Testing Rival Theories of Budgetary Decision–making in the US States

This article tests three common budgetary decision–making theories in the US states. Pooled time series cross–section analysis is used from 1960 to 1996 to test the garbage can theory and incrementalism, and from 1989 to 1996 to test various theories of rational budgeting. The results demonstrate that there was some support for all three theories in terms of their impact on reducing state budget outputs. Rational budgeting reduces expenditures in aggregate, incrementalism has relatively low explanatory power below the aggregates, and garbage can budgeting is more prevalent in functional areas than for government as a whole. These findings imply that the future research agenda on budgetary decision–making theories should focus more on a system–wide approach, which takes into account many of the characteristics of all three rival models of decision–making, rather than exclusively focusing on each one singly.     

Density estimation in the uniform deconvolution model

We consider the problem of estimating a probability density function based on data that are corrupted by noise from a uniform distribution. The (nonparametric) maximum likelihood estimator for the corresponding distribution function is well defined. For the density function this is not the case. We study two nonparametric estimators for this density. The first is a type of kernel density estimate based on the empirical distribution function of the observable data. The second is a kernel density estimate based on the MLE of the distribution function of the unobservable (uncorrupted) data.     

An Examination of the Interaction Between Modelling and Its Relationship with Construction Kits: Lessons from the Past and for the Future

Construction kits have played a significant part in nurturing the growth and development of the minds and manipulation-based skills of children (and adults) in formal and non-formal education settings. These kits have origins rooted in the representation of the built world and now have a diversity of form and function, including technical versions with moving parts. This article examines some of the historically based ideas that lie behind the role that kits may have in terms of physical modelling. The article traces the transformation of kits from simple bricks and blocks into more complicated pieces for space-filling and achieving the transfer of forces and motion. This transformation occurred during the Victorian era when the influence of the ideas of educationalists and, perhaps rather strangely, exponents of early aviation, played major roles in determining the diversity of forms of construction kit and modelled possibilities that are now to be seen in classrooms and homes. The article ends with a review of some of the lessons from the past and present that will need to be considered in relation to concrete modelling in schools for the future. This revised version was published online in July 2006 with corrections to the Cover Date.     

Identifying “best” applicants in recruiting using data envelopment analysis

Selecting the most promising candidates to fill an open position can be a difficult task when there are many applicants. Each applicant achieves certain performance levels in various categories and the resulting information can be overwhelming. We demonstrate how data envelopment analysis (DEA) can be used as a fair screening and sorting tool to support the candidate selection and decision-making process. Each applicant is viewed as an entity with multiple achievements. Without any a priori preference or information on the multiple achievements, DEA identifies the non-dominated solutions, which, in our case, represent the “best” candidates. A DEA-aided recruiting process was developed that (1) determines the performance levels of the “best” candidates relative to other applicants; (2) evaluates the degree of excellence of “best” candidates’ performance; (3) forms consistent tradeoff information on multiple recruiting criteria among search committee members, and, then, (4) clusters the applicants.     

Getting the Most Out of a Mandatory Subordinated Debt Requirement

Recent advances in asset pricing—the reduced-form approach to pricing risky debt and derivatives—are used to quantitatively evaluate several proposals for mandatory bank issue of subordinated debt. We find that credit spreads on both fixed- and floating-rate subordinated debt provide relatively clean signals of bank risk and are not unduly influenced by nonrisk factors. Fixed-rate debt with a put is unacceptable, but making the putable debt floating resolves most problems. Our approach also helps to clarify several different notions of “bank risk.”     

An Empirical Analysis of Entrant and Incumbent Bidding in Road Construction Auctions

This paper explores differences in the bidding patterns of entrants and incumbents in road construction auctions. We find that entrants bid more aggressively and win auctions with significantly lower bids than incumbents. The differences in their bidding patterns are consistent with a model of auctions in which the distribution of an entrant's costs exhibits greater dispersion than that of an incumbent's and relations of stochastic dominance in the distributions do not persist for the entire range of estimated costs. We also find that more efficient firms bid, on average, more aggressively and firms with greater backlogs bid less aggressively.     

DURATION MOMENTS AND YIELD CURVE MOVEMENTS

In this paper we will analyze the relationship between the value and duration moments of a cash flow and movements in the yield curve. We will show that for changes in the yield curve which can be related to tⁿ , the 1st order changes in the net present value of a cash flow are linearly dependent on the n + lth duration moments, and that the 2nd order changes are dependent on the sum of duration moments of order 2 n + 1 and 2 n + 2. We will use this relationship to tilt tracking portfolios so as to protect them against specific changes in the yield curve.