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Gender Bias in Farm Activities: Evidences from Household Level Data of a Developing Economy

Dharmabrata Mohapatra , Dukhabandhu Sahoo, Souryabrata Mohapatra
American Journal of Rural Development. 2019, 7(1), 30-43. DOI: 10.12691/ajrd-7-1-5
Received January 28, 2019; Revised March 04, 2019; Accepted March 09, 2019

Abstract

Despite the fact that women remained socially subordinate to men, they participated in resource control, decision-making, and production. Yet the status of farm women in general is much lower than that of male counterparts largely because of the customary male dominance in the society, inherent shyness of farm women, lack of opportunities and very poor accessibility to modern technologies. The present study is an endeavor to address this issue in a traditionally agrarian society, i.e. Odisha, India. The data are analyzed through descriptive statistics like mean, standard deviation, cross tabulation and Logit regression estimation techniques is adopted. For estimation of the aforesaid regression model the statistical packages like SPSS 20.0 and Stata 13.0 are used. Land is mostly owned by male person, which is basically due to hereditary reason (82.9 %). But cultural reason and to get the Government benefits are the minor factors. So far as reasons for land ownership at district level is concerned hereditary is the only reason to own the land. Factors like age, year of education and income from Primary Occupation do not improve the knowledge of parents regarding the property right of their girl children as these factors are not significant.

1. Introduction

Even though women's contribution was central in both the agricultural division of labor and its reproduction, traditional structures of resource allocation have provided them little or no access to the basic factors of production in agriculture with some exception. Despite the fact that they remained socially subordinate to men, they participated in resource control, decision-making, and production. Yet the status of farm women in general is much lower than that of male counterparts largely because of the customary male dominance in the society, inherent shyness of farm women, lack of opportunities and very poor accessibility to modern technologies. The present study is an endeavor to address this issue in a traditionally agrarian society, i.e. Odisha, India. The rest of the paper is organized as follows: the following section reviews the relevant literature to identify the research gap and set the objectives for the study. The third section gives an outline of the research design while the results are discussed in the fourth section. The last section concludes the study with some policy implications.

2. Review of Literature and the Research Gap

It was 2 who first ever showed the adverse conditions of women in agriculture. Reference 2 analyzed how work was divided between men and women, the types of jobs that constituted productive work, and the type of education women needed to enhance development. It argued that women's contributions, both domestic and in the paid workforce, contributed to national economies. But it was found that their contribution to the society was overlooked and ignored. The persistence decline in women labour force participation is a trending phenomenon a matter of serious concern. The recent data NSSO (2011) survey showed that in the period between 2005 - 2010 the female labour force participation declined from 33.3 % to 26.5 % in rural areas. The ILO 6 ranked India at the 120th place out of 130 countries so far as women labour force participation is concerned.

According to 1 found that women participation had a positive impact in decision making. In observing the impact of women labor force participation in economic growth several studies found that women’s economic activity and their development have shown a U-shaped relationship 3, 5, 7, 10. It indicates that initially female labour force participation will decline with growing economic development and remain stable for some time and rise again to give it a “U” shape. The reason behind it is due to structural shifts of women condition, imp-act of income effect and increase in education level of women in the society 5.

As household incomes increase women tend to leave the labour forces as they don’t need to contribute to the family earnings. Reference 4 studied from secondary data trend of women participation in agricultural activities in India and found that there is an increasing participation in the agricultural sector. Reference 8 revealed in his paper the actual role of women in agricultural and allied activities. He talked about their real problems, barriers and status in the agricultural sector. Women spend long hours in fetching water, preparing food, and all other activities including agricultural activities. It is also revealed that that total household income is positively related with farm size, number of female earning member and income of the women. It is found that income was affected when family size was large. From the analysis it was found that input availability, credit facility, education, motivation, training and support have the potential to increase gender participation in farm activities. The recent trends in women’s employment participation in NSS and Census data show a marginal increase while increase causalisation and informalisation of women’s work is the trend 11, 12. Reference 9 pointed out that accelerated shift toward the cash crops leads to commercialization of agriculture. It resulted in reduced employment opportunities for women.However, there is dearth of study with respect to the role of women in agriculture in Odisha. Toward this there lies a gap in the literature. The proposed study is an endeavour to bridge this gap.

