5,027 research outputs found
The developmental state in Brazil: comparative and historical perspectives
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?
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
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
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
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
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
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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