Dynamic portfolio choice with deferred annuities

We derive the optimal life-cycle portfolio choice and consumption pattern for households facing uncertain labor income, risky capital market, and mortality risk. In addition to stocks and bonds, the households have access to deferred annuities. Deferred payout life annuities are financial contracts providing life-long income to the annuitant after a specified period of time conditional on survival. We find that deferred annuities play an important role in household portfolios and generate significant welfare gains. Households with high benefits from state pensions, moderate risk aversion and moderate labor income risk purchase deferred annuities from age 40 and gradually increase their portfolio share. At retirement, deferred annuities account for 78% of total financial wealth. Households with low state pensions and high labor income risk purchase more annuities and earlier. Uncertainty with respect to future mortality rates has the same effect, i.e. household hedge against longevity risks using deferred annuities.     

Mortgage timing

We study how the term structure of interest rates relates to mortgage choice at both household and aggregate levels. A simple utility framework of mortgage choice points to the long-term bond risk premium as distinct from the yield spread and the long yield as a theoretical determinant of mortgage choice: when the bond risk premium is high, fixed-rate mortgage payments are high, making adjustable-rate mortgages more attractive. We confirm empirically that the bulk of the time variation in both aggregate and loan-level mortgage choice can be explained by time variation in the bond risk premium, whether bond risk premia are measured using forecasters’ data, a vector autoregressive (VAR) term structure model, or a simple household decision rule based on adaptive expectations. The household decision rule moves in lock-step with mortgage choice, lending credibility to a theory of strategic mortgage timing by households.     

Selection of telemarketing employees by standardized assessment procedures

Previous marketing research has focused on the optimal use of an existing salesforce, reflecting relatively little interest in the effects of salesforce selection on subsequent sales performance. A predictive validity study is described herein in which 85 telemarketing employees in a large telecommunications company were, prior to being hired, administered a battery of cognitive-ability and self-report trait measures. Three months later they were assessed on their job performance. Two cognitive-ability tests—one measuring perceptual speed and accuracy, the other, divergent thinking ability—and a number of scales from both a widely used personality questionnaire (the California Psychological Inventory [CPI]) and a special-purpose telemarketing selection instrument (the Telemarketing Applicant Inventory) yielded significant validities (of between 0.18 and 0.41) for at least one of several aggregated job-performance measures. A predictively-effective composite was derived, consisting of the two cognitive-ability tests noted and three CPI scales (Self-Acceptance, Socialization, and Achievement via Conformance). The composite yielded statistically-significant and useful predictive validities (of between 0.32 and 0.49) for several aggregated job-performance criteria. Utility analysis—a technique often used to examine the organizational consequences of selection strategies—was performed, with the present results reflecting substantial gains to the hiring organization. The reported research highlights the importance of effective hiring practices in achieving optimal subsequent salesforce performance. © 1997 John Wiley & Sons, Inc.     

On some properties of Markov chain Monte Carlo simulation methods based on the particle filter

Andrieu et al. (2010) prove that Markov chain Monte Carlo samplers still converge to the correct posterior distribution of the model parameters when the likelihood estimated by the particle filter (with a finite number of particles) is used instead of the likelihood. A critical issue for performance is the choice of the number of particles. We add the following contributions. First, we provide analytically derived, practical guidelines on the optimal number of particles to use. Second, we show that a fully adapted auxiliary particle filter is unbiased and can drastically decrease computing time compared to a standard particle filter. Third, we introduce a new estimator of the likelihood based on the output of the auxiliary particle filter and use the framework of Del Moral (2004) to provide a direct proof of the unbiasedness of the estimator. Fourth, we show that the results in the article apply more generally to Markov chain Monte Carlo sampling schemes with the likelihood estimated in an unbiased manner.     

A Review of: “UNCERTAINTY AND ITS EFFECT ON CAPITAL INVESTMENT ANALYSIS,” by Martin B. Solomon,Jr. Management Science,Volume 12, No. 8, April 1966

In this paper we extend Thompson's [17] work using time series models within the discounted cash flow framework to estimate the cost of equity capita] for a firm. In particular we do the following: First, we prove the existence and uniqueness of a solution for the cost of equity capital. Secondly, we verify that the cost of equity function is continuously differentiable and derive the formula for its reliability. Formulas for both the cost and its reliability are in terms of infinite sums or infinite dimension matrices. Thirdly, we derive estimators of the cost of equity capital and its reliability which are in terms of finite sums and easy to calculate. We show that these estimated converge to the cost of equity capital and its reliability. Finally, our procedure for estimation applies to a wide variety of time series models that may be used to forecast dividends.     

Scenario development for corporate planning

The term “scenario” is familiar to those involved in forecasting, but too few people are aware of what exactly a scenario is, or how it can best be developed and applied. The author describes a method developed over several years in response to a need which most forecasting efforts have left unfulfilled. The method enables quantitative and qualitative forecasts to be combined in a manner which can be directly related to an organisation's planning and decision-making processes, and which permits the evaluation of a company's objectives and performance in the light of those forecasts. The analysis of an organisation's likely performance in given scenarios can, in turn, provide a basis for contingency planning.     

Extending Fisch and Block’s (2018) tips for a systematic review in management and business literature

Management Review Quarterly - A systematic literature review is designed to synthesize meaningful knowledge from a large number of studies on a research topic. Over the past decade, management...     

The relationship among psychological need satisfaction,class engagement,and academic performance: Evidence from China

Utilizing self-determination theory, the authors examined the relationship among psychological need satisfaction, class engagement, and academic performance among Chinese accounting students. The structural equation modeling analysis indicated that (a) students’ psychological need satisfaction for autonomy, competence, and relatedness were significantly positively associated with their perceived autonomy support from instructors; (b) students’ class engagement was significantly positively associated with their psychological needs for competence and relatedness; and (c) students’ academic performance was significantly positively associated with their class engagement (i.e., effort and persistence). These findings emphasize the importance of satisfying students’ psychological needs in the learning process. Implications for educators are discussed.