How local personal vote-earning attributes affect the aggregate party vote share: Evidence from the Belgian flexible-list PR system (2003–2014)

Politics ◽  
2018 ◽  
Vol 39 (4) ◽  
pp. 464-479
Author(s):  
Gert-Jan Put ◽  
Jef Smulders ◽  
Bart Maddens
Keyword(s):  
Regression Models ◽  
Empirical Test ◽  
Original Data ◽  
Ordinary Least Squares ◽  
Vote Share ◽  
District Level ◽  
National Party ◽  
Data Set ◽  
Geographically Distributed ◽  
Party Vote Shares

This article investigates the effect of candidates exhibiting local personal vote-earning attributes (PVEA) on the aggregate party vote share at the district level. Previous research has often assumed that packing ballot lists with localized candidates increases the aggregate party vote and seat shares. We present a strict empirical test of this argument by analysing the relative electoral swing of ballot lists at the district level, a measure of change in party vote shares which controls for the national party trend and previous party results in the district. The analysis is based on data of 7527 candidacies during six Belgian regional and federal election cycles between 2003 and 2014, which is aggregated to an original data set of 223 ballot lists. The ordinary least squares (OLS) regression models do not show a significant effect of candidates exhibiting local PVEA on relative electoral swing of ballot lists. However, the results suggest that ballot lists do benefit electorally if candidates with local PVEA are geographically distributed over different municipalities in the district.

Unsuccessful Success? Failed No-Confidence Motions, Competence Signals, and Electoral Support

2011 ◽  
Vol 44 (11) ◽  
pp. 1474-1499 ◽  
Author(s):  
Laron K. Williams
Keyword(s):  
Formal Model ◽  
Original Data ◽  
Vote Share ◽  
Data Set ◽  
Parliamentary Democracies ◽  
Electoral Support ◽  
The Government ◽  
Opposition Parties

If no-confidence motions are primarily motivated by bringing down governments, why do only approximately 5% of no-confidence motions in advanced parliamentary democracies from 1960 result in the termination of government? In this project the author addresses this puzzle by developing a formal model of the electoral benefits of no-confidence motions and tests these hypotheses with the use of an original data set. No-confidence motions represent highly visible opportunities for opposition parties to highlight their strength or ability compared to the government in the hopes of improving their vote shares. The author finds support for the signal-based theory on a sample of 20 advanced parliamentary democracies from 1960 to 2008. Although no-confidence motions result in decreases for the government parties, the opposition parties that propose the motion experience boosts in vote share. This relationship is even stronger when the proposing party is an alternative governing possibility—illustrated by the conditioning impacts of the number of parliamentary parties and the opposition party’s ideological extremism. This provides an explanation as to why opposition parties would continue to challenge the government even though the motions are likely to fail.

scholarly journals A reality check for students? How participating to the Model United Nations influences skills, IR perceptions, and perspectives on future career

Politics ◽  
2019 ◽  
Vol 40 (2) ◽  
pp. 245-261
Author(s):  
Fabrizio Coticchia ◽  
Enrico Calossi ◽  
Lorenzo Cicchi
Keyword(s):  
United Nations ◽  
Role Playing ◽  
Original Data ◽  
Multivariate Regression Analysis ◽  
Ordinary Least Squares ◽  
Data Set ◽  
Future Career ◽  
Alternative Hypotheses ◽  
University Enrolment ◽  
Personal Skills

Despite a growing number of studies on simulations and International Relations (IR), few analyses investigate how participating in a simulation affects students’ perceptions of relevant IR issues. In addition, almost none of the current analyses on role playing and IR investigate how the involvement in a simulation affects students’ views on university enrolment or future career. This article seeks to fill these gaps, addressing how students’ interpretations and expectations change after participating in the Model United Nations (MUN). This article studies how the MUN is perceived as an experience that helps improve personal skills such as language ability, negotiation skills, and knowledge related to IR issues. This article also analyses how perceptions about selected IR issues and views on future university enrolment or future career vary before and after the MUN. The article is based on an original data set from a survey submitted to high school and university students participating to two MUNs held in Spring 2018. This article also employs ordinary least squares (OLS) multivariate regression analysis to test alternative hypotheses.

