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Using cross-sectional occupational data over time can present a challenge because of changes in occupation classifications.
These changes in occupation history appear to have resulted from political developments within the valley.
These improvements in risk-sharing led to higher savings, higher consumption and changes in occupation for user households.
29% showed no changes in occupation over the 10-year period and were classified as "fixed careers".
These processes increasingly lead to discontinuous employment histories characterised by changes in occupation, precarious employment and periods out of work [18, 29].
These authors model individual occupation decisions and changes in occupation over time, taking account of individual characteristics such as wealth and wealth constraints, education levels, family background, prior work experience, preferences for independent work, and so on.
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In the following two sections, we analyze, with a higher degree of disaggregation, whether the above mentioned changes in occupations could be understood in a polarization framework.
However, the polarisation of wages does not seem to be common in Spain, as there is no evidence that changes in pay followed the same pattern as changes in occupations.
This question is relevant because one might want to use the observed changes in occupations over time to shed some light on the evolution of the demand for labour in the near future.
Certain outcomes of the threshold dynamics similar to feedback loops in social-ecological systems were identified, including considerations of out-migration and change in occupation, of which ultimate impacts remain unclear.
This value is used as an input to the Hamiltonian for the next iteration, and this process is repeated until the maximum change in occupation at any site is <5 × 10−7 per iteration.
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