Abstract
Although what one deserves requires evaluation of chance, this is not perfectly feasible as a public policy given current limitations in our knowledge. As a result, some have recommended a political process to determine what counts as chance. This chapter rejects this suggestion and argues that a fundamental baseline that all can agree on, even the most hardened skeptic, is to consider the outcomes of the natural lottery as chance. This argument is followed by a more tentative suggestion as to how we use those natural lottery outcomes to estimate the desert-basis. The chapter recommends an initial, plausible baseline and a ratchet system to further refine our estimates that is open to both classical models such as linear regression and more black-box models that might come from machine learning techniques. It then describes the data and methods. Lastly, this chapter confronts some objections by skeptics about these estimations.
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Notes
- 1.
Roemer (1998), 8.
- 2.
The dangers of a political process, rather than finding a starting point that all can agree on, is both a misspecification of circumstances as well as effort, often by treating years of education and hours of labor as “Effort.” Fleurbaey (1995b); Almås et al. (2011); Lefranc et al. (2009); Pistolesi (2007).
- 3.
- 4.
Aaberge et al. use father’s annual earnings in one year when son was 16–18 years of age as a circumstance of chance. Interestingly, they suggest that their model was not sensitive to such a one-year point estimate when fathers were different ages as a substitution of “years of education,” although not “pre-birth years of education,” yielded similar results. Cf. Aaberge et al. (2011).
- 5.
Cf. “But if we fully understand Reid’s notion of agent causation we can see, I think, that no event or agent can cause someone to agent-cause some change.” Rowe (1987).
- 6.
Thus, we may not even use “number of siblings” as a circumstance, rather we must use “pre-birth number of siblings” until the skeptic acquiesces or is ignored. For “number of siblings” based research, cf. Aaberge et al. (2011); Nor may we use the outcomes of IQ tests taken at the age of 18, cf. Björklund et al. (2011).
- 7.
- 8.
It should be noted that economists’ suggested measure, hours of formal market labor, fails this criterion as well. First, many survey respondents simply tick off 2000 as “full-time, full-year” when answering this survey question, but more importantly, no administrative source currently has formal labor market hours data.
- 9.
Chetty et al. (2014).
- 10.
- 11.
Perhaps we say that the studentized Breusch-Pagan test should have a p-value > 0.05.
- 12.
I would of course be happy if statisticians were able to provide a better test under the same guidelines: simple, robust, conservative estimate of value of autonomous effort and circumstances of chance.
- 13.
Guyon et al. (2010), 71.
- 14.
Groves (2005), 215–217.
- 15.
I make no recommendation that we collect genetic data from the population, but the idea of a recessive gene offers the perfect test case as this guarantees that heterozygous carriers are identical to homozygous non-carriers except for the presence of an element on which no human can directly discriminate.
- 16.
Correlation requires two continua, but carrying the unexpressed CF gene or not carrying are “categories” or “factors,” not “continua.” Benshalom and Stead (2010).
- 17.
Logue and Slemrod (2008).
- 18.
We can see now that although we must reject the outcomes of an IQ test administered at the age of 18 (as well as BMI and component measures), it would be perfectly valid to use genetic information measurements made at age 0 or 18 as long as they met our three criteria. For use of IQ test outcomes, cf. Björklund et al. (2011).
- 19.
- 20.
Lamont (1995).
- 21.
Atkinson and Stiglitz (1980), 359.
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Dwyer, J.d.l.T. (2020). The Natural Lottery Alone. In: Chance, Merit, and Economic Inequality. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-030-21126-4_10
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