Trade and Employment From Myths to Facts - International Labour ...

Trade and Employment: From Myths to Facts
to the country unit without affecting the results. In the imagined randomized trial,
most subjects will be from the large countries, randomly assigned to one group or
the other. 44
In the following, the discussion is structured around three types of regressions
that have typically been conducted when analysing the relationship between trade
and employment. The first subsection discusses an exercise in which sectoral information
is explored to analyse how import penetration has affected sectoral
employment within one single country. In the second subsection, the relationship
between trade and the wage premium is discussed, a relationship that has been the
object of a large body of econometric work. Last, but not least, a cross-country
analysis is presented.
Box 3-9: Econometrics: A reminder of the basics
To evaluate the econometric work done on the issue of trade and employment, it is
best to keep in mind several basic ideas about what the method entails:
• First, all econometric models are (or should be) designed to mimic a randomized
controlled trial. Hence, pick a group of country subjects, randomly assign them to
two groups. Let one trade and the other not and then measure the employment
response after a determinate length of time.
• Second, when working with observational data, the default interpretation of the results
should be that the observations are correlated and that no causal relationship
can be imputed. This “guilty until proven innocent” approach is the recommended
way to avoiding type I errors, failing to reject a false hypothesis. This is because
the overwhelming majority of theories in economics involve simultaneous causality. 45
• Third, econometric tests can never “prove” anything. All that is possible is to fail
to reject a theory that seems correct.
• Fourth, econometric methods cannot distinguish between theories since any given
set of observations is likely to fail to contradict some theory. Data do generate theories,
and working backward from data to theory ensures that the data will fail to
contradict the theory and so will be of no intellectual value.
• Fifth, econometric models can test a theory “all up” in the sense of the overall
direction of causality between independent and dependent variables, or it can test
a component of a theory that is necessarily true if the theory as a whole is to work.
44 Sometimes this can be done, or approximately so. Consider the coastal cities of China that are
heavily involved in world trade. The rural counterpart is not, so in some sense there is a natural
experiment. On closer inspection, the example fails, however, since the assumption that coastal and
rural Chinese are statistically identical is obviously problematic. When subjects can self-sort into
one of the two groups, control or treatment, the results are subject to “selection bias” and are
generally not valid. See Kennedy (1998) for a non-technical discussion of selection bias.
45 Paraphrasing Kennedy (1998), for any given set of variables some researcher is hoping that there
will be a discernible relation between one and the others, while some other is hoping that there
will not be (because of multi-collinearity).
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