Determinants of trade flow of some selected nontraditional agricultural export commodities in Nigeria

This study analysed the determinants of trade flow of some selected non-traditional agricultural export commodities in Nigeria, for the period 2007  to 2017. The objective of the study was to analyse the factors that determine the export of these commodities. The study used trade data of thirty-  six importing countries of these commodities around the world. The secondary data used was sourced from various institutions’ databases. A  balanced panel data from 36 countries for the years 2007-2017 were used with one dependent variable and ten explanatory variables (a total of  n=396, N=36, and T=11); all variables were expressed in natural logarithm. The gravity estimation model was used in data analysis. The Hausman  test was used in model selection and the test rejected the null hypothesis (random effects were efficient). Therefore, the fixed effects model was  used in the gravity model results’ interpretation. The gravity model results indicate that Nigeria’s export of non-traditional commodities (classified as  HS12 in the United Nations International Trade Statistics) follows the basic gravity model apriori expectations, implying that bilateral trade flows  will increase in proportion to the trading partner’s Gross Domestic Product (GDP) and decrease in proportion to the distance involved.The level of  openness of Nigeria’s economy and that of the importing countries were major determinants of trade flow of Nigeria’s HS12 commodity exports.  This variable carried the expected positive sign for both Nigeria and its trading Partners and was also statistically significant at the 5% level.  However, the real exchange rate variable was not a major determinant of HS12 commodity trade. The distance variable was statistically significant  indicating the need for regional trade expansion. The dummy variable of the trading partner being an African country was positive and a significant  factor in the determinants of the HS12 commodities. However, colonial or official language ties were negatively signed and significant, implying that  this was not a major contributor to trade in these commodities. The study recommends that favorable import and export promotion policies and  trade openness to boost growth in the quantity of non-traditional exports should form part of government trade policies; and Nigeria should also  take advantage of the proposed African Free Trade Area considering the gains she stands to make through proximity in distance.&nbsp

Determinants of livelihood diversification among farm households in Akamkpa Local Government Area, Cross River State, Nigeria

The study examined the determinants of livelihood diversification of farm households in Akamkpa Local Government Area, Cross River State, Nigeria. The specific objectives were to describe the socio-economic characteristics of respondents in the study area, identifying the factors influencing farm household livelihood diversification as well as to identify the constraints to farm household livelihood diversification. A multistage sampling technique was used in sampling the respondents. A set of validated questionnaire were used to gather data for the study while a total of 60 respondents were selected. Data were analyzed with both descriptive and inferential statistics. The study revealed that the majority (60%) were female, aged 20-30years, married (46%) and literate. The majority of them had household size ranging from 4-7 persons, engaged in farming (61.7%) and diversified to non-farm income. The result also revealed that (70%) of the respondents did not have access to credit. The factors influencing livelihood diversification among the farm households were volume of credit received, household size, farm size and marital status.. More so, the major constraints to livelihood diversification among them were unstable electricity (78.3%), poor access to market (65%), insufficient market price of commodity (58.3%), inadequate access to loan (51.7%), inadequate skilled labour (51.7%), high cost of business premises (51.7%) and appreciation in tax rate (51.7%).. The study recommends improved access to credit and strengthening of the credit institutional arrangement to improve the livelihoods of rural households.Keywords: Determinants, Farm, Households, Livelihood, Diversificatio

Market supply response of imported sardinella in Cross River State, Nigeria

This study was carried out to determine the market supply response of imported frozen sardinella in Cross River State, Nigeria. Secondary data used for the study were obtained from the records of the five wholesalecompanies in Cross River state. Cointegration and error correction models were used in analyzing market supply response. The following results were obtained; the short-run and long-run own price elasticity were 2.062 and 1.257 which were significant at the 5 percent and 1 percent levels respectively. The error correction coefficient Ect(-1) was - 1.536 which was significant at the 5 percent level. The own price long-run elasticity estimates were in accordance with a priori expectations. Adjustment from short-run towards long-run equilibrium was achieved instantaneously. Consequently, short-run elasticity estimates were found to be larger than those of the long-run. This study recommends the provision good distribution network to avert distortions in supply.KEY WORDS: Market Supply, Cointegration, Short Run, Long Run, Price Elasticity

Description and Cross-Sectional Analyses of 25,880 Adults and Children in the UK National Registry of Rare Kidney Diseases Cohort

Introduction The National Registry of Rare Kidney Diseases (RaDaR) collects data from people living with rare kidney diseases across the UK, and is the world’s largest, rare kidney disease registry. We present the clinical demographics and renal function of 25,880 prevalent patients and sought evidence of bias in recruitment to RaDaR. Methods RaDaR is linked with the UK Renal Registry (UKRR, with which all UK patients receiving kidney replacement therapy [KRT] are registered). We assessed ethnicity and socioeconomic status in the following: (i) prevalent RaDaR patients receiving KRT compared with patients with eligible rare disease diagnoses receiving KRT in the UKRR, (ii) patients recruited to RaDaR compared with all eligible unrecruited patients at 2 renal centers, and (iii) the age-stratified ethnicity distribution of RaDaR patients with autosomal dominant polycystic kidney disease (ADPKD) was compared to that of the English census. Results We found evidence of disparities in ethnicity and social deprivation in recruitment to RaDaR; however, these were not consistent across comparisons. Compared with either adults recruited to RaDaR or the English population, children recruited to RaDaR were more likely to be of Asian ethnicity (17.3% vs. 7.5%, P-value < 0.0001) and live in more socially deprived areas (30.3% vs. 17.3% in the most deprived Index of Multiple Deprivation (IMD) quintile, P-value < 0.0001). Conclusion We observed no evidence of systematic biases in recruitment of patients into RaDaR; however, the data provide empirical evidence of negative economic and social consequences (across all ethnicities) experienced by families with children affected by rare kidney diseases

The ASOS Surgical Risk Calculator: development and validation of a tool for identifying African surgical patients at risk of severe postoperative complications

Background: The African Surgical Outcomes Study (ASOS) showed that surgical patients in Africa have a mortality twice the global average. Existing risk assessment tools are not valid for use in this population because the pattern of risk for poor outcomes differs from high-income countries. The objective of this study was to derive and validate a simple, preoperative risk stratification tool to identify African surgical patients at risk for in-hospital postoperative mortality and severe complications. Methods: ASOS was a 7-day prospective cohort study of adult patients undergoing surgery in Africa. The ASOS Surgical Risk Calculator was constructed with a multivariable logistic regression model for the outcome of in-hospital mortality and severe postoperative complications. The following preoperative risk factors were entered into the model; age, sex, smoking status, ASA physical status, preoperative chronic comorbid conditions, indication for surgery, urgency, severity, and type of surgery. Results: The model was derived from 8799 patients from 168 African hospitals. The composite outcome of severe postoperative complications and death occurred in 423/8799 (4.8%) patients. The ASOS Surgical Risk Calculator includes the following risk factors: age, ASA physical status, indication for surgery, urgency, severity, and type of surgery. The model showed good discrimination with an area under the receiver operating characteristic curve of 0.805 and good calibration with c-statistic corrected for optimism of 0.784. Conclusions: This simple preoperative risk calculator could be used to identify high-risk surgical patients in African hospitals and facilitate increased postoperative surveillance. © 2018 British Journal of Anaesthesia. Published by Elsevier Ltd. All rights reserved.Medical Research Council of South Africa gran