The Role of MSMEs in Enhancing Income and Economic Well-being of Owners/Managers in Assam,India

Abstract

The aim of this study is to investigate the contribution of micro, small and medium enterprises (MSMEs) to the economic well-being and earnings of their owners/managers with reference to the Cachar district of Assam. A standardised questionnaire is utilised to collect data from 200 randomly chosen MSMEs operating in the Cachar district of Assam, a developing region of India, to accomplish the aim of the study. Descriptive statistics are used to analyse the collected data. Additionally, the study employs Wilcoxon signed-rank test to examine the statistical difference between the income of MSME owners/managers before and after joining MSMEs. The results demonstrate that MSMEs enhance the monthly income of 74 per cent of owners/managers. The results of the Wilcoxon signed-rank test indicate that the median income of MSME owners/managers has significantly increased after their involvement in MSMEs. The study also indicates that almost 9 out of every 10 MSMEs generate earnings of the owner-managers above the poverty line, whereas 83.9 per cent of MSMEs generate household income of owners/managers above the defined poverty line. MSMEs significantly improve the households’ material well-being by enhancing the spending ability of their owners/managers and increasing asset holding.

Keywords

Micro small and medium enterprises well-being poverty Wilcoxon signed-rank test Cachar Assam

Introduction

Micro, small and medium enterprises (MSMEs)¹ are widely recognised for their significant contribution to economic development and job creation around the globe. MSMEs have now become one of the key vehicles for solving various socio-economic concerns and meeting development goals in both advanced and emerging economies (Ayalu et al., 2023; Sanu & Anjum, 2023). For instance, MSMEs account for 50–60 per cent of value-added and 60 per cent of employment across the ‘Organization for Economic Cooperation and Development (OECD)’ countries (International Labour Organization, 2019; OECD, 2019). The recent International Labour Organization statistics reveal that small and medium enterprises (SMEs) and own-account workers account for over 70 per cent of worldwide employment. These enterprises generate income and employment for a large share of rural and urban workers and produce essential goods and services for a rapidly growing population (Harvie, 2003). Recognising their importance, the international communities now see MSMEs as a vehicle through which inclusive growth is achieved.

In India, the MSME sector is also important for the country’s socio-economic development. This sector, which includes around 63.4 million units across the country, accounts for 31.83 per cent of India’s gross value added (Government of India, 2019), 45 per cent of India’s industrial output, and 48.10 per cent of exports, both directly and indirectly (Government of India, 2019). According to the Ministry of MSMEs’ Annual Report (2022–2023), independent non-agricultural MSMEs hired 110.98 million people in a variety of industry sectors, including manufacturing, trading, other services, and non-captive energy generation in 2015–2016. Despite its abundant natural resources, Assam encounters many economic issues, ranking as one of India’s least developed states. The enigma of prosperity coexisting with poverty is apparent in a variety of socio-economic indices. While the large industries of the state are not making any significant progress, the MSME sector constitutes the mainstay of the industrial sector in the state. Assam has enormous potential for the development of MSMEs based on its factor endowments. The sector significantly contributes to the industrialisation process, job creation and the fulfilment of other socio-economic objectives in the state. As per the latest available data, there were 51,910 registered MSMEs (micro—45,215, small—6,141 and medium—554) in Assam, which employed 504,037 persons up to 31 March 2021 (Government of Assam, 2021–2022).

In a diverse country like India, with differences in geography, customs and economic parameters, the centralised common policies and initiatives aimed at the development of MSMEs may not yield the best results. Consequently, specialised interventions are required depending on the outcomes of region-specific studies. In this context, the current study seeks to investigate the effect of MSMEs on the income and economic well-being of their owners/managers in the Cachar district of Assam.

