Jeffrey Pai

419 total citations
27 papers, 291 citations indexed

About

Jeffrey Pai is a scholar working on Soil Science, Economics and Econometrics and Statistics and Probability. According to data from OpenAlex, Jeffrey Pai has authored 27 papers receiving a total of 291 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Soil Science, 12 papers in Economics and Econometrics and 7 papers in Statistics and Probability. Recurrent topics in Jeffrey Pai's work include Agricultural risk and resilience (12 papers), Insurance and Financial Risk Management (9 papers) and Financial Risk and Volatility Modeling (6 papers). Jeffrey Pai is often cited by papers focused on Agricultural risk and resilience (12 papers), Insurance and Financial Risk Management (9 papers) and Financial Risk and Volatility Modeling (6 papers). Jeffrey Pai collaborates with scholars based in Canada, United States and China. Jeffrey Pai's co-authors include Milton S. Boyd, Налини Равишанкер, Ke Wang, Lysa Porth, Qiao Zhang, Lilian Shiao-Yen Wu, J. R. M. Hosking, H. Holly Wang, Johnny Siu‐Hang Li and Rui Zhou and has published in prestigious journals such as Journal of Econometrics, Computational Statistics & Data Analysis and Journal of Risk & Insurance.

In The Last Decade

Jeffrey Pai

26 papers receiving 275 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Jeffrey Pai Canada 11 137 117 77 44 42 27 291
Wenjun Zhu Singapore 10 85 0.6× 83 0.7× 21 0.3× 29 0.7× 22 0.5× 37 271
Lysa Porth Canada 11 106 0.8× 169 1.4× 15 0.2× 65 1.5× 13 0.3× 33 308
Joseph A. Atwood United States 11 151 1.1× 162 1.4× 13 0.2× 27 0.6× 15 0.4× 34 346
Joshua D. Woodard United States 15 282 2.1× 419 3.6× 37 0.5× 109 2.5× 7 0.2× 35 611
Bernard J. Morzuch United States 11 111 0.8× 31 0.3× 24 0.3× 76 1.7× 6 0.1× 21 349
Mathieu Pigeon Canada 9 139 1.0× 18 0.2× 32 0.4× 22 0.5× 79 1.9× 23 306
Michaël Bourdeau-Brien Canada 6 179 1.3× 36 0.3× 140 1.8× 77 1.8× 24 0.6× 11 319
Cindy Yu United States 10 540 3.9× 44 0.4× 306 4.0× 17 0.4× 162 3.9× 40 875
Anders Milhøj Denmark 9 179 1.3× 13 0.1× 184 2.4× 105 2.4× 25 0.6× 19 366
Brenda López Cabrera Germany 7 294 2.1× 61 0.5× 108 1.4× 20 0.5× 9 0.2× 20 414

Countries citing papers authored by Jeffrey Pai

Since Specialization
Citations

This map shows the geographic impact of Jeffrey Pai'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 Jeffrey Pai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jeffrey Pai more than expected).

Fields of papers citing papers by Jeffrey Pai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jeffrey Pai. 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 Jeffrey Pai. The network helps show where Jeffrey Pai may publish in the future.

