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Social consumption: The world of veblen revisited
Abstracts / Mathematical Social Sciences 30 (1995) 319-329
323
• Causal effects are fundamentally comparisons of potential outcomes, not coefficients in regression or structural equation models, although there can be relationships between such coefficients and causal effects. • Even assuming random assignment of the instrument, instrumental variables estimators only estimate causal effects under specific assumptions about the potential outcomes (i.e. stability, exclusion restriction, monotonicity), under which the estimand equals the 'complier average causal effect' (CACE). • With fixed data, differences between the quantity estimated by the instrumental variables estimator (i.e. the instrumental variables estimand = IVE) and CACE can be explored using sensitivity analyses to investigate violations of stability, exclusion and monotonicity assumptions. • Even when the assumptions hold, so that IVE = CACE, standard instrumental variables techniques generally provide inferior inferences for the causal estimand. • Principled inference for CACE generally requires the use of Bayesian methods in the presence of missing data, which are now highly developed, both conceptually and computationally. • Posterior predictive check distributions can provide frequency-valid p-values under Fisher null hypotheses, which although analogous to intent-to-treat tests, have greater power against alternatives that incorporate information about compliance and science, and therefore, under realistic assumptions, can dominate standard intent-to-treat tests according to their own criteria. Social Consumption: The World of Veblen Revisited. Gary S. Becker, University
Professor of Economics and Sociology, University of Chicago, 1126 East 59th Street, Chicago, IL 60637, USA In many situations the demand by an individual for a good or activity depends on the composition of the other persons who consume the same good or activity. We consider the effects of such dependence in the context of two groups, which for simplicity we call leaders and followers. We assume that both leaders and followers prefer to consume goods consumed mainly by leaders. We consider the type of market equilibria that emerge, especially the degree of segregation and integration between the leaders and followers in their consumption and related behavior. The equilibria depend crucially on the type of supply responses that are feasible. Firms gain if they can discover ways to separate leaders because leaders are then willing to pay more. We consider several competitive equilibria, including differences in the qualities of goods, new goods with high prices due to relatively little learning-by-doing experience, and high prices due to intrinsic limits on quantity, such as in first editions, master paintings, old photographs, and other 'old' goods.
324
Abstracts / Mathematical Social Sciences 30 (1995) 319-329
We also consider trademarks and advertising as ways to tailor goods to leaders. This analysis can explain the common lament that says designer jeans and other fashion goods are priced much higher than can be justified by the quality of the goods. This may be precisely why such goods are popular! We give examples of behavior, such as restricting the distribution of trademarked goods, that is consistent with our interpretation.
On the Interpretation of Decision Problems with Imperfect Recall. Ariel Rubinstein, Professor of Economics, Tel Aviv University, Ramat-Aviv, 69978 Tel Aviv, Israel In this paper it is argued that extensive decision problems (extensive games with a single player) with imperfect recall suffer from major ambiguities in the interpretation of information sets and strategies. This indeterminacy allows for different kinds of analysis. We address the following issues: (1) Randomization of information sets. (2) Consistency of beliefs and time consistency of optimal plans. (3) The multi-selves approach to decision making. (4) Methods of inference of past choices. We illustrate our discussion through an example that we call the 'absentminded driver paradox'.
