The Development of Accounting in Africa in the Era of International Financial Reporting Standards

This thesis consists of two separate, but related studies on the development of accounting in Africa in the era of International Financial Reporting Standards. The first part of this thesis presents the first empirical test of a hypothetical classification of financial reporting in Africa based on de facto or actual practices as opposed to de jure rules. Three multivariate techniques (principal component analysis, cluster analysis, and multidimensional scaling) were used to analyse the accounting policies of large, listed companies in Africa that are required by law to adopt IFRS. It was found that there is a dichotomy between the IFRS policy choices of companies in Francophone and Lusophone countries, on the one hand, and those in common law jurisdictions, on the other, thus confirming the two-group classification schemes proposed by Elad (2015) and Nobes (1983). The results of this study extend previous research by demonstrating that international differences in financial reporting in Africa have survived in the era of IFRS and that pre-IFRS regulations enshrined in national and regional charts of account appear to have influenced IFRS policy choice. Furthermore, companies in common law countries tend to provide more extensive disclosures in their IFRS financial statements than their counterparts in code law countries. These findings have important policy implications, particularly in the context of recent recommendations of the World Bank, the International Monetary Fund, and the Pan-African Federation of Accountants that large entities in Africa adopt IFRS. The systematic differences in the choice of IFRS options between companies in civil law and common law jurisdictions suggest that it would be difficult to achieve internationalcomparability and consistency in financial reporting. The second part of the study uses semi structured telephone interviews to undertake interpretive accounting research (Baker and Bettner, 1997, p.293) to assess the perception of accounting professionals in relation to IFRS adoption and its use in Ghana. It concludes that despite the problems associated with its adoption and implementation, overall, International Financial Reporting Standards are viewed as necessary for the financial reporting needs of the country

The Impact of NAFTA on Agricultural Commodity Trade: A Partial Equilibrium Analysis.

This paper examines the effects of the North American Free Trade Agreement on agricultural commodity trade using extensive data. The data cover agricultural exports and imports between the U.S. and NAFTA partners over the extended period of 1989-2010. The commodities covered in our analyses include; corn, soy bean, cotton, wheat, fresh vegetables, poultry, dairy products, and red meats. Since the signing of the agreement, U.S. total agricultural commodity trade with NAFTA members has increased three-fold from $18 billion in 1994 to$61 billion in 2010. A partial equilibrium model, in which we derive each trading partner's excess demand and excess supply, is used to study the impact of NAFTA on trade, controlling for other trade-inducing variables such as exchange rates, tariffs, per capita incomes, and relative prices. Regression results show mixed effects of NAFTA on different commodities while graphical and counterfactual analyses indicate strictly positive effects.NAFTA, Agricultural commodities, trade, partial equilibrium analysis, Agribusiness, Agricultural and Food Policy, Crop Production/Industries, International Relations/Trade, Marketing,

Impact of Subsidies Across Alabama Counties: An Econometric Interpretation

Fixed effect time series effect models are used to analyze the spatial and time series pattern of the effects of subsidies on manufacturing income across twenty counties in Alabama from 1970 to 1999. The results from the fixed effect model indicate that median populated counties performed better than larger and smaller counties while the time series effect model indicates that the impact of subsidies is marginal across the state over time.Agricultural and Food Policy,

Chinese Market Access Barriers of U.S Oilseeds and Grains

China was admitted into the WTO in December 2001 and this raised the hopes of the US that China will open up to agricultural trade with the US. However, this potential has not been realized. The goal of this study is to determine the impacts of trade impediments and barriers of the market access of US oilseeds and grains in China. A market access variable that was obtained by dividing the total value of U.S soybean and corn exports to China by U.S agricultural G.D.P was regressed on China’s per capita income, exchange rate of the yuan to the dollar, arable land to labor ratio in the U.S and a dummy variable representing China’s WTO accession. The result found per capita income to have a positive impact on market access of U.S oilseeds and grains in China. Exchange rate of the yuan to the dollar was found to be significant and has a negative impact on market access. However, China’s WTO accession and the arable land to labor ratio in the U.S did not have any significance on the market access of U.S oilseeds and grains.Market Access, Market Access Barriers, U.S Oil seeds and Grains, Import, International Development, International Relations/Trade,

