A multistage sampling technique applies for the selection of sample design. The Gujarat state is comprised of 33 districts; Ahmedabad, Anand, Botad, Dahod, Kheda, Panchmahal, Mahisagar, Chota Udaipur, and Vadodara districts cover under Central Gujarat region. In the first stage, out of these nine districts, giving an equal chance for each district, two districts, namely Dahod and Anand, were selected based on having the highest tribal people (43.83%) and non-tribal people (0.69%), respectively.

At the second stage, prepared a list of taluka-wise ST populations from each selected district, i.e., Dahod and Anand. Following with; three talukas from each selected district were selected considering tribal and non-tribal populations. Thus, for the selection of tribal areas, i.e., from Dahod district, three talukas, i.e., Jhalod, Dahod, and Fatepura, were selected based on the highest ST population, 26.98%, 23.51 %, and 14.08 %, respectively; whereas the non-tribal areas are selected from Anand district, three talukas, i.e., Anklav, Tarapur, and Sojitra, were having the lowest ST population, 1.18 %, 1.79, % and 2.57 %, respectively.

At the third stage, prepared a list of villages. Then, a total of three villages from each selected taluka were selected randomly. Nine villages were selected, from the tribal district (Dahod) and nine villages, from the non-tribal district (Anand). Thus, a total of eighteen villages were selected for the study.

To select the group size, arranged the respondents based on their landholdings in ascending order. They were classified into five size groups, i.e., landless agriculture labor, marginal farm households (up to 1.00 hectare), small farm households (> 1.00 to 2.00 hectares), medium farm households (> 2.00 to 4.00 hectares), and large farm households (above 4.00 hectares). Then a sample of twenty respondents’ was selected from each selected village, ensuring probability proportion to each stratum. Thus, of 180 respondents from the tribal district (Dahod) and 180 respondents from the non-tribal district (Anand) were selected. Thus, total of 360 respondents were finally chosen for the study.

The study used primary data. The data collected for the poverty situation from the selected respondents for the year 2018-19. Personal interviews using an interview schedule used considering the study’s nature and obtaining correct and perfect information. Based on experts’ suggestions, revised the interview schedule, and before finalizing the interview schedule, it was pre-tested with 10 percent of the total respondents.

The principal analytical tools employed for the study were the Foster-Greer-Thorbecke (FGT) index of poverty and tabular analysis.

Minimum consumption expenditure per person was used as a standard of measurement to examine poverty. Consumption is a better indicator of longterm household welfare as it consists of a minor temporal variation than income (MoFED, 2013). Also, in India, as elsewhere, consumption is likely to be measured more accurately than income. Minimum food consumption is associated with satisfying specific nutrition standards. Considering consumption to be an indicator of household welfare, it has adjusted for different household members due to their calorie requirement differences. It can deflate household consumption expenditure by an adult equivalent scale, which depends on each family member’s nutritional requirement.

In this study, based on individual household minimum consumption expenditure per person data, the first step was classifying a given household, whether he is poor or non-poor than the standard poverty line. The poverty line is a Per Capita Consumption expenditure per person or a cut of a standard living level below which an individual is considered flawed (Planning Commission of India, 2014 and MoFED, 2013). According to the Planning Commission of India (2014), monthly per capita consumption expenditure of ₹ 1102.83 in rural areas and ₹ 1507.06 in urban areas treated as the poverty line at the Gujarat state level. It implies a monthly consumption expenditure of ₹ 5514.15 in rural areas or ₹ 7535.3 in urban areas for a family of five at 2011-12 prices. Any household/individual failing to meet this consumption expenditure level can treat as a poor household. Hence, the abovementioned poverty line was employed as a cut-off value between poor and non-poor families for this study. People are counted as poor when their measured standard of living is below the poverty line, otherwise non-poor (Planning Commission of India, 2014).

Based on the above poverty line and data from households, this study has used three poverty dimension instruments that were identified by (Foster et al. 1984) to attain our objective to examine the extent of poverty in the State. These include the headcount index, poverty gap index and severity index, or Foster-Greer-Thorbecke (FGT) index of poverty. These three poverty dimension instruments also help us to see the poverty situations. By using these three poverty measures, we identified the percentage of the poor (headcount index), the aggregate poverty gap (poverty gap index), and the distribution of income among the poor (poverty severity index) in central Gujarat to achieve our second objective.

