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We study the out-of-sample forecasting performance of 32 exchange rates vis-a-vis theNew Taiwan Dollar (NTD) in a 32-variable vector autoregression (VAR) model. TheBayesian approach is applied to the large-scale VAR model (LBVAR), and its (time-varying) forecasting performance is compared to the random-walk model in terms of bothforecast accuracy and Giacomini-Rossi fluctuation tests. We find the random-walk modeloutperforms the LBVAR model in a short-run forecasting competition. Moreover, thedominance of a random-walk in the competition is stable over time. Accordingly, we donot find any benefit of incorporating a rich set of information in predicting the exchangerates vis-a-vis the NTD.

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This study investigates the effect of service exports disaggregated into nine categories (transport, travel, construction, government, ICT, personal, cultural and recreational, financial, insurance, and other business services) on the survival of goods exports in Kenya. Estimates from the discrete-time probit model with random effects on bilateral trade data covering 1996 to 2019 show that export of services positively and significantly impact the duration of goods exports. A disaggregation of the goods into intermediate, consumption, capital, differentiated and homogenous products shows that transport and ICT service exports increase the duration of export of goods. Therefore, the simultaneous advancement of goods and service exports would foster the export survival of goods. In particular, the results indicate that export survival of value chain commodities would be enhanced through enhancing modes of transportation alongside communication and connectivity infrastructure. Our results also have implications for the African Continental Free Trade Area (AfCFTA) which seeks to synchronously negotiate and promote trade in goods and trade in services within Africa.

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This study aims to explore the levels of regional disparity in carbon emissions and intensity among different countries. Our study employs the distribution dynamics approach to uncover transition probabilities and the long-term evolution of relative per capita carbon emissions (REPC) and relative carbon intensity (REPGDP) across 204 countries. We split the analysis period into pre-crisis (2000-2007) and post-crisis (2007-2016) and divided countries into four income groups. The results indicate the emergence of new convergence clubs post-crisis in both REPC and REPGDP. Furthermore, the majority (many) of the low- (high) income countries congregate to extremely low (above the global average) REPC levels in the long run. Finally, using mobility probability plots, we identify low-(high-) income countries with REPC (REPGDP) levels of 2.3 (3.8) times the global average to have the highest probabilities of around 100 (65) per cent of diverging further above the worldwide average in the coming years. The study expands knowledge about convergence-divergence patterns in carbon emissions and intensity, which is crucial for energy management and effective climate policies. Moreover, it can aid in climate change projections and promote a fairer climate framework, encouraging high-emission countries to take greater responsibility.

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I examine whether private education expenditures and public K-12 funding are substitutes or complements for households whose children attend public school. Using a longitudinal microdata set, the Panel Study of Income Dynamics, I estimate the response of private household expenditures on education in response to changes in public expenditures. This paper implements a fixed-effects model that controls for unobservable household characteristics. I find evidence of complementarity between public and private education spending with an average elasticity of 2.4.

EN :

This paper studies the variation across countries in mortality rates due to COVID-19. A two-stage approach is used to model international data on the spread of COVID-19. The first stage applies a convergence club framework to identify clusters of countries within which the development of the epidemic is similar. The second stage models the membership of these clusters as a function of policy responses and public responses to the pandemic, with a particular focus on education as a determinant of the public response. Data include COVID-19 mortality per million, tertiary education completed, age structure, and voice and accountability and government effectiveness measures for each country in the dataset. We find evidence of two convergence clubs, one with a higher and one with a lower COVID-19 death rate. We also find evidence to support the hypothesis that relatively high levels of educational attainment in a population predicts a lower COVID19 death rate among individuals 65 or more years of age. We speculate that this is attributable to more informed prosocial behaviors directed toward elderly people in the form of adherence to guidelines intended to reduce spread of the virus.