Miracle-dz/UniFAR-FTUs huggingface dataset:
Computer adoption and diffusion at the bottom of the U.S. labor market: Disentangling the effects of skills and wages on computer use

This research presents estimates of the determinants of computer technology adoption at the bottom of the skill distribution. Using data from the October Supplements to the Current Population Surveys, we present evidence that computer adoption at the bottom of the labor market is mainly driven by differences in wages and that the role of education in determining computer use is absent. Using instrumental variables for both wages and education we show this effect to be economically important and statistically significant. The implications of this result are important because it suggests no direct relationship between skills and computer technology use at work, an argument often used by policy makers to emphasize the importance of investing in computer literacy and to prepare for working in the “new economy”. * We would like to especially thank Josh Angrist and David Autor for extremely helpful discussions and comments. In addition, we would like to thank David Lee for sharing his data on U.S. state minimum wages. Finally, we both acknowledge financial support from the Netherlands Organization for Scientific Research.
International monetary and financial economics

A more concise and accessible text that covers the key concepts students need to learn in a course on international money and finance which combines treatment of both international financial economics and open economy macroeconomics. In presenting the material, this text concentrates on diagrammatic and conceptual explanations and consequently uses algebra sparingly. To pique student interest, this text addresses many current issues appearing in leading business-oriented publications such as The Economist, The Wall Street Journal, and Financial Times, and incorporates an emphasis on real-world business and policy issues.
A new class of FLANN filters with application to nonlinear active noise control

FLANN and generalized FLANN filters exploiting trigonometric functions are often used in active noise control. However, they cannot approximate arbitrarily well every causal, time-invariant, finite-memory, nonlinear system, i.e., they are not universal approximators as the Volterra filters. In this paper, we propose a novel class of FLANN filters, called Complete FLANN filters, which satisfy the Stone-Weierstrass theorem, and thus can arbitrarily well approximate any nonlinear, time-invariant, finite-memory, continuous system. CFLANN filters are members of the class of nonlinear filters characterized by the property that their output depends linearly on the filter coefficients. As a consequence, they can be efficiently implemented in the form of a filter bank and adapted using algorithms simply derived from those applied to linear filters. In the paper, we apply a nonlinearly Filtered-X NLMS algorithm for CFLANN filters and describe some useful applications in the area of nonlinear active noise control.
An appraisal of financially distressed companies' earnings management

Purpose – This study aims to examine the earnings management behaviour of financially distressed listed companies in China for the period 2002‐2006.Design/methodology/approach – The present study uses discretionary accruals to serve as a proxy variable for earnings management, with the type of ultimate ownership and the type of industry to which the company belongs functioning as independent variables.Findings – The empirical results show that the desire to avoid continued special treatment (ST) status and the risk of being de‐listed leads firms to adopt different earnings management behaviour before and after being designated as an ST firm.Research limitations/implications – The desire to avoid being de‐listed is as strong among managers of state‐owned companies as it is among private companies.Practical implications – Implementing the effective regulation of corporate earnings management is therefore an issue of great importance. It is recommended that the government needs to take the degree of industry.
A study on content-based classification and retrieval of audio database

Nowadays, available audio corpora are rapidly increasing from fast growing Internet and digitized libraries. How to effectively classify and retrieve such huge databases is a challenging task. Content based technology is studied to automatically classify audio into hierarchy classes. Based on a small set of features selected by the sequential forward selection (SFS) method from 87 extracted ones, four classifiers, namely nearest neighbor (NN), modified k-nearest neighbor (k-NN), Gaussian mixture model (GMM), and probabilistic neural network (PNN) are compared. Experiments were conducted on a common database and a more comprehensive database built by the authors. Finally, the PNN classifier combined with Euclidean distance measurement was chosen for audio retrieval, using query by example.
The Wealth Position of Immigrant Families in Canada

The economic assimilation of immigrants is a key concern for economists and policy makers. The topic has been widely explored in terms of earnings assimilation of immigrants. Using the 1999 Survey of Financial Security, this study attempts to look at the issue from the wealth perspective. Among married families, immigrants have higher wealth than their native-born counterparts from the 40th to 90th percentiles of the distribution, with the wealth gap ranging between $20,000 and $78,000. Among single families, immigrants have higher wealth from the 55th to 95th percentiles, with the wealth gap ranging between $14,000 and $145,000. At the bottom of the distribution, however, evidence suggests that immigrants have lower wealth, although the gap is generally below $10,000. Various decomposition results indicate that the age of the major income recipient (and of the spouse for married families) as well as factors affecting permanent income explain a significant portion of the wealth gap in cases where immigrant families have higher wealth than the native-born. At the bottom of the wealth distribution, however, the wealth gap cannot be explained by the age of the major income recipient, permanent income factors, or family size (or lone-parent status), suggesting that low-wealth immigrant families may behave differently than low-wealth Canadian-born families in their wealth accumulation process. The wealth gap is also studied from a cohort perspective. Not surprisingly, recent immigrants have lower wealth than comparable Canadian-born families, and immigrants who arrived before 1976 have higher wealth. While immigrants who arrived in Canada between 1976 and 1985 are widely believed to initially have had more of an earnings disadvantage than their predecessors with respect to the Canadian-born, this study finds that, over the upper segment of the distribution, the wealth of this cohort is not significantly different from that of comparable Canadian-born families. But over the lower portion of the distribution, the cohort has lower wealth.
Mass Preferences on Shared Representation and the Composition of Legislative Districts

