The research was assessed status of adopting improved rice technology as well as evaluate its impact on rice productivity and gross farm income in Ethiopia. The research showed the importance of adopting improved rice technologies using impact evaluating techniques such as propensity scoring matching (PSM). The research was used descriptive and econometric methods of data analysis to elaborate the respondents’ characteristics, farming practices, adoption status and to estimate its impact. The research used multistage sampling methods to select 180 smallholder rice producers. Amhara and Benshangul Gumuz region are the potential rice producers which targeted for this study. Zones, districts and kebles of these regions were selected random that can be represent the region as well as the rice producers in Ethiopia. The research revealed that 44.44% of the respondents were adopted improved rice technology and pawe_1 is the most frequently used by respondents. The econometric result revealed that treated groups were gained high rice output 3,019.70 quintal per hectare over the controlled groups 1,971.40 quintal per hectare as well as in terms of gross income treated groups were earned higher income which is 46,159.78 ETHB than the controlled groups which were earned 29,797.14 ETHB on average. This indicated that adopting improved rice technology was brought 34.72% and 35.45% of increment in rice productivity and gross income on smallholders’ rice producers respectively. Adopting of agricultural technologies are a means of improving the smallholder farmers crop production, productivities and income generated from that farm activities. Therefore, any governmental and non-governmental institution should be focused on the outreach of these agricultural technologies to end user over all part of the country.
Published in | International Journal of Agricultural Economics (Volume 9, Issue 2) |
DOI | 10.11648/j.ijae.20240902.17 |
Page(s) | 110-119 |
Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
Copyright |
Copyright © The Author(s), 2024. Published by Science Publishing Group |
Adoption, Impact, Improve Variety, Groundnut Productivity, Income and PSM
2.1. Description of the Study Area
2.2. Sampling Procedure and Sample Size Determination
District | # of sample unit selected | Share of sample in % |
---|---|---|
Pawi | 95 | 52.78 |
Jawe | 85 | 47.14 |
180 | 100 |
2.3. Source and Techniques of Data Collection
2.4. Econometric Analysis
2.4.1. Propensity Score Matching (PSM)
2.4.2. Estimating Propensity Score Techniques
3.1. Demographic and Socioeconomic Characteristics of Respondents
Dummy variables | Adopter | Non-Adopter | Total | X2 |
---|---|---|---|---|
Sex(adopter) | 80 | 100 | 180 | 0.01 |
Male | 70 | 87 | 157 | |
Extension Contact | 80 | 100 | 180 | 1.28 |
Yes | 46 | 49 | 95 | |
Soil Fertility | 80 | 100 | 180 | 5.95** |
Yes | 45 | 38 | 83 | |
Trained on Rice Production | 80 | 100 | 180 | 5.52** |
Yes | 35 | 27 | 62 | |
Member of Cooperative | 80 | 100 | 180 | 9.43*** |
Yes | 48 | 37 | 85 |
3.2. Respondents Socio-Economic Characteristics
Continous variables | Adopter | Non-Adopter | Whole sample | T-Value |
---|---|---|---|---|
Age | 41.60 | 43.02 | 42.38 | 1.22 |
Education | 1.54 | .98 | 1.23 | 2.64** |
Farm exp | 5.48 | 5 | 5.21 | 1.22 |
farm land | 2.92 | 2.98 | 2.95 | 0.65 |
Rice land | 0.589 | 0.59 | 0.59 | 0.12 |
Own TLU | 4.5 | 4.39 | 4.44 | 0.40 |
Dist/FTC | 1.75 | 1.95 | 1.86 | 1.64 |
Dist/market | 22.94 | 28.53 | 26.04 | 8.33*** |
Dist/coop | 1.34 | 1.52 | 1.44 | 1.26 |
Dist/mill | 1.57 | 1.50 | 1.53 | 0.47 |
3.3. Improved Rice Variety Preference and Its Adoption in North Western Ethiopia
Rice Variety | District | Total | Adoption rate | |
---|---|---|---|---|
Pawe | Jawi | |||
Pawe_1 | 31 | 19 | 50 | 27.78 |
NERICA_4 | 11 | 9 | 20 | 11.11 |
X-Jegina | 3 | 7 | 10 | 5.55 |
NERICA_1 | 0 | 0 | 0 | 0 |
SUPERICA_1 | 0 | 0 | 0 | 0 |
Old Rice Variety | 50 | 50 | 100 | 55.56 |
3.4. Adoption of Improved Rice Technology by District
District | Treated | Controlled | % of Treated | % of Controlled |
---|---|---|---|---|
Pawi | 45 | 50 | 47.36 | 52.64 |
Jawe | 35 | 50 | 41.18 | 58.82 |
Whole | 80 | 100 | 44.44 | 55.56 |
3.5. Determining Exogenous Variables Causing Over Estimate of Outcome Variable
Cofactors | Coefficients | Std.err | Z Value |
