Publication activity
Articles grouped by publication year
Hover over a year or focus the chart and use arrow keys to inspect values.
2026 is year to date. 0 undated publications excluded.
Top 5 in the selected collection · Ranked by Crossref lifetime citations. Only articles with at least one known citation are included; source totals are never combined.
2025 · Puja Rani Saha · Hasina Sheykh · Shamim Ahmed
Publication activity alongside incoming citations.
Articles grouped by publication year
Hover over a year or focus the chart and use arrow keys to inspect values.
2026 is year to date. 0 undated publications excluded.
OpenAlex · year of the citing work
Hover over a year or focus the chart and use arrow keys to inspect values.
2017–2026 annual-history window. 2026 is year to date. Unknown years have gaps.
Leading affiliations and themes in this collection.
Full distributions & methodology ↓Independent sources. Clear time scales.
Crossref and OpenAlex · separate totals for the same publication cohorts
Hover over a year or focus the chart and use arrow keys to inspect values.
Latest lifetime totals, grouped by the cited article’s year. These are not citations received in that year.
OpenAlex · incoming citation links grouped by citing-work year
Hover over a year or focus the chart and use arrow keys to inspect values.
2017–2026 annual-history window. 2026 is year to date. Unknown years have gaps.
Select journals to compare the same collection filters. Source totals stay separate. These measures describe research activity, not journal quality.
Articles by publication year
Latest lifetime totals · grouped by publication year
Latest lifetime totals · grouped by publication year
By year of the citing work · 2017–2026
2026 is year to date. Crossref and OpenAlex lifetime charts share a citation scale. Unknown observations appear as gaps; known zero stays zero. Annual receipts use available OpenAlex histories and may not sum to lifetime totals. 0 undated publications excluded from publication-year charts.
Crossref citation coverage: 3 / 4 publications (75.0%). Latest observation: 21 Oct 2026, 00:21 UTC. Means and percentages use records with known counts.
DOI-matched OpenAlex observations for the same selected publications. These counts are separate from Crossref and are never added together.
Observation range: 29 Oct 2026 16:53 UTC — 30 Oct 2026 19:16 UTC. Missing matches are not zero citations. Previous observations may remain if a refresh fails or a DOI no longer matches.
OpenAlex affiliations and primary-topic classification. Each publication counts once per institution or country; multi-affiliated publications appear in multiple groups, so percentages can sum above 100%. Countries describe author affiliations, not nationality. Topics use one primary topic per publication.
4 / 4 with data · 0 missing or unmatched. Percentages use all 4 selected publications.
4 / 4 with data · 0 missing or unmatched. Percentages use all 4 selected publications.
4 / 4 with data · 0 missing or unmatched. Percentages use all 4 selected publications.
Citations are the latest recorded totals for articles published in each year, not citations received during that year. Crossref and OpenAlex remain separate and share the same citation scale. 2026 is incomplete; newer articles have had less time to receive citations.
0 undated publications excluded. Unknown citation counts are shown as —, never as zero. Partial coverage can understate totals; expand each table for known / total records.
| Publication year | Journal / scope | Publications | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2025 | All selected publications | 4 | 4 | 3/4 | 4/4 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2025 | All selected publications | 1 | 4 | 3/4 | 4/4 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2025 | All selected publications | 1 | 4 | 3/4 | 4/4 |
Incoming citations to the selected publications, grouped by the year of the citing work. This is separate from lifetime citation totals grouped by the cited article’s publication year.
The publication filters above define which articles receive the citations. The citation-year range below only controls this chart and the incoming-citation comparison. Removing publication-year filters includes older articles’ incoming citations too.
Annual history available for 4 / 4 selected publications. Supported display window: 2017–2026; 2026 is incomplete. Within a successfully fetched ten-year window, omitted years mean zero. Missing histories and years beyond a saved observation’s window remain unknown (—); partial coverage can understate totals.
