Relevant bibliographies by topics / Association rule

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Association rule'

Author: Grafiati
Published: 4 June 2021
Last updated: 11 June 2025

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Journal articles on the topic "Association rule"

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Thomas, Binu, and G. Raju. "A Novel Web Classification Algorithm Using Fuzzy Weighted Association Rules." ISRN Artificial Intelligence 2013 (December 19, 2013): 1–10. http://dx.doi.org/10.1155/2013/316913.

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In associative classification method, the rules generated from association rule mining are converted into classification rules. The concept of association rule mining can be extended in web mining environment to find associations between web pages visited together by the internet users in their browsing sessions. The weighted fuzzy association rule mining techniques are capable of finding natural associations between items by considering the significance of their presence in a transaction. The significance of an item in a transaction is usually referred as the weight of an item in the transaction and finding associations between such weighted items is called fuzzy weighted association rule mining. In this paper, we are presenting a novel web classification algorithm using the principles of fuzzy association rule mining to classify the web pages into different web categories, depending on the manner in which they appear in user sessions. The results are finally represented in the form of classification rules and these rules are compared with the result generated using famous Boolean Apriori association rule mining algorithm.
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Ali, Nzar Abdulqader. "Finding minimum confidence threshold to avoid derived rules in association rule minin." Journal of Zankoy Sulaimani - Part A 17, no. 4 (2015): 271–78. http://dx.doi.org/10.17656/jzs.10443.

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Taniar, David, Wenny Rahayu, Vincent Lee, and Olena Daly. "Exception rules in association rule mining." Applied Mathematics and Computation 205, no. 2 (2008): 735–50. http://dx.doi.org/10.1016/j.amc.2008.05.020.

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Khurana, Garvit. "Association Rule Hiding using Hash Tree." International Journal of Trend in Scientific Research and Development Volume-3, Issue-3 (2019): 787–89. http://dx.doi.org/10.31142/ijtsrd23037.

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Sasikala, D., and K. Premalatha. "Application of Class Based Association Rule Pruning to Generate Optimal Association Rules in Healthcare." Journal of Medical Imaging and Health Informatics 11, no. 11 (2021): 2859–61. http://dx.doi.org/10.1166/jmihi.2021.3876.

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The association rule mining approach produces uninteresting association rules. When the set of association rules become large, it becomes less interesting to the user. In order to pick interesting association rules among peak volumes of found association rules, it is critical to aid the decision-maker with an efficient post-processing phase. Theymotivate the need for association analysis performance. Practically it is an overhead to analyze the large set of association rules. In this work, association rule pruning technique called Class Based Association Rule Pruning (CBARP). This pruning techniques is proposed to prune the weak association rules of the healthcare system. The results are compared with Semantic Tree Based Association Rule Mining (STAR) technique and it demonstrate that the CBARP method outperforms other methods for the given support values.
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Tata, Gayathri, and Durga N. "Privacy Preserving Approaches for High Dimensional Data." International Journal of Trend in Scientific Research and Development 1, no. 5 (2017): 1120–25. https://doi.org/10.31142/ijtsrd2430.

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This paper proposes a model for hiding sensitive association rules for Privacy preserving in high dimensional data. Privacy preservation is a big challenge in data mining. The protection of sensitive information becomes a critical issue when releasing data to outside parties. Association rule mining could be very useful in such situations. It could be used to identify all the possible ways by which 'non confidential' data can reveal 'confidential' data, which is commonly known as 'inference problem'. This issue is solved using Association Rule Hiding ARH techniques in Privacy Preserving Data Mining PPDM . Association rule hiding aims to conceal these association rules so that no sensitive information can be mined from the database. Tata Gayathri | N Durga "Privacy Preserving Approaches for High Dimensional Data" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-1 | Issue-5 , August 2017, URL: https://www.ijtsrd.com/papers/ijtsrd2430.pdf
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XU, YUE, and YUEFENG LI. "MINING NON-REDUNDANT ASSOCIATION RULES BASED ON CONCISE BASES." International Journal of Pattern Recognition and Artificial Intelligence 21, no. 04 (2007): 659–75. http://dx.doi.org/10.1142/s0218001407005600.

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Association rule mining has many achievements in the area of knowledge discovery. However, the quality of the extracted association rules has not drawn adequate attention from researchers in data mining community. One big concern with the quality of association rule mining is the size of the extracted rule set. As a matter of fact, very often tens of thousands of association rules are extracted among which many are redundant, thus useless. In this paper, we first analyze the redundancy problem in association rules and then propose a reliable exact association rule basis from which more concise nonredundant rules can be extracted. We prove that the redundancy eliminated using the proposed reliable association rule basis does not reduce the belief to the extracted rules. Moreover, this paper proposes a level wise approach for efficiently extracting closed itemsets and minimal generators — a key issue in closure based association rule mining.
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Prakash, R. Vijaya, S. S. V. N. Sarma, and M. Sheshikala. "Generating Non-redundant Multilevel Association Rules Using Min-max Exact Rules." International Journal of Electrical and Computer Engineering (IJECE) 8, no. 6 (2018): 4568–76. https://doi.org/10.11591/ijece.v8i6.pp4568-4576.

