Entrepreneurial Firms and Signaling for Creditworthiness: a Bayesian Modeling Approach

To fulfill their growth aspirations, entrepreneurial ventures depend on shortterm, liquid sources of debt financing such as bank loans. However, because of the twin problems of information asymmetry and moral hazard, banks make their lending decisions by considering the venture’s creditworthiness score provided by private information exchanges. Using theoretical arguments grounded in venture financing literature and signaling theory, we develop two new concepts, the venture’s emergent volatility of size and deliberate diversity of the financing portfolio, and test the signaling impact of these two attributes on venture creditworthiness. Further, we incorporate in the model multilevel features, by considering at both firm and industry levels. In doing so, we make use of hierarchical Bayesian models with beta distributed likelihoods and use Markov chain Monte Carlo methods to obtain model parameters. This research is likely the first empirical study to examine the financial health of entrepreneurial firms based on emergent volatilities as well as deliberate diversities, and contrasted for entrepreneurial ventures in manufacturing versus services. Our paper offers guidance on how variability in firm-level attributes (intended or otherwise) sends signals that affect the firm’s creditworthiness, and therefore, its ability to secure debt-financing.