Income Sources of Farm Households in India: Determinants, Distributional Consequences and Policy Implications

Birthal, Pratap S.; Negi, Digvijay S.; Jha, Awadesh K.; Singh, Dhiraj Kumar

doi:10.5958/j.0974-0279.27.1.003

Cited by 52 publications

(56 citation statements)

References 18 publications

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“…This was due to disparity in the number of their income-earning sources. Diversification of income sources outside of the forestry sector was a good strategy for farmers to increase their incomes, particularly when their farmlands were very limited (Kalavathi et al 2010;Birthal et al 2014;Zhao 2014). In relation to that, HKm farmers spent significant time collecting stone and sand, because this natural resource was abundant in their vicinity.…”

Section: The Structure Of Household Incomesmentioning

confidence: 99%

The income structure of smallholder forest farmers in rural Sumbawa, Indonesia

Achmad¹,

Diniyati²

2018

Biodiversitas

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Achmad B, Diniyati D. 2018. The income structure of smallholder forest farmers in rural Sumbawa, Indonesia. Biodiversitas 19: 936-946. This research investigated the economic well-being of forest farmers in Labuhan Badas Village, Sumbawa regency of Indonesia. It aimed: (i) to describe the daily economic activities of community-based forest (HKm) farmers who reside inside the state forest and of farmers in privately owned forest (POF) who reside outside the state forest areas; and (ii) to analyse their income structure in relation to the corresponding economic activities. The research was conducted from August 2015 to April 2016. The survey sample consisted of 34 HKm and 34 POF farmers who were selected purposively. Data collected through interview and focus group discussion techniques were analyzed descriptively. The research determined that the incomes of HKm farmers were generated from14 sources, mainly from activities in the non-agricultural sector, while those for POF farmers were generated from 12 sources mainly from activities in the agricultural sector. The total income of HKm farmers was significantly lower than the income of POF farmers and indicated a moderate level of economic disadvantage. The economic welfare of farmers in both research locations has been assessed to be below an adequate level. Therefore various economic innovations such as the cultivation of honey bees and the processing of unused potential resources (e.g. making wine from cashew fruit) are needed to accelerate the attainment of a decent level of economic well-being

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Section: The Structure Of Household Incomesmentioning

confidence: 99%

The income structure of smallholder forest farmers in rural Sumbawa, Indonesia

Achmad¹,

Diniyati²

2018

Biodiversitas

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“…Farm families are also engaged in nonfarm economic activities (FAO 2014). In India, although agriculture is considered the main source of income for farm households, nonfarm economic activities also contribute significantly (44%) to their incomes (Birthal et al 2014). Such a diversification toward nonfarm activities is considered important to provide economic sustainability to the livelihoods of farm households (Lanjouw & Shariff 2004;de Janvry et al 2005) as the small-scale farming alone cannot provide economic prosperity.…”

Section: Introductionmentioning

confidence: 99%

Technology adoption by small-scale full-time and part-time family farm households in the subtropics of Jammu & Kashmir

Peshin¹,

Sharma²,

Kumar³

et al. 2018

Agri. Econ. Rese. Revi.

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This paper has assessed technology adoption and its impact on the agricultural productivity for small-scale full-time and part-time farm households in the subtropical region of Jammu & Kashmir (J&K). We find only 24% of the farm households being exclusively dependent on farming for their livelihoods. For the remaining households, agriculture is a secondary economic activity. They are engaged in nonfarm economic activities, and use more of external inputs, such as fertilizers and pesticides than do the fulltime farm households. The high-yielding varieties, irrigation, herbicides and nitrogenous fertilizers are identified as important determinants of crop yield.

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“…Recent studies by Puskur (2006) utilized the tapped Gini Coefficient index to measure the disparity in the ownership of cattle in India, and from Fang, Zhu and Deng (2013) that proved the extent of distribution in China. Birthal et al (2014) used Gini Coefficient to measure income disparities among farmer households in India.…”

Section: Methodsmentioning

confidence: 99%

Analysis of Income Distribution among Goat Farmer Households in Banjarnegara District, Central Java Province Indonesia

Sugiarto

Ahmad

2015

anprod

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Abstract. The objective of this study was to describe the structure of household's income of goat farmer and analyze the distribution of goat farmer household's income in Banjarnegara. For this analysis, Banjarnegara district was divided into three agro ecological zones on the basis of altitude, i.e. low, medium and high land. 180 goat farmers were selected using multistage sampling and data were measured using descriptive statistic and Gini Coefficient. The study concluded that goat farming as a side job contributed 29% of total household income. The income from non-goat farming remain dominating a structure of household income by 71%. There was a high inequality household income among goat farmers with Gini Coefficient of 0.562. The high level of total income inequality was due to a greater relative inequality in non-goat farming income. Since there was a relationship between farm size and income, increasing the number of goats must be actualized to the goat farmers with no other livelihood. This would be able to reduce inequality of total income of goat farmers.Key words: income structure, inequality, gini coefficient Abstrak. Penelitian ini bertujuan menggambarkan struktur pendapatan rumah tangga peternak kambing dan menganalisa distribusi pendapatan rumah tangga peternak kambing di Banjarnegara. Dari hasil analisa, kabupaten Banjarnegara terbagi menjadi tiga wilayah agro ekologi berdasarkan ketinggian yaitu dataran rendah, sedang dan tinggi. 180 peternak kambing dipilih secara multistage sampling dan data diukur dengan statistic deskriptif dan koefisien Gini. Disimpulkan bahwa peternak kambing sebagai pekerjaan sampingan menyumbang 29% dari total pendapatan rumah tangga. Pendapatan di luar beternak kambing tetap mendominasi struktur pendapatan rumah tangga sebesar 71%. Ada ketidakrataan pendapatan yang tinggi karena besarnya ketidaksamaan relatif dalam pendapatan diantara peternak kambing dengan koefisien gini sebesar 0.562. Tingginya ketidaksamaan total pendapatan disebabkan karena ketidaksamaan pendapatan relatif pada pendapatan di luar beternak kambing. Karena adanya hubungan antara jumlah hewan ternak dan pendapatan, maka untuk jumlah kambing perlu ditingkatkan bagi peternak yang tidak mempunyai penghasilan lain. Hal ini akan dapat mengurangi ketidaksamaan total pendapatan peternak kambing.

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Income Sources of Farm Households in India: Determinants, Distributional Consequences and Policy Implications

Cited by 52 publications

References 18 publications

The income structure of smallholder forest farmers in rural Sumbawa, Indonesia

The income structure of smallholder forest farmers in rural Sumbawa, Indonesia

Technology adoption by small-scale full-time and part-time family farm households in the subtropics of Jammu & Kashmir

Analysis of Income Distribution among Goat Farmer Households in Banjarnegara District, Central Java Province Indonesia

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