Literature Review

The role of MSMEs in economic growth, job creation and development has been well-documented in the literature. There is a substantial body of research that highlights the contribution of MSMEs to national income and employment generation in both developed and developing nations, as well as in economic blocs (Abor & Quartey, 2010; Endris & Kassegn, 2022; ILO, 2019; Kongolo, 2010; Maksimov et al., 2017; Manzoor et al., 2021; OECD, 2019). A cross-country empirical study conducted by Ayyagari et al. (2003) shows that SMEs, including both formal and informal enterprises, account for 60–70 per cent of GDP across countries, and these enterprises are also responsible for a larger share of employment in all countries, irrespective of their income level. Another estimation carried out by the International Finance Corporation (2010) indicates that SMEs contribute a sizeable share to formal GDP, accounting for an average of 49 per cent in high-income nations and 29 per cent in low-income nations.

A large number of studies also established a connection between MSMEs and poverty reduction (Beck et al., 2005; Harvie, 2003; Manzoor et al., 2019; Mukras, 2003; Nursini, 2020; Vandenberg, 2006). Vandenberg (2006) asserted that MSMEs generate and maintain jobs that allow poor people to work and earn enough money to buy goods and services. A recent empirical investigation by Nursini (2020) demonstrates that MSMEs diminish poverty in Indonesia directly as well as indirectly. Similarly, Mazoor et al. (2019) reveal that the growth of SMEs helps alleviate poverty in the SAARC region. A few studies have also unfolded the contribution of MSMEs to local community development. For example, Ayalu et al. (2023) investigated the importance of micro and small enterprises to sustainable community livelihood in the Tigray region of Ethiopia. The findings expose that MSMEs contribute to employment generation, economic growth and income generation for the local population.

As MSMEs are considered the backbone of the Indian economy, several studies have been carried out in India on different aspects of MSMEs, including their contribution to economic growth, employment generation, problems and prospects, productivity and efficiency, innovation and internationalisation (Aggarwal & Joshi, 2024; Bagodi et al., 2021; Dixit & Pandey, 2011; Roy et al., 2016; Sharma & Sharma, 2010; Singh & Kaur, 2021, among others). Some studies have also been done in Assam to explore the various aspects of MSMEs in the state (Chakraborty & Chakraborty, 2017; Sanu & Anjum, 2023; Sanu et al., 2020; Sarda & Baruah, 2020; Sarmah et al., 2021).

However, to the best knowledge of the authors, no empirical studies have probed the contribution of MSMEs to the economic well-being and income of their owner-managers in the state of Assam in general and Cachar district in particular. This study is a modest effort to fill this gap in the literature.

Objectives

The precise objectives of the current research are as follows:

To estimate and compare the income of MSME owners/managers before and after joining MSMEs.

To examine whether the income generated by MSMEs for their owners/managers is sufficient to lift them out of poverty.

To investigate whether MSMEs enhance the material well-being of their owners/managers by increasing their spending ability (on goods and services) and asset holding.

Data and Methodology

Sample Description, Survey Tools and Data Analysis Techniques

The current study utilises primary data collected employing a structured questionnaire and personal interview schedule from MSMEs situated in the Cachar area of Assam, India. The target population for this research consists of Cachar district’s registered micro, small and medium-sized businesses. The study questionnaire was handed out to 200 MSMEs drawn at random from the district’s revenue circles/tehsils. Because top management is familiar with every aspect of the organisation, most responders were owner-managers; however, chief executive officers were also targeted in some circumstances.

We have employed descriptive statistics like frequencies, percentages, mean, median and minimum and maximum values to analyse the collected data. Furthermore, Wilcoxon signed-rank test is applied to test the statistical difference between the incomes of MSME owners/managers before and after joining MSMEs.

Estimation of Income/Net Profits

In order to estimate the profits of sample MSMEs, the present study used two different methods. The first method was used for enterprises that were not sole proprietorships. This method involved asking directly how much profit the enterprise earns over a specified time period (per month or per year). The information thus obtained was converted to average monthly figures. The second method of income estimates, which was used for sole proprietorships only, involved asking the following three questions: (a) Does your household consume or use any product or services from this enterprise? (b) Do you use part of the money you receive from the enterprise for yourself or your household? (c) Is there any money left after the enterprise’s expenses and after utilising some of it for yourself or your household? For each of these three questions, the owners/managers were then asked for the value in rupees and how often they used or consumed this amount. The values were then converted to average monthly figures. The second method of income estimates, which is in line with the World Bank’s Living Standard Measurement Surveys, was found to be the most accurate and relatively easiest way of measuring income/net profits of MSMEs when it was compared with the other four measures of profit estimation on a sample of 448 enterprises in Zimbabwe (Daniels, 2001, 2003).

