The Effects of Tunnel Technology on Crop Productivity and Livelihood of Smallholder Farmers in Nepal
Abstract
:1. Introduction
Tunnel House Technology in Nepal
2. Materials and Methods
2.1. Data
2.2. Econometric Framework
- Correlated with T: cov (z, T) ≠ 0;
- Uncorrelated with µ: cov (z, µ) = 0.
3. Results and Discussion
3.1. Comparison of the Adopters and Non-Adopters
3.2. Impact of Tunnel Adoption on Crop Productivity
3.3. Impact on Net Crop Income
4. Conclusions
Limitations of the Study
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Variable | Description of Variable | Full Sample | Non-Adopters (NA) | Tunnel Adopters (A) | Difference (A-NA) |
---|---|---|---|---|---|
N | Number of Respondents | 154 | 92 | 62 | |
Socio-demographic | |||||
Age | Age of respondent (years) | 39.62 | 41.48 | 36.68 | −4.80 *** |
Gender | Gender of the farmer working most of the time in the farm (1 = male; 0 = female) | ||||
Female | Respondent is female (%) | 0.17 | 0.2 | 0.14 | −0.06 |
Male | Respondent is male | 0.33 | 0.4 | 0.27 | −0.13 |
Household size | Numbers of members in the household | 5.63 | 5.51 | 5.81 | 0.3 |
Active members | Number of members of the working-age group (15–59 years) | 3.88 | 3.87 | 3.89 | 0.02 |
Dependent members | Number of members of age groups below 15 and above 59 years | 1.78 | 1.64 | 1.92 | 0.28 |
Ethnicity | Ethnic background of the respondent | 0 | |||
Dalit | Respondent is from Dalit ethnic community (1 = Dalit; 0 = others) | 0.06 | 0.09 | 0.03 | −0.06 * |
Indigenous | Respondent is from indigenous community (1 = indigenous; 0 = others) | 0.19 | 0.19 | 0.19 | −0.01 * |
Higher caste | Respondent is from Brahmin and Chettri community (1 = higher caste; 0 = other) | 0.25 | 0.31 | 0.19 | −0.12 |
Educational status | Education level measured in years of schooling | ||||
Unschooled | Respondent with no formal schooling (%) | 0.06 | 0.11 | 0 | −0.11 *** |
Secondary level | Respondent with 12 or less years of schooling (%) | 0.32 | 0.34 | 0.31 | −0.03 ** |
Intermediate | Responded with more than 12 years of formal education (%) | 0.12 | 0.15 | 0.1 | −0.05 |
Economic variables | |||||
Farm size | Area of land under vegetable cultivation measured in hectare (ha) | 0.226 | 0.373 | 0.15 *** | |
Cost per ha | Cost of production of vegetables in 1 ha of land (USD/ha) | 11,441.86 | 5606.31 | 17,277.41 | 11,671.10 *** |
Crop productivity | Total quantity of vegetables produced in 1 ha of land (Ton/ha) | 34.92 | 19.73 | 50.11 | 30.38 *** |
Income per ha | Total income from vegetable in 1 ha of land (USD/ha) | 15,355.82 | 8233.6 | 22,478.05 | 14,244.44 *** |
Net crop income per ha | Profit from vegetables in 1 ha of land (USD/ha) | 3913.96 | 2627.29 | 5200.63 | 2573.34 ** |
Neighbours’ influence | Influence of neighbours’ farming practices on adoption of tunnel technology (1 = yes; 0 = otherwise) | 0.33 | 0.35 | 0.32 | −0.03 ** |
Distance to nearest agrovet | Distance between the farm gate and nearest agrovet (km) | 13.06 | 15.53 | 9.4 | −6.13 ** |
Variable | Coefficient |
---|---|
Age | −0.057 *** (0.019) |
Gender | −0.340 (0.304) |
Active members | 0.086 (0.116) |
Dependent members | 0.094 (0.120) |
Dalit | −1.494 *** (0.572) |
Indigenous | 0.431 (0.311) |
Educational status | 0.946 *** (0.324) |
Farm size | 2.919 *** (0.808) |
Neighbours’ influence | 2.319 *** (0.678) |
Distance to nearest agrovet | −0.159 *** (0.033) |
Constant | −0.967 (1.504) |