Co-authorship network of co-authors of Jeffrey Pai

This figure shows the co-authorship network connecting the top 25 collaborators of Jeffrey Pai. A scholar is included among the top collaborators of Jeffrey Pai 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 Jeffrey Pai. Jeffrey Pai 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.
Zhou, Rui, Johnny Siu‐Hang Li, & Jeffrey Pai. (2018). Evaluating effectiveness of rainfall index insurance. Agricultural Finance Review. 78(5). 611–625. 4 indexed citations
2.
Porth, Lysa, Milton S. Boyd, & Jeffrey Pai. (2016). Reducing Risk Through Pooling and Selective Reinsurance Using Simulated Annealing: An Example from Crop Insurance. The Geneva Risk and Insurance Review. 41(2). 163–191. 8 indexed citations
3.
Zhou, Rui, Johnny Siu‐Hang Li, & Jeffrey Pai. (2016). Hedging crop yield with exchange-traded weather derivatives. Agricultural Finance Review. 76(1). 172–186. 4 indexed citations
4.
Boyd, Milton S., et al.. (2015). Factors affecting farmers’ willingness to purchase weather index insurance in the Hainan Province of China. Agricultural Finance Review. 75(1). 103–113. 20 indexed citations
5.
Pai, Jeffrey, Milton S. Boyd, & Lysa Porth. (2014). Insurance Premium Calculation Using Credibility Analysis: An Example From Livestock Mortality Insurance. Journal of Risk & Insurance. 82(2). 341–357. 10 indexed citations
6.
Porth, Lysa, Jeffrey Pai, & Milton S. Boyd. (2014). A Portfolio Optimization Approach Using Combinatorics With a Genetic Algorithm for Developing a Reinsurance Model. Journal of Risk & Insurance. 82(3). 687–713. 14 indexed citations
7.
Boyd, Milton S., Jeffrey Pai, & Lysa Porth. (2013). Livestock mortality insurance: development and challenges. Agricultural Finance Review. 73(2). 233–244. 8 indexed citations
8.
Boyd, Milton S., Jeffrey Pai, Qiao Zhang, & Ke Wang. (2011). Crop Insurance Principles and Risk Implications for China. Human and Ecological Risk Assessment An International Journal. 17(3). 554–565. 23 indexed citations
9.
Boyd, Milton S., Jeffrey Pai, Qiao Zhang, H. Holly Wang, & Ke Wang. (2011). Factors affecting crop insurance purchases in China: the Inner Mongolia region. China Agricultural Economic Review. 3(4). 441–450. 40 indexed citations
10.
Pai, Jeffrey & Налини Равишанкер. (2010). Fast Bayesian Estimation for VARFIMA Processes with Stable Errors. Journal of Statistical Theory and Practice. 4(4). 663–677. 5 indexed citations
11.
Pai, Jeffrey & Налини Равишанкер. (2009). A multivariate preconditioned conjugate gradient approach for maximum likelihood estimation in vector long memory processes. Statistics & Probability Letters. 79(9). 1282–1289. 6 indexed citations
12.
Pai, Jeffrey & Налини Равишанкер. (2009). Maximum likelihood estimation in vector long memory processes via EM algorithm. Computational Statistics & Data Analysis. 53(12). 4133–4142. 2 indexed citations
13.
Wang, Xikui, et al.. (2007). A semi‐Markov model of disease recurrence in insured dogs. Applied Stochastic Models in Business and Industry. 23(5). 429–437.
14.
Pai, Jeffrey, et al.. (2003). On the nth stop-loss transform order of ruin probability. Insurance Mathematics and Economics. 32(1). 51–60. 11 indexed citations
15.
Pai, Jeffrey & Налини Равишанкер. (1998). Bayesian analysis of autoregressive fractionally integrated moving‐average processes. Journal of Time Series Analysis. 19(1). 99–112. 25 indexed citations
16.
Pai, Jeffrey. (1997). Bayesian analysis of compound loss distributions. Journal of Econometrics. 79(1). 129–146. 13 indexed citations
17.
Kuo, Lynn, et al.. (1997). Bayes Inference for Technological Substitution Data with Data-based Transformation. Journal of Forecasting. 16(2). 65–82. 2 indexed citations
18.
Wu, Lilian Shiao-Yen, Jeffrey Pai, & J. R. M. Hosking. (1996). An algorithm for estimating parameters of state-space models. Statistics & Probability Letters. 28(2). 99–106. 44 indexed citations
19.
Pai, Jeffrey & Налини Равишанкер. (1996). Bayesian modelling of ARFIMA processes by Markov chain Monte Carlo methods. Journal of Forecasting. 15(2). 63–82. 2 indexed citations
20.
Pai, Jeffrey, Налини Равишанкер, & Alan E. Gelfand. (1994). Bayesian analysis of concurrent time series with application to regional IBM revenue data. Journal of Forecasting. 13(5). 463–479. 7 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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