3. Research Design

3.1. Coverage

Universe of the study – The study is carried out in ten Agro-climatic Zones of the state of Odisha.

Sampling methods –In the study, a multi-stage simple random sampling is used.

Sampling size – A maximum of 1020 respondents constitute the sample size.

Units of observation - The households who are involved in the farm and allied activities are the unit of observation.

3.2. Data Collection

The present study has used both secondary and primary data. Relevant secondary data are collected from various published sources of Government of India, Government of Odisha and other organizations. The study has used the various census data, data from the directorate of Agriculture, directorate of Economics and Statistics, Government of Odisha. Primary data are collected through a self-administered semi open questionnaire, which was specifically developed for this study. Before the data were collected a pilot survey was undertaken to validate the questionnaire. The analytical base of the study comprises of cross sectional survey based data from 1020 households.

3.3. Data Analysis

The data are analyzed through descriptive statistics like mean, standard deviation, cross tabulation and Logit regression estimation techniques is adopted. For estimation of the aforesaid regression model the statistical packages like SPSS 20.0 and Stata 13.0 are used.

4. Result and Discussion

4.1. Socio-Economic Profile of the Respondents

It is apparent from the Table 1 that out of the sample respondents of different districts of the study, 87.9 % respondents are male and 12.1 % respondents are female. So far as the sample respondents at district wise is concerned, there are only male respondents in the districts of Cuttack, Koraput, Bhadrak, Ganjam, Boudh, Puri and Bargarh. The share of respondents of these districts within the same gender of the total sample respondents are 6.6 %, 6.8 %, 6.9 %, 6.8 %, 5.9 %, 6.8 %, and 6.3 % respectively. On the other hand, the male respondents in the remaining districts are very substantial except Nayagarh district (female 98.3 %). In contrary to this, the respondents of the remaining sample districts are belonging to nuclear family. The Table 3 reflects that out of total sample respondents, the highest number of respondents (35.1 %) is in the age group of 41-50 followed by 24.2 % of respondents in the age group of 31-40 and 19.9 % of respondents in the age group of 41-50. It is apparent in the Table 4 that most of the respondents (51.9 %) in all the sample districts are equal or below 5 years of education and 40.9 % of them are in the range of 6-10 years of education. Furthermore, it is noticed that a few respondents whose years of education are 11-12 (+2) and 13-15 (+3).

The Table 5 reveals that most of the households (32 %) are having four number of family members followed by 23 % of households with five members, 14 of households with three members, 12.1 % of households with seven members and only 7.3 % of households with two members in the study area. It is also noticed the district level scenario from the table that the households having four family members are highly intensified in most of the sample districts like Cuttack (28.3 %), Koraput (31.7 %), Dhenkanal (41.7 %), Sundargarh (37.1 %), Keonjhar (30 %), Anugul (32.2 %), Bhadrak (44.3 %), Nayagarh (31.7 %), Ganjam (36.7 %), Boudh (53.8 %) and Khurda (39.3 %). Table 6 expresses that with regards to income generated from Primary Occupation (PO) annually, most of the respondents (62.3 %) in all the sample districts are less than or equal to Rs.10000 and only 29.8 % of them are in the range of Rs.10001-Rs.50000. From the Table 8 it is seen that the total annual income of almost half of the respondents (50.4 %) in all the sample districts are equal or less than Rs.10000 followed by 21.2 % and 15.8 % of respondents fall in the range of Rs.10001-25000 and Rs.25001-50000 respectively.

4.2. Role and Status of Women in Various Agricultural Activities

The decision on farming activities are mostly taken by male persons in farming HHs. In the study area, 68.3 % male, 9.0 % female only and 22.7 % both genders take decision on farm activities. With regards to genders' decision on farming activities, male people are largely involved in almost all the sample districts except Keonjhar, implying least engagement in decision making on farming activities. This is due to the fact that men have better knowledge about farm activities, more experiences on farming, and better network with stack holders. So far as joint decision on farming activities are concerned Keonjhar (66.1 %) district is reported as the top position followed by Jharsuguda (57.4 %), Ganjam (53.3 %) and Cuttack (50 %). A peculiar result is noticed in Dhenkanal district where the farming decision is not all taken jointly, rather individually by men (95 %) and women (5 %).

