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.
Research across participating journals · All insights follow your collection filters.
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: 4 / 4 publications (100.0%). Latest observation: 21 Oct 2026, 07:22 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: 21 Oct 2026 00:14 UTC — 21 Oct 2026 07:22 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 |
|---|---|---|---|---|---|
| 2022 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2023 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2024 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2025 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2026 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2022 | All selected publications | 2 | 1 | 1/1 | 1/1 |
| 2023 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2024 | All selected publications | 7 | 1 | 1/1 | 1/1 |
| 2025 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2026 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2022 | All selected publications | 2 | 1 | 1/1 | 1/1 |
| 2023 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2024 | All selected publications | 5 | 1 | 1/1 | 1/1 |
| 2025 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2026 | All selected publications | 0 | 1 | 1/1 | 1/1 |
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): 2026-10-21T00:14:29.326932+00:00 — 2026-10-21T07:22:47.394903+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 | 1 | 4 | 4/4 |
| 2024 | All selected publications | 3 | 4 | 4/4 |
| 2025 | All selected publications | 1 | 4 | 4/4 |
| 2026 | All selected publications | 3 | 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 |
|---|---|
| 2022 | 1 |
| 2023 | 1 |
| 2024 | 1 |
| 2026 | 1 |
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 Business Ecosystem & Strategy Bussecon International Academy | 2 | 7 | 5 | 2/2 | 3.5 | 3.5 | 50.0 | 2/2 · 100.0% |
| International Journal of Research in Business and Social Science SSBFNET | 2 | 2 | 3 | 2/2 | 1.0 | 1.0 | 50.0 | 2/2 · 100.0% |
* Percentage among publications with a known citation count.
Over the years, there have been huge variations in the growth performances of the economies in SSA. Whilst these disparities can be attributed to a wide range of factors, it is generally understood that differences in their economic structures explain the capacity for generating growth and absorbing shocks during a recession. This study contributes to literature by examining the impact of institutional quality and financial development on economic growth in low- and middle-income countries. Data was obtained from the World Bank and covered the period from 1975 to 2020. The study employed an ARDL model to establish both short and long run dynamics in the two sub samples. The study confirmed both short and long run causality from financial and institutional quality to growth. Institutional quality enhances growth in both low- and middle-income countries in the long run. Whilst the direction of the impact is the same, the magnitude of the impact of institutional quality is different within the two categories. Institutional quality plays a more significant role in low-income countries compared to middle income economies. The study brings out potential financial fragility and systemic risks in financial institutions among countries in SSA. Policies that enhance the quality, consistency, and uniformity of legal reasoning in judicial decisions are ideal. Reducing the risk profile for investments may enhance the flow of credit to the private sector by financial institutions.
This paper explores the inter-connectedness of remittances and financial development and how their associated covariates such as savings, investment, money supply and economic growth are impacted by this relationship. The study employs a panel vector autoregression (P-VAR) estimation technique, and the generalized methods of moments (GMM) are applied after removing fixed effects and lagged regressors are used as instruments to have consistent estimators. The main findings of the study demonstrate that (i) remittances and financial development have a feedback interrelationship, and some interlinkages are identified amongst their covariates, (ii) economic growth has a dual connection with financial development and that (iii) savings, investment, and broad money supply influence both financial development and remittances. These findings contribute to current discussions in the literature as they support the importance of deepening financial markets in SSA, and attracting more remittances. The significant role played by the diaspora in improving domestic financial depth is confirmed. Progression in SSA economic growth helps to stimulate those in the diaspora to repatriate most of their earnings back home.
This study examines the relationship between government expenditure on health and economic growth in Botswana. It seeks to test the existence of cointegration and specification of the deterministic components with special reference to the Pantula Principle. This helps to overcome the shortfall of the method by Johansen, which may lead to spurious results by omitting the presence of deterministic components in the analysis. The cointegration approach is used and tested using three methods by Engle and Granger (1987) or EG, a procedure suggested by Johansen (1988) and error correction model (ECM) approach proposed by Granger(1988) and short-run analysis is made using the pairwise granger causality tests. Findings show that the correct model specification for testing long-run relationships consists of one cointegrating vector with a constant which is the most restrictive hypothesis according to the Pantula principle. Using the Johansen approach, total health expenditure and recurring health expenditure have a cointegration relationship with growth while development health expenditure and growth are not cointegrated. The ECM and the approach by EG confirm a weak and/or no cointegration between the variables. Growth has no effect on government expenditure on health in the short run, but a cointegration relationship suggests that it may marginally contribute to an increase in health expenditure over the long term. The study clarifies the correct model to test for cointegration and specification for the deterministic component. It confirms the existence of a healthcare expenditure-led growth hypothesis. This requires Botswana to design a policy that targets specific parts of recurrent and development health expenditure to support human capital development and influence future growth.
The reduction in rural marginalization of infrastructure in Africa has been achieved through the wide diffusion of the so-called fiscal deviation. According to New Institutional Economics, the provision of public resourcing at the local level is more economic since it meets the geographic specificity of infrastructure provisions. However, when intergovernmental fiscal transfers are towards rural road provision, it is majorly because of several structural impediments, that the corrected road will not be realized. This systematic review of literature with regards to devolution and infra-structure provision has laid emphasis on going beyond overly simplistic input-output models to explore the multiple filters regulating decentralized public works. The focus here is on institutional capacity as a crucial explanatory factor and the way deficits in technical engineering, equipment maintenance, and procurement governance conspire to undermine the potency of devolved funding. Moreover, the study discusses the moderating effects in the face of instability in the broader economy, illustrating how hyper-inflation and currency depreciation can deplete real infrastructure funds purchasing power and result in the erosion of the contractor attrition as observed. Finally, the review has identified systemic barriers, such as climate vulnerability and ministerial red-tape friction. The synthesis of empirical literature from 2010 to 2024 suggests that fiscal decentralisation without a built institutional capacity and insulated mechanisms against macroeconomic turbulence cannot deliver in the long run.
