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.     

New Keynesian Phillips Curve and inflation dynamics in Australia

The New Keynesian Phillips Curve (NKPC) was developed as a response to the New Classical critique that Keynesian macroeconomics lacked micro-foundations. The NKPC provides theoretical micro-foundations that attempt to explain, inter alia, nominal rigidities and, explicitly price stickiness. This paper investigates the validity of the NKPC for Australia. In contrast to the findings for the USA and Euro area, we find that neither the output gap nor marginal cost appears to be a key driving force variable across different set of instruments and estimators (GMM and 2SLS) over the sample period from 1959 to 2009. The flattening of the NKPC along with significant presence of price stickiness is also found in the data. In particular, the reduced form coefficients and implied estimates from the structural parameters of the model support the view that inflation dynamics are forward looking while the role of lagged inflation is also statistically important only after 1980s. However, we claim that the forward looking baseline NKPC contrary to the hybrid NKPC is stable and better explains inflation dynamics for the Australian economy.     

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.     

Formative versus reflective measurement models: Two applications of formative measurement

This paper presents a framework that helps researchers to design and validate both formative and reflective measurement models. The framework draws from the existing literature and includes both theoretical and empirical considerations. Two important examples, one from international business and one from marketing, illustrate the use of the framework. Both examples concern constructs that are fundamental to theory-building in these disciplines, and constructs that most scholars measure reflectively. In contrast, applying the framework suggests that a formative measurement model may be more appropriate. These results reinforce the need for all researchers to justify, both theoretically and empirically, their choice of measurement model. Use of an incorrect measurement model undermines the content validity of constructs, misrepresents the structural relationships between them, and ultimately lowers the usefulness of management theories for business researchers and practitioners. The main contribution of this paper is to question the unthinking assumption of reflective measurement seen in much of the business literature.     

Choice and the Internet: From Clickstream to Research Stream

The authors discuss research progress and future opportunities for modeling consumer choice on the Internet using clickstream data (the electronic records of Internet usage recorded by company web servers and syndicated data services). The authors compare the nature of Internet choice (as captured by clickstream data) with supermarket choice (as captured by UPC scanner panel data), highlighting the differences relevant to choice modelers. Though the application of choice models to clickstream data is relatively new, the authors review existing early work and provide a two-by-two categorization of the applications studied to date (delineating search versus purchase on the one hand and within-site versus across-site choices on the other). The paper offers directions for further research in these areas and discusses additional opportunities afforded by clickstream information, including personalization, data mining, automation, and customer valuation. Notwithstanding the numerous challenges associated with clickstream data research, the authors conclude that the detailed nature of the information tracked about Internet usage and e-commerce transactions presents an enormous opportunity for empirical modelers to enhance the understanding and prediction of choice behavior.