From Clients to Citizens: Lessons from Brazil's Bolsa Familia for Delhi

This presentation is a comparative reflection on welfare policy implementation in an Indian city--the city state of Delhi, which is also the national capital, in the light of lessons from Brazil's Bolsa Familia social protection programme. What it does is that it first maps the policy terrain for poverty reduction as seen from the portals of the state, alongside grounded experiences of the poor in terms of how they "receive" these policies, including their experience of interactions with the street-level bureaucracy. This juxtaposition is then raised to discuss a process of practical policy change in Delhi with respect to social protection--the failures in identification of citizens "Below the Poverty Line" (BPL), its replacement by a broader concept of social vulnerability, and finally the entrenched hold of political patrons reversing this process. While the pre-existing policy discourse and implementation arrangements for identifying the poor as "BPL citizens" was one that held out benefits for a politics of patronage and control, the concept of social vulnerability was one that threatened the strong control of the "gatekeeper state". As a part of the process of policy reforms, the city state also engaged with a number of Latin American countries, and specially built linkages with the Brazilian Bolsa Familia--a social policy programme of integrated benefits transfer for the female head of the household. The Bolsa Familia in contrast t Delhi, took strong measures to reduce the hold of the patrons, and rationalise social policy programmes on the platform of integrated benefits transfers. This change in the macro-architecture of social policy happened not just as a measure of technical rationality, but by fostering unmediated links between the state and its most vulnerable citizens. A change in the attitude of state functionaries towards its most poor and vulnerable citizens was critical. Much of the protest and political change in Delhi beginning 2011-15, was in reality an assertion of the poor against the control of the patrons--an assertion of citizenship. The lessons for Delhi therefore are it is important to think about social policy renewal as embedded within the lives of the poor. The state, its policies, and implementation must veer close to what the city's poor expect of the state. These arguments draw from practical policy work with the government, and ethnographic field work in select Delhi slums and unauthorized colonies.

  • Prof. Manisha Priyam, NUEPA
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  • 2017-11-17

Constructing race and ethnicity: Category-making in public policy and administration - the cases of the US and Netherlands

The US federal government named and defined its demographic categories for the first time in 1977, in the Office of Management and Budget Directive No. 15. The Netherlands also defines and uses "identity" categories in registering residents. Empirical research looking at definitions, census and registration form categories, and contemporary policy and administrative practices raises questions as to the meanings of "race" and "ethnicity" in actual use. What, for instance, is being conveyed when a Netherlands medical clinic registration form, asking a question on ethnic origin, provides as possible answers Caucasian, Negro, and Asian? This talk draws on prior and current empirical research in examining the work that state-created categories do (Yanow 2003, Yanow and van der Haar 2013, Yanow, van der Haar, and Volke 2013).

  • Prof. Dvora Yanow, Wageningen University
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  • 2017-11-16

Multiscaling in Finance

The multiscaling behaviour of financial time-series is one of the acknowledged stylized facts in the literature [1]. The source of the measured multifractality in financial markets has been long debated and it has been attributed to mainly two sources: the power law tails and the non linear autocorrelation of the analysed time-series [2,3]. In this talk I will discuss the origin of multiscaling in financial time-series and investigate how to best quantify it [4,5]. In particular I will show results on the application of the Generalized Hurst exponent tool to different financial time series and I will show the powerfulness of such tool to detect changes in markets' behaviours, to differentiate markets accordingly to their degree of development, to asses risk and to provide a new tool for forecasting.

[1] T. Di Matteo, Quantitative Finance 7(1) (2007) 21.
[2] J. W Kantelhardt, Stephan A Zschiegner, Eva Koscielny-Bunde, Shlomo Havlin, Armin Bunde, and H Eugene Stanley, Physica A 316 (2002)87-114
[3] Jozef Barunik, Tomaso Aste, T. Di Matteo, Ruipeng Liu, Physica A 391 (2012) 4234-4251.
[4] R. J. Buonocore, T. Aste, T. Di Matteo, Chaos, Solitons and Fractals 88 (2016) 38-47.
[5] R. J. Buonocore, T. Di Matteo, T. Aste, (2017), Phys.Rev.E, 95 (4) (2017) 042311.

