Impact of Weather Shock on Food Insecurity: A Study on India
341
To capture the impact of remittances on food insecurity a dummy variable (Remit)
is used which takes the value ‘1’ if a household receives remittances, ‘0’ otherwise. It
is expected that remittances into a household reduce its likelihood to be food insecure.
This is because receipt of remittances enhances liquidity and hence the household
can spend more on food.
Poverty is an important determinant of food insecurity. To capture the impact of
poverty on food insecurity a dummy variable (Pov) is used which takes the value ‘1’
if household is poor, ‘0’ otherwise. It is expected that the poor do not have enough
resources to purchase the required amount of food items for their household which
raises their probability of being food insecure.
Cultivation as the main occupation is another determinant of food insecurity. To
capture this variable a dummy variable (Cultivation) is used, which takes the value
‘1’ if a household’s main occupation is cultivation, ‘0’ otherwise. This implies that
the household whose main occupation is cultivation are less likely to be food insecure
than others. This is quite intuitive. The cultivator households in India are primarily
subsistence farmers, and hence allocate a considerable amount of farm produce on
household consumption.
The female adult household members in India take the responsibility of preparing and distributing food among other members. Hence, as their level of education
increases they become more aware about the importance of nutritious contents of
food. Thus, with improvements in their education expenditure by the households on
diverse food items containing calorie, proteins and fats also increases, thereby reducing food insecurity. Therefore, female adult education (FAE), defined as the highest
educational attainment in years among the female adult members of a household is
taken as an explanatory variable.
Residence of the households can also be an important determinant of food insecurity. To capture this variable, a dummy variable (Ur) is used which takes the value
of ‘1’ if a household belongs to urban area and ‘0’ otherwise. In the rural areas, most
of the people are associated with agriculture and the farmers are mostly subsistence
farmers. Hence, they are likely to be relatively more food secure than their urban
counterparts, given the other factors.
To capture the differential impact of different castes on household level
food insecurity, four dummy variables are used. The dummy variable OBC takes
the value of ‘1’ if a household belongs to other backward classes, ‘0’ otherwise.
Similarly, SC = 1 if a household belongs to scheduled caste category, ‘0’ otherwise.
ST = 1 if a household belongs to scheduled tribe category, ‘0’ otherwise. OC = 1 if
a household belongs to other castes, ‘0’ otherwise. Here General caste is taken as
reference category. Similarly, a dummy variable (Hindu) is also used to capture the
differential impact of religion on food insecurity, which takes the value ‘1’ if the
household belongs to Hindu religion, and ‘0’ otherwise.
The summary statistics of the explanatory variables are shown in Table 3. As
seen from Table 3, the rainfall for the year 2012, i.e., the year to which our study
is related, is around 24.10% deficient than the long run average rainfall. An average sample household consists of five members. The average income of the sample
households is INR 29,402. From the table, it is also seen that 76% of the household
341
To capture the impact of remittances on food insecurity a dummy variable (Remit)
is used which takes the value ‘1’ if a household receives remittances, ‘0’ otherwise. It
is expected that remittances into a household reduce its likelihood to be food insecure.
This is because receipt of remittances enhances liquidity and hence the household
can spend more on food.
Poverty is an important determinant of food insecurity. To capture the impact of
poverty on food insecurity a dummy variable (Pov) is used which takes the value ‘1’
if household is poor, ‘0’ otherwise. It is expected that the poor do not have enough
resources to purchase the required amount of food items for their household which
raises their probability of being food insecure.
Cultivation as the main occupation is another determinant of food insecurity. To
capture this variable a dummy variable (Cultivation) is used, which takes the value
‘1’ if a household’s main occupation is cultivation, ‘0’ otherwise. This implies that
the household whose main occupation is cultivation are less likely to be food insecure
than others. This is quite intuitive. The cultivator households in India are primarily
subsistence farmers, and hence allocate a considerable amount of farm produce on
household consumption.
The female adult household members in India take the responsibility of preparing and distributing food among other members. Hence, as their level of education
increases they become more aware about the importance of nutritious contents of
food. Thus, with improvements in their education expenditure by the households on
diverse food items containing calorie, proteins and fats also increases, thereby reducing food insecurity. Therefore, female adult education (FAE), defined as the highest
educational attainment in years among the female adult members of a household is
taken as an explanatory variable.
Residence of the households can also be an important determinant of food insecurity. To capture this variable, a dummy variable (Ur) is used which takes the value
of ‘1’ if a household belongs to urban area and ‘0’ otherwise. In the rural areas, most
of the people are associated with agriculture and the farmers are mostly subsistence
farmers. Hence, they are likely to be relatively more food secure than their urban
counterparts, given the other factors.
To capture the differential impact of different castes on household level
food insecurity, four dummy variables are used. The dummy variable OBC takes
the value of ‘1’ if a household belongs to other backward classes, ‘0’ otherwise.
Similarly, SC = 1 if a household belongs to scheduled caste category, ‘0’ otherwise.
ST = 1 if a household belongs to scheduled tribe category, ‘0’ otherwise. OC = 1 if
a household belongs to other castes, ‘0’ otherwise. Here General caste is taken as
reference category. Similarly, a dummy variable (Hindu) is also used to capture the
differential impact of religion on food insecurity, which takes the value ‘1’ if the
household belongs to Hindu religion, and ‘0’ otherwise.
The summary statistics of the explanatory variables are shown in Table 3. As
seen from Table 3, the rainfall for the year 2012, i.e., the year to which our study
is related, is around 24.10% deficient than the long run average rainfall. An average sample household consists of five members. The average income of the sample
households is INR 29,402. From the table, it is also seen that 76% of the household