Occupational transformation in India: issues and challenges.

Behera, Deepak Kumar

1. Introduction

Structural transformation is central to the idea of modern economic development. The pattern of employment growth was a key factor in facilitating the structural transformation of the economy as it happened in the developmental experience of developed economies. In the case of India, there are three apparent observations at the outset regarding the nature of its structural transformation. First, there has been a significant structural transformation in income. No commensurate change in the occupational structure occurred, however, for quite some time. In the post-Reform period (1) there is now some acceleration in transforming occupations. Second, this is led by the service sector, instead of by industry. Third, an overwhelming share of the modern economy is informal. The "informal economy's" contribution to quality of work conditions and to social security is extremely marginal. India's transformative trajectory is at a significant turning point. It is the task of this paper to measure the magnitude of the transformation. While doing so, we will estimate some determinants of structural transformation in the Indian economy.

2. Structural Transformation: The Indian Experience

When India embarked on the development process after Independence in 1950, the economy's GDP comprised about 60 per cent agriculture, 13 per cent industry, and 27 per cent services. It was structurally comparable to the economy of Great Britain in the late eighteenth century, of Germany at the beginning of the nineteenth, of the United States and Italy in the mid-nineteenth century, and of Japan in 1900. Similar comparisons hold with respect of the share of the labor force in different sectors: in India, agriculture accounted for about 75 per cent, industry about 11 and services 16 per cent of total employment in 1950. This is comparable to the United States of 1841, with 72 per cent of its workers in agriculture, 12 per cent in industry and 16 per cent in services, or to the Japan of 1880 with the respective shares of employment in the three sectors being 65, 15 and 20 per cent (Papola, 2005).

[FIGURE 1 OMITTED]

What India has achieved in the structural transformation of income in a span of sixty years represents a rate of change greater than experienced in developed countries. The share of agriculture in GDP in India declined from around 60 per cent in 1950-51 to 36.38 per cent in 1983 and further declined to 14 per cent by 2010-11. That of industry increased from 13 to 24, then to 28 per cent; and that of services went from 28 to 40, and then rose to 58 per cent (see Figure 1). A significant difference is to be noted: while most developed countries came upon a predominance of services in their economies after going through an industrial phase, India pretty much arrived at its present service sector dominance by going directly from agriculture to service.

The accelerating growth of GDP in India is not accompanied by a commensurate growth in employment. This asymmetry is noted by a plethora of studies like Rao (1979), Bhattacharya and Mitra (1997), Kuldeep and Dhindsa (2000), Gandhi and Gansan (2002), Papola (2005), and Dev (2008), and is evident from the data (see Table 1). However, there is some increased movement in the sources of employment in the three decades since 1983, as 23.21 per cent of jobs shifted away from agriculture. This is a much larger shift compared to the first 30 years after Independence, when only 4.7 per cent came out of agriculture. An increased share of agricultural workers are moving out of agriculture and joining the non-agricultural sector every decade. In the next three decades, if this rate of transformation persists, the share of agricultural labor may fall below 10 percent, a feature akin to developed countries.

We see three aspects of this change. One, the service sector has absorbed more labor than the industrial sector (2). Second, the shift of labor has taken place from the informal sector (3) of agriculture to the informal sector of the non-agriculture. Third, there is a large share of self-employed workers within the non-agricultural share. Their productivity tends to be generally less. Fourth, there is a question whether the so-called modern, yet unorganized, sector can absorb the substantial surplus labor that exists in agriculture.

This is partly due to the location of jobs within the economy. In the agricultural sector, where a majority of the work force is found, 31.97 per cent of people were self-employed and 21.48 per cent were casual laborers in 2009-10 (see Table 2). As it can be seen Table 1, after a sharp increase in the share of the self-employed category in agriculture by 2004-05, this share was in decline by 2009-10. With a decrease in self-employed workers, the share of casual labor has gone up in the agricultural sector. But in the non-agricultural sector, only casual laborers and regular-wage or salaried workers have increased their share in 2009-10 compared to the previous years.

From 1993-94 to 2009-10, the proportion of self-employment has decreased. Casual workers have increased significantly in the rural areas compared to 2004-05, perhaps because of the impact of the NREGA. For regular-salaried workers, there has been a marginal increase. This suggests there must have been a transfer of the labor force from the agricultural sector to the other sectors. But overall there has been a declining growth of employment in the modern sector (i.e. combination of both industry and services). This suggests a slowing process of transformation from agriculture to non-agriculture.

