Optimal allocation of the sample size to strata under box constraints

In stratified random sampling without replacement boundary conditions, such as the sample sizes within strata shall not exceed the population sizes in the respective strata, have to be considered. Stenger and Gabler (Metrika, 61:137–156, 2005) have shown a solution that satisfies upper boundaries of sample fractions within the strata. However, in modern applications one may wish to guarantee also minimal sampling fractions within strata in order to allow for reasonable separate estimations. Within this paper, an optimal allocation in the Neyman-Tschuprov sense is developed which satisfies upper and lower bounds of the sample sizes within strata. Further, a stable algorithm is given which ensures optimality. The resulting sample allocation enables users to bound design weights within stratified random sampling while considering optimality in allocation.     

Shaping buyer–supplier relationships in manufacturing contexts: Design and test of a contingency model

Although the idea that buyer–supplier partnerships can yield considerable benefits to firms is largely diffused among researchers and practitioners, the approach adopted in this paper is that no “one best way” exists in buyer–supplier relationships, but rather a “best way” for each specific exchange context. Hence, this paper proposes a contingency model for shaping and managing buyer–supplier relationships in manufacturing contexts. In order to test the model, an empirical study was performed on a sample of 45 buyer–supplier relationships within the Italian white goods industry. A three-dimensional performance indicator was computed to compare supplier performance achieved within relations matching the model's suggestions with those set differently. The results strongly suggest that suppliers involved in relationships set accordingly to the contingency model are likely to enjoy superior performance.     

A structural analysis of the correlated random coefficient wage regression model

We estimate a dynamic programming model of schooling decisions in which the log wage regression function is set within a correlated random coefficient model. We show that estimates of the dynamic programming model can be used to obtain a number of treatment effects, including the local average treatment effect (LATE). However, unlike LATE parameters obtained in a standard IV framework, our LATE estimates are obtained without imposing separability between individual specific heterogeneity and schooling choices and are therefore not subject to a “monotonicity” restriction. We find that returns to schooling are characterized by a high degree of dispersion across individuals.     

Shifts in autonomy, responsibility and control from centre to periphery in public administration: the case of the ministry of finance in Italy

In tackling administrative reform and in the hope of improving the effective allocation of resources, most European governments have shown a growing interest in adopting private sector management models in the public administration. The assumption underlying this paper is that the decisive variables in the different national contexts have to do with the relationships between the central and the peripheral administrative levels, and the way in which administrative actors at the two levels interpret their roles and participate in the reform process. The paper examines the case of the reform of the Italian Ministry of Finance. In seeking to improve its performance and the services it provides, the ministry reform is intended to introduce a management system in which the key concepts are the planning, programming and control of administrative action and results. According to reform rhetoric, shaping a new class of administrative managers at the local level is the crux of the question. However, research results hint that the “creation” of this new local executive staff is yet to be completed. The working hypothesis advanced is that this is due to local executives’ lack of confidence in the “system”, inasmuch as the reform process has so far been characterised by a tendency to give them responsibility without autonomy and autonomy without control. The greater their lack of trust, the lesser their willingness to risk the consequences of failure and the greater their tendency to stick to defensive positions and to return to previous “bureaucratic” conceptions and ways of operating.     

On Certain Indices for Ordinal Data with Unequally Weighted Classes

In this paper, some new indices for ordinal data are introduced. These indices have been developed so as to measure the degree of concentration on the “small” or the “large” values of a variable whose level of measurement is ordinal. Their advantage in relation to other approaches is that they ascribe unequal weights to each class of values. Although, they constitute a useful tool in various fields of applications, the focus here is on their use in sample surveys and specifically in situations where one is interested in taking into account the “distance” of the responses from the “neutral” category in a given question. The properties of these indices are examined and methods for constructing confidence intervals for their actual values are discussed. The performance of these methods is evaluated through an extensive simulation study.     

Asymptotic properties of random extremes under general normalization from nonidentical distributions

In this paper we study the weak convergence of the generally normalized extremes (extremes under nonlinear monotone normalization) of random number of independent (nonidentically distributed) random variables. When the random sample size is assumed to converge in probability and the interrelation between the basic variables and their random size is not restricted, the limit forms as well as the sufficient conditions of convergence are derived. Moreover, when the random sample size is assumed to converge weakly and independent of the basic variables, the necessary and sufficient conditions for the convergence are derived.Acknowledgment. The authors are grateful to a referee for several helpful comments and for pointing out the extensive paper by Galambos (1992) leading to improvement of the representation of the paper.Received January 2002     

A comparison of nonresponse in mail,telephone, and face-to-face surveys

This article reports a meta-analysis of 45 studies that explicitly compare the response obtained using a mail, telephone or face-to-face survey. The data analysis uses a generalized hierarchical linear model. Sampling procedure (e.g., local convenience sample, random general sample), saliency of topic, and research organization (university, government versus market research) had an effect on the response. On the average, the face-to-face condition achieved the highest completion rate (70.3%), the telephone survey the next highest (67.2%), and the mail survey the lowest (61.3%). There is a significant interaction with the year of publication: The response to face-to-face and telephone surveys is going down in the period covered by this analysis (1947 to 1992), but the response to mail surveys is going up slightly. We attribute this to the large amount of research on nonresponse problems with mail surveys, and recommend more research and development in this direction for face-to-face and telephone methods.     