Annual-history observations (UTC): 2026-10-29T16:53:00.581992+00:00 — 2026-10-30T19:16:18.289020+00:00. Older observations may be retained after failed or incomplete refreshes.
| Citation year | Journal / scope | OpenAlex · Citations received by year | Publications | Annual history known |
|---|---|---|---|---|
| 2017 | All selected publications | 0 | 4 | 4/4 |
| 2018 | All selected publications | 0 | 4 | 4/4 |
| 2019 | All selected publications | 0 | 4 | 4/4 |
| 2020 | All selected publications | 0 | 4 | 4/4 |
| 2021 | All selected publications | 0 | 4 | 4/4 |
| 2022 | All selected publications | 0 | 4 | 4/4 |
| 2023 | All selected publications | 0 | 4 | 4/4 |
| 2024 | All selected publications | 0 | 4 | 4/4 |
| 2025 | All selected publications | 0 | 4 | 4/4 |
| 2026 | All selected publications | 1 | 4 | 4/4 |
Counts represent citation links, not unique citing papers across a journal: one paper citing two selected articles contributes two links. Older citations outside this window are excluded, so annual sums need not equal lifetime totals. OpenAlex methodology ↗
Publications by publication year. 2026 is an incomplete year.
| Period | Publications |
|---|---|
| 2025 | 4 |
Latest Crossref totals for the selected publications; not citations received in the selected years.
Unknown counts are excluded from the mean, median and cited-publication rate.
Same filters, source and counting rules across journals. Descriptive statistics, not a quality ranking.
| Journal / publisher | Publications | Crossref citations | OpenAlex citations | OpenAlex coverage | Crossref mean | Crossref median | Crossref cited %* | Crossref coverage |
|---|---|---|---|---|---|---|---|---|
| International Journal of Finance & Banking Studies SSBFNET | 4 | 1 | 1 | 4/4 | 0.33 | 0 | 33.3 | 3/4 · 75.0% |
* Percentage among publications with a known citation count.
This paper examines the exchange rate pass-through (ERPT) and its impact on home inflation in Bangladesh, particularly in the post-pandemic era. Examining important economic factors including the nominal exchange rate (NER), money supply (M2), industrial production (IP), and global commodity index (GCI) using monthly data from January 2002 to August 2023 helps one to grasp their combined influence on consumer price inflation (CPI). By means of Johansen cointegration and Vector Error Correction Model (VECM) approaches, the study reveals important short-term and long-term dynamics. Contrary to patterns in many emerging nations, the results show that changes in exchange rates have apparently little impact on home prices. Rather, changes in the money supply and world commodities prices mostly influence inflation; the latter becomes a major factor. The study also exposes an unexpected positive link between industrial production and CPI, implying complexity in Bangladesh's production-driven economic structure. Moreover, this investigation underlines how complex monetary expansion, external commodities shocks, and devaluation of money interact to shape inflationary pressures. These results offer legislators important new perspectives and support strong monetary policies and focused involvement in world commodities markets to help to lower inflation. This study clarifies ERPT in developing countries and provides direction on inflation control techniques for Bangladesh.
This is a study about the financing of large group health insurance in the United States. Almost 8 in 10 covered employees in private large firms are enrolled in self-insured (or self-funded) health plans in contrast to only 20 percent of employees in small firms. More than half of all large standard (non-supplemental) health plans are self-insured although their number is decreasing. Considering their significantly greater risk of exposure and transaction costs, the question for scholarly investigation is why (and how) do private large firms self-fund employer-sponsored health insurance? Using plan-level data from health plan administrator filings of Forms 5500 and Summary Annual Reports (2014-2022) with the U.S. Department of Labor, six variables are examined in this study relative to large group self-insurance: industry/sectoral distribution, plan size/enrollment, plan administration, benefits coverage, plan assets and investments, and statutory compliance. Findings suggest that industry/sectoral and enrollee distributions of large health plans are not widely dispersed while their assets and investments and statutory exemptions offer comparative advantages. These plans have also increasingly relied on stop-loss insurance, third-party administration, supplemental health benefits, and less major medical plans to mitigate actuarial risks that involve considerable financial exposure to fluctuating claims costs, potential for catastrophic claims, and cash flow unpredictability. The intertwining theoretical and practical implications of large group self-insurance in healthcare finance and risk management are addressed by way of conclusion.
