We analyze the long-term workforce composition when the quality of mentoring available to majority and minority juniors depends on their representation in the workforce. A workforce with at least 50 percent majority workers invariably converges to one where the majority is overrepresented relative to the population. To maximize welfare, persistent interventions, such as group-specific fellowships, are often needed, and the optimal workforce may include minority workers of lower innate talent than the marginal majority worker. We discuss the role of mentorship determinants, talent dispersion, the scope of short-term interventions, various policy instruments and contrast our results to the classic fairness narrative.
Exploratory ventures outside the established disciplinary boundaries can yield added insights and explanatory power. Imposing cognitive limitations on human logical reasoning ability (bounded rationality) is a well-known case in point. Extending cognition to parts of body outside the brain, and to environment outside the body is another. In contrast, the present article takes a constructive approach, also in an exploratory spirit. For the sake of exposition, we consider three tiered realms of scientific inquiry: physical or inanimate, biological or animate, and socio-psychological or sentient. In this three-tier framework, we explore the extent of gains in modeling human action within the confines of physical principles such as optimization. In this exercise, concepts of complexity and emergence account for the absence of analytically derivable mapping from micro or finer grain phenomena to macro or coarser grain phenomena. A general notion of embodiment captures the inclusion of a more expansive range of explanatory factors in modeling and understanding a given phenomenon. Emergence and embodiment play complementary roles in exploration of human behavior.
Limit theory is developed for least squares regression estimation of a model involving time trend polynomials and a moving average error process with a unit root. Models with these features can arise from data manipulation such as overdifferencing and model features such as the presence of multicointegration. The impact of such features on the asymptotic equivalence of least squares and generalized least squares is considered. Problems of rank deficiency that are induced asymptotically by the presence of time polynomials in the regression are also studied, focusing on the impact that singularities have on hypothesis testing using Wald statistics and matrix normalization. The paper is largely pedagogical but contains new results, notational innovations, and procedures for dealing with rank deficiency that are useful in cases of wider applicability.
There is a growing debate about whether upzoning is an effective policy response to housing shortages and unaffordable housing. This paper provides empirical evidence to further inform debate by examining the various impacts of recently implemented zoning reforms on housing construction in Auckland, the largest metropolitan area in New Zealand. In 2016, the city upzoned approximately three quarters of its inner suburban land to facilitate construction of more intensive housing. We use a quasi-experimental approach to analyze the short-run impacts of the reform on construction, allowing for potential shifts in construction from non-upzoned to upzoned areas (negative spillovers) that would, if unaccounted for, lead to an overestimation of treatment effects. We find strong evidence that upzoning stimulated construction. Treatment effects remain statistically significant even under implausibly large spillovers that would necessitate a six-fold increase in the trend rate of construction in control areas under the counterfactual of no-upzoning. Our findings support the argument that upzoning can stimulate housing supply and suggest that further work to identify factors that mediate the efficacy of upzoning in achieving wider objectives of the policy would assist policymakers in the design of zoning reforms in the future.
We study personalized pricing (or first-degree price discrimination) in a general oligopoly model. In the short-run, when the market structure is fixed, the impact of personalized pricing hinges on the degree of market coverage (i.e., how many consumers buy). If coverage is high (e.g., because the production cost is low, or the number of firms is large), personalized pricing intensifies competition and so harms firms but benefits consumers, whereas the opposite is true if coverage is low. However in the long-run, when the market structure is endogenous, personalized pricing always benefits consumers because it induces the socially optimal level of firm entry. We also study the asymmetric case where some firms can use consumer data to price discriminate while others cannot, and show it can be worse for consumers than when either all or no firms can personalize prices.
We study personalized pricing in a general oligopoly model. When the market structure is fixed, the impact of personalized pricing relative to uniform pricing hinges on the degree of market coverage. If market conditions are such that coverage is high, personalized pricing harms firms and benefits consumers, whereas the opposite is true if coverage is low. However, when the market structure is endogenous, personalized pricing benefits consumers because it induces socially optimal firm entry. Finally, when only some firms have data to personalize prices, consumers can be worse off compared to when either all or no firms personalize prices.