There is an increasing trend toward the non-farm sector in India in general, but the increase in non-agricultural work has been much less than the decline in agricultural employment. So there is a need for much faster growth of non-agricultural employment, even within rural areas since, as the majority of the population are in rural areas, the costs of migration would therefore be much less. (see Figure 2). However, the evidence in current trends does not suggest that this is happening. That there is an increased share of the self-employed can imply that more people are opting for cultivation, with small and marginal farm households dominating. This can disguise a lot of unemployment.

97.6 per cent of agriculture sector employment is informal, most of which is self-employed and casual labor (see Table 4). 71.6 per cent of workers in the non-agriculture sector are unorganized and 28.4 percent are organized. In both agricultural and non-agricultural sectors, the self-employed make up about 60 per cent of unorganized employment, whereas regular salaried employment makes up about 18 per cent of both.

What transpires from reading the structure of employment is that the overwhelming share of workers is in the lowly paid, insecure informal sector, sans any social security. Hence, the quality of employment in India is generally very poor. It is not capable of lifting the standards of living of people in any substantial terms.

2.1. Estimating the Rate of Structural Transformation in India

The dynamic change in structural transformation can be captured more rigorously from estimating the rate of change of structural transformation (RST). If Lt is the total workforce of the economy and [L.sub.n] is the non-agricultural (sum of industry and services) workforce, then the share of the non-agriculture sector is given by [L.sub.n]/[L.sub.t], which is also a measure of the degree to which a developing economy has diversified its production base. The rate of structural transformation may then be defined as the increment in [L.sub.n]/[L.sub.t] ratio per annum. Then the rate of structural transformation is:

RST = [L.sub.n]/[L.sub.t] ([L.sub.n] - L) (1)

The above equation has been derived as in the following:

Let 't' be the time period, and then the first difference of [L.sub.n]/[L.sub.t] with respect to time will be;

[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII] (2)

Using the approximation [partial derivative][tau] = [DELTA][tau] = 1 year, the above equation will be rewritten as:

[DELTA]([L.sub.n]/[L.sub.t]) = RST = [DELTA][L.sub.n]/[L.sub.t] - [L.sub.n][DELTA][L.sub.n]/[L.sup.2s.sub.t] (3)

RST = [L.sub.n]/[L.sub.t] ([DELTA][L.sub.n]/[L.sub.t] - [DELTA][L.sub.t]/[L.sub.t]) (4)

RST = [L.sub.n]/[L.sub.t] ([L.sub.n] - [L'.sub.t]) (5)

Thus the rate of transformation, contemplated as the rate of change of the ratio of non-agricultural employment to total employment over the period, is the ratio multiplied by the difference between the incremental change in non-agricultural and total employment. We have estimated the RST for two types of transformation: (a) from agricultural to non-agricultural and (b) from informal to formal (4).

The estimated rate of structural transformation is given in Table 5. The Rate of Transformation in terms of output has accelerated appreciably. Compared to the pre-Reform period (1973-91), it has accelerated from 0.56 percent to 0.863 percent during 1991-10.

While there is no commensurate growth in RST in occupational terms, there has been some transformation in the recent period. The RST of agricultural work to non-agricultural work has increased marginally from 0.57 to 0.586. This is even faster when we consider agricultural work's movement to unorganized non-agricultural work, where it has increased from 0.598 to 0.705. Whereas it has clearly worsened regarding the RST of agricultural to organized work, it declined from -0.023 to -.108 percent. Similarly, it has equally worsened in the case of unorganized work moving to organized work, from -0.026 to -0.114 percent between the pre- and post-Reform periods.

In conclusion, first of all, transformation in output has been a lot quicker than in employment for the past quarter-century in India, and further accelerated in the post-reform period. Second, the occupational transformation from agriculture to non-agriculture has marginally increased, while that from agriculture to unorganized non-agriculture has markedly increased. Thus it suggests that now there is a movement in occupational transformation, but it is totally in terms of movement towards the unorganized modern sector.

2.1.1. Factors behind the Pace of Transformation of Employment:

Occupational transformation in India has obviously been slow. There are several factors behind such slow movement. While the list of factors that affect structural transformation is extensive, we shall discuss some of them here, doing so in terms of supply-side and demand-side. We shall, however, include several others in our econometric exercise in the subsequent section.

2.1.1.1. Supply-side Factors

2.1.1.1a. Population Growth and Labor Supply

One of the most important factors that can slow the rate of transformation is the growth of the backlog of labor on the supply side that is to be accommodated in the modern sector, which in turn depends on the population growth rate. On the supply side, the population growth rate and the associated factors, inter alia, are important to determining labor supply. The size of the net working population is directly determined by age and sex, fertility, mortality, and migration patterns; and participation rates tend to be determined economically, socially and culturally.

