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Journal Articles | 2024

What explains rice exports? An analysis of major rice-exporting countries

Poornima Varma

This study examines the drivers of rice trade. The analysis uses the standard comparative advantage model, the Heckscher–Ohlin–Vanek (HOV) framework, supplemented with a gravity-type equation. Using the Poisson pseudo-maximum likelihood (PPML) estimation for data from 2002 to 2020, the analysis broadly confirms HOV model predictions. Results indicate that arable land, along with GDP, distance, precipitation and crop season temperature, significantly influences rice trade dynamics. The results showed that the precipitation play a key role in influencing the rice trade rather than the blue water availability. However, agricultural water stress discouraged exports and encouraged imports.

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Journal Articles | 2024

What happens when parents find violence acceptable? A case of violent-humorous commercials targeted at children

Akshaya Vijayalakshmi, Russell N.Laczniak

We examine the influence of violent–humorous commercials on children and whether parental mediation can temper children’s aggressive responses to violent–humorous ads. We find that (a) violent–humorous ads lead to higher levels of aggressive affect in children, and (b) violent ads lead to higher levels of aggressive cognition and aggressive affect in children (Study 1). We also find that active parental mediation does not have the intended effect of reducing children’s aggressive responses after they view violent–humorous commercials (Study 1). This effect, which is contradictory to general expectations, occurs because parents are less likely to perceive the violent–humorous (vs. solely violent) ad as violent (Studies 2A and 2B) and, consequently, they show less interest in critically mediating the ad (Study 3). Through this study, for the first time, we show (a) the impact of violent–humorous ads on children (vs. adults); (b) the impact of violent–humorous ads on aggression (beyond attitudes toward ads); and (c) the effect of parents’ violent–humorous ad beliefs on parental mediation. The findings of our study suggest that the humor in a violent–humorous ad appears to trivialize the violence in the ad, with not-so-trivial consequences.

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Journal Articles | 2024

Bayesian predictive inference for nonprobability samples with spatial poststratification

Dhiman Bhadra, Balgobin Nandram

Non-probability sampling involves selecting samples from a population in which the probability of selection is unknown and some population units may have zero selection probabilities. This differentiates it from probability sampling where selection is governed by a probability model and every population unit has a non-zero chance of being selected. Nonprobability samples usually suffer from selection bias and hence may not represent the target population accurately. An important problem that arises in this context is the prediction of responses corresponding to non-sampled units, which should ideally have been sampled. In this article, we propose three modeling frameworks to address this issue. We use propensity scores to balance the sampled and non-sampled units and a Bayesian estimation scheme for parameter inference and prediction. We incorporate a spatial poststratification scheme to assess the predictive ability of our models on a simulated dataset. In addition, we perform model selection routines to identify the optimal model having the best predictive ability.

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Journal Articles | 2024

Interpretable classifier models for decision support using high utility gain patterns

Srikumar Krishnamoorthy

Ensemble models such as gradient boosting and random forests are proven to offer the best predictive performance on a wide variety of supervised learning problems. The high performance of these black box models, however, comes at a cost of model interpretability. They are also inadequate to meet regulatory demands and explainability needs of organizations. The model interpretability in high performance black-box models is achieved with the help of post-hoc explainable models such as Local Interpretable Model-agnostic Explanations (LIME) and SHapley Additive exPlanations (SHAP). This paper presents an alternate intrinsic classifier model that extracts a class of higher order patterns and embeds them into an interpretable learning model. More specifically, the proposed model extracts novel High Utility Gain (HUG) patterns that capture higher order interactions, transforms the model input data into a new space, and applies interpretable classifier methods on the transformed space. We conduct rigorous experiments on forty benchmark binary and multi-class classification datasets to evaluate the proposed model against the state-of-the-art ensemble and interpretable classifier models. The proposed model was comprehensively assessed on three key dimensions: 1) quality of predictions using classifier measures such as accuracy, F1 , AUC, H-measure, and logistic loss, 2) computational performance on large and high-dimensional data, and 3) interpretability aspects. The HUG-based learning model was found to deliver performance comparable to that of the state-of-the-art ensemble models. Our model was also found to achieve 2-40% (45%) prediction quality (interpretability) improvements with significantly lower computational requirements over other interpretable classifier models. Furthermore, we present case studies in finance and healthcare domains and generate one- and two-dimensional HUG profiles to illustrate the interpretability aspects of our HUG models. The proposed solution offers an alternate approach to build high performance and transparent machine learning classifier models. We hope that our ML solution help organizations meet their growing regulatory and explainability needs.

