Assessing Economic Complexity with Input-Output Based Measures



(living) systems (Finn 1976, Zucchetto 1981, Bosserman 1982, Ulanovicz 1983) and the
complexity of social networks (Wasserman and Faust 1994, Jackson 2006).

These measures were chosen from among those input-output methodologies directly
giving (or making it possible to deduce) holistic indexes of connectedness that can be
considered good indicators or proxies of complexity as sectoral interdependence. In order to
fully understand and quantify economic complexity in this sense, these measures should be
complemented with other forms of uncovering structures, such as qualitative input-output
analysis based on the theory of directed graphs (Czamansky 1974, Campbell 1975, Aroche-
Reys 2003), minimum flow analysis (Schnable 1994, 1995), fields of influence and feedback
loops analysis (Sonis and Hewings 1991, Sonis et al. 1997, van der Linden et al. 2000), the
concept of important coefficients (Jensen and West 1980, Aroche-Reys 1966), the
fundamental economic structure approach (Simpson and Tsukui 1965, Jensen et al. 1987,
Thakur 2008), and the neural network approach to input-output analysis (Wang 2001),
among others.

The structure of this paper is as follows: in section 2, the measures of complexity are
presented and briefly discussed; in section 3, a detailed quantification is made of economic
complexity as connectedness, applying the rich menu of (input-output) measures presented in
the previous section and confronting them empirically, using the interindustry tables of
several OECD countries; and section 4 concludes the paper.



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