Farm size, livelihood diversification and farmer’s income in India

Abstract The basic objective of this study is to analyse the role of farm size and diversification in determining farmer’s total income from both farm and non-farm sources. Using data from NSS 70th Round Situation Assessment Survey, we estimate a log-linear regression model that relates farmer’s inc...
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Autor*in:	Das, Varun Kumar [verfasserIn] Ganesh-Kumar, A.

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2018

Schlagwörter:	Farm size Farm income Farmer’s income On-farm/off-farm diversification

Anmerkung:	© Indian Institute of Management Calcutta 2018

Übergeordnetes Werk:	Enthalten in: Decision - [S.l.] : Springer India, 2004, 45(2018), 2 vom: 28. Feb., Seite 185-201
Übergeordnetes Werk:	volume:45 ; year:2018 ; number:2 ; day:28 ; month:02 ; pages:185-201

Links:	Volltext

DOI / URN:	10.1007/s40622-018-0177-9

Katalog-ID:	SPR036892998

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allfields	10.1007/s40622-018-0177-9 doi (DE-627)SPR036892998 (SPR)s40622-018-0177-9-e DE-627 ger DE-627 rakwb eng Das, Varun Kumar verfasserin aut Farm size, livelihood diversification and farmer’s income in India 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Indian Institute of Management Calcutta 2018 Abstract The basic objective of this study is to analyse the role of farm size and diversification in determining farmer’s total income from both farm and non-farm sources. Using data from NSS 70th Round Situation Assessment Survey, we estimate a log-linear regression model that relates farmer’s income to farm size, on-farm and off-farm diversification, and various other control factors representing farm, household and locational characteristics. We estimate this model for total income over the whole year and separately for the two seasons, kharif and rabi. We find that farm size has a negative relationship with farmer’s income per capita after controlling for various factors. Our results also lend support to our hypothesis that there is an optimal level of diversification that maximizes farmer’s income. We find that the optimal number of crops to be engaged in is 2 in both seasons, 2 animal husbandry activities in both seasons, 4 non-farm activities in kharif and 3 non-farm activities in rabi season. Comparing these estimates with the actual levels as per the NSS data shows that farmers on an average are already engaged in the optimal number of crops, but they are at sub-optimal level in terms of animal husbandry and non-farm activities. We also find that there is a minimum threshold level of education, viz., “Literate with Formal Schooling”, required to improve income levels. NSS data show that on an average, marginal and small farmers who constitute nearly 85 per cent of agricultural households have an education level below this threshold. Thus, improving their education levels is another point for policy intervention that can help raise their income levels. Another interesting finding from our analysis is that participating in MGNREGS may have an adverse impact on income levels, possibly via the opportunity cost of time spent in such public works. Farm size (dpeaa)DE-He213 Farm income (dpeaa)DE-He213 Farmer’s income (dpeaa)DE-He213 On-farm/off-farm diversification (dpeaa)DE-He213 Ganesh-Kumar, A. aut Enthalten in Decision [S.l.] : Springer India, 2004 45(2018), 2 vom: 28. Feb., Seite 185-201 (DE-627)491442440 (DE-600)2194154-3 2197-1722 nnns volume:45 year:2018 number:2 day:28 month:02 pages:185-201 https://dx.doi.org/10.1007/s40622-018-0177-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_266 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 45 2018 2 28 02 185-201
spelling	10.1007/s40622-018-0177-9 doi (DE-627)SPR036892998 (SPR)s40622-018-0177-9-e DE-627 ger DE-627 rakwb eng Das, Varun Kumar verfasserin aut Farm size, livelihood diversification and farmer’s income in India 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Indian Institute of Management Calcutta 2018 Abstract The basic objective of this study is to analyse the role of farm size and diversification in determining farmer’s total income from both farm and non-farm sources. Using data from NSS 70th Round Situation Assessment Survey, we estimate a log-linear regression model that relates farmer’s income to farm size, on-farm and off-farm diversification, and various other control factors representing farm, household and locational characteristics. We estimate this model for total income over the whole year and separately for the two seasons, kharif and rabi. We find that farm size has a negative relationship with farmer’s income per capita after controlling for various factors. Our results also lend support to our hypothesis that there is an optimal level of diversification that maximizes farmer’s income. We find that the optimal number of crops to be engaged in is 2 in both seasons, 2 animal husbandry activities in both seasons, 4 non-farm activities in kharif and 3 non-farm activities in rabi season. Comparing these estimates with the actual levels as per the NSS data shows that farmers on an average are already engaged in the optimal number of crops, but they are at