With the rising climate change concerns, there have been contrasting arguments regarding the effect of economic activities on carbon emissions in a nation. The study adopted the econometric models, the Pairwise Granger Causality test, and the Autoregressive Distributed Lag model (ARDL). The ARDL bounds test for co-integration indicated that carbon emission and economic growth in Nigeria have a long-run relationship. Similarly, the long-run coefficients indicated that asides Energy Use, all independent variables have a significant effect on carbon emissions in the long run. However, the squared GDP and population growth have positive effect on carbon emissions, while GDP, trade openness, financial sector development and urbanization have negative effect on carbon emissions in the long run. Furthermore, the ECM coefficient was negative and statistically significant, meaning that in the event of any economic disequilibrium, the system will correct itself in the short run at a rate of 76 percent every quarter, eventually attaining long-term equilibrium. For the Granger Causality, result indicated that a significant bidirectional relationship exists between carbon emission and economic growth in Nigeria. It was recommended that a balance be established between carbon emission and economic growth in Nigeria by ensuring that unproductive activities that results in carbon emission are curtailed.

Keywords: Carbon intensity, Environmental Kuznets Curve, Clean technologies, Energy use.

This study analyzed the effect of government financing on agriculture value added in Nigeria between 2003 and 2022 using annual time series data sourced from Central Bank of Nigeria Statistical Bulletin and World Bank Development. Agricultural value added was used as the dependent variable while government financing on agriculture was used as the independent variable. Auto Regressive Distributed Lag (ARDL) Model was used to analyze data. The results of ARDL Model revealed that government financing on agricultural sector had a significant negative relationship with agricultural value added in Nigeria. The researcher therefore recommended that government should fund or support intending agricultural investors and producers through financial initiatives that would help in developing value added enterprises/businesses.

Keywords: government financing, agricultural value added, agricultural financing, agricultural sector, Auto regressive distributed lag model

This article provides an overview of credit scoring, including how it functions, what it is, and how the methods for scoring have changed over time. It discusses various scoring models and the sources of data used for credit scoring, such as combined models, traditional credit bureau scores, and custom models. In this article, modern scoring methods and traditional scoring methods are also compared. Furthermore, it outlines the main steps in creating credit scoring models, describes different ways to estimate statistics, and emphasizes the important factors for assessing their effectiveness. The article explained credit scoring is a key method for reducing the risk of lending money, giving lenders a fair and organized way to check if a borrower is reliable. Beginning in the 1950s, credit scoring has expanded from being used for personal loans to also include small business loans. This growth is mainly due to advancements in statistical techniques and better access to data. The advantages of credit scoring, such as speeding up the lending process and making it more fair, are recognized. However, potential problems like concerns over data accuracy and the risk of excluding borrowers who don’t fit the typical profile are also considered. Overall, this study highlights the important role credit scoring plays in current lending practices and its influence on risk management in the financial sector.

Keywords: credit scoring, credit bureau scores, customized models, pooling models, credit risk
JEL Codes: C45, D14, G21.

Based on the importance of investment in supporting the economic growth, the main objective of this study is to investigate the determinants of the investment in Cote d’Ivoire over the period 1980-2020, by using ADF unit root test, Johansen cointegration test, OLS model, Granger causality test, and CUSUM test. The results showed that investment is positively and significantly related with communication infrastructure, imports and inflation, but it is related negatively and insignificantly with external debt. Imports have the biggest effect on the investment. Besides, there are bidirectional long-run causality relationships between investment, external debt and imports, and unidirectional long-run causality relationships running from communication infrastructure and inflation to investment, but there are no short-run causality relationships between the variables. Hence, it is recommended that the Ivorian government uses external debt more efficiently, reduces corruption, improves the infrastructure and creates an attractive investment climate, as well as reducing most tariff and nontariff barriers, which will support the investment in the country.

Keywords: Cote d’Ivoire, Ivory Coast, investment, external debt, infrastructure, VAR
JEL Codes: O11, E20, G15