The present study also collected information regarding capital assets, namely, buildings, equipment, machinery, hand tools and vehicles. For each item, the owner-manager was asked the year of purchase and the amount spent on it. The Wholesale Price Index for Capital Goods (2011–2012 = 100) was used to inflate the values. Then, assuming a straight-line depreciation, these figures were used as a rough estimate of annual implicit depreciation charges. This helped the researcher to split the gross profit into two parts, namely, depreciation and leftover net profits. The final income estimate is based on monthly net profits divided by the total number of proprietors and unpaid staff.

It is important to note that the income estimates employed in this study are not very precise. The income figures should be viewed as indicative rather than final. However, the researchers believe that they are reliable indicators and do help to understand the pattern of income earned in the MSME sector of Cachar district.

Results and Discussion

Monthly Income of Owners/Managers by Various Characteristics

Table 1 shows the net profits/income per owner/manager per month by location and gender. A comparison of net profits by location of the enterprises indicates that urban-based MSMEs earn a much higher return per month than their rural counterparts. This difference is also statistically significant, suggesting that there is wide variability in profits between urban and rural MSMEs.

Table 1.

Monthly Income/Profits of Micro, Small and Medium Enterprise (MSME) Owner/Manager by Location and Gender.

Category	Average Income	Std. Dev.	Maximum	Minimum
Location
Urban	22,300* (17,000)	14,388.53	61,000	2,900
Rural	14,389.64* (11,000)	11,567.84	50,000	3,000
Gender
Male-owned	19,675* (16,000)	13,848.78	61,000	3,000
Female-owned	12,300* (9,000)	10,739.31	50,000	2,900

Note: * indicates levels of significance at 5%. The figures in parentheses () indicate the median monthly income.

As shown in Table 1, the maximum average monthly income for an owner-manager in urban MSMEs is ₹61,000, while the corresponding figure for an owner/manager in rural MSMEs is ₹50,000. The standard deviation indicates that the variability of net profits per month per owner-manager is also higher in urban-based MSMEs. Table 1 also shows that MSMEs owned by men tend to earn significantly higher net profits than MSMEs owned by women. The average monthly income for male-owned MSMEs is ₹19,675, while the corresponding figure for female-owned MSMEs is only ₹12,300. The variations in return may be due to the type of operations or structures of male- and female-run MSMEs. The survey findings show that most women-run MSMEs in the Cachar district engage in low-income service activities such as beauty salons and beauty treatments and cloth designing. Furthermore, past research reveals that female entrepreneurs are risk-averse, and their other household obligations force them to select businesses that are simple to handle.

Net profits per owner-manager per month in the various sectors/activities of the sample MSMEs are presented in Table 2. The findings reveal that enterprises in the ‘mineral-based products’ sector earn the highest profits, followed by those in ‘other manufacturing items’, and then ‘food and agro-based products’. The lowest returns are observed in ‘textiles, garments and other wearing apparel’, followed by ‘wood and cane products’ and ‘repairing and maintenance’. The difference between the average earnings in the mineral-based products sector (₹28,805), the highest-earning sector, and the ‘textiles, garments and other wearing apparel’ sector (₹8,937), the lowest-earning sector, is ₹19,868. This indicates that there is considerable variability in net profits among the different sectors/activities of MSMEs in the Cachar district.

Table 2.

Profits/Income Per Owner/Manager Per Month by Industry Sector/Nature of Activity.

