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A rock or a soft place?
This question can stir up a fair bit of debate, and I have heard it
being argued one way and the other. “You should pay them all
the same,” some loudly proclaim, “because they’re a team and
you don’t want to create envy and inequality within the group!”
Others will bellow in agony: “But you need to incentivize people,
stupid! Equal pay kills their motivation; you should pay more
to people who (seem to) contribute more, to keep them happy
while stimulating the others to better themselves!!”
And who knows whether it is one way or the other? The
problem is, it is very difcult to research this properly, and nd
a conclusive and reliable answer. You’d need information on
the exact remuneration of all people in a team, their individual
performance, and their team performance, and have a whole
bunch of identical teams to make meaningful comparisons. And
that’s easier said than done.
However, Professor Matt Bloom, from the University of Notre
Dame, decided to give it a try. And to make sure that he had
a clean research sample, with a whole bunch of similar teams
doing the same task, for which he could collect all the relevant
info, he chose major league baseball.
And, although a bit unconventional, that’s perhaps not such a
bad idea. I don’t know much about baseball (and would prefer
to keep it that way!) but I assume the rules are the same for
everyone, the teams the same size, working on the same task,
etc. Thus, Matt collected performance data on 1,644 players in
29 teams, assessing their individual performance through batting
runs, elding runs, earned run averages, pitching runs, player
ratings and all this (for me) abacadabra. For team performance,
he measured a combination of on-eld performance and nancial
performance, using game wins and revenue and valuation data.
This gave him measures for team performance and the individual
performance of each member of the team.
Then he measured player compensation. The newspaper USA
Today apparently publishes salary and performance incentives
for all players, so he used that. Finally, he created an indicator of
“pay dispersion”, or how big are the differences in the levels of