  • Prof. Tiziana D. Matteo, King's College London
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  • 2017-11-10

High Non-GAAP Earnings Predict Abnormally High CEO Pay

Using the standard academic model of executive compensation, we document excessive CEO pay for the S&P 500 firms that report non-GAAP earnings that are much higher than their GAAP earnings. We also find that, on average, such firms have weak contemporaneous and future operating performance relative to other firms. Moreover, contrary to management's usual assertion that non-GAAP earnings more accurately convey a firm's core earnings, we find that non-GAAP earnings do not better correlate with contemporaneous stock returns when compared to GAAP net income or operating income. This latter finding confirms prior results that firms' reporting of non-GAAP earnings does not mislead investors, maybe because firms are simultaneously required to report GAAP earnings and a reconciliation of the adjustments to GAAP earnings. Overall, our evidence suggests that, on average, boards of directors are influenced by large positive non-GAAP earnings adjustments in justifying CEO pay that would otherwise be not supported by the firm's stock price or GAAP earnings performance.

  • Dr. S P Kothari, Sloan School of Management, MIT
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  • 2017-11-09

Demonetization 2016 and Black Economy

On 8 November 2016, India demonetized high denomination currency, wiping out 86 per cent of the currency in circulation. India's well-functioning economy went into a tailspin. This move, it was claimed, was made to wipe out corruption, deter the generation of black money, weed out fake Indian currency notes and curb terrorism. Did it achieve any of this? RBI has admitted that 99 per cent of the old currency notes are back. To understand these issues we need to know more about the black economy. Businesses, especially in the unorganized sectors, came to a grinding halt. Farmers had difficulty buying inputs and many lost their jobs. India continues to grapple with the effects of this move. Credibility of RBI, banks and money is damaged, accountability of institutions has been eroded; and the social divide has widened. There have been many arguments and counter-arguments, but the complete picture needs to be understood.

  • Prof. Arun Kumar, ISS New Delhi
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  • 2017-11-07

The Kumbh Mela Experiment (KME): Measuring and understanding the dynamics of mankind's largest crowd - Experiences from Kumbh Mela 2016 in Ujjain

The Kumbh Mela Experiment (KME) is an ongoing Indo-Dutch collaborative research project funded jointly by the Department of Electronics and Information Technology (DeitY), Govt. of India, and Netherlands Organization for Scientific Research (NWO), Netherlands. The Transportation Engineering (TE) Lab at the Indian Institute of Science (IISc) Bangalore is the lead partner of this project. The aim of the project is to use big data and Internet of Things (IOT) for understanding crowd dynamics in mass gatherings and develop a crowd management solution particularly focusing on crowd risk. As the name clearly suggests, the data collection was done during the recently held Kumbh Mela (Simhasth-2016) in Ujjain, M.P., India during 22nd April to 21st May 2016. An "Indo-Dutch Collaborative Research Camp" was set up in the Kumbh Mela area for the months of April and May 2016 to carry out data collection and experimentation activities during Simhasth-2016 for the KME project. The primary data sources/devices used were: about 540 wearable tracking devices, 3000 wearable lanyard devices, Go Pro cameras, drones, questionnaire survey etc. The secondary data sources include: police CCTV camera data and drone data, Mahakal Temple CCTV data, etc. This presentation on KME will explain the scientific aspects of the project and the experiences of data collection.

  • Prof. Ashish Verma, IISc Bangalore
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  • 2017-11-07

"I" seek uniqueness and "WE" avoid risk: The role of consumer motivation in retail shopping

Retailers frequently use selling cues for effective promotional campaigns. Drawing from consumer regulatory focus motivation and selling cue literature, this research explores the influences of selling cue, consumer motivation, and product type on consumer perceptions of risk, product uniqueness and purchase intentions. Results from three studies show that selling cue and consumer motivation influence purchase intentions. Perceived product risk and perceived product uniqueness act as psychological mechanisms. Results also show that selling cue and product type influences purchase intentions. These results add to existing literature and have managerial implications.

  • Prof. Gopal Das, IIM Rohtak
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  • 2017-11-03