A recent economic study has revealed that the employment landscape within Morocco's local communities is influenced not only by administrative boundaries but also by the dynamics of neighboring communities. This interconnectedness affects unemployment rates, job opportunities, and economic activity, leading to the classification of these communities into five distinct functional groups based on their economic activity, ability to provide jobs, educational levels, and presence of public institutions.
The findings of this study were published in the journal Networks and Spatial Economics and relied on official data from the High Commission for Planning, particularly from the general population and housing census of 2024, as well as the national map of economic institutions for the years 2023 and 2024.
The research utilized detailed data at the community level, comparing them based on several indicators, including business density, the share of industrial and service activities, stable job numbers, workforce absorption capacity, basic education levels, and the presence of public institutions and administrations.
Five Functional Groups of Communities
The analysis resulted in the categorization of communities into five groups that differ significantly in their economic and social compositions, reflecting the diverse conditions of the local job market and the fact that not all regions conform to the same model.
The first group consists of 586 communities characterized by a higher prevalence of service activities, with average levels in other indicators. These communities exhibit a presence of services, although they do not reach the activity density seen in major economic centers.
The second group includes 580 communities classified within the “fragile margin” due to low business density, limited workforce absorption capacity, and a decline in the educational attainment index.
The third group, consisting of 252 communities, shows a relatively higher level of basic education against average economic indicators. This situation suggests that these communities possess relatively better human resources compared to the economic activity available within them.
The fourth group contains 82 communities described as “integrated economic hubs,” which recorded the highest levels of business density, stable jobs, and workforce absorption capacity, along with high education indicators.
Finally, the fifth group comprises 23 communities distinguished by a strong presence of public institutions and administrations, with the relevant index measuring this presence being nearly six times the national average, despite a relatively weaker activity from the private sector.
Seventeen communities were left outside these five groups during the classification phase due to their isolation within the neighborhood network used for analysis.
The Impact of Proximity on Unemployment Rates
The study demonstrated that unemployment rates do not distribute independently among communities. Communities with higher unemployment tend to be located near those experiencing similar elevated levels, with a similar pattern observed in areas with lower rates. The impact index of unemployment from neighboring communities was calculated at 0.548, indicating that an increase in the average unemployment rate in surrounding areas by one percentage point is associated with an approximate increase of 0.55 points in the unemployment of the concerned community, after considering other factors included in the analysis.
Researchers also noted correlations between educational indicators and the job market; however, they cautioned that these statistical relationships do not imply that higher education levels lead to unemployment. Instead, they may reflect the nature of local job opportunities and their alignment with the qualifications of job seekers.
Furthermore, effects extending from communities with industrial or administrative presence to neighboring regions underscore the need to view the local job market as a phenomenon that occasionally transcends the administrative boundaries of each community.
The study relies on data from 2024, offering a snapshot of the job market during a specific period. However, researchers lacked direct data on daily population movements between residential and work locations. Consequently, the five groups were established based on similarities among communities in their economic and social characteristics and their neighborhood relationships, rather than tracking daily movements of workers and employees between areas of residence and work sites.
Using a simplified indicator of educational level, specifically literacy rates, the study allows for comparisons among communities but does not differentiate between various degrees, specialties, or professional skills.
The results prompt a reevaluation of employment issues at the level of interconnected community groups, particularly when job opportunities are concentrated in one community while job seekers reside in neighboring areas. This situation makes transportation, training, housing, and infrastructure essential elements linked to the functioning of the local job market.
The study advocates for differentiated employment policies based on the nature of each group, from improving infrastructure and training in the most vulnerable communities to enhancing transportation and housing and creating jobs that fit qualifications in economic hubs, while strengthening economic ties between neighboring communities.
As reported by hespress.com.
