Template-Type: ReDIF-Paper 1.0 Author-Name: NIdhi Aggarwal Author-Name-First: Nidhi Author-Name-Last: Aggarwal Author-Email: nidhi.aggarwal@iimu.ac.in Author-Workplace-Name: Indian Institute of Management, Udaipur Author-Name: Venkatesh Panchapagesan Author-Name-First: Venkatesh Author-Name-Last: Panchapagesan Author-Email: venky@iimb.ac.in Author-Workplace-Name: Indian Institute of Management, Bangalore Author-Name: Susan Thomas Author-Name-First: Susan Author-Name-Last: Thomas Author-Email: sthomas.entp@gmail.com Author-Workplace-Name: xKDR Forum Title: When is the order-to-trade ratio fee effective? Abstract: Regulators use measures such as a fee on high order to trade ratio (OTR) to slow down high frequency trading. Their impact on market quality is, however, mixed. We study a natural experiment in the Indian stock market where such a fee was introduced twice, with differences in motivation and implementation. Using a difference-in-difference approach, we find that the fee decreased OTR and improved market quality when it was imposed on all orders, while it had little effect when it was imposed selectively on some orders. Improvement in liquidity was driven by a reduction in adverse selection costs following lower OTR. Length: 43 pages Creation-Date: 2022-03 File-URL: https://papers.xkdr.org/papers/2022_otrimpactF.pdf File-Format: Application/pdf File-Function: First version, 2022 Number: 11 Classification-JEL: G14,G18 Handle: RePEc:anf:wpaper:11 Template-Type: ReDIF-Paper 1.0 Author-Name: Surbhi Bhatia Author-Name-First: Surbhi Author-Name-Last: Bhatia Author-Email: surbhibhatia1906@gmail.com Author-Workplace-Name: Independent Researcher Author-Name: Manish K. Singh Author-Name-First: Manish Author-Name-Last: Singh Author-Email: mks@hs.iitr.ac.in Author-Workplace-Name: Department of Humanities and Social Sciences Indian Institute of Technology Roorkee and XKDR Forum Title: Fifty years since Altman (1968): Performance of financial distress prediction models Abstract: Using bankruptcy filings under the new Insolvency and Bankruptcy Code (2016), we investigate the effect of firm characteristics and balance sheet variables on the forecast of one-year-ahead default for Indian manufacturing firms. We compare traditional discriminant analysis and logistic regression models with state-of-the-art variable selection technique-the least absolute shrinkage and selection operator, and the unsupervised techniques of variable selection-to identify key predictive variables. Our findings suggest that the ratios considered as important by Altman (1968) still hold relevance for the prediction of default, no matter the technique applied for variables selection. We find cash to current liability (a liquidity measure) as an additional robust and significant predictor of default. In terms of predictive accuracy, the reduced-form multivariate discriminant analysis model used in Altman (1968) performs at par with the more advanced econometric specification for both in-sample and full-sample default prediction. Length: 31 pages Creation-Date: 2022-06 File-URL: https://papers.xkdr.org/papers/bhatiaSingh2022_altman_zscore.pdf File-Format: Application/pdf File-Function: First version, 2022 Number: 12 Classification-JEL: C53, G17, G32, G33 Handle: RePEc:anf:wpaper:12 Template-Type: ReDIF-Paper 1.0 Author-Name: Renuka Sane Author-Name-First: Renuka Author-Name-Last: Sane Author-Email: renukas@gmail.com Author-Workplace-Name: NIPFP Author-Name: Ajay Shah Author-Name-First: Ajay Author-Name-Last: Shah Author-Email: ajayshah@mayin.org Author-Workplace-Name: XKDR Forum Title: Crime victimisation surveys in Indian criminal justice system reform Abstract: A primal goal in state building is the establishment of conditions of safety for residents. This creates conditions for individuals to explore the world, and engage in creativity and leadership, across all walks of life from economics to politics, thus positively impacting upon the culture. The criminal justice system is the state-run institutional arrangement which is tasked with creating these conditions of safety of individuals. Traditionally, policy thinking on the criminal justice system has emphasised inputs (expenditures, recruitment) and outputs(trials, prisoners). As with other elements of public policy, it is important to measure outcomes: the safety as seen by residents. Crime victimisation surveys are the fundamental building block of the criminal justice system which deliver outcomes measurement. A regular program of such measurement can feed back into improved working of the criminal justice system, and the analysis of the causes and consequences of personal safety. In this paper we review developments on this measurement program in India of recent years. Length: 14 pages Creation-Date: 2022-08 File-URL: https://papers.xkdr.org/papers/SaneShah2022_cvs.pdf File-Format: Application/pdf File-Function: First version, 2022 Number: 13 Classification-JEL: H41, C81, K42 Handle: RePEc:anf:wpaper:13 Template-Type: ReDIF-Paper 1.0 Author-Name: Nidhi Aggarwal Author-Name-First: Nidhi Author-Name-Last: Aggarwal Author-Email: nidhi.aggarwal@iimu.ac.in Author-Workplace-Name: Indian