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{{Short description|Method of allocating seats in a parliament}}
{{Short description|Method of allocating seats in a parliament}}
'''House monotonicity''' is a property of [[Mathematics of apportionment|apportionment methods]], which are methods of allocating seats in a [[parliament]] among [[federal states]] (or among [[political party]]). The property says that, if the number of seats in the "house" (the parliament) increases, then no state should lose a seat. A method that fails to satisfy house-monotonicity is said to have the '''Alabama paradox'''.<ref name=":0">{{cite book|last=Balinski|first=Michel L.|url=https://archive.org/details/fairrepresentati00bali|title=Fair Representation: Meeting the Ideal of One Man, One Vote|last2=Young|first2=H. Peyton|publisher=Yale University Press|year=1982|isbn=0-300-02724-9|location=New Haven|url-access=registration}}</ref>{{Rp|134–141}}
'''House monotonicity<ref name=":0">{{cite book|last=Balinski|first=Michel L.|url=https://archive.org/details/fairrepresentati00bali|title=Fair Representation: Meeting the Ideal of One Man, One Vote|last2=Young|first2=H. Peyton|publisher=Yale University Press|year=1982|isbn=0-300-02724-9|location=New Haven|url-access=registration}}</ref>{{Rp|134–141}}''' (also called '''house-size monotonicity'''<ref>{{Citation|last=Pukelsheim|first=Friedrich|title=Securing System Consistency: Coherence and Paradoxes|date=2017|url=https://doi.org/10.1007/978-3-319-64707-4_9|work=Proportional Representation: Apportionment Methods and Their Applications|pages=159–183|editor-last=Pukelsheim|editor-first=Friedrich|place=Cham|publisher=Springer International Publishing|language=en|doi=10.1007/978-3-319-64707-4_9|isbn=978-3-319-64707-4|access-date=2021-09-02}}</ref>) is a property of [[Mathematics of apportionment|apportionment methods]]. These are methods for allocating seats in a [[parliament]] among [[federal states]] (or among [[political party]]). The property says that, if the number of seats in the "house" (the parliament) increases, and the method is re-activated, then no state should have less seats than it previously had. A method that fails to satisfy house-monotonicity is said to have the '''Alabama paradox'''.


House monotonicity is a special case of ''[[resource monotonicity]]'' for the setting in which the resource consists of identical discrete items (the seats).
House monotonicity is the special case of ''[[resource monotonicity]]'' for the setting in which the resource consists of identical discrete items (the seats).


== Methods violating house-monotonicity ==
== Methods violating house-monotonicity ==
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All the [[Highest averages method|highest-averages methods]] (= divisor methods) satisfy house monotonicity.<ref name=":0" />{{Rp|Cor.4.3.1}} This is easy to see when considering the implementation of divisor methods as picking sequences: when a seat are added, the only change is that the picking sequence is extended with one additional pick. Therefore, all states keep their previously-picked seats.
All the [[Highest averages method|highest-averages methods]] (= divisor methods) satisfy house monotonicity.<ref name=":0" />{{Rp|Cor.4.3.1}} This is easy to see when considering the implementation of divisor methods as picking sequences: when a seat are added, the only change is that the picking sequence is extended with one additional pick. Therefore, all states keep their previously-picked seats.

Similarly, [[rank-index methods]], which are generalizations of divisor methods, satisfy house-monotonicity.


Moreover, [[Highest averages method|''capped divisor methods'']], which are variants of divisor methods in which a state never gets more seats than its upper quota, also satisfy house-monotonicity. An example is the [[Michel Balinski|Balinsky]]-[[Peyton Young|Young]] quota method.<ref>{{Cite journal|last=Balinski|first=M. L.|last2=Young|first2=H. P.|date=1975-08-01|title=The Quota Method of Apportionment|url=https://doi.org/10.1080/00029890.1975.11993911|journal=The American Mathematical Monthly|volume=82|issue=7|pages=701–730|doi=10.1080/00029890.1975.11993911|issn=0002-9890}}</ref>
Moreover, [[Highest averages method|''capped divisor methods'']], which are variants of divisor methods in which a state never gets more seats than its upper quota, also satisfy house-monotonicity. An example is the [[Michel Balinski|Balinsky]]-[[Peyton Young|Young]] quota method.<ref>{{Cite journal|last=Balinski|first=M. L.|last2=Young|first2=H. P.|date=1975-08-01|title=The Quota Method of Apportionment|url=https://doi.org/10.1080/00029890.1975.11993911|journal=The American Mathematical Monthly|volume=82|issue=7|pages=701–730|doi=10.1080/00029890.1975.11993911|issn=0002-9890}}</ref>

