Some years ago, I started doing research on...
Some years ago, I started doing research on the impacts of increasing economic integration with a focus on the heterogenous developmental trajectories emerging from such an integration (see, e.g., here or here for some outcomes). When reviewing the relevant literature, we became aware of an interdisciplinary gap that arises when it comes to operationalizing ‘economic integration’ or ‘economic openness’. While (mainstream) economists tend to proxy economic openness by dividing total trade volume through GDP (usually dubbed as “trade-to-GDP ratio”), sociologists preferred to divide trade volume through population size. What might seem to be a minor difference at first sight can have profound implications: the second strategy gives us something like “trade volume per capita” (by dividing though population size N) while the former also takes into account the average income as an additional variable to correct for (the denominator can be effectively written as GDP = GDP/N * N). In other words, the economists‘ way of measuring openness makes rich countries look more ‘closed’ and poor countries look more ‘open’, relative to an approach that captures the size of an economy based only on population size.
As these nuances can result in significant differences for certain applications (e.g. when creating simple ‘rankings’ of economic openness), it’s easy to see why it is imperative that we think thoroughly about the choice of measures we use. In the case of economic openness, the issue may quicly become even more pernicious if we consider that most established measures are based solely on trade activity and neglect the financial component of economic integration.
This short story on different conceptualizations and measurement strategies of economic openness just illustrates a classic argument from philosophy of science, namely that our measurements are often underpinned by implicit or explicit theoretical considerations. This ‘theory-ladenness’ of observational data is not much concern for the large majority of economists, who are mostly happy to use whichever measure is established, i.e. used widely or, at least, used widely in the top journals ;-) But for heterodox economists, this feature presents an additional burden as (1) established measures might not fit our own theoretical preconceptions (and hence, have to be adapted to better conform to our research interest) and/or (2) might be based on misleading, but often hidden assumptions (which requires us to critically reflect on established measures and, potentially, suggest alternatives).
It is, for instance, widely accepted that GDP is a misleading measure of economic soundness that comes with a series of value judgements. Hence, it is a prime example for theory-ladenness in general, but it also serves well to illustrate the two more subtle points on measurement issues sketched above. For instance, Shaik’s and Tonak’s classic book “Measuring the wealth of nations: the political economy of national accounts” represents an effort to translate conventional national accounts into a classic-marxist framework to better differentiate between productive and unproductive labor (where the latter includes components like policing, marketing or finance) to arrive at alternative estimates for national income. In this example, an existing measurement scheme is reinterpreted in light of an alternative theoretical approach.
Also relevant is the typical handling of GDP data, which is affected by hidden assumptions, and serves to illustrate the second obligation of the heterodox economist; namely, to detect and potentially raise awareness of such implicit assumption built into our measurement-strategies. One such implicit assumption often taken for granted by most, is that the growth rate of average GDP/capita is to be seen as the ‘representative’ growth rate for any economy. Few recognize that this decision prioritizes the ensemble average (i.e. the growth of mean income) over the time-average (i.e. the mean growth of income). In other words, our measure of GDP growth is not at all sensitive to the question of to whom aggregate growth accrues; a measure of GDP growth based on time averages, on the other hand, would provide such a sensitivity. More specifically, a time average-based GDP measure would be higher (lower), compared to the conventional one, when society becomes more equal (unequal) in relative terms (more can be found in this neat paper).
While this argument might seem a little subtle at first it has a clear-cut relation to heterodox theorizing as the conventional measure for growth rates seemingly relies on a form of ergodicity assumption. I deliberately say “form of” as the formal definition of an ergodic system amounts to the assumption that ensemble and time average always conincide, which seems not to be the intention here. Rather, the time average is simply declared irrelevant – although it can be highly informative when dealing with non-ergodic systems (like, presumably, our economies). Alternatively, this difference between ensemble and time average in the context of GDP growth can also be framed in terms of conventional welfare theory: conventional measures suggest that income translates linearly into utility (and, hence, distribution can be neglected for welfare consideration), while measures based on a time average would assume diminishing utility with respect to income (and, hence, distribution matters for welfare).
Maybe I simply have some ill-guided affection for digging too much into foundations ;-) But you might agree with me that careful reflection of these foundations is often essential and, at the same time, has great potential to help us to put our perspective into place and gain important insights along the way.*
All the best,
Jakob
* See also here for an alternative example relating to Tobin’s q.
PS: In our distinctive pluralist spirit, we have collected all calls form heterodox associations for next year’s ASSA-meeting in a single post, which provides a neat overview on your options when aiming to visit San Antonio in early 2024!