scholarly journals The Impact of Postsecondary Remediation Using a Regression Discontinuity Approach: Addressing Endogenous Sorting and Noncompliance

2008 ◽  
Author(s):  
Juan Carlos Calcagno ◽  
Bridget Terry Long
Keyword(s):  
Regression Discontinuity ◽  
Postsecondary Remediation ◽  
The Impact

The Impact of Gavi on Vaccination Rates: Regression Discontinuity Evidence

2015 ◽  
Author(s):  
Sarah Dykstra ◽  
Amanda L. Glassman ◽  
Charles Kenny ◽  
Justin Sandefur
Keyword(s):  
Regression Discontinuity ◽  
Vaccination Rates ◽  
The Impact

scholarly journals Effectiveness of a Power Factor Correction Policy in Improving the Energy Efficiency of Large-Scale Electricity Users in Ghana

Energies ◽  
2019 ◽  
Vol 12 (13) ◽  
pp. 2582 ◽  
Author(s):  
Samuel Lotsu ◽  
Yuichiro Yoshida ◽  
Katsufumi Fukuda ◽  
Bing He
Keyword(s):  
Energy Efficiency ◽  
Power Factor ◽  
Large Scale ◽  
Regression Discontinuity ◽  
Power Factor Correction ◽  
Energy Crisis ◽  
Regression Discontinuity Design ◽  
The Government ◽  
Power Factor Improvement ◽  
The Impact

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.

scholarly journals A regression discontinuity analysis of the social distancing recommendations for older adults in Sweden during COVID-19

2021 ◽  
Author(s):  
Carl Bonander ◽  
Debora Stranges ◽  
Johanna Gustavsson ◽  
Matilda Almgren ◽  
Malin Inghammar ◽  
...  
Keyword(s):  
Older Adults ◽  
Regression Discontinuity ◽  
Model Specification ◽  
Regression Discontinuity Design ◽  
Sharp Drop ◽  
Social Distancing ◽  
Disease Outcomes ◽  
The Social ◽  
National Register Data ◽  
The Impact

Objectives: To study the impact of non-mandatory, age-specific social distancing recommendations for older adults (70+ years) in Sweden on isolation behaviors and disease outcomes during the first wave of the COVID-19 pandemic. Methods: Our study relies on self-reported isolation data from COVID Symptom Study Sweden (n = 96,053) and national register data on COVID-19 hospitalizations, deaths, and confirmed cases. We use a regression discontinuity design to account for confounding factors, exploiting the fact that exposure to the recommendation was a discontinuous function of age. Results: By comparing individuals just above to those just below the age limit for the policy, our analyses revealed a sharp drop in the weekly number of visits to crowded places at the 70-year-threshold (-13%). Severe COVID-19 cases (hospitalizations or deaths) also dropped abruptly by 16% at the 70-year-threshold. Our data suggest that the age-specific recommendations prevented approximately 1,800 to 2,700 severe COVID-19 cases, depending on model specification. Conclusion: The non-mandatory, age-specific recommendations helped control the COVID-19 pandemic in Sweden.

scholarly journals Estimating the Impact of Air Pollution on Inbound Tourism in China: An Analysis Based on Regression Discontinuity Design

2019 ◽  
Vol 11 (6) ◽  
pp. 1682 ◽  
Author(s):  
Daxin Dong ◽  
Xiaowei Xu ◽  
Yat Wong
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Regression Discontinuity ◽  
Tourism Development ◽  
Tourism Industry ◽  
Regression Discontinuity Design ◽  
Reverse Causality ◽  
Chinese Cities ◽  
Inbound Tourism ◽  
The Impact