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Association Rule mining plays an important role in the discovery of knowledge and information. Association Rule mining discovers huge number of rules for any dataset for different support and confidence values, among this many of them are redundant, especially in the case of multi-level datasets. Mining non-redundant Association Rules in multi-level dataset is a big concern in field of Data mining. In this paper, we present a definition for redundancy and a concise representation called Reliable Exact basis for representing non-redundant Association Rules from multi-level datasets. The given non-redundant Association Rules are loss less representation for any datasets.
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KORPIPÄÄ, PANU. "Visualizing constraint-based temporal association rules." Artificial Intelligence for Engineering Design, Analysis and Manufacturing 15, no. 5 (2001): 401–10. http://dx.doi.org/10.1017/s0890060401155034.

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When dealing with time continuous processes, the discovered association rules may change significantly over time. This often reflects a change in the process as well. Therefore, two questions arise: What kind of deviation occurs in the association rules over time, and how could these temporal rules be presented efficiently? To address this problem of representation, we propose a method of visualizing temporal association rules in a virtual model with interactive exploration. The presentation form is a three-dimensional correlation matrix, and the visualization methods used are brushing and glyphs. Interactive functions used for displaying rule attributes and exploring temporal rules are implemented by utilizing Virtual Reality Modeling Language v2 mechanisms. Furthermore, to give a direction of rule potential for the user, the rule statistical interestingness is evaluated on the basis of combining weighted characteristics of rule and rule matrix. A constraint-based association rule mining tool which creates the virtual model as an output is presented, including the most relevant experiences from the development of the tool. The applicability of the overall approach has been verified by using the developed tool for data mining on a hot strip mill of a steel plant.
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Shimada, Kaoru, Kotaro Hirasawa, and Jinglu Hu. "Genetic Network Programming with Acquisition Mechanisms of Association Rules." Journal of Advanced Computational Intelligence and Intelligent Informatics 10, no. 1 (2006): 102–11. http://dx.doi.org/10.20965/jaciii.2006.p0102.

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A method of association rule mining using Genetic Network Programming (GNP) is proposed to improve the performance of association rule extraction. The proposed mechanisms can calculate measurements of association rules directly using GNP, and measure the significance of the association via the chi-squared test. Users can define the conditions of importance of association rules flexibly, which include the chi-squared value and the number of attributes in a rule. The proposed system evolves itself by an evolutionary method and obtains candidates of association rules by genetic operations. Extracted association rules are stored in a pool all together through generations and reflected in genetic operators as acquired information. Besides, our method can contain negation of attributes in association rules and suit association rule mining from dense databases. In this paper, we describe an extended algorithm capable of finding important association rules using GNP with sophisticated rule acquisition mechanisms and present some experimental results.
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Dissertations / Theses on the topic "Association rule"

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Palanisamy, Senthil Kumar. "Association rule based classification." Link to electronic thesis, 2006. http://www.wpi.edu/Pubs/ETD/Available/etd-050306-131517/.

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Thesis (M.S.)--Worcester Polytechnic Institute.<br>Keywords: Itemset Pruning, Association Rules, Adaptive Minimal Support, Associative Classification, Classification. Includes bibliographical references (p.70-74).
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Wong, Wai-kit. "Security in association rule mining." Click to view the E-thesis via HKUTO, 2007. http://sunzi.lib.hku.hk/HKUTO/record/B39558903.

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Wong, Wai-kit, and 王偉傑. "Security in association rule mining." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2007. http://hub.hku.hk/bib/B39558903.

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REN, XIAOHUI. "COMPARING QUANTITATIVE ASSOCIATION RULE METHODS." University of Cincinnati / OhioLINK, 2004. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1089133333.

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Qing, Yang. "Pruning and summarizing discovered time series association rules." Thesis, Mittuniversitetet, Avdelningen för informationssystem och -teknologi, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-31828.

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Sensors are widely used in all aspects of our daily life including factories, hospitals and even our homes. Discovering time series association rules from sensor data can reveal the potential relationship between different sensors which can be used in many applications. However, the time series association rule mining algorithms usually produce rules much more than expected. It’s hardly to under-stand, present or make use of the rules. So we need to prune and summarize the huge amount of rules. In this paper, a two-step pruning method is proposed to reduce both the number and redundancy in the large set of time series rules. Be-sides, we put forward the BIGBAR summarizing method to summarize the rules and present the results intuitively.
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Rantzau, Ralf. "Extended concepts for association rule discovery." [S.l. : s.n.], 1997. http://www.bsz-bw.de/cgi-bin/xvms.cgi?SWB8937694.

