scholarly journals HOW TO MAKE A PIE: REPRODUCIBLE RESEARCH FOR EMPIRICAL ECONOMICS AND ECONOMETRICS

2020 ◽  
Vol 34 (5) ◽  
pp. 1134-1169
Author(s):  
Valérie Orozco ◽  
Christophe Bontemps ◽  
Elise Maigné ◽  
Virginie Piguet ◽  
Annie Hofstetter ◽  
...  
Keyword(s):  
Reproducible Research ◽  
Empirical Economics

scholarly journals Do economics journals foster replicable research?

2017 ◽  
Author(s):  
Sven Vlaeminck ◽  
Ralf Toepfer
Keyword(s):  
Compliance Rate ◽  
Data Availability ◽  
Economic Research ◽  
Reproducible Research ◽  
Necessary Condition ◽  
Scientific Integrity ◽  
Empirical Economics ◽  
Replication Studies ◽  
Data Archives ◽  
Data Policy

Watch the VIDEO here.Replications are pivotal for the credibility of empirical economics. It is widely recognized in economics that replication studies are a necessary condition for scientific integrity. Alarmingly, several studies indicate that a significant share of empirical economics research cannot be replicated. At the same time, the awareness among researchers, that empirically-based research is often based on shaky grounds, has increased in the last years. It becomes more and more evident that there is a need for more replications in economics to regain trust and credibility in empirical economics research.Though established scholarly journals have adopted replication policies in recent years, replication activities only slightly increased. Against this background our talk investigates if and how journals in economics foster replicable research. For this purpose, we will address two aspects:Journals’ data policies and their effective enforcement in economics: The first part of our talk presents the findings of a new study, in which we evaluated almost 600 articles published in 37 well-regarded journals with a data availability policy. First, we highlight the share of articles that fall under the data policy. Subsequently, the talk contrasts for how many of these data-based articles replication files were available in journals’ data archives and/or the supplemental information section of the article. Moreover, the exact requirements of journals’ data policies have been contrasted to the replication files available on journals’ web pages (respectively in their data archives).We developed a ‘compliance rate’ for each journal in our study. The higher the compliance rate the more do journals enforce their data policy. In the first part of our talk, we also discuss the question whether voluntary data policies are effective in fostering replicable research. For this purpose, we compare the compliance rate of journals with a voluntary data policy to their mandatory counterparts.Journals as publication outlets for replication studies: Though researchers agree that replication studies are needed to regain trust and credibility in empirical economic research, replication activities only slightly increased in recent years.  One reason for that finding can be that in the current system replicating other people’s result does not progresses researcher’s career. Another reason is the paucity of publication outlets for such replication studies. In this part of our talk we also discuss whether established journals should implement replication sections or whether a journal which is entirely dedicated to replication, would be a better way to foster the publication of replication studies. As a showcase we will briefly introduce the newly founded “International Journal for Re-Views in Empirical Economics” (IREE).To conclude, we sketch the current and potential future developments in economics when it comes to reproducible research. 

Grid Enabling Empirical Economics: A Microdata Application

2007 ◽  
Vol 30 (4) ◽  
pp. 349-370 ◽  
Author(s):  
Simon Peters ◽  
Ken Clark ◽  
Pascal Ekin ◽  
Anja Le Blanc ◽  
Stephen Pickles
Keyword(s):  
Empirical Economics

scholarly journals UWB-gestures, a public dataset of dynamic hand gestures acquired using impulse radar sensors

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Shahzad Ahmed ◽  
Dingyang Wang ◽  
Junyoung Park ◽  
Sung Ho Cho
Keyword(s):  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Ultra Wideband ◽  
Reproducible Research ◽  
Hand Gesture ◽  
Hand Gestures ◽  
Radar Sensors ◽  
The Past ◽  
Human Volunteers ◽  
Public Dataset

AbstractIn the past few decades, deep learning algorithms have become more prevalent for signal detection and classification. To design machine learning algorithms, however, an adequate dataset is required. Motivated by the existence of several open-source camera-based hand gesture datasets, this descriptor presents UWB-Gestures, the first public dataset of twelve dynamic hand gestures acquired with ultra-wideband (UWB) impulse radars. The dataset contains a total of 9,600 samples gathered from eight different human volunteers. UWB-Gestures eliminates the need to employ UWB radar hardware to train and test the algorithm. Additionally, the dataset can provide a competitive environment for the research community to compare the accuracy of different hand gesture recognition (HGR) algorithms, enabling the provision of reproducible research results in the field of HGR through UWB radars. Three radars were placed at three different locations to acquire the data, and the respective data were saved independently for flexibility.

scholarly journals Towards Reproducible Research of Event Detection Techniques for Twitter

2019 ◽  
Author(s):  
Andreas Weiler ◽  
Harry Schilling ◽  
Lukas Kircher ◽  
Michael Grossniklaus
Keyword(s):  
Event Detection ◽  
Reproducible Research ◽  
Detection Techniques

Reproducible research: Geophysics papers of the future — Introduction

Geophysics ◽  
2017 ◽  
Vol 82 (6) ◽  
pp. WBi-WBii ◽  
Author(s):  
Filippo Broggini ◽  
Joseph Dellinger ◽  
Sergey Fomel ◽  
Yang Liu
Keyword(s):  
Reproducible Research ◽  
The Future

The New Statistics with R

2021 ◽  
Author(s):  
Andy Hector
Keyword(s):  
Linear Model ◽  
Evolutionary Biology ◽  
Environmental Science ◽  
Research Training ◽  
Model Analysis ◽  
Scientific Data ◽  
Information Criteria ◽  
Reproducible Research ◽  
Data Sets ◽  
R Programming

Statistics is a fundamental component of the scientific toolbox, but learning the basics of this area of mathematics is one of the most challenging parts of a research training. This book gives an up-to-date introduction to the classical techniques and modern extensions of linear-model analysis—one of the most useful approaches in the analysis of scientific data in the life and environmental sciences. The book emphasizes an estimation-based approach that takes account of recent criticisms of overuse of probability values and introduces the alternative approach using information criteria. The book is based on the use of the open-source R programming language for statistics and graphics, which is rapidly becoming the lingua franca in many areas of science. This second edition adds new chapters, including one discussing some of the complexities of linear-model analysis and another introducing reproducible research documents using the R Markdown package. Statistics is introduced through worked analyses performed in R using interesting data sets from ecology, evolutionary biology, and environmental science. The data sets and R scripts are available as supporting material.

Roundtable: Challenges in repeatable experiments and reproducible research in data science

2021 ◽  
Vol 13 (2) ◽  
pp. 100-108
Author(s):  
K.V. Vorontsov ◽  
V.I. Iglovikov ◽  
V.V. Strijov ◽  
A.E. Ustuzhanin ◽  
A.S. Khritankov
Keyword(s):  
Data Science ◽  
Reproducible Research
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