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Bias

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Full-Text Articles in Social and Behavioral Sciences

Blind Spots: The Effects Of Information And Stakes On Fairness Bias And Dispersion, James Konow Dec 2005

Blind Spots: The Effects Of Information And Stakes On Fairness Bias And Dispersion, James Konow

Economics Faculty Works

Mounting empirical research provides evidence of fairness bias and its economic and social effects, where fairness bias refers here to a deviation of claims from unbiased justice due to a personal stake. A far less appreciated issue is dispersion of fairness views and claims, which is also important for its effects on disagreements, empirical analysis, and philosophical theories. This study undertakes a systematic analysis of the effects on fairness bias and dispersion of two variables: stakes and information. Most philosophical and social science analyses related to justice and bias associate heightened bias with increased information and, conversely, impartiality with the …

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Hac Estimation By Automated Regression, Peter C.B. Phillips Jul 2004

Hac Estimation By Automated Regression, Peter C.B. Phillips

Cowles Foundation Discussion Papers

A simple regression approach to HAC and LRV estimation is suggested. The method exploits the fact that the quantities of interest relate to only one point of the spectrum (the origin). The new estimator is simply the explained sum of squares in a linear regression whose regressors are a set of trend basis functions. Positive definiteness in the estimate is therefore automatically enforced and the technique can be implemented with standard regression packages. No kernel choice is needed in practical implementation but basis functions need to be chosen and a smoothing parameter corresponding to the number of basis functions needs …

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Prewhitening Bias In Hac Estimation, Donggyu Sul, Peter C.B. Phillips, Chi-Young Choi Sep 2003

Prewhitening Bias In Hac Estimation, Donggyu Sul, Peter C.B. Phillips, Chi-Young Choi

Cowles Foundation Discussion Papers

HAC estimation commonly involves the use of prewhitening filters based on simple autoregressive models. In such applications, small sample bias in the estimation of autoregressive coefficients is transmitted to the recoloring filter, leading to HAC variance estimates that can be badly biased. The present paper provides an analysis of these issues using asymptotic expansions and simulations. The approach we recommend involves the use of recursive demeaning procedures that mitigate the effects of small sample autoregressive bias. Moreover, a commonly-used restriction rule on the prewhitening estimates (that first order autoregressive coefficient estimates, or largest eigenvalues, greater than 0.97 be replaced by …

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Bias In Dynamic Panel Estimation With Fixed Effects, Incidental Trends And Cross Section Dependence, Peter C.B. Phillips, Donggyu Sul Sep 2003

Bias In Dynamic Panel Estimation With Fixed Effects, Incidental Trends And Cross Section Dependence, Peter C.B. Phillips, Donggyu Sul

Cowles Foundation Discussion Papers

Explicit asymptotic bias formulae are given for dynamic panel regression estimators as the cross section sample size N → ∞. The results extend earlier work by Nickell (1981) and later authors in several directions that are relevant for practical work, including models with unit roots, deterministic trends, predetermined and exogenous regressors, and errors that may be cross sectionally dependent. The asymptotic bias is found to be so large when incidental linear trends are fitted and the time series sample size is small that it changes the sign of the autoregressive coefficient. Another finding of interest is that, when there is …

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Strivers And Underachievers: Effects On First Year College Grades And Retention, Heather M. O'Neill May 2003

Strivers And Underachievers: Effects On First Year College Grades And Retention, Heather M. O'Neill

Business and Economics Faculty Publications

In 1999, the Educational Testing Service created a Strivers Index where students who scored 200 points higher than expected on the SAT exam, based on their socioeconomic background, were called Strivers. Similarly, an Underachiever is a student who scores 200 below expected on the SAT. The presumption is that tagging a student as Striver or Underachiever will assist admissions offices in selecting the students. How Strivers and Underachievers perform in their first year academically and their college persistence patterns are examined in this paper.

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A Method For Testing Low-Value Spatial Clustering For Rare Diseases, Ge Lin, Tonglin Zhang Jan 2003

A Method For Testing Low-Value Spatial Clustering For Rare Diseases, Ge Lin, Tonglin Zhang

Regional Research Institute Working Papers

This paper proposes a method that tests for the existence of low-value spatial clustering while accounting for the influence of high-value clustering. Although the method was developed in reference to the Tango test, it can be extended to other testing methods. The simulation results showed that the proposed method is able to effectively detect low-value clustering with substantially lower rates of type I errors than those of the Tango test, while maintaining comparable statistical power. Applying the method in a case study of leukemia in Minnesota demonstrated an overall tendency toward low-value clustering of leukemia mortality for males but provided …