sub-optimal level in terms of animal husbandry and non-farm activities. We also find that there is a minimum threshold level of education, viz., “Literate with Formal Schooling”, required to improve income levels. NSS data show that on an average, marginal and small farmers who constitute nearly 85 per cent of agricultural households have an education level below this threshold. Thus, improving their education levels is another point for policy intervention that can help raise their income levels. Another interesting finding from our analysis is that participating in MGNREGS may have an adverse impact on income levels, possibly via the opportunity cost of time spent in such public works. Farm size (dpeaa)DE-He213 Farm income (dpeaa)DE-He213 Farmer’s income (dpeaa)DE-He213 On-farm/off-farm diversification (dpeaa)DE-He213 Ganesh-Kumar, A. aut Enthalten in Decision [S.l.] : Springer India, 2004 45(2018), 2 vom: 28. Feb., Seite 185-201 (DE-627)491442440 (DE-600)2194154-3 2197-1722 nnns volume:45 year:2018 number:2 day:28 month:02 pages:185-201 https://dx.doi.org/10.1007/s40622-018-0177-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_266 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 45 2018 2 28 02 185-201
allfields_unstemmed	10.1007/s40622-018-0177-9 doi (DE-627)SPR036892998 (SPR)s40622-018-0177-9-e DE-627 ger DE-627 rakwb eng Das, Varun Kumar verfasserin aut Farm size, livelihood diversification and farmer’s income in India 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Indian Institute of Management Calcutta 2018 Abstract The basic objective of this study is to analyse the role of farm size and diversification in determining farmer’s total income from both farm and non-farm sources. Using data from NSS 70th Round Situation Assessment Survey, we estimate a log-linear regression model that relates farmer’s income to farm size, on-farm and off-farm diversification, and various other control factors representing farm, household and locational characteristics. We estimate this model for total income over the whole year and separately for the two seasons, kharif and rabi. We find that farm size has a negative relationship with farmer’s income per capita after controlling for various factors. Our results also lend support to our hypothesis that there is an optimal level of diversification that maximizes farmer’s income. We find that the optimal number of crops to be engaged in is 2 in both seasons, 2 animal husbandry activities in both seasons, 4 non-farm activities in kharif and 3 non-farm activities in rabi season. Comparing these estimates with the actual levels as per the NSS data shows that farmers on an average are already engaged in the optimal number of crops, but they are at sub-optimal level in terms of animal husbandry and non-farm activities. We also find that there is a minimum threshold level of education, viz., “Literate with Formal Schooling”, required to improve income levels. NSS data show that on an average, marginal and small farmers who constitute nearly 85 per cent of agricultural households have an education level below this threshold. Thus, improving their education levels is another point for policy intervention that can help raise their income levels. Another interesting finding from our analysis is that participating in MGNREGS may have an adverse impact on income levels, possibly via the opportunity cost of time spent in such public works. Farm size (dpeaa)DE-He213 Farm income (dpeaa)DE-He213 Farmer’s income (dpeaa)DE-He213 On-farm/off-farm diversification (dpeaa)DE-He213 Ganesh-Kumar, A. aut Enthalten in Decision [S.l.] : Springer India, 2004 45(2018), 2 vom: 28. Feb., Seite 185-201 (DE-627)491442440 (DE-600)2194154-3 2197-1722 nnns volume:45 year:2018 number:2 day:28 month:02 pages:185-201 https://dx.doi.org/10.1007/s40622-018-0177-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_266 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 45 2018 2 28 02 185-201
allfieldsGer	10.1007/s40622-018-0177-9 doi (DE-627)SPR036892998 (SPR)s40622-018-0177-9-e DE-627 ger DE-627 rakwb eng Das, Varun Kumar verfasserin aut Farm size, livelihood diversification and farmer’s income in India 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Indian Institute of Management Calcutta 2018 Abstract The basic objective of this study is to analyse the role of farm size and diversification in determining farmer’s total income from both farm and non-farm sources. Using data from NSS 70th Round Situation Assessment Survey, we estimate a log-linear regression model that relates farmer’s income to farm size, on-farm and off-farm diversification, and various other control factors representing farm, household and locational characteristics. We estimate this model for total income over the whole year and separately for the two seasons, kharif and rabi. We find that farm size has a negative relationship with farmer’s income per capita after controlling for various factors. Our results also lend support to our hypothesis that there is an optimal level of diversification that maximizes farmer’s income. We find that the optimal number of crops to be engaged in is 2 in both seasons, 2 animal husbandry activities in both seasons, 4 non-farm activities in kharif