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Zhang, Ya Klein Cerry M. "Association rule mining in cooperative research." Diss., Columbia, Mo. : University of Missouri--Columbia, 2009. http://hdl.handle.net/10355/6540.

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The entire thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file; a non-technical public abstract appears in the public.pdf file. Title from PDF of title page (University of Missouri--Columbia, viewed January 26, 2010). Thesis advisor: Dr. Cerry M. Klein. Includes bibliographical references.
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Icev, Aleksandar. "DARM distance-based association rule mining." Link to electronic thesis, 2003. http://www.wpi.edu/Pubs/ETD/Available/etd-0506103-132405.

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HajYasien, Ahmed. "Preserving Privacy in Association Rule Mining." Thesis, Griffith University, 2007. http://hdl.handle.net/10072/365286.

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With the development and penetration of data mining within different fields and disciplines, security and privacy concerns have emerged. Data mining technology which reveals patterns in large databases could compromise the information that an individual or an organization regards as private. The aim of privacy-preserving data mining is to find the right balance between maximizing analysis results (that are useful for the common good) and keeping the inferences that disclose private information about organizations or individuals at a minimum. In this thesis we present a new classification for privacy preserving data mining problems, we propose a new heuristic algorithm called the QIBC algorithm that improves the privacy of sensitive knowledge (as itemsets) by blocking more inference channels. We demonstrate the efficiency of the algorithm, we propose two techniques (item count and increasing cardinality) based on item-restriction that hide sensitive itemsets (and we perform experiments to compare the two techniques), we propose an efficient protocol that allows parties to share data in a private way with no restrictions and without loss of accuracy (and we demonstrate the efficiency of the protocol), and we review the literature of software engineering related to the associationrule mining domain and we suggest a list of considerations to achieve better privacy on software.<br>Thesis (PhD Doctorate)<br>Doctor of Philosophy (PhD)<br>School of Information and Communication Technology<br>Faculty of Engineering and Information Technology<br>Full Text
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Marinica, Claudia. "Association Rule Interactive Post-processing using Rule Schemas and Ontologies - ARIPSO." Phd thesis, Université de Nantes, 2010. http://tel.archives-ouvertes.fr/tel-00912580.

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This thesis is concerned with the merging of two active research domains: Knowledge Discovery in Databases (KDD), more precisely the Association Rule Mining technique, and Knowledge Engineering (KE) with a main interest in knowledge representation languages developed around the Semantic Web. In Data Mining, the usefulness of association rule technique is strongly limited by the huge amount and the low quality of delivered rules. Experiments show that rules become almost impossible to use when their number exceeds 100. At the same time, nuggets are often represented by those rare (low support) unexpected association rules which are surprising to the user. Unfortunately, the lower the support is, the larger the volume of rules becomes. Thus, it is crucial to help the decision maker with an efficient technique to reduce the number of rules. To overcome this drawback, several methods have been proposed in the literature such as itemset concise representations, redundancy reduction, filtering, ranking and post-processing. Even though rule interestingness strongly depends on user knowledge and goals, most of the existing methods are generally based on data structure. For instance, if the user looks for unexpected rules, all the already known rules should be pruned. Or, if the user wants to focus on specific family of rules, only this subset of rules should be selected. In this context, we address two main issues: the integration of user knowledge in the discovery process and the interactivity with the user. The first issue requires defining an adapted formalism to express user knowledge with accuracy and flexibility such as ontologies in the Semantic Web. Second, the interactivity with the user allows a more iterative mining process where the user can successively test different hypotheses or preferences and focus on interesting rules. The main contributions of this work can be summarized as follows: (i) A model to represent user knowledge. First, we propose a new rule-like formalism, called Rule Schema, which allows the user to define his/her expectations regarding the rules through ontology concepts. Second, ontologies allow the user to express his/her domain knowledge by means of a high semantic model. Last, the user can choose among a set of Operators for interactive processing the one to be applied over each Rule Schema (i.e. pruning, conforming, unexpectedness, . . . ). (ii) A new post-processing approach, called ARIPSO (Association Rule Interactive Post-processing using rule Schemas and Ontologies), which helps the user to reduce the volume of the discovered rules and to improve their quality. It consists in an interactive process integrating user knowledge and expectations by means of the proposed model. At each step of ARIPSO, the interactive loop allows the user to change the provided information and to reiterate the post-processing phase which produces new results. (iii) The implementation in post-processing of the proposed approach. The developed tool is complete and operational, and it implements all the functionalities described in the approach. Also, it makes the connection between different elements like the set of rules and rule schemas stored in PMML/XML files, and the ontologies stored in OWL files and inferred by the Pellet reasoner. (iv) An adapted implementation without post-processing, called ARLIUS (Association Rule Local mining Interactive Using rule Schemas), consisting in an interactive local mining process guided by the user. It allows the user to focus on interesting rules without the necessity to extract all of them, and without minimum support limit. In this way, the user may explore the rule space incrementally, a small amount at each step, starting from his/her own expectations and discovering their related rules. (v) The experimental study analyzing the approach efficiency and the discovered rule quality. For this purpose, we used a real-life and large questionnaire database concerning customer satisfaction. For ARIPSO, the experimentation was carried out in complete cooperation with the domain expert. For different scenarios, from an input set of nearly 400 thousand association rules, ARIPSO filtered between 3 and 200 rules validated by the expert. Clearly, ARIPSO allows the user to significantly and efficiently reduce the input rule set. For ARLIUS, we experimented different scenarios over the same questionnaire database and we obtained reduced sets of rules (less than 100) with very low support.
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Books on the topic "Association rule"