From the above Table 10, it is clearly noticed that experience plays a vital role in taking decision about the farming activities. The other factors attributed to farming decision are availability of information on agricultural activities (17.6 %), accessibility of information (2.9 %), time constraints due to households and other activities (5.8 %), experience (73.3 %) and others (0.4 %). Experience is the crucial factor to determine the farming decision in many sample districts like Cuttack (65.5 %), Kalahandi (60 %), Dhenkanal (98.3 %), Sundargarh (54.8 %), Jharsuguda (37.7 %), Keonjhar (94.4 %), Anugul (96.6 %), Malkangiri (95.2 %), Jajpur (46.7 %), Nayagarh (83.3 %), Ganjam (96.7 &), Boudh (78 %), Puri (85 %) and Bargarh (83.6 %). The same reason is solely attributed to the farming decision in Bhadrak district. In Koraput district, availability of information about agricultural activities is highly intensified whereas in Jharsuguda, time constraints due of household and other activities, especially for women, are highly powerful in determining the farming decision.

Table 7 highlights the facts that as far as earning of income from Secondary Occupation (SO) are concerned most of the sample respondents (78.7 %) whose annual income is equal or below Rs.10000 followed by 19.7 % of respondents in the range of Rs.10001-Rs.50000. With regards to the respondents at district level, the annual income of sample respondents are only equal or less than Rs.10000 in Kalahandi, Keonjhar, Malkangiri and Khurda districts. In most of the districts, the income of respondents falls in the same income slab. On the other hand, only in few districts like Cuttack, Bhadrak and Anugul where the highest number of respondents whose annual income from SO lies between Rs.10001 and Rs.50000. In the entire sample districts, the annual income of a major chunk of respondents lie in the low income slab whereas a marginal number of respondents are in the high income slab.

The Table 8 reflects that there exists a high degree of gender discrimination in taking decision about farming activities. The decision on farming activities are mostly taken by male persons in farming HHs. In the study area, 68.3 % male, 9.0 % female only and 22.7 % both genders take decision on farm activities. With regards to genders' decision on farming activities, male people are largely involved in almost all the sample districts except Keonjhar, implying least engagement in decision making on farming activities. This is due to the fact that men have better knowledge about farm activities, more experiences on farming, and better network with stack holders. So far as joint decision on farming activities are concerned Keonjhar (66.1 %) district is reported as the top position followed by Jharsuguda (57.4 %), Ganjam (53.3 %) and Cuttack (50 %). A peculiar result is noticed in Dhenkanal district where the farming decision is not all taken jointly, rather individually by men (95 %) and women (5 %). It is clearly noticed that experience plays a vital role in taking decision about the farming activities. The other factors attributed to farming decision are availability of information on agricultural activities (17.6 %), accessibility of information (2.9 %), time constraints due to households and other activities (5.8 %), experience (73.3 %) and others (0.4 %). Experience is the crucial factor to determine the farming decision in many sample districts like Cuttack (65.5 %), Kalahandi (60 %), Dhenkanal (98.3 %), Sundargarh (54.8 %), Jharsuguda (37.7 %), Keonjhar (94.4 %), Anugul (96.6 %), Malkangiri (95.2 %), Jajpur (46.7 %), Nayagarh (83.3 %), Ganjam (96.7 &), Boudh (78 %), Puri (85 %) and Bargarh (83.6 %). The same reason is solely attributed to the farming decision in Bhadrak district. In Koraput district, availability of information about agricultural activities is highly intensified whereas in Jharsuguda, time constraints due of household and other activities, especially for women, is highly powerful in determining the farming decision.

