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243
Skill Differences and the Effect of Immigrants on the Wages of Natives
 U.S. Bureau of Labor Statistics, Economic Working Paper no.273. Washington D.C
, 1996
"... Abstract. This paper examines the effects of changes in the supply of immigrant labor on the wages of natives in the 1980s. Estimates are presented indicating that immigrants and natives are nearly perfect substitutes within broad skill categories. This result is then used to calculate the effects o ..."
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Cited by 35 (0 self)
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Abstract. This paper examines the effects of changes in the supply of immigrant labor on the wages of natives in the 1980s. Estimates are presented indicating that immigrants and natives are nearly perfect substitutes within broad skill categories. This result is then used to calculate the effects of the large influx of immigrants to the U.S. labor market. The calculations presented suggest that immigration depressed the wages of native dropouts by as much as 3 percent and can account for up to 24 percent of the increase in the college – high school wage differential in the 1980s.
Word informativeness and automatic pitch accent modeling
 in EMNLP/VCL
, 1999
"... To appear in Proc. of EMNLP/VLC, 1999. In intonational phonology and speech synthesis research, it has been suggested that the relative informativeness of a word can be used to predict pitch prominence. The more information conveyed by a word, the more likely it will be accented. But there are other ..."
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Cited by 33 (4 self)
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To appear in Proc. of EMNLP/VLC, 1999. In intonational phonology and speech synthesis research, it has been suggested that the relative informativeness of a word can be used to predict pitch prominence. The more information conveyed by a word, the more likely it will be accented. But there are others who express doubts about such a correlation. In this paper, we provide some empirical evidence to support the existence of such a correlation by employing two widely accepted measures of informativeness. Our experiments show that there is a positive correlation between the informativeness of a word and its pitch accent assignment. They also show that informativeness enables statistically significant improvements in pitch accent prediction. The computation of word informativeness is inexpensive and can be incorporated into speech synthesis systems easily. 1
Action as language in a shared visual space
 Proceedings of the ACM Conference on Computer Supported Cooperative Work
, 2004
"... A shared visual workspace allows multiple people to see similar views of objects and environments. Prior empirical literature demonstrates that visual information helps collaborators understand the current state of their task and enables them to communicate and ground their conversations efficiently ..."
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Cited by 33 (10 self)
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A shared visual workspace allows multiple people to see similar views of objects and environments. Prior empirical literature demonstrates that visual information helps collaborators understand the current state of their task and enables them to communicate and ground their conversations efficiently. We present an empirical study that demonstrates how action replaces explicit verbal instruction in a shared visual workspace. Pairs performed a referential communication task with and without a shared visual space. A detailed sequential analysis of the communicative content reveals that pairs with a shared workspace were less likely to explicitly verify their actions with speech. Rather, they relied on visual information to provide the necessary communicative and coordinative cues. Categories and Subject Descriptors
Automatic template creation for information extraction
, 1998
"... Information Extraction (IE) approaches currently assume that a template exists which sufficiently defines the requirements of the task. Substantial human effort is required to generate these basic templates and to provide a development corpus. In the two principal IE competitions, the Message Unders ..."
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Information Extraction (IE) approaches currently assume that a template exists which sufficiently defines the requirements of the task. Substantial human effort is required to generate these basic templates and to provide a development corpus. In the two principal IE competitions, the Message Understanding Conference (MUC) and Tipster, the templates were constructed directly from the experience of analysts. This manual approach cannot always be assumed. This proposal concerns the automatic construction of MUCstyle templates, substantially reducing the human effort required. The approach will carry out a corpusbased analysis of taskrelevant documents, identifying and analysing the interaction between the fundamental elements. A resource which defines semantic relationships will be necessary to identify and categorise these fundamental elements. This application is of particular interest to researchers in the field of IE and automatic abstracting. 1 1.
Computing Maximum Likelihood Estimates in loglinear models
, 2006
"... We develop computational strategies for extended maximum likelihood estimation, as defined in Rinaldo (2006), for general classes of loglinear models of widespred use, under Poisson and productmultinomial sampling schemes. We derive numerically efficient procedures for generating and manipulating ..."