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Zhang, Chengqi, and Shichao Zhang, eds. Association Rule Mining. Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-46027-6.

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Dass, Rajanish. Classification using association rules. Indian Institute of Management, 2008.

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Gkoulalas-Divanis, Aris, and Vassilios S. Verykios. Association Rule Hiding for Data Mining. Springer US, 2010. http://dx.doi.org/10.1007/978-1-4419-6569-1.

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Gkoulalas-Divanis, Aris. Association rule hiding for data mining. Springer, 2010.

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Harte, Michael. Sectarianism and the G.A.A. in the contect of Rule 21. The Author], 1999.

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1930-, Doyle R. F., and MinDak Tug of War Association., eds. Official MinDak Tug of War Association rule book/training guide. The Association, 1989.

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Kazienko, Przemysław. Associations: Discovery, analysis and applications. Oficyna Wydawnicza Politechniki Wrocławskiej, 2008.

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Colorado. Office of State Auditor. Performance audit, Modified Rule of 75 Early Retirement Program. State of Colorado, Office of the State Auditor, 1988.

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1978-, Koh Yun Sing, and Rountree Nathan 1974-, eds. Rare association rule mining and knowledge discovery: Technologies for infrequent and critical event detection. Information Science Reference, 2010.

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Kim, Chung-sŏp. The Korean Paekjǒng under Japanese rule: The quest for equality and human rights. Routledge, 2003.

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Book chapters on the topic "Association rule"

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Kakas, Antonis C., David Cohn, Sanjoy Dasgupta, et al. "Association Rule." In Encyclopedia of Machine Learning. Springer US, 2011. http://dx.doi.org/10.1007/978-0-387-30164-8_38.

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Fürnkranz, Johannes. "Association Rule." In Encyclopedia of Systems Biology. Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4419-9863-7_838.

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Toivonen, Hannu. "Association Rule." In Encyclopedia of Machine Learning and Data Science. Springer US, 2023. http://dx.doi.org/10.1007/978-1-4899-7502-7_13-1.

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Toivonen, Hannu. "Association Rule." In Encyclopedia of Machine Learning and Data Mining. Springer US, 2017. http://dx.doi.org/10.1007/978-1-4899-7687-1_38.

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Cleophas, Ton J., and Aeilko H. Zwinderman. "Association Rule Analysis." In Machine Learning in Medicine. Springer Netherlands, 2013. http://dx.doi.org/10.1007/978-94-007-6886-4_11.

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Liu, Zhen “Leo.” "Association Rule Learning." In Artificial Intelligence for Engineers. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-75953-6_13.

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Sarjon, Defit, and Noor Md Sap Mohd. "Association Rules Using Rough Set and Association Rule Methods." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-45683-x_27.

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Bramer, Max. "Association Rule Mining I." In Principles of Data Mining. Springer London, 2016. http://dx.doi.org/10.1007/978-1-4471-7307-6_16.

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Bramer, Max. "Association Rule Mining II." In Principles of Data Mining. Springer London, 2016. http://dx.doi.org/10.1007/978-1-4471-7307-6_17.

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Bramer, Max. "Association Rule Mining I." In Principles of Data Mining. Springer London, 2020. http://dx.doi.org/10.1007/978-1-4471-7493-6_16.

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Conference papers on the topic "Association rule"

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Tang, Xiaojuan, Song-Chun Zhu, Yitao Liang, and Muhan Zhang. "RulE: Knowledge Graph Reasoning with Rule Embedding." In Findings of the Association for Computational Linguistics ACL 2024. Association for Computational Linguistics, 2024. http://dx.doi.org/10.18653/v1/2024.findings-acl.256.

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Vineela, G., M. Alekhya, A. Jayanth, J. M. V. Lakshmi Harshitha, Venkatrama Phani Kumar S, and Venkata Krishna Kishore K. "An Experimental Analysis of Association Rule Mining Algorithms to Extract Strong and Interesting Association Rules." In 2024 Second International Conference on Advances in Information Technology (ICAIT). IEEE, 2024. http://dx.doi.org/10.1109/icait61638.2024.10690451.

