Many of you would have been aware of the increasing use of randomised evaluations in Social Science research and for public policy reasons. Taking an epistemological look, I give a robust argument on why the claims of randomised evaluations actually evade the problem of induction. Hope to get your thoughts. Thanks in advance !
1. Introduction
The usage of randomised evaluations in
social inquiry has been recent and responses to them have been wide ranging.
Some have described it as the “gold standard” in empirical research, (Duflo,
Glennerster,&Kremer, 2006) while others though have been more critical of
their value in making predictions. (Deaton, 2009)
Randomised evaluations[1]
(REs) seek to make predictions on the impact of an
intervention, when it is attempted in a new situation. REs work by first
determining the impact of the intervention. Subsequently, for the new situation
it is expected that the impact would be similar.
To determine an intervention’s impact, numerous
subjects are selected and randomly assigned to either the treatment or control
group. Intervention being investigated is introduced for the treatment group.
The control group serves as a counter factual and no intervention is
introduced. Then, after a certain period of time, the mean impact of subjects
in both groups is evaluated. Given that all subjects were equivalent before the
study, any difference in results between the treatment and control groups is
attributed to the intervention.
REs are
increasingly being used to justify knowledge claims
in Developmental Economics (Ester Duflo, 2006). Hence, it would be useful for
us to examine their epistemological status.
In this paper, I will specifically focus
on how the problem of induction poses a challenge to external claims of REs [2]
being considered knowledge. While accepting that no viable solution exists to
the problem of induction faced by RE’s external claims, I will argue that we
ought to consider “inductive validity” rather than deductive validity as the
standard to be met. By further elaborating what would constitute an inductively
valid inference, I will show that the criteria can be met by external claims
and hence conclude that the problem of induction does not undermine their
epistemic status.
2. Claims of RE and Problem of Induction
Typically in a RE, there are two types of
knowledge claims made- Internal and external. Internal claims pertain to the
observed impact of the intervention. For instance, in a RE conducted to find
the impact of providing subsidised meals on school attendance, the internal
claim was that the intervention increased attendance rate by 30
percent. (Christel Vermeersch, 2004) External claims, on other hand, are
predictions of impact. For the same RE, the external claim would be a
prediction of comparable impact when the intervention is administered in
another situation, say a neighbouring school.
Much of RE’s epistemic superiority over other
empirical methods has been credited to its ability to generate highly justified
internal claims. Unlike a standard empirical study, in a RE, a control group is
always constructed (Ester Duflo, 2006). The control group shows accurately what
the impact would have been if not for the intervention and thus any difference
between the treatment and control is attributed to the intervention alone.
Also, the samples are randomized, reducing selective bias. Internal claims are
not undermined by the problem of induction as there is no element of projection
within them.
The high internal validity however does
not mean that external claims do not face the problem of induction. External
claims are justified inductively, based on the assumption of “uniformity of
nature”. However, this assumption is presumed without its validity being proven
(Hacking, 2001) Hence, the question of whether external claims are justified
arises.
Solving or evading the problem of induction is
important. The primary purpose of REs is to determine high impact interventions
and scale-them up. Thus if an appropriate response to the problem of induction
is lacking, then belief in the external claim is thoroughly undermined.
Any solution to the problem of induction, involves
proof that assumption of “”uniformity of nature” holds. Doing so warrants
“deductive validity”, allowing the external claim to be considered knowledge.
An evasion, on other hand, responds to the problem by asserting that the
“uniformity of nature” assumption need not be proven valid for an inductively
reasoned belief to be accepted as knowledge. (Hacking, 2001) Both are possible
responses that would be considered, developed and evaluated next.
3. Solution to
the Problem of Induction
Goodman (2002) argues that the problem of induction is
intractable considering that it demands distinguishing predictions
“antecedently between true and false” and this task is akin to demanding
“prevision rather than philosophical explanation”. He asserts that the
assumption of the uniformity of nature cannot be proven in all fields employing
inductive reasoning.
This is clearly not the case. With John Foster’s
(2004) Nomological Explanatory Solution (NES) it is possible to validate the
assumption in Natural Science studies. However,
as I will show subsequently, such solutions are indeed ineffective for in case
of RE’s external claims.
The key ideas of NES can be summarised as follows
1) If
there is consistent regularity in observations , then it cannot be a mere
coincidence
2) Inference
to the best explanation is used to elucidate the regularity
3) The
explanation “involves the postulation of some law or set of laws of nature” ,
which have to be considered as naturally necessitating the observation
4) The
explanatory “law” entails the weaker claim, that it will hold in the future as
well
To illustrate how the NES works, consider the case of
graphite always conducting electricity when charge is applied. The observation
that graphite consistently conducts electricity demands an explanation. In
response, we could explain this phenomenon by arguing that graphite has
delocalised electrons thereby enabling it to carry electricity. The explanation
necessitates that graphite conducts electricity, whenever charge is applied.
From this explanatory law, the weaker claim that “graphite will be an electric
conductor in the future “is entailed as well. When NES is applied, there are no
extrapolative steps and the problem of induction appears to be solved.
