How friends with money affect corporate cash policies? The international evidence

Abstract

We examine the association between managerial social capital and the cash flow sensitivity of cash in an international setting. We find that social capital reduces the marginal propensity to save cash out of cash flows. This association is stronger for more financially constrained firms, firms with high hedging needs, and firms with more uncertain cash flows. The effect of social capital is partially moderated by the extent of legal protection standards and financial development. We also show that social capital matters for valuation. These findings are robust to alternative model specifications, alternative variable measurement, and tests for endogeneity.

Network centrality and value relevance of insider trading: Evidence from Europe

“…We contribute to the existing literature on social networks and corporate and executive outcomes by studying the net economic impact of connectedness on insider trading. Our findings closely relate to the recent studies in corporate finance, which have linked managerial social networks to executive compensation (Engelberg et al, 2012;Horton et al, 2012), access to financing (Engelberg et al, 2012;Ferris et al, 2017b;Javakhadze & Rajkovic, 2018), investment efficiency (El-Khatib et al, 2015), financial development (Javakhadze et al, 2016b), cash-flow sensitivity (Javakhadze et al, 2016a), corporate risk taking (Ferris et al, 2017a), debt contracting (Fogel et al, 2018), and credit ratings (Benson et al, 2018). We extend this literature and show how insider networks influence the trading behavior of insiders and whether such trades have long-term valuation consequences.…”

“…Such networks help them in acquiring not only firm-specific information, but also information and trends on peer companies, industry, and the general economy (Goergen et al, 2019). We argue that as (a) networked insiders have superior channels of information and resource exchange (Fogel et al, 2018;Javakhadze & Rajkovic, 2018), (b) corporate insiders are known to trade in shares of their firms based on their informational advantage (Piotroski & Roulstone, 2005;Seyhun, 1986), and (c) insider trades have long-term valuation consequences for the stock price (Aboody et al, 2005;Ravina & Sapienza, 2010), we expect trades of networked insiders to have higher value-relevant information. We therefore construct our first hypothesis as follows:…”

“…As routine trades are unlikely to have any long-term value relevance (Cohen et al, 2012), we only focus on opportunistic transactions. 13 To calculate the network measures, we obtain data from BoardEx, which is a widely used source for estimating network centralities (e.g., El-Khatib et al, 2015;Fogel et al, 2018;Javakhadze & Rajkovic, 2018). We gather data on all publicly listed firms and their insiders from BoardEx.…”

“…Their findings show that well-connected insiders trade less frequently and for smaller values while earning short-term profits when purchasing. As previous studies document robust long-term valuation consequences of insider trading (e.g., Huddart & Ke, 2007;Ke et al, 2003;Ravina & Sapienza, 2010) and networked insiders have an informational advantage through their extensive channels of communication and resource exchange (Javakhadze & Rajkovic, 2018;Javakhadze et al, 2016a;Larcker et al, 2013), we reexamine the trading patterns of well-connected insiders and assess the long-term valuation consequences of their trades. 1 We also examine whether networked insiders exploit their informational advantage and trade to earn long-term abnormal dollar profits or whether they trade to convey signals about future firm prospects.…”

Firm life cycle and trade credit

“…Therefore, we argue that reverse causality is not a concern for our study.23 Jiang (2017, p. 127) notes that "the magnitude of the IV estimates is, on average, nine times of that of the uninstrumented estimates even when economic insights do not suggest a downward bias of the latter. "24 Contemporary finance literature also uses this method for overcoming measurement error(Javakhadze & Rajkovic, 2019;Lyandres et al, 2019).…”