Inferring Inequality With Home Production

We revisit the causes, welfare consequences, and policy implications of the dispersion in households' labor market outcomes using a model with uninsurable risk, incomplete asset markets, and home production. Allowing households to be heterogeneous in both their disutility of home work and their home production efficiency, we find that home production amplifies welfare‐based differences, meaning that inequality in standards of living is larger than we thought. We infer significant home production efficiency differences across households because hours working at home do not covary with consumption and wages in the cross section of households. Heterogeneity in home production efficiency is essential for inequality, as home production would not amplify inequality if differences at home only reflected heterogeneity in disutility of work.

A UNIFIED FRAMEWORK FOR OPTIMAL TAXATION WITH UNDIVERSIFIABLE RISK

This paper considers a model of linear capital taxation for an economy where capital and labor income are subject to idiosyncratic uninsurable risk. To keep the model tractable, we assume that investment decisions are made before uncertainty is realized, so that the realization of the capital and labor income shocks only affects current consumption. In this setting, we are able to jointly analyze capital and labor income risk and derive analytical results regarding the optimal taxation of capital. We find that the optimal capital tax is positive in the long run if there is only capital income risk. The reason for this is that the capital tax provides insurance against capital income risk. Furthermore, for high levels of risk, increasing the capital tax may actually induce capital accumulation. On the other hand, if there is only labor income risk, the optimal capital tax is zero. The sign of the optimal tax can only be negative if the two types of risk are negatively correlated and labor income risk is large enough.

Forensic Engineering: Professional Liability Risks of Engineering Sustainable Materials and Systems, Designing for Durability, and Pushing Materials to Their Limits

<p>Professional engineers in the US may be found negligent and therefore liable for damages arising from failure to exercise a level of care, diligence, and skill exercised by other reputable practitioners in similar circumstances in an effort to accomplish the purpose for which the professional engineer was hired. If the professional engineer has accepted the obligation to design for sustainability or durability, or where materials, elements, or assemblies are intended by design to be “pushed to their limits” in normal service, the professional engineer may be accepting an extreme or uninsurable risk.</p><p>The subject of this paper is the standard of care and the relationship between the standard of care and design for sustainability or durability, or design where the engineered features are expected to be “pushed to their limits” in normal service. The paper’s contents include 1) an explanation of the concept of the standard of care, and 2) the professional liability pitfalls inherent in a design effort intended to result in sustainability or durability, or intended to achieve limit-state behavior in normal service. The subject is relevant for practitioners wishing to understand professional responsibilities for such designs.</p>

An Assessment of Experimental Evidence on Agricultural Technology Adoption in Developing Countries

This article reviews recent results on technology adoption in developing countries, primarily from field experiments. It focuses on studies that highlight three constraints to adoption: credit, insurance, and information. Interventions supplying credit are consistently effective in spurring technology adoption for a minority of farmers, while interventions supplying insurance have had more mixed results. This review suggests that one mitigating factor on demand for both of these products is incomplete information, which adds additional uninsurable risk to the technology adoption decision. A broad group of studies identify the presence of strong informational frictions. The review concludes with some potential directions for future research.

Archipelago of Risk: Uncertainty, Borders and Migration Detention Systems

This essay takes Deleuze’s ‘Postscript’ as a point of departure for a theory of risk analytics. The illustrative case in this essay is the Australian ‘Detention Network’, a vast system of migration detention that has been wholly privatised since 1997 and has served as a laboratory for similar systems in other parts of the world. This illustration tests the limits of normative and constructivist theories of risk. The principal argument in this essay is that contemporary analytics of risk are preoccupied with integrating uncertainty (or uninsurable risk) into formulations of risk, and that this necessarily gives rise to complex, archipelagic systems of abstract and physical dimensions. it places the emphasis on contracts as mechanisms that assemble stochastic processes into sociotechnical systems and forms of value.

On Additive Premium Calculation Principles

A premium calculation principle is a general rule that assigns a premium P to any given risk S. Intuitively, P is what the insurance carrier charges (apart from an expense allowance) for taking over the risk S (see [3], p. 85-87). Mathematically, S is a random variable, and P depends on S through its distribution function. The value of P may be finite or infinite; in the latter case we speak of an uninsurable risk.A premium calculation principle is called additive, if the premium assigned to the sum of two independent risks is the sum of the premiums that are assigned to the two risks individually. For example, the variance principle, P = E[S] + β Var [S] (β > o), is additive, because the variance of the sum of independent random variables equals the sum of the variances. Additivity is a very desirable property, from a theoretical as well as from a practical point of view (as pointed out by Borch [2], p. 429).The variance principle is not entirely satisfactory for various reasons. For one thing it does not take account of the skewness of S (a risk whose distribution is skewed to the right seems to be more dangerous than one with a symmetrical distribution). Furthermore, it produces in some cases a premium P that exceeds S with probability one (example: β = .3, S = o or 10, each with probability 1/2).