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.
Government Spending, Corruption and Economic Growth
2016255 citationsGiorgio d’Agostino, J. Paul Dunne et al.World Developmentprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
hero ref
This map shows the geographic impact of Luca Pieroni'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 Luca Pieroni with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Luca Pieroni more than expected).
This network shows the impact of papers produced by Luca Pieroni. 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 Luca Pieroni. The network helps show where Luca Pieroni may publish in the future.
Co-authorship network of co-authors of Luca Pieroni
This figure shows the co-authorship network connecting the top 25 collaborators of Luca Pieroni.
A scholar is included among the top collaborators of Luca Pieroni 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 Luca Pieroni. Luca Pieroni is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Pieroni, Luca, et al.. (2020). Regularization of Immigrants and Fertility in Italy. Munich Personal RePEc Archive (Munich University).1 indexed citations
5.
d’Agostino, Giorgio, et al.. (2018). Further evidence of the relationship between social transfers and income inequality in OECD countries. RePEc: Research Papers in Economics.1 indexed citations
Pieroni, Luca, et al.. (2016). Revisiting the relationship between welfare spending and income inequality in OECD countries. MPRA Paper.3 indexed citations
Bartolucci, Francesco, Leonardo Grilli, & Luca Pieroni. (2012). Estimating dynamic causal effects with unobserved confounders: a latent class version of the inverse probability weighted estimator. LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas).1 indexed citations
Bartolucci, Francesco, Leonardo Grilli, & Luca Pieroni. (2012). Inverse probability weighting to estimate causal effects of sequential treatments: a latent class extension to deal with unobserved confounding.1 indexed citations
Pieroni, Luca & Fabrizio Pompei. (2006). Localizzazione geografica delle innovazioni e mercato del lavoro. RePEc: Research Papers in Economics. 96(2). 277–328.1 indexed citations
18.
Aristei, David & Luca Pieroni. (2005). Estimating the Role of Government Expenditure in Long-run Consumption. RePEc: Research Papers in Economics.2 indexed citations
19.
Pieroni, Luca, et al.. (2004). Analisi fondamentale di mercato con aspettative razionali: un modello per il mercato delle materie prime. RePEc: Research Papers in Economics. 94(2). 187–224.
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.