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Kudriavtsev, Mikhail, Andrew McCarren, Hyowon Lee, and Marija Bezbradica. "Efficient Visualization of Association Rule Mining Using the Trie of Rules." In 16th International Conference on Knowledge Discovery and Information Retrieval. SCITEPRESS - Science and Technology Publications, 2024. http://dx.doi.org/10.5220/0012995500003838.

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Soni, Sunita, Jyothi Pillai, and O. P. Vyas. "An associative classifier using weighted association rule." In 2009 World Congress on Nature & Biologically Inspired Computing (NaBIC). IEEE, 2009. http://dx.doi.org/10.1109/nabic.2009.5393687.

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Baez-Monroy, Vicente O., and Simon O'Keefe. "An Associative Memory for Association Rule Mining." In 2007 International Joint Conference on Neural Networks. IEEE, 2007. http://dx.doi.org/10.1109/ijcnn.2007.4371304.

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Zhou, Ling, and Stephen Yau. "Association rule and quantitative association rule mining among infrequent items." In the 8th international workshop. ACM Press, 2007. http://dx.doi.org/10.1145/1341920.1341929.

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Olaru, Andrei, Claudia Marinica, and Fabrice Guillet. "Local mining of Association Rules with Rule Schemas." In 2009 IEEE Symposium on Computational Intelligence and Data Mining (CIDM). IEEE, 2009. http://dx.doi.org/10.1109/cidm.2009.4938638.

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Davis, Warren L., Peter Schwarz, and Evimaria Terzi. "Finding representative association rules from large rule collections." In Proceedings of the 2009 SIAM International Conference on Data Mining. Society for Industrial and Applied Mathematics, 2009. http://dx.doi.org/10.1137/1.9781611972795.45.

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Yang, Pu-Tai, Kai-Hao Yang, Ching-Chi Chen, and Shwu-Min Horng. "Subjective Association Rule Mining." In ICMLC 2018: 2018 10th International Conference on Machine Learning and Computing. ACM, 2018. http://dx.doi.org/10.1145/3195106.3195174.

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Morimoto, Yasuhiko. "Optimized transitive association rule." In the 2005 ACM symposium. ACM Press, 2005. http://dx.doi.org/10.1145/1066677.1066799.

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Reports on the topic "Association rule"

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Rodríguez Burgos, Ojel L. Freedom and the Rule of Law. Puerto Rico Institute for Economic Liberty, 2022. http://dx.doi.org/10.53095/13582005.

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The word freedom is used constantly, but little understood; to understand it, it is important to see the State as a civil association of individuals, where different ways of living and purposes coexist. This coexistence depends on a rule of law, which allows individuals to pursue their conception of the good life consistent with the rules of the association. The freedom requires a rule of law, which allows free action and cooperation of individuals in the market and thus benefits the economy.
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Sandford, Robert, Kaveh Madani, Emily Lorra Hines, et al. The Future of Freshwater in Canada. Massey College and the United Nations University Institute for Water, 2023. https://doi.org/10.53328/inr23rs01.

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In September of 2023, the Forum for Leadership on Water and Massey College at the University of Toronto partnered to offer a symposium that aimed to bring the water community in Canada together to break down barriers, generate ideas and agree on solutions to a growing water and water-related climate crisis in Canada. The purpose of the symposium was to engage and inspire meaningful conversation and debate across disciplines, affiliations and governments with respect to policy, legislation, finance and actions needed to ensure the sustainability of Canada’s great freshwater resource. This report, produced in association with the United Nations University Institute of Water, Environment and Health (UNU-INWEH) is a summary synthesis of the proceedings of what may well turn out to be a turning point in Canadian understanding of the threats global climate breakdown and the loss of hydrologic stationarity now pose and may pose in the future to water security in this country and how we can address them. The symposium was conducted under the Chatham House Rule, which is an unwritten agreement that allows the use of information from a discussion without direct quote or attribution to a speaker or the organization they represent. Though it will identify the keynote speakers, this report will respect this rule and will highlight the ideas and discussions from the symposium without citing the specific speakers.
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Nugent, Stevonne, and Juan Pedro Schmid. Okun and Jamaica at 50: How Does Unemployment React to Growth? Inter-American Development Bank, 2013. http://dx.doi.org/10.18235/0008435.

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Jamaica is projected to exit a prolonged recession that has left deep scars in the socioeconomic conditions of the country. Besides increasing macroeconomic vulnerabilities and halting economic growth, advances in poverty and unemployment were reversed. Unemployment bottomed in 2009 at 9.5 percent but increased over the following years until reaching more than 16 percent by April 2013, and poverty increased from 9.9 percent in 2007 to 17.6 percent in 2010. Following the literature on Okun's rule of thumb, we explore how the projected recovery will be reflected in the labor market. Results indicate that there is an association between GDP growth and unemployment - a 1 percent growth in GDP results in a 0.3 percent reduction in unemployment. These values indicate that under current growth projections, unemployment in Jamaica will remain above the psychologically important threshold of 10 percent for several years.
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Megersa, Kelbesa. Tax Transparency for an Effective Tax System. Institute of Development Studies (IDS), 2021. http://dx.doi.org/10.19088/k4d.2021.070.