---|---|---|---|
Sex | 0.09 | 0.30 | 0.31 |
Education | 0.14 | 0.07 | 1.93 |
Age | -0.03 | 0.02 | -1.51 |
Rice farm experience | 0.09 | 0.05 | 1.18 |
Allocated land for rice production | 0.22 | 0.36 | 0.6 |
Access to credit | 0.13 | 0.22 | 0.58 |
Labor force | 0.09 | 0.14 | 0.67 |
Extension contact | 0.17 | 0.20 | 0.85 |
Soil fertility | 0.46 | 0.20 | 2.27 |
Trained on rice production | 0.49 | 0.21 | 2.30 |
Member of Cooperatives | 0.57 | 0.20 | 2.84 |
Constant | -0.92 | 0.70 | -1.31 |
3.6. Estimate Propensity Score Matching and Identifying the Common Support Region
Groups | Ob | Mean | Std. de | Min | Max |
---|---|---|---|---|---|
Treated | 80 | 0.5575 | 0.2149 | 0.0532 | 0.9056 |
Controlled | 100 | 0.3590 | 0.1818 | 0.0455 | 0.7820 |
Common Support | On Support | Off Support | Whole | ||
Treated | 74 | 6 | 80 | ||
Controlled | 96 | 4 | 100 | ||
Whole | 170 | 10 | 180 |
3.7. Treated and Controlled Groups of Propensity Score Sketching
3.8. Selection of Best Matching Method
Matching Estimators with different band width | Selection Criteria | ||
---|---|---|---|
Balancing Test | Pseudo R2 | Matched Sample Size | |
Kernel | |||
0.01 | 6 | 0.1305 | 147 |
0.1 | 6 | 0.1305 | 170 |
0.25 | 6 | 0.1305 | 170 |
0.5 | 6 | 0.1305 | 170 |
Radius | |||
0.01 | 6 | 0.1305 | 170 |
0.1 | 6 | 0.1305 | 170 |
0.25 | 6 | 0.1305 | 170 |
0.5 | 6 | 0.1305 | 170 |
Neighbor | |||
Neighbor 1 | 6 | 0.1305 | 170 |
Neighbor 2 | 6 | 0.1305 | 170 |
Neighbor 3 | 6 | 0.1305 | 170 |
Neighbor 4 | 6 | 0.1305 | 170 |
3.9. Impact of Improved Rice Variety Adoption on Rice Productivity in NW Ethiopia
Outcome variable | Sample | Adopters | Non-Adopters | diff | SE | T-Stat |
---|---|---|---|---|---|---|
Rice Yield | Unmatched | 3,015.70 | 1971.20 | 1,044.5 | 124.00 | 4.95 |
ATT | 3,019.70 | 1971.40 | 1,048.4 | 143.44 | 4.42 | |
ATU | 1,971.40 | 3,019.70 | 1,048.4 | |||
ATE | 1,048.4 | |||||
Log of Rice Yield | Unmatched | 12.39 | 11.66 | 0.73 | 0.09 | 4.51 |
ATT | 12.40 | 11.66 | 0.74 | 0.11 | 4.07 | |
ATU | 11.66 | 12.40 | 0.74 | |||
ATE | 0.74 |
3.10. Impact of Improved Rice Variety Adoption on Gross Farm Income in NW Ethiopia
Outcome variable | Sample | Adopters | Non-Adopters | diff | SE | T-Stat |
---|---|---|---|---|---|---|
Gross Farm income | Unmatched | 45,687.93 | 29,863.48 | 15,824.45 | 124.0 | 4.95 |
ATT | 46,159.78 | 29,797.14 | 16,362.64 | 143.4 | 4.42 | |
ATU | 29,797.14 | 46,159.78 | 16,362.64 | |||
ATE | 16,362.64 | |||||
Log of gross Farm income | Unmatched | 17.01 | 16.27 | 0.74 | 0.09 | 4.51 |
ATT | 17.03 | 16.27 | 0.76 | 0.11 | 4.07 | |
ATU | 16.27 | 17.03 | 0.76 | |||
ATE | 0.76 |
3.11. Analysis of Sensitivity on Rice Productivity and Gross Farm Income
Gamma | Omega (Ω+) | Omega (Ω-) |
---|---|---|
dx=1 | 3.2e-15 | 3.2e-15 |
dx =1.25 | 4.1e-12 | 4.1e-12 |
dx =1.5 | 2.1e-12 | 2.1e-12 |
dx =1.75 | 8.1e-12 | 8.1e-12 |
dx =2 | 1.1e-16 | 1.1e-16 |
dx =2.25 | 4.2e-15 | 4.2e-15 |
dx =2.5 | 9.1e-12 | 9.1e-12 |
dx =2.75 | 1.1e-12 | 1.1e-12 |
dx =3 | 9.1e-12 | 9.1e-12 |
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APA Style
Tesfay, W., Woundiferaw, B. (2024). Impact of Improved Rice Variety Adoption on Smallholder Farmers Rice Productivity and Gross Farm Income Enhancement in North Western Ethiopia. International Journal of Agricultural Economics, 9(2), 110-119. https://doi.org/10.11648/j.ijae.20240902.17
ACS Style
Tesfay, W.; Woundiferaw, B. Impact of Improved Rice Variety Adoption on Smallholder Farmers Rice Productivity and Gross Farm Income Enhancement in North Western Ethiopia. Int. J. Agric. Econ. 2024, 9(2), 110-119. doi: 10.11648/j.ijae.20240902.17
AMA Style
Tesfay W, Woundiferaw B. Impact of Improved Rice Variety Adoption on Smallholder Farmers Rice Productivity and Gross Farm Income Enhancement in North Western Ethiopia. Int J Agric Econ. 2024;9(2):110-119. doi: 10.11648/j.ijae.20240902.17
