Visual Culture Analysis of The Last Ditch of the Chivalry, or a President in Petticoats

This lithograph is a Northern depiction of the capture of former Confederate President Jefferson Davis. Titled The Last Ditch of the Chivalry, or a President in Petticoats , and picturing Davis in a woman’s dress and bonnet, the Northern press painted Davis as a coward. Rather than being a man and standing up to the Union troops, Davis disguised himself as a woman and attempted to cowardly escape. Although in actuality Davis was wearing a rain jacket and shawl rather than a full dress and bonnet, the Northern press mocked him. This piece demonstrates the prominence of male Southern honor, and how the ideals of being a man contradicted with the expectations for women. Davis’ flee also symbolizes the fall of the Confederacy

Inference on Treatment Effects After Selection Amongst High-Dimensional Controls

We propose robust methods for inference on the effect of a treatment variable on a scalar outcome in the presence of very many controls. Our setting is a partially linear model with possibly non-Gaussian and heteroscedastic disturbances. Our analysis allows the number of controls to be much larger than the sample size. To make informative inference feasible, we require the model to be approximately sparse; that is, we require that the effect of confounding factors can be controlled for up to a small approximation error by conditioning on a relatively small number of controls whose identities are unknown. The latter condition makes it possible to estimate the treatment effect by selecting approximately the right set of controls. We develop a novel estimation and uniformly valid inference method for the treatment effect in this setting, called the "post-double-selection" method. Our results apply to Lasso-type methods used for covariate selection as well as to any other model selection method that is able to find a sparse model with good approximation properties. The main attractive feature of our method is that it allows for imperfect selection of the controls and provides confidence intervals that are valid uniformly across a large class of models. In contrast, standard post-model selection estimators fail to provide uniform inference even in simple cases with a small, fixed number of controls. Thus our method resolves the problem of uniform inference after model selection for a large, interesting class of models. We illustrate the use of the developed methods with numerical simulations and an application to the effect of abortion on crime rates

A Computationally Efficient Limited Memory CMA-ES for Large Scale Optimization

We propose a computationally efficient limited memory Covariance Matrix Adaptation Evolution Strategy for large scale optimization, which we call the LM-CMA-ES. The LM-CMA-ES is a stochastic, derivative-free algorithm for numerical optimization of non-linear, non-convex optimization problems in continuous domain. Inspired by the limited memory BFGS method of Liu and Nocedal (1989), the LM-CMA-ES samples candidate solutions according to a covariance matrix reproduced from $m$ direction vectors selected during the optimization process. The decomposition of the covariance matrix into Cholesky factors allows to reduce the time and memory complexity of the sampling to $O(mn)$, where $n$ is the number of decision variables. When $n$ is large (e.g., $n$ > 1000), even relatively small values of $m$ (e.g., $m=20,30$) are sufficient to efficiently solve fully non-separable problems and to reduce the overall run-time.Comment: Genetic and Evolutionary Computation Conference (GECCO'2014) (2014

Legal Rules and Bankruptcy Rates: Historical Evidence from the States

Since the early twentieth century, observers have attributed the wide variation in state bankruptcy rates to variation in state legal rules such as garnishment and bankruptcy exemptions. Recent econometric analyses, however, conclude that legal rules do not matter. We explore the impact of legal rules on bankruptcy rates using a new technique—fixed effects vector decomposition—to exploit historical variation in legal rules. The technique allows us to estimate the impact of timeinvariant legal rules in a fixed effects framework. We find that the variation in state legal rules explains much of the variation in state wage earner bankruptcy rates for 1926 to 1932.Bankruptcy, fixed effects vector decomposition, law and economics

Temperature dependent deviations from ideal quantization of plateau conductances in GaAs quantum point contacts

We present detailed experimental studies of the temperature dependence of the plateau conductance of GaAs quantum point contacts in the temperature range from 0.3 K to 10 K. Due to a strong lateral confinement produced by a shallow-etching technique we are able to observe the following unexpected feature: a linear temperature dependence of the measured mid-plateau conductance. We discuss an interpretation in terms of a temperature dependent, intrinsic series resistance, due to non-ballistic effects in the 2D-1D transition region. These results have been reproduced in several samples from different GaAs/GaAlAs heterostructures and observed in different experimental set-ups.Comment: 7 pages, 6 figures; to appear in proceedings of ICPS 2002, Edinburg

Memory Effects and Scaling Properties of Traffic Flows

Traffic flows are studied in terms of their noise of sound, which is an easily accessible experimental quantity. The sound noise data is studied making use of scaling properties of wavelet transforms and Hurst exponents are extracted. The scaling behavior is used to characterize the traffic flows in terms of scaling properties of the memory function in Mori-Lee stochastic differential equations. The results obtained provides for a new theoretical as well as experimental framework to characterize the large-time behavior of traffic flows. The present paper outlines the procedure by making use of one-lane computer simulations as well as sound-data measurements from a real two-lane traffic flow. We find the presence of conventional diffusion as well as 1/f-noise in real traffic flows at large time scales.Comment: 3 figure