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This rapid review examines evidence on the transparency in the tax system and its benefits; e.g. rising revenue, strengthen citizen/state relationship, and rule of law. Improvements in tax transparency can help in strengthening public finances in developing countries that are adversely affected by COVID-19. The current context (i.e. a global pandemic, widespread economic slowdown/recessions, and declining tax revenues) engenders the urgency of improving domestic resource mobilisation (DRM) and the fight against illicit financial flows (IFFs). Even before the advent of COVID-19, developing countries’ tax systems were facing several challenges, including weak tax administrations, low taxpayer morale and “hard-to-tax” sectors. The presence of informational asymmetry (i.e. low tax transparency) between taxpayers and tax authorities generates loopholes for abuse of the tax system. It allows the hiding of wealth abroad with a limited risk of being caught. Cases of such behaviour that are exposed without proper penalty may result in a decline in the morale of citizens and a lower level of voluntary compliance with tax legislation. A number of high-profile tax leaks and scandals have undermined public confidence in the fairness of tax systems and generated a strong demand for effective counteraction and tax transparency. One of the key contributing factors to lower tax revenues in developing countries (that is linked to low tax transparency) is a high level of IFFs. These flows, including international tax evasion and the laundering of corruption proceeds, build a major obstacle to successful DRM efforts. Research has also identified an association between organisational transparency (e.g. transparency by businesses and tax authorities) and stakeholder trust (e.g. between citizens and the state). However, the evidence is mixed as to how transparency in particular influences trust and perceptions of trustworthiness.
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5

Lazonick, William, and Matt Hopkins. Why the CHIPS Are Down: Stock Buybacks and Subsidies in the U.S. Semiconductor Industry. Institute for New Economic Thinking Working Paper Series, 2021. http://dx.doi.org/10.36687/inetwp165.

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The Semiconductor Industry Association (SIA) is promoting the Creating Helpful Incentives to Produce Semiconductors (CHIPS) for America Act, introduced in Congress in June 2020. An SIA press release describes the bill as “bipartisan legislation that would invest tens of billions of dollars in semiconductor manufacturing incentives and research initiatives over the next 5-10 years to strengthen and sustain American leadership in chip technology, which is essential to our country’s economy and national security.” On June 8, 2021, the Senate approved $52 billion for the CHIPS for America Act, dedicated to supporting the U.S. semiconductor industry over the next decade. As of this writing, the Act awaits approval in the House of Representatives. This paper highlights a curious paradox: Most of the SIA corporate members now lobbying for the CHIPS for America Act have squandered past support that the U.S. semiconductor industry has received from the U.S. government for decades by using their corporate cash to do buybacks to boost their own companies’ stock prices. Among the SIA corporate signatories of the letter to President Biden, the five largest stock repurchasers—Intel, IBM, Qualcomm, Texas Instruments, and Broadcom—did a combined $249 billion in buybacks over the decade 2011-2020, equal to 71 percent of their profits and almost five times the subsidies over the next decade for which the SIA is lobbying. In addition, among the members of the Semiconductors in America Coalition (SIAC), formed specifically in May 2021 to lobby Congress for the passage of the CHIPS for America Act, are Apple, Microsoft, Cisco, and Google. These firms spent a combined $633 billion on buybacks during 2011-2020. That is about 12 times the government subsidies provided under the CHIPS for America Act to support semiconductor fabrication in the United States in the upcoming decade. If the Congress wants to achieve the legislation’s stated purpose of promoting major new investments in semiconductors, it needs to deal with this paradox. It could, for example, require the SIA and SIAC to extract pledges from its member corporations that they will cease doing stock buybacks as open-market repurchases over the next ten years. Such regulation could be a first step in rescinding Securities and Exchange Commission Rule 10b-18, which has since 1982 been a major cause of extreme income inequality and loss of global industrial competitiveness in the United States.
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Viswanathan, Meera, Jennifer Cook Middleton, Alison Stuebe, et al. Maternal, Fetal, and Child Outcomes of Mental Health Treatments in Women: A Systematic Review of Perinatal Pharmacologic Interventions. Agency for Healthcare Research and Quality (AHRQ), 2021. http://dx.doi.org/10.23970/ahrqepccer236.

