Rice Science ›› 2020, Vol. 27 ›› Issue (1): 56-66.DOI: 10.1016/j.rsci.2019.12.006
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Kwasi Bannor Richard1,2(), Amarnath Krishna Kumar Gupta2, Oppong-Kyeremeh Helena1, Abawiera Wongnaa Camillus3
Received:
2018-08-05
Accepted:
2018-12-09
Online:
2020-01-28
Published:
2019-09-30
Kwasi Bannor Richard, Amarnath Krishna Kumar Gupta, Oppong-Kyeremeh Helena, Abawiera Wongnaa Camillus. Adoption and Impact of Modern Rice Varieties on Poverty in Eastern India[J]. Rice Science, 2020, 27(1): 56-66.
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Variable | Description | Measurement | Expected sign | Mean | SD | ||
---|---|---|---|---|---|---|---|
Dependent variable | |||||||
Adoption of new rice variety | Adoption of new rice variety | 1 = Adopters, 0 = Non-adopters | Nil | 0.950 | 0.217 | ||
Adoption intensity | Percentage of total land allocated to new variety for production | Proportion of land allocation | Nil | 83.942 | 30.110 | ||
Independent variable | |||||||
Demographic characteristics | |||||||
Age | Number of years from birth | Number | - | 47.124 | 10.183 | ||
Education | Highest formal educational level attained | School years | + | 5.438 | 5.578 | ||
Household size | Number of adult household members | Number | + | 2.234 | 2.238 | ||
Caste | Minority / lower caste | 1 = Yes, 0 = Otherwise | + | 0.061 | 0.240 | ||
Experience in rice farming | Number of years in rice farming | Number | + | 26.335 | 17.759 | ||
Management characteristics | |||||||
Farm record | Keep farm records | 1 = Keep records, 0 = Otherwise | + | 0.405 | 0.492 | ||
Risk aversion | Growing of other crops in addition to rice as proxy for risk aversion | 1 = Risk averse, 0 = Otherwise | - | 0.877 | 0.329 | ||
Off-farm job | Participation in off-farm job | 1 = Yes, 0 = Otherwise | - | 0.438 | 0.497 | ||
Access to credit | Having received credit for 2016-2017 production year | 1 = Yes, 0 = Otherwise | + | 0.235 | 0.424 | ||
Amount of credit received | Total amount of credit received for 2016-2017 production year | Amount in rupees | + | 955.934 | 7175.050 | ||
Membership of FBO | Membership of FBO | 1 = Yes, 0 = Otherwise | + | 0.237 | 0.426 | ||
Production characteristics | |||||||
Land size | Average land size planted for 2016-2017 | Hectares | + | 2.616 | 2.641 | ||
Number of rice plots | Total number of plots used for rice production | Number | + | 5.478 | 4.213 | ||
Flood | Land is prone to floods | 1 = Yes, 0 = Otherwise | +/- | 0.253 | 0.436 | ||
Seed cost | Average total cost of seed for production | Amount in rupees | - | 1172.860 | 5479.500 | ||
Insecticide cost | Average total cost of insecticide for production | Amount in rupees | - | 1819.350 | 6776.610 | ||
NPK cost | Total cost of NPK for production | Amount in rupees | - | 10883.250 | 37037.880 | ||
Yield | Average number of bags of rice harvested for 2016-2017 | Number | + | 17.337 | 32.522 | ||
High yielding | Perception of MVs with high yielding | 1 = Yes, 0 = Otherwise | + | 0.275 | 0.447 | ||
Disease resistance | Perception of MVs with disease resistance | 1 = Yes, 0 = Otherwise | + | 0.255 | 0.436 | ||
Seed availability | Ease accessibility of MV seeds | 1 = Yes, 0 = Otherwise | + | 0.275 | 0.447 | ||
Post-harvest characteristics | |||||||
MV easily marketable | Perception of MVs being highly marketable | 1 = Yes, 0 = Otherwise | + | 0.160 | 0.367 |
Table 1 Description of variables to be used in factors and intensity of adoption analysis.
