Unemployment is simple enough to understand: it is an economic condition in which individuals seeking jobs remain un-hired. Yet measuring how many people are unemployed at any given moment in any given country is rather complex.

Author: Luca Ventura
Project Coordinator: B Pham

 

Experts agree: high unemployment rates threaten growth and social cohesion. What they don't agree on is what unemployment is. While the jobless rate represents the percentage share of the labor force out of work, there are, in fact, multiple ways to calculate it. Measuring unemployment within a country and comparing international rates is a very complicated affair.

The math is clear: the unemployment rate is calculated by dividing the number of unemployed individuals by all individuals in the labor force. The problem starts when it comes to figuring out exactly how many these people are. It is not just a matter of timely collecting massive amounts of data or about conflicting methods: the very same individuals in question often cannot tell whether they should consider themselves employed or unemployed. 

For example: a person who loses a well-compensated full-time job and settles for a part-time position that pays a fraction is by default classified as “employed”, while another person who actively seeks work but takes a few weeks off from the search not only may be no longer considered unemployed, but not even counted as part of the labor force. An individual who would like to work but is unable due to a disability or medical condition is in the very same position. 

The result is that many economists believe that—because of the existence of persons who are unemployed or hidden underemployed—statistics are inherently skewed and paint a too-rosy picture of the work force. Needless to say, unemployment and hidden underemployed too are very difficult to measure. 

Tracking the labor market is a very complicated affair when different tracking tools tell different stories. Whether through census-type methods, employment office records, surveys of a sample of the population or multi-approach techniques, their conclusions will only offer an approximate reflection of the economic and social health of a country.

Nevertheless, over time, unemployment rates remain a crucial indicator of the stability, level of development and growth trajectory of an economy. 

Rising unemployment results in loss of income for individuals and reduced collection of taxes for governments, hence impacting progress and increasing spending on unemployment benefits and social subsidies. Long-term unemployment can also affect social cohesion, lead to negative opinions about the effectiveness of democratic models, prompt cross-border migrations, threaten the economy of trading partners. 

According to the latest edition of the World Employment and Social Outlook compiled by the International Labour Organization (ILO), global unemployment in 2018 remains at a similar level to last year’s.

Peaking at 5.9% in 2009, once the most acute phase of the financial crises was over, the world unemployment rate started slowly decreasing. After 2014, it has essentially stabilized around the 5.5% mark, with a total number of estimated unemployed persons exceeding 192 million. 

The report also highlights that in recent years progress in reducing vulnerable employment (jobs with low-wages and no security or guarantees) has stalled. An estimated 1.4 billion workers were in states of vulnerable employment in 2017, and an additional 35 million are expected to join them by 2019.

Cursory unemployment rates, it goes without saying, also conceal a profusion of different underlying realities on a regional level.

According to ILO, northern Africa features the highest jobless percentage in the world, 11.5 in 2018, with youth and women being over-represented among the unemployed. In Sub-Saharan Africa, where one in three workers is living in conditions of extreme poverty and three out of four are in vulnerable employment, the rate is expected to stick to levels seen since 2017 at 7.2%. Both in Canada and to a greater degree in the United States, owing to a strong economy, the number of people out of work is at historic lows with a compound rate close to 4%. In Latin America and the Caribbean, the proportion of working-age people not earning compensation is projected to decrease marginally, from 8.2% in 2017 to 7.7% by 2019. 

In the Middle East where unemployment for this year is projected at 7.8%, one-third of the almost 5 million people without jobs are women even though they represent just 16% of the labor force. In Central and Western Asia, the regional jobless rate is expected to remain at 8.5% in 2018 and 2019, with vulnerable employment affecting about 30% of workers.

Meanwhile, Asia and the Pacific are continuing to create jobs at a fast pace, keeping the unemployment low by international standards at around 4%. However, almost half of all workers—more than 900 million—are in vulnerable forms of employment.

In Eastern Europe, falling jobless rates in nations such as Poland, Ukraine and Slovakia only partly offset expectations of growing unemployment in the Czech Republic: the proportion of labour force out of work in the region is projected to decline modestly from 5.2% this year to 5.1% the next. 

