Income diversification and financial performance : should banks trade?

Purpose: The purpose of this study is to examine the effect of income diversification on the financial performance of commercial banks in Kenya. Design/methodology/approach: The study used a sample of 31 commercial banks and panel data for the period 2008-2017. Data was extracted from the individual bank’s financial reports and the Central Bank of Kenya’s bank supervision annual reports. The data was analyzed through descriptive and inferential statistics, while the hypothesis was tested using fixed effect regression based on the results of the Hausman test. Financial performance was measured as return on assets (ROA), while Herfindahl-Hirschman Index (HHI) was used to measure income diversification. The study controlled for firm size, firm age and lending strategy. Findings: The findings indicated that income diversification had a positive and significant effect on banks’ financial performance in Kenya. The control variables had varied effects; firm size had a positive effect, while firm age and lending strategy had a negative effect. Practical implications: The article offers insights to bank managers and the regulator. First managers should consider an optimal level of diversification to compensate for the deteriorating interest revenue. Second, the regulator should relax laws that limit the extent banks can diversify their revenue streams. Originality/value: Unlike previous studies which focused on developed and emerging economies, this study centered on a developing economy, and the findings are consistent with the propositions of the modern portfolio theory.peer-reviewe

An Empirical Test of the Relationship between Private Savings and Economic Growth: A Case Study of Kenya

The study aims at investigating the long run and short run relationships between private savings and economic growth in Bahrain. The study covers the period (1990-2013).The study methodology is based on the econometrics analytical approach to estimate the parameters’ value and the trends of the economic relations between the study variables by using the co-integration and Granger causality techniques. Johansen co-integration test indicates that a positive long run relationship between the study variables, while Granger causality test reveals that significant bilateral causality between the private savings and the economic growth, this means that the economic growth Granger causes the private saving, and also the private savings Granger cause the economic growth. These results indicate that the economic growth could stimulate the private saving, and the private savings could accelerate the economic growth in the long run. The study recommends that government and policy makers in the kingdom of Bahrain should employ policies that would attract more private savings in order to accelerate economic growth which would lead to raise GDP per capita and Bahraini standard of living. Keyword: Private Savings, Economic growth, Econometrics, Kingdom of Bahrain

Understanding abortion-related stigma and incidence of unsafe abortion: experiences from community members in Machakos and Trans Nzoia counties Kenya

Introduction: The rate of unsafe abortions in Kenya has increased from 32 per 1000 women of reproductive age in 2002 to 48 per 1000 women in 2012. This is one of the highest in Sub-Saharan Africa. In 2010, Kenya changed its Constitution to include a more enabling provision regarding the provision of abortion services. Abortion-related stigma has been identified as a key driver in silencing women's ability to reproductive choice leading to seeking to unsafe abortion. We sought to explore abortion-related stigma at the community level as a barrier to women realizing their rights to a safe, legal abortion and compare manifestations of abortion stigma at two communities from regions with high and low incidence of unsafe abortion. Methods: A qualitative study using 26 focus group discussions with general community members in Machakos and Trans Nzoia Counties. We used thematic and content analysis to analyze and compare community member's responses regarding abortion-related stigma. Results: Although abortion is recognized as being very common within communities, community members expressed various ways that stigmatize women seeking an abortion. This included being labeled as killers and are perceived to be a bad influence for women especially young women. Women reported that they were poorly treated by health providers in health facilities for seeking abortion especially young unmarried women. Institutionalization of stigma especially when Ministry of Health withdrew of standards and guidelines only heightened how stigma presents at the facilities and drives women seeking an abortion to traditional birth attendants who offer unsafe abortions leading to increased morbidity and mortality as a result of abortion-related complications. Conclusion: Community members located in counties in regions with high incidence of unsafe abortion also reported higher levels of how they would stigmatize a woman seeking an abortion compared to community members from counties in low incidence region. Young unmarried women bore the brunt of being stigmatized. They reported a lack of a supportive environment that provides guidance on correct information on how to prevent unwanted pregnancy and where to get help. Abortion-related stigma plays a major role in women's decision on whether to have a safe or unsafe abortion.Pan African Medical Journal 2016; 2

Exploring Dynamic Asset Pricing within Bachelier Market Model

This paper delves into the dynamics of asset pricing within Bachelier market model, elucidating the representation of risky asset price dynamics and the definition of riskless assets

Does the ‘Process’ of Process Capital Matter to Performance? Evidence from Kenyan Commercial Banks

