What To Do (and Not to Do) with Time-Series Cross-Section Data

4.7k indexed citations
published 1995

Countries where authors are citing What To Do (and Not to Do) with Time-Series Cross-Section Data

Specialization
Citations

This map shows the geographic impact of What To Do (and Not to Do) with Time-Series Cross-Section Data. 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 What To Do (and Not to Do) with Time-Series Cross-Section Data with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites What To Do (and Not to Do) with Time-Series Cross-Section Data more than expected).

Fields of papers citing What To Do (and Not to Do) with Time-Series Cross-Section Data

Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of What To Do (and Not to Do) with Time-Series Cross-Section Data. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the What To Do (and Not to Do) with Time-Series Cross-Section Data.

About What To Do (and Not to Do) with Time-Series Cross-Section Data

This paper, published in 1995, received 4.7k indexed citations . Written by Nathaniel Beck and Jonathan N. Katz covering the research area of General Economics, Econometrics and Finance and Economics and Econometrics. It is primarily cited by scholars working on Economics and Econometrics (2.2k citations), Political Science and International Relations (1.6k citations) and Sociology and Political Science (1000 citations). Published in American Political Science Review.

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.

This paper is also available at doi.org/10.2307/2082979.

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