Access, Agenda Constraint and Informational Lobbying

We develop a model of informational lobbying in which a policymaker must decide which issues to implement reforms on. On each issue there is an informed interest group that always favour the adoption of reform, and which can lobby the policymaker by offering to provide truthful information about the state of the world. A key feature of our model is that the the policymaker faces resource constraints which inhibit his ability to grant access to lobbying interest groups and may also restrict his ability to implement reform on all issues. We show that while the act of lobbying can signal pro-reform information, it may not do so perfectly. In particular, an interest group may want to lobby the policymaker even when it does not possess pro-reform information in the hope that the policymaker is unable to audit the information provided but still takes the act of lobbying as a signal that the state is favourable to reform. We then show that a restriction on the number of issues on which reforms can be implemented can improve the quality of information transmission by making the disciplining role of access more credible. Indeed, in some cases imposition of such a restriction leads to a Pareto improvement.

  • Prof. Mandar Oak, University of Adelaide, Australia
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  • 2015-12-21

Corporate Social Responsibility Report Narratives and Analyst Forecast Accuracy

Standalone corporate social responsibility (CSR) reports vary considerably in content due in part to their voluntary nature and the lack of an accountability framework in CSR reporting. In this study, we develop a CSR disclosure score based on the tone, readability, length, and the numerical and horizon content of the CSR reports’ narratives, and examine the relationship between CSR disclosure scores and analyst forecast accuracy. We find that while CSR reporters with higher disclosure scores are associated with more accurate analyst forecasts, low score CSR reporters do not have better analyst forecast accuracy than firms issuing no CSR reports. In addition, we also find that while improvement in CSR reporting style (tone and readability) has a stronger effect on improving analyst forecast accuracy, increasing the CSR reporting amount (length, numerical content, and horizon content) alone does not have such an effect. Furthermore, we find that disclosure scores of first-time CSR reports have a weaker association with analyst forecast accuracy than disclosure scores of subsequent CSR reports. Together, our findings suggest that better CSR reporting style and commitment to persistent CSR reporting practices play important role in improving analyst forecast accuracy, but simply increasing the quantity of information to be disclosed on CSR reports has little capital market consequences.

  • Prof. Suresh Radhakrishnan, University of Texas at Dallas
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  • 2015-12-16

Bayesian Nonparametrics - Dirichlet Process and application

This talk would present a brief overview of some popular priors studied in Bayesian nonparametrics. Starting with Dirichlet process, we will explore mixture models hierarchical models and indicate some applications. If time permits, we will also discuss some issues related to asymptotic validation of these methods.

  • Prof. R.V. Ramamoorthi, Michigan State University , USA and Chennai Mathematical Institute, India
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  • 2015-12-15

How does point-of-purchase advertising influence sales? A randomized field study

Point of Purchase (POP) advertising is ubiquitous; it is hard to find a retail store, fast food restaurant, or convenience store that does not have signs and banners advertising various brands. Despite its frequent use, not much research has examined the impact of POP advertising on sales of the product, probably because it is difficult to exactly quantify its influence and distinguish it from price promotion signs. Building on past work on recency of persuasive influence, malleable versus stable consumer preferences, retail aesthetics, technology, and competitor activity, we propose that POP advertising is at best likely to have no influence on sales and at worst could have a negative influence. To disentangle the causal influence of POP advertising we used a randomized field study. The study included over 300 stores from a large retailer, two product categories, one hedonic and one functional, and sales pre and post intervention.
The analyses indicated no positive influence of POP advertising on sales; in one case the influence is negative. Along with theoretical insights, the result informs managerial practice that money currently spent on POP advertising could potentially be spent on other profitable marketing activities.

