The dependent variable is the degree of income fluctuation due to climatic shocks (in the form of drought and flood). The ideal method as emerged from literature for measuring income fluctuations is to study the change in the average annual income of farmers over the years (Yang 2010). However, in the Indian context, the data on farmers’ income is not available on annual basis from secondary sources. Also, carrying out such primary surveys on annual basis is cumbersome, difficult and costs intensive. Taking this into account, the present study is designed to measure the income fluctuation of farmers with the subjective experience in enduring the income risk.
Information about to all the crops grown by sample farmers during three major seasons i.e. Kharif (rainy), Rabi (winter), and zaid (summer) was collected. The Cost incurred in various inputs, storage, marketing, and other agricultural operation were deducted from income realized by selling the product of these crops. The households’ head was asked about the yield losses incurred in years of serious climatic risks (drought or floods). Based on this information, the fluctuation in their income was then calculated for both the periods i.e. during a normal year and during the year they faced a climatic risk. Given the Indian agricultural scenario, a loss of up to 15 % of average annual income in normal year was considered as no significant loss (considering that farming is a risky enterprise) and is represented as ‘unchanged (0)’.
Explanatory variables included in this research are studied under two major categories; a. formal risk management mechanisms and b. informal risk management mechanisms along with households’ socio-economic characteristics. Formal risk management mechanisms include ex-ante risk mitigation mechanisms and ex-post risk coping variables. Ex-ante risk mitigations are government lead preparations ahead of arising damages from unforeseen risks. The level of development of commercial insurance markets and difficulty in accessing government relief has been studied under this category Insurance coverage during and related aspects of Kisan Credit Card (KCC) are considered under this category.
KCC is an innovative short-term credit distribution system primarily formed to meet the input related credit requirements of the farmers since 1998 (Singh and Sekhon 2005; Bista et al 2012; Sharma et al 2013). The scheme has undergone several progressions over the subsequent period. Lately, all the credit loans taken under KCC are brought the under ambit of insurance to protect the interest of the farmer against loss of crop yield caused by natural calamities, pest attacks, etc. The amount of compensation received by farmers under KCC along with its adequacy against the total losses, as perceived by the farmers; are considered in the study. We also included the difficulty experienced in accessing this compensation to determine the efficacy of formal risk mitigation options.
Given widespread illiteracy and the absence of collateral, Indian farmers are largely deprived of utilizing government reliefs efficiently. These shortcomings of our food providers also stir up trouble for agencies providing government reliefs (including insurance companies). Here the staff behavior of these agencies in terms of interacting and educating these farmers is instrumental in accessing and utilizing the risk management instruments available for them. Also, if the average time taken in the preparation of documents is less, access to compensation becomes relatively easy for farmers. Furthermore, in an efficient functioning scenario, the release of the final compensation amount should not take much time. Correspondingly, the farmers must not be forced to make frequent visits to insurance agencies in an easy regime. Hence, based on cumulative scoring of aforesaid factors, the ‘difficulty in obtaining compensation’ rating was obtained. Based on this scoring we categorized the difficult experience into three categories (Table 1).
Ex-post risk coping variables are help reduce the aftereffect of damages due to risk. This category includes the amount of loan taken from formal institutions to smooth up daily consumption need, the scale of loan (measured by the number of agencies contacted for taking the loan), and difficulty in obtaining this loan (measured with the help of cumulative scores of bank staff behavior, the average time is taken in document preparation, total time taken in the release of loan amount and number of visits to banks). The variables reflect the degree of development of the formal credit market along with extent of inter-temporal consumption smoothening.
The second category of informal risk coping mechanism is further categorized into ex-ante risk reduction and ex-post risk coping mechanisms. Ex-ante risk reduction responses are unconscious preparations for risk minimizations. Variables, such as, membership of organization (that are helpful in technology sensitization among farm communities) along with access and adoptions of conservative production strategy are studied under this category.
Ex-post risk coping mechanisms indicate the degree of development of informal credit market. It is measured by the amount and scale of the informal credit (measured by the number of agency contacted for it). Risk pooling social networking has been subsumed under this variable. This category also includes the level of difficulty in the access to private loans which is measured with the help of cumulative scores of agency behavior; the average time is taken in document preparation, total time taken in the release of credit amount and number of visits to the agency. The agency usually contacted for informal credit in the study area includes friends, relatives, private moneylenders, and market traders.
Besides two major categories, farmers’ demographic characteristics that include: social and economic variables are also included in the model. ‘Social category’ includes the age of household heads (average age of male and female heads of households), average years of schooling, and household size. On the other hand economic characteristics include average income level of the household, asset value of household (other than land), land size (in hectares), and number of cattle owned by the household. Further, an additional variable of location dummy was incorporated in the model to examine significant differences in the results of drought and flood-prone areas.
To eradicate the possibility of interactions among the explanatory variables, five different regression models are run. These models are developed under the constant control of family characteristics to understand the robustness of the results. First four models, namely model I, model II, model III, and model IV are worked by including variables of formal ex-ante risk mitigation, formal ex-post risk coping, informal ex-ante risk reduction and informal ex-post risk coping respectively along with family socio-economic characteristics. Model V was run by including all the explanatory variables (along with odd ratios).
Table 1
Explanation and assignment of variables
Variable category | variable explanation | Variable Assignment |
| explained variable | |
| dependent variable-income | 0-basically unchanged, 1-significantly lowered |
| explanatory variables | |
| formal mechanisms | |
ex-ante risk mitigation | amount of compensation | in Indian rupees (₹) |
| adequacy of compensation | 0-not adequate, 1-adequate |
| difficulty in obtaining compensation | 1-no access, 2 = moderately difficult, 3-easy |
ex-post risk coping | amount of formal credit | in Indian rupees (₹) |
| scale of formal credit | 1-none, 2-one or two, 3-two to four, 4-more than four |
| difficulty in obtaining formal credit | 1-no access, 2 = moderately difficult, 3-easy |
| informal mechanisms | |
ex-ante risk reduction | membership of any organization | 0-no, 1-yes |
| access and adoption of latest agricultural technology | 0-no, 1-yes |
ex-post risk coping | amount of informal credit | in Indian rupees (₹) |
| scale of informal credit | 1-none, 2-one or two, 3-two to four, 4-more than four |
| difficulty in obtaining informal credit | 1-no access 2 = moderately difficult, 3-easy |
| household characteristics | |
Social | age of the household head | in years |
| education | 0-illiterate, 1-literate |
| number of family members | In numbers |
economic | average income level | 1-below 1 lakh, 2 − 1 to 3 lakhs, 3- more than 3lakh |
| asset value of household other than land | in Indian rupees (₹) |
| land size | In hectare (ha) |
| number of cattle | In numbers |
| other control variable | |
| location dummy | 0-bikaner, 1-kota |