Challenge of Job Creation

At all India level, about 77% of the households are reported to be having no regular wage/salaried person (Fifth Annual Survey 2015-16). Unemployment rate is estimated to be 5% at all India level in 2015-16 under the USP (Usual Principal Status) approach which was 4.9% in 2013-14, 4.7% in 2012-13, 3.8% in 2011-12, and 9.3% in 2009-10 (no report provided by Labour Bureau for year 2014-15). Unsurprisingly unemployment rate is significantly higher among women (8.7%) as compared to men (4.0%). It simply means that unemployment rate is more than double for women in India than men. Manufacturing alone won’t create many direct jobs in short run despite various initiative including "Make In India" and Foreign Trade Policy - 2015 because of poor physical and social infrastructure. The primary growth in jobs will come from the service sector. Even when reforms happen in agriculture, most of the jobs will be created in areas that will show up in national income accounts as services such as transportation, logistics.

One of the major structural issuesis, many persons who are reported as employed or workers in official publications do not get work for the entire duration of their stay in the labour force(Fifth Annual Survey 2015-16). And even those who get some work for the entire duration may be getting work for only a small fraction of the time they are available for work. This apart, some may be working on jobs which do not allow them to fully utilise their abilities and thus are under paid. All this constitutes underemployment which remains a worrying aspect of the employment - unemployment scenario in the country. 

Thus, creating job is India's central challenge (Economic Survey 2016-17). Critical elements of this policy response are;

1. Generating rapid economic growth

2. Nurturing an enabling environment for investment

3. Targeted action in certain labour intensive sectors.

There is another challenge of employment generation which has been largely neglected in India and that is rising voluntary unemployment. Data compiled by the Centre for Monitoring Indian Economy (CMIE survey) based on household survey with a reasonably decent sample size reveals that voluntary unemployment has gone up dramatically. While incomes are going up, women are voluntarily opting out of employment. Further, people are unwilling to settle for jobs, particularly after having ‘invested’ in education, that do not give them a salary above a particular level. This is evident from the high unemployment rate in Kerala (12.5%) which has been listed on top rank in human development (India HDR, 2011) with highest literary rate calculated at 93.91% (Census, 2011). On the contrary, Bihar with lower human development has unemployment rate of only 6%, though literacy rate of Bihar is the lowest in India calculated at 63.8% only.

It is argued that Labour Force Participation Rates (LFPRs) in Kerala are reduced by high levels of unemployment through a 'discouraged worker effect,' especially for females, forcing them into economic inactivity or into marginal work or the type of work which escapes census enumeration (Eapen, 1992). Isaac (2000) argues that unemployment rate among young women is high. Even after long waiting periods, majority of young women remain unemployed. Hence, they cease to be job seekersand confine themselves to their houses and thus are classified under‘out of the labourforce’categoryby official surveys.

Lack of employment opportunities that match the educational achievements of an employment seeker is the second important reason noted for low work participation rates. A large proportion of unemployed persons in Kerala is educated, due to the spread of education across classes and castes (Census, 2011).  The most important effect of the spread of education on the labour market is the transformation of job expectations of the educated job seekers. The spread of education in Kerala has created a definite preference for jobs in the formal service sector (Mukherjee and Isaac, 1991).  The limited number of jobs available in the formal sector led to a fall in Work Participate on Rates (WPRs), especially for women.

Unwillingness to Work : Myth or Reality

Voluntary unemployment occurs when the person decides not to participate in the labour market, not because of the unavailability of jobs, but because of not finding the jobs of her/his choice or is not satisfied with the wage system (Peterson, 1986).While the insufficient job creation could lead to resentment due to people’s high aspirations, there is a dramatic rise in voluntary unemployment across the country, where people choose not to work below a certain income level after ‘investing’ in education.

The voluntary unemployment also surfaces when, the worker is neither willing to work nor searches for a job, as she is satisfied with the amount given by the government in the form of unemployment benefits, subsidies etc. High-income tax rates could also be one of the reasons behind a worker not choosing to work.As the country gets richer and people get more educated, many of its citizens are found choosing to stay away from the job market, further exacerbating unemployment numbers.

Typically, a high rate of unemployment discourages people who search for jobs through a rise in the job search costs. High job search costs eventually push people out of the 'labour force' as they stop looking for jobs. This phenomenon is referred as ‘discouraged worker effect’ which is being defined as a situation where people who want a job, and are currently available for work, give up active job search because they believe they cannot find a job.

Another reason for voulntary unemployment may be the information asymmetry specially among the first-time job seekers, who might not have sufficient information about the nature of a job and decide to remain unemployed until the time they get the desired opportunity. Frictional unemployment is also a form of voluntary unemployment wherein the worker deliberately leaves her job in the search for better job pursuits. Business Correspondence Model applied in banking sector in India is one of the example of this where highest attrition rate occurs (Dwivedi, 2015).

Definition of full employment and the kinds of unemployment are key issues of the theory of employment.   The second issue of the employment theory is the interconnection between full employment, voluntary unemployment and involuntary unemployment, and their measurement. The point is whether voluntary and involuntary unemployment are mutually exclusive or can they co-exist. The economics  literature  either  ignored  the  coexistence  of  these  two  kinds  of  unemployment  or  claimed  they  were  both  the  same  (Lucas, 1978;  Pissarides, 2000). 

