Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
THE ESTIMATION AND APPLICATION OF LONG MEMORY TIME SERIES MODELS
This map shows the geographic impact of John Geweke'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 John Geweke with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John Geweke more than expected).
This network shows the impact of papers produced by John Geweke. 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 John Geweke. The network helps show where John Geweke may publish in the future.
Co-authorship network of co-authors of John Geweke
This figure shows the co-authorship network connecting the top 25 collaborators of John Geweke.
A scholar is included among the top collaborators of John Geweke 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 John Geweke. John Geweke is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
All Works
20 of 20 papers shown
1.
Frischknecht, Bart D., Christine Eckert, John Geweke, & Jordan J. Louviere. (2013). A Simple Method to Estimate Preference Parameters for Individuals. SSRN Electronic Journal.3 indexed citations
Barnett, William A., John Geweke, & Karl Shell. (2005). Economic complexity : chaos, sunspots, bubbles, and nonlinearity : proceedings of the Fourth International Symposium in Economic Theory and Econometrics. Cambridge University Press eBooks.4 indexed citations
Geweke, John, et al.. (1999). Simulation Based Inference for Dynamic Multinomial Choice Models. Munich Personal RePEc Archive (Ludwig Maximilian University of Munich).3 indexed citations
Horowitz, Joël L., Michael P. Keane, Denis Bolduc, et al.. (1994). Advances in Random Utility Models. Munich Personal RePEc Archive (Ludwig Maximilian University of Munich).3 indexed citations
Barnett, William A., William A. Barnett, William A. Barnett, et al.. (1988). Dynamic Econometric Modeling. Cambridge University Press eBooks.78 indexed citations
18.
Geweke, John. (1985). Macroeconometric Modeling and the Theory of the Representative Agent. American Economic Review. 75(2). 206–210.23 indexed citations
Geweke, John. (1982). Measurement of Linear Dependence and Feedback between Multiple Time Series. Journal of the American Statistical Association. 77(378). 304–313.1396 indexed citations breakdown →
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.