Socio-economic Conditions & Determinants of Income: A Tell of Informal Workers of Urban Odisha, India

Introduction

Informal sector employment¹ and its impact on economic growth have received greater attention not only in India but also in all underdeveloped and developing countries in the world (Banerjee, 1983; Breman, 1996; Datta, 2016; Himanshu, 2019; Jha and Lahoti, 2021; Barik, 2024). In India, it is about 91 percent of the total labor force (475 million) in the informal sector, more than 90 percent in the unorganized sector, and about 91 percent additional laborers were engaged in the unorganized informal sector only (Economic Survey Report 2021-22; Mehrotra, 2022). It is in excess of 92 percent, both in the informal and formal sectors, working as self-employed or casual laborers, and approximately 50 percent of the national income appears in this informal sector. Similarly, the NSSO 73^rd round report (2015-2016) analyzed that major states such as Uttar Pradesh, West Bengal, Tamil Nadu, Maharashtra, and Karnataka occupy all most 50 percent of the workers. The state such as Himachal Pradesh was the lowest contributor (0.58%) to the total workforce, and Uttar Pradesh had the highest (15%) in India. However, the state of Odisha has been occupied with the 13^th position (3% of workers) in engaging in the unincorporated non-agricultural sector in India, except for the construction sector. It accounts for 4.74 percent of workers from the rural areas and 1.57 percent in urban areas, and 98.74 percent and 98.31 percent, respectively, of the total workforce in India. The condition of informal workers in Odisha is diverse in nature, because of the struggle for the survival of the mass poor, lack of suitable job, non-subsistence level of wage rate, and non-sustainability of the work or due to the ‘vicious circle of poverty’.

Therefore, in informal sector employment, the income level and determinants of income are of paramount importance. As a result, this study conducted an empirical investigation to understand the different difficulties related to informal sector workers (ISWs) in Odisha, specifically Cuttack. The CTC (Cuttack City) was selected as the sample area, as it is the 1^st capital city and also concentrate the 2^nd highest informal sectors employment (after Bhubaneswar) in Odisha. However, the main purpose of this research is to discover the main determinants of the income of vulnerable ISWs working in the CTC of Odisha. The rest of the study is organized as follows: review of the literatures (section-2), methodology and data (section-3), empirical analysis and discussions (section-4), and finally, conclusions and policy recommendations (section-5).

Review of literature

In this paper, the literature review is followed by international-level studies (studies made other than India), national-level studies (study at the national level excluding Odisha), and regional-level studies (specifically in Odisha) to understand the causes and consequences of income variation among workers.

The literature review begins with the ‘Blinder-Oaxaca Decomposition Theorem, 1973. According to the author, the main causes of wage discrimination among white, black, male, and female workers in the USA are differences in age-wage profiles, unequal income distribution, union membership, occupational status, educational discrimination, and job experience. On the other hand, the author noted that the major causes of male-female wage discrimination in the USA include variations in tradition, culture, and overt discrimination within the same occupation (Meher and Dash, 2014). In this study, the existence of racial income differences (minorities and employment discrimination), which play a crucial role in the income gap between black and white workers, as not considered. Lower income of the black workers is due to very less investment on the human capital, ‘taste for discrimination’ for the black workers and the acquisition of market valued characteristics than the white workers. Similarly, in France, the pay gap among workers is due to gender bias, demand for skilled workers, and non-monetary gains such as job protection in the civil sector (Odisha Economic Survey, 2020-21 and Tandon, 2022). In Europe, disparities in working conditions, occupational exposure, gender, health conditions, immigration status, and employment arrangements are major contributors to the pay disparity between workers (both non-migrants and migrants). According to the IMF (2015) and ILO(2015 and 2021) income inequality sharply worldwide due to the inequality of opportunity for obtaining education, occupational choices reducing skills, weaker social mobility, and workplace inequalities. Income inequality is increasing in emerging economies of G-20 (i.e., Indonesia and China) and decreasing in developing countries (i.e., Brazil and Argentina) due to social and political cohesion, less sustained economic growth, and lower consumption, according to the ILO, IMF, OECD and WBG (2015). Similarly, according to the ILO report (2021), income inequality increases sharply under COVID-19 due to a decrease in relative levels of income, quality of employment opportunities, and inter-sectional division among workforce groups (i.e., on the basis of race and ethnicity, education, age, migration status, formal and informal workers, etc.). On the one hand, Blinder (1973) found that the differences in the age-wage-profile, unequal income distribution, membership in the union, occupational status, educational discrimination and job experience are the main reasons for wage discrimination among white-black and male-female workers in the USA. On the other hand, Oaxaca (1973) observed that differences in tradition, culture, and overt discrimination within the same occupation are important reasons for the male-female wage discrimination in the USA. According to Loury (1977), racial income differences (minorities and employment discrimination) which play a vital role in the income difference between black and the white workers have not been taken into consideration. Lower income of the black workers is due to very less investment on the human capital, ‘taste for discrimination’ for the black workers and the acquisition of market valued characteristics than the white workers. Similarly, in France, the pay gap among workers is due to gender bias, demand for skilled workers, and non-monetary gains such as job protection in the civil sector. However, in Europe, the important reason for the income variation between workers (both non-migrant and migrant) is the difference in working conditions, occupational exposure, gender, health condition, migration status, and employment arrangements (Perez et al., 2012).

