scholarly journals Innovation panel surveys in Germany

2014 ◽  
pp. 135-177 ◽  
Author(s):  
Bettina Peters ◽  
Christian Rammer
Keyword(s):  
Panel Surveys

Ideological Inversion and the (De)legitimation of Neoliberalism in Chile

2020 ◽  
Author(s):  
Ismael Puga
Keyword(s):  
Mixed Methods ◽  
Social Economic ◽  
Social Study ◽  
Social Practices ◽  
Economic Order ◽  
Window Of Opportunity ◽  
Panel Surveys ◽  
Mixed Methods Approach ◽  
Strategic Adaptation ◽  
The Social

Using a mixed-methods approach based on discussion focus groups and panel surveys of the Longitudinal Social Study of Chile, this chapter demonstrates that Chilean’s neoliberal economic order is not legitimized by the vast majority of the population. Instead, the author argues that social norms are in serious conflict with the prevailing socioeconomic order. Within Chilean society, both citizens and social analysts are prone to agree with the existence of a “neoliberal consensus” due to the strategic adaptation of social practices that take place within a socioeconomic order that most individuals accept as a given. As a consequence, a “fantasy consensus” emerges in Chilean society in order to stabilize the social economic order, thus avoiding collective mobilization and social change. In this scenario, the protest waves that Chilean society has faced since 2011 offer additional proof that the “fantasy consensus” has experienced serious fissures, thus opening a window of opportunity to delegitimize Chile’s neoliberal order in the country.

President Obama and the Emergence of Islamophobia in Mass Partisan Preferences

2021 ◽  
pp. 106591292110072
Author(s):  
Michael Tesler
Keyword(s):  
Theoretical Basis ◽  
Independent Predictor ◽  
Survey Experiment ◽  
President Obama ◽  
Significant Independent Predictor ◽  
Cross Sectional ◽  
Panel Surveys ◽  
Voter Preferences ◽  
Nationally Representative ◽  
The Relationship

This article argues that the unusually large and persistent association between Islamophobia and opposition to President Obama helped make attitudes about Muslims a significant, independent predictor of Americans’ broader partisan preferences. After detailing the theoretical basis for this argument, the article marshals repeated cross-sectional data, two panel surveys, and a nationally representative survey experiment, to test its hypotheses. The results from those analyses show the following: (1) attitudes about Muslims were a significantly stronger independent predictor of voter preferences for congress in 2010–2014 elections than they were in 2004–2008; (2) attitudes about Muslims were a significantly stronger independent predictor of mass partisanship during Obama’s presidency than they were beforehand; and (3) experimentally connecting Obama to Democratic congressional candidates significantly increased the relationship between anti-Muslim sentiments and Americans’ preferences for Republican congressional candidates. The article concludes with a discussion of the implications of these results for American politics in the Trump era.

scholarly journals Optimal Allocation of Interviews to Baseline and Endline Surveys in Place-Based Randomized Trials and Quasi-Experiments

2018 ◽  
Vol 42 (4) ◽  
pp. 391-422 ◽  
Author(s):  
Donald P. Green ◽  
Winston Lin ◽  
Claudia Gerber
Keyword(s):  
Random Sample ◽  
Treatment Effect ◽  
Randomized Trials ◽  
Optimal Allocation ◽  
Average Treatment Effect ◽  
Baseline Survey ◽  
Baseline Measure ◽  
Panel Surveys ◽  
Planning Stage ◽  
Average Treatment

Background: Many place-based randomized trials and quasi-experiments use a pair of cross-section surveys, rather than panel surveys, to estimate the average treatment effect of an intervention. In these studies, a random sample of individuals in each geographic cluster is selected for a baseline (preintervention) survey, and an independent random sample is selected for an endline (postintervention) survey. Objective: This design raises the question, given a fixed budget, how should a researcher allocate resources between the baseline and endline surveys to maximize the precision of the estimated average treatment effect? Results: We formalize this allocation problem and show that although the optimal share of interviews allocated to the baseline survey is always less than one-half, it is an increasing function of the total number of interviews per cluster, the cluster-level correlation between the baseline measure and the endline outcome, and the intracluster correlation coefficient. An example using multicountry survey data from Africa illustrates how the optimal allocation formulas can be combined with data to inform decisions at the planning stage. Another example uses data from a digital political advertising experiment in Texas to explore how precision would have varied with alternative allocations.

scholarly journals A Randomized Response Technique for Reducing the Effect of Initial Non-response of the Regression Estimator in Panel Surveys