In the loanable funds theory, the interest rate serves as a balancing factor between the savings offered for loans and the funds borrowed for investment. In Keynes’s theory, by contrast, it is a monetary phenomenon that balances the demand and the supply of money. At first glance, the monetary phenomenon of the interest rate may seem quite different and is often considered groundbreaking and revolutionary. In Keynes’s theory, people hold part of their savings in money to cope with uncertainty about the returns from long-term bonds, and it is savings held in money that leads the interest rate to be a monetary phenomenon. While people hold part of their savings in money, they also invest their savings by purchasing long-term bonds. The interest rate also balances savings offered, though only in part and not the whole, and funds borrowed in the bond market, as in the loanable funds theory. In this regard, Keynes’s theory and the loanable funds theory are not as strikingly different as it may first appear. The main exegetical work of Keynes’s ideas is Keynesian economics. In this theory, the interest rate is also a monetary phenomenon, as is expected of exegetical work. However, it is not due to savings held in money as in Keynes’s theory; rather, it is due to the cash holdings required for purchasing goods and services. This paper examines the differences among these three interest rate theories, the reasons behind them, and their practical implications.
Using a large sample of bond rating downgrades of US firms announced by the three largest rating agencies during 1997-2023, I find that cumulative abnormal stock returns (CAR) spanning the day of and day following downgrade announcements are significantly and negatively related to annual report readability, indicating that downgrades are more informative among firms with more readable annual reports. My baseline regression results indicate that a one standard deviation improvement in annual report readability corresponds to a reduction in the announcement CAR of approximately forty-three basis points, which is economically meaningful given that it constitutes roughly 27% of the sample average announcement CAR of -1.62%. Furthermore, additional analysis reveals that the informativeness enhancing effect that better annual report readability has on rating downgrades is stronger among firms that should be more difficult to monitor and evaluate, including lower rated firms, firms with high stock return volatility, and younger firms. Overall, the results strongly support the hypothesis that well-written annual reports facilitate more timely and informative bond rating downgrades, especially among more informationally problematic firms.
Using a large sample of bond rating downgrades of US firms announced by the three largest rating agencies during 1997-2023, I find that cumulative abnormal stock returns (CAR) spanning the day of and day following downgrade announcements are significantly and negatively related to annual report readability, indicating that downgrades are more informative among firms with more readable annual reports. My baseline regression results indicate that a one standard deviation improvement in annual report readability corresponds to a reduction in the announcement CAR of approximately forty-three basis points, which is economically meaningful given that it constitutes roughly 27% of the sample average announcement CAR of -1.62%. Furthermore, additional analysis reveals that the informativeness enhancing effect that better annual report readability has on rating downgrades is stronger among firms that should be more difficult to monitor and evaluate, including lower rated firms, firms with high stock return volatility, and younger firms. Overall, the results strongly support the hypothesis that well-written annual reports facilitate more timely and informative bond rating downgrades, especially among more informationally problematic firms.
