Primary Commodity Dependence and Debt Problem in Less Developed Countries

Economists have proffered myriads of causes of the debt problem faced by less developed countries (LDCs). This paper uses the panel data technique to investigate the fundamental causes of the debt problem among primary commodity dependent LDCs. The results show a strong link between high levels of indebtedness and unfavourable terms of trade among commodity-dependent countries. Further results show that the degree of openness of the LDC's economy also has a significant influence on its external debt level.

Volatility of primary commodity prices: some evidence from agricultural exports in Sub-Saharan Africa.

This paper utilizes three univariate ARCH-type models to empirically examine persistence and asymmetry in volatility of prices of primary agricultural commodities produced in Sub-Sahara Africa. Maximum likelihood estimation results of the three models ranked the GARCH version as the best statistical fit, lending support for hypotheses of persistence, symmetry and variability in volatility. This pattern of volatility could effectively jeopardize the success of traditional commodity price risk management policies used in this region. Policymakers should appreciate potential benefits associated with market-based strategies for managing commodity exposure of these countries.GARCH; TGARCH; EGARCH; price volatility; agricultural commodities; Sub-Saharan Africa.

Macroeconomic Determinants Of Non-Fuel Primary Commodity Price Movements

This paper uses cointegration and error correction modelling techniques to examine the relationship between non-fuel commodity prices and world macroeconomic and monetary variables. The results show that fluctuations in industrial production of OECD countries, real effective exchange rate of the U.S. dollar and oil prices have significant short- and long- run impact on non-fuel commodity prices. In addition, there is evidence of highly significant positive correlation between the index of non-fuel commodity prices and crude oil price. This implies non-fuel commodity-dependent developing countries that are net importers of oil can derive little benefit from upward movements in commodity prices

Parental expectations and school enrolment decisions: Evidence from rural Ghana

We use field data to investigate factors which influence parents’ decision to enrol children in schools in rural Ghana. The empirical results identified a host of socio-economic and household-level factors including remittances parents expect from investing in education, parents perception of a child's desirable professions, cost of schooling and discount rate as significant determinants of parental school enrolment decision. When gender of the child and remittances are taken into account, we show male parents are more likely to invest in education of boys than girls because they expect significantly higher returns from their investment in boys. Female parents do not show such gender preference. The proportion of children enrolled in school is positively related to average cost of schooling for male parents Gender of parent plays a significant role in school enrolment decision making

Carbon trading amidst global uncertainty: The role of policy and geopolitical uncertainty

Economic policy uncertainty (EPU) and geopolitical uncertainty (GPU) can fuel speculation, flood the carbon trading market with excess allowances, and undermine the scheme's efficacy in tackling climate change. While the existing literature documents the adverse effects of uncertainty on macroeconomic and financial variables, the impact on the carbon trading risk remains unclear. This paper analyses the effects of EPU and GPU on the volatility and other risk levels in the carbon market using daily European Union Emissions Trading Scheme data (February 2, 2009 to 8/31/2022) and monthly data on the uncertainty indicators (2009M2–2022M8). The findings reveal that unstable policies and geopolitical tensions heighten carbon market risk since global uncertainty increases information asymmetry and risk premium and causes a delay in investment decisions. Future deliberation among the Cooperation of Parties under the United Nations Framework Convention on Climate Change should incorporate measures to mitigate global uncertainty while pushing for decarbonization and transition to clean technology

A firm-level analysis of the upstream-downstream dichotomy in the oil-stock nexus

In this paper, we query whether the stock prices of nonintegrated firms in the upstream and downstream sectors of the global oil supply chain respond symmetrically to changes in oil prices. This inquiry relates to the “homogenous expectation” assumption among investors and fund managers pertaining to the returns and variances of assets of specialized firms operating in upstream and downstream sectors of the supply chain. Motivated by the Arbitrage Pricing Theory, we formulate a Panel Autoregressive Distributed Lag (PARDL) model, which explains the possible macroeconomic factors in the oil-stock nexus as well as any inherent persistence and heterogeneity effects due to large cross-sections and time. In accordance with the Shin et al. (2014) approach, a Nonlinear Panel ARDL model is also formulated to test for possible asymmetric responses of the nonintegrated oil firms to positive and negative changes in the oil price. Our findings indicate that the stock prices of upstream and downstream firms move in contrasting directions in response to changes in the benchmark crude oil prices in the long-run. Specifically, we show that the stock prices of upstream sector firms increased in response to an increase in oil prices, while the reverse holds for the stock prices of downstream firms. In the short run, returns on the stock of firms in both sectors increase following an increase in oil prices; however, downstream firms’ stock returns decreased in response to negative oil price shocks. The findings further show that both sectors respond differently to episodic changes in market conditions that emanated from the global financial crisis. However, upstream firms show a stronger response to changing market conditions than their downstream counterparts

