Lamar Crombach

This paper introduces the Journal Popularity Score (JPS), a usage-based indicator of journal popularity derived from visits to journal pages on the SciRev.org website. Whereas citation-based indicators measure journal status through references to published work, the JPS captures researchers' interest in journals as possible publication outlets. Using SciRev traffic data for 2020-2025, after removing documented and likely bot traffic, we examine how journal visits vary by discipline, citation-based prestige, open access status, publisher type, and region of visiting researchers. The results show that journal popularity is highly unevenly distributed and differs strongly across disciplines. It is positively related to citation-based indicators, but only moderately, indicating that popularity cannot be reduced to citation-based impact alone. Subscription journals still receive the largest share of visits, while open access journals account for almost 30 percent, with notable regional differences. Publisher patterns further show the strong position of large commercial publishers, learned-society journals, and established open access publishers. The JPS therefore adds a new perspective to journal evaluation by capturing researchers’ active interest in journals as possible publication outlets.

This paper introduces the Journal Popularity Score (JPS), a usage-based indicator of journal popularity derived from visits to journal pages on the SciRev.org website. Whereas citation-based indicators measure journal status through references to published work, the JPS captures researchers' interest in journals as possible publication outlets. Using SciRev traffic data for 2020-2025, after removing documented and likely bot traffic, we examine how journal visits vary by discipline, citation-based prestige, open access status, publisher type, and region of visiting researchers. The results show that journal popularity is highly unevenly distributed and differs strongly across disciplines. It is positively related to citation-based indicators, but only moderately, indicating that popularity cannot be reduced to citation-based impact alone. Subscription journals still receive the largest share of visits, while open access journals account for almost 30 percent, with notable regional differences. Publisher patterns further show the strong position of large commercial publishers, learned-society journals, and established open access publishers. The JPS therefore adds a new perspective to journal evaluation by capturing researchers’ active interest in journals as possible publication outlets.

This data descriptor presents the Subnational Corruption Database (SCD), which provides data on corruption in 1,473 subnational areas of 178 countries. The SCD includes a comprehensive overall corruption index, the Subnational Corruption Index (SCI), and its two components: the Subnational Grand Corruption Index (SGCI) and Subnational Petty Corruption Index (SPCI). The SCD is constructed by combining data of 807 surveys held in the period 1995–2022 and includes the corruption experiences and perceptions of 1,326,656 respondents along 19 separate dimensions. The data are available for multiple years, allowing longitudinal analyses. At the national level, the SCI correlates strongly with established corruption indices, like the Transparency International Corruption Perceptions Index (CPI) and the World Bank Control of Corruption Index (CCI). We create subnational estimates of the CPI and CCI by superimposing the subnational variation of the SCI around the national averages of these indices. The presentation of subnational data in the SCD and the separation between grand and petty corruption significantly broaden the global knowledge base in the field of corruption.

Current models inadequately address the role of information transfer in explaining the slow fertility decline in sub‐Saharan Africa (SSA) in the 1990s and 2000s. We posit that an important reason for this slow decline was the high level of social isolation of the rural population in the region, as a result of which new ideas regarding fertility had difficulty reaching them. Applying Poisson regression to survey data on 180,000 women across 25 SSA countries spanning 1995–2010, we find clear associations of travel distance to urban areas and TV ownership with desired and actual fertility. Interaction analyses reveal a compensatory relationship between distance and TV ownership, with the effect of distance almost disappearing for households with a TV and the effect of TV disappearing for households close to urban areas. The role of information access is further stressed by the finding that socioeconomic factors, while highly significant overall, offer limited explanatory value for women living at great distance from urban centres or without TV access. If information transfer is indeed as important as our findings suggest, the increasing availability of smartphones and social media in rural SSA might lead to a faster fertility decline in the region than foreseen by the latest UN population estimates.

Governments try to improve re‐election chances by using fiscal instruments; they can shift voters' expectations of government competence because some voters are impaired by uninformedness. We argue that uninformed voters may also be impaired in another way which has not been considered in the literature, namely that uninformed voters are uncertain about the precision of that expected competence. Analytically, we show that political budget cycles (PBCs) are only produced when we have many uninformed voters and their expected competence of the government is fairly uncertain; or with few uninformed voters and certain expectations. This could explain two empirical puzzles on why we sometimes find and sometimes not (i) PBCs in developed and democratic countries with strong institutions, and (ii) that press freedom exacerbates PBCs. In a panel of 70 countries (1986–2015) we find empirical support for these findings. Results are robust to alternative specifications and explanations like fiscal rules, corruption and expected downturns.

Data for low- and middle- income countries (LMICs) are used to investigate the effect of the demographic transition on economic growth at sub-national level. We introduce a detailed classification of demographic window phases, determine how these phases are distributed among and within LMICs, and analyze the relationship between the demographic window of opportunity (DWO) and economic growth for 1921 urban and rural areas of sub-national regions within 91 LMICs. Many areas in Asia, Latin America and the Middle East have entered the window, but most of Sub-Saharan Africa is still in the traditional or pre-window phase. Our analyses reveal higher growth rates in areas passing through the DWO. Positive growth effects are particularly strong in rural and more educated regions and in countries with lower levels of corruption. Policy measures aimed at effectively using the DW for achieving growth should combine investments in education and rural development with better governance.