Calibration of stormwater quality regression models: a random process?

2010 ◽  
Vol 62 (4) ◽  
pp. 875-882 ◽  
Author(s):  
A. Dembélé ◽  
J.-L. Bertrand-Krajewski ◽  
B. Barillon
Keyword(s):  
Experimental Data ◽  
Least Squares ◽  
Regression Models ◽  
Linear Models ◽  
Least Squares Method ◽  
Weighted Least Squares ◽  
Ordinary Least Squares ◽  
Data Sets ◽  
Data Set ◽  
Urban Catchments

Regression models are among the most frequently used models to estimate pollutants event mean concentrations (EMC) in wet weather discharges in urban catchments. Two main questions dealing with the calibration of EMC regression models are investigated: i) the sensitivity of models to the size and the content of data sets used for their calibration, ii) the change of modelling results when models are re-calibrated when data sets grow and change with time when new experimental data are collected. Based on an experimental data set of 64 rain events monitored in a densely urbanised catchment, four TSS EMC regression models (two log-linear and two linear models) with two or three explanatory variables have been derived and analysed. Model calibration with the iterative re-weighted least squares method is less sensitive and leads to more robust results than the ordinary least squares method. Three calibration options have been investigated: two options accounting for the chronological order of the observations, one option using random samples of events from the whole available data set. Results obtained with the best performing non linear model clearly indicate that the model is highly sensitive to the size and the content of the data set used for its calibration.

Safety net for agriculture: effect of idiosyncratic income shock on remittance payments

2017 ◽  
Vol 44 (1) ◽  
pp. 2-20 ◽  
Author(s):  
Eric Akobeng
Keyword(s):  
Empirical Test ◽  
Safety Net ◽  
Ordinary Least Squares ◽  
Least Square ◽  
Income Shocks ◽  
Data Set ◽  
Content Type ◽  
Income Shock ◽  
Remittance Flows ◽  
Female Headed Households

Purpose The purpose of this paper is to examine the effect of illness-driven agriculture income shocks on remittance payments in Ghana using a nationally representative household pseudo-panel data set for 1991/1992, 1998/1999 and 2005/2006. Design/methodology/approach The two-stage least square instrumental variable technique is used. This is compared with the ordinary least squares estimator. Findings The author finds that households in Ghana use remittances to protect themselves from negative agriculture income shocks. The study further reveals that the protection is resilient in female-headed households. Research limitations/implications The question of remittances as a safety net mechanism is interesting, but the limitation is the challenges involving the counterfactual setup in studying the effects of endogenous migration choices. Practical implications The study provides that, as far as microeconomic factors are concerned, remittances increase in times of negative agriculture income shocks attributed to illness in Ghana. Social implications The finding points to the fact that remittance payments play an essential role as an informal safety net during illness-driven agriculture income shock especially for female-headed households in Ghana. This has an important implication for poverty reduction in Ghana. Originality/value It provides an empirical test of the claim that remittance flows buffer idiosyncratic shock with micro-level household data that incorporates both internal and international remittances. The paper introduces gender dimension into idiosyncratic shocks’ impact. Also, the data set makes it possible to provide a reliable set of agriculture income shock estimates.

Diameter Prediction for Correcting Continuous Forest Inventory Data

1991 ◽  
Vol 8 (2) ◽  
pp. 76-82
Author(s):  
Douglas Eberhardt ◽  
Edwin J. Green
Keyword(s):  
Basal Area ◽  
Original Data ◽  
Ordinary Least Squares ◽  
Inventory Data ◽  
Time Intervals ◽  
Data Set ◽  
Advantages And Disadvantages ◽  
Continuous Forest ◽  
Time Period ◽  
Regular Time

Abstract Permanent plot data are used in many studies. Trees are measured for diameter, height, and other characteristics at regular time intervals. Occasionally, errors in the diameter measurements result in a larger diameter reported at the time of the first measurement rather than the second, thus making some of the data apparently unusable. Currently there are at least two basic methods in use to compensate and estimate the growth on trees exhibiting illogical consecutive diameters. This study examines these two techniques in addition to a few others, and evaluates the advantages and disadvantages of each method. A 5% random sample was drawn from a data set void of obviously incorrect diameter measurements. For each tree in the sample, one of the two diameter measurements was assumed to be incorrect and was replaced by a predicted estimate from one of the candidate methods. The sample was then put back into the original data set and the estimated basal area plot growth was calculated for that time period. This was then compared to the true plot growth, and the resulting differences were examined. Based upon these differences, it was concluded that ordinary least squares or the introduced standard deviation technique will provide the best results if applied on a plot by plot basis. North. J. Appl. For. 8(2):76-82.