Scholars of redistricting often discuss “communities of interest” as a guideline for drawing districts, but scholarship offers little guidance on how citizens construe communities and interests in the context of representation. In this article, we seek to better understand how citizens’ perceptions of people and places affect preferences regarding representation. Using an original survey conducted in 15 Massachusetts communities, we explore whether citizens have meaningful preferences about the communities with whom they share the same representative. To the extent they do, we test whether these preferences are driven by geographic considerations or other factors such as partisanship, race, and socioeconomic status. Our findings not only offer the opportunity to refine the concept of “communities of interest” to account for voter preferences but also more broadly speak to the literature on the increasingly political nature of residential preferences and their impact on political attitudes, participation, and voting behavior.
Interest Rates, Exchange Rates and Macroeconomic Performance

In recent years, there has been a renewed interest in the fact that a change in exchange rates has an impact on main economic indicators and therefore on macroeconomic performance. The aim of this paper is to study the implications of the relationship between exchange rates and changes in short-term interest rates on macroeconomic performance in the Turkish economy. The results of this study show that monetary policy shocks may affect financial sector and real sector through exchange rates.
Taxes and Financial Constraints: Evidence from Linguistic Cues

type="main"> Using a new measure of financial constraints based on firms’ qualitative disclosures, we find that financially constrained firms—firms that use more negative words in their annual reports—pursue more aggressive tax planning strategies as evidenced by: (1) higher current and future unrecognized tax benefits, (2) lower short- and long-run current and future effective tax rates, (3) increase in tax haven usage for their material operations, and (4) higher proposed audit adjustments from the Internal Revenue Service. We exploit the unexpected closures of local banks as exogenous liquidity shocks to show that firms’ external financial constraints affect their tax avoidance strategies. Overall, the linguistic cues in firms’ qualitative disclosures provide incremental information beyond traditional accounting variables or commonly used effective tax rates to reveal and predict tax aggressiveness, both contemporaneously and in the future.
Diagnostic virology.

Diagnostic virology has now entered the mainstream of medical practice. Multiple methods are used for the laboratory diagnosis of viral infections, including viral culture, antigen detection, nucleic acid detection, and serology. The role of culture is diminishing as new immunologic and molecular tests are developed that provide more rapid results and are able to detect a larger number of viruses. This review provides specific recommendations for the diagnostic approach to clinically important viral infections.
Behavioral Channels in the Cross‐Market Diffusion of Major Terrorism Shocks

The diffusion mechanism of terrorist shocks to third countries’ stock market responses is explored by employing a Heckit model. Stock market response is broken down to (i) the direction of reaction and (ii) conditional on negative reaction, its magnitude. The analysis puts forward two behavioral factors (memory‐based utility/availability heuristic, social amplification of risk), proxied by past terrorism record and terrorism risk concern as the shocks’ diffusion channels. The findings are that the likelihood and the size of negative stock market reaction increase with terrorism record and risk concern. Additionally, weak evidence is uncovered for a mitigation of risk concern's impact by favorable macroeconomic stance. Furthermore, the impact of behavioral factors, especially over the magnitude of reaction, is robust when controlling for economic linkages. The latter are also significant predictors of the direction of stock market reaction, but not of its magnitude.
Natural history and galsulfase treatment in mucopolysaccharidosis VI (MPS VI, Maroteaux–Lamy syndrome)—10‐year follow‐up of patients who previously participated in an MPS VI survey study

