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This chapter does three things. First, it estimates regional gross domestic product (GDP) for three different geographical levels in Switzerland (97 micro regions, 16 labor market basins, and 3 large regions). Second, it analyzes the evolution of regional inequality relying on a heuristic model inspired by Williamson (1965), which features an initial growth impulse in one or several core regions and subsequent diffusion. Third, it uses index number theory to decompose regional inequality into three different effects: sectoral structure, productivity, and comparative advantage.

The results can be summarized as follows: As a consequence of the existence of multiple core regions, Swiss regional inequality has been comparatively low at higher geographical levels. Spatial diffusion of economic growth occurred across different parts of the country and within different labor market regions. This resulted in a bell-shaped evolution of regional inequality at the micro regional level and convergence at higher geographical levels. In early and in late stages of the development process, productivity differentials were the main drivers of inequality, whereas economic structure was determinant between 1888 and 1941. The poorest regions suffered from comparative disadvantage, that is, they were specialized in the vary sector (agriculture), where their relative productivity was comparatively lowest.

This research examines the use of a number of time series model structures of a moderate allocation mutual fund, PRWCX. PRWCX was rated as the top fund in its category during the past five years. The fund invests at least 50% of its total assets that the fund manager believes that have above average potential for capital growth. The remaining assets are generally invested in convertible securities, corporate and government debt bank loans, and foreign securities. Forecasting the total NAV of such a moderate allocation mutual fund, composed of an extremely large number of investments, requires a method that produces accurate results. These models are exponentially smoothing (single, double, and Winter’s Method), trend models (linear, quadratic, and exponential) are Box-Jenkins models.

A number of multidimensional poverty measures that respect the ordinal nature of dimensions have recently been proposed within the counting approach framework. Besides ensuring a reduction in poverty, however, it is important to monitor distributional changes to ensure that poverty reduction has been inclusive in reaching the poorest. Distributional issues are typically captured by adjusting a poverty measure to be sensitive to inequality among the poor. This approach, however, has certain practical and conceptual limitations. It conflicts, for example, with some policy-relevant measurement features, such as the ability to decompose a measure into dimensions post-identification and does not create an appropriate framework for assessing disparity in poverty across population subgroups. In this chapter, we propose and justify the use of a separate decomposable inequality measure – a positive multiple of “variance” – to capture the distribution of deprivations among the poor and to assess disparity in poverty across population subgroups. We demonstrate the applicability of our approach through two contrasting inter-temporal illustrations using Demographic Health Survey data sets for Haiti and India.

In this chapter, we conduct a metadata analysis of articles published in accounting, business and finance journals ranked by Australian Business Dean Council (ABDC), and benchmarked against the Chartered Association of Business Schools (ABS) ranking, that discuss firm- and country-level greenhouse gas (GHG) emission practices and reporting. Number of publications on GHG research, research methods, number of citations and ratio, across countries and continents are some of the topics we cover. We employ a list of articles on accounting, business and finance journals ranked A* and A in the ABDC journal rankings from 2015 to 2022. The study uses a structured literature review to analyse 74 papers on GHG reporting practices at the firm- and country level. Although this line of enquiry is still nascent and developing, the study found underrepresentation of Africa and the Middle East in GHG literature generally. In addition, majority of the articles examined also concentrate on quantitative methods. Most of the articles on GHG research are A-ranked in the ABDC ranking scheme. It was also found that few studies focus on the countries and companies with the highest emissions. While there has been some progress in interrogating GHG across the globe, there is still much room for further research. A key area of future research is exploring the GHG reporting practices in the African and the Middle Eastern sub-regions. There is also a need to examine countries and companies with high emissions. A further study needs to explore the benefits of other research methods in addition to quantitative methods, as different research methods could yield different insights that would enhance research-based conclusions.

Knowledge of the dependence structure between financial assets is crucial to improve the performance in financial risk management. It is known that the copula completely summarizes the dependence structure among multiple variables. We propose a multivariate exponential series estimator (ESE) to estimate copula densities nonparametrically. The ESE has an appealing information-theoretic interpretation and attains the optimal rate of convergence for nonparametric density estimations in Stone (1982). More importantly, it overcomes the boundary bias of conventional nonparametric copula estimators. Our extensive Monte Carlo studies show the proposed estimator outperforms the kernel and the log-spline estimators in copula estimation. It also demonstrates that two-step density estimation through an ESE copula often outperforms direct estimation of joint densities. Finally, the ESE copula provides superior estimates of tail dependence compared to the empirical tail index coefficient. An empirical examination of the Asian financial markets using the proposed method is provided.

