Wage-differentials in India's construction industry.

AuthorChheda, Kadambari
PositionReport - Statistical data

Workers in India's construction industry are extremely diverse in nature, ranging from large number of unskilled workers to highly skilled engineers and technicians. The present study employs the panel regression technique to test the extended version of Mincerian wage equation for six different groups of construction workers. The results showed that work-experience is the most significant factor that influences the wages of India's construction workers whereas general education (years of schooling) is insignificant unlike other industries (where general education plays a crucial role in increasing the wage-rates). Also, depending on the nature of work, location, sector etc., technical education and formal vocation education play an important role in influencing the wages of the construction workers.

Introduction

In developing economies, wages are influenced by strict labor market dualism and strong entry barriers amongst different segments of the labor markets (Heckman & Hotz, 1986). In India, dualism in the labor market has caused major variations in the wages and incomes of the workers (Sen, 1998). Several times it has been observed that workers performing similar type of work are paid differently in the country (Das, 2012). There are a few studies (Das, 2012; Krishna & Paul, 2012; Sengupta & Das, 2014) that have attempted to examine the causes of wage differentials amongst various group of workers at aggregate level. However, none of these studies inspected wage differentials distinctively for any specific industry. The present paper attempts to contribute to the existing literature, by examining wage differentials amongst the workers in construction industry in India.

Construction industry was particularly chosen for the present study because the workers who are engaged in this industry are extremely diverse in nature, ranging from large number of unskilled workers to highly skilled engineers and technicians. Wages form a major portion of income for a majority of the construction workers. According to 12th Five Year Plan Report on Construction Industry, amongst the entire construction workforce, 2.5% were skilled engineers, 2.75% were technicians and foremen, 2.26% were clerical staff, 9.1% were skilled workers and 83.3% were unskilled workers in 2012. This clearly indicates that labor-market of the construction industry is significantly segmented. Hence, there is a probability of existence of high wage differentials in this industry.

A flexible method to check wage differentials among different groups of workers is through the human capital theory (Becker, 1964; Mincer, 1958; 1974) according to which the rise in accumulation of human capital (i.e. education, skills and work-experience), leads to rise in the productivity and earnings of the workers. The present study employs the panel regression technique to test the extended version of Mincer (1974) wage equation, popularly known as "human capital earnings function", for the construction workers in India. The primary data source of the study is the National Sample Surveys (NSS) quinquennial unit-level data, which is one of the most exhaustive and extensive employment data for India. Most of the labor studies in India use this data as it consists of extensive data on different set of workers employed. It covers vast details of household characteristics, personal details, working details and wages of the workers in India. The present study uses the two rounds of NSS, i.e. 61st quinquennial (2004-05) and 68th quinquennial (2011-12).

We use panel-data set to empirically investigate the relationship between wages and 'human capital' variables (work-experience, education, technical education and vocation training), for six different groups of construction workers in India, separately. The six different groups are: (1) formal construction workers, (2) informal construction workers, (3) rural construction workers, (4) urban construction workers, (5) male construction workersand (6) female workers. The motive for separating workers into different groups, is to observe the fluctuations in each group individually, caused due to 'human capital' variables. This will contribute to understand precisely the influence of 'skill' variables (technical education and vocation training), in addition to 'education' and 'work-experience', on the wages of the construction workers in India.

Human Capital Theory

A persistent debate amongst various scholars, policy-makers and academia is "what determines wages" (Groshen, 1990). A relevant question in this debate inquires about why there is diversity in wage payments to various workers (Mortensen, 2003). According to Krishna and Paul (2012), wage disparities in the Indian labor market can be attributed to mainly two reasons: first, they are employed in different economic activities; and the second, due to different skill-sets and education-levels (workers are heterogeneous in nature). Therefore, skills and education play a crucial role in the labor market not only for entering the labor market but also for explaining the variations in wages. Sengupta and Das (2014) showed that wage differences amongst workers could be explained by dividing the wage determining factors into two parts: (i) "observed" part (defined by variations in education, skill, work experience and social factors) and (ii) "unobserved" part (explained by the unknown factors). One of the significant methods to examine the "observed" part is the human capital theory. Human capital theory is an important theory of labour economics that studies impact of different "human-capital" variables (such as work-experience, education and training variables) on the wage-rates.

The foundation of human capital is from the time of classical economics (1776), which eventually developed into a scientific theory (Fitzsimons, 1999). Human capital generates positive spillovers in the economy (Acemoglu & Angrist, 2000). According to Romer (1990), it is 'a fundamental source of economic productivity'. Rosen (1999) denotes human capital as 'an investment that people make in themselves to increase their productivity'. Schultz (1961) was of view that accumulation of a person's human capital will largely affect his/her wage, firm's productivity and eventually national economy. Within the wide scope of demand and supply, several prominent economists like Schultz (1961), Becker (1962) and Mincer (1974) have stressed that market wage is a function of education, skills and experience acquired through years of schooling and training. They referred these variables as "human capital" variables which assist in explaining significant part of the variation in wages of the workers.

The early studies by Mincer (1958, 1974) and Becker (1964) were significant contributions to the human capital theory. The work by Mincer (1958) showed that training and skills positively influenced the incomes of workers. According to him, the variable 'training' could be divided into two sections: (a) formal training (years of schooling) and (b) informal training- work experience. In this model, he substituted worker's age for his/her work experience. According to Polacheck (2007), Mincer treated schooling and training as a part of investment on a worker; a worker likes to invest up to a limit where investment cost equals the present value of gains from it. The equation also directed that worker's wages increases consistently over a period at a decreasing rate yielding a concave earnings outline for most of the workers. The study by Lemieux (2003) has pointed out two reasons for Mincerian equation to be popular and a significant contribution to labor economics. They are: first it was an initial formal model which discussed investment in human capital; second, it provided the foundation for estimating causal effect of education on earnings, which was a crucial contribution.

Becker (1964) further worked on human capital model and showed the importance and effects of "on-the-job training." He described the distinction between: "firm specific" training and "general" training (Chiswick, 2003). "Firm specific" training refers to the skills developed by specific education, whereas "general" training refers to knowledge acquired through education and which can be useful in any work (i.e. reading, writing). According to Fugaret.al (2013), Becker's opinion on human capital was comparable to "physical means of production". That is, if one invests in human capital then their output would depend partially on the human capital's rate of return. This concludes that additional investment in the human capital would lead to addition to the total output. Several...

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