Environmental and Social Accounting for Brazil

An environmentally extendedSocial Accounting Matrix (SAM) has beenconstructed for Brazil for the first time. Wereview in detail previous studies in thisfield, describe the construction, structure anddata sources of the Brazilian SAM, anddemonstrate the effect of system closure.Examining a range of type-I and type-IImultipliers, we show that incomes generated byfinal consumption are highly skewed towardsrich households, but energy requirements andcarbon emissions are higher for the consumptionof the poor. A significant negative correlationexists between employment and income on onehand, and energy requirements and carbonemissions on the other, while a significantpositive correlation exists between imports,and energy and carbon. These correlationsdemonstrate that there is scope for policiesthat pursue imports substitution and reduceenergy consumption and carbon emissions whilstincreasing employment and income.     

Energieversorgungsrisiken,Energiepreiskrise und Klimaschutz erfordern gemeinsame Antworten

Wirtschaftsdienst - In the past two years, the world has changed and global crises (e. g. the COVID-19 pandemic, war in Ukraine) increasingly dominate the headline. Decades of certainties no longer...     

„Communication Excellence“

Literaturhinweise

Zusammengestellt von M.A. Lydia Ebersbach     

General Bayesian time-varying parameter vector autoregressions for modeling government bond yields

US yield curve dynamics are subject to time-variation, but there is ambiguity about its precise form. This paper develops a vector autoregressive (VAR) model with time-varying parameters and stochastic volatility, which treats the nature of parameter dynamics as unknown. Coefficients can evolve according to a random walk, a Markov switching process, observed predictors, or depend on a mixture of these. To decide which form is supported by the data and to carry out model selection, we adopt Bayesian shrinkage priors. Our framework is applied to model the US yield curve. We show that the model forecasts well, and focus on selected in-sample features to analyze determinants of structural breaks in US yield curve dynamics.