Impact of Expanded United States Sugar Imports from CAFTA Countries on the Ethanol Market

The need to decrease the United States’ dependency on oil has pushed ethanol to the forefront of energy sources. In the U.S., corn is used to make ethanol. Corn-based ethanol production has been profitable over the past few years, but there has been a near doubling of corn prices in late 2006 and early 2007 (Outlaw, et. al., 2007). The trend is a constant rise in prices, which has given way to ethanol production by other sources of raw materials like sugarcane. Sugarcane ethanol is the most cost-efficient biofuel available anywhere in the world, and in the United States, the government supports sugar prices. Through the US sugar policy, sugar prices are controlled, and foreign imports are severely limited. Brazil is leading the way in sugarcane ethanol, and its neighbors in Central America are following suit. In 2006, the Central American Free Trade Agreement (CAFTA) was established. The agreement allows sugar imports into the U.S. from these countries duty free. Those countries have extreme ethanol growth potential with low production costs and large sources of sugarcane. This paper uses GIS and statistical tools to determine the impact of the expanded U.S. sugar imports from CAFTA-DR countries on the U.S. ethanol market in terms of production and regional concentration. To estimate the relationship between ethanol production and sugar imports, an OLS regression model has been developed with monthly U.S. ethanol production as a function of imported sugarcane, gas, ethanol , and corn prices; covering January 2000 to September 2008.Ethanol, Sugarcane, Sugar, CAFTA-DR, Alternative Fuels, Biofuels, International Relations/Trade,

The Trade Effects of MERCOSUR and The Andean Community on U.S. Cotton Exports to CBI countries

The United States engagement in nonreciprocal preferential trade arrangements has been proliferating with several developing countries throughout the past couple of decades. One of the oldest and more successful of these arrangements has been the Caribbean Basin Initiative (CBI).The CBI is a general term used to refer to the Caribbean Basin Economic Recovery Act of 1983 (CBERA), the Caribbean Basin Economic Recovery Expansion Act of 1990 (CBERA Expansion Act), and the Caribbean Basin Trade Partnership of 2000 (CBTPA) (Ozden and Sharma 2006). The central premise behind the plan was that, by encouraging the CBI countries to become more open and liberal, trade would expand – and eventually translate into economic development and growth (Deere, 1990). The partnership between the U.S. and the CBI provides duty and quota free treatment for 1) textile and apparel products assembled from U.S. fabric in CBI beneficiary countries from U.S. fabric and 2) yarn and apparel assembled from CBI regional fabric, subject to a quantitative limit which increases over time. Cotton is a major commodity for the U.S. generating about $4-5 billion in annual cash receipts (Dodson 1995). Furthermore, cotton is a major raw material for the textile and apparel industries creating heavy dependence by these industries on cotton production. The demand for raw fiber is derived from consumer demand for textile products where cotton is an important textile fiber (Marseli and Epperson, 2002). This paper analyzes the effects these regional trade agreements have on CBI countries cotton imports from US by calculating the associated trade creation and trade diversion values.Panel data, trade diversion, trade creation, CBI, cotton imports, Agricultural and Food Policy, International Relations/Trade,

Black Voices Matter: Racial Trauma, Challenging Systemic Oppression and Shifting the Narrative

As educational psychologists (EPs), we are driven by improving outcomes and opportunities for children and young people. The resurgence of the “Black Lives Matter” movement prompted us to reflect on issues relating to the impact of systemic racism in the UK, experiences of EPs from Black and minority ethnic backgrounds, and the role of the EP in challenging the dominant narrative. This paper will discuss the current social climate, specifically anti-Black racism and how this may lead to experiences of racial trauma among Black people. We will also discuss institutional racism in systems including education and its link to the school to prison pipeline. Professional and personal reflections will be shared, as well as thoughts about working in a predominantly White profession. Throughout this piece, the authors will be keeping in mind the lived experience of children and reflecting on how the issues discussed, can relate to EP practice