Globalization, changing customer expectation and shrinking product life-cycle depict process capital as a source of competitive advantage in modern economies. Consequently, organizations are gradually becoming more process oriented to cope with a dynamic environment. However, the process capital and performance causality is scanty in extant literature. Besides, previous studies overlooked the process aspect of process capital. Thus, the objective of this study was to determine whether the “process” of process capital matters to firm performance. The hypothesis was tested using panel data for the years 2008-2017 extracted from 31 commercial banks in Kenya. The findings showed that process capital had a positive and significant effect on performance (β = 0.275, ρ-value 0.000<0.05). Consistent with the resource based view theory; the study concluded that the process of process capital influences firm performance

Where Are the Newly Diagnosed HIV Positives in Kenya? Time to Consider Geo-Spatially Guided Targeting at a Finer Scale to Reach the “First 90”

Background: The UNAIDS 90-90-90 Fast-Track targets provide a framework for assessing coverage of HIV testing services (HTS) and awareness of HIV status – the “first 90.” In Kenya, the bulk of HIV testing targets are aligned to the five highest HIV-burden counties. However, we do not know if most of the new HIV diagnoses are in these five highest-burden counties or elsewhere. Methods: We analyzed facility-level HTS data in Kenya from 1 October 2015 to 30 September 2016 to assess the spatial distribution of newly diagnosed HIV-positives. We used the Moran's Index (Moran's I) to assess global and local spatial auto-correlation of newly diagnosed HIV-positive tests and Kulldorff spatial scan statistics to detect hotspots of newly diagnosed HIV-positive tests. For aggregated data, we used Kruskal-Wallis equality-of-populations non-parametric rank test to compare absolute numbers across classes. Results: Out of 4,021 HTS sites, 3,969 (98.7%) had geocodes available. Most facilities (3,034, 76.4%), were not spatially autocorrelated for the number of newly diagnosed HIV-positives. For the rest, clustering occurred as follows; 438 (11.0%) were HH, 66 (1.7%) HL, 275 (6.9%) LH, and 156 (3.9%) LL. Of the HH sites, 301 (68.7%) were in high HIV-burden counties. Over half of 123 clusters with a significantly high number of newly diagnosed HIV-infected persons, 73(59.3%) were not in the five highest HIV-burden counties. Clusters with a high number of newly diagnosed persons had twice the number of positives per 1,000,000 tests than clusters with lower numbers (29,856 vs. 14,172). Conclusions: Although high HIV-burden counties contain clusters of sites with a high number of newly diagnosed HIV-infected persons, we detected many such clusters in low-burden counties as well. To expand HTS where most needed and reach the “first 90” targets, geospatial analyses and mapping make it easier to identify and describe localized epidemic patterns in a spatially dispersed epidemic like Kenya's, and consequently, reorient and prioritize HTS strategies.publishedVersio

Where Are the Newly Diagnosed HIV Positives in Kenya? Time to Consider Geo-Spatially Guided Targeting at a Finer Scale to Reach the “First 90”

Background: The UNAIDS 90-90-90 Fast-Track targets provide a framework for assessing coverage of HIV testing services (HTS) and awareness of HIV status – the “first 90.” In Kenya, the bulk of HIV testing targets are aligned to the five highest HIV-burden counties. However, we do not know if most of the new HIV diagnoses are in these five highest-burden counties or elsewhere. Methods: We analyzed facility-level HTS data in Kenya from 1 October 2015 to 30 September 2016 to assess the spatial distribution of newly diagnosed HIV-positives. We used the Moran's Index (Moran's I) to assess global and local spatial auto-correlation of newly diagnosed HIV-positive tests and Kulldorff spatial scan statistics to detect hotspots of newly diagnosed HIV-positive tests. For aggregated data, we used Kruskal-Wallis equality-of-populations non-parametric rank test to compare absolute numbers across classes. Results: Out of 4,021 HTS sites, 3,969 (98.7%) had geocodes available. Most facilities (3,034, 76.4%), were not spatially autocorrelated for the number of newly diagnosed HIV-positives. For the rest, clustering occurred as follows; 438 (11.0%) were HH, 66 (1.7%) HL, 275 (6.9%) LH, and 156 (3.9%) LL. Of the HH sites, 301 (68.7%) were in high HIV-burden counties. Over half of 123 clusters with a significantly high number of newly diagnosed HIV-infected persons, 73(59.3%) were not in the five highest HIV-burden counties. Clusters with a high number of newly diagnosed persons had twice the number of positives per 1,000,000 tests than clusters with lower numbers (29,856 vs. 14,172). Conclusions: Although high HIV-burden counties contain clusters of sites with a high number of newly diagnosed HIV-infected persons, we detected many such clusters in low-burden counties as well. To expand HTS where most needed and reach the “first 90” targets, geospatial analyses and mapping make it easier to identify and describe localized epidemic patterns in a spatially dispersed epidemic like Kenya's, and consequently, reorient and prioritize HTS strategies