The kinds  of  unemployment  depend  on  the  type  of  economy under  discussion (Walras, 1954)  namely,  is  the  economy  characterized  by  free  competition,  where  the market  forces  govern  the  activities  of  economy;  or  are  there  external  forces  (government,  monopoly,  trade unions)  which  intervene  in  the  activities  of  economy and  therefore,  it  is  a  disequilibrium  phenomenon. In  the previous  case,  under  the  framework  of  assumptions, there  is  voluntary  unemployment  and  in the  latter case  there  is  forced  unemployment.  Keynes, combined  these  two types  of  unemployment  and  called  it  “voluntary”  and  introduced  an  additional  type  of unemployment  –involuntary,  which  is  also  derived  from  the  free  competition  such  as voluntary  unemployment,  but  with  different  assumptions (Keynes, 1936).

Further, the  kind  of  unemployment  depends  on  the  character  of  the original  aggregate  supply  curve  of  labour (Davar, 2012). When  the  original  aggregate supply  function  is  a  strongly  increasing  function,  as  in  Walras’s  approach,  there  might  be only  voluntary  unemployment,  and  its  magnitude  is  the  difference  between  the  available quantity  of  labour  and  the  equilibrium  point.  So,  in  such  a  case,  an  individual  is  unemployed according  to  his  own  wishes,  because  an  equilibrium  wage  defined  by  free  competition  is less  than  a  wage  which  he  requires. But,  at  the  same  time  it  is  incorrect  to  confuse  Walras’s voluntary  unemployment  with  leisure (Walras, 2005). Leisure is determined by an individual prior to his  arrival to the market, whereas the voluntary unemployment is obtained by market forces.

On the other hand, if  the  supply  curve  of  labour  is weakly  increasing,  which  means that  the  supply  function might have a  horizontal  segment.There could be involuntaryunemployment if the equilibrium point is located between boundary points of the horizontal segment. The  magnitude  of  involuntary  unemployment  is  the  difference  between  the  right boundary  point  of  the  horizontal  segment  and  an  equilibrium  point.  So,  in  such  a  case,  an individual  is  involuntary  unemployed  against  to  her  own  wishes,  because  an  equilibrium wage  defined  by  free  competition  is  equal  to  a  wage  which  she  requires.

Keynes considered three kinds of unemployment:  frictional, voluntary and involuntary (Taylor, 1987). Keynes  considered  “voluntary”  unemployment  as  being  due  to  the  refusal  or  inability of  a  unit  of  labour,  as  a  result  of  legislation  of  social  practices  or  of  combination  for collective  bargaining  or  of  slow  response  to  change  or  of  mere  human  obstinacy,  to  accept  a reward  corresponding  to  the  value  of  the  product  attributable  to  its  marginal  productivity. It  shows  that  Keynes,  combined  Walras’s  two  types  of  unemployment:  voluntary  and  forced. Moreover,  Keynes’s  definition  of  full  employment  includes  “frictional”  and “voluntary”  unemployment  (Keynes, 1936).

Policy Development Under Data Vaccume

High quality, open, transparent, and uncensored data are needed to support democratic establishments. Yet there are problems of interpretation and consistency between the different types of data (Deaton, 2010). To take an example, National Sample Surveys find less consumption than do the National Accounts Statistics, whose measures also grow more rapidly. Part of the problem lies with the surveys - as more people spend more on a wider variety of things, the total is harder to capture - but there are weaknesses on the National Accounts Statistics side too (Deaton, 2015).Dreze and Deaton (2002) found no support for sweeping claims based on Surveys that the 1990s have been a period of ‘unprecedented improvement.’ Infact, poverty decline in the 1990s proceeded more or less in line with earlier trends.

The latest employment data based on household surveys conducted by the National Sample Survey Organisation (NSSO) is available for year 2011-12. These data use to come on after five years, and thus a fresh set of data was expected sometime in 2018, as a stand-alone survey on labour and employment, independent of the quinquennial exercise. Moreover, the data compiled by the Labour Bureau from enterprises for select sectors on a quarterly basis is not amenable to find out what is really happening to labour and employment due to its sample size and faulty design. Further, the current official data on labour and employment may prove detrimental as they can be used to claim ‘jobless growth’ as well as ‘growth-less jobs’ as per the subjectivity of the observer. Apart of this, they are not able to capture the pre-dominantly informal and unorganised nature of the Indian economy. Therefore, they always reveal the half-truth and draw an imperfect picture.

The real problem with employment data is that they hide more than they reveal (Karnik, 2017). Despite indicating broad trends, these data do not provide any insight into the quality of the country’s workforce. Information on independent work and part-time jobs are excluded in current data assessment by the Labour Bureau and the National Sample Survey Office (NSSO) which currently constitute important part of labour market. Further, conclusions about aggregate national trends derived from extremely small sample sizes like “Quarterly Report on Changes in Employment in Selected Sectors” based on a sample of only 1,936 enterprises may not be accurate (McKinsey Global Institute, 2017).

The above discussion clearly shows that while the highest priority is being given to job creation considering high unemployment, policy making and analysis has been conducted in a data vacuum or under ambit of insufficient data. A task force led by the NITI Aayog vice chairman on employment data has been formed which has been given the task to come up with reliable and timely data solution for tracking employment trends, however, there is still no clarity over how the new data will be computed or how often they will be published.