Number of observations | 154 |
Mean dependent var | 0.403 |
SD dependent var | 0.492 |
Pseudo r-squared | 0.479 |
χ2 | 99.449 |
Akaike crit. (AIC) | 130.159 |
Bayesian crit. (BIC) | 163.565 |
Variable | Treatment Model | OLS | |
---|---|---|---|
First Stage | Second Stage | ||
Adoption of tunnel technology | 32.989 *** (1.634) | 25.717 *** (1.363) | |
Age | −0.046 ** (0.018) | 0.033 (0.064) | −0.030 (0.059) |
Gender | −0.296 (0.303) | 0.139 (1.173) | −0.378 (1.105) |
Household size | 0.063 (0.112) | −0.188 (0.444) | |
Active members | −0.238 (0.415) | ||
Dependent members | 0.052 (0.131) | −0.202 (0.538) | −0.277 (0.407) |
Dalit | −1.750 *** (0.597) | 0.908 (1.800) | −1.513 (1.687) |
Indigenous | 0.389 (0.305) | −2.526048 | −1.457 (1.093) |
Educational status | 0.921 *** (0.320) | −0.121 (0.536) | −0.432 (0.564) |
Farm size | 2.931 *** (0.771) | 7.980 *** (2.760) | 14.094 *** (2.597) |
Neighbours’ influence | 2.148 *** (0.658) | 0.481 (1.234) | |
Distance to nearest agrovet | −0.163 *** (0.029) | −0.456 *** (0.097) | |
Constant | −1.082 (1.402) | 17.392 *** (3.690) | 27.611 *** (4.019) |
ath (ρ) | −0.671 *** (0.207) | ||
ln (σ) | 1.890 *** (0.063) | ||
N | 154 | 154 | |
Wald χ2/F-statistic | 655.38 | 85.876 | |
Log-likelihood | −552.402 | ||
R-squared | 0.869 | ||
LR test of independent equations (Prob > χ2) | 0 | ||
Durbin (score) χ2 | 18.834 *** | ||
Wu–Hausman F score | 19.926 *** |
Variable | Treatment Model | OLS | |
---|---|---|---|
First Stage | Second Stage | ||
Adoption of tunnel technology | 1746.252 *** (386.138) | 2448.086 *** (258.463) | |
Age | −0.056 *** (0.019) | −9.794 (11.910) | −6.241 (11.275) |
Gender | −0.276 (0.310) | −74,032.52 | −73,706.38 |
Household size | 0.054 (0.119) | −10,656.26 | |
Active members | −116.326 (78.633) | ||
Dependent members | 0.019 (0.135) | −22.911 (96.671) | −10,729.1 |
Dalit | −1.490 *** (0.562) | −648.452 ** (328.949) | −369.690 (319.783) |
Indigenous | 0.407 (0.309) | −3.560 (212.643) | −61.703 (207.193) |
Educational status | 0.736 ** (0.372) | −17,068.11 | −38.211 (106.829) |
Farm size | 2.785 *** (0.779) | 3853.835 *** (521.072) | 3161.127 *** (492.295) |
Neighbours’ influence | 1.922 ** (0.768) | 349.721 (233.887) | |
Distance to nearest agrovet | −0.162 *** (0.032) | 68.329 *** (18.327) | |
Constant | −0.039 (1.672) | 691.860 *** (673.998) | 984.956 ** (761.838) |
ath (ρ) | 0.291 ** (0.261) | ||
ln (σ) | 7.081 *** (0.060) | ||
N | 154 | 154 | |
Wald χ2/F-statistic | 171.24 | 23.982 | |
Log-likelihood | −1361.2 | ||
R-squared | 0.65 | ||
LR test of independent equations (Prob > χ2) | 0 | ||
Durbin (score) χ2 | 6.059 ** | ||
Wu–Hausman F score | 5.856 ** |
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KC, D.; Jamarkattel, D.; Maraseni, T.; Nandwani, D.; Karki, P. The Effects of Tunnel Technology on Crop Productivity and Livelihood of Smallholder Farmers in Nepal. Sustainability 2021, 13, 7935. https://doi.org/10.3390/su13147935
KC D, Jamarkattel D, Maraseni T, Nandwani D, Karki P. The Effects of Tunnel Technology on Crop Productivity and Livelihood of Smallholder Farmers in Nepal. Sustainability. 2021; 13(14):7935. https://doi.org/10.3390/su13147935
Chicago/Turabian StyleKC, Diwakar, Dinesh Jamarkattel, Tek Maraseni, Dilip Nandwani, and Pratibha Karki. 2021. "The Effects of Tunnel Technology on Crop Productivity and Livelihood of Smallholder Farmers in Nepal" Sustainability 13, no. 14: 7935. https://doi.org/10.3390/su13147935