Institute of Management, Udaipur Author-Name: Manish K. Singh Author-Name-First: Manish K. Author-Name-Last: Singh Author-Email: mks@hs.iitr.ac.in Author-Workplace-Name: Indian Institute of Technology, Roorkee Author-Name: Susan Thomas Author-Name-First: Susan Author-Name-Last: Thomas Author-Email: sthomas.entp@gmail.com Author-Workplace-Name: O. P. Jindal Business School and XKDR Forum Title: Do decreases in Distance-to-Default predict rating downgrades? Abstract: Credit rating agencies have long been criticised for being slow to downgrade ratings, when the financial health of the firm deteriorates. This stands out in sharp contrast to how security market prices of the firm respond more rapidly, during the same time. In this paper, we ask whether this disparity between the two indicators can be bridged. We estimate a logit model for the probability of a rating downgrade, using a large dataset of firms in India which combines both high frequency market price data and lower frequency accounting data. We find that changes in measures such as the Distance to Default, in combination with firm characteristics such as ownership structure, can predict a higher probability of ratings downgrades, before they are announced. This will be particularly useful for regulated financial firms, which have to re-weight their portfolios to satisfy micro-prudential requirements, based on downgrades in credit ratings. Length: 31 pages Creation-Date: 2022-09 File-URL: https://papers.xkdr.org/papers/2022Aggarwaletal_changeindtdandratings.pdf File-Format: Application/pdf File-Function: First version, 2022 Number: 14 Classification-JEL: G21, G24, G32 Handle: RePEc:anf:wpaper:14 Template-Type: ReDIF-Paper 1.0 Author-Name: Rishab Bailey Author-Name-First: Rishab Author-Name-Last: Bailey Author-Email: rishab.bailey@gmail.com Author-Workplace-Name: XKDR Forum Author-Name: Ajay Shah Author-Name-First: Ajay Author-Name-Last: Shah Author-Email: ajayshah@mayin.org Author-Workplace-Name: XKDR Froum Author-Name: Ameya Naik Author-Name-First: Ameya Author-Name-Last: Naik Author-Email: ameya.naik@egov.org.in Author-Workplace-Name: eGovernments Foundation Author-Name: Brinda Lashkari Author-Name-First: Brinda Author-Name-Last: Lashkari Author-Email: brinda.lashkari@egovernments.org Author-Workplace-Name: eGovernments Foundation Title: Comments to MEITY on the Draft National Data Governance Framework Policy Abstract: In May 2022, the Ministry of Electronics and Information Technology (MEITY) initiated consultations on a draft National Data Governance Framework Policy. In our comments to MEITY, we point out that while the policy may be well intentioned in promoting development of the Indian startup ecosystem, creating a restricted access platform may not be the best method of achieving such a goal. In addition to being dif- ficult to restrict downstream uses of data only to Indian entities, a restricted access platform could come at a cost to open data initiatives which enhance government accountability. In addition to suggestions directed at enhancing useability of the proposed data access platform an protecting against harm from unethical data usage, we also suggest methods to enhance the accountability and capacity of the institutional mechanisms envisaged under the framework. Length: 7 pages Creation-Date: 2022-06 File-URL: https://papers.xkdr.org/papers/2022Baileyetal_responseNDGFP.pdf File-Format: Application/pdf File-Function: First version, 2022 Number: 15 Classification-JEL: H83, H82, H4 Handle: RePEc:anf:wpaper:15 Template-Type: ReDIF-Paper 1.0 Author-Name: Pavithra Manivannan Author-Name-First: Pavithra Author-Name-Last: Manivannan Author-Email: pavithra.manivannan4@gmail.com Author-Workplace-Name: XKDR Forum Author-Name: Susan Thomas Author-Name-First: Susan Author-Name-Last: Thomas Author-Email: sthomas.entp@gmail.com Author-Workplace-Name: XKDR Forum and Jindal Global Business School Author-Name: Bhargavi Zaveri Author-Name-First: Bhargavi Author-Name-Last: Zaveri Author-Email: bhargavizaveri@gmail.com Author-Workplace-Name: National University of Singapore Title: Evaluating contract enforcement by courts in India: a litigant's lens. Abstract: The literature on the performance evaluation of the judiciary captures the perspectives of judges, researchers and court administrators. However, it is not obvious if a litigant who proposes to access the judiciary for the resolution of a dispute would use the same or similar metrics when evaluating the performance of courts. In this paper, we review the global literature that evaluates the performance of the judiciary and identify which of the metrics in the literature would directly matter to a litigant who proposes to access the courts for redress. Using the litigant's expectations as performance metrics, we develop an evaluative framework for comparing similar courts. Our work creates the foundation for developing an information system that could potentially help litigants make informed choices when approaching courts. Length: 26 pages Creation-Date: 2022-11 File-URL: https://papers.xkdr.org/papers/2022Manivannanetal_courtmetrics.pdf File-Format: Application/pdf File-Function: