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Ben Klemens

Publications and source records attributed to Ben Klemens.

3 recordsLinked to original sources

Measures of the Capital Network of the U.S. Economy

About two million U.S. corporations and partnerships are linked to each other and human investors by about 15 million owner-subsidiary links. Comparable social networks such as corporate board memberships and socially-built systems such as the network of Internet links are "small worlds," meaning a network with a small diameter and link densities with a power-law distribution, but these properties had not yet been measured for the business entity network. This article shows that both inbound links and outbound links display a power-law distribution with a coefficient of concentration estimable to within a generally narrow confidence interval, overall, for subnetworks including only business entities, only for the great connected component of the network, and in subnetworks with edges associated with certain industries, for all years 2009-2021. In contrast to other networks with power-law distributed link densities, the network is mostly a tree, and has a diameter an order of magnitude larger than a small-world network with the same link distribution. The regularity of the power-law distribution indicates that its coefficient can be used as a new, well-defined macroeconomic metric for the concentration of capital flows in an economy. Economists might use it as a new measure of market concentration which is more comprehensive than measures based only on the few biggest firms. Comparing capital link concentrations across countries would facilitate modeling the relationship between business network characteristics and other macroeconomic indicators.

econ.GN

A Useful Algebraic System of Statistical Models

This paper proposes a single form for statistical models that accommodates a broad range of models, from ordinary least squares to agent-based microsimulations. The definition makes it almost trivial to define morphisms to transform and combine existing models to produce new models. It offers a unified means of expressing and implementing methods that are typically given disparate treatment in the literature, including transformations via differentiable functions, Bayesian updating, multi-level and other types of composed models, Markov chain Monte Carlo, and several other common procedures. It especially offers benefit to simulation-type models, because of the value in being able to build complex models from simple parts, easily calculate robustness measures for simulation statistics and, where appropriate, test hypotheses. Running examples will be given using Apophenia, an open-source software library based on the model form and transformations described here.

stat.ME

A Peer-based Model of Fat-tailed Outcomes

It is well known that the distribution of returns from various financial instruments are leptokurtic, meaning that the distributions have "fatter tails" than a Normal distribution, and have skew toward zero. This paper presents a graceful micro-level explanation for such fat-tailed outcomes, using agents whose private valuations have Normally-distributed errors, but whose utility function includes a term for the percentage of others who also buy.

q-fin.TR