2021 ◽  
Author(s):  
Mursala Khan
Keyword(s):  
Response Rate ◽  
Vital Role ◽  
Complex Nature ◽  
Randomized Response ◽  
Sensitive Questions ◽  
Cross Sectional ◽  
Panel Surveys ◽  
Survey Technique ◽  
Planning Methods ◽  
Family Planning Methods

Abstract The results of Sample surveys play a vital role in decision making. One of the main issues being faced by survey statisticians during the collection of survey data is the problem of non-response which may affect survey cost and accuracy of estimates. The problem of non-response becomes more severe if the survey contains sensitive questions like related to family planning methods, use of drugs. To diminish the non-response rate arising in the case of direct questioning (DQ) technique, Warner (1965) proposed an indirect survey technique known as the randomized response (RR) technique. He addressed this problem for a cross-sectional data. This method is a well-known procedure that produces more valid responses on sensitive questions in surveys. The method avoids the direct link between respondent’s response and the sensitive question through the help of a randomization device. Thereby protecting respondent’s privacy which in turn greatly increases survey response rate. However, due to the complex nature of panel estimator, the work is missing the in the context of RR technique. To cover this gap, we propose a linear regression model in the context of panel surveys/longitudinal studies under the application of the RR technique. We solve all these issues through simulation study.

The LIVES Daily Hassles Scale and Its Relation to Life Satisfaction

Assessment ◽  
2021 ◽  
pp. 107319112110478
Author(s):  
Shagini Udayar ◽  
Ieva Urbanaviciute ◽  
Davide Morselli ◽  
Grégoire Bollmann ◽  
Jérome Rossier ◽  
...  
Keyword(s):  
Life Satisfaction ◽  
Factor Analysis ◽  
Principal Axis ◽  
Daily Hassles ◽  
Hierarchical Regression ◽  
Panel Surveys ◽  
Five Factors ◽  
Confirmatory Factor ◽  
Principal Axis Factor Analysis ◽  
German Speaking

Although daily hassles have been of interest since the 1980s, only a few tools have been developed to assess them. Most of them are checklists or open-ended questions that are demanding for participants in panel surveys. Therefore, to facilitate daily hassles integration into large surveys, the aim of this study was to present a new tool assessing daily hassles, the LIVES–Daily Hassles Scale (LIVES-DHS), and to examine its relation to life satisfaction, in a sample of 1,170 French- and German-speaking adults living in Switzerland. In a first random subsample, we conducted a principal axis factor analysis, and the results suggested a five-factor solution. Furthermore, we conducted a confirmatory factor analysis on a second random subsample, and it supported the hierarchical factor structure of the scale. The LIVES-DHS consists of 18 items represented by five factors that describe five sources of daily hassles: financial, physical, relational, environmental, and professional. The bivariate correlations showed that the LIVES-DHS could differentiate the concept of daily hassles from associated concepts. Finally, the hierarchical regression showed that daily hassles negatively predicted life satisfaction and added a significant incremental variance beyond that accounted for by age, gender, household income, education level, and personality traits.

Implications of online incidental and selective exposure for political emotions: Affective polarization during elections

2021 ◽  
pp. 146144482110613
Author(s):  
Qinfeng Zhu ◽  
Brian E Weeks ◽  
Nojin Kwak
Keyword(s):  
Digital Media ◽  
Presidential Elections ◽  
Emotional Responses ◽  
Selective Exposure ◽  
Panel Surveys ◽  
Political Emotions ◽  
Incidental Exposure ◽  
Shared Information ◽  
Using Data ◽  
Political Groups

The Internet and social media create an environment in which individuals can selectively approach information supporting their political worldviews while also being incidentally exposed to socially shared information that challenges their beliefs. These competing information consumption patterns may help explain whether and how digital media contribute to affective polarization (i.e. affect-based division between political groups). This study examines how pro-attitudinal selective exposure and counter-attitudinal incidental exposure in tandem influence political emotions. Using data from 2, two-wave panel surveys conducted during the 2016 and 2020 US presidential elections, our findings demonstrate that seeking consonant political information is consistently associated with anger toward political opponents and enthusiasm toward like-minded partisans. In contrast, despite the purported democratic benefits endowed on political disagreement, cross-cutting incidental exposure does not temper political emotional responses associated with pro-attitudinal selective exposure. However, we find little evidence that unexpected exposure to disagreeable information backfires either.

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