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Behaviour > 11 - public goods games (part 2) > Flashcards

11 - public goods games (part 2) Flashcards

1
Q

what are issues with creating experimental games in lab

A
  1. error - games might be too complex - subject doesnt understand - subjects might think others wont understand
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2
Q

what is NE

A

each players strategy maximises their own payoff, given the strategies of the other players

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3
Q

what are the 2 different interpretations of NE

A

hold unconditionally - subjects play NE perfectly

conditionally on completion of convergence process that players learn - NE is conditional on completing learning process

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4
Q

what are the 3 issues with public good experimental games
- that means wont find real answer

is game theory correct - do people maximise based on what others do?

reasons why NE wont be reached?

A
  1. error
  2. equilibrium - is it conditional or unconditional
  3. control of preferences
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5
Q

what is the issue with controlling preferences

A

game theory = maximise utility
experiment = assumes utility is determined by money payoff

but what if players care about other things, money isnt the only thing that captures utility

  • subjects will be playing a different game to the one experiments intended
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6
Q

what is the method used to implement a public good in the lab

A

VCM
voluntary contributions mechanismh

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7
Q

what is a public good

A

non-rival = one persons consumption of it will not reduce another persons ability to consume it

non- excludable = everybody has access to it

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8
Q

what is a voluntary contributions mechanism

A
  • play game in group
  • money payoffs are proportional to points earned
  • each person endowed with E token - choose independently and simultaenously what to do with them
  • can divide E between private account and public account
  • each token in private account gives 1 point
  • each token in public earns m points for everyone - m<1
  • everyone benefits from public good
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9
Q

what is the dominant strategy in VCM

if player wants to maximise own payoff (points)

A
  • m<1
  • so will contribute nothing to public account
  • all tokens in private account + whatever anyone else put in public
  • if everyone doesnt contribute –> everyone gets E
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10
Q

what would happen if everyone contributes

A
  • mnE points > E points (not contributing)
  • everyone is better off if they all contribute everything
  • if they cooperated
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11
Q

what are the typical findings of VCM if game is played once

A
  • 20% free riders - dont contribute
  • average contribution of endowments - 40-60%
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12
Q

what are typical findings of VCM if game is repeated

and you get feedback on what other members in group contributed

A
  • contribution starts off at 50% of endowment
  • decays over next rounds
  • contribution rates fall
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13
Q

what 3 reasons explain why players contribute

  • when dominant strategy is not to

(has to account for initial contribution and decay)

A
  1. error
  2. learning
  3. strategic
  4. preference explanations
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14
Q

why players contribute

error

A

initially they are confused about the game
- as they learn
contributions decay

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15
Q

why players contribute

strategic

A

players start by contributing in early rounds because they think it will raise future contribution of others - so they will benefit from this

  • want to benefit off of the fact that others are confused (why would they think that others would contribute)
  • contributions decay in later rounds to benefit from the cooperation of others
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16
Q

why players contribute

preference explanations

A

altruism
conditional cooperation
self satisfaction

17
Q

Keser (1996)
what

A

wants to test if error is the reason for the contributions

18
Q

Keser
how does he test for error

A
  • redesigns the game so that NE involves some contribution
  • so that error can be seen in either direction - distinguish error from those that actually want to contribute
  • possible errors on both side on NE
19
Q

what did keser find

error

A
  • only 30% of people played the dominant strategy
  • majority of people made contributions above the dominant strategy level
  • few contributed less than 7
20
Q

what does keser results suggest

A
  • over contribution is not fully explained by error
  • if it was we would see error symettrically on either side of NE
  • but saw far more people contribute above
  • error is not the sole answer
  • but shows that still a few people did make errors and contributed less - so still a factor just not big
21
Q

Andreoni 1998

what was the aim

A
  • separate the learning hypothesis from the strategic hypothesis
  • learning = early contributions are due to error, conditional convergence of NE
  • strategic = players contribute in hopes of boosting future contributions - and then decays in later rounds
22
Q

Andreoni

experiment ran

A

partners and strangers
play game repeatedly

suprise restart - to test learning hypothesis

23
Q

what were the predictions in Andreoni 1998

A
  • strategic = predicts higher contribution in partners until final round - can influence others decisions - but not in strangers
  • learning = no difference in decay rates between strangers and partners - after suprise restart decay should continue not respark
24
Q

Andreoni findings

A
  • strangers contribute more than partners - not consistent with strategic hypotehsis
  • after restart - partenrs return to contribution levels similar to first round - not consistent with learning hypothesis
25
Q

Croson 1996

A

replicates strangers and partners

26
Q

croson 1996 findings

A

jump from parterns after restart

strangers contribute less than partenrs - strategic hypothesis

27
Q

Yamakawa 2016

what experiment

3 different treatments

A
  1. human treatment
    -VCM, 20 rounds, pairs
  2. computer treatment
    - each pair is 1 human and 1 computer
    - computers choices are predetermined - by a humans choice in the H treatment
    - human in this pair cant influence the computers decisions
  3. human computer treatment
    - computer plays on behalf of second human who receives its payoffs
28
Q

what is the incentive behind having computers

and then having computers but playing for a human

Yamakawa

A
  • no incentive to influence its decisions
  • no incentive to play altruistically
  • if people contribute to the computer - it must be because of error = no other reason?
  • playing for a human - will capture the altruism
  • solely pick up the effect of wanting to financially benefit the other
29
Q

rationale behind Yamakawa

A

no incentive to contribute because against computer

C = captures errors
HC = captures altruism

30
Q

Yamakawa

results

A

H - people contribute and then there is a decay at the end

C - no contribution at all = so people not making errors - people werent confused about the game

HC - closer to C (no contribution) than to H - evidence of strategic motive - altruism isnt a big factor otherwise would of been closer to H

  • when humans interact with humans that can respond - they contribute more
31
Q

what papers say that error/learning doesnt play big factor for why

people crontribute
decays

A

keser - errors on both sides
Andreoni - restart
Yamakawa - C game no one contributes

Behaviour (26 decks)

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