Linking service innovation to firm performance

2017 ◽  
Vol 11 (4) ◽  
pp. 730-750 ◽  
Author(s):  
Markus Chiahan Tsai ◽  
Chunhsien Wang
Keyword(s):  
Firm Performance ◽  
Market Orientation ◽  
Service Innovation ◽  
Original Data ◽  
Ordinary Least Squares ◽  
Least Squares Regression ◽  
Data Set ◽  
Content Type ◽  
Marketing Orientation ◽  
Service Oriented

Purpose How in essence a firm’s service innovation affects its performance is always an intriguing and important issue to business researchers and practitioners. However little is known about the moderating effects of a firm’s approach to innovation and capability of marketing orientation that influence this aforementioned relationship and the underlying mechanisms. This paper aims to examine how ambidextrous innovation (exploration and exploitation innovation) and market orientation capabilities (market-sensing and customer-linking capabilities) can shape the relationship between service innovation and firm performance. Research model was developed based on theoretical foundation of the resource-based view and the rationed perspective. Design/methodology/approach Using an original data set comprising 170 service-oriented firms from Taiwan, the authors found that ambidextrous innovation and market orientation capabilities can significantly enhance performance for service-oriented firms. The authors used the traditional ordinary least squares regression and the zero-inflated Poisson regression to test the five hypotheses. Findings The empirical results fully support the hypotheses that ambidextrous innovation and market orientation capabilities can significantly enhance firm performance. These results imply that the benefits of ambidextrous innovation and market orientation capabilities can coexist in a service innovation deployment and that these combined benefit firm performance. Originality/value The ambidextrous innovation and market orientation capabilities play catalytic roles during innovative service implementation in the service-oriented sectors. The roles of these factors have rarely been examined together before. Hence, this study addresses the gaps in current understanding and provides valuable insights, particularly in the context of the future service innovation deployment. In addition, the theoretical and managerial implications of the findings provide useful and valuable information for both the researchers and managers of the service-oriented.

Determinants of housing prices in Baku: empirical analyses

2019 ◽  
Vol 12 (2) ◽  
pp. 281-297 ◽  
Author(s):  
Khatai Aliyev ◽  
Mehin Amiraslanova ◽  
Nigar Bakirova ◽  
Narmin Eynizada
Keyword(s):  
Housing Market ◽  
Regression Models ◽  
Polynomial Regression ◽  
Housing Prices ◽  
Ordinary Least Squares ◽  
Real Estate Market ◽  
Cross Sectional ◽  
Data Set ◽  
Content Type ◽  
Factors Affecting

Purpose This paper aims to reveal major factors affecting housing prices (flats and houses) in Baku, the capital of Azerbaijan Republic. Design/methodology/approach Based on cross-sectional data set of 497 flats and 443 houses, polynomial regression models are estimated for flats and houses separately. Regression models are estimated by using ordinary least squares. Findings Location, largeness, repair level and existence of bill of sale are major price determinants for flats. For houses, number of rooms also matters. Findings reveals that houses are land intensive (more floors, less land area) toward city center, and vice versa. Price difference due to existence of bill of sale diminishes significantly toward the surrounding areas. Research limitations/implications The data set represents view of sellers and does not take into consideration price bargaining in time of sale; probability of information asymmetries exists which not could accounted for, and urgency of sale is not considered. Practical implications Estimation results can be used for housing valuation by real estate market participants and investors. Social implications Research findings reveal importance of bill of sale as a major price determinant and expected to attract policymakers’ attention to solve such a big social problem. Additionally, models can be based for price estimations in Baku housing market. Originality/value The study contributes to the literature by empirically analyzing housing market in Baku, Azerbaijan. Research produces new practically valuable findings.