Competitive prizes: when less scrutiny induces more effort

We consider a principal who is keen to induce his agents to work at their maximal effort levels. To this end, he samples n days at random out of the T days on which they work, and awards a prize of B dollars to the most productive agent. The principal’s policy (B, n) induces a strategic game Γ(B, n) between the agents. We show that to implement maximal effort levels weakly (or, strongly) as a strategic equilibrium (or, as dominant strategies) in Γ(B, n), at the least cost B to himself, the principal must choose a small sample size n. Thus less scrutiny by the principal induces more effort from the agents.The need for reduced scrutiny becomes more pronounced when agents have information of the history of past plays in the game. There is an inverse relation between information and optimal sample size. As agents acquire more information (about each other), the principal, so to speak, must “undo” this by reducing his information (about them) and choosing the sample size n even smaller.     

Some aspects of random permutation models in finite population sampling theory

Summary We first consider Neyman's optimum allocation of sample size to strata in the light of available auxiliary information for which a suitable random permutation model is assumed. For a special case of this model the allocation of the sample size reduces to the same as when a certain superpopulation regression model is assumed. Motivated by this, more generally, we discuss some optimality results under random permutation models and compare them with the corresponding results when a superpopulation regression model is assumed.     

Optimum allocation in multivariate stratified random sampling: stochastic matrix mathematical programming

The allocation problem for multivariate stratified random sampling as a problem of stochastic matrix integer mathematical programming is considered, minimizing the estimated covariance matrix of estimated means subject to fixed cost or fixed total sample size. With these aims the asymptotic normality of sample covariance matrices for each strata is established. Some alternative approaches are suggested for its solution. An example is solved by applying the proposed techniques.     

Two–step sequential sampling

Choosing the sample size in advance is a familiar problem: often, additional observations appear to be desirable. The final sample size then becomes a random variable, which has rather serious consequences.
Two such sample extension situations will be considered here. In the first situation, the observed sample variance determines whether or not to double the original sample size. In the second situation, the variances observed in two independent samples are compared; their ratio determines the number of additional observations.     

An extension of the monocentric urban spatial equilibrium model to a multicenter setting: The case of the two-center city

Firms in a monocentric city conforming in substance to the “new urban economics” produce an export commodity under agglomeration economies and employ homogeneous labor and capital. Workers reside about the CBD in decreasing densities with distance. A developer establishes a second export production center within the city's residential area. Conditions for economic viability and growth of the subcenter are examined, and its impacts on short-run and long-run city location patterns are discussed. A limiting condition on subcenter employment size is provided.     

Making sustainable sourcing decisions: practical evidence from the automotive industry

Achieving environmental and sustainable performance within an organisation’s supply chain and manufacturing operations will be feasible if upstream supply partners have the same commitments in performing their operations in a sustainable manner. Given the debate above, we propose a comprehensive framework to address the sustainable supplier selection and order allocation (SSS&OA) problem. The framework developed is practical, that starts by using an audition check-list specific for each sustainability dimension (environmental, economic and social), from which the weighted values of its comprised criteria are obtained. The weighted scores of the selected sustainable suppliers are utilised by a proposed bi-objective order allocation model in order to make sourcing decisions. The strength of the proposed framework is its practical applicability to provide a solution for SSS&OA problems which is validated through a real-world application. Finally, research findings, theoretical and managerial insights and also directions for additional research are presented.     

Stratification of Skewed Populations: A Comparison of Optimisation‐based versus Approximate Methods

Survey statisticians use either approximate or optimisation‐based methods to stratify finite populations. Examples of the former are the cumrootf (Dalenius & Hodges, 1957 ) and geometric (Gunning & Horgan, 2004 ) methods, while examples of the latter are Sethi ( 1963 ) and Kozak ( 2004 ) algorithms. The approximate procedures result in inflexible stratum boundaries; this lack of flexibility results in non‐optimal boundaries. On the other hand, optimisation‐based methods provide stratum boundaries that can simultaneously account for (i) a chosen allocation scheme, (ii) overall sample size or required reliability of the estimator of a studied parameter and (iii) presence or absence of a take‐all stratum. Given these additional conditions, optimisation‐based methods will result in optimal boundaries. The only disadvantage of these methods is their complexity. However, in the second decade of 21st century, this complexity does not actually pose a problem. We illustrate how these two groups of methods differ by comparing their efficiency for two artificial populations and a real population. Our final point is that statistical offices should prefer optimisation‐based over approximate stratification methods; such a decision will help them either save much public money or, if funds are already allocated to a survey, result in more precise estimates of national statistics.     

