COVID-19 is currently having major short run effects with possible serious long run implications for the environment and the management of natural resources in Latin America. We discuss the possible effects of the pandemic on air pollution, deforestation and other relevant environmental dimensions across the region. With contributions from environmental economists from eight countries, we give an overview of the initial and expected environmental effects of this health crisis.

Historically, transport infrastructure connecting the most agriculturally productive areas of Mozambique and the richer southern region has been poor. A primary bottleneck was an unreliable ferry service over the Zambezi river, addressed by construction of a road bridge in 2009. In this paper we identify the impact of this transport infrastructure enhancement on integration of national maize markets.

The long and persistent swings in the real exchange rate have for a long time puzzled economists. Recent models built on imperfect knowledge economics seem to provide a theoretical explanation for this persistence. Empirical results, based on a cointegrated vector autoregressive (CVAR) model, provide evidence of error-increasing behavior in prices and interest rates, which is consistent with the persistence observed in the data.

This article examines the effect of commercial bank performance on an indicator of energy efficiency (i.e. energy intensity) while controlling for the mediating effect of political institution. To achieve this goal, the study develops a theoretical model based on the neoclassical theory of the firm that links energy efficiency to bank sector development, and a unique bank-based data by Andrianova et al. (2015) for 43 Sub-Saharan African countries from 1998 to 2012.

Agricultural price distortion which is the discrepancy between world market price of agricultural produce and price received by farmers as a result of market interventions by governments, either through subsidies or taxes or even trade protection systems, has received rare attention in the cocoa and coffee sub-sectors. This study examines the contribution of mobile phone technology in reducing price distortions in cocoa and coffee production.

Analysis of the unconditional impacts of foreign direct inflows (FDIs) and industrialization on energy intensity does not show the hidden roles of some economic conditions such as income and trade openness. In this study, we focused on the conditional impacts of FDIs and industrialization on energy productivity using a panel data consisting of thirteen (13) East African countries covering 1980–2011. The baseline result shows that higher income and a well-integrated economy are pro-energy productive, but FDIs and intense industrialization are anti-energy productive in the sub-region.

This paper investigated the short-run causal relationships and the long-run equilibrium relationships among carbon dioxide emissions, economic growth, technical efficiency, and industrial structure for three African countries. Using Bounds cointegration approach the result showed evidence of multiple long-run equilibrium relationships for Ghana and Senegal but a one-way long-run equilibrium relationship for Morocco. The result from the Toda and Yomamoto granger causality test showed a mix of bidirectional, unidirectional, and neutral relationships for all countries.

Forecasting the risk of extreme losses is an important issue in the management of financial risk and has attracted a great deal of research attention. However, little attention has been paid to extreme losses in a higher frequency intraday setting. This paper proposes a novel marked point process model to capture extreme risk in intraday returns, taking into account a range of trading activity and liquidity measures. A novel approach is proposed for defining the threshold upon which extreme events are identified taking into account the diurnal patterns in intraday trading activity.

We propose a multivariate dynamic intensity peaks‐over‐threshold model to capture extremes in multivariate return processes. The random occurrence of extremes is modeled by a multivariate dynamic intensity model, while temporal clustering of their size is captured by an autoregressive multiplicative error model. Applying the model to daily returns of three major stock indexes yields strong empirical support for a temporal clustering of both the occurrence and the size of extremes.