Sector/Activities	Average Income	Std. Dev.	Maximum	Minimum
Food and agro-based products	24,109.67 (25,000)	14,033.39	53,000	6,000
Wood and cane products	9,456.25 (7,500)	7,435.76	32,000	3,300
Textile, garments and other wearing apparel	8,937.5 (8,000)	4,411.32	16,000	4,000
Metal fabrication and other engineering works	18,715.62 (15,000)	13,872.94	50,000	3,675
Mineral-based products	28,805.26 (25,000)	13,677.98	61,000	3,800
Paper and paper-based products	20,880 (15,000)	16,108.13	49,000	8,000
Other manufacturing items	25,618.18 (19,500)	17,980.03	3,300	60,000
Repairing and maintenance	10,994.11 (10,000)	8,107.20	30,000	3,000
Other services	14,746.55 (15,000)	9,777.54	50,000	2,900
Total	18,384.37 (15,000)	13,625.50	61,000	2,900

Note: The figures in parentheses () indicate the median monthly income.

A Comparison of Current Earnings of Owners/Managers/Workers with Their Previous Professions

To further investigate the impact of MSMEs on the income of owners/managers, the study compares the monthly average income of owners/managers before and after their involvement in MSMEs. For this purpose, the respondents were first asked to reveal whether their average monthly income after joining the enterprise(s) had highly increased, increased, remained the same or decreased. The responses thus obtained are summarised in Table 3.

Table 3.

Status of the Income of Owners/Managers After Joining Micro, Small and Medium Enterprises (MSMEs).

Monthly Income Status	Frequency	Per cent
Highly increased	44	22.0
Increased	104	52.0
Not changed	37	18.5
Decreased	15	7.5
Total	200	100.0

As shown in Table 3, 22 per cent of owners/managers reported that their average monthly earnings after joining MSMEs had highly increased, and 52 per cent revealed that their average monthly income had increased. Therefore, MSMEs resulted in an increment in the average monthly income of 74 per cent of owners/managers. On the other hand, 18.5 per cent of owners/managers revealed that their monthly earnings remained the same even after joining MSMEs, while only 7.5 per cent of respondents reported that their average monthly income decreased after joining MSMEs. These results indicate that MSMEs momentously increase the income of their owners/managers.

Table 4 and Figure 1 illustrate the average monthly income of owners/managers before and after joining MSMEs. The data show a clear shift in the income of the (now) owner-managers from relatively lower to higher levels. A comparison of the number of (now) owner-managers in different income ranges indicates that before joining MSMEs, 124 individuals had an income less than ₹10,000, but this figure decreased to 71 after their involvement in MSMEs. Before joining MSMEs, there were only 52 (now) owner-managers in the income range of ₹10,001–20,000, but this number rose to 69 after joining MSMEs. Similarly, while only one (now) owner-manager had an income exceeding ₹40,000 before joining MSMEs, the number of owners/managers with an income above ₹40,000 increased to 18 after joining MSMEs. Therefore, there is a marked increase in the earnings of the (now) MSME owner-managers compared to their previous earnings.

Table 4.

Monthly Income/Profits of Micro, Small and Medium Enterprise (MSME) Owner-Managers Before and After Joining MSMEs.

Income Range	Before Joining MSMEs		After Joining MSMEs
Income Range	No. of Owner-Managers	% of Owner-Managers	No. of Owner-Managers	% of Owner-Managers
<10,000	124	62.0	71	35.5
10,001–20,000	52	26.0	69	34.5
20,001–30,000	20	10.0	27	13.5
30,001–40,000	3	1.5	15	7.5
>40,000	1	.5	18	9.0
Total	200	100.0	200	100.0

Figure 1.

Percentage Distribution of Owners/Managers in Different Income Bands Before and After Joining Micro, Small and Medium Enterprises (MSMEs).

