A Note on Close Elections and Regression Analysis of the Party Incumbency Advantage

2014 ◽  
Vol 5 (1-2) ◽  
pp. 1-11
Author(s):  
Peter M. Aronow ◽  
David R. Mayhew ◽  
Winston Lin
Keyword(s):  
Regression Analysis ◽  
Least Squares ◽  
Control Strategy ◽  
House Of Representatives ◽  
Regression Discontinuity ◽  
Ordinary Least Squares ◽  
Regression Discontinuity Design ◽  
Least Squares Regression ◽  
Incumbency Advantage ◽  
The Us

AbstractMuch research has recently been devoted to understanding the effects of party incumbency following close elections, typically using a regression discontinuity design. Researchers have demonstrated that close elections in the US House of Representatives may systematically favor certain types of candidates, and that a research design that focuses on close elections may therefore be inappropriate for estimation of the incumbency advantage. We demonstrate that any issues raised with the study of close elections may be equally applicable to the ordinary least squares analysis of electoral data, even when the sample contains all elections. When vote share is included as part of a covariate control strategy, the estimate produced by an ordinary least squares regression that includes all elections either exactly reproduces or approximates the regression discontinuity estimate.

Quantile Regression Analysis and Other Alternatives to Ordinary Least Squares Regression

Methodology ◽  
2014 ◽  
Vol 10 (3) ◽  
pp. 81-91 ◽  
Author(s):  
Harry Haupt ◽  
Friedrich Lösel ◽  
Mark Stemmler
Keyword(s):  
Regression Analysis ◽  
Quantile Regression ◽  
Least Squares ◽  
Corporal Punishment ◽  
Ordinary Least Squares ◽  
Study Data ◽  
Physical Punishment ◽  
Least Squares Regression ◽  
Prevention Project ◽  
Quantile Regression Analysis

Data analyses by classical ordinary least squares (OLS) regression techniques often employ unrealistic assumptions, fail to recognize the source and nature of heterogeneity, and are vulnerable to extreme observations. Therefore, this article compares robust and non-robust M-estimator regressions in a statistical demonstration study. Data from the Erlangen-Nuremberg Development and Prevention Project are used to model risk factors for physical punishment by fathers of 485 elementary school children. The Corporal Punishment Scale of the Alabama Parenting Questionnaire was the dependent variable. Fathers’ aggressiveness, dysfunctional parent-child relations, various other parenting characteristics, and socio-demographic variables served as predictors. Robustness diagnostics suggested the use of trimming procedures and outlier diagnostics suggested the use of robust estimators as an alternative to OLS. However, a quantile regression analysis provided more detailed insights beyond the measures of central tendency and detected sources of considerable heterogeneity in the risk structure of father’s corporal punishment. Advantages of this method are discussed with regard to methodological and content issues.

scholarly journals Performance of Deming regression analysis in case of misspecified analytical error ratio in method comparison studies

1998 ◽  
Vol 44 (5) ◽  
pp. 1024-1031 ◽  
Author(s):  
Kristian Linnet
Keyword(s):  
Regression Analysis ◽  
Least Squares ◽  
Measurement Errors ◽  
Method Comparison ◽  
Ordinary Least Squares ◽  
Least Squares Regression ◽  
Analytical Error ◽  
First Case ◽  
Error Ratio ◽  
Deming Regression

Abstract Application of Deming regression analysis to interpret method comparison data presupposes specification of the squared analytical error ratio (λ), but in cases involving only single measurements by each method, this ratio may be unknown and is often assigned a default value of one. On the basis of simulations, this practice was evaluated in situations with real error ratios deviating from one. Comparisons of two electrolyte methods and two glucose methods were simulated. In the first case, misspecification of λ produced a bias that amounted to two-thirds of the maximum bias of the ordinary least-squares regression method. Standard errors and the results of hypothesis-testing also became misleading. In the second situation, a misspecified error ratio resulted only in a negligible bias. Thus, given a short range of values in relation to the measurement errors, it is important that λ is correctly estimated either from duplicate sets of measurements or, in the case of single measurement sets, specified from quality-control data. However, even with a misspecified error ratio, Deming regression analysis is likely to perform better than least-squares regression analysis.

How Much of the Incumbency Advantage is Due to Scare-Off?