Variable | Description | Measurement | Expected sign | Mean | SD | ||
---|---|---|---|---|---|---|---|
Dependent variable | |||||||
Adoption of new rice variety | Adoption of new rice variety | 1 = Adopters, 0 = Non-adopters | Nil | 0.950 | 0.217 | ||
Adoption intensity | Percentage of total land allocated to new variety for production | Proportion of land allocation | Nil | 83.942 | 30.110 | ||
Independent variable | |||||||
Demographic characteristics | |||||||
Age | Number of years from birth | Number | - | 47.124 | 10.183 | ||
Education | Highest formal educational level attained | School years | + | 5.438 | 5.578 | ||
Household size | Number of adult household members | Number | + | 2.234 | 2.238 | ||
Caste | Minority / lower caste | 1 = Yes, 0 = Otherwise | + | 0.061 | 0.240 | ||
Experience in rice farming | Number of years in rice farming | Number | + | 26.335 | 17.759 | ||
Management characteristics | |||||||
Farm record | Keep farm records | 1 = Keep records, 0 = Otherwise | + | 0.405 | 0.492 | ||
Risk aversion | Growing of other crops in addition to rice as proxy for risk aversion | 1 = Risk averse, 0 = Otherwise | - | 0.877 | 0.329 | ||
Off-farm job | Participation in off-farm job | 1 = Yes, 0 = Otherwise | - | 0.438 | 0.497 | ||
Access to credit | Having received credit for 2016-2017 production year | 1 = Yes, 0 = Otherwise | + | 0.235 | 0.424 | ||
Amount of credit received | Total amount of credit received for 2016-2017 production year | Amount in rupees | + | 955.934 | 7175.050 | ||
Membership of FBO | Membership of FBO | 1 = Yes, 0 = Otherwise | + | 0.237 | 0.426 | ||
Production characteristics | |||||||
Land size | Average land size planted for 2016-2017 | Hectares | + | 2.616 | 2.641 | ||
Number of rice plots | Total number of plots used for rice production | Number | + | 5.478 | 4.213 | ||
Flood | Land is prone to floods | 1 = Yes, 0 = Otherwise | +/- | 0.253 | 0.436 | ||
Seed cost | Average total cost of seed for production | Amount in rupees | - | 1172.860 | 5479.500 | ||
Insecticide cost | Average total cost of insecticide for production | Amount in rupees | - | 1819.350 | 6776.610 | ||
NPK cost | Total cost of NPK for production | Amount in rupees | - | 10883.250 | 37037.880 | ||
Yield | Average number of bags of rice harvested for 2016-2017 | Number | + | 17.337 | 32.522 | ||
High yielding | Perception of MVs with high yielding | 1 = Yes, 0 = Otherwise | + | 0.275 | 0.447 | ||
Disease resistance | Perception of MVs with disease resistance | 1 = Yes, 0 = Otherwise | + | 0.255 | 0.436 | ||
Seed availability | Ease accessibility of MV seeds | 1 = Yes, 0 = Otherwise | + | 0.275 | 0.447 | ||
Post-harvest characteristics | |||||||
MV easily marketable | Perception of MVs being highly marketable | 1 = Yes, 0 = Otherwise | + | 0.160 | 0.367 |
Variable | Adopter | Non-adopter | Overall | |||||
---|---|---|---|---|---|---|---|---|
Frequency (n = 346) | Percentage (%) | Frequency (n = 17) | Percentage (%) | Frequency (n = 363) | Percentage (%) | |||
Poverty status | ||||||||
Poor | 10 | 2.9 | 6 | 35.3 | 16 | 4.4 | ||
Non-poor | 336 | 97.1 | 11 | 64.7 | 347 | 95.6 | ||
Intensity of adoption | ||||||||
1-30 | 18 | 5.2 | ||||||
31-60 | 42 | 12.1 | ||||||
61-90 | 31 | 9.0 | ||||||
>90 | 255 | 73.7 |
Table 2 Poverty and intensity of adoption of sampled respondents.
