Some Problems in Forecasting Population for Government Planning Purposes

Some governments rely on centralized, official sets of population forecasts for planning capital facilities. But the nature of population forecasting, as well as the milieu of government forecasting in general, can lead to the creation of extrapolative forecasts not well suited to long-range planning. This report discusses these matters, and suggests that custom-made forecasts and the use of forecast guidelines and a review process stressing forecast assumption justification may be a more realistic basis for planning individual facilities than general-purpose, official forecasts.     

Inference for Parameters Defined by Moment Inequalities: A Recommended Moment Selection Procedure

This paper is concerned with tests and confidence intervals for parameters that are not necessarily point identified and are defined by moment inequalities. In the literature, different test statistics, critical‐value methods, and implementation methods (i.e., the asymptotic distribution versus the bootstrap) have been proposed. In this paper, we compare these methods. We provide a recommended test statistic, moment selection critical value, and implementation method. We provide data‐dependent procedures for choosing the key moment selection tuning parameter κ and a size‐correction factor η.     

Methods for Constructing Uncertainty Intervals for Queries of Bayesian Nets

In this paper the issue of finding uncertainty intervals for queries in a Bayesian Network is reconsidered. The investigation focuses on Bayesian Nets with discrete nodes and finite populations. An earlier asymptotic approach is compared with a simulation‐based approach, together with further alternatives, one based on a single sample of the Bayesian Net of a particular finite population size, and another which uses expected population sizes together with exact probabilities. We conclude that a query of a Bayesian Net should be expressed as a probability embedded in an uncertainty interval. Based on an investigation of two Bayesian Net structures, the preferred method is the simulation method. However, both the single sample method and the expected sample size methods may be useful and are simpler to compute. Any method at all is more useful than none, when assessing a Bayesian Net under development, or when drawing conclusions from an ‘expert’ system.     

Jackknifing the kaplan-meier survival estimator for censored data: Simulation results and asymptotic analysis

It is shown by simulation t h a t the (arc-sine transformation of the) Kaplan-Meier survival estimator for censored data can be usefully jackknifed to give conservative confidence limits for survival probabilities when samples are small (25 and 50). Mathematical demonstration of the asymptotic, large-sample, validity of the jackknife is included.     

Further Evidence on the Great Crash,the Oil-Price Shock,and the Unit-Root Hypothesis

Recently, Perron has carried out tests of the unit-root hypothesis against the alternative hypothesis of trend stationarity with a break in the trend occurring at the Great Crash of 1929 or at the 1973 oil-price shock. His analysis covers the Nelson–Plosser macroeconomic data series as well as a postwar quarterly real gross national product (GNP) series. His tests reject the unit-root null hypothesis for most of the series. This article takes issue with the assumption used by Perron that the Great Crash and the oil-price shock can be treated as exogenous events. A variation of Perron's test is considered in which the breakpoint is estimated rather than fixed. We argue that this test is more appropriate than Perron's because it circumvents the problem of data-mining. The asymptotic distribution of the estimated breakpoint test statistic is determined. The data series considered by Perron are reanalyzed using this test statistic. The empirical results make use of the asymptotics developed for the test statistic as well as extensive finite-sample corrections obtained by simulation. The effect on the empirical results of fat-tailed and temporally dependent innovations is investigated, in brief, by treating the breakpoint as endogenous, we find that there is less evidence against the unit-root hypothesis than Perron finds for many of the data series but stronger evidence against it for several of the series, including the Nelson-Plosser industrial-production, nominal-GNP, and real-GNP series.     

Robustness of the two-sample t-test umdeh violations of the homogeneity of farjance assumptioi

When the two-sample t-test has equal sample slies, it is widely considered to be a robust procedure (with respect to the significaoce level) under violatioa of the assuaptioo of equal variances. This paper is coa-earned with a quantification of the amount of robustness which this procedure has under such violations, The approach is through the concept of "religion of robustness" and the resluts show an extremely strong degree of robustness for the equal an extremely strong degree of robustness for the equal sample size t-test, probably more so than most statistyicians realise. This extremely high level of robustness, however, reduces quickly as the sample sizes begin to vary from equality. The regions of robustnes obtained show that while most users would likely be satisfied with the degree of robustness inherent when the two sample sizes each vary by 10% from equality, most would wish to be much more cautions when the variation is 20%. The study covers sample sizes n₁ -= n ² = 5(5)30(10)50 plus 10% and 20% variations thereof for the two-tailed test and nominal significance levels of 0.01 and 0.05.     

Currents in a Stream: College Student Identities and Ethnic Identities and Their Relationship with Self‐Esteem,Efficacy, and Grade Point Average in an Urban University*

Objectives. We investigate how college student identities and ethnic identities vary among black, white, and Asian students and among immigrant, second‐, and third‐generation students at a large public urban university (in counterpoint to recent studies at highly selective schools). In addition, we explore how those identities are related to college students' sense of self‐esteem and efficacy and their academic performance. Methods. We use survey data from a sample (N=652) of students attending a large diverse public urban university to create new indexes for several dimensions of college identity and ethnic identity and use existing self‐esteem and efficacy indexes to compare black, white, and Asian students, as well as immigrant, second‐generation, and third‐generation students. Results. Among several significant identity differences, we find: (1) whites are lower than blacks on college identity indexes, and immigrant students are higher than subsequent‐generation students on college student identity measures; (2) whites are lower than blacks and Asians on ethnic identity measures; only the ethnic activities index declines linearly from immigrant to second‐ to third‐generation students; (3) blacks have higher self‐esteem and efficacy than whites or Asians; whites have higher GPAs than blacks or Asians, while immigrant students have higher GPAs than third‐generation students; and (4) at least one college student identity dimension and one ethnic identity dimension is related to self‐esteem, efficacy, and GPA. Conclusions. How young adults conceive of themselves as college students and the way they formulate their own racial‐ethnic identities is related to their self‐esteem, efficacy, and academic performance. Moreover, the pattern that these relationships take is somewhat different at a large diverse public urban university than at highly selective universities.     

Forecast Updating and Supplier Coordination for Complementary Component Purchases

We study a supply chain where an original equipment manufacturer (OEM) buys subassemblies, comprised of two complementary sets of components, from a contract manufacturer (CM). The OEM provides a demand forecast at the time when the CM must order the long lead‐time set of components, but must decide whether or not to provide updated forecasts as a matter of practice. Forecast updates affect the CM's short lead‐time purchase decision, and the anticipation of updates may also affect the long lead‐time purchase decision. While the OEM and CM both incur lost sales costs, the OEM can decide whether or not to share the overage costs otherwise fully borne by the CM. We investigate when the OEM is better served by committing to provide updated forecasts and/or committing to share overage costs. For a distribution‐free, two‐stage forecast‐update model, we show that (1) the practice of providing forecast updates may be harmful to the OEM and (2) at the OEM's optimal levels of overage risk sharing, the CM undersupplies relative to the supply chain optimal quantity. For a specific forecast‐update model, we computationally investigate conditions under which forecast updating and risk sharing are in the best interest of the OEM.