While NES is effective in solving the problem of
induction for Natural Science claims, the same cannot be said of RE’s external
claims. In the case of REs, enumerative induction is used to justify external
claims. No rational explanation is offered for the difference in average impact
between the treatment and control group. Hence, the belief in the uniformity of
nature is speculative.
In contrast, inference to the best explanation is used
to account for past regularities in the Natural Sciences .Forming
explanations to elucidate results
obtained is a central feature of scientific inquiry (G.Hempel, 2001) .This
qualifies NES to be an adequate solution for the problem of induction for
Natural Sciences.
Even if efforts are undertaken to offer rational
explanation for the impact changes observed, NES would still be ineffective.
NES is only effective if results observed are a “product of natural necessity”.
Otherwise the claim, that future occurrences
would be similar, involves extrapolation and the external claim won’t be
valid.
It is hard to argue that human behaviour is a complete
product of natural necessity for it involves eliciting a specific action from
human beings, who have free will.
Causes might “incline but not necessitate” human action. (Flew, 1995)
To illustrate this better, consider the RE, where
teachers were monitored using cameras and higher teacher attendance was
observed (Hanna, 2005). A possible explanation for the results could be that
teachers attend classes more regularly when they are monitored so as to
maintain a positive image. Even if we take this explanation to be true, given
any situation humans would always have some degree of freedom to choose how
they act. In this case it is possible for some teachers to willingly decide not
to attend work regularly despite knowing that their reputation would be
sullied. Thus, monitoring teachers might induce but certainly not necessitate
the expected action. This means that the assumption that nature will be uniform
has not been proven. Thus, deductive validity is still lacking.
Compare this with the Natural Sciences where the
explanatory laws invariably “require” that future occurrences be similar to
past results. In the graphite example, it is inconceivable of graphite not
conducting electricity when charge is applied. Hence, projections are
deductively valid.
Hence, it is
incorrect for Goodman to claim that solving the problem of induction is
intractable in the case of all fields. I have demonstrated that NES effectively
solves the problem in case of the Natural Science field. However, the problem
does indeed seem[3] unsolvable for REs.
4. Evading the problem of induction
A solution to the problem of induction faced by REs
does seem inconceivable. However, just on this account we cannot conclude that
belief in the external claim is undermined
by the problem of induction. As established
earlier in Section 2, in addition to considering the possibility
of a solution to the problem, we need to consider whether the problem can be
evaded or not.
Goodman (2002)
suggests a compelling evasion by arguing that it is inappropriate for inductive
inference to strive towards attaining
deductive validity. He proposes
that they should instead be judged on whether they attain “inductive validity”. Goodman’s argument is convincing as he
distinguishes between inductive and deductive inferences and it is reasonable to
have different epistemic standards for both types of inference.
This however raises the question of what criteria need to be fulfilled
for an inference to be considered “inductively valid”. Strength of
evidence is certainly a factor. We would be more justified in believing an inductive inference when
it is backed up with strong
evidence. By strong evidence I mean statistically significant evidence, which
ensures that results obtained are not due to chance.
However as Goodman rightly points out, not all inferences are considered “inductively
valid” despite strong evidence. For instance, assuming that there
is a strong positive correlation
between the number of Google searches of a country and the country’s
prosperity, we would not be
rationally justified to
predict that a country will become more prosperous because it
attempts to boost
the number of searches. However, if there is a positive correlation of same magnitude between
per capita spending on education and country’s level of prosperity, we would be
considerably more justified
to predict that when a country boost’s spending in education than its level
of prosperity would increase.
The differences in treatment of both the inductive
statements can be attributed to the former being an accidental inference and latter being a law-like
inference. In a law-like inference, we can propose a justified explanation for
why the causal factor necessitates, even if not completely, the result. Thus
expectations of similar results are justified. In the earlier example of education
spending, it is reasonable to believe that increased spending leads to a better skilled
work force hence enhancing productivity. However there is no convincing logical
explanation for the link between the number of searches of the country in
Google and its prosperity level. This leads us to term the former statement as
being an accidental inference and hence it cannot be
considered “inductively valid”.
Thus far, we have identified two factors for an
inference to be considered inductively valid. Firstly it must have strong evidential
support and secondly it must be law-like. External
claims of REs meet both these criteria.
Some
might argue that REs must
provide rational explanation to elucidate the relationship
between the intervention and the
result, so as to prevent any accidental inference. I, however, contend
otherwise. For a law-like
statement what ought to be proven is that the intervention cause the result
being observed. The mutual presence of the causal agent and result must not be
a mere accident. In the case of RE, any difference in results is attributed to
the intervention being studied alone as all other relevant factors are kept
constant. Hence the intervention must
have resulted in the differences in the result. Thus, it cannot be accidental.
To
clarify this point, consider the RE conducted to establish the relationship
between providing subsidised
meals and students’ attendance rate in rural villages (Christel
Vermeersch, 2004).
From a set of similar schools, some schools were randomly selected, to offer a subsidised
food service. Whereas in
the control group, there
was no such intervention. After 24 months, it was established that the students’ attendance
rate for the schools in the treatment group was much higher than schools in the
control group. Assuming all other
parameters had been kept constant, the only difference between
schools in both groups is the presence of intervention. Hence, we can conclude
that the intervention must have caused the varying impact. Thus, any correlation
cannot be an accident and RE claims are indeed law-like.