Mucopolysaccharidosis VI (MPS VI) is a clinically heterogeneous and progressive disorder with multiorgan manifestations caused by deficient N‐acetylgalactosamine‐4‐sulfatase activity. A cross‐sectional Survey Study in individuals (n = 121) affected with MPS VI was conducted between 2001 and 2002 to establish demographics, urinary glycosaminoglycan (GAG) levels, and clinical progression of disease. We conducted a Resurvey Study (ClinicalTrials.gov: NCT01387854) to obtain 10‐year follow‐up data, including medical histories and clinical assessments (n = 59), and survival status over 12 years (n = 117). Patients received a mean (SD) of 6.8 (2.2) years of galsulfase ERT between baseline (Survey Study) and follow‐up. ERT patients increased in height by 20.4 cm in the 4–7‐year‐old baseline age group and by 16.8 cm in the 8–12‐year‐old baseline age group. ERT patients <13 years‐old demonstrated improvement in forced vital capacity (FVC) by 68% and forced expiratory volume in 1 sec (FEV1) by 55%, and those ≥13 years‐old increased FVC by 12.8% and maintained FEV1. Patients with >200 µg/mg baseline uGAG levels increased FVC by 48% in the <13‐year‐old baseline age group and by 15% in the ≥13‐year‐old baseline age group. ERT patients who completed the 6‐min walk test demonstrated a mean (SD) increase of 65.7 (100.6) m. Cardiac outcomes did not significantly improve or worsen. Observed mortality rate among naïve patients was 50% (7/14) and 16.5% (17/103) in the ERT group (unadjusted hazard ratio, 0.24; 95% CI, 0.10–0.59). Long‐term galsulfase ERT was associated with improvements in pulmonary function and endurance, stabilized cardiac function and increased survival. © 2014 Wiley Periodicals, Inc.
The Human Capital Convergence Fallacy: A Cross Country Empirical Investigation.

This article adapts a modification of Tamura’s theoretical proposition and conducts a cross-country empirical investigation in an attempt to evaluate convergence on two different human capital proxies; namely enrollment rates and per capita researchers. The analysis considers three country groups at significantly different development levels: Advanced, developed and less developed countries. The hypothesis of convergence is rejected when alternative, to enrollment rates, approximations to human capital are used, merely implying the existence of a “convergence trap” for countries with significantly lower endowments of human capital. The results provide circumstantial evidence of within group convergence and between group divergences when enrollment in education is considered, but no convergence/divergence when research effort is considered. This last finding suggests the possibility of a “convergence trap”, since initial human capital endowment could drive a process of worldwide polarization.
Dopaminergic Signaling and Striatal Neurodegeneration in Huntington's Disease

Huntington's disease (HD) is a neurodegenerative disorder caused by polyglutamine (polyQ) expansion in Huntingtin protein (Htt). PolyQ expansion in Httexp causes selective degeneration of striatal medium spiny neurons (MSNs) in HD patients. Striatal MSN neurons receive glutamatergic input from the cortex and dopaminergic input from the substantia nigra. In previous studies with the yeast artificial chromosome (YAC128) transgenic HD mouse model, we established a connection between glutamate receptor activation, disturbed calcium (Ca2+) signaling, and apoptosis of HD MSNs (Tang et al., 2005). Here, we used the same YAC128 mouse model to investigate the role of dopaminergic signaling in HD. We discovered that glutamate and dopamine signaling pathways act synergistically to induce elevated Ca2+ signals and to cause apoptosis of YAC128 MSNs in vitro. We demonstrated that potentiating effects of dopamine are mediated by D1-class dopamine receptors (DARs) and not by D2-class DARs. Consistent with in vitro findings, in whole-animal experiments we found that persistent elevation of striatal dopamine levels exacerbated the behavioral motor deficits and MSN neurodegeneration in YAC128 mice. We further discovered that the clinically relevant dopamine pathway inhibitor tetrabenazine alleviated the motor deficits and reduced striatal cell loss in YAC128 mice. Our results suggest that dopamine signaling pathway plays an important role in HD pathogenesis and that antagonists of dopamine pathway such as tetrabenazine or dopamine receptor blockers may have a therapeutic potential for treatment of HD beyond well established “symptomatic” benefit.
A New Approach to Multi-Step Forecasting Using Dynamic Stochastic General Equilibrium Models

DSGE models are of interest because they offer structural interpretations, but are also increasingly used for forecasting. Estimation often proceeds by methods which involve building the likelihood by one-step ahead (h=1) prediction errors. However in principle this can be done using different horizons where h>1. Using the well-known model of Smets and Wouters (2007), for h=1 classical ML parameter estimates are similar to those originally reported. As h extends some estimated parameters change, but not to an economically significant degree. Forecast performance is often improved, in several cases significantly.
Inferring 3D free-form shapes from contour drawings

We have built a proof-of-concept system allowing us to get one plausible 3D shape from a complex 2D drawing. The shape approximately matches the 2D drawing, and has a reasonable 3D form. We apply and generalize Williams’ process for inferring a 3D shape from 2D contours [Williams 1994]: completion of hidden contours (“figural completion”), topological reconstruction of the shape (“paneling construction”), and smooth embedding by relaxation. Figure 2(left) and Figure 3 show two input drawings and the desired outputs of the first and last stages mentioned.
RNN-DBSCAN: A Density-Based Clustering Algorithm Using Reverse Nearest Neighbor Density Estimates