Variable | Adopter | Non-adopter | Overall | |||||
---|---|---|---|---|---|---|---|---|
Frequency (n = 346) | Percentage (%) | Frequency (n = 17) | Percentage (%) | Frequency (n = 363) | Percentage (%) | |||
Poverty status | ||||||||
Poor | 10 | 2.9 | 6 | 35.3 | 16 | 4.4 | ||
Non-poor | 336 | 97.1 | 11 | 64.7 | 347 | 95.6 | ||
Intensity of adoption | ||||||||
1-30 | 18 | 5.2 | ||||||
31-60 | 42 | 12.1 | ||||||
61-90 | 31 | 9.0 | ||||||
>90 | 255 | 73.7 |
Variable | Double hurdle estimate | Tobit regression | Heckman estimate | ||
---|---|---|---|---|---|
Hurdle 1 (Probit regression) | Hurdle 2 (Truncated regression) | Probit regression | Ordinary least squares | ||
Demographic characteristics | |||||
Age | 0.0043** (0.0019) | 0.0016 (0.0016) | 0.0016 (0.0016) | 0.1538** (0.0727) | 0.0022 (0.0026) |
Education | 0.0179* (0.0101) | 0.0119 (0.0226) | 0.0119 (0.0227) | 0.6328 (0.6041) | 0.0163 (0.0363) |
Caste | -0.0536 (0.0399) | -1.3784 (2.4230) | |||
Household size | -0.0452*** (0.0172) | 0.0243* (0.0136) | -0.0244* (0.0137) | -1.5981* (0.9176) | -0.0209 (0.0142) |
Experience | -0.0032** (0.0014) | -0.0015* (0.0009) | -0.0015* (0.0009) | -0.1128* (0.0600) | -0.0027* (0.0016) |
Management characteristics | |||||
Farm records | 0.0125 (0.0246) | 0.4734 (1.1471) | |||
Risk aversion | 0.1256*** (0.0415) | 0.1319* (0.0831) | 0.1312* (0.0832) | 2.9912** (1.2257) | 0.1600* (0.0779) |
Off-farm | -0.1128*** (0.0279) | 0.0074 (0.0607) | 0.0072 (0.0614) | -3.2509** (1.2601) | 0.0008 (0.0569) |
Credit | 0.0493 (0.0520) | 0.0500 (0.0522) | -0.0199 (0.0670) | ||
Amount of credit | -0.0000412* (0.0000) | -0.0000412 (0.0000) | |||
FBO membership | 0.0290 (0.0573) | -0.0170 (0.0576) | 0.0035 (0.0676) | ||
Production characteristics | |||||
Land size | 0.0319*** (0.0010) | 0.0534*** (0.0178) | 0.0537*** (0.0181) | 1.1300* (0.6953) | 0.0481* (0.0129) |
Number of rice plots | 0.0044 (0.0073) | 0.0045 (0.0073) | -0.0002 (0.0071) | ||
Flooding land | 0.0059 (0.0169) | 0.2162 (1.2032) | |||
Seed cost | -0.00002* (0.0000) | -0.0006 (0.0004) | |||
Insecticide cost | -8.46e-06* (5.16e-06) | 0.00004*(0.00002) | -4.28e-07 (4.02e-07) | -0.0003 (0.0004) | 0.0000 (0.0000) |
NPK cost | -1.47e-07 (5.84e-06) | -0.00006* (0.00004) | 2.05e-07 (4.58e-07) | 0.0000 (0.0004) | 0.0000 (0.0000) |
Yield | 0.0040*** (0.0015) | 0.1427* (0.8585) | |||
MVs high yield | 0.0457*** (0.0167) | 0.1317** (0.0585) | -0.1317 (0.0585) | 1.9609 (1.3097) | 0.1212** (0.0638) |
MVs resistant to diseases | 0.0351*** (0.0127) | 1.9082 (1.6247) | |||
MVs seed availability | 0.0400** (0.0170) | 0.0972* (0.0609) | 0.0988** (0.0619) | 1.5497* (0.9122) | 0.1385** (0.0622) |
