1,720,976 research outputs found
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Essays in program evaluation
Full text linkThis dissertation consists of three chapters on program evaluation, or the estimation of treatment effects.
The first chapter discusses bootstrap methods for inference on matching estimators, a popular approach to program evaluation. Abadie & Imbens (2008) showed that the standard non-parametric bootstrap fails to provide valid inference with matching estimators, and conjectured that a wild bootstrap could solve the problem. Otsu & Rai (2017) confirmed this conjecture, providing a wild bootstrap procedure that is valid in general. Their bootstrap builds in a bias correction procedure that requires estimation of conditional mean functions, a procedure that is generally necessary for consistent matching estimation. However, this step also introduces a new source of estimation error, lessening the efficiency of the bootstrap. I show that even in a special case, when bias correction in the estimator is unnecessary, the conditional mean function estimation is a required element of any wild bootstrap for the matching estimator. This shows that the Otsu & Rai bootstrap cannot be modified to be more efficient even by leveraging much stronger assumptions. Simulations provide additional support for this conclusion.
The second chapter also deals with matching estimators. I consider the problem faced by a practitioner who wishes to use matching estimation to estimate a treatment effect - in particular, choosing from a large set of available matching procedures. I cast matching estimators as two-step procedures - a weight-generation step followed by a weighted difference in means - and derive weights that minimize mean-squared error (MSE) under certain conditions. Understanding why the optimal weights behave the way they do generates insights about which matching procedures are likely to minimize MSE, enabling practitioners to use their economic intuition, knowledge of the empirical context, and knowledge of the sampling process to choose an appropriate matching procedure. I develop a simple `augmented' matching procedure to illustrate, and through simulation confirm that the guidance I offer is correct.
In the final chapter, I apply my program evaluation expertise to a question in the economics of education - specifically, the effect of teacher gender on student test scores. Previous literature in this vein has focused on the estimation of average effects. By exploiting random assignment of students to teachers in a field experiment, I study heterogeneity in the impact of teacher gender on math and reading test outcomes for primary school students of differing ability. I find that assignment to a female teacher is generally positive for male students, while it has no significant effect for female students. In addition, I find very little heterogeneity in the effect of teacher gender along the ability axis, suggesting that average effect estimates from previous investigations do not mask significant heterogeneity. My results are consistent with differential teacher behavior based on gender stereotypes, and somewhat inconsistent with differential student behavior based on gender stereotypes.</p
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
The Federal Reserve System and the federal funds rate: evaluating the Fed's rate-targeting decisions through the use of Taylor-type monetary policy rules
Full text linkIn the U.S., monetary policy decisions are handled by our central bank, the Federal Reserve System. By targeting a desired interest rate level and using three main "tools" to adjust the money supply in order to achieve this rate, the Federal Reserve guides our economy in order to maintain its long-term goals of price stability and sustainable economic growth. To help the public better understand the actions of the Federal Reserve, economist John B. Taylor devised a monetary policy rule in 1993 that is both simple and reasonably accurate. In the decade since his pivotal rule, numerous researchers have attempted to challenge, expand, or redefine this equation to make it more accurate and useful. My paper reexamines two rules, Taylor's original rule as well as another expanded rule, by using a larger set of observations. I also present and test additional models that build on these two to determine if there are other important factors the Fed takes into account when deciding on the appropriate targeted federal funds rate. In the two models that I present, it appears that when inflation is above the target level, the Fed responds to changes in inflation and GDP much more aggressively. On the other hand, when inflation is at or below the objective, the Fed follows a policy of interest rate smoothing.</p
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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