First version, 2022 Number: 16 Classification-JEL: K, K41 Handle: RePEc:anf:wpaper:16 Template-Type: ReDIF-Paper 1.0 Author-Name: Agam Gupta Author-Name-First: Agam Author-Name-Last: Gupta Author-Email: agam@iitd.ac.in Author-Workplace-Name: Indian Institute of Technology Delhi Author-Name: Yash Khandelwal Author-Name-First: Yash Author-Name-Last: Khandelwal Author-Email: yash_k@ee.iitr.ac.in Author-Workplace-Name: Indian Institute of Technology Roorkee Author-Name: Manish K. Singh Author-Name-First: Manish Author-Name-Last: Singh Author-Email: mks@hs.iitr.ac.in Author-Workplace-Name: Indian Institute of Technology Roorkee and xKDR Forum Author-Name: Ashutosh Singla Author-Name-First: Ashutosh Author-Name-Last: Singla Author-Email: ashutosh_s@cs.iitr.ac.in Author-Workplace-Name: Indian Institute of Technology Roorkee Title: Do fantasy sports players' actions influence their performance in Dream11 contests? Adding data to the debate on skill vs chance Abstract: Daily fantasy sports platforms allow users to compete with one another by creating their own teams within some constraints, using their knowledge or intuition about the performance of players in real life. Since players’ actual performance on the match day is uncertain, emerging as a winner in such contests combines skill and chance. Using data from Dream11, a fantasy sports platform in India, through participation in public contests on the platform during the ICC T20 cricket World Cup, we test whether skill or chance plays the dominant role for winners. When we proxy lack of skill by randomly selecting teams via computer simulation and comparing the performance of real teams with simulated teams, our findings suggest that chance and skill are evenly balanced. In our sample of 31 games, in almost 50% games, we see that teams picked randomly perform at par or better than the real teams constructed by real users. Furthermore, we observe that while real teams perform better in games where the skill gap between two teams is much higher, randomly simulated teams fare better in closely matched teams. However, when we do within players comparison across matches, we found that participants playing with multiple teams and participants playing more games outperform the rest. Length: 32 pages Creation-Date: 2022-12 File-URL: https://papers.xkdr.org/papers/2022_Guptaetal_rpSkill_vs_chance.pdf File-Format: Application/pdf File-Function: First version, 2022 Number: 17 Classification-JEL: Z2, Z21, Z28 Handle: RePEc:anf:wpaper:17 Template-Type: ReDIF-Paper 1.0 Author-Name: Harleen Kaur Author-Name-First: Harleen Author-Name-Last: Kaur Author-Email: hrlin.kaur@gmail.com Author-Workplace-Name: Independent Researcher' Author-Name: Ajay Shah Author-Name-First: Ajay Author-Name-Last: Shah Author-Email: ajayshah@mayin.org Author-Workplace-Name: xKDR Froum Author-Name: Siddhartha Srivastava Author-Name-First: Siddhartha Author-Name-Last: Srivastava Author-Email: siddharta93@gmail.com Author-Workplace-Name: NIPFP Title: Process improvement for government drug procurement in India Abstract: In India, drug quality is an important problem. Government agencies are an important buyer of drugs, and also face significant problems with drug quality. In this paper, we examine the mechanisms used for drug purchase by four Indian states - Rajasthan, Punjab, Bihar and Gujarat. We establish a taxonomy of 13 design elements that define the drug procurement process. We engage in deductive reasoning about the design elements that appear to be useful and those that are less so. This work would help policy makers placed in an Indian public sector context in devising better procedures for drug purchase. Length: 19 pages Creation-Date: 2022-12 File-URL: https://papers.xkdr.org/papers/KSS2021_improving_india_drugs_procurement.pdf File-Format: Application/pdf File-Function: First version, 2022 Number: 18 Classification-JEL: I11, I18, H83 Handle: RePEc:anf:wpaper:18 Template-Type: ReDIF-Paper 1.0 Author-Name: Ayush Patnaik Author-Name-First: Ayush Author-Name-Last: Patnaik Author-Email: ayushpatnaik@gmail.com Author-Workplace-Name: xKDR Forum Author-Name: Ajay Shah Author-Name-First: Ajay Author-Name-Last: Shah Author-Email: ajayshah@mayin.org Author-Workplace-Name: xKDR Froum Author-Name: Susan Thomas Author-Name-First: Susan Author-Name-Last: Thomas Author-Email: sthomas.entp@gmail.com Author-Workplace-Name: xKDR Forum Title: Foundations for nighttime lights data analysis Abstract: Nighttime lights captured from satellites has emerged as an important way to measure prosperity. Every researcher who uses the files released by NASA and NOAA faces the challenge of pre-processing it in addressing data quality issues. We present NighttimeLights.jl, a package written in Julia, which implements conventional and novel methods for cleaning the data. The package also serves as a platform for methodological research in remote sensing. Length: 9 pages Creation-Date: 2022-12 File-URL: https://papers.xkdr.org/papers/2022Patnaiketal_foundationsforNighttimelightsDataanalysis.pdf File-Format: Application/pdf File-Function: First version, 2022 Number: 19 Classification-JEL: Y90 Handle: RePEc:anf:wpaper:19