The present study also examines whether the differences in income before and after joining MSMEs are statistically significant. Traditionally, if the data fulfil the normality assumption, parametric tests (such as the t-test) are employed to assess the statistical significance of interval (scale) data. However, in this study, both the Kolmogorov–Smirnov and Shapiro–Wilk tests (Razali & Wah, 2011; Shapiro & Wilk, 1965) (see Table A2), along with visual inspection of the data through histograms, normal Q–Q plots and box plots (see Figures A1, A2, A3 and A4), indicate that the income data before and after joining MSMEs are not normally distributed. Therefore, to test the statistical difference between the income data before and after joining MSMEs, this study employs Wilcoxon signed-rank test, which is a non-parametric test equivalent to the dependent t-test (paired t-test).

The results of the Wilcoxon signed-rank test are presented in Tables 5 and 6. Table 5 shows that there are 13 negative ranks, indicating that the earnings of 13 owners/managers decreased after joining MSMEs, while there are 171 positive ranks, suggesting that the income levels of 171 owners/managers increased post-joining. Additionally, the earnings of 16 owner-managers remained unchanged even after joining MSMEs. Table 6 indicates that the Z-statistic is significant at less than 1 per cent level; therefore, the null hypothesis of no difference between the median income before and after joining MSMEs is rejected. Since the mean rank is higher for income levels after joining MSMEs (as shown in Table 5), it can be concluded that the monthly income of owners/managers significantly increased after joining MSMEs compared to their average monthly income in their previous occupations.

Table 5.

Ranking of Current and Previous Income Based on Wilcoxon Signed-rank Test.

		N	Mean Rank	Sum of Ranks
Current income – previous income	Negative ranks	13^a	70.65	918.50
	Positive ranks	171^b	94.16	16,101.50
	Ties	16^c
	Total	200

Note: ^aCurrent income < previous income; ^bCurrent income > previous income; ^cCurrent income = previous income.

Table 6.

Test Statistics Based on Wilcoxon Signed-rank Test.

	Current Income – Previous Income
Z	–10.494
p Value (two-tailed)	.000

Note: Z-statistics is based on negative ranks.

A Comparison of Net Profits/Income with Poverty Line (World Bank’s $1.90 Per Day²)

In this section, an attempt is made to compare the monthly earnings of MSME owners and managers with the poverty line defined by the World Bank in 2015 ($1.90 per day per person). The exchange rate of the rupee in terms of the dollar was determined by averaging the monthly exchange figures for the year 2018. The estimated monthly poverty line was thus set at ₹3,897. Table 7 reports the percentage of MSMEs that generate earnings above this absolute poverty line. The findings reveal that, overall, nearly 9 out of every 10 MSMEs generate earnings for their owners/managers above the poverty line. The distribution of MSMEs between rural and urban areas indicates that in urban areas, 95 per cent of MSMEs generate earnings above the poverty line, whereas in rural areas, approximately 82 per cent of MSMEs earn returns above this threshold.

Table 7.

Percentage of Micro, Small and Medium Enterprises (MSMEs) that Generate Earnings of Owners/Managers Above Poverty Line (World Bank’s $1.90 Per Day).

All MSMEs	88.5
Location
Urban MSMEs	95.0
Rural MSMEs	81.8
Gender
Male-owned MSMEs	90.3
Female-owned MSMEs	80.0
Education
High school or less	80.3
Senior secondary or more	100

Considering the gender of owners/managers, the study results indicate that male-owned MSMEs lift more people out of poverty than female-owned MSMEs. Specifically, about 9 out of every 10 male-owned MSMEs generate income above the poverty line, while 8 out of every 10 female-owned MSMEs do the same. The results further demonstrate that higher levels of education among owners/managers have a crucial impact on the poverty alleviation capacity of MSMEs. Eighty per cent of the MSMEs owned or managed by entrepreneurs with a high school education or lower generate income above the poverty line, whereas all MSMEs managed by owners/managers with senior secondary education or higher generate earnings above this threshold.