In
addition to being law-like, RE claims are also backed up by statistically
significant results. All results are subjected to rigorous statistical testing
and are only accepted if
the probability of them arising
due to chance is between
5 to 10 percent. (Esther Duflo, 2006). Thus REs are reasonably
accurate and there is strong justification for expecting similar results.
REs are limited to establishing that the intervention can cause the
results obtained. For a new situation, they cannot prove that introduction of
the intervention alone would be sufficient to expect similar results. This
is because there might be unidentified confounding factors that also have to be
jointly present to obtain similar results. For example, for the RE on school
attendance rate, a factor which
has to be jointly necessary might be close proximity of the
school to the villages. REs cannot identify such factors. So, some might contend that external claims are
inductively invalid since we cannot confirm the presence of such
confounding factors.
However
such an argument fails to take into account there are numerous subjects being tested in a RE. Given
that allocation of the subjects into experimental and control groups is random,
the presence of the necessary confounding variable would have occurred randomly
in it as well. The results obtained are hence an aggregation of subjects with
and without the confounding variable. Considering the probability of the
confounding variable being present in the new situation is similar to that of
the subjects being tested, the average impact would still be a good estimate.
Hence there is good justification for external claims.
In
Section 3, I discussed about how the presence of human free will poses a challenge for RE’s external claims to
achieve deductive validity. Some might extend that argument by asserting that inductive validity is also
impossible since there is no guarantee that individuals would behave in a similar manner even same
conditions are imposed.
Such an argument commits the fallacy of
composition by assuming that knowledge of how a group acts in response to an
intervention is
contingent on knowing how individual agents act. Admittedly, REs are limited in their ability to predict
an intervention’s impact
on an individual. However, this does not imply that external claims are not
justified when making prediction on large groups.
This
idea can be substantiated
by invoking David Stove’s “Law Of Large Numbers” argument (Stove, 1986). Stove argues that we are justified
to expect results to approximate to the actual probability when a large number
of cases are sampled.
To illustrate this, let’s assume that
a RE has determined that the chance of a teacher attending school because of a monitoring
scheme being implemented is
80%[4].
The pre-determined chance is the same regardless of whether the number of
subjects in the new projected situation is large or small. However, when the
same intervention is attempted, we are more justified in believing that the attendance
rate of teachers would
be approximately 80% when the number of subjects in the new situation is large.
For example, consider two schools with 100 and 5 teachers each. When the
monitoring scheme is implemented in both schools, we are more justified to
claim that attendance rate would be 80 out 100 rather 4 out of 5. This illustration establishes that for
external claims to attain inductive validity the number of subjects in the new
projected situation should be high.
5.
Conclusion
The problem of induction arguably
poses the most significant challenge to the epistemic status of REs’ external
claims. To respond to the problem, the possibility of either solving or evading
the problem was considered.
Through applying John
Foster’s NES, I demonstrated
that the problem of
induction is not intractable in all fields as Goodman claimed. The problem of
induction can indeed be solved in the case of Natural Science predictions.
However, RE’s external claims pertain to complex, indeterminable human
behaviour; as such it is impossible to validate the assumption of “uniformity
of nature”.
Lack of an effective solution does
not mean that the
epistemic status of REs’ external claims is undermined though.
Using Goodman’s argument
for evasion of the problem, I highlighted that it is only reasonable to expect
inductive statements to attain inductive validity rather than deductive validity. This
then raised a question of what constituted an inductively valid
inference.
To
this, I proposed that inferences must be law-like and have strong evidential support. Also, we
must note that REs can only provide an estimation of a trend for a large group
rather than determine how individuals would exactly behave in response to an
intervention. Hence, an additional criterion of the external claim being a
prediction of impact over a large group also was also included.
The first two criteria of inferences being law-like and having strong evidential
support are always met in an external claim because of the
very methodology of REs. Whether impact predictions based on RE
results, are made for large groups or not is determined by the user of the RE.
Fulfilling this criterion is certainly feasible.
Hence, it is possible for RE’s external claims
to be inductively valid and thus they can successfully evade the problem of induction. This means that the problem
of induction does not undermine the epistemic status of RE’s external claims. To conclude that external claims are knowledge would be however premature
as other epistemic challenges have to be considered as well. But it does mean
that external claims can still possibly be regarded as knowledge despite the
problem of induction.
[1] Randomised evaluations have been used in many fields of Economics.
However, in this paper, the term RE can be taken to exclusively mean randomised
evaluations used in Developmental Economics.
[2] The differences between internal and external
claims will be elaborated in Section 2.
[3] We have only demonstrated that NES is ineffective in solving the
problem of induction. There might be other possible solution which might
possibly be effective. Thus the assertion that the problem of induction is
intractable for REs has been couched in tentative terms.
[4] This illustration is
modified from the RE entitled, “Monitoring Works. Getting Teachers to Come to
School” (Hanna, 2005)