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Journal Articles | 2019

On robust estimates of correlated risk in cyber-insured IT firms: A first look at optimal AI-based estimates under “Small” data

Ranjan Pal, Leana Golubchik, Konstanations Psounis, and Tathagata Bandyopadhyay

ACM Transactions on Management Information Systems

In this article, we comment on the drawbacks of the existing AI-based Bayesian network (BN) cyber-vulnerability analysis (C-VA) model proposed in Mukhopadhyay et al. (2013) to assess cyber-risk in IT firms, where this quantity is usually a joint distribution of multiple risk (random) variables (e.g., quality of antivirus, frequency of monitoring, etc.) coming from heterogeneous distribution families. As a major modeling drawback, Mukhopadhyay et al. (2013) assume that any pair of random variables in the BN are linearly correlated with each other. This simplistic assumption might not always hold true for general IT organizational environments. Thus, the use of the C-VA model in general will result in loose estimates of correlated IT risk and will subsequently affect cyber-insurance companies in framing profitable coverage policies for IT organizations. To this end, we propose methods to (1) find a closed-form expression for the maximal correlation arising between pairs of discrete random variables, whose value finds importance in getting robust estimates of copula-induced computations of organizational cyber-risk, and (2) arrive at a computationally effective mechanism to compute nonlinear correlations among pairs of discrete random variables in the correlation matrix of the CBBN model (Mukhopadhyay et al. 2013). We also prove that an empirical computation of MC using our method converges rapidly, that is, exponentially fast, to the true correlation value in the number of samples. Our proposed method contributes to a tighter estimate of IT cyber-risk under environments of low-risk data availability and will enable insurers to better assess organizational risks and subsequently underwrite profitable cyber-insurance policies.

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Journal Articles | 2019

Regression models for group testing: Identifiability and asymptotics

Arindam Chatterjee and Tathagata Bandyopadhyay

Journal of Statistical Planning and Inference

Group testing has been widely used in epidemiology and related fields to estimate prevalence of rare diseases. Parametric binary regression models are used in group testing to estimate the covariate adjusted prevalence. Unlike the standard binary regression model (viz., logistic, complementary log–log, etc.), the regression model for group testing data connects the maximum of a group of independent binary responses to its covariate values. Recently, in group testing literature, it has been extensively used for estimating covariate adjusted prevalence of a disease making the tacit assumptions that (i) the regression model is identifiable, and (ii) the standard asymptotic theory is valid for the maximum likelihood estimators of the regression parameters. Verifying these assumptions is found to be non-trivial theoretical issues. In this paper, we give theoretical proofs of these assumptions under a set of simple sufficient conditions, thus, providing a theoretical justification for likelihood based inference on the regression parameters. We also provide an outline of the proof extending the asymptotic theory to the data obtained by Dorfman retesting, where all subjects in a positive group are retested.

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Journal Articles | 2019

Estimation of log-odds ratio from group testing data using Firth correction

Surupa Roy and Tathagata Banerjee

Biometrical Journal: Journal of Mathematical Methods in Biosciences

We consider the estimation of the prevalence of a rare disease, and the log-odds ratio for two specified groups of individuals from group testing data. For a low-prevalence disease, the maximum likelihood estimate of the log-odds ratio is severely biased. However, Firth correction to the score function leads to a considerable improvement of the estimator. Also, for a low-prevalence disease, if the diagnostic test is imperfect, the group testing is found to yield more precise estimate of the log-odds ratio than the individual testing.

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Journal Articles | 2019

Adapting the women's empowerment in agriculture index to specific country context: Insights and critiques from fieldwork in India

Soumya Gupta, Dhiraj Singh, Prabhu Pingali, and Vidya Vemireddy

Global Food Security

The Women's Empowerment in Agriculture Index (WEAI) is a direct, multi-dimensional measure of women's access to resources and decision-making in various domains of agriculture. However, several challenges characterize its use: adaptation of questionnaires to local agricultural contexts, modifications to index construction once underlying activities and adequacy thresholds are modified, and sensitivity analysis. In this paper, we address such challenges based on our experience of adapting and using the WEAI across 3600 households in India. In doing so we contribute to the methodological and technical base underlying the index, expand the WEAI evidence base for South Asia, and highlight the importance of tailoring the index to specific agricultural contexts in order to impact public policies in a meaningful way.

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Journal Articles | 2019

Nutritional outcomes of empowerment and market integration for women in rural India

Soumya Gupta, Vidya Vemireddy, and Prabhu Pingali

Food Security

Over half of all women of reproductive age are affected by anaemia in India. In this paper we study the role that both household market integration and women’s empowerment in agriculture can play in determining women’s dietary diversity. Our analysis is based on primary data from 3600 households across India on agriculture, nutrition and anthropometric outcomes. We account for market integration by way of per capita household purchases (quantity) of cereals and non- cereal food groups, such as pulses, meat/ fish/ poultry, fruits and vegetables, eggs and dairy. We construct an adapted version of the Abbreviated Women’s Empowerment in Agriculture Index (A-WEAI) that is context- specific and agriculture- oriented. After controlling for individual, household and village- level explanatory factors, we find that – for a given level of per capita market purchases – women who are empowered in their agricultural decisions have significantly higher dietary diversity scores relative to women who are disempowered of such decisions. More specifically it is women’s empowerment in two areas: input in production decisions and membership in self- help groups that supports this result. Women’s empowerment also enhances dietary diversity in the presence of disaggregated per capita purchases of non-cereals such as pulses, meat, dairy and eggs. This highlights the importance of reorienting India’s agricultural price and procurement policies beyond staple grains to ensure better dietary diversity.

