-InhabitedRecently Inhabited
    ΓPrePostPrePostPrePost
    112.221.510.315.16.24.4
    217.430.314.821.611.113.1
    321.336.918.326.514.618.8
    424.642.421.230.617.423.2
    527.547.223.834.219.826.9
    • Note: Results were obtained using “mhbounds” in Stata Version 12 used for testing unobserved bias with binary dependent variables (see Becker and Caliendo 2007). Reported values are for the Mantel-Haenszel statistic Q + mh (assumption: overestimation of treatment effect). p-Values for all test statistics are less than 0.001 and thus are not displayed in the table. Pre indicates the prepolicy period from 1990 to 1996, post indicates the postpolicy period from 2000 to 2008. Γ is a measure of the degree of hidden bias required to change results of the estimated treatment effect from the kernel matching results (TABLE 5).

  • TABLE A5

    Panel Data Results with Time Trend

    Variable (Dependent deforest = 1)Recently SettledLong-InhabitedNonresident
    With 2 km BufferWithout 2 km BufferWith 2 km BufferWithout 2 km BufferWith 2 km BufferWithout 2 km Buffer
    Coef.Coef.Coef.Coef.Coef.Coef.
    Treat−0.003
    (0.006)
    −0.013***
    (0.002)
    −0.011*
    (0.006)
    −0.014*
    (0.007)
    −0.005
    (0.004)
    −0.008
    (0.005)
    Post0.018
    (0.035)
    0.085***
    (0.024)
    0.015
    (0.015)
    0.023
    (0.019)
    0.007
    (0.010)
    0.016
    (0.013)
    Treat × Post−0.081
    (0.059)
    −0.134***
    (0.013)
    −0.041**
    (0.021)
    −0.052**
    (0.023)
    −0.024
    (0.015)
    −0.034**
    (0.017)
    Time Trend0.026***
    (0.008)
    0.023***
    (0.006)
    0.007*
    (0.004)
    0.008
    (0.005)
    0.004*
    (0.003)
    0.005
    (0.003)
    Constant−0.057***
    (0.016)
    −0.038***
    (0.015)
    −0.006
    (0.008)
    −0.005
    (0.010)
    −0.005
    (0.005)
    −0.003
    (0.006)
    Observations344,264204,832753,432675,576721,504585,256
    Groups43,03325,60494,17984,44790,18873,157
    • Note: Data are from remote sensing satellite images. Observations are based on 30 m × 30 m parcels of land. Panel format is based on periods where deforestation was observed. There are eight periods from 1990 to 2009. Each pixel was coded as 1 if it experience deforestation during that period and then remained 1 for all subsequent periods. Results based on a linear probability model where the dependent variable equals 1 if pixel is deforested, 0 otherwise.

    • * Significant at 10%;

    • ** significant at 5%;

    • *** significant at 1%.

  • TABLE A6

    Leakage Estimates for “Buffer” Coefficient for Concession Groups

    2 km Buffer5 km Buffer10 km Buffer
    ModelUnmatchedMatchedUnmatchedMatchedUnmatchedMatched
    Resident Indigenous
    OLS−0.0411−0.037−0.027−0.0280.0008−0.010
    Clustered Std. Err.(0.012)***(0.014)***(0.012)**(0.013)**(0.019)(0.015)
    Observations960414724695480421369464826932
    Pseudo R20.1810.14740.17570.1190.1670.0896
    Nonresident
    OLS0.01150.00560.015−0.00140.015−0.010
    Clustered Std. Err.(0.011)(0.009)(0.013)(0.008)(0.034)(0.032)
    Observations95,00738,17694,72329,67494,60224,568
    Pseudo R20.1680.2390.1640.2360.1640.242
    • Note: Clustered standard errors in parentheses. OLS, ordinary least squares.

    • * Significant at 10%;

    • ** significant at 5%;

    • *** significant at 1%.