The interrelationship between population growth and labor supply is characterized by four main points: first, population growth tends to lag in its effect on labor supply (5) [Bloom and Freeman, 1986]. Second, an increase in the fertility rate, with an increased dependency rate, will increase the labor supply up to a point and decline later. Third, the fertility increase and mortality decline are likely to have an immediate effect on the labor supply through their "behavioral" effects on the labor force participation rates (6). Fourth, work participation rates, which also influence labor supply, are determined by economic, cultural and social aspects.

The decline in the death rate in India has been faster than the fall in the birth rate, which increased population growth until 1981. Since 1951 to 1971, the population growth has significantly increased in the country for the bottom segment; i.e., those people who come under the poverty line (7). Partly due to family programming and partly to natural transition, decline in the birth rate over the death rate became possible by 1981. And after 1981, the population rate declined successively from 2.2 per cent in 1981 to 1.95 percent in 2001 and further declined to 1.62 percent in 2011 (8) (see Table 6). The urban population rates rose due to the growth of urbanization and increasing migration from rural areas. The urban population share has increased from 24 percent during 1981 to 31 percent during 2011. It is believed that more than half of all India's population growth by 2026 is likely to end up living in the urban sector. This has important ramifications for transformation. Gender specific interstate migration trends reveal that females are becoming increasingly represented in all types of migratory movements. Apart from the large exodus observed due to marriage, younger females are also seen to be migrating to urban areas for educational purposes. The prime reason for male migration remains employment and business (Perveen, 2004).

The population explosion in the early phase of development is perhaps a natural phenomenon, as happened in Europe between 1840-1911. However, the increase's impact on structural transformation was mitigated partly by the export of populations to its colonies and partly by absorbing the labor force into industry, which was favored by a low capital-labor ratio. India, a late entrant into industrial development, has lacked both of these alternatives, making the transformation a frustratingly slow process.

2.1.1.1b. Labor Force Participation Rate and Work Force Participation Rate

The population growth rate has declined in recent times considerably, but with an increase in the absolute number of people in the working-age population (age 15-59); and in urbanization, the participation rate in the labor market has increased. Figure 3 depicts the labor force and work force participation rates in India, and we see that both labor force participation rates (LFPRs) and work force participation rates (WFPRS) have increased in males and females irrespective of the location of residence. During India's post-reform phase, LFPRs have increased for both urban males and females and for rural females. WFPRs have declined for both males and females in rural areas, at the same time there are increasing WFPRs in males and females in urban areas. Urban female WFPRs have remained markedly lower than rural WFPRs. This difference partly reflects the greater difficulty of combining work with household duties in urban areas instead of in villages where work on the family farm or in the family enterprise tends to be the predominant activity. An important implication for transformation is that there is an increased need to create urban employment.

[FIGURE 3 OMITTED]

2.1.1.2. Demand-side Factors

Employment creation in the non-agricultural sector, on the demand-side, depends on rate of labor productivity and the capital-labor ratio. In India, there has been a remarkable growth of nonagricultural sector employment since 1983-04, compared to the agricultural sector. There was a marginal slowdown in employment growth in the non-agricultural sector during the post-reform period of 1993-09 (see Table 7). There is also a faster growth of labor productvity in the non-agricultural sector (5.12 per cent in the post-reform phase) associated with an increase in higher output growth (8.24 per cent), but with a marginal decline in employment growth (3.12 percent) in the sector compared to its previous decade.

If one looks at factor composition (9), it is observed that the capital-labor ratio has gone up from 4.67 per cent in the pre-reform period to 5.5 per cent during the post-reform period. (A short analysis of pre and post reform is given in footnote 2.) The increase in the capital-labor ratio can largely explain the decline in employment. Thus, on the demand-side, if the increase in labor productivity can augment employment, the rise in capital-labor ratio can dampen the same and the net effect depends on the relative strength of each.

3. Determinants of Structural Transformation:

An Econometric Estimation

We have noted that occupational structural transformation in India has been slower compared to income transformation; nonetheless, there is evidence that in the recent period it has quickened. In order to know the strength of various factors that may determine its movement we shall undertake a simple econometric exercise. The list of variables that are considered to have impact on the rate of employment transformation are urbanization, nonagricultural income, non-agricultural investment, technology used in the non-agricultural sector, non-agricultural informal employment, the rural-urban wage differential (Todaro model hypothesis), and skilled labor. Such variables are now presented in the following equation.