This is a study about the financing of large group health insurance in the United States. Almost 8 in 10 covered employees in private large firms are enrolled in self-insured (or self-funded) health plans in contrast to only 20 percent of employees in small firms. More than half of all large standard (non-supplemental) health plans are self-insured although their number is decreasing. Considering their significantly greater risk of exposure and transaction costs, the question for scholarly investigation is why (and how) do private large firms self-fund employer-sponsored health insurance? Using plan-level data from health plan administrator filings of Forms 5500 and Summary Annual Reports (2014-2022) with the U.S. Department of Labor, six variables are examined in this study relative to large group self-insurance: industry/sectoral distribution, plan size/enrollment, plan administration, benefits coverage, plan assets and investments, and statutory compliance. Findings suggest that industry/sectoral and enrollee distributions of large health plans are not widely dispersed while their assets and investments and statutory exemptions offer comparative advantages. These plans have also increasingly relied on stop-loss insurance, third-party administration, supplemental health benefits, and less major medical plans to mitigate actuarial risks that involve considerable financial exposure to fluctuating claims costs, potential for catastrophic claims, and cash flow unpredictability. The intertwining theoretical and practical implications of large group self-insurance in healthcare finance and risk management are addressed by way of conclusion.
In the loanable funds theory, the interest rate serves as a balancing factor between the savings offered for loans and the funds borrowed for investment. In Keynes’s theory, by contrast, it is a monetary phenomenon that balances the demand and the supply of money. At first glance, the monetary phenomenon of the interest rate may seem quite different and is often considered groundbreaking and revolutionary. In Keynes’s theory, people hold part of their savings in money to cope with uncertainty about the returns from long-term bonds, and it is savings held in money that leads the interest rate to be a monetary phenomenon. While people hold part of their savings in money, they also invest their savings by purchasing long-term bonds. The interest rate also balances savings offered, though only in part and not the whole, and funds borrowed in the bond market, as in the loanable funds theory. In this regard, Keynes’s theory and the loanable funds theory are not as strikingly different as it may first appear. The main exegetical work of Keynes’s ideas is Keynesian economics. In this theory, the interest rate is also a monetary phenomenon, as is expected of exegetical work. However, it is not due to savings held in money as in Keynes’s theory; rather, it is due to the cash holdings required for purchasing goods and services. This paper examines the differences among these three interest rate theories, the reasons behind them, and their practical implications.
This paper examines the exchange rate pass-through (ERPT) and its impact on home inflation in Bangladesh, particularly in the post-pandemic era. Examining important economic factors including the nominal exchange rate (NER), money supply (M2), industrial production (IP), and global commodity index (GCI) using monthly data from January 2002 to August 2023 helps one to grasp their combined influence on consumer price inflation (CPI). By means of Johansen cointegration and Vector Error Correction Model (VECM) approaches, the study reveals important short-term and long-term dynamics. Contrary to patterns in many emerging nations, the results show that changes in exchange rates have apparently little impact on home prices. Rather, changes in the money supply and world commodities prices mostly influence inflation; the latter becomes a major factor. The study also exposes an unexpected positive link between industrial production and CPI, implying complexity in Bangladesh's production-driven economic structure. Moreover, this investigation underlines how complex monetary expansion, external commodities shocks, and devaluation of money interact to shape inflationary pressures. These results offer legislators important new perspectives and support strong monetary policies and focused involvement in world commodities markets to help to lower inflation. This study clarifies ERPT in developing countries and provides direction on inflation control techniques for Bangladesh.
Source coverage refers to this result set; a publication may occur in several sources. Sync times refer to contributing journals.
Missing abstracts: 0 · Missing authors: 0 · Missing publication dates: 0 · Dates without day precision: 0
| Source | Most recent successful journal sync | Latest attempt |
|---|---|---|
| crossref | 21 Oct 2026 00:21 UTC · ijfbs | complete · ijfbs · 21 Oct 2026 00:21 UTC |
| ojs-rest | 21 Oct 2026 00:21 UTC · ijfbs | complete · ijfbs · 21 Oct 2026 00:14 UTC |
| oai-pmh | 20 Oct 2026 19:56 UTC · ijfbs | complete · ijfbs · 20 Oct 2026 19:55 UTC |
| openalex-enrichment | 21 Oct 2026 00:22 UTC · ijfbs | complete · ijfbs · 21 Oct 2026 00:21 UTC |