scholarly journals Adoption of improved agricultural technology and its impact on household income: a propensity score matching estimation in eastern Ethiopia

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Muluken G. Wordofa ◽  
Jemal Y. Hassen ◽  
Getachew S. Endris ◽  
Chanyalew S. Aweke ◽  
Dereje K. Moges ◽  
...  
Keyword(s):  
Propensity Score ◽  
Propensity Score Matching ◽  
Technology Use ◽  
Household Income ◽  
Agricultural Technology ◽  
Primary Data ◽  
Farm Income ◽  
Agricultural Technologies ◽  
Eastern Ethiopia ◽  
The Impact

Abstract Background Adoption of improved agricultural technologies remains to be a promising strategy to achieve food security and poverty reduction in many developing countries. However, there are limited rigorous impact evaluations on the contributions of such technologies on household welfare. This paper investigates the impact of improved agricultural technology use on farm household income in eastern Ethiopia. Methods Primary data for the study was obtained from a random sample of 248 rural households, 119 of which are improved technology users and the rest are non-users. The research employed the Propensity Score Matching (PSM) procedure to establish the causal relationship between adoption of improved crop and livestock technologies and changes in farm income. Results Results from the econometric analysis show that households using improved agricultural technologies had, on average, 23,031.28 Birr (Birr is the official currency of Ethiopia. The exchange rate according to the National Bank of Ethiopia (NBE) was 1 USD = 27.6017 Birr on 04 October 2018.) higher annual farm income compared to those households not using such technologies. Our findings highlight the importance of promoting multiple and complementary agricultural technologies among rural smallholders. Conclusions We suggest that rural technology generation, dissemination and adoption interventions be strengthened. Moreover, the linkage among research, extension, universities and farmers needs to be enhanced through facilitating a multistakeholders innovation platforms.

Impact of Improved Agricultural Technology Use on Household Income in Eastern Ethiopia: Empirical Evidence from a Propensity Score Matching Estimation

2021 ◽  
pp. 232102492110076
Author(s):  
Muluken G. Wordofa ◽  
Jemal Y. Hassen ◽  
Getachew S. Endris ◽  
Chanyalew S. Aweke ◽  
Dereje K. Moges ◽  
...  
Keyword(s):  
Propensity Score ◽  
Propensity Score Matching ◽  
Technology Use ◽  
Household Income ◽  
Agricultural Technology ◽  
Primary Data ◽  
Farm Income ◽  
Agricultural Technologies ◽  
Eastern Ethiopia ◽  
The Impact

This article investigates the impact of improved agricultural technology use on farm household income in eastern Ethiopia. Primary data for the study were obtained from a random sample of 248 rural households, 119 of which are improved technology users and the rest are non-users. The research employed the propensity score matching procedure to establish the causal relationship between adoption of improved crop and livestock technologies and changes in farm income. Results from the econometric analysis show that households using improved agricultural technologies had, on average, 23,031.28 Birr1 higher annual farm income compared to those households not using such technologies. Our findings highlight the importance of promoting multiple and complementary agricultural technologies among rural smallholders. Therefore, we suggest that rural technology generation, dissemination and adoption interventions be strengthened. Moreover, the linkage among research, extension, universities and farmers needs to be enhanced through facilitating multistakeholder innovation platforms.

scholarly journals Impact Evaluation of Raskin Program using Matching Method: Case of IFLS 5

JEJAK ◽  
2018 ◽  
Vol 11 (1) ◽  
pp. 207-223
Author(s):  
Endiarjati Dewandaru Sadono
Keyword(s):  
Propensity Score ◽  
Propensity Score Matching ◽  
Family Life ◽  
Household Income ◽  
Impact Evaluation ◽  
Matching Method ◽  
Indonesia Family Life Survey ◽  
Small Benefit ◽  
Using Data ◽  
The Impact