[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII] (6)

Where,

STR = Structural Transformation i.e. share of non-agricultural employment to total Employment.

UP = Urbanization; i.e., the share of urban population to total population

Y = Share of Non-agricultural sector GDP; i.e., the nonagricultural GDP to total GDP

GCF = Share of gross capital formation in non-agricultural sector; i.e., the non-agricultural total investment to total investment

K/L = Share of capital-labor ratio in non-agricultural sector

UE = Share of unorganized sector employment in the nonagricultural sector; i.e., unorganized sector employment in nonagricultural sector to total employment

RW = Rural-Urban real wage differential; i.e., the difference between real wages for Casual Workers between rural and urban areas at 1999-00 prices.

HC = Human capital; i.e., the literacy rate

[L.sub.91] = liberalization dummy; i.e., 0 for before 1991 (i.e., 1972-73 to

1990-91) and 1 for after 1991 (i.e., 1991-92 to 2009-10).

NA = Non-agricultural sector

AE = employment in agricultural sector

NAE = employment in non-agricultural sector

[FIGURE 4 OMITTED]

Table 6 is for the structural transformation of employment which can be estimated for both the categories; first, for agriculture to nonagricultural sector, and second from informal to formal sector. The specification for the latter is as in the following:

[STR.sub.UE[right arrow]OE] = [alpha] + [[beta].sub.1], (UP) + [[beta].sub.2] [(LP).sub.Org] + [[beta].sub.3][(GCF).sub.Org] + [[beta].sub.4][(K/L).sub.Org] + [[beta].sub.5](HC) + [[beta].sub.6]([L.sub.91]) (7)

Where,

STRUE-OE = Structural Transformation; i.e., the share of organized sector employment to Total Employment.

UP = Urbanization; i.e., the share of urban population to total population

LP = share of labor productivity in the organized sector

GCF = share of gross capital formation in the organized sector

K/L = share of capital-labor ratio in the organized sector

HC = Human capital; i.e., the literacy rate

[L.sub.91] = liberalization dummy i.e. 0 for before 1991 i.e. 1972-73 to 1990-91 and 1 for after 1991

i.e. 1991-92 to 2009-10

We expect the following to exert their influence on the rate of structural transformation: On the positive side, aggregate non-sector's income, gross capital formation in non-agriculture, rural-urban wage differential, urban employment creation, human capital and liberalization dummy. On the negative side, the share of urban population, and the capital-labor ratio..

For the period 1972-73 to 2009-10, the data required for estimation of the above model are collected from various sources. First, data about output, gross capital formation and net fixed capital stock at 1999-00 prices are collected from National Account Statistics, Central Statistical Office, Government of India. Second, population and employment data are compiled from various periodic estimates of NSSO (10) and Census data. Because there is no continuous data set available for employment in India, the present study makes an interpolation to construct a time series of data on employment. For organized sector employment, data is taken from the Employment Market Information (EMI) series of the Director General of Employment and Training publishing in the Annual Employment Reviews. Employment for the unorganized sector is obtained by the residual method by subtracting organized sector employment from the total employment. Third, wage data are compiled initially from the rural labor enquiry and latter merged with the quinquennial employment and unemployment surveys conducted by the NSSO (11). Is the NSS something different from the NSSO? Fourth, literacy data is collected through various sources such as Census data, selected education statistics and the NSSO report on the literacy rate. Beside NAS and NSSO, extensive use has been made of other relevant secondary sources like the Handbook of Statistics on Indian Economy published by the Reserve Bank of India (RBI), Agricultural Statistics published by the Ministry of Agriculture and various official reports. Some of the mid-year values of certain variables have been calculated by an interpolation method to fill the data set for making it into a time series framework (12). In order to examine the above model specification equation, simple Ordinary Least Square (OLS) technique is employed.

3.1. Empirical Results

The estimation results for agricultural to non-agricultural employment transformation and unorganized sector to organized sector employment transformation are presented in tables 8 and 9. The predicted and actual employment transformations for both the segments are plotted in Figures 4-A and B respectively.

