Towards the Methodological Turn in the Philosophy of Science - Mechanism and Causality in Biology and Economics - page 10

mechanisms is employed by philosophers and scientists in a sense to contrast with
black boxes. But whether mechanisms can be completely known remains under
debate. For instance, in the above-mentioned economic approaches of mechanism
design and input-output analysis, the mechanism of the economy is regarded as
being perceivable, given suitable tools—mathematical methods for mechanism
design and statistical analysis for the input-output analysis—exist. As Leontief
put it, to understand an economy requires nothing but a “direct structural analysis,”
like a mechanic looking under the hood (Leontief 1954 ). Leontief thought not only
is such a direct observation possible, but it is the only promising way of under-
standing the operational characteristics of the economy (Leontief 1954 , p. 230). By
contrast, Trygve Haavelmo, the pioneer of the probabilistic approach to economet-
rics, used his famous mechanical analogy to illustrate the methodology of econo-
metric models (Haavelmo 1944 , pp. 27-8): The empirical relationship between the
amount of throttle and the speed of a car, under uniform circumstances, is regular.
Such a relationship is useful for driving a car in a prescribed speed, but is not
fundamental. The throttle-speed relationship not only lacks of autonomy because it
breaks down as the condition changes, but also, the relationship tells us little about
how the car works, hence it “leaves the whole inner mechanism of a car in complete
mystery” (Haavelmo 1944 , 371 p. 27).
Thus, while Haavelmo thought that understanding the inner mechanism is of
primary importance, he contrasted with the economists such as Leontief in think-
ing that a direct observation is impossible. This characterizes the practices of
econometricians, who have been trying to use a mix of tools from economics,
mathematics, and statistics to analyze empirical data and, in part, concerned
whether the data-generating process ,or DGP , that is regarded as being responsible
for producing the observed data is real or fictitious and whether it can be fully
known. 2 Ontology aside, many have maintained that econometric models do not
allow observation of the DGP directly. One can receive only an incomplete image
of the underlying structure by inferring from observed data. Because, unlike a
mousetrap, scientific mechanisms are usually not available for direct observation,
hopes for complete descriptions of mechanisms and/or causal structures would be in
vain.
Even so, the incomplete notions of mechanisms and causal structures are still
useful for understanding science. In order to represent the underlying mechanism,
scientists use what MDC called “mechanism schemata” or “mechanism sketches”
as incomplete description. For them, mechanism sketches are black boxes, serving
to indicate required future research work in order to establish mechanism schemata.
Mechanism schemata, in contrast, contain more, but still incomplete, information
and are usually represented by diagrams. Since neither sketches nor schemata are
thorough and detailed, to understand mechanisms via sketches and schemata might
be related to the “black box inference” in the philosophy of science. Although the
term was made famous by Sober ( 1998 ) who discussed particularly the linkage
2 See Chao ( 2009 , esp. Ch. 7) for the philosophical discussion on the DGP.