Barbara Pacini

655 total citations
26 papers, 447 citations indexed

About

Barbara Pacini is a scholar working on Statistics and Probability, Economics and Econometrics and Organic Chemistry. According to data from OpenAlex, Barbara Pacini has authored 26 papers receiving a total of 447 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Statistics and Probability, 5 papers in Economics and Econometrics and 3 papers in Organic Chemistry. Recurrent topics in Barbara Pacini's work include Advanced Causal Inference Techniques (11 papers), Statistical Methods and Bayesian Inference (9 papers) and Statistical Methods and Inference (8 papers). Barbara Pacini is often cited by papers focused on Advanced Causal Inference Techniques (11 papers), Statistical Methods and Bayesian Inference (9 papers) and Statistical Methods and Inference (8 papers). Barbara Pacini collaborates with scholars based in Italy, Switzerland and Sweden. Barbara Pacini's co-authors include Fabrizia Mealli, Giampiero M. Gallo, Giuliano Giambastiani, Giovanni Poli, Donald B. Rubin, Paolo Frumento, Marina Porcelloni, Lucio Picci, Stefania Colarusso and Uwe Koch and has published in prestigious journals such as Journal of the American Statistical Association, Biometrics and Journal of Medicinal Chemistry.

In The Last Decade

Barbara Pacini

24 papers receiving 416 citations

Peers

Barbara Pacini

FINAN

Hikaru Hasegawa Japan

Jon Stewart United Kingdom

Bryan Campbell Canada

Burcu Aydın United States

Gesa Witt Germany

Yannis Bilias United States

Chad Kendall United States

Whitney L. Johnson United States

Janusz Miśkiewicz Poland

Josep Vives Spain

Hikaru Hasegawa Japan

Barbara Pacini

60 ×0.4

54 ×0.4

158 ×1.4

18 ×0.2

FINAN

51 ×0.9

Citations per year, relative to Barbara Pacini Barbara Pacini (= 1×) peers Hikaru Hasegawa

Countries citing papers authored by Barbara Pacini

Since Specialization

Citations

This map shows the geographic impact of Barbara Pacini's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Barbara Pacini with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Barbara Pacini more than expected).

Fields of papers citing papers by Barbara Pacini

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Barbara Pacini. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Barbara Pacini. The network helps show where Barbara Pacini may publish in the future.

Co-authorship network of co-authors of Barbara Pacini

This figure shows the co-authorship network connecting the top 25 collaborators of Barbara Pacini. A scholar is included among the top collaborators of Barbara Pacini based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Barbara Pacini. Barbara Pacini is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Pacini, Barbara, et al.. (2024). The Impact of Fines on Deceptive Advertising: Evidence from Italy. Journal of Consumer Policy. 48(1). 23–50. 1 indexed citations

Ranjbar, Setareh, Nicola Salvati, & Barbara Pacini. (2023). Estimating heterogeneous causal effects in observational studies using small area predictors. Computational Statistics & Data Analysis. 184. 107742–107742. 1 indexed citations

Chambers, Ray, Setareh Ranjbar, Nicola Salvati, & Barbara Pacini. (2022). Weighting, Informativeness and Causal Inference, with an Application to Rainfall Enhancement. Journal of the Royal Statistical Society Series A (Statistics in Society). 185(4). 1584–1612. 1 indexed citations

Pacini, Barbara, et al.. (2021). Technological transition and market structure: The switch-off and local television in Italy. CINECA IRIS Institutial research information system (University of Pisa). 13(2). 297–316. 2 indexed citations

Frumento, Paolo, Fabrizia Mealli, Barbara Pacini, & Donald B. Rubin. (2015). The fragility of standard inferential approaches in principal stratification models relative to direct likelihood approaches. Statistical Analysis and Data Mining The ASA Data Science Journal. 9(1). 58–70. 5 indexed citations

Mattei, Alessandra, Fabrizia Mealli, & Barbara Pacini. (2014). Identification of causal effects in the presence of nonignorable missing outcome values. Biometrics. 70(2). 278–288. 14 indexed citations

Mealli, Fabrizia & Barbara Pacini. (2013). Using Secondary Outcomes to Sharpen Inference in Randomized Experiments With Noncompliance. Journal of the American Statistical Association. 108(503). 1120–1131. 51 indexed citations

Gallo, Giampiero M. & Barbara Pacini. (2013). Indicatori tecnici e volatilità di serie storiche finanziarie. Università degli Studi di Bologna. 58(3). 457–480.

Mealli, Fabrizia, et al.. (2012). Estimation of Causal Effects in Latent Strata with an Encouragement for Response. Communication in Statistics- Theory and Methods. 41(16-17). 3150–3161. 1 indexed citations

10.

Frumento, Paolo, Fabrizia Mealli, Barbara Pacini, & Donald B. Rubin. (2012). Evaluating the Effect of Training on Wages in the Presence of Noncompliance, Nonemployment, and Missing Outcome Data. Journal of the American Statistical Association. 107(498). 450–466. 61 indexed citations

11.

Mealli, Fabrizia & Barbara Pacini. (2008). Comparing principal stratification and selection models in parametric causal inference with nonignorable missingness. Computational Statistics & Data Analysis. 53(2). 507–516. 12 indexed citations

12.

Mealli, Fabrizia & Barbara Pacini. (2008). Exploiting instrumental variables in causal Inference with nonignorable outcome nonresponse using principal stratification. 2 indexed citations

13.

Mealli, Fabrizia & Barbara Pacini. (2007). Finding alternative sources of identification in generalized selection models using principal stratification. Presentato a International Conference on Causal Inference, Uppsala.. 1 indexed citations

14.

Koch, Uwe, Savina Malancona, Stefania Colarusso, et al.. (2006). 2-(2-Thienyl)-5,6-dihydroxy-4-carboxypyrimidines as Inhibitors of the Hepatitis C Virus NS5B Polymerase: Discovery, SAR, Modeling, and Mutagenesis. Journal of Medicinal Chemistry. 49(5). 1693–1705. 72 indexed citations

15.

Lemaire, Sébastien, Guillaume Prestat, Giuliano Giambastiani, et al.. (2003). Palladium-catalyzed pseudo-domino cyclizations. Journal of Organometallic Chemistry. 687(2). 291–300. 19 indexed citations

16.

Pacini, Barbara & Lucio Picci. (2001). Introduzione alla statistica. 11 indexed citations

17.

Gallo, Giampiero M. & Barbara Pacini. (2000). The effects of trading activity on market volatility. European Journal of Finance. 6(2). 163–175. 88 indexed citations

18.

Giambastiani, Giuliano, Barbara Pacini, Marina Porcelloni, & Giovanni Poli. (1998). A New Palladium-Catalyzed Intramolecular Allylation to Pyrrolidin-2-ones¹. The Journal of Organic Chemistry. 63(3). 804–807. 42 indexed citations

19.

Gallo, Giampiero M. & Barbara Pacini. (1998). Early News is Good News: The Effects of Market Opening on Market Volatility. Studies in Nonlinear Dynamics and Econometrics. 2(4). 11 indexed citations

20.

Pacini, Barbara, Eric G. Brown, Paola Martelli, et al.. (1993). Adenylyl cyclase activity in roots of Pisum sativum. Phytochemistry. 34(4). 899–903. 17 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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