and 3 non-farm activities in rabi season. Comparing these estimates with the actual levels as per the NSS data shows that farmers on an average are already engaged in the optimal number of crops, but they are at sub-optimal level in terms of animal husbandry and non-farm activities. We also find that there is a minimum threshold level of education, viz., “Literate with Formal Schooling”, required to improve income levels. NSS data show that on an average, marginal and small farmers who constitute nearly 85 per cent of agricultural households have an education level below this threshold. Thus, improving their education levels is another point for policy intervention that can help raise their income levels. Another interesting finding from our analysis is that participating in MGNREGS may have an adverse impact on income levels, possibly via the opportunity cost of time spent in such public works. Farm size (dpeaa)DE-He213 Farm income (dpeaa)DE-He213 Farmer’s income (dpeaa)DE-He213 On-farm/off-farm diversification (dpeaa)DE-He213 Ganesh-Kumar, A. aut Enthalten in Decision [S.l.] : Springer India, 2004 45(2018), 2 vom: 28. Feb., Seite 185-201 (DE-627)491442440 (DE-600)2194154-3 2197-1722 nnns volume:45 year:2018 number:2 day:28 month:02 pages:185-201 https://dx.doi.org/10.1007/s40622-018-0177-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_266 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 45 2018 2 28 02 185-201
allfieldsSound	10.1007/s40622-018-0177-9 doi (DE-627)SPR036892998 (SPR)s40622-018-0177-9-e DE-627 ger DE-627 rakwb eng Das, Varun Kumar verfasserin aut Farm size, livelihood diversification and farmer’s income in India 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Indian Institute of Management Calcutta 2018 Abstract The basic objective of this study is to analyse the role of farm size and diversification in determining farmer’s total income from both farm and non-farm sources. Using data from NSS 70th Round Situation Assessment Survey, we estimate a log-linear regression model that relates farmer’s income to farm size, on-farm and off-farm diversification, and various other control factors representing farm, household and locational characteristics. We estimate this model for total income over the whole year and separately for the two seasons, kharif and rabi. We find that farm size has a negative relationship with farmer’s income per capita after controlling for various factors. Our results also lend support to our hypothesis that there is an optimal level of diversification that maximizes farmer’s income. We find that the optimal number of crops to be engaged in is 2 in both seasons, 2 animal husbandry activities in both seasons, 4 non-farm activities in kharif and 3 non-farm activities in rabi season. Comparing these estimates with the actual levels as per the NSS data shows that farmers on an average are already engaged in the optimal number of crops, but they are at sub-optimal level in terms of animal husbandry and non-farm activities. We also find that there is a minimum threshold level of education, viz., “Literate with Formal Schooling”, required to improve income levels. NSS data show that on an average, marginal and small farmers who constitute nearly 85 per cent of agricultural households have an education level below this threshold. Thus, improving their education levels is another point for policy intervention that can help raise their income levels. Another interesting finding from our analysis is that participating in MGNREGS may have an adverse impact on income levels, possibly via the opportunity cost of time spent in such public works. Farm size (dpeaa)DE-He213 Farm income (dpeaa)DE-He213 Farmer’s income (dpeaa)DE-He213 On-farm/off-farm diversification (dpeaa)DE-He213 Ganesh-Kumar, A. aut Enthalten in Decision [S.l.] : Springer India, 2004 45(2018), 2 vom: 28. Feb., Seite 185-201 (DE-627)491442440 (DE-600)2194154-3 2197-1722 nnns volume:45 year:2018 number:2 day:28 month:02 pages:185-201 https://dx.doi.org/10.1007/s40622-018-0177-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_266 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 45 2018 2 28 02 185-201
language	English
source	Enthalten in Decision 45(2018), 2 vom: 28. Feb., Seite 185-201 volume:45 year:2018 number:2 day:28 month:02 pages:185-201
sourceStr	Enthalten in Decision 45(2018), 2 vom: 28. Feb., Seite 185-201 volume:45 year:2018 number:2 day:28 month:02 pages:185-201
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Farm size Farm income Farmer’s income On-farm/off-farm diversification
isfreeaccess_bool	false
container_title	Decision
authorswithroles_txt_mv	Das, Varun Kumar @@aut@@ Ganesh-Kumar, A. @@aut@@
publishDateDaySort_date	2018-02-28T00:00:00Z
hierarchy_top_id	491442440
id	SPR036892998
language_de	englisch
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author	Das, Varun Kumar
spellingShingle	Das, Varun Kumar misc Farm size misc Farm income misc Farmer’s income misc On-farm/off-farm diversification Farm size, livelihood diversification and farmer’s income in India
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topic_title	Farm size, livelihood diversification and farmer’s income in India Farm size (dpeaa)DE-He213 Farm income (dpeaa)DE-He213 Farmer’s income (dpeaa)DE-He213 On-farm/off-farm diversification (dpeaa)DE-He213