@article{10.11648/j.ijae.20240902.17, author = {Welay Tesfay and Belete Woundiferaw}, title = {Impact of Improved Rice Variety Adoption on Smallholder Farmers Rice Productivity and Gross Farm Income Enhancement in North Western Ethiopia }, journal = {International Journal of Agricultural Economics}, volume = {9}, number = {2}, pages = {110-119}, doi = {10.11648/j.ijae.20240902.17}, url = {https://doi.org/10.11648/j.ijae.20240902.17}, eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijae.20240902.17}, abstract = {The research was assessed status of adopting improved rice technology as well as evaluate its impact on rice productivity and gross farm income in Ethiopia. The research showed the importance of adopting improved rice technologies using impact evaluating techniques such as propensity scoring matching (PSM). The research was used descriptive and econometric methods of data analysis to elaborate the respondents’ characteristics, farming practices, adoption status and to estimate its impact. The research used multistage sampling methods to select 180 smallholder rice producers. Amhara and Benshangul Gumuz region are the potential rice producers which targeted for this study. Zones, districts and kebles of these regions were selected random that can be represent the region as well as the rice producers in Ethiopia. The research revealed that 44.44% of the respondents were adopted improved rice technology and pawe_1 is the most frequently used by respondents. The econometric result revealed that treated groups were gained high rice output 3,019.70 quintal per hectare over the controlled groups 1,971.40 quintal per hectare as well as in terms of gross income treated groups were earned higher income which is 46,159.78 ETHB than the controlled groups which were earned 29,797.14 ETHB on average. This indicated that adopting improved rice technology was brought 34.72% and 35.45% of increment in rice productivity and gross income on smallholders’ rice producers respectively. Adopting of agricultural technologies are a means of improving the smallholder farmers crop production, productivities and income generated from that farm activities. Therefore, any governmental and non-governmental institution should be focused on the outreach of these agricultural technologies to end user over all part of the country. }, year = {2024} }
TY - JOUR T1 - Impact of Improved Rice Variety Adoption on Smallholder Farmers Rice Productivity and Gross Farm Income Enhancement in North Western Ethiopia AU - Welay Tesfay AU - Belete Woundiferaw Y1 - 2024/04/17 PY - 2024 N1 - https://doi.org/10.11648/j.ijae.20240902.17 DO - 10.11648/j.ijae.20240902.17 T2 - International Journal of Agricultural Economics JF - International Journal of Agricultural Economics JO - International Journal of Agricultural Economics SP - 110 EP - 119 PB - Science Publishing Group SN - 2575-3843 UR - https://doi.org/10.11648/j.ijae.20240902.17 AB - The research was assessed status of adopting improved rice technology as well as evaluate its impact on rice productivity and gross farm income in Ethiopia. The research showed the importance of adopting improved rice technologies using impact evaluating techniques such as propensity scoring matching (PSM). The research was used descriptive and econometric methods of data analysis to elaborate the respondents’ characteristics, farming practices, adoption status and to estimate its impact. The research used multistage sampling methods to select 180 smallholder rice producers. Amhara and Benshangul Gumuz region are the potential rice producers which targeted for this study. Zones, districts and kebles of these regions were selected random that can be represent the region as well as the rice producers in Ethiopia. The research revealed that 44.44% of the respondents were adopted improved rice technology and pawe_1 is the most frequently used by respondents. The econometric result revealed that treated groups were gained high rice output 3,019.70 quintal per hectare over the controlled groups 1,971.40 quintal per hectare as well as in terms of gross income treated groups were earned higher income which is 46,159.78 ETHB than the controlled groups which were earned 29,797.14 ETHB on average. This indicated that adopting improved rice technology was brought 34.72% and 35.45% of increment in rice productivity and gross income on smallholders’ rice producers respectively. Adopting of agricultural technologies are a means of improving the smallholder farmers crop production, productivities and income generated from that farm activities. Therefore, any governmental and non-governmental institution should be focused on the outreach of these agricultural technologies to end user over all part of the country. VL - 9 IS - 2 ER -