In Northern, Southern and Western Europe, helped by better than expected economic activity, unemployment is on course to decrease from 8.4% in 2017 to 7.7% in 2017 and 7.4% in 2019. The largest overall improvements, of the order of two percentage points, are likely to be seen in Spain and Greece (14.6% and 21.1% estimated respectively this year). In Italy, France and Portugal unemployment rates have been declining in the years following the debt crises and will continue to do so in 2019, albeit at a slower pace than before. In Ireland and in the UK they should remain stable at around 6% and 4% each.

Whereas these numbers can tell us where jobs are today, they suggest little about their nature and where they will go tomorrow. In particular, while the development of automation enabled by robotics and artificial intelligence comes bringing many promises (higher productivity, economic growth, increased safety), it also raises important questions about the kind of impact it will have on the labor force. With many activities having the potential to be automated, some believe that workers will be displaced en masse from their jobs while others say technological advancements will create more jobs than they render obsolete.

The McKinsey Global Institute has examined more than 2,000 work activities focusing on 46 countries representing about 80 percent of the global workforce, and quantified the technical feasibility of automating each of them. The proportion of occupations that can be fully automated using currently demonstrated technology, McKinsey concluded, is actually small: less than 5%. However, even if whole occupations are not automated, partial automation will affect almost all occupations to a greater or lesser degree, with about 60% of them having at least 30% of activities technically that can be performed by machines. 

It bears repeating: these results are based on existing technologies. As for what will happen 10, 20 or perhaps 50 years from now, a famous quote always comes handy: prediction is very difficult, especially if it's about the future.

*Values are expressed in terms of a percentage.