With regards to land ownership, it is clearly seen in the Table 10 that land is mostly owned by male person (89.1 %). Furthermore, it is reported by the respondents that a marginal percentage of women (4.8 %) own the land and likewise, both male and female jointly owned the land is also very diminutive (5.5 %). Looking at the district level figure, it is apparent that in almost all the sample districts the land ownership is entitled in the hand of male persons. But in Bargarh and Nayagarh districts the entire lands are owned by only male person and the women debarred from the right of ownership of land. In Jajpur district, 56.7 % of land is owned by male, 33.3 % by female and 10 % by both the gender. Similarly, a major portion of land is owned by male persons in Cuttack (84.5 %), Anugul (88.1 %) and Sundargarh (85.5 %) districts. A peculiar result is found in Jharsuguda district that 29.5 of land is owned by both men and women, which is highest percentage of ownership among all the sample district. In the remaining districts, above 90 % of land is owned by male persons.

The Table 11 shows that income from SO and agricultural output have a significant effect on knowledge about property right of girl children. But the factors like age, year of education and income from PO do not improve the knowledge of parents regarding the property right of their girl children as these factors are not significant.

5. Conclusion

The result shows that land is mostly owned by male person (89.1%). Furthermore, it is reported by the respondents that a marginal percentage of women (4.8 %) own the land and likewise, both male and female jointly owned the land is also very diminutive (5.5 %). Looking at the district level figure, it is apparent that in almost all the sample districts the land ownership is entitled in the hand of male persons. But in Bargarh and Nayagarh districts the entire lands are owned by only male person and the women debarred from the right of ownership of land. In Jajpur district, 56.7 % of land is owned by male, 33.3 % by female and 10 % by both the gender. Similarly, a major portion of land is owned by male persons in Cuttack (84.5 %), Anugul (88.1 %) and Sundargarh (85.5 %) districts. A peculiar result is found in Jharsuguda district that 29.5 of land is owned by both men and women, which is highest percentage of ownership among all the sample district. In the remaining districts, above 90 % of land is owned by male persons. Land is mostly owned by male person, which is basically due to hereditary reason (82.9 %). But cultural reason and to get the Government benefits are the minor factors. So far as reasons for land ownership at district level is concerned hereditary is the only reason to own the land in the districts of Kalahandi, Bhadrak, Ganjam and Puri. However, in Jajpur district the ownership of land is basically caused by cultural reason (73.3 %) and to get the Government benefits (21.7) but not by hereditary reason (5 %). In Anugul district, mostly the Government benefits (81.4 %) causethe people to own the land. Similarly, in Jharsuguda district, the of land is caused by hereditary (39.3 %), cultural reasons (32.8 %) and the Government benefits (27.9 %). In rest of the districts, hereditary factor is highly intensified to the land. The Table 11 shows that income from SO and agricultural output have a significant effect on knowledge about property right of girl children. But the factors like age, year of education and income from PO do not improve the knowledge of parents regarding the property right of their girl children as these factors are not significant.

Fund

This research work was facilitated with funding from ICSSR, New Delhi.

References

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[2]  Boserup, E. 1970. Women’s Role in Economic Development. New York, NY, St. Martin’s Press.
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[3]  Fatima, A., & Sultana, H. (2009). Tracing out the U-shape relationship between female labor force participation rate and economic development for Pakistan. International Journal of Social Economics, 36(1/2), 182-198.
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[4]  Ghosh, M., & Ghosh, A. (2014). Analysis of women participation in Indian agriculture. IOSR J. Human. Soc. Sci, 19(5), 1-6.
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[5]  Goldin, C. (1994). The U-shaped female labor force function in economic development and economic history (No. w4707). National Bureau of Economic Research.
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[6]  International Labour Office. (2013). Global Employment Trends 2013: Recovering from a second jobs dip. International Labour Office-ILO.
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[7]  Kottis, A. P. (1990). Shifts over time and regional variation in women's labor force participation rates in a developing economy: The case of Greece. Journal of Development Economics, 33(1), 117-132.
In article      View Article
 
[8]  Mondal, M. (2013). The role of rural women in agriculture sector of Sagar Island, West Bengal, India. Int. J. Eng. Sci, 2(2), 81-86.
In article      
 
[9]  Mridul Eapen (1994), 'Rural Non- Agricultural Employment in Kerala, some Emerging Tendencies', Economic and Political Weekly, Volume XXIX, Number 2 I, May 2 1.
In article      
 
[10]  Tansel, A. (2002). Economic development and female labor force participation in Turkey: Time-series evidence and cross-section estimates.
In article      
 