  • Prof Himanshu Mishra and Prof. Arul Mishra, University of Utah
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  • 2015-12-15

Corporate Debt Restructuring, Bank Competition and Stability: Evidence from creditors’ perspective

This paper estimates the causal effect of a unique programme of corporate debt restructuring (CDR) on stability of Indian banks over the period 1992-2012. The banks who participated in the programme were extended regulatory forbearance on asset classification and provisioning on the restructured corporate loans. We find that banking stability of the participated banks increases substantially after the implementation of the programme. Using stochastic frontier analysis approach, we estimate two variant measures of market power and investigate the interactive effect of CDR on bank stability. The result shows that the positive effect of CDR on stability declines at higher level of market power, implying that the CDR mechanism is less effective for the participating banks beyond a threshold level of market power. We also find that the second phase of deregulation and the direct effect of market power have significant positive effect on the overall soundness of Indian banks. To provide unbiased treatment effects of CDR eliminating any sample selection bias, we further confirm the positive effect of CDR on bank stability using a number of alternative matching estimators. Our results (both parametric and non-parametric) remain insensitive to an array of robustness tests including quality of matching.

  • Prof. Sushanta Mallick, Queen Mary University of London, UK
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  • 2015-12-14

Identifying the most and least promising customers through similarity kernels

Research has demonstrated that identifying profitable customers and acquiring them is far more expensive than retaining existing customers. The higher cost emerges because firms are unable to identify the truly profitable customers or those that would convert to their brand. In their inability to accurately identify leads they spend resources on many leads that appear potential but do not convert resulting in a lot of waste. One way to identify the small number of promising customers is to recognize that promising customers appear like anomalies. However, traditional statistical methods cannot identify anomalous observations combining both numeric and categorical variables in a dataset. This task becomes complex in this age of BigData that contain variables that can’t be assumed to follow any statistical distribution, are at times sparse and are generated via a dynamic process where it is hard to fit a stable predictive model a priori.

We present a method of detecting anomalous yet promising customers using similarity kernels that can handle mixed attribute data. We test the performance of six kernel based algorithms to detect anomalies using both simulated and real marketplace data. Our proposed method holds implications for research on word-of-mouth (WOM) to find out consumers who are most likely to diffuse a message versus those who are least likely to. In customer churn it helps companies to correctly identify customers who are more likely to churn so that they can invest resources on them and avoid wasteful spending on those who are less likely to churn. In sales data it helps identify heavy users of a product generating high sales versus non-users on whom offers have no influence. In market segmentation research the presence of such extreme observations can lead to consumers being classified into wrong clusters. Correctly identifying the most valuable, from the least valuable, customers can result in targeted sales promotion offers, accurate online advertisement delivery and even better direct marketing.

  • Prof. Arul Mishra, University of Utah
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  • 2015-12-11

Missing Men, Migration and Labour Markets:Evidence from India

How do labor markets function when a large part of the able-bodied male workforce is absent due to out-migration? This question holds great significance as it affects regions covering over 200 million people in India and many other parts of the world. In this paper, we analyze individual and district level data on internal and international migration, remittances, sex ratios and labor market variables in India from the perspective of the migrant’s source region and find that the ‘missing men’ phenomenon is associated with

(a) Feminization of the agricultural workforce (b) Higher levels of male employment in the construction and rural non-farm services sector and (c) Higher rural wages for males due to tighter labor markets. We argue that these associations are likely to be causal in nature through an instrumental variable strategy that employs historic migration networks that evolved in the late nineteenth century as instruments for current migration.

  • Prof. Chinmay Tumbe, Tata Institute of Social Sciences, Hyderabad
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  • 2015-12-02

Economic Inequality from Statistical Physics Point of View

Similarly to the probability distribution of energy in physics, the probability distribution of money among the agents in a closed economic system is also expected to follow the exponential Boltzmann-Gibbs law, as a consequence of entropy maximization. Analysis of empirical data shows that income distributions in the USA, European Union, and other countries exhibit a well-defined two-class structure. The majority of the population (about 97%) belongs to the lower class characterized by the exponential ("thermal") distribution. The upper class (about 3% of the population) is characterized by the Pareto power-law ("superthermal") distribution, and its share of the total income expands and contracts dramatically during booms and busts in financial markets. Globally, data analysis of energy consumption per capita around the world shows decreasing inequality in the last 30 years and convergence toward the exponential probability distribution, in agreement with the maximal entropy principle. Similar results are found for the global probability distribution of CO2 emissions per capita. Global inequality matters for the international effort to reach an agreement for addressing climate change. This work was supported by a grant from the Institute for New Economic Thinking (INET). All papers are available at For recent coverage in Science magazine, see

  • Prof. Victor Yakovenko, University of Maryland, USA
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  • 2015-12-02