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Gmm Estimation Of Autoregressive Roots Near Unity With Panel Data, Hyungsik Roger Moon, Peter C.B. Phillips Jan 2003

Gmm Estimation Of Autoregressive Roots Near Unity With Panel Data, Hyungsik Roger Moon, Peter C.B. Phillips

Cowles Foundation Discussion Papers

This paper investigates a generalized method of moments (GMM) approach to the estimation of autoregressive roots near unity with panel data and incidental deterministic trends. Such models arise in empirical econometric studies of firm size and in dynamic panel data modeling with weak instruments. The two moment conditions in the GMM approach are obtained by constructing bias corrections to the score functions under OLS and GLS detrending, respectively. It is shown that the moment condition under GLS detrending corresponds to taking the projected score on the Bhattacharya basis, linking the approach to recent work on projected score methods for models …

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Infected Judgment: Legal Responses To Physician Bias, Mary Crossley Jan 2003

Infected Judgment: Legal Responses To Physician Bias, Mary Crossley

Articles

Substantial evidence indicates that clinically irrelevant patient characteristics, including race and gender, may at times influence a physician's choice of treatment. Less clear, however, is whether a patient who is the victim of a biased medical decision has any effective legal recourse. Heedful of the difficulties of designing research to establish conclusively the role of physician bias, this article surveys published evidence suggesting the operation of physician bias in clinical decision making. The article then examines potential legal responses to biased medical judgments. A patient who is the subject of a biased decision may sue her doctor for violating his …

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Dynamic Panel Estimation And Homogeneity Testing Under Cross Section Dependence, Peter C.B. Phillips, Donggyu Sul May 2002

Dynamic Panel Estimation And Homogeneity Testing Under Cross Section Dependence, Peter C.B. Phillips, Donggyu Sul

Cowles Foundation Discussion Papers

This paper deals with cross section dependence, homogeneity restrictions and small sample bias issues in dynamic panel regressions. To address the bias problem we develop a panel approach to median unbiased estimation that takes account of cross section dependence. The new estimators given here considerably reduce the effects of bias and gain precision from estimating cross section error correlation. The paper also develops an asymptotic theory for tests of coefficient homogeneity under cross section dependence, and proposes a modified Hausman test to test for the presence of homogeneous unit roots. An orthogonalization procedure is developed to remove cross section dependence …

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Gmm Estimation Of Autoregressive Roots Near Unity With Panel Data, Hyungsik Roger Moon, Peter C.B. Phillips Aug 2000

Gmm Estimation Of Autoregressive Roots Near Unity With Panel Data, Hyungsik Roger Moon, Peter C.B. Phillips

Cowles Foundation Discussion Papers

This paper investigates a generalized method of moments (GMM) approach to the estimation of autoregressive roots near unity with panel data. The two moment conditions studied are obtained by constructing bias corrections to the score functions under OLS and GLS detrending, respectively. It is shown that the moment condition under GLS detrending corresponds to taking the projected score on the Bhattacharya basis, linking the approach to recent work on projected score methods for models with infinite numbers of nuisance parameters (Waterman and Lindsay, 1998). Assuming that the localizing parameter makes a nonpositive value, we establish consistency of the GMM estimator …

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Estimation Of Autoregressive Roots Near Unity Using Panel Data, Hyungsik Roger Moon, Peter C.B. Phillips Jun 1999

Estimation Of Autoregressive Roots Near Unity Using Panel Data, Hyungsik Roger Moon, Peter C.B. Phillips

Cowles Foundation Discussion Papers

Time series data are often well modelled by using the device of an autoregressive root that is local to unity. Unfortunately, the localizing parameter (c) is not consistently estimable using existing time series econometric techniques and the lack of a consistent estimator complicates inference. This paper develops procedures for the estimation of a common localizing parameter using panel data. Pooling information across individuals in a panel aids the identification and estimation of the localising parameter and leads to consistent estimation in simple panel models. However, in the important case of models with concomitant deterministic trends, it is shown that pooled …

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The Systematic Bias Effects Of Incomplete Responses In Rotation Samples, William (Bill) H. Williams Jan 1970

The Systematic Bias Effects Of Incomplete Responses In Rotation Samples, William (Bill) H. Williams

Publications and Research

Rotation samples are frequently used in continuing surveys in order to obtain estimates of changes in a characteristic over time as well as separate estimates of the characteristic at specific points in time. Rotation designs involve the retention of some sampling units and the replacement of others. It has been observed in some studies that there are systematic changes in the estimate of a characteristic, depending on the frequency of appearance of a rotation group in the sample. It is shown in this paper that these systematic changes must occur provided (1) the probability of a selected unit actually appearing …

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