Although a comparison of owners’/managers’ income is made with the poverty line in Table 7, it does not provide sufficient information about their household poverty. To compare the contribution of MSMEs to household poverty alleviation, the owners/managers were first asked what proportion of their income comes from the MSMEs. The owners/managers who reported that the enterprise(s) in which they were involved were the sole source of all or almost all of their household income, their earnings were compared with a household size-adjusted poverty line. Table 8 summarises the proportion of household income contributed by MSMEs. As shown in the table, 56 per cent of MSMEs in operation contribute all or almost all of the household income of their owners/managers. In comparison, 25.5 per cent of MSMEs provide more than half of the total household income. Therefore, MSMEs play a key role in providing household income in the Cachar district.

Table 8.

Contribution of Micro, Small and Medium Enterprises (MSMEs) to Household Income of Owner/Manager.

Contribution to Household Income as Estimated by Owners/Managers	Percentage of all MSMEs	Percentage of MSMEs in Rural Areas	Percentage of MSMEs in Urban Areas
All or almost all	56.0	43.4	68.3
More than half	25.5	32.3	18.8
About half	13.0	15.2	10.9
Less than half	3.5	6.1	1.0
Negligible amount	2.0	3.0	1.0

Table 9 shows that among the MSMEs that contribute all or almost all household income, 83.9 per cent generate income for their owners/managers above the adjusted poverty line. The distribution of enterprises by location indicates that MSMEs in urban areas lift more households out of poverty compared to those in rural areas. Similarly, male-owned MSMEs alleviate poverty for more households than female-owned MSMEs. The findings also reveal that MSMEs owned by educated owners/managers reduce household poverty to a greater extent.

Table 9.

Percentage of Micro, Small and Medium Enterprises (MSMEs) That Generate Household Earnings of Owners/Managers Above Poverty Line (World Bank’s $1.90 Per Day).

All MSMEs	83.9
Location
Urban MSMEs	88.4
Rural MSMEs	76.7
Gender
Male-owned MSMEs	87.5
Female-owned MSMEs	62.5
Education
High school or less	66.0
Senior secondary or more	96.9

Note: This table includes all those MSMEs which accounted for all or almost all of the income of owners’/managers’ families. The poverty line is adjusted to the family size of owners/managers.

Impact of MSMEs on Owners’/Managers’ Household Spending Ability and Well-being

Although income is a common proxy for economic well-being and/or deprivation, especially in developed countries, many researchers have argued that consumption or expenditure is a better measure of material well-being in developing countries. This is because people benefit from the actual consumption of goods and services rather than the receiving of income itself. Moreover, some researchers have contended that, unlike consumption, income can be a misleading indication of the economic status of a household because transitory events such as layoffs or changes in family status cause more fluctuations in income than in consumption without reflecting necessary changes in well-being. Consumption is also less fragile to under-reporting bias.

Considering the above arguments, an attempt is made here to study the changes in the pattern of MSME owner-managers’/workers’ household expenditure after their involvement in the enterprises. For this purpose, the owners and managers were asked to reveal whether their household’s ability to spend on food, clothing, housing, education and health services had increased, decreased or remained the same after their involvement in MSMEs. The responses thus gathered are summarised in Table 10.

Table 10.

Status of Household’s Ability to Spend After Owners’/Managers’ Involvement in Micro, Small and Medium Enterprises (MSMEs).

Exp. Items	Increased		Decreased		Not Changed
Exp. Items	No. of Owners-Managers	% of Owners-Managers	No. of Owners-Managers	% of Owners-Managers	No. of Owners-Managers	% of Owners-Managers
Food	126	63.0	10	5.0	64	32.0
Clothing	137	68.5	12	6.0	51	25.5
Housing	113	56.5	9	4.5	78	39.0
Education	137	68.5	10	5.0	53	26.5
Health services	126	63.0	9	4.5	65	32.5
Other basic needs	132	66.0	10	5.0	58	29.0
Overall expenditure	142	71.0	9	4.5	49	24.5

The majority of owners/managers reported that their household’s ability to spend on food, clothing, housing, education, health services and other basic needs has shown an increasing trend. Conversely, only a small proportion of owner-managers indicated that their household’s ability to spend on these items declined after their involvement in MSMEs. Therefore, MSMEs significantly enhance the well-being of households whose members join MSMEs as owners/managers in the Cachar district of Assam.