In recent years, income inequality has increased worldwide due to the inequality of opportunities for obtaining education, occupational choices reducing skills, weaker social mobility, and workplace inequalities. Income inequality is increasing in emerging economies of G-20 (i.e., Indonesia and China) and decreasing in developing countries (i.e., Brazil and Argentina) due to social and political cohesion, less sustained economic growth, and lower consumption, according to the ILO, IMF, OECD and WBG (2015). Similarly, according to the ILO report (2021), income inequality increases sharply under COVID-19 due to a decrease in relative levels of income, quality of employment opportunities, and inter-sectional division among workforce groups (i.e., on the basis of race and ethnicity, education, age, migration status, formal and informal workers, etc.). Some macroeconomic determinants of income inequality among different income groups have also been identified from panel data by Basumatary et al. (2024). According to the different income-group countries from 1996 to 2019, the main determinants of low-income countries with a positive impact on income inequality are the HDI, civil liberty, and governance. In lower-middle-income countries, there is a positive association between population growth, globalization, governance, and income inequality. In upper-middle-income countries, economic and population growth, civil liberty, and governance are positively related to income inequality. However, in high-income countries, economic growth, population growth, gender equality, and natural resources have a positive impact on income inequality (Basumatary et al., 2024). A primary work-based study on female informal workers in Hosanna City, Ethiopia, found that socio-economic advancement is also largely influenced byage, work experience, income, savings, and migration (Lemma and Sharma, 2025).

In the case of India, Banerjee (1983) explained that a potential migrant has the ability to know his/her real-income differentials at the time of urban informal sector employment or unemployment compared to the formal sector. There is a huge income gap between informal and formal sector employment due to the high wage rate of formal workers, a subsistence level or lower than the subsistent level wage rate of informal workers, lack of human capital, and institutional barriers. Owing to the lack of trade unions, minimum wage laws, unemployment insurance, and welfare benefits in traditional economies, poor workers have a poorer standard of life, which contributes to the income gap. Some of the studies in India observed that the possibility of an informal individual being poor is less in a large city than in any other rural area; in case of the migrant people, it is the higher caste category than the lower caste people. This is due to the existence of different levels of monthly per capita income and consumption in urban and rural areas (due to the impact of urbanization and globalization) and the wage disadvantages of non-migrants in rural areas (Breman, 1996; Dabla-Norris et al., 2015). The difference exists among the higher and lower caste categories of people because of the changes in the real wages over time among the male and female workers and the work transformation from agricultural to the non-agricultural work. Due to the overrepresentation of female migrant workers in casual labor, the author noted that migrant workers have lower salary rates than non-migrant workers, although migrants have wage advantages for male workers in regular jobs. According to the study, there is a salary disparity between state and private mining in India (Samanta et. al., 2022). According to them, workers working in the public sector earn higher wages than those in the private sector, and the wage gap is higher at the bottom and lower at the top owing to unequal wage distribution. Similarly, inter-industry wage differentials have also been observed in India due to the absence of convergence and persistence among the manufacturing sector, for which the same skilled laborers receive different wages in different manufacturing industries. According to Padhi et al. (2019), the main reasons for gender-based wage discrimination in India are mostly non-monetary factors such as defeminisation, casualization, and informalization. Other non-monetary factors such as social problems, education, health, and social protection play a vital role in increasing inequality in India (Himanshu, 2019; Munshi and Singh, 2024). Another important factor that also plays a crucial role in increasing the income differences between the low-income households is the COVID-19 pandemic (Jha and Lahoti, 2021). This pandemic not only worsens the financial situation of the nation but also breaks down the backbone of the financial support of many households. However, due to the significant growing technological progress and excess supply of workers, the capital share is increasing significantly at the expense of labor share, but technological progress can increase labor share by mounting suitable employment opportunities (Ozdemir, 2023).

