Consumption Over the Life Cycle

This paper estimates a structural model of optimal life‐cycle consumption expenditures in the presence of realistic labor income uncertainty. We employ synthetic cohort techniques and Consumer Expenditure Survey data to construct average age‐profiles of consumption and income over the working lives of typical households across different education and occupation groups. The model fits the profiles quite well. In addition to providing reasonable estimates of the discount rate and risk aversion, we find that consumer behavior changes strikingly over the life cycle. Young consumers behave as buffer‐stock agents. Around age 40, the typical household starts accumulating liquid assets for retirement and its behavior mimics more closely that of a certainty equivalent consumer. Our methodology provides a natural decomposition of saving and wealth into its precautionary and life‐cycle components.     

ASSESSING CONGRUENCEAMONG DISTANCE MATRICES: SINGLE-MALT SCOTCH WHISKIES REVISITED

A test of congruence among distance matrices is described. It tests the hypothesis that several matrices, containing different types of variables about the same objects, are congruent with one another, so they can be used jointly in statistical analysis. Raw data tables are turned into similarity or distance matrices prior to testing; they can then be compared to data that naturally come in the form of distance matrices. The proposed test can be seen as a generalization of the Mantel test of matrix correspondence to any number of distance matrices. This paper shows that the new test has the correct rate of Type I error and good power. Power increases as the number of objects and the number of congruent data matrices increase; power is higher when the total number of matrices in the study is smaller. To illustrate the method, the proposed test is used to test the hypothesis that matrices representing different types of organoleptic variables (colour, nose, body, palate and finish) in single‐malt Scotch whiskies are congruent.     

Transductive versions of the LASSO and the Dantzig Selector

Transductive methods are useful in prediction problems when the training dataset is composed of a large number of unlabeled observations and a smaller number of labeled observations. In this paper, we propose an approach for developing transductive prediction procedures that are able to take advantage of the sparsity in the high dimensional linear regression. More precisely, we define transductive versions of the LASSO (Tibshirani, 1996) and the Dantzig Selector (Candès and Tao, 2007). These procedures combine labeled and unlabeled observations of the training dataset to produce a prediction for the unlabeled observations. We propose an experimental study of the transductive estimators that shows that they improve the LASSO and Dantzig Selector in many situations, and particularly in high dimensional problems when the predictors are correlated. We then provide non-asymptotic theoretical guarantees for these estimation methods. Interestingly, our theoretical results show that the Transductive LASSO and Dantzig Selector satisfy sparsity inequalities under weaker assumptions than those required for the “original” LASSO.     

Efficient circular neighbour designs for spatial interference model

We consider circular block designs for field-trials when there are two-sided spatial interference between neighbouring plots of the same blocks. The parameter of interest is total effects that is the sum of direct effect of treatment and neighbour effects, which correspond to the use of a single treatment in the whole field. We determine universally optimal approximate designs. When the number of blocks may be large, we propose efficient exact designs generated by a single sequence of treatment. We also give efficiency factors of the usual binary block neighbour balanced designs which can be used when the number of blocks is small.     

An adaptive sequential Monte Carlo method for approximate Bayesian computation

Approximate Bayesian computation (ABC) is a popular approach to address inference problems where the likelihood function is intractable, or expensive to calculate. To improve over Markov chain Monte Carlo (MCMC) implementations of ABC, the use of sequential Monte Carlo (SMC) methods has recently been suggested. Most effective SMC algorithms that are currently available for ABC have a computational complexity that is quadratic in the number of Monte Carlo samples (Beaumont et al., Biometrika 86:983?C990, 2009; Peters et al., Technical report, 2008; Toni et al., J.?Roy. Soc. Interface 6:187?C202, 2009) and require the careful choice of simulation parameters. In this article an adaptive SMC algorithm is proposed which admits a computational complexity that is linear in the number of samples and adaptively determines the simulation parameters. We demonstrate our algorithm on a toy example and on a birth-death-mutation model arising in epidemiology.     

When Passion Leads to Problematic Outcomes: A Look at Gambling

Vallerand et al. (2003) have proposed that individuals can have two distinct types of passion toward an activity. Harmonious passion, an internal force leading one to choose to engage in the activity, is proposed to be associated with positive consequences. Obsessive passion, an internal pressure forcing one to engage in an activity, is posited to be associated with negative consequences. The present study sought to determine the role of the two types of passion in various cognitive and affective states associated with dependence and problems with gambling. Participants (n = 412) were recruited at the Montréal Casino and given a questionnaire measuring passion toward gambling, as well as consequences associated with dependence and problem gambling. Results showed that obsessive passion for gambling predicted poorer vitality and concentration in daily tasks, as well as increased rumination, anxiety, negative mood, guilt, and problem gambling. These relations were not found for harmonious passion for gambling. Results are discussed in light of the motivational approach to passion (Vallerand et al., 2003).     

When outsourcing fragments: customer creativity and technological transmutations

One of the most fundamental decisions made in firms is about what functions or activities the firm should perform within its own hierarchy, and which of these it should rely on the market to perform. Outsourcing is ‘an agreement in which one company contracts out a part of their existing internal activity to another company’. However, this article contends that outsourcing has changed, and is changing in ways that make the application of neat, legal and technically correct definitions hard to use, and even harder to apply in strategy. Under the new outsourcing paradigm, technology is not a passive ‘substance’, rather it is an active ‘force’. We aim to look at the ways in which technologies are re-shaped and transmuted by consumers. Through this analysis, we add the consumer activity to the conventional definition of outsourcing. We focus on one of the most highly anticipated and influential new products of 2007 – the Apple iPhone.     

Planners' Perspectives on Obstacles to Sustainable Urban Development: Implications for Transformative Planning Strategies

A major problem confronting planning is the gap between transformative proposals and enduring urban development trends. The paper interprets interviews with 62 planners involved in a sustainable urban development strategy in a large region focussed on Toronto, Canada. Surveyed planners were asked about the obstacles they encounter when attempting to modify prevailing urban development. Mentioned obstacles are consistent with expectations arising from three major perspectives on inertia: institutionalism, political economy and path dependence. Interviews also highlight the role of planners' practical knowledge in identifying and interpreting obstacles, and the existence of a consensus among respondents over sustainable urban development.     

Entry and Exit in OTC Derivatives Markets

We develop a parsimonious model to study the equilibrium and socially optimal decisions of banks to enter, trade in, and possibly exit, an OTC market. Although we endow all banks with the same trading technology, banks' optimal entry and trading decisions endogenously lead to a realistic market structure composed of dealers and customers with distinct trading patterns. We decompose banks' entry incentives into incentives to hedge risk and incentives to make intermediation profits. We show that dealer banks enter more than is socially optimal. In the face of large negative shocks, they may also exit more than is socially optimal when markets are not perfectly resilient.