MSMEs also help their owners/managers and others acquire various types of assets, such as consumer durables, houses, land and plots, which directly impact household well-being. The percentage of owners/managers who purchased different types of assets for their households due to their involvement in MSMEs is provided in Table 11. It is observed that 72.5 per cent of owner-managers purchased various communication facilities, such as TVs, telephones/mobile phones, radios and computers/laptops for their households. Additionally, 53.5 per cent bought modern furniture for their household needs, while 23.5 per cent built or purchased houses. Furthermore, 29 per cent acquired plots, land or flats, and 60.5 per cent of owners/managers purchased various types of vehicles, including two-wheelers and four-wheelers. Lastly, 70 per cent of them bought different electrical appliances, such as fans, refrigerators, air conditioners, washing machines and electronic stoves.

Table 11.

Assets Holding as a Result of Micro, Small and Medium Enterprises (MSMEs).

Asset	% of Owners/Managers
Communication facilities (TV, radio, land phone/mobile and others)	71.5
Furniture (bed, chair, tables, sofa, almirah, wardrobes and others)	53.5
House	23.5
Plot/land/flat	29.0
Vehicles (Bicycle, motorbike, four-wheelers)	60.5
Electrical appliances (fan, fridge, iron, electric stove and others)	70.0
Other consumer durables	22.5

Conclusion and Policy Implications

This study investigated the impact of MSMEs on the earnings and economic well-being of their owners/managers and households in a less-developed region of a developing economy. To this end, primary data have been collected employing a questionnaire and personal interview schedule from MSMEs situated in the Cachar area of Assam, India. We have randomly selected 200 registered MSMEs from the study area to gather the required information. Descriptive statistics such as frequencies, percentages, mean, median and minimum and maximum values are used to analyse the collected data. Additionally, the study employs Wilcoxon signed-rank test to examine the statistical difference between the income of MSME owners/managers before and after joining MSMEs.

The findings suggest that altogether, MSMEs resulted in a boost in the average monthly income of 74 per cent of owners/managers. The results of the Wilcoxon signed-rank test indicate that the median income of MSME owners/managers has significantly increased after their involvement in MSMEs. This evidence suggests that MSMEs offer better jobs in terms of net profits and wages. A comparison of the income of MSME owner-managers/workers with the World Bank’s poverty line shows that overall, almost 9 out of every 10 MSMEs generate earnings of the owner-managers above the poverty line. The findings also reveal that MSMEs significantly increase the households’ material well-being by enhancing the spending ability of owners/managers. MSMEs also assist their owners/managers in having various types of assets such as consumer durables, houses, land and plots.

The empirical evidence drawn from the present research has several practical implications. The government should use the development of MSMEs as a strategy for alleviating poverty and enhancing economic well-being in the regions like Cachar district of Assam. In addition to the common schemes and policies, the policy designers may formulate targeted policies and schemes for the promotion of MSMEs in less-developed regions.

Appendix

Table A1.

Profile of Owners/Managers and Summary Characteristics of their Enterprises.

Variable/Category	Frequency	Per cent
Gender
Male	162	81
Female	38	19
Education
Primary and below	57	28.50
High school	77	38.50
Senior secondary	39	19.50
Graduation and above	27	13.50
Age of owners/managers
25 and below	19	9.50
26–35	60	30
36–45	81	40.50
46 and above	40	20
Marital status
Married	154	77
Never married	34	17
Separated/divorced	8	4
Widower/widowed	4	2
Segments/nature of activity
Manufacturing	125	62.50
Services	58	29
Repairing and maintenance	17	8.50
Location
Rural	111	55.50
Urban	89	44.50
Age of enterprise (years)
5 and below	83	41.50
6–10	39	19.50
11–20	61	30.50
20 and above	17	8.50
Ownership type
Proprietary	172	86
Partnership	12	6
Private Ltd. company	4	2
Public Ltd. company	2	1
Cooperatives	3	1.50
Others	7	3.50

Table A2.