[11]  Unni J (1999) Women Workers in Agriculture: Some recent trends. In: Papola TS and Alakh N Sharma (Eds) Gender and Employment in India. Vikas Publishing House, New Delhi, 99-121.
In article      
 
[12]  Vaisaria P (1999) Level and Pattern of Female Employment. In: Papola T.S. and Alakh N. Sharma (Eds) Gender and Employment in India. Vikas Publishing House, New Delhi, 1911-1994.
In article      
 

Published with license by Science and Education Publishing, Copyright © 2019 Dharmabrata Mohapatra, Dukhabandhu Sahoo and Souryabrata Mohapatra

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Cite this article:

Normal Style
Dharmabrata Mohapatra, Dukhabandhu Sahoo, Souryabrata Mohapatra. Gender Bias in Farm Activities: Evidences from Household Level Data of a Developing Economy. American Journal of Rural Development. Vol. 7, No. 1, 2019, pp 30-43. http://pubs.sciepub.com/ajrd/7/1/5
MLA Style
Mohapatra, Dharmabrata, Dukhabandhu Sahoo, and Souryabrata Mohapatra. "Gender Bias in Farm Activities: Evidences from Household Level Data of a Developing Economy." American Journal of Rural Development 7.1 (2019): 30-43.
APA Style
Mohapatra, D. , Sahoo, D. , & Mohapatra, S. (2019). Gender Bias in Farm Activities: Evidences from Household Level Data of a Developing Economy. American Journal of Rural Development, 7(1), 30-43.
Chicago Style
Mohapatra, Dharmabrata, Dukhabandhu Sahoo, and Souryabrata Mohapatra. "Gender Bias in Farm Activities: Evidences from Household Level Data of a Developing Economy." American Journal of Rural Development 7, no. 1 (2019): 30-43.
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  • Table 11. Logistic Regression result (Dependent variable: Knowledge about Property right of Girl Children)
[1]  Bastidas, E. P. (1999). Gender issues and women's participation in irrigated agriculture: the Case of two private irrigation canals in Carchi, Ecuador (Vol. 31). IWMI.
In article      
 
[2]  Boserup, E. 1970. Women’s Role in Economic Development. New York, NY, St. Martin’s Press.
In article      PubMed
 
[3]  Fatima, A., & Sultana, H. (2009). Tracing out the U-shape relationship between female labor force participation rate and economic development for Pakistan. International Journal of Social Economics, 36(1/2), 182-198.
In article      View Article
 
[4]  Ghosh, M., & Ghosh, A. (2014). Analysis of women participation in Indian agriculture. IOSR J. Human. Soc. Sci, 19(5), 1-6.
In article      View Article
 
[5]  Goldin, C. (1994). The U-shaped female labor force function in economic development and economic history (No. w4707). National Bureau of Economic Research.
In article      View Article
 
[6]  International Labour Office. (2013). Global Employment Trends 2013: Recovering from a second jobs dip. International Labour Office-ILO.
In article      
 
[7]  Kottis, A. P. (1990). Shifts over time and regional variation in women's labor force participation rates in a developing economy: The case of Greece. Journal of Development Economics, 33(1), 117-132.
In article      View Article
 
[8]  Mondal, M. (2013). The role of rural women in agriculture sector of Sagar Island, West Bengal, India. Int. J. Eng. Sci, 2(2), 81-86.
In article      
 
[9]  Mridul Eapen (1994), 'Rural Non- Agricultural Employment in Kerala, some Emerging Tendencies', Economic and Political Weekly, Volume XXIX, Number 2 I, May 2 1.
In article      
 
[10]  Tansel, A. (2002). Economic development and female labor force participation in Turkey: Time-series evidence and cross-section estimates.
In article      
 
[11]  Unni J (1999) Women Workers in Agriculture: Some recent trends. In: Papola TS and Alakh N Sharma (Eds) Gender and Employment in India. Vikas Publishing House, New Delhi, 99-121.
In article      
 
[12]  Vaisaria P (1999) Level and Pattern of Female Employment. In: Papola T.S. and Alakh N. Sharma (Eds) Gender and Employment in India. Vikas Publishing House, New Delhi, 1911-1994.
In article