Assessing Economic Complexity with Input-Output Based Measures

Looking at the correlation coefficients of the early 1970s, a degenerate bundle exists with
the isolated measure M11 - CAIA, pointing to an autonomous emergent concept of economic
complexity, which did not persist into the 1990s.

4. CONCLUDING REMARKS

Connectedness is a crucial feature of input-output analysis, which can be used for
studying economic complexity as sectoral interdependence.

There are many ways to quantify connectedness, and it is a useful exercise to compare
different measures, both theoretically and empirically.

In this paper, a menu of twelve measures is presented and briefly discussed. All these
measures are quantified using an input-output database of nine OECD countries in the early
1970s and 1990s, which gives us an interesting inter-country comparison and shows us two
decades in the evolution of economic complexity as sectoral interdependence.

Looking at the absolute values of the measures, it appears that large economies (Japan
and USA) are more “intensely connected” (and so, more complex) than small ones (the
Netherlands, Denmark). It also appears that there is a slight reduction in complexity and a
decreasing dispersion of countries along the “interrelatedness scale”, with one peculiar
exception of complex upgrading (the UK).

A closer inspection of the values, applying a method of identifying emergent concepts
using the correlation coefficients, points to the emergence of three bundles of measures: a
Boolean-based group of two measures with weak correlation with all the others; a group of
eight measures based on all technical coefficients (and production multipliers), with strong
positive correlations between them and weak positive correlations with the Boolean group; a

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