To improve competitive edge, Indonesia needs better jobs

The country needs to focus on improving education and skills training to improve job quality and quantity.

Indonesia’s long-standing employment objective is to provide enough more productive jobs to exhaust the still large supply of low-wage workers, mainly in agriculture and the informal sector.

The country’s new goal is to prepare the workforce for quantum changes to the quality and nature of jobs brought by “Industry 4.0” or the Fourth Industrial Revolution, including automation and data exchange in manufacturing technologies as well as digitalization.

Not only does Indonesia need to create a more skilled workforce, it must also adjust to new global patterns of digital technology and the related demand for skills.

These challenges are by no means simple. But drawing on lessons learned from the 1997-1998 Asian financial crisis, there is a growing consensus among policy makers that better jobs and greater productivity are fundamental for sustaining rapid and more inclusive growth.

Enhanced productivity is thus essential to maintaining Indonesia’s competitiveness.

Improving the quality of jobs is critical not only for boosting productivity, but also for improving living standards and for reducing poverty. A clear understanding of the labor market, demographic and labor force transitions, and investment in education and skills development should help create a basis for sustainable growth for the next generation.

These old and new challenges to enhance productivity are discussed in great detail in the recently published book Indonesia: Enhancing Productivity through Quality Jobs edited by Edimon Ginting, Christopher Manning, and myself. The study maintains that moving forward on selected labor market policies and issues requires a high degree of commitment among stakeholders to implement the reforms in good faith. It has three key messages.

First, the central challenge is to ensure that improved education outcomes create sufficient quality jobs to raise productivity for rapid and more inclusive development. Continual skills development can help meet the demands of the rapidly changing work environment.

Improving the education landscape entails making higher education more accessible, especially in the countryside to encourage younger workers to seek more productive employment outside agriculture.

Second, the growth of cities must be sustainable in order to enlarge and spread productivity and income gains. This is a priority for a country where half of the population already lives in urban areas.

Urbanization, however, is still not bringing enough productivity or income gains. The benefits of urbanization are overwhelmed by structural problems (congestion, stressed infrastructure, and environmental pressures) that hinder productivity gains, especially in large cities.

Lastly, Indonesia should continue to improve labor market institutions and regulations that promote both a wider range of employment options and better income security for workers throughout their lifecycle. Such policies should result in enhanced welfare and productivity.

Our study highlights opportunities created by the demographic dividend and some positive signs regarding female engagement in the workforce. However, the main challenge in the labor market is a large backlog of lower productivity labor in agriculture and in the informal sector.

Given the labor-saving effects of modern technology, the country’s economy needs to create a more diversified services sector—including for instance financial and business services—to absorb the labor surplus.

In tandem with the labor migration from agriculture, Indonesia has urbanized rapidly. Urban districts tend to attract a high share of low-productivity services.

Education and training for skills in demand are both key for sustaining productivity growth. Beyond quantity, the country needs to focus on the quality of education and the relevance of skills training like digital literacy.

This blog post is part of a series by the Asian Development Bank and Thinking Machines Data Science, Inc.