Nonparametric rank-based test procedures for non-additive models in the two-way layout I. no replications

One of the major unresolved problems in the area of nonparametric statistics is the need for satisfactory rank-based test procedures for non-additive models in the two-way layout, especially when there is only one observation on each combination of the levels of the experimental factors. In this paper we consider an arbitrary non-additive model for the two-way layout with n levels of each factor. We utilize both alignment and ranking of the data together with basic properties of Latin squares to develop rank tests for interaction (non-additivity). Our technique involves first aligning within one of the main effects, ranking within the other main effects (columns and rows) and then adding the resulting ranks within “interaction bands” corresponding to orthogonal partitions of the interaction for the model, as denoted by the letters of an n × n Latin square. A Friedman-type statistic is then computed on the resulting sums. This is repeated for each of (n?1) mutually orthogonal Latin squares (thus accounting for all the interaction degrees of freedom). The resulting (n?1) Friedman-type statistics are finally combined to obtain an overall test statistic. The necessary null distribution tables for applying the proposed test for non-additivity are presented and we discuss the results of a Monte Carlo simulation study of the relative powers of this new procedure and other (parametric and nonparametric) procedures designed to detect interaction in a two-way layout with one observation per cell.     

Growth curve models with restrictions on random parameters

In the classical growth curve setting, individuals are repeatedly measured over time on an outcome of interest. The objective of statistical modeling is to fit some function of time, generally a polynomial, that describes the outcome's behavior. The polynomial coefficients are assumed drawn from a multivariate normal mixing distribution. At times, it may be known that each individual's polynomial must follow a restricted form. When the polynomial coefficients lie close to the restriction boundary, or the outcome is subject to substantial measurement error, or relatively few observations per individual are recorded, it can be advantageous to incorporate known restrictions. This paper introduces a class of models where the polynomial coefficients are assumed drawn from a restricted multivariate normal whose support is confined to a theoretically permissible region. The model can handle a variety of restrictions on the space of random parameters. The restricted support ensures that each individual's random polynomial is theoretically plausible. Estimation, posterior calculations, and comparisons with the unrestricted approach are provided.     

Age,Trend, and Cohort Effects in a Macro Model of Canadian Expenditure Patterns

A quadratic almost ideal demand system allowing for age, cohort, and trend effects is developed at the macro level. The model is estimated by maximum likelihood, using a three-tier iterative/search method applied to pooled 1961–1992 time series for five regions of Canada and six categories of expenditure. Hypothesis tests indicate support for the model specification. Elasticities are compared with those reported in other studies, with special attention to food. Effects of demographic and trend variables on elasticities and expenditure shares are investigated. An overall conclusion is that such effects can be very important in a macro demand system.     

Integrating Census Data to Support a Motion for Change of Venue

This applied demography case study illustrates the practical application of demographic concepts and methods to an issue facing the court. We show how census data can be used to support a legal motion for a change of venue. “Change of venue,” the legal term for moving a trial to a new location, usually is sought to avoid prejudice against one of the parties to a lawsuit. The case study will interest demographic practitioners, and it can be used as an instructional case in teaching applied demography: students can replicate it using data for any particular pair of populous metropolitan communities. By doing so, students would gain proficiency working with Public Use Microdata Sample (PUMS) household records—and the person records within household records—to identify and categorize family and nonfamily relationships among household members, and practical experience translating legal issues into questions that can be answered empirically using American Community Survey (ACS) data.     

Estimating the Effects of a Time‐Limited Earnings Subsidy for Welfare‐Leavers

In the Self Sufficiency Project (SSP) welfare demonstration, members of a randomly assigned treatment group could receive a subsidy for full‐time work. The subsidy was available for 3 years, but only to people who began working full time within 12 months of random assignment. A simple optimizing model suggests that the eligibility rules created an “establishment” incentive to find a job and leave welfare within a year of random assignment, and an “entitlement” incentive to choose work over welfare once eligibility was established. Building on this insight, we develop an econometric model of welfare participation that allows us to separate the two effects and estimate the impact of the earnings subsidy on welfare entry and exit rates among those who achieved eligibility. The combination of the two incentives explains the time profile of the experimental impacts, which peaked 15 months after random assignment and faded relatively quickly. Our findings suggest that about half of the peak impact of SSP was attributable to the establishment incentive. Despite the extra work effort generated by SSP, the program had no lasting impact on wages and little or no long‐run effect on welfare participation.     

The Relationship between Procedural Rationality and Political Behavior in Strategic Decision Making

Despite the central place of rationality and political behavior in the decision-making literature, we know little about the relationship between these two dimensions. Can decisions be made using both rational and political methods, or must managers use one approach or the other? These questions were addressed in a study of 61 strategic decisions in 24 companies using a multiple-informant, structured interview protocol. Results indicate that procedural rationality and political behavior are independent dimensions of the strategic decision-making process. The implications of our findings for future strategic decision-making research are discussed.     

Directed Matching and Monetary Exchange

We develop a model of monetary exchange where, as in the random matching literature, agents trade bilaterally and not through centralized markets. Rather than assuming they match exogenously and at random, however, we determine who meets whom as part of the equilibrium. We show how to formalize this process of directed matching in dynamic models with double coincidence problems, and present several examples and applications that illustrate how the approach can be used in monetary theory. Some of our results are similar to those in the random matching literature; others differ significantly.     

ON THE SELECTION OF CRITICAL VALUES IN SEQUENTIAL DECISION PROBLEMS

This paper explores the effect which the choice of critical values in sequential decisions has on the overall distribution of payoffs. It demonstrates in the context of a simple two-stage sequential decision model that the mean and variance of the overall distribution can be highly sensitive to the choice of critical values. Finally, it considers the problem of selecting optimal critical values when a standard meanvariance approach is used.