Decomposition of the efficiency of the Chinese state-owned commercial banks at the provincial level

This study adopts a bank production function approach to the measurement of banking efficiency at the provincial level in the Chinese state-owned commercial banking sector from 1998 to 2003. Applying Data Envelopment Analysis and efficiency decomposition analysis, this paper has revealed a significant level of pure technical input inefficiency and, to a lesser extent, scale inefficiency across the provincial branches of all the banking groups. The study has also uncovered the extent of inefficiency in individual banking inputs and provincial branches. Finally, the provincial-level efficiency is further decomposed into within-banking-group and between-banking-group effects

Nonparametric time series forecasting with dynamic updating

We present a nonparametric method to forecast a seasonal univariate time series, and propose four dynamic updating methods to improve point forecast accuracy. Our methods consider a seasonal univariate time series as a functional time series. We propose first to reduce the dimensionality by applying functional principal component analysis to the historical observations, and then to use univariate time series forecasting and functional principal component regression techniques. When data in the most recent year are partially observed, we improve point forecast accuracy using dynamic updating methods. We also introduce a nonparametric approach to construct prediction intervals of updated forecasts, and compare the empirical coverage probability with an existing parametric method. Our approaches are data-driven and computationally fast, and hence they are feasible to be applied in real time high frequency dynamic updating. The methods are demonstrated using monthly sea surface temperatures from 1950 to 2008.Functional time series, Functional principal component analysis, Ordinary least squares, Penalized least squares, Ridge regression, Sea surface temperatures, Seasonal time series.

"Light from chaos" in two dimensions

We perform a Monte-Carlo study of the lattice two-dimensional gauged XY-model. Our results confirm the strong-coupling expansion arguments that for sufficiently small values of the spin-spin coupling the ``gauge symmetry breaking" terms decouple and the long-distance physics is that of the unbroken pure gauge theory. We find no evidence for the existence, conjectured earlier, of massless states near a critical value of the spin-spin coupling. We comment on recent remarks in the literature on the use of gauged XY-models in proposed constructions of chiral lattice gauge theories.Comment: 6 pages, 7 figure

Fine-Structure Line Emission from the Outflows of Young Stellar Objects

The flux and line shape of the fine-structure transitions of \NeII\ and \NeIII\ at 12.8 and 15.55\,$\mu$m and of the forbidden transitions of \OI\ $\lambda6300$ are calculated for young stellar objects with a range of mass-loss rates and X-ray luminosities using the X-wind model of jets and the associated wide-angle winds. For moderate and high accretion rates, the calculated \NeII\ line luminosity is comparable to or much larger than produced in X-ray irradiated disk models. All of the line luminosities correlate well with the main parameter in the X-wind model, the mass-loss rate, and also with the assumed X-ray luminosity --- and with one another. The line shapes of an approaching jet are broad and have strong blue-shifted peaks near the effective terminal velocity of the jet. They serve as a characteristic and testable aspect of jet production of the neon fine-structure lines and the \OI\ forbidden transitions.Comment: 8 pages, 5 figures, published in Ap

Rainbow plots, Bagplots and Boxplots for Functional Data

We propose new tools for visualizing large numbers of functional data in the form of smooth curves or surfaces. The proposed tools include functional versions of the bagplot and boxplot, and make use of the first two robust principal component scores, Tukey's data depth and highest density regions. By-products of our graphical displays are outlier detection methods for functional data. We compare these new outlier detection methods with exiting methods for detecting outliers in functional data and show that our methods are better able to identify the outliers.Highest density regions, Robust principal component analysis, Kernel density estimation, Outlier detection, Tukey's halfspace depth

Physical drivers of the summer 2019 North Pacific marine heatwave.

Summer 2019 observations show a rapid resurgence of the Blob-like warm sea surface temperature (SST) anomalies that produced devastating marine impacts in the Northeast Pacific during winter 2013/2014. Unlike the original Blob, Blob 2.0 peaked in the summer, a season when little is known about the physical drivers of such events. We show that Blob 2.0 primarily results from a prolonged weakening of the North Pacific High-Pressure System. This reduces surface winds and decreases evaporative cooling and wind-driven upper ocean mixing. Warmer ocean conditions then reduce low-cloud fraction, reinforcing the marine heatwave through a positive low-cloud feedback. Using an atmospheric model forced with observed SSTs, we also find that remote SST forcing from the central equatorial and, surprisingly, the subtropical North Pacific Ocean contribute to the weakened North Pacific High. Our multi-faceted analysis sheds light on the physical drivers governing the intensity and longevity of summertime North Pacific marine heatwaves