Cognitive Comparative Advantage and the Organization of Work: Lessons from Herbert Simon's Vision of the Future

In a marvelous but somewhat neglected paper, 'The Corporation: Will It Be Managed by Machines?' Herbert Simon articulated from the perspective of 1960 his vision of what we now call the New Economy the machine-aided system of production and management of the late twentieth century. Simon's analysis sprang from what I term the principle of cognitive comparative advantage: one has to understand the quite different cognitive structures of humans and machines (including computers) in order to explain and predict the tasks to which each will be most suited. Perhaps unlike Simon's better-known predictions about progress in artificial intelligence research, the predictions of this 1960 article hold up remarkably well and continue to offer important insights. In what follows I attempt to tell a coherent story about the evolution of machines and the division of labor between humans and machines. Although inspired by Simon's 1960 paper, I weave many other strands into the tapestry, from classical discussions of the division of labor to present-day evolutionary psychology. The basic conclusion is that, with growth in the extent of the market, we should see humans 'crowded into' tasks that call for the kinds of cognition for which humans have been equipped by biological evolution. These human cognitive abilities range from the exercise of judgment in situations of ambiguity and surprise to more mundane abilities in spatio-temporal perception and locomotion. Conversely, we should see machines 'crowded into' tasks with a well-defined structure. This conclusion is not based (merely) on a claim that machines, including computers, are specialized idiots-savants today because of the limits (whether temporary or permanent) of artificial intelligence; rather, it rests on a claim that, for what are broadly 'economic' reasons, it will continue to make economic sense to create machines that are idiots-savants.

Empirical Analysis of Credit Risk Regime Switching and Temporal Conditional Default Correlation in Credit Default Swap Valuation: The Market liquidity effect

In this paper, we extend the debate concerning Credit Default Swap valuation to include time varying correlation and co-variances. Traditional multi-variate techniques treat the correlations between covariates as constant over time; however, this view is not supported by the data. Secondly, since financial data does not follow a normal distribution because of its heavy tails, modeling the data using a Generalized Linear model (GLM) incorporating copulas emerge as a more robust technique over traditional approaches. This paper also includes an empirical analysis of the regime switching dynamics of credit risk in the presence of liquidity by following the general practice of assuming that credit and market risk follow a Markov process. The study was based on Credit Default Swap data obtained from Bloomberg that spanned the period January 1st 2004 to August 08th 2006. The empirical examination of the regime switching tendencies provided quantitative support to the anecdotal view that liquidity decreases as credit quality deteriorates. The analysis also examined the joint probability distribution of the credit risk determinants across credit quality through the use of a copula function which disaggregates the behavior embedded in the marginal gamma distributions, so as to isolate the level of dependence which is captured in the copula function. The results suggest that the time varying joint correlation matrix performed far superior as compared to the constant correlation matrix; the centerpiece of linear regression models.