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Background. Untreated maternal mental health disorders can have devastating sequelae for the mother and child. For women who are currently or planning to become pregnant or are breastfeeding, a critical question is whether the benefits of treating psychiatric illness with pharmacologic interventions outweigh the harms for mother and child. Methods. We conducted a systematic review to assess the benefits and harms of pharmacologic interventions compared with placebo, no treatment, or other pharmacologic interventions for pregnant and postpartum women with mental health disorders. We searched four databases and other sources for evidence available from inception through June 5, 2020 and surveilled the literature through March 2, 2021; dually screened the results; and analyzed eligible studies. We included studies of pregnant, postpartum, or reproductive-age women with a new or preexisting diagnosis of a mental health disorder treated with pharmacotherapy; we excluded psychotherapy. Eligible comparators included women with the disorder but no pharmacotherapy or women who discontinued the pharmacotherapy before pregnancy. Results. A total of 164 studies (168 articles) met eligibility criteria. Brexanolone for depression onset in the third trimester or in the postpartum period probably improves depressive symptoms at 30 days (least square mean difference in the Hamilton Rating Scale for Depression, -2.6; p=0.02; N=209) when compared with placebo. Sertraline for postpartum depression may improve response (calculated relative risk [RR], 2.24; 95% confidence interval [CI], 0.95 to 5.24; N=36), remission (calculated RR, 2.51; 95% CI, 0.94 to 6.70; N=36), and depressive symptoms (p-values ranging from 0.01 to 0.05) when compared with placebo. Discontinuing use of mood stabilizers during pregnancy may increase recurrence (adjusted hazard ratio [AHR], 2.2; 95% CI, 1.2 to 4.2; N=89) and reduce time to recurrence of mood disorders (2 vs. 28 weeks, AHR, 12.1; 95% CI, 1.6 to 91; N=26) for bipolar disorder when compared with continued use. Brexanolone for depression onset in the third trimester or in the postpartum period may increase the risk of sedation or somnolence, leading to dose interruption or reduction when compared with placebo (5% vs. 0%). More than 95 percent of studies reporting on harms were observational in design and unable to fully account for confounding. These studies suggested some associations between benzodiazepine exposure before conception and ectopic pregnancy; between specific antidepressants during pregnancy and adverse maternal outcomes such as postpartum hemorrhage, preeclampsia, and spontaneous abortion, and child outcomes such as respiratory issues, low Apgar scores, persistent pulmonary hypertension of the newborn, depression in children, and autism spectrum disorder; between quetiapine or olanzapine and gestational diabetes; and between benzodiazepine and neonatal intensive care admissions. Causality cannot be inferred from these studies. We found insufficient evidence on benefits and harms from comparative effectiveness studies, with one exception: one study suggested a higher risk of overall congenital anomalies (adjusted RR [ARR], 1.85; 95% CI, 1.23 to 2.78; N=2,608) and cardiac anomalies (ARR, 2.25; 95% CI, 1.17 to 4.34; N=2,608) for lithium compared with lamotrigine during first- trimester exposure. Conclusions. Few studies have been conducted in pregnant and postpartum women on the benefits of pharmacotherapy; many studies report on harms but are of low quality. The limited evidence available is consistent with some benefit, and some studies suggested increased adverse events. However, because these studies could not rule out underlying disease severity as the cause of the association, the causal link between the exposure and adverse events is unclear. Patients and clinicians need to make an informed, collaborative decision on treatment choices.
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Barrera-Osorio, Felipe, Paul Gertler, Nozomi Nakajima, and Harry A. Patrinos. Promoting Parental Involvement in Schools: Evidence from Two Randomized Experiments. Research on Improving Systems of Education (RISE), 2021. http://dx.doi.org/10.35489/bsg-rise-wp_2021/060.

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Parental involvement programs aim to strengthen school-home relations with the goal of improving children’s educational outcomes. We examine the effects of a parental involvement program in Mexico, which provides parent associations with grants and information. We separately estimate the effect of the grants from the effect of the information using data from two randomized controlled trials conducted by the government during the rollout of the program. Grants to parent associations did not improve educational outcomes. Information to parent associations reduced disciplinary actions in schools, mainly by increasing parental involvement in schools and changing parenting behavior at home. The divergent results from grants and information are partly explained by significant changes in perceptions of trust between parents and teachers. Our results suggest that parental involvement interventions may not achieve their intended goal if institutional rules are unclear about the expectations of parents and teachers as parents increase their involvement in schools.
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Suominen, Kati, and Antoni Estevadeordal. Rules of Origin in FTAs in Europe and in the Americas: Issues and Implications for the EU-Mercosur Inter-Regional Association Agreement. Inter-American Development Bank, 2004. http://dx.doi.org/10.18235/0011087.

