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Full-Text Articles in Social and Behavioral Sciences
From Bards To Search Engines: Finding What Readers Want From Ancient Times To The World Wide Web, Stephen Maurer
From Bards To Search Engines: Finding What Readers Want From Ancient Times To The World Wide Web, Stephen Maurer
Stephen M. Maurer
Copyright theorists often ask how incentives can be designed to create better books, movies, and art. But this is not the whole story. As the Roman satirist Martial pointed out two thousand years ago, markets routinely ignore good and even excellent works. The insight reminds us that incentives to find content are just as necessary as incentives to make it. Recent social science research explains why markets fail and how timely interventions can save deserving titles from oblivion. This article reviews society’s long struggle to fix the vagaries of search since the invention of literature. We build on this history …
On The Strategic Use Of Border Tax Adjustments As A Second-Best Climate Policy Measure, Charles F. Mason, Edward B. Barbier, Victoria Umanskaya
On The Strategic Use Of Border Tax Adjustments As A Second-Best Climate Policy Measure, Charles F. Mason, Edward B. Barbier, Victoria Umanskaya
Charles F Mason
No abstract provided.
Review: Halper, Stefan A. Beijing Consensus: Legitimizing Authoritarianism In Our Time. New York, Ny: Basic Books, [2010] 2012. 336 Pp., Lukas K. Danner
Review: Halper, Stefan A. Beijing Consensus: Legitimizing Authoritarianism In Our Time. New York, Ny: Basic Books, [2010] 2012. 336 Pp., Lukas K. Danner
Dr. Lukas K. Danner
No abstract provided.
Some Matlab Routines To Compute Crps And Quantile Weighted Ps, Michael S. Smith
Some Matlab Routines To Compute Crps And Quantile Weighted Ps, Michael S. Smith
Michael Stanley Smith
Three routines to compute the CRPS of Gneiting and Raftery (JASA 2007) and the quantile weighted probability score (QWPS) extension in Gneiting and Ranjan (JBES, 2011). They are based on numerical integration as discussed in the Appendix of Smith and Vahey (2015), and I have found them to be much more accurate than using Monte Carlo approximation to the difference of two expectations, as advocated in Panagiotelis and Smith (IJF, 2008).