Post-harvest characteristics | |||||
MV easily marketable | -0.0102 (0.0560) | -0.0090 (0.0567) | 0.0334 (0.0780) | ||
Constant | 3.8425** (1.8949) | 4.4946*** (0.1123) | 4.4951*** (0.1125) | 3.8412* (2.2493) | 4.4692 (0.1463) |
No. of observations | 264 | 331 | 331 | 257 | |
Wald chi2(18), (15) for truncated and heckman, (15) | 45.22 | 64.16 | 44.22 | ||
Prob > χ2 | 0.0004 | 0.0000 | 0.0001 | ||
Pseudo R2 | 0.6571 | - | 0.1917 | -- | |
Inverse mills ratio P value | 0.313 | ||||
Log pseudo likelihood | -13.46 | -1672.67 | -117.74 | -- | |
Lambda (ʎ) χ0.1 | 3136.78 25.99 |
Table 3 Factors influencing adoption and intensity of adoption modern varieties.
Variable | Double hurdle estimate | Tobit regression | Heckman estimate | ||
---|---|---|---|---|---|
Hurdle 1 (Probit regression) | Hurdle 2 (Truncated regression) | Probit regression | Ordinary least squares | ||
Demographic characteristics | |||||
Age | 0.0043** (0.0019) | 0.0016 (0.0016) | 0.0016 (0.0016) | 0.1538** (0.0727) | 0.0022 (0.0026) |
Education | 0.0179* (0.0101) | 0.0119 (0.0226) | 0.0119 (0.0227) | 0.6328 (0.6041) | 0.0163 (0.0363) |
Caste | -0.0536 (0.0399) | -1.3784 (2.4230) | |||
Household size | -0.0452*** (0.0172) | 0.0243* (0.0136) | -0.0244* (0.0137) | -1.5981* (0.9176) | -0.0209 (0.0142) |
Experience | -0.0032** (0.0014) | -0.0015* (0.0009) | -0.0015* (0.0009) | -0.1128* (0.0600) | -0.0027* (0.0016) |
Management characteristics | |||||
Farm records | 0.0125 (0.0246) | 0.4734 (1.1471) | |||
Risk aversion | 0.1256*** (0.0415) | 0.1319* (0.0831) | 0.1312* (0.0832) | 2.9912** (1.2257) | 0.1600* (0.0779) |
Off-farm | -0.1128*** (0.0279) | 0.0074 (0.0607) | 0.0072 (0.0614) | -3.2509** (1.2601) | 0.0008 (0.0569) |
Credit | 0.0493 (0.0520) | 0.0500 (0.0522) | -0.0199 (0.0670) | ||
Amount of credit | -0.0000412* (0.0000) | -0.0000412 (0.0000) | |||
FBO membership | 0.0290 (0.0573) | -0.0170 (0.0576) | 0.0035 (0.0676) | ||
Production characteristics | |||||
Land size | 0.0319*** (0.0010) | 0.0534*** (0.0178) | 0.0537*** (0.0181) | 1.1300* (0.6953) | 0.0481* (0.0129) |
Number of rice plots | 0.0044 (0.0073) | 0.0045 (0.0073) | -0.0002 (0.0071) | ||
Flooding land | 0.0059 (0.0169) | 0.2162 (1.2032) | |||
Seed cost | -0.00002* (0.0000) | -0.0006 (0.0004) | |||
Insecticide cost | -8.46e-06* (5.16e-06) | 0.00004*(0.00002) | -4.28e-07 (4.02e-07) | -0.0003 (0.0004) | 0.0000 (0.0000) |
NPK cost | -1.47e-07 (5.84e-06) | -0.00006* (0.00004) | 2.05e-07 (4.58e-07) | 0.0000 (0.0004) | 0.0000 (0.0000) |
Yield | 0.0040*** (0.0015) | 0.1427* (0.8585) | |||