Market reforms and commodity price volatility: the case of East African Coffee Market

The goal of this paper is to examine the impact of commodity market reforms on producer price volatility using evidence from the East African coffee market. The results, based on time-varying volatility models and key summary statistics, show that coffee market reforms in the East African Community (EAC) are associated with changes in producer price volatility and volatility persistence at both country and regional levels. However, reforms were not the only cause of changes in price volatility. The study further shows that reforms had different effects on prices volatilities of Arabica and Robusta varieties of coffee grown in individual EAC countries. These findings have wider implication for commodity market reforms and producer price stabilization policies in the EAC and coffee producing countries in sub-Sahara Africa

U.S. stocks in the presence of oil price risk: Large cap vs. small cap

This study queries the act of making generalization about the dynamics of returns and volatility spillovers between oil price and U.S. stocks by merely considering only large cap stocks. It argues that this kind of generalization may be misleading, as the reactions of large cap, mid cap and small cap stocks to change in oil prices are not expected to be uniform. Our findings show that it is incorrect to make such generalization when considering oil risk/volatility spillovers from oil to U.S. stock, as evidence shows that oil price volatility impacts more on mid cap and small cap than large cap

Improving the predictability of the oil–US stock nexus: The role of macroeconomic variables

In this study, we revisit the oil–stock nexus by accounting for the role of macroeconomic variables and testing their in-sample and out-of-sample predictive powers. We follow the approaches of Lewellen (2004) and Westerlund and Narayan (2015), which were formulated into a linear multi-predictive form by Makin et al. (2014) and Salisu et al. (2018) and a nonlinear multi-predictive model by Salisu and Isah (2018). Thereafter, we extend the multi-predictive model to account for structural breaks and asymmetries. Our analyses are conducted on aggregate and sectoral stock price indexes for the US stock market. Our proposed predictive model, which accounts for macroeconomic variables, outperforms the oil-based single-factor variant in forecasting aggregate and sectoral US stocks for both in-sample and out-of-sample forecasts. We find that it is important to account for structural breaks in our proposed predictive model, although asymmetries do not seem to improve predictability. In addition, we show that it is important to pre-test the predictors for persistence, endogeneity, and conditional heteroscedasticity, particularly when modeling with high-frequency series. Our results are robust to different forecast measures and forecast horizons

Hedging potentials of green investments against climate and oil market risks

Purpose: This study examines the ability of clean energy stocks to provide cover for investors against market risks related to climate change and disturbances in the oil market.Design/methodology/approach: The study adopts the Feasible Quasi Generalized Least Squares technique to estimate a predictive model based on Westerlund and Narayan’s (2015) approach to evaluating the hedging effectiveness of clean energy stocks. The out-of-sample forecast evaluations of the oil risk-based and climate risk-based clean energy predictive models are explored using Clark and West’s model (2007) and a modified Diebold & Mariano forecast evaluation test (Harvey et al., 1997) for nested and non-nested models respectively.Findings: The study finds ample evidence that clean energy stocks may hedge against oil market risks. This result is robust to alternative measures of oil risk and holds when applied to data from the COVID-19 pandemic. In contrast, the hedging effectiveness of clean energy against climate risks is limited to 4 of the 6 clean energy indices and restricted to climate risk measured with Climate Policy Uncertainty.Originality/value: The study contributes to the literature by providing extensive analysis of hedging effectiveness of several clean energy indices (global, US, Europe, and Asia) and sectoral clean energy indices (solar and wind) against oil market and climate risks using various measures of oil risk (WTI and Brent volatility) and climate risk (Climate Policy Uncertainty and Energy and Environmental Regulation) as predictors. It also conducts forecast evaluations of the clean energy predictive models for nested and non-nested models