Beras untuk Keluarga Miskin (RASKIN) program has been applied since 1998 and has been renamed as Beras Sejahtera (RASTRA) in early 2017, but their effectiveness is still debatable. This study tries to evaluate the impact of RASKIN program on household income. Using data from 3,745 households in Indonesia Family Life Survey (IFLS) 5 that has been estimated using propensity score matching, this study has identified precisely that RASKIN program has a negative and significant effect on household income. This happens because the benefits that reveived by Rumah Tangga Sasaran (RTS) are very small. The small benefit is affected by the amount of rice received, frequency and price that have been paid to get RASKIN is not in accordance with the guidelines. The result of this study is along with previous studies, where the amount and price of rice that distributed through RASKIN program is not exactly correct. Therefore, there must be a change in program format, not just renaming from RASKIN to RASTRA only.

scholarly journals The Impact of Program Participation on Rural Household Income: Evidence from China’s Whole Village Poverty Alleviation Program

2019 ◽  
Vol 11 (6) ◽  
pp. 1545 ◽  
Author(s):  
Junying Lin ◽  
Zhonggen Zhang ◽  
Lingli Lv
Keyword(s):  
Propensity Score ◽  
Propensity Score Matching ◽  
Household Income ◽  
Poverty Alleviation ◽  
Household Head ◽  
The Political ◽  
Program Participation ◽  
Household Data ◽  
The Poor ◽  
The Impact

Villagers’ participation in poverty alleviation programs has received considerable attention, especially with regard to the poor. However, not much is known about the welfare effect of villagers’ program participation. This paper analyzes the impact of villagers’ program participation on their incomes. We used household data from 529 villagers in China’s Whole Village Poverty Alleviation Program. We focused on two types of program participation—discussion and voting. Using the propensity score matching approach, we estimate the impact of rural households’ program participation on their income. The results show that the education and the political career of the household head determine program participation. Households participating in discussion and voting have a positive and significant effect on household income. Richer households benefit more from the program. However, the poor receive less benefits. We conclude that broadening villager’s participation can boost the effectiveness of China’s poverty alleviation program.

scholarly journals Does microcredit use helps farmers win battle against food insecurity: evidence from Jimma zone of Southwest Ethiopia

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Amanuel Berhanu ◽  
Abayineh Amare ◽  
Birki Gurmessa ◽  
Yadeta Bekele ◽  
Tamiru Chalchisa
Keyword(s):  
Food Security ◽  
Propensity Score ◽  
Propensity Score Matching ◽  
Smallholder Farmers ◽  
Labour Force ◽  
Household Food Security ◽  
Farm Income ◽  
Household Food ◽  
Jimma Zone ◽  
The Impact

Abstract Background Lack of access to credit precludes smallholder farmers from making investment that generates greater level of income, consumption and wealth. To reverse this limit, Oromia Credit and Saving Share Company has been providing microcredit for rural households for the last two decades in the study area. Yet, there is limited knowledge on the impact of this microcredit service on rural household food security in Jimma zone. Therefore, this research aims at generating location-specific data on the impact of microcredit utilization on household food security in the study area. A multistage sampling procedure was employed to select 360 sample households. Data were generated through household survey, focus group discussion and key informant interview. Both descriptive and econometric data analysis techniques (binary logit model and Propensity score matching) were used. Results The results reveal that educational level, family size; land size and non/off-farm income of the households influenced microcredit utilization positively, whereas livestock ownership and farm income negatively influenced it. The analysis of food security status indicate that large proportion of households are food secure. The Propensity score matching result expose that microcredit utilization has generated a positive and significant impact on household food security. Conclusions Efforts towards scaling out services of microcredit institutions should target improving financial literacy of the rural poor and their current financial need on the basis of other resources such as land and livestock they owned with the ultimate goal of ensuring household food security. It is also imperative to realize the labour force capacity of the households in the process of expanding credit service.

Welfare impacts of rural credit and saving program in Kurfa Chele district, eastern Ethiopia: a propensity score matching estimation

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Eric N. Okoyo ◽  
Muluken Gezahegn Wordofa ◽  
Jemal Y. Hassen ◽  
Moges Bezabih
Keyword(s):  
Propensity Score ◽  
Propensity Score Matching ◽  
Family Size ◽  
Educational Status ◽  
Calorie Intake ◽  
Eastern Ethiopia ◽  
Content Type ◽  
Rural Credit ◽  
Credit Program ◽  
The Impact