Finite sample inference for quantile regression models

Under minimal assumptions, finite sample confidence bands for quantile regression models can be constructed. These confidence bands are based on the “conditional pivotal property” of estimating equations that quantile regression methods solve and provide valid finite sample inference for linear and nonlinear quantile models with endogenous or exogenous covariates. The confidence regions can be computed using Markov Chain Monte Carlo (MCMC) methods. We illustrate the finite sample procedure through two empirical examples: estimating a heterogeneous demand elasticity and estimating heterogeneous returns to schooling. We find pronounced differences between asymptotic and finite sample confidence regions in cases where the usual asymptotics are suspect.     

Tiebout choice and residential segregation by race in US metropolitan areas, 1980–2000

This article examines the link between local government fragmentation, or “Tiebout choice,” and segregation between black and white residents. As suggested by Tiebout [Tiebout, C., 1956. A pure theory of local public expenditures. Journal of Political Economy 64, 416–424.], fragmented local governance structures may encourage households to vote with their feet and sort into communities based on their willingness to pay for local public services. This outcome has been well documented. The nuance explored here is that, if the demand for local public services varies by race or if households have preferences for neighbors with specific racial characteristics, local government fragmentation may foster an increase in residential segregation by race across neighborhoods and jurisdictions. Results from metropolitan-level regressions suggest that increased Tiebout choice is associated with increases in black–white residential segregation within US metropolitan areas. Comparable results are obtained from household-level estimates, where the black racial composition of a household's census tract of residence is regressed on household-level controls and racially stratified measures of Tiebout choice. Results from both approaches suggest that a 10% increase in Tiebout choice would increase neighborhood segregation by no more than 1%, while segregation across jurisdictions would increase by between 4% and 7%.     

About “strategy” and “strategies” in supply management

This article addresses the context and content of a generic supply strategy and discusses its strategy-making process. Building mostly on fundamental strategic management theories, the authors explain the role of supply strategy in its managerial context. In so doing, some light is shed on the meaning and use of the terms “strategy” and “strategies”. Also, a practical conceptual framework for supply strategy formulation is provided. The generic checklist, built by segmenting supply management decisions, is intended to guide supply professionals in addressing strategic issues to create value to customers, avoiding confusion and optimising resource allocation.     

Evaluating estimation methods for ordinal data in structural equation modeling

This study examined the performance of two alternative estimation approaches in structural equation modeling for ordinal data under different levels of model misspecification, score skewness, sample size, and model size. Both approaches involve analyzing a polychoric correlation matrix as well as adjusting standard error estimates and model chi-squared, but one estimates model parameters with maximum likelihood and the other with robust weighted least-squared. Relative bias in parameter estimates and standard error estimates, Type I error rate, and empirical power of the model test, where appropriate, were evaluated through Monte Carlo simulations. These alternative approaches generally provided unbiased parameter estimates when the model was correctly specified. They also provided unbiased standard error estimates and adequate Type I error control in general unless sample size was small and the measured variables were moderately skewed. Differences between the methods in convergence problems and the evaluation criteria, especially under small sample and skewed variable conditions, were discussed.     

Measuring the consequences of promoting inner city homeownership

This paper examines low- and moderate-income households in the City of Philadelphia who are becoming homeowners for the first time. We examine two Nehemiah developments subsidized by the City of Philadelphia that offer newly constructed homes at well-below cost. This paper uses a unique survey of these new owners to measure what Nehemiah residents gain in terms of structure and community attributes as they make the transition from renting to owning. The new owners in the Nehemiah complexes significantly improve their housing structures while raising their exposure to crime and weak local public schools. As part of the City’s community development strategy, these developments were expected to increase economic activity near these sites. We document that there is no evidence of local benefit spillovers for census tracts where the Nehemiah developments were built. Our survey results suggest that the new housing developments represent an “oasis” where there are few interactions between the new homeowners and the incumbent residents of the greater community.     

A fuzzy-QFD approach to supplier selection

This article suggests a new method that transfers the house of quality (HOQ) approach typical of quality function deployment (QFD) problems to the supplier selection process. To test its efficacy, the method is applied to a supplier selection process for a medium-to-large industry that manufactures complete clutch couplings.The study starts by identifying the features that the purchased product should have (internal variables “WHAT”) in order to satisfy the company's needs, then it seeks to establish the relevant supplier assessment criteria (external variables “HOW”) in order to come up with a final ranking based on the fuzzy suitability index (FSI). The whole procedure was implemented using fuzzy numbers; the application of a fuzzy algorithm allowed the company to define by means of linguistic variables the relative importance of the “WHAT”, the “HOW”–“WHAT” correlation scores, the resulting weights of the “HOW” and the impact of each potential supplier.Special attention is paid to the various subjective assessments in the HOQ process, and symmetrical triangular fuzzy numbers are suggested to capture the vagueness in people's verbal assessments.