The model’s mathematical expression in Foster, Greer and Thorbecke (FGT, 1984) for poverty measurement was explained by considering, P_α as a poverty measurement class. By leveling real per-adult (per capita) household consumption expenditure per person, Y_i, as: (1)Y1≤Y2≤…Yq≤Z<Yq+1…≤Yn

Where

Z = Poverty line, n = Total population, q= Number of poor

Then, P_α is given by, (2)Pα=1N∑i=1q(Z−YiZ)α

Where:

P_α = Poverty measure, Z = Poverty line, N = Sample size; q = Number of persons/household below the poverty line; Y_i = Per capita consumption expenditure, α = is the weight attached to the severity of the poor, which takes the value 0, 1, 2 depending on the degree of concern about poverty, In the equation, Z – Y_i = 0 if Y_i > Z.

Headcount index: Share of the population whose monthly per capita consumption expenditure is below the poverty line, that is, the population’s share that cannot afford to buy a basic basket of goods. However, this index does not capture differences among the poor. (3)P0=1N∑i=1q(Z−YiZ)0

Poverty gap index: This index indicates the depth of poverty or provides information regarding how far households are from the poverty line. This measure captures the mean aggregate monthly per capita consumption expenditure shortfall relative to the poverty line across the whole population. In other words, it estimates the total resources needed to bring all the poor to the level of the poverty line (divided by the number of individuals in the population). (4)P1=1N∑i=1q(Z−YiZ)1

Poverty severity index(squared poverty gap): This takes into account not only the distance separating the poor from the poverty line (the poverty gap), but also the inequality among the poor; that is, a higher weight is placed on those households further away from the poverty line. (5)P2=1N∑i=1q(Z−YiZ)2

Through different poverty measuring approaches, poverty indices measure in the tribal and non-tribal areas of Central Gujarat and depicted in Table 1. The headcount index (the poverty incidence) was 0.139 and 0.056 for landless agricultural labor, 0.233 and 0.178 for marginal farm households, and 0.028 and 0.011 for small farm households in tribal and non-tribal areas. It shows the population proportion for which consumption expenditure is less than the poverty line, i.e., ₹ 1102.83 per month per person. It means 13.9 percent and 5.6 percent for landless agricultural labor, 23.3 percent and 17.8 percent for marginal farm households, 2.8 percent and 1.1 percent in small farm households were under the defined poverty line in the tribal and non-tribal area, respectively. It observed the highest poverty in marginal farm households followed by landless agricultural labors and small farm households in both selected regions. Thus, an overall tribal area (40.55%) had more poverty than non-tribal (24.44%).

Further, it observed no poverty among medium and large farm households of the non-tribal area and large farm households of the tribal areas. Only 1 percent medium farm household was poor in a tribal area. Thus, it may conclude that because of the large landholdings and greater access to other income-generating assets, poverty incidence did not observe among medium and large farmers in both study areas except 1.00 percent of a medium farmers in tribal areas.

Sailbala (2005) observed similar findings that poverty incidence was high among the marginal farmers, scheduled tribes, and lower-income categories. Radhakrishna and Panda (2006) also observed that poor households were generally landless laborers or farmers with marginal landholdings, and poverty prevails among the scheduled tribe and scheduled caste population. Pattanaik (2007) also concluded that poverty was high among low landholding farmers relative to higher landholding farmers.

The poverty gap index indicates the extent to which the poor’s per capita expenditure falls below the poverty line in the study area. The overall poverty gap index was 0.11 and 0.04 in the tribal and non-tribal regions, respectively. It concluded that, on average, 11 percent and 4 percent of poverty line cash transfers needed to lift each poor person out of poverty in the tribal and non-tribal areas, respectively. The poverty gap for different farm classes in both the areas was found maximum for landless agricultural labour, followed by marginal, small and medium farm households. The poverty depth varied from 32 percent and 11 percent for landless agriculture labor to 1 percent for medium farm households and 1 percent for small farm households in tribal and non-tribal areas. It indicates that poverty depth was more for landless households and marginal farm households of the tribal region. The squared poverty gap index shows the degree of inequality among the inadequate means higher income distribution inequality among the poor; higher is the squared poverty gap index. The squared poverty gap index was calculated by squaring the poverty gap index,, which weighted below poverty line observations, showing the poorest among the poor. The squared poverty gap index data shows poverty was less severe in the non-tribal area compared to tribal areas. The squared poverty gap index value was 0.04 and 0.01 in the tribal and non-tribal areas in Central Gujarat.