Rotational Characteristics of the Green Solar Corona: 1947-1991

1994 ◽  
Vol 144 ◽  
pp. 139-141 ◽  
Author(s):  
J. Rybák ◽  
V. Rušin ◽  
M. Rybanský
Keyword(s):  
Solar Corona ◽  
World Wide ◽  
Rotation Period ◽  
Original Data ◽  
Coronal Emission ◽  
Time Intervals ◽  
Data Set ◽  
The World ◽  
Coronal Emission Line ◽  
Homogeneous Data

AbstractFe XIV 530.3 nm coronal emission line observations have been used for the estimation of the green solar corona rotation. A homogeneous data set, created from measurements of the world-wide coronagraphic network, has been examined with a help of correlation analysis to reveal the averaged synodic rotation period as a function of latitude and time over the epoch from 1947 to 1991.The values of the synodic rotation period obtained for this epoch for the whole range of latitudes and a latitude band ±30° are 27.52±0.12 days and 26.95±0.21 days, resp. A differential rotation of green solar corona, with local period maxima around ±60° and minimum of the rotation period at the equator, was confirmed. No clear cyclic variation of the rotation has been found for examinated epoch but some monotonic trends for some time intervals are presented.A detailed investigation of the original data and their correlation functions has shown that an existence of sufficiently reliable tracers is not evident for the whole set of examinated data. This should be taken into account in future more precise estimations of the green corona rotation period.

Electing the Senate

2017 ◽  
Author(s):  
Wendy J. Schiller ◽  
Charles Stewart III
Keyword(s):  
Original Data ◽  
State Legislators ◽  
Internal Conflict ◽  
Data Set ◽  
Senate Elections ◽  
Political Actors ◽  
The Public ◽  
Seventeenth Amendment ◽  
The People ◽  
Election Process

From 1789 to 1913, U.S. senators were not directly elected by the people—instead the Constitution mandated that they be chosen by state legislators. This radically changed in 1913, when the Seventeenth Amendment to the Constitution was ratified, giving the public a direct vote. This book investigates the electoral connections among constituents, state legislators, political parties, and U.S. senators during the age of indirect elections. The book finds that even though parties controlled the partisan affiliation of the winning candidate for Senate, they had much less control over the universe of candidates who competed for votes in Senate elections and the parties did not always succeed in resolving internal conflict among their rank and file. Party politics, money, and personal ambition dominated the election process, in a system originally designed to insulate the Senate from public pressure. The book uses an original data set of all the roll call votes cast by state legislators for U.S. senators from 1871 to 1913 and all state legislators who served during this time. Newspaper and biographical accounts uncover vivid stories of the political maneuvering, corruption, and partisanship—played out by elite political actors, from elected officials, to party machine bosses, to wealthy business owners—that dominated the indirect Senate elections process. The book raises important questions about the effectiveness of Constitutional reforms, such as the Seventeenth Amendment, that promised to produce a more responsive and accountable government.

scholarly journals Least Likely Observations in Regression Models for Categorical Outcomes

2002 ◽  
Vol 2 (3) ◽  
pp. 296-300 ◽  
Author(s):  
Jeremy Freese
Keyword(s):  
Logistic Regression ◽  
Regression Models ◽  
Binary Logistic Regression ◽  
Positive Outcome ◽  
Ordinary Least Squares ◽  
Parameter Estimates ◽  
Least Squares Regression ◽  
Binary Logistic Regression Model ◽  
Ordered Logistic Regression ◽  
Negative Outcome

This article presents a method and program for identifying poorly fitting observations for maximum-likelihood regression models for categorical dependent variables. After estimating a model, the program leastlikely will list the observations that have the lowest predicted probabilities of observing the value of the outcome category that was actually observed. For example, when run after estimating a binary logistic regression model, leastlikely will list the observations with a positive outcome that had the lowest predicted probabilities of a positive outcome and the observations with a negative outcome that had the lowest predicted probabilities of a negative outcome. These can be considered the observations in which the outcome is most surprising given the values of the independent variables and the parameter estimates and, like observations with large residuals in ordinary least squares regression, may warrant individual inspection. Use of the program is illustrated with examples using binary and ordered logistic regression.

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