Journal of Evolutionary Economics

This paper examines the effects of bribery on product and process innovation at the firm level in Latin American countries. We provide insights into the heterogeneous effects of bribery on the types of innovations across firms. Using the locality-sector average of bribe payments as a percentage of firm annual sales, we control for endogeneity bias, which is a recurring econometric problem in corruption-innovation studies. Overall, we find evidence to support the ‘sand the wheels’ hypothesis and argue that this negative effect is slightly higher in process innovation compared to product innovation. Using interaction terms to see the effects of bribery on different firm sizes and institutional structures, we find that bribery hurts firm innovation for micro and small firms, but not for large firms. The results also suggest that the negative effect of corruption on firm level innovation is stronger for firms in weak institutional environments than for firms in strong institutional settings. Practical interventions to promote strong institutional governance are not easy to arrange when corruption is endemic. Greater awareness of the extortionist environment of companies in these countries in the international community may bring pressures to bear for reform.

Two alternative views of an economy are combined and studied. The first view is that of technological evolution as a process of combinatorial innovation. Recently a simple mathematical model (TAP) was introduced to study such a combinatorial process. The second view is that of a network of product transformations forming an autocatalytic set. Autocatalytic (RAF) sets have been studied extensively in the context of chemical reaction networks. Here, we combine the two models (TAP and RAF) and show that they are compatible. In particular, it is shown that product transformation networks resulting from the combinatorial TAP model have a high probability of containing autocatalytic (RAF) sets. We also study the size distribution and robustness of such “economic autocatalytic sets”, and compare our results with those from the chemical context. These initial results strongly support earlier claims that the economy can indeed be seen as an autocatalytic set, and reconcile seemingly opposing views of evolution vs. mutualism in economics.

We consider the implications for general equilibrium theory of the problems of consistency and completeness as shown in the Gödel-Rosser theorems of the 1930s. That a rigorous consistent formal system is incomplete poses serious problems for dealing with unresolved problems in a fully formal system such as general equilibrium theory. We review the underlying mathematical issues and apply them to this problem for general equilibrium theory. We also consider alternative approaches such as agent-based modeling founded on empirically estimated behavioral assumptions for agents that may allow for a better way to model non-equilibrium evolutionary economic dynamics.

Mark Perlman, one of the preeminent historians of economics, was subject to many and varied influences throughout his long career. Among the more indirect influences was the work of Joseph Schumpeter. While indirect, Schumpeter’s writings were held in high esteem, as Perlman considered his work authoritative. One can see shades of Schumpeter in many of Perlman’s own writings in the history of economics.

In this paper, we study transmission of traits through generations in multifactorial inheritance models with sex- and time-dependent heritability. We further analyze the implications of these models under heavy-tailedness of traits’ distributions. Among other results, we show that in the case of a trait (for instance, a medical or behavioral disorder or a phenotype with significant heritability affecting human capital in an economy) with not very thick-tailed initial density, the trait distribution becomes increasingly more peaked, that is, increasingly more concentrated and unequally spread, with time. But these patterns are reversed for traits with sufficiently heavy-tailed initial distributions (e.g., a medical or behavioral disorder for which there is no strongly expressed risk group or a relatively equally distributed ability with significant genetic influence). Such traits’ distributions become less peaked over time and increasingly more spread in the population. The proof of the results in the paper is based on the general results on majorization properties of heavy-tailed distributions obtained recently in Ibragimov (Econom Theory 23: 501–517, 2007) and also presented in the author’s Ph.D. dissertation (Ibragimov, New majorization theory in economics and martingale convergence results in econometrics. Yale University, 2005) and several their extensions derived in this work.