Election results and opportunistic policies: A new test of the rational political business cycle model

The literature on the rational political business cycle suggests that politicians systematically manipulate economic and fiscal conditions before elections to increase their chance of gaining reelection. Most tests of this theory look for evidence of pre- election distortions in fiscal policy. We propose a new test that, instead, explores the implied two-way interaction between the magnitude of the opportunistic distortion and the margin of victory. The test is implemented using a panel of 278 Portuguese municipalities (from 1979 to 2005). The results show that (1) opportunism pays off, leading to a larger win-margin for the incumbent; (2) incumbents behave more opportunistically when their win-margin is small. These results are consistent with the theoretical model

Recovery from Linear Measurements with Complexity-Matching Universal Signal Estimation

We study the compressed sensing (CS) signal estimation problem where an input signal is measured via a linear matrix multiplication under additive noise. While this setup usually assumes sparsity or compressibility in the input signal during recovery, the signal structure that can be leveraged is often not known a priori. In this paper, we consider universal CS recovery, where the statistics of a stationary ergodic signal source are estimated simultaneously with the signal itself. Inspired by Kolmogorov complexity and minimum description length, we focus on a maximum a posteriori (MAP) estimation framework that leverages universal priors to match the complexity of the source. Our framework can also be applied to general linear inverse problems where more measurements than in CS might be needed. We provide theoretical results that support the algorithmic feasibility of universal MAP estimation using a Markov chain Monte Carlo implementation, which is computationally challenging. We incorporate some techniques to accelerate the algorithm while providing comparable and in many cases better reconstruction quality than existing algorithms. Experimental results show the promise of universality in CS, particularly for low-complexity sources that do not exhibit standard sparsity or compressibility.Comment: 29 pages, 8 figure

Correcting for Distortions due to Ionization in the STAR TPC

Physics goals of the STAR Experiment at RHIC in recent (and future) years drive the need to operate the STAR TPC at ever higher luminosities, leading to increased ionization levels in the TPC gas. The resulting ionic space charge introduces field distortions in the detector which impact tracking performance. Further complications arise from ionic charge leakage into the main TPC volume from the high gain anode region. STAR has implemented corrections for these distortions based on measures of luminosity, which we present here. Additionally, we highlight a novel approach to applying the corrections on an event-by-event basis applicable in conditions of rapidly varying ionization sources.Comment: 6 pages, 7 figures, proceedings of the Workshop on Tracking in High Multiplicity Environments (TIME 05) in Zurich, Switzerland, submitted to Nucl. Instr. and Meth.

A practical guide and software for analysing pairwise comparison experiments

Most popular strategies to capture subjective judgments from humans involve the construction of a unidimensional relative measurement scale, representing order preferences or judgments about a set of objects or conditions. This information is generally captured by means of direct scoring, either in the form of a Likert or cardinal scale, or by comparative judgments in pairs or sets. In this sense, the use of pairwise comparisons is becoming increasingly popular because of the simplicity of this experimental procedure. However, this strategy requires non-trivial data analysis to aggregate the comparison ranks into a quality scale and analyse the results, in order to take full advantage of the collected data. This paper explains the process of translating pairwise comparison data into a measurement scale, discusses the benefits and limitations of such scaling methods and introduces a publicly available software in Matlab. We improve on existing scaling methods by introducing outlier analysis, providing methods for computing confidence intervals and statistical testing and introducing a prior, which reduces estimation error when the number of observers is low. Most of our examples focus on image quality assessment.Comment: Code available at https://github.com/mantiuk/pwcm

First Weak-lensing Results from "See Change": Quantifying Dark Matter in the Two Z>1.5 High-redshift Galaxy Clusters SPT-CL J2040-4451 and IDCS J1426+3508

We present a weak-lensing study of SPT-CLJ2040-4451 and IDCSJ1426+3508 at z=1.48 and 1.75, respectively. The two clusters were observed in our "See Change" program, a HST survey of 12 massive high-redshift clusters aimed at high-z supernova measurements and weak-lensing estimation of accurate cluster masses. We detect weak but significant galaxy shape distortions using IR images from the WFC3, which has not yet been used for weak-lensing studies. Both clusters appear to possess relaxed morphology in projected mass distribution, and their mass centroids agree nicely with those defined by both the galaxy luminosity and X-ray emission. Using an NFW profile, for which we assume that the mass is tightly correlated with the concentration parameter, we determine the masses of SPT-CL J2040-4451 and IDCS J1426+3508 to be M_{200}=8.6_{-1.4}^{+1.7}x10^14 M_sun and 2.2_{-0.7}^{+1.1}x10^14 M_sun, respectively. The weak-lensing mass of SPT-CLJ2040-4451 shows that the cluster is clearly a rare object. Adopting the central value, the expected abundance of such a massive cluster at z>1.48 is only ~0.07 in the parent 2500 sq. deg. survey. However, it is yet premature to claim that the presence of this cluster creates a serious tension with the current LCDM paradigm unless that tension will remain in future studies after marginalizing over many sources of uncertainties such as the accuracy of the mass function and the mass-concentration relation at the high mass end. The mass of IDCSJ1426+3508 is in excellent agreement with our previous ACS-based weak-lensing result while the much higher source density from our WFC3 imaging data makes the current statistical uncertainty ~40% smaller.Comment: Accepted to Ap