Differences Make a Difference: Diversity in Social Learning and Value Creation
Yiwei Fang, Bill Francis, Iftekhar Hasan
Journal of Corporate Finance,
2018
Abstract
Prior research has demonstrated that CEOs learn privileged information from their social connections. Going beyond the importance of the number of social ties in a CEO's social network, this paper studies the value generated from a diverse social environment. We construct an index of social-network heterogeneity (SNH) that captures the extent to which CEOs are connected to people of different demographic attributes and skill sets. We find that higher CEO SNH leads to greater firm value through the channels of better corporate innovation and diversified M&As. Overall, the evidence suggests that CEOs' exposure to human diversity enhances social learning and creates greater growth opportunities for firms.
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To Invest or Not to Invest, That Is the Question: Analysis of Firm Behavior under Anticipated Shocks
Dejan Kovač, Nikola Kleut, Boris Podobnik, Vuk Vukovic
Plos One,
No. 8,
2016
Abstract
When companies are faced with an upcoming and expected economic shock some of them tend to react better than others. They adapt by initiating investments thus successfully weathering the storm, while others, even though they possess the same information set, fail to adopt the same business strategy and eventually succumb to the crisis. We use a unique setting of the recent financial crisis in Croatia as an exogenous shock that hit the country with a time lag, allowing the domestic firms to adapt. We perform a survival analysis on the entire population of 144,000 firms in Croatia during the period from 2003 to 2015, and test whether investment prior to the anticipated shock makes firms more likely to survive the recession. We find that small and micro firms, which decided to invest, had between 60 and 70% higher survival rates than similar firms that chose not to invest. This claim is supported by both non-parametric and parametric tests in the survival analysis. From a normative perspective this finding could be important in mitigating the negative effects on aggregate demand during strong recessionary periods.
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Sign Restrictions, Structural Vector Autoregressions, and Useful Prior Information
Christiane Baumeister, James D. Hamilton
Econometrica,
No. 5,
2015
Abstract
This paper makes the following original contributions to the literature. (i) We develop a simpler analytical characterization and numerical algorithm for Bayesian inference in structural vector autoregressions (VARs) that can be used for models that are overidentified, just‐identified, or underidentified. (ii) We analyze the asymptotic properties of Bayesian inference and show that in the underidentified case, the asymptotic posterior distribution of contemporaneous coefficients in an n‐variable VAR is confined to the set of values that orthogonalize the population variance–covariance matrix of ordinary least squares residuals, with the height of the posterior proportional to the height of the prior at any point within that set. For example, in a bivariate VAR for supply and demand identified solely by sign restrictions, if the population correlation between the VAR residuals is positive, then even if one has available an infinite sample of data, any inference about the demand elasticity is coming exclusively from the prior distribution. (iii) We provide analytical characterizations of the informative prior distributions for impulse‐response functions that are implicit in the traditional sign‐restriction approach to VARs, and we note, as a special case of result (ii), that the influence of these priors does not vanish asymptotically. (iv) We illustrate how Bayesian inference with informative priors can be both a strict generalization and an unambiguous improvement over frequentist inference in just‐identified models. (v) We propose that researchers need to explicitly acknowledge and defend the role of prior beliefs in influencing structural conclusions and we illustrate how this could be done using a simple model of the U.S. labor market.
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Entry and Strategic Information Display in Credit Markets
Jan Bouckaert, Hans Degryse
Economic Journal,
No. 513,
2006
Abstract
In many countries, lenders voluntarily provide information about their borrowers to private credit registries. A recent World Bank survey reveals that the display of a lender's own borrower information is often not reciprocated. That is, access to these registries does not require the prior provision of proprietary data. We argue that incumbent lenders release information about a portion of their profitable borrowers for strategic reasons. The reasoning is that the pool of unreleased borrowers becomes characterised by a severe adverse selection problem. This prevents the entrants from bidding for all the incumbent's profitable borrowers and reduces their scale of entry.
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