2015 ◽  
Vol 3 (3) ◽  
pp. 493-514 ◽  
Author(s):  
Andrew B. Hall ◽  
James M. Snyder
Keyword(s):  
Regression Discontinuity ◽  
Regression Discontinuity Design ◽  
Incumbency Advantage ◽  
Previous Election ◽  
Us Senate ◽  
State Legislative

This paper uses a regression discontinuity design to estimate the degree to which incumbents scare off challengers with previous officeholder experience. The estimates indicate a surprisingly small amount of scare-off, at least in cases where the previous election was nearly tied. As Lee and others have shown (and as we confirm for our samples) the estimated party incumbency advantage in these same cases is quite large—in fact, it is about as large as the average incumbency advantage for all races found using other approaches. Drawing from previous estimates of the electoral value of officeholder experience, we thus calculate that scare-off in these cases accounts for only about 5–7 percent of the party incumbency advantage. We show that these patterns are similar in elections for US House seats, statewide offices and US senate seats, and state legislative seats.

DOES TRUST PROMOTE ENTREPRENEURSHIP IN A DEVELOPING COUNTRY?

2018 ◽  
Vol 63 (05) ◽  
pp. 1385-1403 ◽  
Author(s):  
KITAE SOHN ◽  
ILLOONG KWON
Keyword(s):  
Developing Countries ◽  
Property Rights ◽  
Least Squares ◽  
Developing Country ◽  
Ordinary Least Squares ◽  
Community Level ◽  
Two Stage ◽  
The Us ◽  
The Difference ◽  
The Individual

Trust was found to promote entrepreneurship in the US. We investigated whether this was true in a developing country, Indonesia. We failed to replicate this; this failure was true whether trust was estimated at the individual or community level or whether ordinary least squares (OLS) or two stage least squares (2SLS) was employed. We reconciled the difference between our results and those for the US by arguing that the weak enforcement of property rights in developing countries and the consequent hold-up problem make it more efficient for entrepreneurs to produce generic goods than relationship-specific goods—producing generic goods does not depend on trust.

International association meetings

2017 ◽  
Vol 24 (3) ◽  
pp. 218-233 ◽  
Author(s):  
Susana Cró ◽  
António Miguel Martins
Keyword(s):  
Regression Analysis ◽  
Least Squares ◽  
Host Country ◽  
International Association ◽  
Ordinary Least Squares ◽  
Travel And Tourism ◽  
Meeting Planners ◽  
Competitiveness Index ◽  
Destination Management Organizations ◽  
Selection Of

The aim of our study is to discuss whether the key frequently identified destination attributes desired by associations and meeting planners determine the number of association meetings organized by each country in 2014. Regression analysis was used by ordinary least squares for the number of association meetings organized in 2014 by each country that shows the importance of 12 countries’ destination attributes reported in the meetings, incentives, conventions and events/exhibitions sector literature and included in the travel and tourism competitiveness index. Our study contributes to the literature in two ways: (i) to identify and evaluate the key attributes in the attraction of association meetings (until now dispersed) and (ii) empirically test the importance of these attributes in the selection of meeting host country. From a practical perspective, these findings give valuable information for destination management organizations and meeting planners about the factors that should be improved in each country in order to be selected more often in the organization of those events.

scholarly journals Tolerance Intervals in a Heteroscedastic Linear Regression Context with Applications to Aerospace Equipment Surveillance

2009 ◽  
Vol 2009 ◽  
pp. 1-8 ◽  
Author(s):  
Janet Myhre ◽  
Daniel R. Jeske ◽  
Michael Rennie ◽  
Yingtao Bi
Keyword(s):  
Linear Regression ◽  
Least Squares ◽  
Performance Metrics ◽  
Weighted Least Squares ◽  
Ordinary Least Squares ◽  
Automated System ◽  
Least Squares Regression ◽  
Data Set ◽  
Tolerance Intervals ◽  
Power Of The Test

A heteroscedastic linear regression model is developed from plausible assumptions that describe the time evolution of performance metrics for equipment. The inherited motivation for the related weighted least squares analysis of the model is an essential and attractive selling point to engineers with interest in equipment surveillance methodologies. A simple test for the significance of the heteroscedasticity suggested by a data set is derived and a simulation study is used to evaluate the power of the test and compare it with several other applicable tests that were designed under different contexts. Tolerance intervals within the context of the model are derived, thus generalizing well-known tolerance intervals for ordinary least squares regression. Use of the model and its associated analyses is illustrated with an aerospace application where hundreds of electronic components are continuously monitored by an automated system that flags components that are suspected of unusual degradation patterns.

Sign in / Sign up

Export Citation Format

Share Document