I’m assuming the point is that I’ve not seen the examples used as examples of dynamic equilibrium before, not that I’ve not seen the equilibrium before? Given that that’s the case:
Total area of districts in a city. Poor areas become gentrified, rich areas go out of fashion, elderly residents become economically (or biologically) inactive, and become run-down. Overall the distribution changes very slowly, even though the standards of what constitutes a “rich” or “poor” area generally increase with time. This is broken if the municipal government fails or something.
Size of staff in a company. For most well-established companies, people enter and leave at a rate much much faster than the company grows or shrinks.
In terms of dynamic equilibria of outcomes, political parties in certain democracies. The short term predictions can be based on the current political landscape, but in the long term, people get tired of politicians, so each politician’s reign is limited. Discontent is always a limiting factor on staying in office.
Great examples. The first one points to equilibria on multiple timescales—e.g. at one timescale people moving in are in equilibrium with people moving out or dying, and at another timescale the distribution of neighborhoods is in equilibrium.
I’m assuming the point is that I’ve not seen the examples used as examples of dynamic equilibrium before, not that I’ve not seen the equilibrium before? Given that that’s the case:
Total area of districts in a city. Poor areas become gentrified, rich areas go out of fashion, elderly residents become economically (or biologically) inactive, and become run-down. Overall the distribution changes very slowly, even though the standards of what constitutes a “rich” or “poor” area generally increase with time. This is broken if the municipal government fails or something.
Size of staff in a company. For most well-established companies, people enter and leave at a rate much much faster than the company grows or shrinks.
In terms of dynamic equilibria of outcomes, political parties in certain democracies. The short term predictions can be based on the current political landscape, but in the long term, people get tired of politicians, so each politician’s reign is limited. Discontent is always a limiting factor on staying in office.
Great examples. The first one points to equilibria on multiple timescales—e.g. at one timescale people moving in are in equilibrium with people moving out or dying, and at another timescale the distribution of neighborhoods is in equilibrium.