Tests of Normality (Income).

	Kolmogorov–Smirnov^*			Shapiro–Wilk
	Statistic	df	Sig.	Statistic	df	Sig.
Income before joining MSMEs	0.138	200	0.000	0.850	200	0.000
Income after joining MSMEs	0.162	200	0.000	0.878	200	0.000

Notes: *Lilliefors significance correction. MSMEs, micro, small and medium enterprises.

Figure A1.

Normal Q–Q Plot of Income Before Joining Micro, Small and Medium Enterprises (MSMEs).

Figure A2.

Normal Q–Q Plot of Income Before Joining Micro, Small and Medium Enterprises (MSMEs).

Figure A3.

Histogram of Income After Joining Micro, Small and Medium Enterprises (MSMEs).

Figure A4.

Normal Q–Q Plot of Income After Joining Micro, Small and Medium Enterprises (MSMEs).

Footnotes

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Funding

The authors received no financial support for the research, authorship and/or publication of this article.

Notes

ORCID iDs

Md Sahnewaz Sanu

Shabana Anjum

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The Role of MSMEs in Enhancing Income and Economic Well-being of Owners/Managers in Assam,India

Abstract

Keywords

Introduction

Literature Review

Objectives

Data and Methodology

Sample Description, Survey Tools and Data Analysis Techniques

Estimation of Income/Net Profits

Results and Discussion

Monthly Income of Owners/Managers by Various Characteristics

Monthly Income/Profits of Micro, Small and Medium Enterprise (MSME) Owner/Manager by Location and Gender.

Profits/Income Per Owner/Manager Per Month by Industry Sector/Nature of Activity.

A Comparison of Current Earnings of Owners/Managers/Workers with Their Previous Professions

Status of the Income of Owners/Managers After Joining Micro, Small and Medium Enterprises (MSMEs).

Monthly Income/Profits of Micro, Small and Medium Enterprise (MSME) Owner-Managers Before and After Joining MSMEs.

Percentage Distribution of Owners/Managers in Different Income Bands Before and After Joining Micro, Small and Medium Enterprises (MSMEs).

Ranking of Current and Previous Income Based on Wilcoxon Signed-rank Test.

Test Statistics Based on Wilcoxon Signed-rank Test.

A Comparison of Net Profits/Income with Poverty Line (World Bank’s $1.90 Per Day 2 )

Percentage of Micro, Small and Medium Enterprises (MSMEs) that Generate Earnings of Owners/Managers Above Poverty Line (World Bank’s $1.90 Per Day).

Contribution of Micro, Small and Medium Enterprises (MSMEs) to Household Income of Owner/Manager.

Percentage of Micro, Small and Medium Enterprises (MSMEs) That Generate Household Earnings of Owners/Managers Above Poverty Line (World Bank’s $1.90 Per Day).

Impact of MSMEs on Owners’/Managers’ Household Spending Ability and Well-being

Status of Household’s Ability to Spend After Owners’/Managers’ Involvement in Micro, Small and Medium Enterprises (MSMEs).

Assets Holding as a Result of Micro, Small and Medium Enterprises (MSMEs).

Conclusion and Policy Implications

Appendix

Profile of Owners/Managers and Summary Characteristics of their Enterprises.

Tests of Normality (Income).

Normal Q–Q Plot of Income Before Joining Micro, Small and Medium Enterprises (MSMEs).

Normal Q–Q Plot of Income Before Joining Micro, Small and Medium Enterprises (MSMEs).

Histogram of Income After Joining Micro, Small and Medium Enterprises (MSMEs).

Normal Q–Q Plot of Income After Joining Micro, Small and Medium Enterprises (MSMEs).

Footnotes

Declaration of Conflicting Interests

Funding

Notes

ORCID iDs

References

A Comparison of Net Profits/Income with Poverty Line (World Bank’s $1.90 Per Day²)