Women’s participation in farm decision-making activities in Jammu and Kashmir: An analysis using participation decision index

Introduction

Agriculture continues to be a primary source of livelihood for a large proportion of the rural population in developing regions, where farm households depend heavily on family labour for agricultural operations. Within this context, women constitute a significant workforce and contribute substantially to crop production, livestock management, and allied agricultural activities. Despite their extensive involvement in agricultural operations, women's role in farmlevel decision-making has traditionally remained under-recognized and inadequately documented, particularly in patriarchal rural societies. Farm decision-making is a critical component of agricultural management, encompassing decisions related to crop selection, input use, irrigation, harvesting, storage, marketing, asset management, and financial transactions. Participation in such decisions not only reflects women's empowerment but also influences farm productivity, resource use efficiency, and household welfare. Increasing attention has therefore been directed towards understanding the extent to which women participate in agricultural decision-making and the factors that shape their involvement. In India, women's participation in agriculture is characterized by regional, socio-economic, and institutional variations. While several studies have highlighted women's active involvement in farm operations, evidence suggests that their participation in strategic and financial decisions-such as land transactions, credit utilization, and marketing-remains relatively limited. These disparities underscore the need for region-specific empirical studies that capture both the level and pattern of women's participation in farm decision-making. The Union Territory of Jammu and Kashmir presents a unique socio-economic and agro-ecological setting, where agriculture and allied activities form the backbone of rural livelihoods. The region exhibits diverse cropping systems, varying landholding patterns, and differential access to education, infrastructure, and institutional support. In such a setting, understanding women's participation in farm decision-making assumes particular significance, as it has implications for agricultural sustainability, gender equity, and rural development.

Although some studies have examined women's role in agriculture in the region, systematic assessments quantifying their participation across multiple farm decision-making activities and identifying key determinants remain limited. Moreover, there is a lack of comprehensive indices-based evaluations that capture overall participation levels in a measurable and comparable manner. Against this backdrop, the present study attempts to analyze women's participation in farm decision-making activities in Jammu and Kashmir using the Participation Decision Index (PDI). The study further examines district-wise variations in participation and identifies the socio-personal, socio-economic, and institutional factors influencing women's involvement in farm decision-making through regression analysis.

Objectives of the Study

The specific objectives of the study are: 1. To assess the extent of women's participation in different farm decision-making activities. 2. To measure the overall level of participation using the Participation Decision Index (PDI). 3. To examine district-wise variations in women's participation in farm decision-making. 4. To identify the determinants influencing women's participation in farm decision-making activities.

Materials and Methods

Study Area

The present study was conducted in the Union Territory of Jammu and Kashmir, which represents diverse agro-climatic, socio-economic, and institutional settings. Six districts-Jammu, Doda, Rajouri, Anantnag, Srinagar, and Baramulla-were selected to capture spatial variations across different geographical zones of the region. Agriculture and allied activities constitute a major source of livelihood in these districts, with women playing an important role in farm operations and household-based agricultural activities.

Sampling Design and Sample Size

A multistage sampling technique was adopted for the selection of respondents. In the first stage, six districts were purposively selected to ensure representation of different agro-climatic zones. In the subsequent stages, blocks, villages, and respondents were selected using appropriate sampling procedures. A total of 240 farm women actively engaged in agricultural activities were selected as respondents for the study.

Data Collection

Primary data were collected through a pre-tested structured interview schedule designed to elicit information on women's participation in farm decision-making activities and their sociopersonal, socio-economic, and institutional characteristics. The schedule included questions related to demographic attributes, educational status, landholding size, income, access to resources, and institutional support, along with participation in farm decision-making.

Measurement of Women's Participation in Farm Decision-Making

Women's participation in farm decision-making was assessed across fifteen major farm-related activities, including crop selection, land preparation, sowing practices, irrigation, use of inputs, harvesting, storage, marketing, livestock management, asset transactions, and farm credit.

Responses were recorded on a three-point continuum, namely:

Scores of 3, 2, and 1 were assigned to these responses, respectively. Weighted mean scores were computed for each decision-making activity to determine the extent of participation and to rank the activities accordingly.

Participation Decision Index (PDI)

The overall level of women's participation in farm decisionmaking was measured using the Participation Decision Index (PDI). The index was calculated by dividing the actual score obtained by a respondent by the maximum possible score and multiplying the result by 100.

Participation Decision Index (PDI) = (Actual score obtained / Maximum possible score) × 100

Based on equal-interval classification, respondents were categorized into three levels of participation:

• Low participation: PDI less than 50

• Medium participation: PDI ranging from 50 to 74.99

• High participation: PDI equal to or greater than 75

Regression Analysis

To identify the factors influencing women's participation in farm decision-making, multiple linear regression analysis was employed. The Participation Decision Index (PDI) was considered as the dependent variable, while selected sociopersonal, socio-economic, and institutional characteristics of the respondents were included as independent variables. The regression relationship was expressed in the following functional form:

where, β₀ = constant (intercept), β₁ to β₁₀ = regression coefficients, X₁ to X₁₀ = independent variables, and ε = random error term.