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Rules of origin (RoO) are a central topic both in the Inter-Regional Association Agreement negotiations between the European Union (EU) and the Southern Common Market (Mercosur), and in the 34-country negotiations of the Free Trade Area of the Americas (FTAA). The purpose of this paper is to provide a detailed mapping of the different rules of origin regimes in FTAs in Europe and the Americas, and to draw lessons from these regimes to the EU-Mercosur RoO negotiations, in particular. The paper offers four recommendations. First, the EU¿s standardized RoO regime will play a central role in the EU-Mercosur RoO negotiations. However, there is plenty of room for mutual tariff concessions. At the minimum, the EU¿s tariff preferences for Mercosur should approximate those provided to Chile in order to foster Mercosur¿s chances to augment its industrial exports to the European market. Second, the EU-Mercosur FTA RoO regime should incorporate general and sector-specific adjustment mechanisms in order to enable Mercosur to better utilize the preferential treatment provided by the EU. Third, Mercosur will need to further consolidate its common market in order to take full advantage of the RoO regime¿s likely provision of diagonal cumulation. Fourth, Mercosur should make the most of its strategy of simultaneous trade negotiations in the Americas and with the EU by ensuring a high degree of compatibility between its two major future agreements.
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Varisco, Tyler, Hannah Fish, Joshua Bolin, et al. The Pharmacy Access to Resources and Medication for Opioid Use Disorder (PhARM-OUD) Guideline. University of Houston, 2024. http://dx.doi.org/10.52713/pharm-oud.

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Buprenorphine is the only agonist medication for opioid use disorder that may be dispensed directly to patients from a community pharmacy pursuant to a prescription from any Drug Enforcement Administration (DEA) licensed prescriber in all fifty states. The potential accessibility, efficacy, and relative safety of buprenorphine makes it an ideal therapeutic option for the management of opioid use disorder. Still, around half of community pharmacies in the United States do not maintain buprenorphine in their inventory. Community pharmacists must contend with a convoluted meshwork of state and federal laws and regulations that complicate the wholesale purchase and dispensing of buprenorphine. Additionally, stigma toward persons with opioid use disorder often interferes with the quality of care delivered at the pharmacy counter. Prevailing clinical practice guidelines for the medical management of OUD do not address the complexities of pharmacy practice, creating a clear and present need for direct pharmacist guidance. The Pharmacy Access to Resources and Medication for Opioid Use Disorder Guideline was created to provide actionable steps to improve access to buprenorphine in community pharmacies. A steering committee led by the National Community Pharmacists Association, National Association of Boards of Pharmacy, and the University of Houston College of Pharmacy recruited and empaneled a 22-member expert panel to draft and refine recommendations to address barriers to buprenorphine dispensing identified through focus group interviews with community pharmacist in Texas, California, and West Virginia. The panel’s recommendations were generated through a four-round, Delphi process that occurred between November 2023 and March, 2024. Nine main recommendations and 35 supporting recommendations were generated. After drafting the document, the National Association of Boards of Pharmacy hosted a public comment period between April 15, 2024, and June 1, 2024. A second, thirteen-member review panel was convened to revise the recommendations at the National Pharmacists Association headquarters in Mount Prospect, Illinois on June 11, 2024. The central message of the final document, which was endorsed by several leading medicine, pharmacy, and advocacy organizations, is that pharmacists should dispense buprenorphine under most circumstances pursuant to a valid prescription from a DEA licensed prescriber. The document urges caution in applying quantitative thresholds to buprenorphine dispensing decisions and encourages pharmacists to rely on their professional judgement rather than arbitrary decision rules designed to reduce liability at the cost of patient health and safety. In many parts, the guidance reminds pharmacists that OUD is a chronic disease that responds to medical management. Community pharmacists and pharmacies are encouraged to incorporate this guidance into their practice to ensure that they are adequately meeting the needs of the patients that they serve.
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Navarro, Lucas. Entrepreneurship Policy and Firm Performance: Chile's CORFO Seed Capital Program. Inter-American Development Bank, 2014. http://dx.doi.org/10.18235/0008445.

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This paper uses administrative data from projects for which an application was made to CORFO's (Chile's main development agency) Seed Capital Program (SCP) during the 2008-12 period. This paper analyzes the impact of the program, which is a subsidy provided to new, innovative firms, on Start, Growth, and Survival. The projects are supported by sponsors in the application process. Results of our analysis indicate that, controlling for observed characteristics, projects that received the subsidy had a 9.5 percentage point higher probability of starting to sell. Among created firms, subsidized (Treated) firms showed a 17 percentage point higher probability of significant Growth (in sales) and a similar effect on Survival. The analysis also examined a change in the program rules in 2011, whereby sponsors were paid based on performance instead of fixed fees, as it was before 2011. For projects affected by the policy change, results indicate no overall association of the program with the probability of Start and a positive correlation with Growth and Survival. These results could be a consequence of sponsors making better project selections for funding. The change in rules means that the program contributes more to the Growth and Survival of new firms than to their Start, which would take place anyway. The data available for this study did not make it possible to control for potential selection biases, and thus the results need to be viewed with caution, and data collection standards need to improve to help identify the true effect of this type of program.
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