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Working Papers | 2017

Shiny Alternative for Finance in the Classroom

Jayanth R. Varma and Vineet Virmani

Despite the popularity of open-source languages like R and Python in modern empirical research and the data-science industry, spreadsheet programs like Microsoft Excel remain the data analysis software of choice in much of the business-school curriculum, including at IIMA. Even if instructors are comfortable with modern programming languages, they have to pitch their courses at the level of computer literacy prevalent among students. Excel then appears to be a natural choice given its popularity, but this choice constrains the depth of analysis that is possible and requires a certain amount of dumbing-down of the subject by the instructor. Recent software advances however make the ubiquitous web browser a worthy challenger to the spreadsheet.
This article introduces one such browser-based tool called Shiny for bringing finance applications to the classroom and smart phones. Fueled by the availability of high-quality R packages in finance and statistics, Shiny brings together the power of
HTML with the R programming language. It naturally creates an environment for the instructor to focus on the role of parameters and assumptions in analysis without the clutter of data, and allows the instructor to go beyond the toy problems that are necessitated by the nature of spreadsheets. The learning curve is short for an interested instructor with even a rudimentary exposure to programming in any language. The
article ends with the discussion of a fully-worked out example of Shiny for teaching the mean variance efficient frontier in a basic investments course.

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Working Papers | 2017

Travel Time Prediction for Taxi-GPS Data Streams

A. K. Laha and Sayan Putatunda

The analysis of data streams offers a great opportunity for development of new methodologies and applications in the area of Intelligent Transportation Systems. In this paper, we propose a new incremental learning approach for the travel time prediction problem for taxi GPS data streams in different scenarios and compare the same with four other existing methods. An extensive performance evaluation using
four real life datasets indicate that when the drop-off location is known and the training data sizes are small to moderate the Support Vector Regression method is the best choice considering both prediction accuracy and total computation time. However when the training data size becomes large the Randomized K-Nearest Neighbor Regression with Spherical Distance becomes the method of choice. Even when
the drop-off location is unknown then the Support Vector Regression method is the best choice when the training data size is small to moderate while for large training data size the Linear Regression method is a good choice. Finally, when continuous prediction of remaining travel time and continuous updating of total travel time along the trajectory of a trip are considered we find that the Support Vector
Regression method has the best predictive accuracy. We also propose a new hybrid method which improves the prediction accuracy of the
SVR method in the later part of a trip.

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Working Papers | 2017

Enabling a Mobile Cloud Service: Data-Sharing in Ad-hoc Device-to-Device Mobile Networks

Kavitha Ranganathan

The objective of this work is to build a data-sharing application for an ad-hoc network of mobile devices, where users can exchange data/files among themselves without relying on traditional communication channels like telecom or network operators. In other words, we aim to build a mobile cloud service for data sharing. This paper examines the resource discovery and selection (also called replica selection) issue in such a mobile cloud. We propose a novel decentralized algorithm where nodes can first discover and then choose the best replica to request for, from among the different alternatives identified. Additionally, our paper comes up with a new metric to evaluate different replicas, that is, what could be a desirable definition of the 'best' replica in such a network.

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Working Papers | 2017

India's Horticulture Sector - A Port- Level Analysis of Onion Export Pricing

Poornima Varma and Issar Akash

Extending the traditional model of agricultural pricing behaviour and market structure with the constructed commodity specific export weighted exchange rates, this paper analyses the exchange rate induced market power, asymmetric effects of exchange rate, country specific discrimination as well as the impact of government's minimum export price policy on the export prices of Indian onion exporters using port-level data. Onion price escalation has been seen to cause tears not only in the kitchen but tumble governments. Although this study observes a competitive market structure in majority of the destination market, however, the pricing-to-market behaviour was prevalent in three destination markets where the exporters were following local currency stabilization. Furthermore, minimum export price policy variable showed that even when the minimum export price requirement was in place, exporters were able to adjust their price downward and sell in those markets.

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Working Papers | 2017

Adoption of Natural Resource Management Technologies under Information Constraints: The Case of System of Rice Intensification (SRI) in India

Poornima Varma

This study examines the role of information constraints in the adoption of System of Rice Intensification (SRI) in India by explicitly incorporating information in the adoption model. The results showed that effective information along with other factors such as membership in farmer organisation, availability of labourers, irrigation facility etc were important in determining the SRI adoption. The results also revealed the importance of scaling up of activities under the Government of India's National Food Security Mission programme for promoting greater dissemination and adoption of SRI.

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Working Papers | 2017

Adoption of System of Rice Intensification and its Impact on Rice Yields and Household Income: An Analysis for India

Poornima Varma

Natural resource management (NRM) technologies, such as the system of rice intensification (SRI) are recognized as a promising systemic approach to enhance rice production at affordable costs without harming the environment. Yet there is no consensus in the literature with respect to the factors influencing the adoption as well as the welfare outcomes of adoption. This paper identifies the factors that affect farmers' decisions to adopt SRI in major rice producing States of India and its impact on rice yield and household income. The multinomial endogenous treatment effects model adopted in the present study analyses the factors influencing the adoption and the impact of adoption in a joint framework. Results suggest that household assets, irrigation, access to information etc. increased the likelihood of household adopting SRI whereas the size of landholding, the number of years household stayed in rice cultivation, fear of poor yield, etc. decreased the likelihood of adopting SRI. The welfare impacts of SRI adoption revealed that all combinations of SRI individually and as a group (plant management, water management and soil management) had an impact on yield. However, the impact of SRI adoption on household income was quite mixed.