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Journal Articles | 2019

Impostor phenomenon in STEM: occurrence, attribution, and identity

Devasmita Chakraverty

Studies in Graduate and Postdoctoral Education

Purpose

This study aims to explore different themes related to impostor phenomenon, as experienced by graduate students and postdocs in science, technology, engineering and mathematics (STEM) fields.

Design/methodology/approach

Open-ended survey responses from 120 US-based participants from 40 states and Washington, D.C., describing an occasion when they felt like an impostor, were analyzed thematically.

Findings

Following content analysis, three themes emerged: occurrence, attribution and identity. While impostor-like feelings were experienced as early as high school or college, the majority experienced it during PhD application, on being admitted to a PhD program and throughout PhD training. The people experiencing impostor phenomenon attributed their achievements and success to others (other’s name, prestige, or connections, other’s mistake, other’s lies or misrepresentation, or other’s kindness) or self (self-inadequacy, pretense, luck or self-doubt) rather than their own hard work or ability. Gender-based and race/ethnicity-based identity also shaped the experiences of the impostor phenomenon.

Research limitations/implications

Open-ended survey responses varied in length and level of detail. Responses provided a one-time snapshot of a memory related to impostor-feelings that stood out, not indicating if the feeling persisted or evolved with time. The findings are not generalizable over a larger population.

Originality/value

This study identified multiple themes related to the impostor phenomenon not investigated before, enriching existing research while also providing methodological rigor for the development of follow-up studies.

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Journal Articles | 2019

Impact of vertical integration on market power in Indian manufacturing sector during the post-reform period

Rakesh Basant and Pulak Mishra

Journal of Industry Competition and Trade

In the context of declining degrees of vertical integration in major industries of Indian manufacturing sector during the post-reform period, the present paper is an attempt to examine how such “vertical disintegration” has affected firms’ market power and its implications for competition policy. Using panel dataset of 49 majors industries of Indian manufacturing sector for the period 2003–04 to 2010–11 and applying the system generalized method of moments approach to estimate of dynamic panel data models, the paper finds that vertical integration does not cause any significant impact on average market power of firms in an industry. Instead, it is influenced by market size, and selling and technology-related efforts. While selling intensity has a positive impact on market power, the impact of market size and technology intensity is found to be negative. Notably, like vertical integration, market concentration, import to export ratio, and capital intensity also do not have any significant impact on market power. The findings of this paper, therefore, have important implications for competition law and policy in general and policies and regulation relating to technology development and international trade in particular.

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Journal Articles | 2019

Improving the measurement of school climate using item response theory

Sarah Lindstrom Johnson, Ray E. Reichenberg, Kathan Shukla, Tracy E. Waasdorp, and Catherine P. Bradshaw

Educational Measurement: Issues and Practice

The U.S. government has become increasingly focused on school climate, as recently evidenced by its inclusion as an accountability indicator in the Every Student Succeeds Act. Yet, there remains considerable variability in both conceptualizing and measuring school climate. To better inform the research and practice related to school climate and its measurement, we leveraged item response theory (IRT), a commonly used psychometric approach for the design of achievement assessments, to create a parsimonious measure of school climate that operates across varying individual characteristics. Students (n = 69,513) in 111 secondary schools completed a school climate assessment focused on three domains of climate (i.e., safety, engagement, and environment), as defined by the U.S. Department of Education. Item and test characteristics were estimated using the mirt package in R using unidimensional IRT. Analyses revealed measurement difficulties that resulted in a greater ability to assess less favorable perspectives on school climate. Differential item functioning analyses indicated measurement differences based on student academic success. These findings support the development of a broad measure of school climate but also highlight the importance of work to ensure precision in measuring school climate, particularly when considering use as an accountability measure.

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Journal Articles | 2019

Medical negligence and law application of the Bolam and Bolitho rules in India

M P Ram Mohan and Vishakha Raj

Economic and Political Weekly

India has adopted the Bolam rule from the United Kingdom and has been using it to adjudicate cases of medical negligence. The evolution of the Bolam rule in the UK as well as the way the rule is applied in India by the Supreme Court reflects a balance between judicial intervention and deference to medical expertise. Although it is settled that it is the courts and not medical experts who must finally decide on whether the conduct of a doctor is negligent, the standards to be used when evaluating expert evidence and the extent to which such cases must be deferred to are evolving. The Supreme Court has not clearly stated the judicial standard against which it will test these differing opinions of medical experts and has not been consistent in its willingness to do so. Therefore, the application of the Bolam rule in India has been inconsistent and this is likely to have an impact on the decisions made by medical practitioners.

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Journal Articles | 2019

Nuclear energy safety, regulatory independence, and judicial deference: The case of the Atomic Energy Regulatory Board of India

M P Ram Mohan, K V Gopakumar, and Tyson Smith

Administration & Society

Research examining regulatory independence has either suggested de jure independence to be a predictor of de facto independence or suggested that the presence of de jure may not always indicate de facto independence. We study the Indian Atomic Energy Regulatory Board (AERB) to emphasize how AERB has enjoyed de facto independence, even in the absence of de jure independence. Using “judicial deference” principle, and through a mapping of substantive court cases, the article demonstrates Indian judiciary has consistently applied deference to AERB’s decision-making process, thereby showing confidence in the nuclear regulatory regime sustained as its inception.

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IIMA