Prior studies have suggested the existence of a reverse causality relationship between air quality and tourism development: while air quality influences tourism, dynamic segments of the tourism industry (e.g., cruising, airline, foodservice) have impacts on air quality. This reverse causality hinders a precise estimate on the effect of air pollution on tourism development within a conventional econometric framework, since the variable of air pollution is endogenous. This study estimates the impact of air pollution on the inbound tourism industry in China, by controlling for endogeneity based on a regression discontinuity design (RDD). The estimate is derived from a quasi-experiment generated by China’s Huai River Policy, which subsidizes coal for winter heating in northern Chinese cities. By analyzing data from 274 Chinese cities during the period 2009–2012, it is found that air pollution significantly reduces the international inbound tourism: an increase of PM 10 (particulate matter smaller than 10 μ m) by 0.1 mg/m 3 will cause a decline in the tourism receipts-to-local gross domestic product (GDP) ratio by 0.45 percentage points. This study also highlights the importance of controlling for endogeneity, since the detrimental impact of air pollution would otherwise be considerably underestimated. This study further demonstrates that, although air pollution is positively correlated with the average expenditure of each tourist, it substantially depresses the number of inbound tourists. The results imply that air quality could potentially influence inbound tourists’ city destination choices. However, it is interesting to note that travelers in air polluted cities in China tend to spend more money.

scholarly journals The malleability of intelligence: the effects of schooling, genetic factors, socioeconomic status, and their interplay in children.

2021 ◽  
Author(s):  
Nicholas Judd ◽  
Bruno Sauce ◽  
Torkel Klingberg
Keyword(s):  
Socioeconomic Status ◽  
Working Memory ◽  
Genetic Factors ◽  
Fluid Intelligence ◽  
Regression Discontinuity ◽  
Regression Discontinuity Design ◽  
Quasi Experimental ◽  
Independent Effects ◽  
Main Effects ◽  
The Impact

Schooling, socioeconomic status (SES), and genetics all play large roles in intelligence differences. However, it is unclear to what extent their contributions are unique and if they interact. Here we used a multitrait polygenic score for cognition (cog-PGS) with a quasi-experimental regression discontinuity design to isolate how months of schooling relate to intelligence in 7,853 children (aged 9-11). We found large, independent effects of schooling, cog-PGS, and SES on working memory, crystallized (cIQ), and fluid intelligence (fIQ). Intriguingly, we found evidence for gene-by-environment interplay between cog-PGS and SES for cIQ, and a trend in the same direction for fIQ. This interaction was negative meaning that the intelligence of the highest SES children was the least affected by genetic differences, while the lowest SES children were most affected by genetic variability. Schooling showed no interaction with cog-PGS or SES for the three intelligence domains tested. While schooling had strong main effects on intelligence, it did not lessen, nor widen the impact of these preexisting SES or genetic factors.

scholarly journals Effectiveness of pre-operative anaemia screening and increased Tranexamic acid dose on outcomes following unilateral primary, elective total hip or knee replacement: a statistical analysis plan for an interrupted time series and regression discontinuity study

F1000Research ◽  
2020 ◽  
Vol 9 ◽  
pp. 224
Author(s):  
Ashley B. Scrimshire ◽  
Caroline Fairhurst ◽  
Catriona McDaid ◽  
David J. Torgerson
Keyword(s):  
Time Series ◽  
Statistical Analysis ◽  
Blood Transfusion ◽  
Knee Replacement ◽  
Regression Discontinuity ◽  
Interrupted Time Series ◽  
Statistical Analysis Plan ◽  
Study Designs ◽  
The Impact ◽  
Perioperative Blood Transfusion

Perioperative blood transfusion is associated with poorer postoperative outcomes following hip and knee replacement surgery. Evidence for the effectiveness of some measures aimed at reducing blood transfusions in this setting are limited and often rely on weak pre-post study designs. Quasi-experimental study designs such as interrupted time series (ITS) and regression discontinuity design (RDD) address many of the weaknesses of the pre-post study design. In addition, a priori publication of statistical analysis plans for such studies increases their transparency and likely validity, as readers are able to distinguish between pre-planned and exploratory analyses. As such, this article, written prospective of any analysis, provides the statistical analysis plan for an ITS and RDD study based on a data set of 20,772 primary elective hip and knee replacement patients in a single English NHS Trust. The primary aim is to evaluate the impact of a preoperative anaemia optimisation service on perioperative blood transfusion (within 7 days of surgery) using both ITS and RDD methods. A secondary aim is to evaluate the impact of a policy of increased tranexamic acid dose given at the time of surgery, using ITS methods.

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