Safety Factors in Biological Systems: Molecules, Organs and Evolutionary Systems. Jared M. Diamond, Department of Physiology, UCLA, Los Angeles, CA 90095,
USA A major unsolved problem at the interface between physiology and evolutionary biology is: What sets the quantity of any physiological or anatomical component? For example, how is an enzyme's activity, a tissue's mass, a bone's strength, or an iron channel's membrane density determined? Much of modern biology is concerned with the proximate mechanisms setting these quantities, such as rates of protein synthesis and degradation- hence, enzyme activity or tissue m a s s - a t their observed levels. For any physiological component one can calculate its safety factor as the ratio of its capacity to its maximum natural load. It turns out that measured safety factors mostly fall in the range 1.2-10. This observed variation in safety factors can be understood in terms of the varying costs and benefits of excess capacity. Such evolutionary considerations provide a quantitative framework for understanding physiological design. Essentially the same questions of safety factors arise for our engineered structures: How much more strongly do we design our elevator cables, bridges, and buildings than they 'need' to be? Why are safety factors designed to be higher for wooden
323
• Causal effects are fundamentally comparisons of potential outcomes, not coefficients in regression or structural equation models, although there can be relationships between such coefficients and causal effects. • Even assuming random assignment of the instrument, instrumental variables estimators only estimate causal effects under specific assumptions about the potential outcomes (i.e. stability, exclusion restriction, monotonicity), under which the estimand equals the 'complier average causal effect' (CACE). • With fixed data, differences between the quantity estimated by the instrumental variables estimator (i.e. the instrumental variables estimand = IVE) and CACE can be explored using sensitivity analyses to investigate violations of stability, exclusion and monotonicity assumptions. • Even when the assumptions hold, so that IVE = CACE, standard instrumental variables techniques generally provide inferior inferences for the causal estimand. • Principled inference for CACE generally requires the use of Bayesian methods in the presence of missing data, which are now highly developed, both conceptually and computationally. • Posterior predictive check distributions can provide frequency-valid p-values under Fisher null hypotheses, which although analogous to intent-to-treat tests, have greater power against alternatives that incorporate information about compliance and science, and therefore, under realistic assumptions, can dominate standard intent-to-treat tests according to their own criteria. Social Consumption: The World of Veblen Revisited. Gary S. Becker, University
Professor of Economics and Sociology, University of Chicago, 1126 East 59th Street, Chicago, IL 60637, USA In many situations the demand by an individual for a good or activity depends on the composition of the other persons who consume the same good or activity. We consider the effects of such dependence in the context of two groups, which for simplicity we call leaders and followers. We assume that both leaders and followers prefer to consume goods consumed mainly by leaders. We consider the type of market equilibria that emerge, especially the degree of segregation and integration between the leaders and followers in their consumption and related behavior. The equilibria depend crucially on the type of supply responses that are feasible. Firms gain if they can discover ways to separate leaders because leaders are then willing to pay more. We consider several competitive equilibria, including differences in the qualities of goods, new goods with high prices due to relatively little learning-by-doing experience, and high prices due to intrinsic limits on quantity, such as in first editions, master paintings, old photographs, and other 'old' goods.
324
Abstracts / Mathematical Social Sciences 30 (1995) 319-329
We also consider trademarks and advertising as ways to tailor goods to leaders. This analysis can explain the common lament that says designer jeans and other fashion goods are priced much higher than can be justified by the quality of the goods. This may be precisely why such goods are popular! We give examples of behavior, such as restricting the distribution of trademarked goods, that is consistent with our interpretation.
On the Interpretation of Decision Problems with Imperfect Recall. Ariel Rubinstein, Professor of Economics, Tel Aviv University, Ramat-Aviv, 69978 Tel Aviv, Israel In this paper it is argued that extensive decision problems (extensive games with a single player) with imperfect recall suffer from major ambiguities in the interpretation of information sets and strategies. This indeterminacy allows for different kinds of analysis. We address the following issues: (1) Randomization of information sets. (2) Consistency of beliefs and time consistency of optimal plans. (3) The multi-selves approach to decision making. (4) Methods of inference of past choices. We illustrate our discussion through an example that we call the 'absentminded driver paradox'.
Safety Factors in Biological Systems: Molecules, Organs and Evolutionary Systems. Jared M. Diamond, Department of Physiology, UCLA, Los Angeles, CA 90095,
USA A major unsolved problem at the interface between physiology and evolutionary biology is: What sets the quantity of any physiological or anatomical component? For example, how is an enzyme's activity, a tissue's mass, a bone's strength, or an iron channel's membrane density determined? Much of modern biology is concerned with the proximate mechanisms setting these quantities, such as rates of protein synthesis and degradation- hence, enzyme activity or tissue m a s s - a t their observed levels. For any physiological component one can calculate its safety factor as the ratio of its capacity to its maximum natural load. It turns out that measured safety factors mostly fall in the range 1.2-10. This observed variation in safety factors can be understood in terms of the varying costs and benefits of excess capacity. Such evolutionary considerations provide a quantitative framework for understanding physiological design. Essentially the same questions of safety factors arise for our engineered structures: How much more strongly do we design our elevator cables, bridges, and buildings than they 'need' to be? Why are safety factors designed to be higher for wooden