3.1.1. Employment Transformation from Agriculture to Non-agricultural Sector

Let's first look at the estimation of quantitative employment transformation from agriculture to the non-agricultural sector which is presented in Table 8. It has a reasonable goodness fit with an explanatory power of 0.77. The estimated coefficients of all the variables are found to be significant and have expected signs. Estimated results corroborate the view that the transformation from agriculture to non-agricultural employment has been positively influenced by non-agricultural income, non-agricultural investment, the non-agricultural informal sector work force, the rural-urban real wage differential. Human capital and variables like urban population and the non-agricultural capital-labor ratio have negatively influenced the transformation in the economy. From the result, we found that, first, the share of the non-agricultural informal sector work force has the highest coefficient value, suggesting a one unit increase in the share of the non-agricultural informal sector work force will lead to a 0.641 unit increase in the share of the employment transformation rate from agriculture to the non-agricultural sector. Second, human capital has the second highest coefficient value of 0.047. Third, a one percent increase in the share of non-agricultural income leads to 0.042 unit increases in employment transformation in the economy. Fourth, the investment that determines the employment transformation by the Lewisian model suggests only a 0.027 unit increase by each unit share of investment. Fifth, the wage differential that determines the rural-urban migration by the Harris-Todaro model suggests a positive impact to the employment transformation from rural agriculture to the urban non-agricultural sector. On the other hand, urban population and the share of capital-labor ratio in the non-agricultural sector decreases employment transformation by 0.072 and 0.032, respectively. The liberalization dummy positively affects the employment transformation in the economy, but the coefficient is very negligible. In other words, due to economic reform, employment transformation shows a positive sign but the effect has been negligible. From the above explanation, it can be observed that employment growth in the informal sector, on the one hand, and growth in the non-agricultural sector income, on the other, has influenced the employment transformation from the agricultural sector to the non-agricultural sector.

3.1.2. Employment Transformation from Unorganized Sector to Organized Sector

Now we move to estimating the determinants of structural transformation from the informal to the formal sector. The results of the estimation are presented in Table 9. The estimations indicate satisfactory goodness of fit with an R-square of 0.75. We know that the rate of transformation of this type is negative and we are interested to see the determinants. According to the estimation, the employment transformation from the unorganized to the organized sector is positively influenced by investment and human capital and negatively influenced by labor productivity, urban population and capital-labor ratio. This suggests that first, human capital has the highest and positive coefficient of 0.007 unit share. Second, capital formation has the coefficient of 0.001, suggesting a share of organized sector employment increases for each one percent rise in share of investment. On the other hand, with the increase in urban population, the quality of employment transformation has declined by 0.024 unit share. Employment has a negative coefficient share with respect to labor productivity and capital-labor ratio in the organized sector at 0.008 and 0.002 unit of share respectively. The overall result suggests that it is the human capital and investment in the organized sector that has some deterministic influence on the quality of employment transformation in the economy.

4. Conclusion

To summarize, we observe that the structural occupational transformation process in India seemed to have begun after the reforms period. But the transformation is led by a growth of service-sector employment, and is not industry-led. It has been observed that the process has slowed during 1993-04 but picked up again at a much faster pace. If the present trends continue, the number of workers who are dependent upon agriculture might decline substantially in the coming two decades.

However, there are certain anomalies in this transformation. The structural transformation is significant only vis-a-vis agriculture and the unorganized non-agricultural sectors. There is a negative movement towards the organized sector. Hence, the so-called modern sector's employment is not substantially better than that of the traditional, except for a marginal improvement. A quite disturbing aspect is that we foresee a growth of a mammoth unorganized employment for the future located more in services and less in industry, with substantial self-employment.

The structural transformation of employment is not just about a change from agriculture to the non-agricultural sector work, but is about shifting from low-productivity/low-wage to high-productivity/high-wage work (with reasonable social security). Leaving farming for rickshaw pulling or street vending in urban areas, is hardly favorable structural transformation.

Our econometric estimation suggested that this transformation is positively influenced by factors such as a growing share of nonagricultural income, non-agricultural investment, rural-urban real wage differential and human capital. The two major factors that are slowing down this process are the growing (urban) population and the capital-labor ratio. The substantive employment transformation--i.e., from the unorganized to the organized sector--is positively influenced by investment and human capital and negatively influenced by labor productivity, urban population and capital-labor ratio in the organized sector.

This implies that new employment opportunities are likely to occur in the unorganized sector, bringing with them poor working conditions without any social security. Even within the organized sector, an increasing number of workers are being employed in a 'flexible' manner on a casual or contract basis, without social security benefits available to regular workers. Thus, quality jobs, in terms of earnings and social security, may become increasingly scarce, and the share of unprotected workers will increase. The challenge of poverty and unemployment would only worsen. Provision of minimum social protection to this large mass of workers is, therefore, likely to emerge as a much greater challenge.

