The report Job Creation and Local Economic Development 2024: The Geography of Generative AI examines the health of regional labour markets and provides new estimates on regional labour shortages. In addition, it provides new findings on the impact of Generative AI on different regions and workers. It examines how AI technologies can be leveraged to address critical labour market challenges and boost productivity growth.
Job Creation and Local Economic Development 2024 - Country Notes: Chile
(a) Employment rate for the working age population (15-64 year-olds), 2023
Note: The figure shows the regional values and the national and OECD regional average in the working-age employment rate in 2023. The employment rate is defined as the number of working-age employed persons out of the working-age population, where the working-age is defined as 15-64 year-olds.
Source: OECD calculations based on the OECD Regional databases.
In Chile the employment rate in 2023 varies across regions, ranging from a low of 57% in Los Lagos to 74.2% in Aysén. This represents a difference of 17.2 percentage points, above the average OECD regional dispersion of 10 percentage points. The national employment rate in Chile stands at 62.6%, below the OECD benchmark of 69.4%.
(a) Change in the employment rate, 2019 to 2023
Note: The figure shows the difference between 2019 and 2023 for the employment rate for regions in Chile, as well as the national and OECD regional average. The employment rate is defined as the number of working-age employed persons out of the working-age population, where the working-age is defined as 15-64 year-olds.
Source: OECD calculations based on the OECD Regional databases.
By 2023, less than half of (4 out of 16) of Chilean regions saw their employment recover to at least pre-pandemic levels. In Atacama, Coquimbo, Valparaíso, O’Higgins, Maule, Biobío, Araucanía, Los Lagos, Santiago Metropolitan Region, Los Ríos, Arica y Parinacota, and Ñuble employment did not return to pre-crisis levels. Tarapacá experienced the greatest recovery for employment rates, surpassing the pre-pandemic level by 2.1 percentage points. Overall, employment rates are 1.7 percentage points below pre-crisis levels, a stronger recovery than the regional OECD average of 1.5 percentage points.
(a) Change in the gap in the participation rate by age (between 25-64 year-olds and 15-24 year-olds) and gender (between men and women), 2013 to 2023
Note: The figure shows regional values and the national and OECD regional average in the change in the age gap (difference between the prime-age working population (25-64 year-olds) and youth (15-24 year-olds) and the gender gap (difference between men and women) in the participation rate in 2013 and that in 2023. A negative value implies that disparities decreased. The participation rate is defined as the number of employed persons and those looking for work as a share of the population in that subgroup. For gender disparities, it is defined using the working age population of 15-64 year-olds.
Source: OECD calculations based on the OECD Regional databases.
Over the past ten years, the gap in participation rates between prime-age and younger workers (age inclusion gap) increased in 14 out of 16 regions in Chile, on average by 7.9 percentage points. The age inclusion gap grew by 1.3 percentage points across OECD regions. The biggest decrease in age disparities occurred in Los Lagos at -4.1 percentage points, while the biggest increase was in Atacama by 16.8 percentage points. Over the same period, the gap in participation rates between male and female workers (gender inclusion gap) fell in 16 out of 16 regions. The gender inclusion gap fell by, on average, 7.7 percentage points. The smallest decrease in gender disparities was in Magallanes and Chilean Antarctica and Ñuble by -1 percentage points, while the biggest decrease was in Antofagasta at -14 percentage points.
(a) Share of youth not in employment, education or training among the youth working-age population, 2017
Note: The figure shows the regional values and the national and OECD regional average in the NEET rate (not in employment, education or training) for the youth working-age population (15-24 year-olds) in 2017.
Source: OECD calculations based on the OECD Regional databases.
In Chile, no (0 out of 15 regions with available data) have youth not in employment, education, or training (NEET) rates below the OECD benchmark of 16.8%, while the regional mean stands at 24%. The highest rate of youth exclusion is observed in Coquimbo at 30.6%, while the lowest rate is in Santiago Metropolitan Region at 19.8%. This underscores the uneven opportunities for youth across the country.
(a) Labour productivity in USD 2015 PPP per worker, 2022
Note: The figure shows the regional values and the national and OECD regional average of labour productivity (USD 2015 PPP per worker) in 2022. The parentheses describe the difference in labour productivity relative to the national average. Labour productivity is defined as gross value added, measured in USD 2015 purchasing power parity, per worker.
Source: OECD calculations based on the OECD Regional databases.
(a) Ten-year annual labour productivity growth, 2013 to 2022
Note: The figure shows the regional values and the national and OECD regional average in the ten year annual growth rate of labour productivity (USD 2015 PPP per worker) from 2013 to 2022. Labour productivity is defined as gross value added, measured in USD 2015 purchasing power parity, per worker.
Source: OECD calculations based on the OECD Regional databases.
In 1 out of 16 regions in Chile, labour productivity is above the OECD benchmark. Antofagasta leads labour productivity levels at 120% above the regional average. The lowest labour productivity is observed in Ñuble at -37% below the national average. Annual labour productivity growth in Chile over the past ten years is at 1.4%, abovethe OECD regional average of 0.9%. The strongest labour productivity growth is observed in Los Lagos at 5.8% annual growth, and the weakest in Antofagasta where labour productivity fell by 2.2% annually.
(a) Share of workers in low-, middle-, and high-skilled jobs, 2023
Note: The figure shows the share of workers in low-, middle- and high-skilled jobs for regions in Chile as well as the national and OECD regional average in 2023. Job skill is defined using ISCO occupational categories. Low skill corresponds to jobs in sales and services and un-skilled occupations (ISCO 5 and 9), medium-skilled workers hold jobs as clerks, craft workers, plant and machine operators and assemblers (ISCO 4, 7 and 8), and high-skilled workers are those who have jobs in managerial, professional, technical and associated professional occupations (ISCO 1, 2 and 3). The definition of skill is based on the educational level thought to be required of an occupation and does not consider skills not related to educational level.
Source: OECD calculations based on national labour force survey. For countries in the European Union, the survey is the EU-LFS.
In Chile, jobs requiring high skill levels dominate in 3 out of the 16 regions. Santiago Metropolitan Region stands out with the highest share of high-skill jobs (39.6%), below the OECD average of 44%. Atacama has the highest proportion of medium-skill jobs, above the OECD benchmark of 30%. The share of low-skill jobs ranges from 32.5% in Antofagasta to 47.5% in Maule, highlighting notable regional variation in job skill composition.
(a) Share of workers in mismatched jobs by over- and under-skilled, 2023
Note: The figure shows the regional values and the national and OECD regional average in the share of workers in mismatched jobs in 2023. Skill mismatch is calculated following the methodology of the Skills for Jobs Indicators of the OECD’s Directorate for Employment, Labour and Social Affairs, whereby a worker is in a mismatched job when their educational skill level does not match the most common skill level of workers in that occupational group in that country. ‘Over-skilled’ means that the worker has an educational skill level above the most common educational skill level of their occupation. `Under-skilled’ means that the worker has an educational skill level below the most common educational skill level of their occupation.
Source: OECD calculations based on national labour force survey. For countries in the European Union, the survey is the EU-LFS.
Skill mismatches are less prevalent in Chile than in the OECD overall: 34% of workers are in jobs that do not match their educational skill level, compared to 35% across OECD regions. This ranges from 39% mismatched workers in Maule to 29% in Antofagasta.
References
OECD (2024), Job Creation and Local Economic Development 2024: The Geography of Generative AI https://doi.org/10.1787/83325127-en
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