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Cited by 25 (4 self)
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We develop computational strategies for extended maximum likelihood estimation, as defined in Rinaldo (2006), for general classes of loglinear models of widespred use, under Poisson and productmultinomial sampling schemes. We derive numerically efficient procedures for generating and manipulating design matrices and we propose various algorithms for computing the extended maximum likelihood estimates of the expectations of the cell counts. These algorithms allow to identify the set of estimable cell means for any given observable table and can be used for modifying traditional goodnessoffit tests to accommodate for a nonexistent MLE. We describe and take advantage of the connections between extended maximum likelihood
Binary models for marginal independence
 JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B
, 2005
"... A number of authors have considered multivariate Gaussian models for marginal independence. In this paper we develop models for binary data with the same independence structure. The models can be parameterized based on Möbius inversion and maximum likelihood estimation can be performed using a versi ..."
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Cited by 24 (2 self)
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A number of authors have considered multivariate Gaussian models for marginal independence. In this paper we develop models for binary data with the same independence structure. The models can be parameterized based on Möbius inversion and maximum likelihood estimation can be performed using a version of the Iterated Conditional Fitting algorithm. The approach is illustrated on a simple example. Relations to multivariate logistic and dependence ratio models are discussed.
Longrange Dependence in Daily Stock Volatilities
 J. Bus. Ec. Stat
, 2000
"... Recent empirical studies show that the squares of highfrequency stock returns are longrange dependent and can be modeled as fractionally integrated processes, using, for example, longmemory stochastic volatility models. Are such longrange dependencies common among stocks? Are they caused by t ..."
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Cited by 21 (0 self)
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Recent empirical studies show that the squares of highfrequency stock returns are longrange dependent and can be modeled as fractionally integrated processes, using, for example, longmemory stochastic volatility models. Are such longrange dependencies common among stocks? Are they caused by the same sources of variation? In this paper, we classify daily stock returns of S&P 500 companies on the basis of the company's size and its business or industrial sector, and estimate the strength of longrange dependence in the stock volatilities using two different methods. Almost all of the companies analyzed exhibit strong persistence in volatility. We then use a canonical correlation method to identify common longrange dependent components in groups of companies, finding strong evidence in support of common persistence in volatility. Finally, we use a chisquared test to study the effects of company size and sector on the number of common longrange dependent volatility compon...
Large sample theory of maximum likelihood estimates in semiparametric biased sampling models
 Annals of Statistics
, 2000
"... Vardi [Ann. Statist. 13 178–203 (1985)] introduced an ssample biased sampling model with known selection weight functions, gave a condition under which the common underlying probability distribution G is uniquely estimable and developed simple procedure for computing the nonparametric maximum like ..."
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Cited by 19 (5 self)
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Vardi [Ann. Statist. 13 178–203 (1985)] introduced an ssample biased sampling model with known selection weight functions, gave a condition under which the common underlying probability distribution G is uniquely estimable and developed simple procedure for computing the nonparametric maximum likelihood estimator (NPMLE) n of G. Gill, Vardi and Wellner thoroughly described the large sample properties of Vardi’s NPMLE, giving results on uniform consistency, convergence of n n − G to a Gaussian process and asymptotic efficiency of n. Gilbert, Lele and Vardi considered the class of semiparametric ssample biased sampling models formed by allowing the weight functions to depend on an unknown finitedimensional parameter θ. They extended Vardi’s estimation approach by developing a simple twostep estimation procedure in which θ̂n is obtained by maximizing a profile partial likelihood and n ≡ nθ̂n is obtained by evaluating Vardi’s NPMLE at θ̂n. Here we examine the large sample behavior of the resulting joint MLE θ̂nn, characterizing conditions on the selection weight functions and data in order that θ̂nn is uniformly consistent, asymptotically Gaussian and efficient. Examples illustrated here include clinical trials (especially HIV vaccine efficacy trials), choicebased sampling in econometrics and casecontrol studies in biostatistics.