The degree to which the Halpin and Croft Organizational Climate Description Questionnaire generalizes from business and educational settings to hospital settings was investigated. Two criteria were...

The organizational climate of a hospital is investigated, and its impact on job satisfaction is analyzed for nurses and administrators. Different climate dimensions are found to influence individua...

IN recent years several research studies have used a data base consisting of a time series of cross-section samples. A primary reason is that panel data of this type are potentially richer in information than a single cross-section sample. To date, however, the question of how to best analyze data bases of this type has not been fully explored in any of the research. To illustrate, a number of prior research projects which have utilized this type of data base are briefly reviewed. Hoch (1962) used moving cross-section samples as the data base for estimating the parameters of a CobbDouglas production function by analysis of covariance. Specifically the data were collected on 63 Minnesota farms for the years 1946 to 1951. Hoch reported an observed difference between the least squares parameter estimates and covariance estimates and the elasticities developed from these estimates. In terms of method, the major conclusion was that the covariance model might produce less biased elasticities and marginal return estimates. Massy and Frank (1965) investigated the relationship between price changes and dealing activities on a -firm's market share for frequently purchased household and food products. Panel data covering a 101-week time period of family purchase history provided the data base for the study. However, the data were aggregated so no methodological insight could be inferred concerning the question of analyzing time series of cross-section data. Laughhunn and Lyon (1971) applied Bayesian regression in analyzing a time series of cross-section cigarette consumption data using the Tiao and Zellner (1964) approximation method. The primary methodological issue in this research was to observe differences that might exist between classical pooling and the Bayesian regression technique. Comparison of the two techniques revealed very little difference between either parameter estimates or standard errors. Schipper (1964) used covariance regression to analyze a series of cross-section samples (19541957) collected by the Survey Research Center, University of Michigan. The central focus of this study was to analyze consumer discretionary behavior particularly with respect to durable expenditures, short term debt, and discretionary saving. The major methodological finding was that several differences between the covariance regression model and individual cross-section regressions existed. Schipper suggested the individual cross-section analyses might be biased but could not prove this point since he did not use experimental data. Palda and Blair (1970) conducted an analysis of toothpaste demand by using multiple cross sections of data collected by MRCA during the period 1958-1962. One focus of their research was to investigate the potential cross-section specification bias, based on the rationale presented by Simon and Aigner (1970), that can exist because of omitted variables. An interpretation of the results led them to think that the covariance model may reduce the specification bias. This interpretation cannot be considered conclusive since the analysis was not conducted in an experimental framework. Since there is an interest on the part of economic and business researchers to use multiple cross-section sample data, this would appear to be a sufficient reason for evaluating the different methods available for combining and analyzing the samples. Earlier work in this area includes studies by Nerlove (1967, 1968). He assumed models of the form Yit = aYit-l + Uit and Yit = aYit-l + 1-Xit + Uit respectively with Uit = yi + Vit with yi and Vit uncorrelated where =o-2 = 2 +or2. The estimation methods used were OLS, generalized least squares utilizing known p (p = o-A2/o-X2) analysis-of-covariance estimates with cross-sectional effects only, two-round estimates based on an estimated value of p, and maximum likelihood estimates. Generally, Nerlove's findings indicated that generalized least squares (if p is known) produces good esti-

Maslow's need-hierarchy theory of motivation has had a major influence on the thinking and research of many writers studying managerial behavior in an organizational setting. A growing number of groups of managers have been used as subjects in studies concerned with motivation and perceived need satisfactions. One conspicously absent group in recent studies conducted by behavioral scientists has been management scientists, a randomly selected sample of 192 of whom participated in the present study. The objective of the study was to learn about (1) the relation between job level and perceived need satisfaction, (2) the relation between company size and perceived need satisfaction, and (3) the interaction effects of level and size on perceived need satisfaction. Since the management science profession is becoming a significant force in society and organizations, the preliminary findings of this study provide some much needed motivational data. It was generally found that the most predominant independent variable studied was the level of the management scientist in the organization. Hopefully, more controlled and sophisticated research studies will be stimulated by the present study.

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During the past decade, a number of studies have been made of managerial on-the-job satisfaction, Most of these have been conducted using samples from occupationally heterogeneous groups of managers such as those from production, marketing, personnel, sales, and finance. Except for one recent study, managers from public accounting firms have been omitted from consideration.' The purpose of this note is to report on the results of a questionnaire which was designed to determine the effect on job satisfaction of the accountant's level within the organizational hierarchy in large and small CPA firms. The results should prove useful to (1) executives interested in providing a positive atmosphere for productive and high quality work; (2) accounting studies concerned with the psychological rewards of working as a CPA; and (3) researchers interested in determining whether those in professional occupations are similar to nonprofessionals in the attainment of job satisfaction.

The retail price elasticity of demand for cigarettes is a particularly important parameter for social decisions at this time. Results from prior cigarette elasticity studies vary widely, ranging from −0.10 to −1.48. Temporal changes may explain some of this variation, but differences in research methods are more important. The quasi-experimental approach used in this article yields an elasticity estimate (−0.511) free of many of the extraneous and irrelevant systematic influences that afflict time-series and cross-section methods. In addition, the length of run of the elasticity is known and explicit. The method provides built-in protections against bias from trends in collinear variables and produces sensible estimates with reasonably small and measurable dispersion.