For as long as one can remember the path to a better future began with a college degree. Especially in emerging markets where college graduates used to be a scarce commodity this was particularly true. In small, rapidly growing markets the scarcity premium was high. Even public sector jobs paid a substantial premium for college graduates while providing them with job security.
There was also a certain respect for college graduates over and above their economic value which today seems quaint. The disciplines of choice were medicine, law, the sciences, followed by the arts. Economics, business and commerce were subsumed under the arts and have not commanded a premium in either prestige or remuneration.
As with all human endeavors extrapolation, mistaken strategy, slow reaction times have led to a certain cyclicality in the supply of certain trades. The 3 to 4 year gestation of a college degree, (sometimes longer as in medicine for example) also exacerbate cycles as supply lags demand.
A college education has a strong element of signaling embedded in it. Often the precise content of the degree courses bear little relevance to the jobs the graduate actually obtains. Generalist degrees prepare the individual for a wide range of jobs by equipping them with a spectrum of abilities and skills. The MBA is a prime example. The MBA may be specialized with particular accents but is usually sufficiently diverse in scope to equip its bearer with generalist skills to tackle most problems. It’s value lies in its versatility; it can be thought of as an option whose value depends on the diversity of jobs it opens up to its bearer. Be that as it may, the unemployment problem is best addressed by more specifically meeting the labour demands of the economy. Wage transparency should be encouraged to signal the evolution of demand for different types of labour to encourage supply. Current wage data is noisy and suffers from agency issues. Individual’s pay is often secret. First and second moment aggregates and time series should be published to improve he dissemination of labour market information in the economy.
Broadly, finance, managerial, social sciences are oversupplied while the sciences, engineering and the professions are under supplied. Some disciplines are easier than others in terms of obtaining a degree. The hard sciences and engineering are more difficult or considered dry subjects whereas social sciences are more popular, the professions have purposefully established high barriers to entry to encourage under supply but each discipline has its own supply dynamics.
Wages are not just determined by demand and supply, individuals are rewarded based on the return they generate for their employers. Employees are paid depending on their marginal product as well. Certain industries command more assets per person and thus are able and willing to pay higher wages. The highly leveraged financial industry is one such industry that tests the limits. Service industries, and intellectual property based industries also exhibit this capital efficient feature that leverages assets per employee. Consultants offer another good example.
The mismatch between supply and demand of jobs leads to increasing inequality of compensation. Under-supplied labour markets face rising wages and remuneration while oversupplied sectors see unemployment and wage stagnation. Income inequality is not sustainable over the long run. Apart from building social pressures, a rich poor divide encourages Socialist progressive and redistributive tax policies. Governments are vulnerable to such populist policies at a time when they struggle for legitimacy and a balanced budget. This will delay enlightenment in tax policy and keep marginal tax rates high while tax revenues languish and economic growth stagnates.
A more promising goal must be to provide as much information as possible about the demand for jobs in order to facilitate their matching and to encourage effort and enterprise through friendlier tax regimes. In addition to helping allocate resources to training, try content of each course should be made more practical. Purists may argue against this but ultimately the labour market will decide. A theoretical foundation without practical delivery is a waste. Application without fundamental basis is incomplete and risky. While the purists have defended learning for learning’s sake it is expected that pragmatism will prevail. Underfunded universities dependent on government subsidies will eventually be swayed towards a more utilitarian curriculum. Time will tell if this is efficient.
Dynamic systems involving human behavior are invariably cyclical as a result of delays in signal interpretation, reaction times, gestation periods and extrapolation. The soft disciplines such as he arts and social sciences will likely see a contraction in supply while engineering, the hard sciences, and professions will likely see an adjustment upwards in supply. Between science and engineering, immediate demand favours engineering while longer term demand requires scientists. Short term-ism may prevail as corporate management and government tenures favour shorter horizon investments.
A further factor in employment is risk. 30 years of stability, Great Moderation, low volatility and risk mitigation has led to individuals being more willing to accept greater career risk in return for higher reward. The financial crisis of 2008 was a turning point. In the immediate aftermath of the crisis and recession individuals clearly struggled to reconcile risk and reward, many seeking the rewards available in the past but refusing to accept the risks associated with the new landscape. Individuals are already adjusting their preferences and many now seek stability over reward.
Western governments with unsustainable fiscal cash flow characteristics are trying to limit the growth of public sector jobs. In the Emerging Markets which were able to navigate the crisis, healthier balance sheets and cash flow may afford latitude in increasing public sector employment. In any case the demand for public sector employment will likely outstrip supply at least on a relative basis across the globe.
How is the global economy evolving in terms of demand for talent? What are the relevant skills for the next few decades?
How should and how will education respond and evolve to address the needs of the economy going forward?
What are the implications of the evolving nature of labour demand, supply and production on innovation, risk and growth?
These questions will not be answered quickly. The answers will be revealed over multiple years.
There are other factors as well such as automation and robotics where machines may replace or compete with humans in filling certain functions. Repetitive, hazardous, unrewarding tasks will likely find some sort of automated solution. Yet it is not clear how efficient robots will be at replacing humans in a given job. Humans will have a monopoly over certain types of jobs which require that hard to define ‘human touch.’ Even this criterion is a moving target as the abilities of robots adapt and evolve. What is also interesting is to understand the economics of a world where robots are a viable competitor for most if not every job. As robots perform more and more functions, will this create more unemployment? Who owns the robots? Is a more utilitarian economy one that lends itself better to automation and is thus more vulnerable to having machines replace humans? It is well to argue that automation may create more new jobs but it is more reassuring to those about to be replaced if they knew what those jobs might be so they could prepare to fill them. In the limit, if every job was done by a machine, then who owns the machines becomes a very important question. Also, how do people who have no work and do not own machines generate income?