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Deepak Kumar Behera *

National Institute of Technology, Patna

* Assistant Professor, Department of Humanities and Social Sciences, National Institute of T echnology Patna, An Institute under MHRD, Govt. of India, Ashok Rajpath, Patna, Bihar- 800 005, E-mail: dkbehera1982@gmail.com

(1) The balance of payments crisis of 1991 has compelled the Indian State to approach the IMF, which has induced India to take a Structural Adjustment Loan. Internal political instability, a Balance of Payment (BoP) crisis and several interest groups in bureaucracy, media and industry have all eventually led to introduce economic reforms in India in 1991. In order to know the significance of the reform, the whole year is divided into two parts. One is the pre-reform period, which is considered to be before 1991, and the other is the post-reform phase that is considered to be 1991 onwards.

(2) The fact that the earnings level in the tertiary sector (i.e. services sector) has been significantly above that in manufacturing, suggests that growth in the services sector has been productivity-led rather than employment-led (Mazumdar and Sarkar, 2009).

(3) Formal sector is nothing but the organized sector that defines the enterprises or places of work as registered by the government and that have to follow its rules and regulations which are given in various laws such as factories act, minimum wage act etc. The Informal sector, i.e. the unorganized sector, is where the enterprise is not registered by the government and does not follow any rules and regulations--such as no job security, no other benefits to employees.

(4) The classical notions of structural transformation implicitly assume it as transformation from a traditional to modern, where the latter is a formal sector. However, if the labor transition is happening from the informal agricultural to the informal modern sector, then qualitatively this transformation is different. To capture the qualitative dimension, we estimate the transformation from the informal to the formal sector.

(5) If population growth is due to the high fertility rate or to an age distribution that is heavily concentrated in the child-bearing years, the growth in any year will have its impact focused at age 0 of the age distribution. Thus, it will take at least 10 to 15 years before the effects of a particular year's population growth even begin to be felt in the labor force. On the other hand, if population growth is mainly the result of substantial in-migration, its principal effect on the labor supply will not be lagged, since the propensity to migrate tends to be relatively low before the teenage years. Population growth resulting from an excess of births over deaths in rural portions of an economy may create pressures for migration to urban areas. If so, the migrants tend to be of working age, and population growth in the urban areas will have an immediate effect on labor force growth.

(6) Fertility changes may have an effect on the labor force. For example, in some high-fertility populations, it is rare for women to work away from the home. By contrast, in other high-fertility populations women are able to spend a great deal of time working outside the home by having older children take care of their young children. On the other hand, women have relatively more freedom to work, at least for a greater portion of their lives, in low-fertility populations. Thus, a decline in fertility may have an immediate impact on the size of the labor force because of its effect on the participation rates of women. Mortality changes may also have an effect on the labor force. In this case, the effect does not operate entirely through the impact of mortality decline on age-specific participation rates; rather, it also operates through the positive impact of declining morbidity on the quality and productivity of the labor force. In such case, individuals perceive a decline in mortality as extending their work life horizons; it may also provide greater incentives for human capital investments. While such investments will contribute to the overall quality of the labor force, they will also tend to delay the entry of individuals into the labor force and therefore reduce aggregate participation rates. [Bloom and Freeman, 1986]

(7) In order to reduce poverty so as to control the population pressure, Sanjay Gandhi believed that India's problem of poverty could be solved by corrective sterilization of the poor. The resulting civil resistance provoked by mass sterilization camps and by the emergency declared by his mother, Prime Minister Indira Gandhi, in the mid 1970s led to the virtual abandonment of 'forced' family planning programs in India. See Lal, Deepak (2006).

(8) Such a decline in population growth is well supported by the introduction of varied socio- and economic planning in the country, such as: to increase the mean age at marriage and to lower the age-specific marital fertility rate by spreading contraceptive practices; providing specific incentives for a female child; provision of free education for a single child, etc. With the continuing decline in the death rate due to better health and more access to medical services, life expectancy has been increasing. Particularly, female life expectancy has been rising, with an increase in the sex ratio. The historical sex bias towards male children has been declining.

(9) Technology, which is assumed to be neutral in the Lewisian model, has a greater role to play for the development of the modern sector. As we know that the capital-labor ratio is associated with a unique saving ratio and a unique capital-output ratio and hence with a unique rate of output growth, then an increase in the capital-labor ratio will increase the output growth at a much faster rate with the increase in the saving ratio. But on the other hand, with the introduction of more and efficient capital, there will be more substitution of capital for labor

(10) National Sample Survey Office (NSSO) is an organization under the Ministry of Statistics of the Government of India. It is the largest organization in India conducting regular socio-economic surveys. In each five year period, it conducts a quinquennial survey on the employment and unemployment situations in India.

