The Significance of Value Additivity

Whether value is “additive,” that is, whether the value of a whole must equal the sum of the values of its parts, is widely thought to have significant implications in ethics. For example, additivity rules out “organic unities,” and is presupposed by “contrast arguments.” This paper reconsiders the significance of value additivity. The main thesis defended is that it is significant only for a certain class of “mereologies”, roughly, those in which both wholes and parts are “complete”, in the sense that they can exist independently. For example, value additivity is significant in the case of a mereology of material objects, but not in the case of a mereology of propositions.

A Tool Kit for Discounted Cash Flow Valuation: Consistent and Inconsistent Ways to Value Risky Cash Flows

The DCF method or multiples are used to value companies in practice. Starting with the value additivity principle, the paper presents a general framework for DCF valuation. This framework allows defining stepwise and aggregated approaches to value risky cash flows and identifying inconsistent approaches. The framework helps to integrate sales, contribution margin, operating leverage, and financial leverage into valuation approaches and shows the assumptions implied when multiples are used.

An Associative Approach to Additivity and Maximality Effects on Blocking

Schmajuk, Lam, and Gray (SLG, 1996) introduced an attentional-associative model able to describe a large number of classical paradigms. As other models, the SLG model describes blocking in terms of the competition between the blocker and the blocked conditioned stimulus (CS) to gain association with the unconditioned stimulus (US) or outcome. Recent data suggest, however, other factors together with competition might control the phenomenon. For instance, Beckers et al. (2005) reported that blocking and backward blocking are stronger when participants are informed that (a) the predicted US is submaximal than when it is maximal, and (b) the predictions of the US by the CSs are additive than when they are sub-additive. Submaximality refers to the evidence that the predicted US is weaker than its maximal possible value. Additivity denotes the fact that two CSs, each one independently predicting a given US, predict a stronger US when presented together. Beckers et al. suggested that their results are better explained by inferential accounts, which assume involvement of controlled and effortful reasoning, than by associative views. This chapter shows that a configural version of the SLG attentional-associative model is able to quantitatively approximate submaximality and additivity effects on blocking while providing a mechanistic explanation of the results. In general, the chapter illustrates the potential of associative models to account for newly discovered properties of known psychological phenomena.