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In this study, the relative accuracy of four well known methods for forecasting are compared The methods are applied to the time series of earnings per share for a random sample of United States corporations over a lengthy period of time. All the time series exhibit both period‐to‐period movements and seasonal fluctuation. The four models are, (1) Holt‐Winters multiplicative exponential smoothing model, (2) univariate Box‐Jenkins model, (3) linear autoregression of data seasonally adjusted by the Census II–XII method, and (4) linear autoregression of the data seasonally adjusted by the X11‐ARIMA method. The study of financial data of this type is important because (1) these data exhibit time series properties of trend, seasonality, and cycle, (2) earnings per share forecasts are important for purposes of financial planning and investment; and (3) previous studies of this nature were not as exhaustive in terms of the statistical analysis of the results

In this chapter, we examine the notion of ethnic diversity with a view to explore Europe-wide differences in defining and managing ethnic diversity and equality. When compared to gender diversity, ethnic diversity does not enjoy similar level of success in Europe. Our analyses show that this is due to the fact that ethnicity and ethnic categories are national. In fact, there are different levels of discussion on ethnicity, where the debate is limited due to historical, cultural and legal differences.

The purpose of this study is to propose the time series decomposition approach to analyze and predict the failure data of the repairable systems.

This study employs NHPP to model the failure data. Initially, Nelson's graph method is employed to estimate the mean number of repairs and the MCRF value for the repairable system. Second, the time series decomposition approach is employed to predict the mean number of repairs and MCRF values.

The proposed method can analyze and predict the reliability for repairable systems. It can analyze the combined effect of trend‐cycle components and the seasonal component of the failure data.

This study only adopts simulated data to verify the proposed method. Future research may use other real products' failure data to verify the proposed method. The proposed method is superior to ARIMA and neural network model prediction techniques in the reliability of repairable systems.

Results in this study can provide a valuable reference for engineers when constructing quality feedback systems for assessing current quality conditions, providing logistical support, correcting product design, facilitating optimal component‐replacement and maintenance strategies, and ensuring that products meet quality requirements.

The time series decomposition approach was used to model and analyze software aging and software failure in 2007. However, the time series decomposition approach was rarely used for modeling and analyzing the failure data for repairable systems. This study proposes the time series decomposition approach to analyze and predict the failure data of the repairable systems and the proposed method is better than the ARIMA model and neural networks in predictive accuracy.

We document long-run trends in interstate migration rates, using individual-level data from the U.S. Census for the period 1850–1990. Two measures of migration are calculated. The first considers an individual to have moved if she is residing in a state different from her state of birth. The second considers a family to have moved if it is residing in a state different from the state of birth of one of its young children, allowing us to estimate the timing of moves more precisely. Overall migration propensities have followed a U-shaped trend since 1850, falling until around 1900 and then rising until around 1970. We examine variation in the propensity to make an interstate move by age, sex, race, nativity, region of origin, family structure, and education. Counterfactuals based on probit estimates of the propensity to migrate suggest that the rise in migration of families since 1900 could be explained by increased educational attainment, although education may be serving as a proxy for unmeasured covariates. The decline of interstate migration in the late nineteenth century remains to be explained.

Commercial real estate (CRE) is a major investment asset. Yet detailed information on the value of investible CRE in different cities is lacking. The authors propose an innovative method to measure the value of investible CRE using transaction datasets.

The authors take transaction prices and index them to produce a time series of values for each asset. The sum of the values at each point represents the value of investible CRE at that date. The authors’ method is applied to transaction data for New York, London and Toronto.

London had the highest proportions of institutional and foreign ownership, and its turnover was more resilient to the downturn in global CRE following the GFC. The results illustrate the potential of the authors’ method to shed light on the characteristics of investible CRE markets.

The authors use data from Real Capital Analytics (RCA). This provides good coverage of transactions for investible CRE in the cities that the authors examine, but data from other sources might lead to different estimates.

Measuring the value and turnover of investible CRE is important for portfolio strategies that account for the size and liquidity of investment markets. Knowledge of these features, and of ownership patterns, provides a better understanding of market operation.

The authors’ modification of the perpetual inventory technique is simple, novel and practical. The authors propose this approach given the absence of a building-by-building inventory of investible CRE in many markets.

Large population cohorts will need to be productively absorbed into the work force in coming years in order to provide for their old age. Appropriate data and techniques for measuring labour absorption have been scarce. This article suggests two techniques for analysing the data recommended with first priority for censuses by the United Nations. Censuses are used because virtually every country conducts a census while few can afford labour force surveys. Use of the techniques is illustrated for four countries

The purpose of the study was to find out the determinants of strategy implementation by the international reproductive health (RH) non-governmental organizations (NGOs) in Kenya for attainment of MDG 5 by 2015. The objectives of the study were to analyse the effects of the determinants of strategy implementation for attainment of the Millennium Development Goal (MDG) 5 by international RH NGOs operating in Kenya. This study was guided by three specific objectives: to analyse the effect of policy regulations on strategy implementation by international RH NGOs in attainment of MDG 5; to determine the effect of management competencies on strategy implementation by international RH NGOs in attainment of MDG 5 and to explore the effect of resource allocation on strategy implementation by international RH NGOs in attainment of MDG 5 by 2015 in Kenya.

A cross-sectional descriptive study design was carried out from January to March 2012 in Nairobi, Kenya. The study populations comprised of programme staff and RH technical advisors for the international RH NGOs operating in Kenya and headquartered in Nairobi. The sampling design was a census method since all the ten international RH NGOs based in Nairobi were selected. Qualitative and quantitative methods of data collection were used using both closed and open-ended questionnaires. The quantitative data were analysed using SPSS version 20 for both descriptive and inferential analysis. Qualitative data were analysed descriptively. Measures of location and variability were used for analysis and hypothesis tested using Fisher ' s Exact test and regression analysis.

The research findings showed that policy regulations, management competencies and the resource allocations determine successful implementation of the strategic plans. Inadequate resource allocations have a direct bearing on the implementation of the RH programmes which invariably affects the attainment of the MDG 5 by 2015. The study did not accept the null hypotheses and therefore showed that there is relationship between policy regulations, management competencies and resource allocations and the implementation of strategic management plans by international RH NGOs operating in Kenya.

Although numerous studies acknowledge that strategies frequently fail not because of inadequate strategy formulation, but because of insufficient implementation, strategy implementation has received less research attention than strategy formulation. This paper addresses this gap.

The pattern of racial segregation in U.S. elementary and secondary schools has changed significantly over the last 25 years. This chapter examines the relationship between the racial composition of schools and the choices white parents make concerning the schools their children attend. Restricted access files at the Bureau of the Census allow us to identify each household's Census block of residence and, in turn, suburban public school districts and urban public school attendance areas. We find that the racial composition of schools and neighborhoods are very important in the school and location decisions of white families.

The effects of trading day adjustment techniques to improve forecasting accuracy are investigated. The results of forecasting from directly generated monthly data are compared with those of transformed (trading day adjusted) data. Conclusions are offered towards the development of a trading day adjustment model.