(11) Initial rural labor enquiries were conducted by the Ministry of Labor. The first two enquiries were called agricultural labor enquiries because wages and earnings of only agricultural labor households were canvassed. However, beginning in 1963-64, the enquiry was extended to include rural labor households, becoming called rural labor enquiries. Since 1977-78, the responsibility of canvassing the wage schedule was handed over to NSSO and the rural labor enquiries were merged with the quinquennial employment and unemployment surveys.

(12) A similar exercise has also been made by Pattanik and Nayak (2011). Table 1. Percentage Share of Employment and Income in Agriculture and Nonagricultural Sector Year Employment Non-agriculture Agriculture Industry Services Total 1972-73 74.58 06.75 18.67 25.42 1983 68.51 13.83 17.67 31.49 1987-88 64.97 15.93 19.10 35.03 1993-94 63.84 15.01 21.16 36.16 1999-00 60.27 16.22 23.50 39.73 2004-05 56.50 18.70 24.79 43.50 2009-10 51.76 21.93 26.30 48.23 Year Income Non-agriculture Shift in Agriculture Industry Services Total Laborforce away from Agriculture 1972-73 41.01 23.34 35.65 58.99 1983 6.07 36.24 24.15 39.61 63.76 1987-88 31.72 25.23 43.05 68.28 1993-94 4.67 30.01 25.15 44.84 69.99 1999-00 24.99 25.31 49.69 75.01 2004-05 8.23 20.22 26.23 53.55 79.78 2009-10 4.73 * 14.5 28.1 57.4 85.5 Source: computed from various rounds of NSS reports and various issues of NAS. * for 5-year period Table 2. Percentage Share of Employment by Status to Total Employment Category Self Employed Agriculture Non-agriculture 1993-94 38.90 15.75 1999-00 35.70 17.22 2004-05 37.62 19.52 2009-10 31.97 19.18 Category Casual Labor Agriculture Non-agriculture 1993-94 25.06 6.92 1999-00 25.32 7.59 2004-05 20.24 8.33 2009-10 21.48 11.76 Category Regular Wage Salaried Agriculture Non-agriculture 1993-94 0.95 12.41 1999-00 1.01 13.16 2004-05 0.71 13.57 2009-10 0.51 15.09 Source: computed from various rounds of NSSO report. Table 3. Percentage Share of Employment in Non-Agricultural Sector Sector Organized Sector 1983 1993-94 2004-05 2009-10 Mining & Quarrying 54.96 41.65 42.88 45.91 Manufacturing 19.41 16.04 10.06 11.93 Electricity, 89.9 70.38 75.15 63.86 Gas and Water Constmction 17.48 10.03 3.69 2.15 Trade, Hotel & 2.05 1.62 1.13 1.32 Restaurant Transport, Storage 38.32 29.16 15.27 13.20 and Communication Finance, Insurance, 50.72 42.51 24.83 29.00 Real Estate and Business Services Community, Social 36.92 30.49 29.44 28.84 and Personal Services Total 23.80 19.16 12.54 12.15 Non-Agriculture Total Sector 7.93 7.31 5.78 6.16 Sector Un-Organized Sector 1983 1993-94 2004-05 2009-10 Mining & Quarrying 45.04 58.35 57.12 54.09 Manufacturing 80.59 83.96 89.94 88.07 Electricity, 10.1 29.62 24.85 36.14 Gas and Water Constmction 82.52 89.97 96.31 97.85 Trade, Hotel & 97.95 98.38 98.87 98.68 Restaurant Transport, Storage 61.68 70.84 84.73 86.80 and Communication Finance, Insurance, 49.28 57.49 75.17 71.00 Real Estate and Business Services Community, Social 63.08 69.51 70.56 71.16 and Personal Services Total 76.20 80.84 87.46 87.85 Non-Agriculture Total Sector 92.07 92.69 94.22 93.84 Source: Organized Sector Employment data are computed from Ministry of Labor & Employment, Director General of Employment Training (DGET); Unorganized sector employment is computed through residual approach Table 4. Size and Distribution of Organized and Unorganized Sector Workers by Industry and Status during 2004-05 (%) Agriculture Org Un-org Total SE 38.1 64.8 64.2 RW 20.1 0.6 1.1 CL 41.8 34.6 34.7 TOTAL 100 100 100 % to Total 2.4 97.6 100 N on-Agriculture Org Un-org Total SE 5.1 62.8 46.4 RW 74.3 17.4 33.6 CL 20.7 19.8 20 TOTAL 100 100 100 % to Total 28.4 71.6 100 All Org Un-org Total SE 8.3 64.1 56.5 RW 69 6.7 15.2 CL 22.7 