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Working Papers | 2017

Institutional Quality and International Differences in Firm Productivity

Issar Akash, Jamus Jerome Lim, and Sanket Mohapatra

In this paper, we examine how firm-level productivity growth is dependent on a broad range of institutional quality measures at the country level. Using a sample of 3,446 firms in 58 advanced and emerging economics, we show that such institutions exert a statistically and economically significant effect on changes in firm TFP. We utilize data envelopment analysis to construct firm-level measures of Malmquist productivity, which we then condition on a range of country-level institutions, using both a full set of fixed effects and system generalized method of moments to address potential endogeneity concerns. The baseline effect is robust to alternative measures of institutions, variations in model specification, alternative temporal aggregations, and the inclusion of external instruments. Additional decompositions further reveal that the institutional effect operates via improved productive efficiency (rather than technological progress), and that the key institutions are those associated with rule of law and regulatory quality

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Working Papers | 2017

Gold Monetization in India as a Transformative Policy:
A Mixed Method Analysis

Priya Narayanan, Balagopal Gopalakrishnan, and Arvind Sahay

India is the second largest consumer of gold in the world and gold is a major contributor to the current account deficit. Much of the gold goes out of circulation and is not available to support economic activity. To encourage consumers to bring the gold back into circulation, the government of India instituted the Gold Monetization Policy in 2015. This research views the Gold Monetization Policy in India through the lens of consumer associations with gold, as well as the banker and refiner perspectives on implementation challenges. The success of this policy is important for the country to better manage its current account balance, in a milieu where gold consumption holds sociocultural importance. The research uses an empirical approach to analyse how various stakeholders have approached the policy, and provides suggestions to increase uptake of the policy. It employs a mixed method approach to understand the motivations and barriers faced by various stakeholders in the gold ecosystem.
First, a nationwide survey-based study of 1171 households, across 10 states that constitute approximately three-quarters of annual national gold consumption, was conducted to understand the consumer associations with and attributions related to gold. This shows that family functions and festivals to be triggers for gold purchase, indicating ingrained the habit and planned accumulation. There is also high liquidity and safety association of gold (which is also not considered as having any substitute) along with a clear reluctance to sell gold received as a gift. Rural consumers are more reluctant to part with gold as compared to urban but are also ready to pledge gold as collateral suggesting requirement related liquidity use of gold.
Second, an interview based study was conducted with senior management of 6 banks, 5 refiners and one industry consultant to understand the challenges and implications of the policy for members of the gold ecosystem. Discussions with these stakeholders clarified that banks would promote products based on this policy if they had more control on the process and if there was clear separation of risks

or effective mitigation of risks relating to the operationalization of the policy. Finally, an econometric
analysis of gold consumption and its potential determinants was conducted using household data from all 640 districts of the National Sample Survey for 2011-12. The analysis shows that propensity to consume gold is positively correlated with proportion of females in the household and with number of daughters in the household. Also, ceteris paribus, rural households have a higher propensity to consume gold, and Hindu households have a higher propensity to consume gold.
Clearly, increasing the effectiveness of the Gold Monetization Policy depends on a deeper understanding of consumers' interactions with and sentiments towards gold. The effectiveness of the policy also depends on recognizing the challenges faced and incentives required by banks, refiners and other stakeholders in implementing this policy. This research is an attempt at developing such an understanding.

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Working Papers | 2017

Global Risk and Demand for Gold by Central Banks

Balagopal Gopalakrishnan and Sanket Mohapatra

This paper examines the influence of global risk on the holding of gold by central banks based on annual data for 100 countries during 1990-2015. We use a dynamic panel generalized method of moments (GMM) model to estimate this effect, controlling for a variety of domestic factors. Consistent with portfolio diversification and perception of gold as a safe asset, we find that the gold holdings of central banks increase in response to higher global risk. This effect is larger for high-income countries than for developing countries. Moreover, greater capital account openness is associated with a stronger response of central banks' gold holding to global risk, while a higher ratio of overall reserves to imports is associated with a weaker response. We also find evidence that the sensitivity depends on whether the currency regime followed is fixed or floating, with higher responsiveness in the case of fixed rate regimes. The baseline results are robust to alternate estimation methods, exclusion of crisis years, active and passive management of gold reserves and additional controls. These findings suggest that central banks adjust their gold holdings in response to changes in global risk conditions, with the magnitude of response depending on reserve management capacity and country-specific vulnerabilities.

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Working Papers | 2016

Optimization of Customized Pricing with Multiple Overlapping Competing Bids

Goutam Dutta and Sumeetha R. Natesan

In this paper, we consider the case of project procurement where there is a single buyer and multiple sellers who are bidding. We consider one seller having one or more competitors. We formulate the pricing problem from the point of view of one seller having one or multiple competitors (say n). We also assume that based on past experience, we have some idea about the distribution of bid prices of the competitors. We consider uniform distribution to describe the bid price of the competitors. The prices of the competitors are pairwise mutually independent and the price range are either identical or different and overlapping. We consider maximizing the expected contribution. Assuming the contribution as a linear function of price we compute the conditions for maximization of the expected contribution to profit in case of n bidders. Further, we also compare the optimization results with simulation results.

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