910 research outputs found
Predicting Auction Price of Vehicle License Plate with Deep Residual Learning
Due to superstition, license plates with desirable combinations of characters
are highly sought after in China, fetching prices that can reach into the
millions in government-held auctions. Despite the high stakes involved, there
has been essentially no attempt to provide price estimates for license plates.
We present an end-to-end neural network model that simultaneously predict the
auction price, gives the distribution of prices and produces latent feature
vectors. While both types of neural network architectures we consider
outperform simpler machine learning methods, convolutional networks outperform
recurrent networks for comparable training time or model complexity. The
resulting model powers our online price estimator and search engine
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The probability of sale and price premiums in withdrawn auctioned properties
This paper examines the impact of the auction process of residential properties that whilst unsuccessful at auction sold subsequently. The empirical analysis considers both the probability of sale and the premium of the subsequent sale price over the guide price, reserve and opening bid. The findings highlight that the final achieved sale price is influenced by key price variables revealed both prior to and during the auction itself. Factors such as auction participation, the number of individual bidders and the number of bids are significant in a number of the alternative specifications
Conclusion : what's next ?
This book offered a broad overview of the different business models in the wine industry worldwide. It showed the diversity of this highly fragmented and extremely diverse sector. Above all, the different chapters showed that there is no dominant model and no guarantee of success at national scale in whatever we are talking about Old, New or New World wine countries. In particular, this book refutes the idea, however widespread in the Old World, that the model of the large, vertically integrated industries relying on one or more strong brands sold internationally would be the unique way for success in wine-producing countries. (...
Analysis of No-Difference Findings in Evaluation Research
Conclusions of no difference are becoming increasingly important in evaluation research. We delineate three major uses of no-difference findings and analyze their meanings. (1) No-differ ence findings in randomized experiments can be interpreted as support for conclusions of the absence of a meaningful treatment effect, but only if the proper analytic methods are used. (2) Statistically based conclusions in quasi-experiments do not allow causal statements about the treatment impact but do provide a metric to judge the size of the resulting difference. (3) Using no-difference findings to conclude equivalence on control variables is inefficient and potentially misleading. The final section of the article presents alternative methods by which conclusions of no difference may be supported when applicable. These methods include the use of arbitrarily high alpha levels, interval estimation, and power analysis.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/67182/2/10.1177_0193841X8901300604.pd
A comparison of arbitration procedures for risk averse disputants
We propose an arbitration model framework that generalizes many previous quantitative models of final offer arbitration, conventional arbitration, and some proposed alternatives to them. Our model allows the two disputants to be risk averse and assumes that the issue(s) in dispute can be summarized by a single quantifiable value. We compare the performance of the different arbitration procedures by analyzing the gap between the disputants' equilibrium offers and the width of the contract zone that these offers imply. Our results suggest that final offer arbitration should give results superior to those of conventional arbitration.Natural Sciences & Engineering Research Council (NSERC) Discovery Gran
The Effect of Bound Dineutrons upon BBN
We have examined the effects of a bound dineutron, n2, upon big bang
nucleosynthesis (BBN) as a function of its binding energy B_n2. We find a
weakly bound dineutron has little impact but as B_n2 increases its presence
begins to alter the flow of free nucleons to helium-4. Due to this disruption,
and in the absence of changes to other binding energies or fundamental
constants, BBN sets a reliable upper limit of B_n2 <~ 2.5 MeV in order to
maintain the agreement with the observations of the primordial helium-4 mass
fraction and D/H abundance
Individual Heterogeneity in the Returns to Schooling: Instrumental Variables Quantile Regression Using Twins Data
Considerable effort has been exercised in estimating mean returns to education while carefully considering biases arising from unmeasured ability and measurement error. Recent work has investigated whether there are variations from the “mean” return to education across the population with mixed results. We use an instrumental variables estimator for quantile regression on a sample of twins to estimate an entire family of returns to education at different quantiles of the conditional distribution of wages while addressing simultaneity and measurement error biases. We test whether there is individual heterogeneity in returns to education and find that: more able individuals obtain more schooling and that higher ability individuals (those further to the right in the conditional distribution of wages) have higher returns to schooling consistent with a non-trivial interaction between schooling and unobserved abilities in the generation of earnings. The estimated returns are never lower than 9 percent and can be as high as 13 percent at the top of the conditional distribution of wages but they vary significantly only along the lower to middle quantiles. Our findings may have meaningful implications for the design of educational policies
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