Purpose – The aim of this paper is to analyze the changes that took place in occupational segregation by gender, nationality, and age in Switzerland during the period 1970–2000.

Methodology – The paper starts by using correspondence analysis to detect changes in occupational segregation by gender and nationality. It then generalizes a decomposition procedure originally proposed by Karmel and McLachlan by combining their approach with what is now known as the Shapley decomposition. Such a generalization offers a clear breakdown of the variation over time in occupational segregation into a component measuring changes in net segregation and another one corresponding to changes in the margins, the latter itself including variations in the occupational structure and in the shares of the subpopulations (e.g., the genders) in the labor force.

Findings – Between 1970 and 2000 there was a slight increase in gross segregation by gender but a decrease in net segregation. The change in gross segregation is because the change in the margins more than compensated that in the internal structure. But even the change in the margins is the consequence of opposite forces since variations in the occupational structure would have per se led to a decrease in gross segregation.

Originality – The results of the empirical illustration based on Swiss data for 1970 and 2000 prove the usefulness of the approach. They stress in particular that in several instances, variations in gross and net segregation worked in opposite directions.

This paper presents a decomposition forecast of stock prices using time series of weekly stock price data as implemented in Excel. The following decomposition components are presented, analyzed, and interpreted including a moving average, a trend, a periodic function, and two shock variables including a triangular shock variable and a level change. The results of the individual components are compared and a discussion of each component’s efficiency is provided. The trend component is statistically significant over the forecast time. The moving average component displays a bi-modal error distribution over varying spans of the moving average and forecast periods. The first mode coincides with random walk behavior with an optimal span and forecast period of one. The second mode is more interesting and applicable for investing beyond the short-term with an optimal spans and forecast periods beyond 75 weeks. The periodic sine function well captures the typical U.S. business cycle of 4–5 years and significantly improves model performance. Finally, the significant outliers remaining from the decomposition are diagnosed and modeled with a triangular shock variable for the bust and recovery associated with the 2008 financial crisis. The model presented does a good job of decomposing the analytical components in forecasting stock prices and provides a useful illustration of Excel methods.

We formulate static and dynamic empirical models of promotion where the current promotion probability depends on the hierarchical level in the firm, individual human capital, unobserved individual specific attributes, time-varying firm-specific variables, as well as endogenous past promotion histories (in the dynamic version). Within the static versions, we investigate the relative influence of the key determinants of promotions and how these influences vary by hierarchical levels. In the dynamic version of the model, we examine the causal effect of past speed of promotion on promotion outcomes. The model is fit on an eight-year panel of 30,000 American executives employed in more than 300 different firms. The stochastic process generating promotions may be viewed as a series of promotion probabilities which become smaller as an individual moves up in the hierarchy and which are primarily explained by unobserved heterogeneity and promotion opportunities. Firm variables and observed human capital variables (age, tenure, and education) play a surprisingly small role. We also find that, conditional on unobservables, the promotion probability is only enhanced by the speed of promotion achieved in the past (a structural fast track effect) for a subset of the population and is negative for the majority. In general, the magnitude of the individual-specific effect of past speed of promotion is inversely related to schooling, tenure, and hierarchical level.

“It should also be noted that the objective of convergence and equal distribution, including across under-performing areas, can hinder efforts to generate growth. Contrariwise, the objective of competitiveness can exacerbate regional and social inequalities, by targeting efforts on zones of excellence where projects achieve greater returns (dynamic major cities, higher levels of general education, the most advanced projects, infrastructures with the heaviest traffic, and so on). If cohesion policy and the Lisbon Strategy come into conflict, it must be borne in mind that the former, for the moment, is founded on a rather more solid legal foundation than the latter” European Commission (2005, p. 9)Adaptation of Cohesion Policy to the Enlarged Europe and the Lisbon and Gothenburg Objectives.