29.2 28.3 TOTAL 100 100 100 % to Total 5.8 94.2 100 Source: National Commission for Enterprises in the Unorganized Sector, 2007 Table 5. Rate of Structural Transformation in India Sector 1973-74 to 1991-92 to 1973-74 to 1990-91 2009-10 2009-10 Output Transformation Rate Agricultural output to 0.560 0.863 0.708 Total Non-agricultural output Employment Transformation Rate Agricultural work moving 0.570 0.586 0.578 to Non-agricultural work Agricultural work moving 0.598 0.705 0.65 to Unorganized Non-agricultural Work Agricultural work moving -0.023 -0.108 -0.064 to Organized Non-agricultural Work Total Unorganized Sector -0.026 -0.114 -0.069 Work moving to Organized work Source: computed Table 6. Demographic Trends in India, 1951-2011 Year Population Birth Rate Death Rate Net-Migration Growth 1951 1.25 40.9 22.8 1961 1.96 40.0 17.6 1971 2.22 37.8 15.4 1981 2.20 34 13 1991 2.14 30 10 2001 1.95 26 9 -0.08 2011 1.62 22.5 * 7.3 * -0.05 * Life Expectancy Year Infant Mortality Female Male Rate 1951 146 31.7 32.4 1961 129 40.6 41.9 1971 110 44.7 46.4 1981 92 54.7 54.1 1991 75 60.9 59.7 2001 70 61.8 60.4 2011 30 * 72.6 * 67.5 * Note: Birth Rate: the average annual number of births during a year per 1,000 persons in the population; Death Rate: the average annual number of deaths during a year per 1,000 persons in the population; Infant Mortality Rate: the number of deaths of infants under one year old in a given year per 1,000 live births in the same year; Net-Migration: is the difference of immigrants and emigrants of an area in a a period of time, divided (usually) per 1,000 inhabitants (considered on midterm population). A positive value represents more people entering the country than leaving it, while a negative value means more people leaving than entering it; Life expectancy: the number of years that an individual is expected to live. * year 2009 data. Source: Lai (2006) and SRS (2011), Census of India. Table 7. Growth Rate of GDP, Employment, Labor Productivity and Capital-Labor Ratio (at 1999-00) Year 1983-93 Agriculture Non-Agriculture GDP 3.76 5.78 Employment 1.47 3.62 Labor Productivity 2.29 2.16 Capital-Labor Ratio 0.78 4.67 Real Wages * Casual 2.78 4.19 Regular 5.38 0.56 Year 1993-09 Agriculture Non-Agriculture GDP 2.77 8.24 Employment -0.04 3.12 Labor Productivity 2.73 5.12 Capital-Labor Ratio 3.62 5.55 Real Wages * Casual 1.31 0.76 Regular 5.01 0.21 Note: * for 1993-99 and 1999-04 Source: computed from various rounds of NSS reports and issues of NAS. Table 8. Effects of Employment transformation from Agriculture to Non-agricultural sector in India Dependent Variable: STR Independent Variable Name Coefficient 't' statistics Constant 0.183 * 5.86 UP -0.072 * -2.16 [Y.sub.NA] 0.042 * 2.54 [GCF.sub.NA] 0.027 * 4.44 K/[L.sub.NA] -0.032 * -5.41 [UE.sub.NA] 0.641 * 19.69 RW 0.001 * 2.40 HC 0.047 * 2.04 [L.sub.1991] 0.0001 * 1.96 [R.sup.2] 0.77 Durbin-Watson (DW) Test 1.65 Prob (F-Statistics) 0.000 Number of Observations 38 Note: * at 5% significant level Table 9. Effects of Employment transformation from Informal to Formal sector in India Dependent Variable: STR Independent Variable Name Coefficient 't' statistics Constant 0.095 * 13.37 UP -0.024 * -6.47 LP -0.008 * -3.46 GCF 0.001 * 2.13 K/L -0.002 * -2.63 HC 0.007 * 2.96 [L.sub.1991] -0.002 * -2.62 [R.sup.2] 0.75 Durbin-Watson (DW) Test 1.64 Prob (F-Statistics) 0.000 Number of Observation 38 Note: * at 5% significant level Figure. 2. Income and Employment Share of Rural Economy in India Agriculture Non-Agriculture Income Employment Income Employment 1993-94 56.99 78.39 43.01 21.61 1999-00 51.42 67.77 48.58 32.23 2004-05 38.34 73.96 61.66 26.04 Note: Income is Net Domestic Product at current price Source: Estimated by taking data from NAS and NSS