While venture capital firms are increasingly relying on recommendation models in investment decisions, existing startup recommendation models fail to consider the uniqueness of venture capital context, including two-sided matching between investing and investee firms and a lack of information...

I explore the merits and limitations of Pearl’s directed acyclic graphs (DAG) approach for identification in applied economics. Researchers rely on causal inference frameworks to derive causal effects from observational data. Econometricians use either the potential outcomes (PO) or the...

Networks like those of healthcare infrastructure have been a primary target of cyberattacks for over a decade. From just a single cyberattack, a healthcare facility would expect to see millions of dollars in losses from legal fines, business interruption, and malpractice lawsuits. As more...

In this article, we examine the effects of the COVID-19 pandemic on the dynamics of contagion in the economic and financial spheres. The objective of the article is to confirm that the systemic nature of contagion risk is greater in extreme situations than in normal situations. Through this...

In a peer-to-peer complex environment, information is permanently diffused. Such an environment can be modeled as a graph, where there are flows of information. The interest of such modeling is that (1) one can describe the exchanges through time from an initial state of the network, (2) the...

This paper examines the econometric causal model for policy analysis developed by the seminal ideas of Ragnar Frisch and Trygve Haavelmo. We compare the econometric causal model with two popular causal frameworks: Neyman-Holland causal model and the do-calculus. The Neyman-Holland causal model...