Statistical significance of the coefficients was tested at appropriate probability levels, and the overall model fit was assessed using R², adjusted R², and F-statistics.

Statistical Analysis

The collected data were coded, tabulated, and analyzed using appropriate statistical tools. Descriptive statistics such as frequencies, percentages, weighted mean scores, and indices were used to analyze participation patterns, while inferential statistics were applied to examine determinants of participation.

Results and Discussion

Women's Participation in Farm Decision-Making Activities

The extent of women's participation in various farm decisionmaking activities is presented in Table 1. The results reveal that women participated in all fifteen farm-related decision-making activities considered in the study, although the degree of participation varied across different decisions. Overall, the findings indicate that women's participation is relatively higher in livestock-related and operational decisions and comparatively lower in financial and capital-intensive decisions, a pattern commonly observed in agrarian settings.

Level of Women's Participation Based on Participation Decision Index (PDI)

The overall level of women's participation in farm decisionmaking was assessed using the Participation Decision Index (PDI). The computed PDI value of 88.47 indicates a high level of participation among the respondents. The distribution of respondents across different participation categories is presented in Table 2. The results show that none of the respondents fell under the low participation category. A small proportion of respondents (8.33 per cent) belonged to the medium participation category, whereas an overwhelming majority (91.67 per cent) were classified under the high participation category. The predominance of the high participation group suggests that women in the study area are actively and consistently involved in farm-level decision-making processes.

District-wise Variation in Participation Decision Index (PDI)

District-wise mean PDI values are presented in Table 3. The results reveal that women's participation in farm decisionmaking was consistently high across all selected districts, with mean PDI values ranging from 84.72 to 100.00. Among the districts, Srinagar recorded the highest mean PDI value (100.00), followed by Baramulla (87.99) and Anantnag (87.01). The districts of Jammu, Doda, and Rajouri also exhibited high mean PDI values, indicating strong participation across different geographical zones of Jammu and Kashmir. The relatively narrow range of mean PDI values suggests that women's participation in farm decision-making does not vary substantially across districts.

Determinants of Women's Participation in Farm Decision-Making

To identify the factors influencing women's participation in farm decision-making, a multiple linear regression analysis was conducted, with the Participation Decision Index (PDI) as the dependent variable. The model summary presented in Table 4 indicates that the regression model was statistically significant (F = 2.051; p = 0.030), confirming its suitability for explaining variations in participation. The regression coefficients presented in Table 5 reveal that education emerged as the only variable exerting a statistically significant positive influence on women's participation in farm decision-making. The positive and significant regression coefficient indicates that higher levels of education enhance women's participation by improving awareness, confidence, and decision-making capacity. Other variables, including age, family size, landholding size, women's income, access to credit, SHG membership, training contact, access to irrigation, and access to technology, did not exhibit statistically significant independent effects on the Participation Decision Index. This suggests that while these factors may influence participation indirectly, education remains the most critical determinant shaping women's involvement in farm decision-making activities.

Conclusion and Policy Implications

The present study examined women's participation in farm decision-making activities in Jammu and Kashmir using the Participation Decision Index (PDI). The findings clearly indicate that women are actively involved in a wide range of farm-level decisions, with participation observed across all fifteen decisionmaking activities considered in the study. The overall PDI value of 88.47 reflects a high level of participation, with the majority of respondents falling under the high participation category, indicating women's substantial role in agricultural decisionmaking.

The study further revealed that women's participation was relatively higher in livestock-related and operational decisions, such as purchase and sale of animals, sowing practices, irrigation, and harvesting, while comparatively lower participation was observed in financial and capital-intensive decisions, particularly those related to farm credit. District-wise analysis showed consistently high levels of participation across all selected districts, suggesting that women's involvement in farm decision-making is spatially uniform within the study area. Regression analysis identified education as the most significant determinant influencing women's participation in farm decisionmaking. The positive and statistically significant relationship between education and participation underscores the importance of educational attainment in enhancing women's decisionmaking capacity, confidence, and autonomy within the agricultural domain.

Policy Implications

Based on the findings of the study, the following policy implications are suggested:

• Strengthening educational opportunities for rural women, particularly through adult education and functional literacy programmes, can significantly enhance their participation in farm decision-making. • Agricultural extension and capacity-building programmes should adopt a gender-sensitive approach, ensuring active inclusion of women in training, advisory services, and institutional platforms. • Efforts should be made to improve women's access to financial services, including farm credit and formal banking systems, to enhance their role in financial decision-making. • Institutional support mechanisms, such as women-focused self-help groups and cooperative structures, should be

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