Back Matter
  • 1 https://isni.org/isni/0000000404811396, International Monetary Fund

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1

The authors would like to thank S. Pelin Berkmen, Bas Bakker, Natasha Che, Frederik Toscani, Metodij Hadzi-Vaskov, Swarnali Hannan, and other IMF colleagues and participants in the Western Hemisphere seminar for insightful comments and advice. We also thank Luis Herrera Prada for excellent research assistance.

2

In fact, the unemployment rate has barely increased, also partly due to a fall in the labor participation rate, as discouraged workers stopped looking for jobs due to the pandemic. As the economy begins to reopen, the employment rate has started to gradually improve but remains well below its pre-pandemic level.

3

Similarly, (Calero, et al., 2018), build a synthetic panel for nine Latin American economies from 1990–2014 to explore labor market trajectories and earnings over the life cycle.

4

See Caliendo and Schmidl (2016) for a more recent and comprehensive overview of ALMP in Europe.

5

During the 2002 crisis the labor market rapidly deteriorated and unemployment grew to a record of 19.8 percent. At the same time, real wages fell by nearly 11 percent, due to the higher inflation and the government’s attempt to consolidate its fiscal position (Mazzuchi, 2009).

6

In the early 1960s Uruguay had already established a welfare state as in many OECD economies, including pensions, unemployment insurance and contributory health insurance (OECD, 2014).

7

Wage councils were implemented for the first time in the rural sector and for domestic workers in 2008.

8

Since wage councils had been suspended in 1992, firm-level dominated sector-level bargaining between 1992 and 2004. However, firm-level bargaining was not as effective in achieving consensus during collective bargaining, which led to a decline in negotiations.

9

Since the onset of the pandemic, the unemployment rate in Uruguay has increased to about 11 percent, although the full impact of the crisis is yet to be seen as it is not clear how many of the workers with a suspended contract under the enhanced unemployment insurance will ultimately lose their jobs.

10

Brazil, Spain and South Africa have higher youth unemployment than Uruguay, but this is partly explained by a higher overall unemployment. Whereas in Italy, Portugal and Argentina, as in Uruguay, youth unemployment is high although the headline number is relatively low.

11

Skill mismatch could also occur as a result asymmetric information or other matching frictions in the labor market.

12

Youths also lack the necessary skills and thus are also much less likely to work for the government where employee benefits are usually higher relative to private firms. These further limits their opportunity to receive employment protection, thereby leaving them more exposed to economic risks.

13

Data on sectoral job losses since the onset of the pandemic is unavailable for Uruguay. However, it is well-known that the retail, tourism and hospitality services remain greatly affected and the timeline for their reopening is still highly uncertain.

14

While there is evidence that vocational training lowers youth unemployment by around 0.3 percentage points in OECD countries (Baneriji, et al., 2014), more recent studies show that conditional on education level, vocational training facilitates entry to more automatable jobs because the skills associated with this training become obsolete faster than general education skills (Hanushek et al., 2017; ILO, 2020).

15

In 2006 there was a dramatic change in the survey sampling procedure. Surveys were administered across all 19 departments in Uruguay instead of Montevideo only, which was done prior to 2006.

16

The methodology for constructing synthetic panels is predicated on strict comparability of the underlying cross-section surveys. That is, the underlying sample across survey years should be identical such that the time-invariant characteristics remain the same over time. We have checked the questionnaires and validated that they are largely comparable across survey years.

17

In the absence of group-specific fixed effects, variation across cohorts can lead to biased synthetic panel estimates.

18

This might imply that age is highly correlated with other characteristics which are not controlled in the single-equation estimates of Okun’s Law. This result remains if we replace the GDP growth with the output gap (as in the Okun law estimates).

19

The explained portion is the unemployment rate that would be expected given Uruguayan endowments per age group if the returns to those characteristics were the same as in the average LA5 country.

20

In the second to fifth columns, the LA5 average includes Uruguay, which inflates the difference in youth unemployment rates. The decomposition results without Uruguay are qualitatively similar and are available upon request.

21

These results are not shown but are available upon request.

22

Except in Chile where marital status and region of residence account for nearly 11 percent of the unemployment gap.

23

This “scarring” effect of unemployment has been widely documented in the literature, see (Kahn, 2010), (Bell & Blanchflower, 2011), (Oreopoulos, et al., 2012) and (Amarante, et al., 2012).

Youth Unemployment in Uruguay
Author: Mr. Jose L. Torres and Sidonia McKenzie