Country
2010
2011
2012
2013
2014
2015
2016
2017
Algeria 9.96 9.97 11.00 9.83 10.78 11.33 10.50 11.71
Armenia 19.00 19.00 19.00 18.50 18.00 17.90 18.79 18.91
Australia 5.22 5.08 5.23 5.66 6.16 6.05 5.71 5.92
Austria 4.42 4.15 4.38 4.90 5.00 4.90 6.02 5.53
Bahamas, The 15.08 15.89 14.69 16.18 16.35 15.89 12.15 10.10
Belgium 8.27 7.25 7.68 8.43 8.50 8.41 7.86 7.10
Belize 13.72 14.93 16.15 14.09 14.09 13.67 7.97 8.99
Bosnia and Herzegovina 27.20 27.60 28.00 27.00 25.50 24.50 25.40 20.50
Brazil 6.74 5.98 5.48 5.38 5.50 6.06 11.27 12.77
Bulgaria 10.31 11.35 12.38 13.04 12.50 11.89 7.67 6.23
Canada 7.99 7.44 7.31 7.08 6.97 6.89 6.98 6.33
Chile 8.15 7.12 6.43 5.93 6.63 7.00 6.49 6.67
China 4.10 4.10 4.10 4.10 4.10 4.10 4.02 3.90
Colombia 11.80 10.83 10.38 9.65 9.30 9.00 9.20 9.30
Croatia 12.10 13.58 16.06 16.62 16.79 17.12 14.96 12.43
Cyprus 6.29 7.91 11.91 15.89 16.59 16.13 12.95 11.05
Czech Republic 7.28 6.71 6.98 6.95 6.42 5.97 3.95 2.89
Denmark 7.48 7.57 7.53 7.02 6.90 6.60 6.18 5.73
Dominican Republic 5.00 5.78 6.45 7.02 6.37 5.97 5.49 5.10
Ecuador 7.59 6.00 4.93 4.74 5.00 5.00 5.21 4.62
Egypt 9.21 10.38 12.37 13.01 13.42 13.88 12.71 12.25
El Salvador 5.86 5.43 5.60 5.70 5.69 5.64 6.90 7.03
Estonia 16.71 12.33 10.02 8.63 6.97 6.98 6.76 5.76
Fiji 8.90 9.00 8.60 8.70 8.75 8.75 5.50 4.50
Finland 8.38 7.78 7.73 8.15 8.51 8.33 8.79 8.53
France 9.28 9.20 9.79 10.26 9.97 10.04 10.05 9.44
Northern Macedonia 32.05 31.38 31.30 30.02 28.96 28.05 23.75 22.76
Germany 7.08 5.96 5.47 5.31 5.27 5.25 4.15 3.75
Greece 12.53 17.65 24.24 27.25 25.76 23.84 23.55 21.45
Hong Kong SAR 4.32 3.40 3.29 3.13 3.05 3.06 3.88 3.12
Iceland 8.13 7.43 5.77 4.44 4.02 3.49 3.01 2.79
Indonesia 7.14 6.56 6.14 6.25 6.10 5.80 5.61 5.40
Ireland 13.85 14.63 14.67 13.05 11.22 10.46 8.39 6.72
Iran 13.48 12.30 12.20 10.44 11.58 12.24 12.46 11.81
Israel 8.25 7.05 6.85 6.28 6.00 6.00 4.78 4.23
Italy 8.42 8.42 10.68 12.21 12.57 11.97 11.66 11.26
Japan 5.04 4.57 4.34 4.03 3.71 3.78 3.12 2.88
Jordan 12.50 12.90 12.20 12.20 12.20 12.20 15.27 18.30
Kazakhstan 5.78 5.40 5.29 5.23 5.23 4.95 4.95 4.95
Korea 3.73 3.41 3.23 3.13 3.13 3.13 3.68 3.68
Latvia 18.68 16.20 15.05 11.86 10.29 9.71 9.64 8.71
Lithuania 17.81 15.39 13.37 11.77 11.00 10.70 7.86 7.07
Luxembourg 5.80 5.70 6.12 6.86 7.06 6.93 6.34 5.82
Malaysia 3.30 3.05 3.03 3.10 3.00 3.00 3.45 3.43
Malta 6.87 6.39 6.31 6.38 6.00 6.10 5.25 4.58
Mexico 5.37 5.22 4.96 4.92 4.75 4.50 3.88 3.42
Moldova 7.40 6.70 5.60 5.10 6.00 5.80 4.23 4.13
Netherlands 4.46 4.45 5.28 6.73 7.25 6.90 6.02 4.85
New Zealand 6.53 6.53 6.90 6.18 5.66 5.24 5.10 4.7
Norway 3.58 3.28 3.22 3.50 3.70 3.78 4.74 4.22
Panama 6.85 4.66 4.25 4.32 4.32 4.32 5.49 6.00
Paraguay 5.70 5.60 5.80 5.40 5.50 5.50 6.00 5.70
Philippines 7.33 7.03 7.03 7.10 6.90 6.80 5.48 5.72
Poland 9.64 9.63 10.09 10.33 9.50 9.50 6.12 4.89
Portugal 10.77 12.68 15.53 16.18 14.20 13.51 11.10 8.87
Romania 7.28 7.40 7.04 7.31 7.17 7.13 5.90 4.93
Russia 7.30 6.50 5.50 5.50 5.64 6.50 5.53 5.20
San Marino 4.95 5.47 6.90 8.00 8.20 7.80 8.60 8.10
Saudi Arabia 5.55 5.77 5.40 5.50 n/a n/a 5.60 6.00
Singapore 2.18 2.03 1.95 1.90 2.00 2.10 2.08 2.18
Slovak Republic 14.49 13.68 13.97 14.22 13.86 13.23 9.68 8.13
Slovenia 7.27 8.21 8.89 10.14 9.90 9.45 8.03 6.60
South Africa 24.88 24.80 24.88 24.73 25.22 25.00 26.73 27.45
Spain 19.85 21.40 24.80 26.10 24.64 23.54 19.64 17.23
Sri Lanka 5.00 4.10 4.00 4.00 4.00 4.00 4.4 4.4
Sweden 8.58 7.77 7.97 8.00 8.02 7.77 6.95 6.68
Switzerland 3.52 2.84 2.91 3.16 3.36 3.34 3.23 3.19
Taiwan 5.21 4.39 4.24 4.18 4.00 4.00 3.92 3.76
Thailand 1.05 0.66 0.68 0.73 0.70 0.80 0.75 0.70
Turkey 11.13 9.10 8.43 9.04 9.48 9.92 10.91 10.90
United Kingdom 7.85 8.10 7.95 7.60 6.35 5.78 4.90 4.43
United States 9.63 8.93 8.08 7.35 6.29 5.95 4.87 4.35
Uruguay 7.02 6.33 6.33 6.60 6.81 6.85 7.86 7.61

Source: IMF World Economic Outlook Database, October 2018.