PurposeThis study is conducted to evaluate the impact of rural credit on farm household income and food security.Design/methodology/approachA multistage random sampling procedure is implemented to select 180 (82 credit user and 98 non-credit user) households from Kurfa Chele district, eastern Ethiopia. The Propensity Score Matching technique is used to estimate the impact of credit utilization on the welfare indicators.FindingsThe results of the econometric model estimation show that participation in the rural credit program was positively influenced by a household's educational status, family size, voluntary saving and participation in training related to credit and saving. On the contrary, livestock holding and extension advice were found to negatively affect participation. Furthermore, participation in rural credit program is found to increase annual income by 59% and calorie intake by 21%. These are significant results implying that participation in the rural credit and saving program improved household welfare in the study area.Originality/valueThis study is important because it shows the welfare impact of making credit program available to potential users in the study area. Moreover, for effectiveness of the credit program it is necessary to target households with relatively larger family size and those with relatively better education (to induce change among the wider farming community). It is also essential to focus on the saving behavior of the program beneficiaries and enhancing the management system by ensuring that sufficient development agents are in place.

scholarly journals Does Off-Farm Work Improve Farm Income? Empirical Evidence from Tolon District in Northern Ghana

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Benjamin Tetteh Anang ◽  
Kwame Nkrumah-Ennin ◽  
Joshua Anamsigiya Nyaaba
Keyword(s):  
Propensity Score ◽  
Propensity Score Matching ◽  
Empirical Evidence ◽  
Farm Size ◽  
Northern Ghana ◽  
Farm Income ◽  
Income Diversification ◽  
Farm Work ◽  
On Farm ◽  
The Impact

Participation of farm households in off-farm work has gained prominence in recent times as an income diversification strategy. The effect of off-farm work on farm income is however unclear. This paper therefore sought to provide empirical evidence of the income effect of off-farm activity participation using a cross section of maize farmers in Tolon District of Ghana as a case study. In order to account for sample selection bias, the Heckman selection model was used to estimate the factors influencing participation in off-farm work and the determinants of farm income. Furthermore, the study employed propensity score matching to evaluate the impact of off-farm work on farm income. The results indicate that participation in off-farm work is influenced by sex, age, and years of formal education of the respondent, farm size, and number of dependents while farm income is influenced by age of the respondent, farm size, and access to credit. In addition, the result of the propensity score matching revealed that participants in off-farm work increased their farm income by at least GH¢ 1702 as a result of income diversification. The rural economy therefore provides off-farm and on-farm linkages that enhance farmers’ income from agriculture. The creation of employment opportunities outside the farm will therefore complement on-farm work and enhance income from farming.

scholarly journals DAMPAK KONVERSI LAHAN PERTANIAN TERHADAP PENDAPATAN RUMAH TANGGA PETANI DI KABUPATEN KARANGANYAR

2017 ◽  
Vol 27 (1) ◽  
pp. 93
Author(s):  
Umi Barokah ◽  
Suprapti Supardi ◽  
Sugiharti Mulya Handayani
Keyword(s):  
Household Income ◽  
Agricultural Land ◽  
Secondary Data ◽  
Farm Households ◽  
Primary Data ◽  
Farm Income ◽  
Test Analysis ◽  
Field Function ◽  
The Impact

<p>This study aims to (1) analyzing the amount of land conversion and the factors that affect, (2) identify and analyze changes in household income structure of farm households, (3) analyze the impact of conversion on agricultural land to the income distribution, employment and welfare of farm households. The basic method on this study is a descriptive analytic. Determination of the districts location is based on (1) the number of people who worked as farmers themselves, (2) the amount and type of existing industries and (3) ease of reaching the central interconnected economy. Sub-district is elected Jumantono and Jaten. Type of data used include (1) primary data is the results of interviews with farm households, (2) secondary data from relevant instances. The results showed (1) during the 12 years there is a change 0,120 ha of wet rice field function per household farmer and owned land is the only factor affecting the conversion of agricultural land; (2) The proportion of farm income reduced by 8.30% from 42% to 33.7% and the proportion of outside farm income increased 10.30% from 54% to 64.30%), (3) the results of t test analysis with α = 5 % shows the employment and household income of farmers before the conversion is not the same as after the conversion of agricultural land (revenue increased to Rp 1.482 million per year). </p>

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