topic	misc Farm size misc Farm income misc Farmer’s income misc On-farm/off-farm diversification
topic_unstemmed	misc Farm size misc Farm income misc Farmer’s income misc On-farm/off-farm diversification
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title	Farm size, livelihood diversification and farmer’s income in India
ctrlnum	(DE-627)SPR036892998 (SPR)s40622-018-0177-9-e
title_full	Farm size, livelihood diversification and farmer’s income in India
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author_browse	Das, Varun Kumar Ganesh-Kumar, A.
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author-letter	Das, Varun Kumar
doi_str_mv	10.1007/s40622-018-0177-9
title_sort	farm size, livelihood diversification and farmer’s income in india
title_auth	Farm size, livelihood diversification and farmer’s income in India
abstract	Abstract The basic objective of this study is to analyse the role of farm size and diversification in determining farmer’s total income from both farm and non-farm sources. Using data from NSS 70th Round Situation Assessment Survey, we estimate a log-linear regression model that relates farmer’s income to farm size, on-farm and off-farm diversification, and various other control factors representing farm, household and locational characteristics. We estimate this model for total income over the whole year and separately for the two seasons, kharif and rabi. We find that farm size has a negative relationship with farmer’s income per capita after controlling for various factors. Our results also lend support to our hypothesis that there is an optimal level of diversification that maximizes farmer’s income. We find that the optimal number of crops to be engaged in is 2 in both seasons, 2 animal husbandry activities in both seasons, 4 non-farm activities in kharif and 3 non-farm activities in rabi season. Comparing these estimates with the actual levels as per the NSS data shows that farmers on an average are already engaged in the optimal number of crops, but they are at sub-optimal level in terms of animal husbandry and non-farm activities. We also find that there is a minimum threshold level of education, viz., “Literate with Formal Schooling”, required to improve income levels. NSS data show that on an average, marginal and small farmers who constitute nearly 85 per cent of agricultural households have an education level below this threshold. Thus, improving their education levels is another point for policy intervention that can help raise their income levels. Another interesting finding from our analysis is that participating in MGNREGS may have an adverse impact on income levels, possibly via the opportunity cost of time spent in such public works. © Indian Institute of Management Calcutta 2018
abstractGer	Abstract The basic objective of this study is to analyse the role of farm size and diversification in determining farmer’s total income from both farm and non-farm sources. Using data from NSS 70th Round Situation Assessment Survey, we estimate a log-linear regression model that relates farmer’s income to farm size, on-farm and off-farm diversification, and various other control factors representing farm, household and locational characteristics. We estimate this model for total income over the whole year and separately for the two seasons, kharif and rabi. We find that farm size has a negative relationship with farmer’s income per capita after controlling for various factors. Our results also lend support to our hypothesis that there is an optimal level of diversification that maximizes farmer’s income. We find that the optimal number of crops to be engaged in is 2 in both seasons, 2 animal husbandry activities in both seasons, 4 non-farm activities in kharif and 3 non-farm activities in rabi season. Comparing these estimates with the actual levels as per the NSS data shows that farmers on an average are already engaged in the optimal number of crops, but they are at sub-optimal level in terms of animal husbandry and non-farm activities. We also find that there is a minimum threshold level of education, viz., “Literate with Formal Schooling”, required to improve income levels. NSS data show that on an average, marginal and small farmers who constitute nearly 85 per cent of agricultural households have an education level below this threshold. Thus, improving their education levels is another point for policy intervention that can help raise their income levels. Another interesting finding from our analysis is that participating in MGNREGS may have an adverse impact on income levels, possibly via the opportunity cost of time spent in such public works. © Indian Institute of Management Calcutta 2018
