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 saving and investment nexus for China: evidence from cointegration tests
Countries citing papers authored by Paresh Kumar Narayan
Since
Specialization
Citations
This map shows the geographic impact of Paresh Kumar Narayan'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 Paresh Kumar Narayan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Paresh Kumar Narayan more than expected).
Fields of papers citing papers by Paresh Kumar Narayan
This network shows the impact of papers produced by Paresh Kumar Narayan. 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 Paresh Kumar Narayan. The network helps show where Paresh Kumar Narayan may publish in the future.
Co-authorship network of co-authors of Paresh Kumar Narayan
This figure shows the co-authorship network connecting the top 25 collaborators of Paresh Kumar Narayan.
A scholar is included among the top collaborators of Paresh Kumar Narayan 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 Paresh Kumar Narayan. Paresh Kumar Narayan is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Narayan, Paresh Kumar & Xinwei Zheng. (2011). The Relationship between Liquidity and Returns on the Chinese Stock Market. SSRN Electronic Journal.2 indexed citations
10.
Narayan, Paresh Kumar, Seema Narayan, & Stephan Popp. (2010). Does electricity consumption panel Granger cause GDP? A new global evidence. RMIT Research Repository (RMIT University Library).1 indexed citations
Narayan, Paresh Kumar, et al.. (2009). The monetary approach to understanding the balance of payments for the Fiji Islands. Deakin Research Online (Deakin University).1 indexed citations
13.
Narayan, Paresh Kumar & Seema Narayan. (2009). Understanding Fiji's Declining Foreign Reserves Position.. ANU Open Research (Australian National University). 24(2). 95–112.1 indexed citations
14.
Narayan, Paresh Kumar & Seema Narayan. (2008). Does environmental quality influence health expenditures? empirical evidence from a panel of selected OECD countries. RePEc: Research Papers in Economics.1 indexed citations
15.
Narayan, Paresh Kumar & Russell Smyth. (2007). A Panel Cointegration Analysis of the Demand for Oil in the Middle East. SSRN Electronic Journal.2 indexed citations
Narayan, Paresh Kumar & Russell Smyth. (2006). Higher Education, Real Income and Real Investment in China: Evidence from Granger Causality Tests. SSRN Electronic Journal.1 indexed citations
19.
Narayan, Paresh Kumar & Russell Smyth. (2004). Temporal Causality and the Dynamics of Exports, Human Capital and Real Income in China. SSRN Electronic Journal. 1(1). 24–45.77 indexed citations
20.
Narayan, Paresh Kumar. (2004). Economic Impact of Tourism on Fiji's Economy: Empirical Evidence from the Computable General Equilibrium Model. SSRN Electronic Journal.3 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.