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Handbook On Nuclear Regulatory Framework In India Easter Book Company.

Books | 2024

Handbook On Nuclear Regulatory Framework In India Easter Book Company.

M.P. Ram Mohan Tyson R. Smith

Working Papers | 2024

The Glittering Paradox: Unveiling India's Gold Policy Evolution And Its Enduring Flaws

Ramakrishnan Padmanabhan, Chandan Satyarth and Sundaravalli Narayanaswami

In recent years, despite reforms and ambitious initiatives like establishing exchanges to enhance transparency in the gold ecosystem, significant time has been consumed by corrective actions and a lack of clear government direction. The corrective actions included the decisions taken during the intervention phase (2012-2013), the transparency phase (2014-2018) and the RBI circulars, notifications and guidelines post 2012 till date. Some of the aspects of gold policy that require corrective action may include the Free Trade Agreements with different countries and trade blocs, different government of India notifications to tackle the import of gold exploiting the India Government Policy loopholes. A review may be timely of the NITI Aayog Report on Transformation Gold Policy issued in February 2018, the recommendations of IGPC-IIMA working group and the subsequent launch of India International Bullion Exchange (IIBX) and its future. There's a need for decisive steps that promise long-term benefits for the nation.

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Journal Articles | 2024

AI as an inventor debate under the Patent Law: A post-DABUS comparative analysis

Sarvanan A Deva, Prasad M

Artificial Intelligence (AI) has gained momentum during the last decade, achieving narrow intelligence to general intelligence. The Gen AIs can generate original content and create patentable inventions. The key challenge is whether AI machines can be considered as "inventors" under the existing patent laws; this question has been challenged before various domestic courts. In this context, this paper analyses the interplay between AI and existing patent law frameworks; more specifically, we look at a post-DABUS case from a comparative perspective. The paper explores this question predominantly from the viewpoint of Australia, the United Kingdom, and the United States. The limitations of the existing patent regime and the need to adopt a flexible one that could adapt to the challenges posed by AI are highlighted. The crucial factors shaping the future direction of patent law in the context of AI debate, such as the evolving need for a sui generis law and convergence for a global standard, also form a part of this paper.

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Journal Articles | 2024

𝛿- perturbation of bilevel optimization problems: An error bound analysis

Margarita Antoniou, Ankur Sinha, Gregor Papa

In this paper, we analyze a perturbed formulation of bilevel optimization problems, which we refer to as -perturbed formulation. The -perturbed formulation allows to handle the lower level optimization problem efficiently when there are multiple lower level optimal solutions. By using an appropriate perturbation strategy for the optimistic or pessimistic formulation, one can ensure that the optimization problem at the lower level contains only a single (approximate) optimal solution for any given decision at the upper level. The optimistic or the pessimistic bilevel optimal solution can then be efficiently searched for by algorithms that rely on solving the lower level optimization problem multiple times during the solution search procedure. The -perturbed formulation is arrived at by adding the upper level objective function to the lower level objective function after multiplying the upper level objective by a small positive/negative . We provide a proof that the -perturbed formulation is approximately equivalent to the original optimistic or pessimistic formulation and give an error bound for the approximation. We apply this scheme to a class of algorithms that attempts to solve optimistic and pessimistic variants of bilevel optimization problems by repeatedly solving the lower level optimization problem.