The reduction in rural marginalization of infrastructure in Africa has been achieved through the wide diffusion of the so-called fiscal deviation. According to New Institutional Economics, the provision of public resourcing at the local level is more economic since it meets the geographic specificity of infrastructure provisions. However, when intergovernmental fiscal transfers are towards rural road provision, it is majorly because of several structural impediments, that the corrected road will not be realized. This systematic review of literature with regards to devolution and infra-structure provision has laid emphasis on going beyond overly simplistic input-output models to explore the multiple filters regulating decentralized public works. The focus here is on institutional capacity as a crucial explanatory factor and the way deficits in technical engineering, equipment maintenance, and procurement governance conspire to undermine the potency of devolved funding. Moreover, the study discusses the moderating effects in the face of instability in the broader economy, illustrating how hyper-inflation and currency depreciation can deplete real infrastructure funds purchasing power and result in the erosion of the contractor attrition as observed. Finally, the review has identified systemic barriers, such as climate vulnerability and ministerial red-tape friction. The synthesis of empirical literature from 2010 to 2024 suggests that fiscal decentralisation without a built institutional capacity and insulated mechanisms against macroeconomic turbulence cannot deliver in the long run.
Over the years, there have been huge variations in the growth performances of the economies in SSA. Whilst these disparities can be attributed to a wide range of factors, it is generally understood that differences in their economic structures explain the capacity for generating growth and absorbing shocks during a recession. This study contributes to literature by examining the impact of institutional quality and financial development on economic growth in low- and middle-income countries. Data was obtained from the World Bank and covered the period from 1975 to 2020. The study employed an ARDL model to establish both short and long run dynamics in the two sub samples. The study confirmed both short and long run causality from financial and institutional quality to growth. Institutional quality enhances growth in both low- and middle-income countries in the long run. Whilst the direction of the impact is the same, the magnitude of the impact of institutional quality is different within the two categories. Institutional quality plays a more significant role in low-income countries compared to middle income economies. The study brings out potential financial fragility and systemic risks in financial institutions among countries in SSA. Policies that enhance the quality, consistency, and uniformity of legal reasoning in judicial decisions are ideal. Reducing the risk profile for investments may enhance the flow of credit to the private sector by financial institutions.
This study examines the relationship between government expenditure on health and economic growth in Botswana. It seeks to test the existence of cointegration and specification of the deterministic components with special reference to the Pantula Principle. This helps to overcome the shortfall of the method by Johansen, which may lead to spurious results by omitting the presence of deterministic components in the analysis. The cointegration approach is used and tested using three methods by Engle and Granger (1987) or EG, a procedure suggested by Johansen (1988) and error correction model (ECM) approach proposed by Granger(1988) and short-run analysis is made using the pairwise granger causality tests. Findings show that the correct model specification for testing long-run relationships consists of one cointegrating vector with a constant which is the most restrictive hypothesis according to the Pantula principle. Using the Johansen approach, total health expenditure and recurring health expenditure have a cointegration relationship with growth while development health expenditure and growth are not cointegrated. The ECM and the approach by EG confirm a weak and/or no cointegration between the variables. Growth has no effect on government expenditure on health in the short run, but a cointegration relationship suggests that it may marginally contribute to an increase in health expenditure over the long term. The study clarifies the correct model to test for cointegration and specification for the deterministic component. It confirms the existence of a healthcare expenditure-led growth hypothesis. This requires Botswana to design a policy that targets specific parts of recurrent and development health expenditure to support human capital development and influence future growth.
This paper explores the inter-connectedness of remittances and financial development and how their associated covariates such as savings, investment, money supply and economic growth are impacted by this relationship. The study employs a panel vector autoregression (P-VAR) estimation technique, and the generalized methods of moments (GMM) are applied after removing fixed effects and lagged regressors are used as instruments to have consistent estimators. The main findings of the study demonstrate that (i) remittances and financial development have a feedback interrelationship, and some interlinkages are identified amongst their covariates, (ii) economic growth has a dual connection with financial development and that (iii) savings, investment, and broad money supply influence both financial development and remittances. These findings contribute to current discussions in the literature as they support the importance of deepening financial markets in SSA, and attracting more remittances. The significant role played by the diaspora in improving domestic financial depth is confirmed. Progression in SSA economic growth helps to stimulate those in the diaspora to repatriate most of their earnings back home.
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 07:22 UTC · ijrbs | complete · ijrbs · 21 Oct 2026 07:22 UTC |
| ojs-rest | 21 Oct 2026 07:22 UTC · ijrbs | complete · ijrbs · 21 Oct 2026 06:46 UTC |
| oai-pmh | 20 Oct 2026 19:55 UTC · ijrbs | complete · ijrbs · 20 Oct 2026 19:50 UTC |
| openalex-enrichment | 21 Oct 2026 07:23 UTC · ijrbs | complete · ijrbs · 21 Oct 2026 07:22 UTC |