Kericho CLinic-Based ART Diagnostic Evaluation (CLADE): Design, Accrual, and Baseline Characteristics of a Randomized Controlled Trial Conducted in Predominately Rural, District-Level, HIV Clinics of Kenya

<div><p>Background</p><p>Prospective clinical trial data regarding routine HIV-1 viral load (VL) monitoring of antiretroviral therapy (ART) in non-research clinics of Sub-Saharan Africa are needed for policy makers.</p><p>Methods</p><p><u>CL</u>inic-based <u>A</u>RT <u>D</u>iagnostic <u>E</u>valuation (CLADE) is a randomized, controlled trial (RCT) evaluating feasibility, superiority, and cost-effectiveness of routine VL vs. standard of care (clinical and immunological) monitoring in adults initiating dual nucleoside reverse transcriptase inhibitor (NRTI)+non-NRTI ART. Participants were randomized (1:1) at 7 predominately rural, non-research, district-level clinics of western Kenya. Descriptive statistics present accrual patterns and baseline cohort characteristics.</p><p>Results</p><p>Over 15 months, 820 adults enrolled at 7 sites with 86–152 enrolled per site. Monthly site enrollment ranged from 2–92 participants. Full (100%) informed consent compliance was independently documented. Half (49.9%) had HIV diagnosed through voluntary counseling and testing. Study arms were similar: mostly females (57.6%) aged 37.6 (SD = 9.0) years with low CD4 (166 [SD = 106]) cells/m³). Notable proportions had WHO Stage III or IV disease (28.7%), BMI <18.5 kg/m² (23.1%), and a history of tuberculosis (5.6%) or were receiving tuberculosis treatment (8.2%) at ART initiation. In the routine VL arm, 407/409 (99.5%) received baseline VL (234,577 SD = 151,055 copies/ml). All participants received lamivudine; 49.8% started zidovudine followed by 38.4% stavudine and 11.8% tenofovir; and, 64.4% received nevirapine as nNRTI (35.6% efavirenz).</p><p>Conclusions</p><p>A RCT can be enrolled successfully in rural, non-research, resource limited, district-level clinics in western Kenya. Many adults presenting for ART have advanced HIV/AIDS, emphasizing the importance of universal HIV testing and linkage-to-care campaigns.</p><p>Trial Registration</p><p>ClinicalTrials.gov <a href="https://clinicaltrials.gov/ct2/show/NCT01791556" target="_blank">NCT01791556</a></p></div

Baseline Characteristics of the CLinic-based ART Diagnostic Evaluation (CLADE) Trial Participants.

<p>Notes:</p><p>1. Data presented as mean (SD) or n (%)</p><p>2. Two participants who were randomized but did not continue ART are excluded.</p><p>3. Categorical grades based upon the DAIDS Toxicity tables: Grade 1 = mild, Grade 2 = moderate, Grade 3 = severe, Grade 4 = potentially life-threatening</p><p>4. Abbreviations: VCT = Voluntary Counseling and Testing, DTC = Diagnostic Testing and Counseling, PITC = Provider Initiated Testing and Counseling; Tb = tuberculosis, PMTCT = Prevention of Mother to Child Transmission, TMP/SMX = trimethoprim/sulfamethoxazole, D4T = stavudine, 3TC = lamivudine, NVP = nevirapine, EFV = efavirenz, AZT = zidovudine, TDF = tenofovir</p><p>Baseline Characteristics of the CLinic-based ART Diagnostic Evaluation (CLADE) Trial Participants.</p

Effect of universal test-and-treat uptake, defined as same day, 1–14 days, 15–90 days and 91+ days from a HIV diagnosis to combination antiretroviral therapy start on twelve months attrition, defined as lost to follow up or dead, amongst HIV infected adults captured in the national data warehouse in Kenya (2015HY2 to 2018HY1, N = 8592).

Effect of universal test-and-treat uptake, defined as same day, 1–14 days, 15–90 days and 91+ days from a HIV diagnosis to combination antiretroviral therapy start on twelve months attrition, defined as lost to follow up or dead, amongst HIV infected adults captured in the national data warehouse in Kenya (2015HY2 to 2018HY1, N = 8592).</p