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Journal Articles | 2024

Ambient air pollution and daily mortality in ten cities of India: A causal modelling study

"Jeroen de Bont, Bhargav Krishna, Massimo Stafoggia, Tirthankar Banerjee, Hem Dholakia, Amit Garg, Vijendra Ingole, Suganthi Jaganathan, Itai Kloog, Kevin Lane, Rajesh Kumar Mall, Siddhartha Mandal, Amruta Nori-Sarma, Dorairaj Prabhakaran, Ajit Rajiva, Ab

Background

The evidence for acute effects of air pollution on mortality in India is scarce, despite the extreme concentrations of air pollution observed. This is the first multi-city study in India that examines the association between short-term exposure to PM2·5 and daily mortality using causal methods that highlight the importance of locally generated air pollution.

Methods

We applied a time-series analysis to ten cities in India between 2008 and 2019. We assessed city-wide daily PM2·5 concentrations using a novel hybrid nationwide spatiotemporal model and estimated city-specific effects of PM2·5 using a generalised additive Poisson regression model. City-specific results were then meta-analysed. We applied an instrumental variable causal approach (including planetary boundary layer height, wind speed, and atmospheric pressure) to evaluate the causal effect of locally generated air pollution on mortality. We obtained an integrated exposure–response curve through a multivariate meta-regression of the city-specific exposure–response curve and calculated the fraction of deaths attributable to air pollution concentrations exceeding the current WHO 24 h ambient PM2·5 guideline of 15 μg/m3. To explore the shape of the exposure–response curve at lower exposures, we further limited the analyses to days with concentrations lower than the current Indian standard (60 μg/m3).

Findings

We observed that a 10 μg/m3 increase in 2-day moving average of PM2·5 was associated with 1·4% (95% CI 0·7–2·2) higher daily mortality. In our causal instrumental variable analyses representing the effect of locally generated air pollution, we observed a stronger association with daily mortality (3·6% [2·1–5·0]) than our overall estimate. Our integrated exposure–response curve suggested steeper slopes at lower levels of exposure and an attenuation of the slope at high exposure levels. We observed two times higher risk of death per 10 μg/m3 increase when restricting our analyses to observations below the Indian air quality standard (2·7% [1·7–3·6]). Using the integrated exposure–response curve, we observed that 7·2% (4·2%–10·1%) of all daily deaths were attributed to PM2·5 concentrations higher than the WHO guidelines.

Interpretation

Short-term PM2·5 exposure was associated with a high risk of death in India, even at concentrations well below the current Indian PM2·5 standard. These associations were stronger for locally generated air pollutants quantified through causal modelling methods than conventional time-series analysis, further supporting a plausible causal link.

Funding

Swedish Research Council for Sustainable Development.

 

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Journal Articles | 2024

Demonetisation and labour force participation in India: The impact of governance and political alignment

"Pritha Dev, Jeemol Unni"

This paper considers the demonetisation event of November 2016 in India and its impact on labour force participation and incomes with a view to understand the role of governance in how individuals weathered the shock. We measure governance at the state level by measuring if the state was ruled by Bhartiya Janta Party at the time of demonetisation which was also the ruling party in the centre under whom demonetisation was introduced. We use a difference in difference approach to compare outcomes before and after demonetisation for individuals in politically aligned states. We control for financial inclusion by the banking penetration at the state level and whether individuals had a bank account. We find evidence of a gendered impact of the macroeconomic shock of demonetisation. While we find that demonetisation is associated with an overall drop in labour force participation, we find that individuals residing in BJP ruled states fared relatively better and this was particularly true for females. We find that while incomes continued to rise post demonetisation, individuals residing in BJP ruled states had relatively better outcomes. We additionally controlled for states which were up for election in 2017 and find that individuals in states which were BJP ruled and up for reelections showed better employment and income outcomes.

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IIMA