Revision as of 05:56, 2 September 2021

House monotonicity[1]: 134–141  (also called house-size monotonicity[2]) is a property of apportionment methods. These are methods for allocating seats in a parliament among federal states (or among political party). The property says that, if the number of seats in the "house" (the parliament) increases, and the method is re-activated, then no state should have less seats than it previously had. A method that fails to satisfy house-monotonicity is said to have the Alabama paradox.

House monotonicity is the special case of resource monotonicity for the setting in which the resource consists of identical discrete items (the seats).

Methods violating house-monotonicity

An example of a method violating house-monotonicity is the largest remainder method (= Hamilton's method). Consider the following instance with three states:

10 seats house 11 seats house
State Population Fair share Seats Fair share Seats
A 6 4.286 4 4.714 5
B 6 4.286 4 4.714 5
C 2 1.429 2 1.571 1

When one seat is added to the house, the share of state C decreases from 2 to 1.

This occurs because increasing the number of seats increases the fair share faster for the large states than for the small states. In particular, large A and B had their fair share increase faster than small C. Therefore, the fractional parts for A and B increased faster than those for C. In fact, they overtook C's fraction, causing C to lose its seat, since the method examines which states have the largest remaining fraction.

This violation is known as the Alabama paradox due to the history of its discovery. After the 1880 census, C. W. Seaton, chief clerk of the United States Census Bureau, computed apportionments for all House sizes between 275 and 350, and discovered that Alabama would get eight seats with a House size of 299 but only seven with a House size of 300.[3]: 228–231 

Simulation experiments[4] show that monotonicity violations can be quite common. For example, in random elections, Hamilton's method has a chance of 1/18 to violate monotonicity.

Methods satisfying house monotonicity

All the highest-averages methods (= divisor methods) satisfy house monotonicity.[1]: Cor.4.3.1  This is easy to see when considering the implementation of divisor methods as picking sequences: when a seat are added, the only change is that the picking sequence is extended with one additional pick. Therefore, all states keep their previously-picked seats.

Similarly, rank-index methods, which are generalizations of divisor methods, satisfy house-monotonicity.

Moreover, capped divisor methods, which are variants of divisor methods in which a state never gets more seats than its upper quota, also satisfy house-monotonicity. An example is the Balinsky-Young quota method.[5]

Every house-monotone method can be defined as a recursive function of the house size h.[1]: Thm.7.2  Formally, an apportionment method is house-monotone and satisfies both quotas if-and-only-if it is constructed recursively as follows (see mathematics of apportionment for the definitions and notation):[6]

  • ;
  • If , then is found by giving seats to some single state , where:
    • is the set of states that can get an additional seat without violating their upper quota for the new house size;
    • is the set of states that might receive less than their lower quota for some future house size.

See also

References

  1. ^ a b c Balinski, Michel L.; Young, H. Peyton (1982). Fair Representation: Meeting the Ideal of One Man, One Vote. New Haven: Yale University Press. ISBN 0-300-02724-9.
  2. ^ Pukelsheim, Friedrich (2017), Pukelsheim, Friedrich (ed.), "Securing System Consistency: Coherence and Paradoxes", Proportional Representation: Apportionment Methods and Their Applications, Cham: Springer International Publishing, pp. 159–183, doi:10.1007/978-3-319-64707-4_9, ISBN 978-3-319-64707-4, retrieved 2021-09-02
  3. ^ Stein, James D. (2008). How Math Explains the World: A Guide to the Power of Numbers, from Car Repair to Modern Physics. New York: Smithsonian Books. ISBN 9780061241765.
  4. ^ "RangeVoting.org - Apportionment methods". rangevoting.org. Retrieved 2021-08-06.
  5. ^ Balinski, M. L.; Young, H. P. (1975-08-01). "The Quota Method of Apportionment". The American Mathematical Monthly. 82 (7): 701–730. doi:10.1080/00029890.1975.11993911. ISSN 0002-9890.
  6. ^ Smith, Warren D. (January 2007). "Apportionment and rounding schemes". RangeVoting.org.