MVs high yield | 0.0457*** (0.0167) | 0.1317** (0.0585) | -0.1317 (0.0585) | 1.9609 (1.3097) | 0.1212** (0.0638) |
MVs resistant to diseases | 0.0351*** (0.0127) | 1.9082 (1.6247) | |||
MVs seed availability | 0.0400** (0.0170) | 0.0972* (0.0609) | 0.0988** (0.0619) | 1.5497* (0.9122) | 0.1385** (0.0622) |
Post-harvest characteristics | |||||
MV easily marketable | -0.0102 (0.0560) | -0.0090 (0.0567) | 0.0334 (0.0780) | ||
Constant | 3.8425** (1.8949) | 4.4946*** (0.1123) | 4.4951*** (0.1125) | 3.8412* (2.2493) | 4.4692 (0.1463) |
No. of observations | 264 | 331 | 331 | 257 | |
Wald chi2(18), (15) for truncated and heckman, (15) | 45.22 | 64.16 | 44.22 | ||
Prob > χ2 | 0.0004 | 0.0000 | 0.0001 | ||
Pseudo R2 | 0.6571 | - | 0.1917 | -- | |
Inverse mills ratio P value | 0.313 | ||||
Log pseudo likelihood | -13.46 | -1672.67 | -117.74 | -- | |
Lambda (ʎ) χ0.1 | 3136.78 25.99 |
Poverty variable | Adopter | Non-adopter | Overall | Odisha government |
---|---|---|---|---|
Headcount index | 0.156 (15.6) | 0.529 (52.9) | 0.174 (17.4) | 0.357 (35.7) |
Poverty gap index | 0.062 (6.2) | 0.322 (32.2) | 0.074 (7.4) | 0.070 (7.0) |
Poverty severity index | 0.033 (3.3) | 0.197 (19.7) | 0.041 (4.1) | 0.020 (2.2) |
Table 4 Estimates of poverty situation indicators using objective poverty line. %
Poverty variable | Adopter | Non-adopter | Overall | Odisha government |
---|---|---|---|---|
Headcount index | 0.156 (15.6) | 0.529 (52.9) | 0.174 (17.4) | 0.357 (35.7) |
Poverty gap index | 0.062 (6.2) | 0.322 (32.2) | 0.074 (7.4) | 0.070 (7.0) |
Poverty severity index | 0.033 (3.3) | 0.197 (19.7) | 0.041 (4.1) | 0.020 (2.2) |
Estimation method | Per capita expenditure (₹) | SE (₹) | t test | No. of treatments | Number of controls |
---|---|---|---|---|---|
SATT nearest neighbour matching | 3 222.00 | 566.17 | 5.69 | 346 | 13 |
SATT stratification matching | 3 250.27 | 495.02 | 6.57 | 346 | 17 |
SATT radius matching | 3 853.17 | 704.94 | 5.47 | 74 | 13 |
SATT kernel matching | 3 268.36 | 466.30 | 7.00 | 346 | 17 |
Regression with dummy | 3 601.96 | 682.34 | 5.28 | - | - |
Table 5 Matching estimates of sample average treatment effect on the treated (SATT).
Estimation method | Per capita expenditure (₹) | SE (₹) | t test | No. of treatments | Number of controls |
---|---|---|---|---|---|
SATT nearest neighbour matching | 3 222.00 | 566.17 | 5.69 | 346 | 13 |
SATT stratification matching | 3 250.27 | 495.02 | 6.57 | 346 | 17 |
SATT radius matching | 3 853.17 | 704.94 | 5.47 | 74 | 13 |
SATT kernel matching | 3 268.36 | 466.30 | 7.00 | 346 | 17 |
Regression with dummy | 3 601.96 | 682.34 | 5.28 | - | - |
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