Replication in Experimental Economics' highlights the importance of replicating previous economic experiments for understanding the robustness and generalizability of behavior. Replication enables experimental findings to be subjected to rigorous scrutiny. Despite this obvious advantage, direct
replication remains relatively scant in economics. One possible explanation for this situation is that publication outlets favor novel work over tests of robustness. This volume of Research in Experimental Economics raises awareness of the need for replication by being the first collection of papers
specifically dedicated to the replication of previously published work. The chapters, by leading researchers in the field, explore the robustness of topics from the effects of subsidizing charitable giving to people's ability to backwards induct and from the impact of social history on trust to the
role of isolation on valuation. Readers will gain a better understanding of the role that replication plays in scientific discovery as well as valuable insights into the robustness of previously reported findings.
Advances in Econometrics is a research annual whose editorial policy is to publish original research articles that contain enough details so that economists and econometricians who are not experts in the topics will find them accessible and useful in their research. Volume 37 exemplifies this focus
by highlighting key research from new developments in econometrics.
This volume in Advances in Econometrics showcases fresh methodological and empirical research on the econometrics of networks. Comprising both theoretical, empirical and policy papers, the authors bring together a wide range of perspectives to facilitate a dialogue between academics and
practitioners for better understanding this groundbreaking field and its role in policy discussions.
This edited collection includes thirteen chapters which covers various topics such as identification of network models, network formation, networks and spatial econometrics and applications of financial networks. Readers can also learn about network models with different types of interactions,
sample selection in social networks, trade networks, stochastic dynamic programming in space, spatial panels, survival and networks, financial contagion, spillover effects, interconnectedness on consumer credit markets and a financial risk meter.
The topics covered in the book, centered on the econometrics of data and models, are a valuable resource for graduate students and researchers in the field. The collection is also useful for industry professionals and data scientists due its focus on theoretical and applied works.
The Law and Economics of Privacy, Personal Data, Artificial Intelligence, and Incomplete Monitoring presents new findings and perspectives from leading international scholars on several emerging areas issues in legal and economic research.
The collection contains new theoretical papers on privacy, the protection of personal data, the use of regulatory monitoring under legal standards versus rules, a study of the properties of market efficiency in securities fraud litigation, as well as an analysis of non-exclusionary price floors. It
also contains an empirical paper on the relationship between uncertainty of patent approval of artificial intelligence applications and the Supreme Court’s decision in Alice Corp. v. CLS Bank International. Finally, the volume features a law-and-economics assessment of the Chinese financial
system within the context of the trade-off between centralized control and rapid growth.
This 30th volume of Research in Law and Economics showcases the cutting edge theoretical and empirical findings for researchers and professionals considering these complex issues intersecting law, technology, and economics.