5,027 research outputs found

    The developmental state in Brazil: comparative and historical perspectives

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    The record of successful developmental states in East Asia and the partial successes of developmental states in Latin America suggest several common preconditions for effective state intervention including a Weberian bureaucracy, monitoring of implementation, reciprocity (subsidies in exchange for performance), and collaborative relations between government and business. Although Brazil failed to develop the high technology manufacturing industry and exports that have fueled sustained growth in East Asia, its developmental state had a number of important, and often neglected, successes, especially in steel, automobiles, mining, ethanol, and aircraft manufacturing. Where Brazil's developmental state was less successful was in promoting sectors like information technology and nuclear energy, as well as overall social and regional equality. In addition, some isolated initiatives by state governments were also effective in promoting particular local segments of industry and agriculture. Comparisons with East Asia, highlight the central role of state enterprises in Brazil that in effect internalized monitoring and reciprocity and bypassed collaboration between business and government (that was overall rarer in Brazil)

    Business-Government Interaction in Policy Councils in Latin America - Cheap Talk, Expensive Exchanges, or Collaborative Learning?

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    While effective industrial policy requires close cooperation between government and business, there is little agreement on what makes that cooperation work best. This paper analyzes institutional arrangements for public-private cooperation and the character of private sector representation. Questions on institutional design focus on three main issues: i) maximizing the benefits of dialogue and information exchange; ii) motivating participation through authoritative allocation; and iii) minimizing unproductive rent seeking. Key elements in the nature of business representation through associations are the quality of research staff and internal mechanisms for reconciling divergent preferences within associations. The empirical analysis also disaggregates councils by scope (economy-wide versus targeted), function (trade, upgrading, technology, etc.), sector (agriculture, industry, services), and level (national, provincial, and municipal).Industrial policy, Business-Government relations, Rent seeking

    Trustworthy Experimentation Under Telemetry Loss

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    Failure to accurately measure the outcomes of an experiment can lead to bias and incorrect conclusions. Online controlled experiments (aka AB tests) are increasingly being used to make decisions to improve websites as well as mobile and desktop applications. We argue that loss of telemetry data (during upload or post-processing) can skew the results of experiments, leading to loss of statistical power and inaccurate or erroneous conclusions. By systematically investigating the causes of telemetry loss, we argue that it is not practical to entirely eliminate it. Consequently, experimentation systems need to be robust to its effects. Furthermore, we note that it is nontrivial to measure the absolute level of telemetry loss in an experimentation system. In this paper, we take a top-down approach towards solving this problem. We motivate the impact of loss qualitatively using experiments in real applications deployed at scale, and formalize the problem by presenting a theoretical breakdown of the bias introduced by loss. Based on this foundation, we present a general framework for quantitatively evaluating the impact of telemetry loss, and present two solutions to measure the absolute levels of loss. This framework is used by well-known applications at Microsoft, with millions of users and billions of sessions. These general principles can be adopted by any application to improve the overall trustworthiness of experimentation and data-driven decision making.Comment: Proceedings of the 27th ACM International Conference on Information and Knowledge Management, October 201

    A Simple Likelihood Method for Quasar Target Selection

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    We present a new method for quasar target selection using photometric fluxes and a Bayesian probabilistic approach. For our purposes we target quasars using Sloan Digital Sky Survey (SDSS) photometry to a magnitude limit of g=22. The efficiency and completeness of this technique is measured using the Baryon Oscillation Spectroscopic Survey (BOSS) data, taken in 2010. This technique was used for the uniformly selected (CORE) sample of targets in BOSS year one spectroscopy to be realized in the 9th SDSS data release. When targeting at a density of 40 objects per sq-deg (the BOSS quasar targeting density) the efficiency of this technique in recovering z>2.2 quasars is 40%. The completeness compared to all quasars identified in BOSS data is 65%. This paper also describes possible extensions and improvements for this techniqueComment: Updated to accepted version for publication in the Astrophysical Journal. 10 pages, 10 figures, 3 table

    Optimal Time-Series Selection of Quasars

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    We present a novel method for the optimal selection of quasars using time-series observations in a single photometric bandpass. Utilizing the damped random walk model of Kelly et al. (2009), we parameterize the ensemble quasar structure function in Sloan Stripe 82 as a function of observed brightness. The ensemble model fit can then be evaluated rigorously for and calibrated with individual light curves with no parameter fitting. This yields a classification in two statistics --- one describing the fit confidence and one describing the probability of a false alarm --- which can be tuned, a priori, to achieve high quasar detection fractions (99% completeness with default cuts), given an acceptable rate of false alarms. We establish the typical rate of false alarms due to known variable stars as <3% (high purity). Applying the classification, we increase the sample of potential quasars relative to those known in Stripe 82 by as much as 29%, and by nearly a factor of two in the redshift range 2.5<z<3, where selection by color is extremeley inefficient. This represents 1875 new quasars in a 290 deg^2 field. The observed rates of both quasars and stars agree well with the model predictions, with >99% of quasars exhibiting the expected variability profile. We discus the utility of the method at high-redshift and in the regime of noisy and sparse data. Our time series selection complements well independent selection based on quasar colors and has strong potential for identifying high redshift quasars for BAO and other cosmology studies in the LSST era.Comment: 28 pages, 8 figures, 3 tables; Accepted to A

    Employee Attributions of the Why of HR Practices: Their Effects on Employee Attitudes and Behaviors, and Customer Satisfaction

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    The construct of Human Resource (HR) Attributions is introduced. We argue that the attributions that employees make about the reasons why management adopts the HR practices that it does have consequences for their attitudes and behaviors, and ultimately, unit performance. Drawing on the strategic HR literature, we propose a typology of five HR-Attribution dimensions. Utilizing data collected from a service firm, we show that employees make varying attributions for the same HR practices, and that these attributions are differentially associated with commitment and satisfaction. In turn, we show that these attitudes become shared within units and that they are related to unit-level organizational citizenship behaviors and customer satisfaction. Findings and implications are discussed

    Sloan Digital Sky Survey III Photometric Quasar Clustering: Probing the Initial Conditions of the Universe using the Largest Volume

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    The Sloan Digital Sky Survey has surveyed 14,555 square degrees of the sky, and delivered over a trillion pixels of imaging data. We present the large-scale clustering of 1.6 million quasars between z = 0.5 and z = 2.5 that have been classified from this imaging, representing the highest density of quasars ever studied for clustering measurements. This data set spans ~11,000 square degrees and probes a volume of 80(Gpc/h)^3. In principle, such a large volume and medium density of tracers should facilitate high-precision cosmological constraints. We measure the angular clustering of photometrically classified quasars using an optimal quadratic estimator in four redshift slices with an accuracy of ~25% over a bin width of l ~10 - 15 on scales corresponding to matter-radiation equality and larger (l ~ 2 - 30). Observational systematics can strongly bias clustering measurements on large scales, which can mimic cosmologically relevant signals such as deviations from Gaussianity in the spectrum of primordial perturbations. We account for systematics by employing a new method recently proposed by Agarwal et al. (2014) to the clustering of photometrically classified quasars. We carefully apply our methodology to mitigate known observational systematics and further remove angular bins that are contaminated by unknown systematics. Combining quasar data with the photometric luminous red galaxy (LRG) sample of Ross et al. (2011) and Ho et al. (2012), and marginalizing over all bias and shot noise-like parameters, we obtain a constraint on local primordial non-Gaussianity of fNL = -113+/-154 (1\sigma error). [Abridged]Comment: 35 pages, 15 figure
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