FTAA AND NORTH CAROLINA: INCOME REDISTRIBUTION ACROSS LABOR GROUPS

The specific factors model was used to determine potential adjustments due to FTAA on income redistribution among skilled labor groups in North Carolina. All wages but agriculture and manufacture labor are projected to rise. Returns to capital in service will increase while returns to capital in agriculture and manufacture fall.Labor and Human Capital,

Automatic Optimum Atlas Selection for Multi-Atlas Image Segmentation using Joint Label Fusion

Multi-atlas image segmentation using label fusion is one of the most accurate state of the art image segmentation techniques available for biomedical imaging applications. Motivated to achieve higher image segmentation accuracy, reduce computational costs and a continuously increasing atlas data size, a robust framework for optimum selection of atlases for label fusion is vital. Although believed not to be critical for weighted label fusion techniques by some works (Sabuncu, M. R. et al., 2010, [1]), others have shown that appropriate atlas selection has several merits and can improve multi-atlas image segmentation accuracy (Aljabar et al., 2009, [2], Van de Velde et al., 2016) [27]. This thesis proposed an automatic Optimum Atlas Selection (OAS) framework pre-label fusion step that improved image segmentation performance dice similarity scores using Joint Label Fusion (JLF) implementation by Wang et al, 2013, [3, 26]. A selection criterion based on a global majority voting fusion output image similarity comparison score was employed to select an optimum number of atlases out of all available atlases to perform the label fusion step. The OAS framework led to observed significant improvement in aphasia stroke heads magnetic resonance (MR) images segmentation accuracy in leave-one out validation tests by 1.79% (p = 0.005520) and 0.5% (p = 0.000656) utilizing a set of 7 homogenous stroke and 19 inhomogeneous atlas datasets respectively. Further, using comparatively limited atlas data size (19 atlases) composed of normal and stroke head MR images, t-tests showed no statistical significant difference in image segmentation performance dice scores using the proposed OAS protocol compared to using known automatic Statistical Parametric Mapping (SPM) plus a touchup algorithm protocol [4] for image segmentation (p = 0.49417). Thus, leading to the conclusions that the proposed OAS framework is an effective and suitable atlas selection protocol for multi-atlas image segmentation that improves brain MR image segmentation accuracy. It is comparably in performance to known image segmentation algorithms and can lead to reduced computation costs in large atlas data sets. With regards to future work, efforts to increase atlas data size and use of a more robust approach for determining the optimum selection threshold value and corresponding number of atlases to perform label fusion process can be explored to enhance overall image segmentation accuracy. Furthermore, for an unbiased performance comparison of the proposed OAS framework to other image segmentation algorithms, truly manually segmented atlas ground truth MR images and labels are needed

Estimating the Returns to Schooling: A Comparison of Fixed Effects and Selection Effects Models for Twins

Strong empirical links exist between the number of years spent schooling and earnings. How­ever, the relationship may be masked due to the effect of unobserved factors that influence both wages and schooling. Two of the main econometric models, namely fixed-effects and se­lection-effects, used to analyse returns to schooling were compared using monozygotic and di­zygotic twins’ datasets in Ghana. The efficiency of the models was assessed based on the stan­dard errors associated with the return to schooling estimates. Goodness of fit measures was used as a basis for comparison of the performance of the two models. The results revealed that based on their standard errors, the regression estimates from the selection effects model (MZ = 0.1014±0.0197; DZ = 0.0947±0.0095) were more efficient than the regression estimates from the fixed-effects model (MZ = 0.1115±0.0353; DZ = 0.082±0.0127). However, the AICc values of the fixed effects model (MZAICc = 57.8 and DZAICc = 105.4) were smaller than the AICc values of the selection effects model (MZAICc = 151.6 and DZAICc = 221.6). Findings from the study indicate that, although both models produced consistent estimates of the economic returns to schooling, the fixed effects model provided a better fit to the twins’ data set