We propose life history (LH) theory as an overarching theoretical explanation of CEO preferences and decision-making. LH theory has the potential to integrate prior research on variation in top executives’ impact on decision outcomes and to demonstrate how observable differences in behavior can be explained by evolutionary drivers. According to LH theory, individuals pursue fast or slow LH strategies. Fast individuals tend to follow accelerated reproduction strategies and engage in impulsive, opportunistic, and risk-seeking behavior. We theorize how CEO LH strategies shape both on-the-job and off-the-job decisions and thus add to a growing body of research on evolutionary drivers of preferences and decision-making in accounting. We measure CEO LH strategies based on biodemographic micro-data related to reproductive behavior. Our findings linked to on-the-job decisions suggest that firms managed by CEOs who pursue fast LH strategies exhibit more financial irregularities, lower accounting conservatism, and higher earnings management. Findings related to CEO off-the-job decisions show that fast CEOs are more likely to engage in criminal behavior and to have a higher conspicuous consumption and a higher personal leverage. By applying an LH theory lens, we reconcile and advance prior fragmented research on CEO preferences by showing a clear theoretical link between on-the-job and off-the-job decisions.

We present estimators for nonparametric functions that are nonadditive in unobservable random terms. The distributions of the unobservable random terms are assumed to be unknown. We show that when a nonadditive, nonparametric function is strictly monotone in an unobservable random term, and it satisfies some other properties that may be implied by economic theory, such as homogeneity of degree one or separability, the function and the distribution of the unobservable random term are identified. We also present convenient normalizations, to use when the properties of the function, other than strict monotonicity in the unobservable random term, are unknown. The estimators for the nonparametric function and for the distribution of the unobservable random term are shown to be consistent and asymptotically normal. We extend the results to functions that depend on a multivariate random term. The results of a limited simulation study are presented.

Prepared under Contract no. EX-76-A-01-2295, Task order 37.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Economics and Social Science, 1962.

With climate change as prototype example, this paper analyzes the implications of structural uncertainty for the economics of low-probability, high-impact catastrophes. Even when updated by Bayesian learning, uncertain structural parameters induce a critical “tail fattening” of posterior-predictive distributions. Such fattened tails have strong implications for situations, like climate change, where a catastrophe is theoretically possible because prior knowledge cannot place sufficiently narrow bounds on overall damages. This paper shows that the economic consequences of fat-tailed structural uncertainty (along with unsureness about high-temperature damages) can readily outweigh the effects of discounting in climate-change policy analysis.

W l THAT have we learned from ComIV Vmission on Money and Credit about processes and responses in monetary policy? So far as I can see, from Report itself, very little but perhaps experts in monetary economics were not a significant part of audience at whom Report was aimed. So most fruitful course may be to turn primarily to staff papers. Here there is substantial evidence of quantity theory reborn at least in sense that money matters a good deal in determining aggregate spending on current output and of an important postwar change in monetary theory. As noted in my introduction to this volume, this postwar shift in theory is centered in approach to demand for money and other assets. In this theory, channels through which variations in money supply affect levels of income and employment include not only a change in the interest but also changes in relative prices of all assets-real and financialwhich in turn lead to shifts in spending on existing assets and currently produced goods and services. Thus in its extreme form approach suggests that we need to look not at one interest rate but at an extremely large number, including implied interest rates on all real assets and including consumer goods of any degree of durability. In logical terms, this approach offers an elegant rapprochement for devotees of and quantity-theory approaches to role of money, and for monetary-versus-fiscal policy disputes since I930's. If look prevails, we may look back at much of this controversy as a good deal less significant than it has seemed en route. The great controversy over Is savings really equal to investment? of late I930's and early I940's springs to mind. But agreement on this mechanism doesn't necessarily tell us how important money is quantitatively. If we look at staff papers (or at least, at sample I managed), what does professional support for renaissance of money and monetary policy amount to? Friedman and Meiselman, as might be expected, plump for money as a prime determinant of level of spending on current output, and show convincingly that a simple, traditional monetary model versus a simple traditional Keynesian model test gives verdict clearly to stability for velocity over stability for ratio of autonomous to income, including cases where reasonable lags are introduced. Moreover, they go on to spell out portfolio balancing mechanism as at least a plausible mechanism through which this monetary effect may be exerted. If we take Section VI of their paper as a statement of new monetary orthodoxy, on intellectual grounds at least a good deal of basis for long quarrel between monetary and Keynesian economists has been reasoned (or compromised) away. Few, even most ardent neo-Keynesians, would disagree that impact of open market operations may be through spreading net which Friedman and Meiselman spell outnot merely through one (bond) interest rate alone acting on investment decisions. The major challenge to now generally accepted fiscal policy position as our really powerful stabilization tool becomes a strong one if a reasonably stable demand for money is added to mechanism as at least Friedman and Meiselman argue. The C.M.C. staff papers contain no empirical answer to Friedman and Meiselman challenge to show better results with another model. Tobin, in his paper on debt policy, provides an elegant statement of a very similar mechanism through which changes in money stock and liquidity may influence spending decisions on current output through rebalancing of asset portfolios. But I hope it will not be too dissident a note to suggest that we really know very little empirically about validity of this description of channels of monetary policy; and that elaborate portfolio-balancing general equilibrium approach lacks intuitive appeal

Of the behavioral recommendations garnered from modern capital market theory, few, if any, generalizations have been documented as convincingly as the simple advice to hold several assets in one's portfolio. Sharpe made such a conclusion perfectly clear when he stated [27, p. 184]:If the market is efficient and if an investor is privy to no special information or predictive power, what should he do? First, and most important: diversify.

It appears to a widely held view that corporations with similar operational characteristics ought to have similar financial characteristics. For example, one might expect that the financial characteristics of two drug companies would be similar. This seems entirely reasonable. Unfortunately however, there does not appear to be any quantitative analysis of this point in the literature. Furthermore, discussions with our financial colleagues lead to the conclusion that, if such financial differentiation of corporations were possible, it is by no means obvious what the variables of differentiation would be. Consequently, such an analysis was undertaken and is described in this paper. The basic question asked is whether the statistical grouping of corporations by their financial characteristics is similar to their predetermined, external, industrial classification.