Venture Capitalists, Syndication and Governance in Initial Public Offerings

This paper examines the development of effective boards in venture capital (VC)-backed initial public offerings. It argues that VC-backed IPOs suffer from two sets of agency costs which are related to principal–agent and principal–principal relationships between the founders and members of the VC syndicate. Using a unique sample of 293 entrepreneurial IPOs in the UK it shows that VC syndicates invest in relatively more risky firms. VC-backed IPOs have more independent boards than IPOs with no VC involvement, with board independence being higher in syndicated VC-backed firms. These results are consistent with assumption that these governance factors are used to mitigate agency costs associated with VC involvement in IPO firms. We also find that in syndicated IPOs there is a higher equity presence of passive private equity firms investing alongside VC firms.     

Forecasting with factor-augmented error correction models

As a generalization of the factor-augmented VAR (FAVAR) and of the Error Correction Model (ECM), Banerjee and Marcellino (2009) introduced the Factor-augmented Error Correction Model (FECM). The FECM combines error-correction, cointegration and dynamic factor models, and has several conceptual advantages over the standard ECM and FAVAR models. In particular, it uses a larger dataset than the ECM and incorporates the long-run information which the FAVAR is missing because of its specification in differences. In this paper, we examine the forecasting performance of the FECM by means of an analytical example, Monte Carlo simulations and several empirical applications. We show that FECM generally offers a higher forecasting precision relative to the FAVAR, and marks a useful step forward for forecasting with large datasets.