In the case of out-migrants in Odisha, the determinants of remittance sending are different due to their social, economic, and demographic characteristics, and economic growth in some sectors (Odisha Economic Survey, 2020-21). According to Meher and Dash, not all out-migrants are able to send the same remittances to their native place of Odisha due to age, sex, place of residence and social group. However, Sahoo and Paltasingh explained that income inequality rises because of the significant growth in some sectors, specifically in the tertiary sectors after the post-reform period. However, inequality in income arises mostly due to the outbreak of COVID-19, and as unemployment increases at a high time, a wage-cut policy was adopted by some of the IT sectors, leading to poor education, reduction in government expenditure except health, and negative economic growth in different sectors differently, etc. (Odisha Economic Survey, 2020-21). Similarly, due to various socio-economic factors, inequality in income and expenditure is also increasing among non-migrant and migrant informal workers in the rural and urban areas of the country (Barik and Baig, 2022; Barik, 2024). Thus, it is logical that very few studies have been conducted on the informal sector, informal employment, and informal income at the regional level. It is also important to study the dynamics of informal workers and their determinants of income, specifically among migrant and non-migrant ISWs. Therefore, this paper focuses on the empirical study of the Cuttack (CTC) city of Odisha, as the CTC is the oldest, the 1^st capital city and 2^nd largest ISWs.

Methods

The present case study is based purely on a household-level primary survey conducted during March-May 2025 in the CTC of Odisha. In this study, the number of household heads (HHds) was 470 (10 percent criteria of the total slum population was applied), which included both non-migrant (NMs) and migrant (Ms) slum-dwellers, specifically informal sector workers (ISWs). HHds are selected based on the strength of the respondent’s occupation (self-employed, wage-employed, and casual laborers), migration status (whether migrated or non-migrated), and keeping in mind the municipality classification (CTC has three Constituencies; Barabati, Chaudwar and Sadar). Thus, the present study was followed by a multi-stage stratified sampling method for collecting relevant data from the ISWs of the CTC, Odisha. However, before collecting the information from the informal respondents, secondary information was also taken into consideration that is from the Bikash Bhavan CMC (Cuttack Municipality Corporation).

However, the article is related to the socio-economic problems of informal workers and most of them are illiterate, written consent seems to be impossible. Hence, we preferred to take informed verbal consent. In this regard, we explained the purpose and the content of this research (interview) to the participant, and s/he agreed to participate in the study. Thus, in this study, informed verbal consent was obtained before data collection. Similarly, this research is based on primary survey of the households and specifically to the household head, thus, no minor participants were taken into considered. The methodological steps and the total number of non-migrant and migrant respondents are explained in Figure 1.

Figure 1. Methodological ways to select the sample.