A new density-based clustering algorithm, <italic>RNN-DBSCAN</italic>, is presented which uses reverse nearest neighbor counts as an estimate of observation density. Clustering is performed using a <italic>DBSCAN</italic>-like approach based on <inline-formula><tex-math notation="LaTeX">$k$</tex-math><alternatives> <inline-graphic xlink:href="bryant-ieq1-2787640.gif"/></alternatives></inline-formula> nearest neighbor graph traversals through dense observations. <italic>RNN-DBSCAN</italic> is preferable to the popular density-based clustering algorithm <italic>DBSCAN</italic> in two aspects. First, problem complexity is reduced to the use of a single parameter (choice of <inline-formula><tex-math notation="LaTeX">$k$</tex-math><alternatives> <inline-graphic xlink:href="bryant-ieq2-2787640.gif"/></alternatives></inline-formula> nearest neighbors), and second, an improved ability for handling large variations in cluster density (heterogeneous density). The superiority of <italic>RNN-DBSCAN</italic> is demonstrated on several artificial and real-world datasets with respect to prior work on reverse nearest neighbor based clustering approaches (<italic>RECORD</italic>, <italic>IS-DBSCAN</italic>, and <italic> ISB-DBSCAN</italic>) along with <italic>DBSCAN</italic> and <italic>OPTICS</italic>. Each of these clustering approaches is described by a common graph-based interpretation wherein clusters of dense observations are defined as connected components, along with a discussion on their computational complexity. Heuristics for <italic>RNN-DBSCAN </italic> parameter selection are presented, and the effects of <inline-formula><tex-math notation="LaTeX">$k$ </tex-math><alternatives><inline-graphic xlink:href="bryant-ieq3-2787640.gif"/></alternatives></inline-formula> on <italic>RNN-DBSCAN</italic> clusterings discussed. Additionally, with respect to scalability, an approximate version of <italic>RNN-DBSCAN</italic> is presented leveraging an existing approximate <inline-formula><tex-math notation="LaTeX"> $k$</tex-math><alternatives><inline-graphic xlink:href="bryant-ieq4-2787640.gif"/></alternatives></inline-formula> nearest neighbor technique.
Transcription of human respiratory syncytial virus genome RNA in vitro: requirement of cellular factor(s)

Extracts made from human respiratory syncytial virus (RSV)-infected Hep-2 cells synthesized mRNAs encoded by all known viral genes. In contrast, RSV ribonucleoproteins purified from infected cells failed to transcribe in vitro; transcription was restored by addition of a cytoplasmic extract of uninfected Hep-2 cells, demonstrating that a cellular factor(s) has a role in RSV gene expression. Quantitation of the individual gene mRNAs transcribed in vitro revealed polarity of transcription of the genome.
Reorienting When Cues Conflict

Proponents of a geometric module claim that human adults accomplish spatial reorientation in a fundamentally different way than young children and non-human animals do. However, reporting two experiments that used a conflict paradigm, this article shows striking similarities between human adults and young children, as well as nonhuman animals. Specifically, Experiment 1 demonstrates that adults favor geometric information in a small room and rely on features in a larger room, whereas Experiment 2 demonstrates that experience in a larger room produces dominance of features over geometric cues in a small room—the first human case of reliance on features that contradict geometric information. Thus, use of features during reorientation depends on the size of the environment and learning history. These results clearly undermine the modularity claim and the view that feature use during reorientation is purely associative, and we discuss the findings within an adaptive-combination view, according to which a weighting system determines use of feature or geometric cues during reorientation.
Start Up Problem in a Network Good Market: The Use of Advertising by a Monopolist Provider

The start up problem in a network market refers to the necessity for the provider of the good exhibiting positive network externalities to find appropriate tools to make the network start. Rohlfs (1974) was the first to recognise the possible use by the provider of marketing policies in order to attract the critical mass, but a formal treatment of the issue has never been tempted. This essay tries to cover this lack. Through the introduction into the analysis of advertising we examine how this inclusion may modify the received theory.
CENTRE FOR APPLIED MACROECONOMIC ANALYSIS The Australian National University

The primary pro-competitive justification for multiple principals to hire a common bidding agent is efficiency. The efficiency gained by doing so increases the advantage of the common bidding agent. Almost common value auction theory predicts that an advantaged bidder is able to reduce competition by credibly enhancing the ‘winner’s curse’ of disadvantaged rivals. The credible threat results in disadvantaged rivals exiting the bidding process early, leaving the advantaged bidder to purchase most, if not all, units at lower prices than when rivals have common values. The results of our empirical study of a common bidding agent are consistent with this theory.