Issues in the estimation and application of latent structure models of choice

Our paper provides a brief review and summary of issues and advances in the use of latent structure and other finite mixture models in the analysis of choice data. Focus is directed to three primary areas: (1) estimation and computational issues, (2) specification and interpretation issues, and (3) future research issues. We comment on what latent structure models have promised, what has been, to date, delivered, and what we should look forward to in the future.     

The Random Walk Hypothesis in the Emerging Indian Stock Market

This paper examines the random walk hypothesis in the emerging Indian stock market using daily data on individual stocks. The statistical evidence in this paper rejects the random walk hypothesis. The results suggest that daily returns earned by individual stocks and by an equally weighted portfolio show significant non–linear dependence and persistent volatility effects. The non–linear dependence takes the form of ARCH–type conditional heteroskedasticity and does not appear to be caused by nonstationarity of underlying economic variables. Though conditional volatility is time varying, it does not explain expected returns.     

Managerial judgment and forecast combination: An experimental study

This paper examines the role of managerial judgment in forming a final forecast, or judging the achievability of a critical level of sales, when multiple forecasts or opinions are available to the decision maker. Several factors that can help improve the quality of human intervention are identified and incorporated in a decision aid. Experimental results show that aided combination can help the decision maker exploit her relevant private information and mitigate the generally observed negative effects of human intervention. Further, the results suggest that emphasizing expected sales, even when the organization is primarily interested in go/no-go decisions, helps improve performance. Several suggestions for future research are presented.

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Exploring variations in employment practices in the emerging economies of Europe: assessing the impact of foreign ownership and European integration

Few studies have assessed the impact of European Union (EU) integration on the emerging economies of Europe, especially with regard to employment practices. In this study, we focus on three aspects of employment practices and assess whether EU integration has lead to any differences between the emerging economies aligned to the EU and those that remain out of the EU fold. This comparison is quite valid because the emerging economies that we compare have all had a similar background in terms of their economic systems. We use a large World Bank database to compare domestically owned and foreign‐owned firms separately. The results show that, while there is some level of divergence between the two blocs of countries in terms of the percentage of temporary employees and education level of employees, in terms of the percentage of skilled workers employed, however, there is no divergence between firms in the two blocs of countries.     

Sources of time varying return comovements during different economic regimes: evidence from the emerging Indian equity market

We study the economic and non-economic sources of stock return comovements of the emerging Indian equity market and the developed equity markets of the US, UK, Germany, France, Canada and Japan. Our findings show that the probability of extreme comovements in the economic contraction regime is relatively higher than in the economic expansion regime. We show that international interest rates, inflation uncertainty and dividend yields are the main drivers of the asymmetric return comovements. Findings reported in the paper imply that the impact of interest rates and inflation on return comovements could be used for anticipating financial contagion and/or spillover effects. This is particularly critical since during extreme market conditions, the tail return comovements can potentially reveal critical information for active portfolio management.     

Socioeconomic Determinants of Child Health: Empirical Evidence from Indonesia

This paper characterizes the socioeconomic determinants of child health using height‐for‐age z‐score (HAZ), a long‐run measure of chronic nutritional deficiency. We construct a panel data that follows children between ages 3 and 59 months in 1993 through the 1997 and 2000 waves of the Indonesian Family Life Survey. We use this data to identify the various child‐level, household‐level and community‐level factors that affect children's health. Our findings indicate that household income has a large and statistically significant role in explaining improvements in HAZ. We also find a strong positive association between parental height and HAZ. At the community level, we find that provision of electricity and the availability of paved roads are positively associated with improvements in HAZ. Finally, in comparison to community‐level factors, household‐level characteristics play a large role in explaining the variation in HAZ. These findings suggest that policies that address the demand‐side constraints have greater potential to improve children's health outcomes in the future.     

Experience with a simulator for training ammonia plant operators

A computer-based simulator was used for training operators prior to the start-up of a new fertilizer complex which includes a 1,350-MTPD ammonia plant, two 1,100-MTPD urea plants, and a steam and power generation plant with two 18-MW gas turbines. The simulator offered many benefits, which can be used for continued education of operators and engineering studies.     

An intelligent and secure system for predicting and preventing Zika virus outbreak using Fog computing

Zika virus is a mosquito-borne disease that spreads very quickly in different parts of the world. In this article, we proposed a system to prevent and control the spread of Zika virus disease using integration of Fog computing, cloud computing, mobile phones and the Internet of things (IoT)-based sensor devices. Fog computing is used as an intermediary layer between the cloud and end users to reduce the latency time and extra communication cost that is usually found high in cloud-based systems. A fuzzy k-nearest neighbour is used to diagnose the possibly infected users, and Google map web service is used to provide the geographic positioning system (GPS)-based risk assessment to prevent the outbreak. It is used to represent each Zika virus (ZikaV)-infected user, mosquito-dense sites and breeding sites on the Google map that help the government healthcare authorities to control such risk-prone areas effectively and efficiently. The proposed system is deployed on Amazon EC2 cloud to evaluate its performance and accuracy using data set for 2 million users. Our system provides high accuracy of 94.5% for initial diagnosis of different users according to their symptoms and appropriate GPS-based risk assessment.     

Oil and stock market activity when prices go up and down: the case of the oil and gas industry

We examine the asymmetric effects of daily oil price changes on equity returns, market betas, oil betas, return variances, and trading volumes for the US oil and gas industry. The responses of stock returns associated with negative changes in oil prices are higher than that associated with positive changes in oil prices. Stock risk measured by market beta is influenced more due to oil price decreases than due to oil price increases. On the other hand, oil risk exposures (oil betas) and return variances are more influenced by oil price increases than oil price decreases. The results of our study indicate that oil and gas firm returns, market betas, oil betas, return variances respond asymmetrically to oil price changes. We also find that relative changes in oil prices along with firm-specific factors such as firm size, ROA, leverage, market-to-book ratio (MBR) are important in determining the effects of oil price changes on oil and gas firms’ returns, risks, and trading volumes.