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Social and Behavioral Sciences Commons

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Full-Text Articles in Social and Behavioral Sciences

From Productivity To Firm Growth, James Bessen, Erich Denk Jun 2021

From Productivity To Firm Growth, James Bessen, Erich Denk

Faculty Scholarship

It is widely held that more productive firms grow faster, thus reallocating resources and raising aggregate productivity. Yet little empirical research identifies the features of the mechanisms affecting this process. This paper develops and tests a general model encompassing several mechanisms used to overcome informational frictions to growth. We find that firm size, productivity dispersion, and large firm investments in intangibles are all significantly related to changes in firm growth in response to productivity. These factors can account for much of the decline in the response to productivity since 2000 (Decker et al. 2020). Also, industry concentration is directly related …


Fair Innings? The Utilitarian And Prioritarian Value Of Risk Reduction Over A Whole Lifetime, Matthew D. Adler, Maddalena Ferranna, James K. Hammitt, Nicolas Treich Jan 2021

Fair Innings? The Utilitarian And Prioritarian Value Of Risk Reduction Over A Whole Lifetime, Matthew D. Adler, Maddalena Ferranna, James K. Hammitt, Nicolas Treich

Faculty Scholarship

The social value of risk reduction (SVRR) is the marginal social value of reducing an individual’s fatality risk, as measured by some social welfare function (SWF). This Article investigates SVRR, using a lifetime utility model in which individuals are differentiated by age, lifetime income profile, and lifetime risk profile. We consider both the utilitarian SWF and a “prioritarian” SWF, which applies a strictly increasing and strictly concave transformation to individual utility.

We show that the prioritarian SVRR provides a rigorous basis in economic theory for the “fair innings” concept, proposed in the public health literature: as between an older individual …


Theorizing Beyond "The Code Of Capital": A Reply, Katharina Pistor Jan 2021

Theorizing Beyond "The Code Of Capital": A Reply, Katharina Pistor

Faculty Scholarship

In this reply, I respond to and elaborate on the critique of my book “The Code of Capital” published in this special issue. The common thread of the critiques is the call for more theorizing of the themes the book addresses, especially the conception of state power, of resources, social relations and questions of knowledge and access to knowledge about the law, or epistemology. This reply is only a first response to issues that do require further analysis and I am hoping to follow suit on at least some of them in the near future.


The Code Of Capital: How The Law Creates Wealth And Inequality – Core Themes, Katharina Pistor Jan 2021

The Code Of Capital: How The Law Creates Wealth And Inequality – Core Themes, Katharina Pistor

Faculty Scholarship

In this brief introduction, I summarize the core themes of my book “The Code of Capital: How the Law Creates Wealth and Inequality”. Capital, I argue, is coded in law – predominantly in a handful of private law institutions. By relying on legal coding techniques, asset holders invoke the right to enforce claims against others, if necessary with the help of the state’s coercive power.


A Practical Proactive Proposal For Dealing With Attrition: Alternative Approaches And An Empirical Example, John Dinardo, Jordan Matsudaira, Justin Mccrary, Lisa Sanbonmatsu Jan 2021

A Practical Proactive Proposal For Dealing With Attrition: Alternative Approaches And An Empirical Example, John Dinardo, Jordan Matsudaira, Justin Mccrary, Lisa Sanbonmatsu

Faculty Scholarship

Survey nonresponse and attrition undermine the validity of many and possibly most econometric estimates. We propose that survey administrators and evaluators proactively create an instrument for observation, for example, by ex ante randomizing participants to differing intensity of follow-up. We illustrate how to apply our proposed methodology using a carefully conducted randomized controlled trial, the Moving to Opportunity demonstration project, which de facto randomly assigned a subset of subjects to more intensive follow-up. The approach yields treatment effect estimates similar to the unbiased estimator based on complete administrative data and has narrower confidence intervals than alternative bounding approaches.