Regression Discontinuity Design for Cross-Sectional Data, Longitudinal Data, and Intervention Research for Special Education

2017 ◽  
pp. 137-150
2019 ◽  
Vol 21 (1) ◽  
pp. 24-42 ◽  
Author(s):  
Sander Kunst ◽  
Theresa Kuhn ◽  
Herman G van de Werfhorst

Previous research shows a strong and consistent relationship between educational attainment and Euroscepticism. As a result, education is considered to be a powerful predictor of attitudes towards European integration. However, these findings are predominantly found using cross-sectional research designs, therefore leaving open the possibility of strong selection effects due to pre-adult experiences and dispositions which both explain educational attainment and political attitudes. To test whether schooling causally reduces Euroscepticism, this article combines data on the compulsory schooling age with seven rounds of pooled European Social Survey data (2002–2014). Using compulsory schooling reforms within a ‘fuzzy’ regression discontinuity design, the results indicate no conclusive effect of education on Euroscepticism, questioning the impact of additional schooling. Consequently, this study provides a novel insight into the much-debated divide in support for European integration between lower and higher educated.


2017 ◽  
Vol 52 (2) ◽  
pp. 553-582 ◽  
Author(s):  
Qianqian Huang ◽  
Feng Jiang ◽  
Erik Lie ◽  
Tingting Que

We find evidence that labor unions affect chief executive officer (CEO) compensation. First, we find that firms with strong unions pay their CEOs less. The negative effect is robust to various tests for endogeneity, including cross-sectional variations and a regression discontinuity design. Second, we find that CEO compensation is curbed before union contract negotiations, especially when the compensation is discretionary and the unions have a strong bargaining position. Third, we report that curbing CEO compensation mitigates the chance of a labor strike, thus providing a rationale for firms to pay CEOs less when facing strong unions.


2018 ◽  
Vol 10 (1) ◽  
pp. 533-552 ◽  
Author(s):  
Catherine Hausman ◽  
David S. Rapson

Recent empirical work in several economic fields, particularly environmental and energy economics, has adapted the regression discontinuity (RD) framework to applications where time is the running variable and treatment begins at a particular threshold in time. In this guide for practitioners, we discuss several features of this regression discontinuity in time framework that differ from the more standard cross-sectional RD framework. First, many applications (particularly in environmental economics) lack cross-sectional variation and are estimated using observations far from the temporal threshold. This common empirical practice is hard to square with the assumptions of a cross-sectional RD, which is conceptualized for an estimation bandwidth shrinking even as the sample size increases. Second, estimates may be biased if the time-series properties of the data are ignored (for instance, in the presence of an autoregressive process), or more generally if short-run and long-run effects differ. Finally, tests for sorting or bunching near the threshold are often irrelevant, making the framework closer to an event study than a regression discontinuity design. Based on these features and motivated by hypothetical examples using air quality data, we offer suggestions for the empirical researcher wishing to use the RD in time framework.


2021 ◽  
Author(s):  
Mathijs de Haas ◽  
Maarten Kroesen ◽  
Caspar Chorus ◽  
Sascha Hoogendoorn-Lanser ◽  
Serge Hoogendoorn

AbstractIn recent years, the e-bike has become increasingly popular in many European countries. With higher speeds and less effort needed, the e-bike is a promising mode of transport to many, and it is considered a good alternative for certain car trips by policy-makers and planners. A major limitation of many studies that investigate such substitution effects of the e-bike, is their reliance on cross-sectional data which do not allow an assessment of within-person travel mode changes. As a consequence, there is currently no consensus about the e-bike’s potential to replace car trips. Furthermore, there has been little research focusing on heterogeneity among e-bike users. In this respect, it is likely that different groups exist that use the e-bike for different reasons (e.g. leisure vs commute travel), something which will also influence possible substitution patterns. This paper contributes to the literature in two ways: (1) it presents a statistical analysis to assess the extent to which e-bike trips are substituting trips by other travel modes based on longitudinal data; (2) it reveals different user groups among the e-bike population. A Random Intercept Cross-Lagged Panel Model is estimated using five waves of data from the Netherlands Mobility Panel. Furthermore, a Latent Class Analysis is performed using data from the Dutch national travel survey. Results show that, when using longitudinal data, the substitution effects between e-bike and the competing travel modes of car and public transport are not as significant as reported in earlier research. In general, e-bike trips only significantly reduce conventional bicycle trips in the Netherlands, which can be regarded an unwanted effect from a policy-viewpoint. For commuting, the e-bike also substitutes car trips. Furthermore, results show that there are five different user groups with their own distinct behaviour patterns and socio-demographic characteristics. They also show that groups that use the e-bike primarily for commuting or education are growing at a much higher rate than groups that mainly use the e-bike for leisure and shopping purposes.


Energies ◽  
2019 ◽  
Vol 12 (13) ◽  
pp. 2582 ◽  
Author(s):  
Samuel Lotsu ◽  
Yuichiro Yoshida ◽  
Katsufumi Fukuda ◽  
Bing He

Confronting an energy crisis, the government of Ghana enacted a power factor correction policy in 1995. The policy imposes a penalty on large-scale electricity users, namely, special load tariff (SLT) customers of the Electricity Company of Ghana (ECG), whose power factor is below 90%. This paper investigates the impact of this policy on these firms’ power factor improvement by using panel data from 183 SLT customers from 1994 to 1997 and from 2012. To avoid potential endogeneity, this paper adopts a regression discontinuity design (RDD) with the power factor of the firms in the previous year as a running variable, with its cutoff set at the penalty threshold. The result shows that these large-scale electricity users who face the penalty because their power factor falls just short of the threshold are more likely to improve their power factor in the subsequent year, implying that the power factor correction policy implemented by Ghana’s government is effective.


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