abstract_unstemmed	Abstract The basic objective of this study is to analyse the role of farm size and diversification in determining farmer’s total income from both farm and non-farm sources. Using data from NSS 70th Round Situation Assessment Survey, we estimate a log-linear regression model that relates farmer’s income to farm size, on-farm and off-farm diversification, and various other control factors representing farm, household and locational characteristics. We estimate this model for total income over the whole year and separately for the two seasons, kharif and rabi. We find that farm size has a negative relationship with farmer’s income per capita after controlling for various factors. Our results also lend support to our hypothesis that there is an optimal level of diversification that maximizes farmer’s income. We find that the optimal number of crops to be engaged in is 2 in both seasons, 2 animal husbandry activities in both seasons, 4 non-farm activities in kharif and 3 non-farm activities in rabi season. Comparing these estimates with the actual levels as per the NSS data shows that farmers on an average are already engaged in the optimal number of crops, but they are at sub-optimal level in terms of animal husbandry and non-farm activities. We also find that there is a minimum threshold level of education, viz., “Literate with Formal Schooling”, required to improve income levels. NSS data show that on an average, marginal and small farmers who constitute nearly 85 per cent of agricultural households have an education level below this threshold. Thus, improving their education levels is another point for policy intervention that can help raise their income levels. Another interesting finding from our analysis is that participating in MGNREGS may have an adverse impact on income levels, possibly via the opportunity cost of time spent in such public works. © Indian Institute of Management Calcutta 2018
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title_short	Farm size, livelihood diversification and farmer’s income in India
url	https://dx.doi.org/10.1007/s40622-018-0177-9
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up_date	2024-07-03T20:13:27.915Z
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fullrecord_marcxml	<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">SPR036892998</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230328192456.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">201007s2018 xx \|\|\|\|\|o 00\| \|\|eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s40622-018-0177-9</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR036892998</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s40622-018-0177-9-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Das, Varun Kumar</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Farm size, livelihood diversification and farmer’s income in India</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2018</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© Indian Institute of Management Calcutta 2018</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract The basic objective of this study is to analyse the role of farm size and diversification in determining farmer’s total income from both farm and non-farm sources. Using data from NSS 70th Round Situation Assessment Survey, we estimate a log-linear regression model that relates farmer’s income to farm size, on-farm and off-farm diversification, and various other control factors representing farm, household and locational characteristics. We estimate this model for total income over the whole year and separately for the two seasons, kharif and rabi. We find that farm size has a negative relationship with farmer’s income per capita after controlling for various factors. Our results also lend support to our hypothesis that there is an optimal level of diversification that maximizes farmer’s income. We find that the optimal number of crops to be engaged in is 2 in both seasons, 2 animal husbandry activities in both seasons, 4 non-farm activities in kharif and 3 non-farm activities in rabi season. Comparing these estimates with the actual levels as per the NSS data shows that farmers on an average are already engaged in the optimal number of crops, but they are at sub-optimal level in terms of animal husbandry and non-farm activities. We also find that there is a minimum threshold level of education, viz., “Literate with Formal Schooling”, required to improve income levels. NSS data show that on an average, marginal and small farmers who constitute nearly 85 per cent of agricultural households have an education level below this threshold. Thus, improving their education levels is another point for policy intervention that can help raise their income levels. Another interesting finding from our analysis is that participating in MGNREGS may have an adverse impact on income levels, possibly via the opportunity cost of time spent in such public works.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Farm size</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Farm income</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Farmer’s income</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">On-farm/off-farm diversification</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Ganesh-Kumar, A.</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Decision</subfield><subfield code="d">[S.l.] : Springer India, 2004</subfield><subfield code="g">45(2018), 2 vom: 28. 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Farm size, livelihood diversification and farmer’s income in India

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