Results and discussion

Conclusions and policy implications

After a ground-level data collection and analysis, the study may be concluded by slating that informal sector workers, both Ms and NMs, have greater attention at both the national and regional levels for their upliftment in modern society. The findings of this study also show that even though the income of non-migrants is lower than that of migrants due to lower paid wage earnings (e.g., security guard jobs, working as a cook or maid in the household sector, and local rickshaw puller), other livelihood facilities such as local unity, social and job security, sanitation, and other facilities are enjoyed by them due to their voting rights. All the informal workers, both M and NM, are facing the ‘situation of zero minimum income’ due to unavailability of work in all the seasons-months-days in the city. Thus, various socio-economic factors such as casual laborers, regular wage employed, general category people, number of dependencies, vocational training, off-season supporters, gender, memberships with the union, age, age squared, land owned by the HHds, migration status, service sector, agriculture sector, and household sector play a crucial role in these lower income groups and variations.

However, none of these determinants are constant for non-migrant and migrant informal workers in the city. Over all, informal workers are the ultimate victims in cities. Thus, in this post COVID-19 pandemic situation, there is a need for improvements in the area of basic facilities such as housing, electricity, health, vocational education, and social security through citizen forum (a system of open forum in the Bhubaneswar municipality for discussing the problems is faced by public utility and also used as a platform for providing possible solutions to the problem).

The present informal employment study, therefore, needs paramount importance for the country, state and district or from the grass root level (villages) to central government (following the ‘Panchayat Raj System’ in India, i.e. a three-tier development structure for the rural development), 1stly And 2ndly, to develop the poor socio-economic conditions of informal sector workers, both rural and urban governments should facilitate basic amenities such as sanitary facilities, proper drinking water facilities, basic nutritional food facilities at minimal cost, vocational education or training, and regulated shelter facilities with minimal or free costs. In other words, in a traditional sense we can say that we can provide and facilitate the “Roti-Kapda-Makaan” to these vulnerable sections of the state and country. 3rdly, for creating the awareness about health and environment, both the local and central government should facilitate the basic education through “M-E-S” (Mobile-Education-Service, which means, education and awareness services provided by the vehicles to their door step just such as the venders selling their goods and services on everyday basis) to these informal sector workers. However, 4thly, the most important policies need to be re-emphasized by the government—the MGNREGS (Mahatma Gandhi National Rural Employment Guarantee Schemes) and MSMEs (Micro, Small, and Medium Enterprises) — which can play a dual role in reducing unemployment and increasing income both in the village and the urban areas of the country in this post COVID-19, war and inflationary situation.

Therefore, by implementing and applying the above policies for the upliftment of the informal sector workers can also be able to achieve many Sustainable Goals, such as 1) No Poverty (by giving the employment opportunities both in the urban and rural areas), 2) Zero Hunger (by making available the basic nutritional food at minimal cost), 3) Good Health and Well-Being (by creating the awareness about the health and environment), 4) Quality Education (by facilitating the basic education and vocational training through new ‘M-E-S’ programme), 6) Clean Water and Sanitation (by facilitating the basic amenities such as sanitary facilities, proper drinking water facilities), 8) Decent Work and Economic Growth (by generating the work in the organized sector), 9) Industry, Innovation and Infrastructure (by re-emphasizing on the MGNREGS and MSME programmes), 12) Responsible Consumption and Production (by providing the basic nutritional food at minimal cost or minimum support price), and 17) Partnerships for the Goals (by the involvement of both the informal sector workers and the state and central government for achieving all these goals). However, this primary research work is also not free from limitations due to its limited sample size (470 only), restricted area (Cuttack District, Odisha only), lack of information before their migration, and the situation after the COVID-19, war, and hyper inflation. This study is also applicable to developing countries such as India, where the number of informal sectors (more than 90%) and workers (more than 91%) are large.

Declarations

Ethical Clearance: This study meets national and international guidelines for research on humans. In this regard, an ethical approval certificate has been obtained by University level Ethics Committee (ULEC), KIIT Deemed to be University, Bhubaneswar with the ethical clearance certificate no. KIIT/ULEC/012/2025 on dated 15/05/2025.

Materials Used: Due to the primary nature of the article, we have prepared a structured questionnaire for the respondents for data analysis (The Figshare DIO/Identifier no 10.6084/m9.figshare.30581063).