, summary network parameters (e.g., the degree distribution or transitivity index); and (iii) empirical models of strategic … network formation admitting interdependencies in preferences. Current research challenges and open questions are also …

financial institutions. Focusing on a multi sector economy linked through a supply network, we show how structural properties of … the supply network determine both whether aggregate volatility disappears as the number of sectors increases (i … aggregate output from its mean) to sector-specific volatility and to the structural properties of the supply network …

This paper presents and structurally estimates a model of endogenous network formation and legislative activity of … of Congress as exogenously given and instead embed it in a model of endogenous network formation useful for developing …

Financial network structure is an important determinant of systemic risk. This paper examines how the U.S. interbank … network evolved over a long and important period that included two key events: the founding of the Federal Reserve and the …, initially reducing overall network concentration. The network became even more focused on Fed cities during the Depression, as …

I build a simple dynamic model of the formation of an international social network of importers and exporters. Firms … can only export into markets in which they have a contact. They acquire new contacts both at random, and via their network …

linked fields. Our analysis uses 1.8 million U.S. patents and their citation properties to map the innovation network and its … strength. Past innovation network structures are calculated using citation patterns across technology classes during 1975 …-1994. The interaction of this pre-existing network structure with patent growth in upstream technology fields has strong …

A new algorithm for the group minimization problem (GP) is proposed. The algorithm can be broadly described as follows …-known algorithm of Glover, and checked for non-negativity. The first non-negative point is an optimal solution of (GP). Advantages and … disadvantages of the algorithm are discussed; in particular, the implementation of the algorithm (which can be easily extended so as …

objective function for the algorithm designer and a model of their information sets and interaction. We build such a model that … allows the training data to exhibit a wide range of "biases." Prevailing wisdom is that biased data change how the algorithm … is trained and whether an algorithm should be used at all. In contrast, we find two striking irrelevance results. First …

algorithm in terms of model complexity or the number of predictors to accommodate. Each firm then appoints a data analyst that … uses the chosen algorithm to estimate demand for multiple consumer segments, based on which, it devises a targeting policy …