DSGE Model-Based Forecasting of Modeled and Non-Modeled Inflation Variables in South Africa

2013 ◽  
Author(s):  
Rangan Gupta ◽  
Patrick Tunda Kanda ◽  
Mampho P. Modise ◽  
Alessia Paccagnini
Keyword(s):  
South Africa ◽  
Dsge Model ◽  
Model Based

scholarly journals DSGE model-based forecasting of modelled and nonmodelled inflation variables in South Africa

2014 ◽  
Vol 47 (3) ◽  
pp. 207-221 ◽  
Author(s):  
Rangan Gupta ◽  
Patrick T. Kanda ◽  
Mampho P. Modise ◽  
Alessia Paccagnini
Keyword(s):  
South Africa ◽  
Dsge Model ◽  
Model Based

scholarly journals Analysis of Four Years of Global XCO2 Anomalies as Seen by Orbiting Carbon Observatory-2

2019 ◽  
Vol 11 (7) ◽  
pp. 850 ◽  
Author(s):  
Janne Hakkarainen ◽  
Iolanda Ialongo ◽  
Shamil Maksyutov ◽  
David Crisp
Keyword(s):  
South Africa ◽  
Biomass Burning ◽  
Fossil Fuel ◽  
Global Scale ◽  
Complex Model ◽  
Fuel Combustion ◽  
Local Concentration ◽  
Fossil Fuel Combustion ◽  
Tropical Regions ◽  
Model Based

NASA’s carbon dioxide mission, Orbiting Carbon Observatory-2, began operating in September 2014. In this paper, we analyze four years (2015–2018) of global (60°S–60°N) XCO2 anomalies and their annual variations and seasonal patterns. We show that the anomaly patterns in the column-averaged CO2 dry air mole fraction, XCO2, are robust and consistent from year-to-year. We evaluate the method by comparing the anomalies to fluxes from anthropogenic, biospheric, and biomass burning and to model-simulated local concentration enhancements. We find that, despite the simplicity of the method, the anomalies describe the spatio-temporal variability of XCO2 (including anthropogenic emissions and seasonal variability related to vegetation and biomass burning) consistently with more complex model-based approaches. We see, for example, that positive anomalies correspond to fossil fuel combustion over the major industrial areas (e.g., China, eastern USA, central Europe, India, and the Highveld region in South Africa), shown as large positive XCO2 enhancements in the model simulations. We also find corresponding positive anomalies and fluxes over biomass burning areas during different fire seasons. On the other hand, the largest negative anomalies correspond to the growing season in the northern middle latitudes, characterized by negative XCO2 enhancements from simulations and high solar-induced chlorophyll fluorescence (SIF) values (indicating the occurrence of photosynthesis). The largest discrepancies between the anomaly patterns and the model-based results are observed in the tropical regions, where OCO-2 shows persistent positive anomalies over every season of every year included in this study. Finally, we demonstrate how XCO2 anomalies enable the detection of anthropogenic signatures for several local scale case studies, both in the Northern and Southern Hemisphere. In particular, we analyze the XCO2 anomalies collocated with the recent TROPOspheric Monitoring Instrument NO2 observations (used as indicator of anthropogenic fossil fuel combustion) over the Highveld region in South Africa. The results highlight the capability of satellite-based observations to monitor natural and man-made CO2 signatures on global scale.

scholarly journals Growth, Water Resilience, and Sustainability: A DSGE Model Applied to South Africa

2016 ◽  
Vol 02 (04) ◽  
pp. 1650022
Author(s):  
Chuan-Zhong Li ◽  
Ranjula Bali Swain
Keyword(s):  
South Africa ◽  
Capital Accumulation ◽  
Poor Country ◽  
Change Scenario ◽  
Limiting Factor ◽  
Precipitation Pattern ◽  
Dsge Model ◽  
Stochastic Variation ◽  
Long Run ◽  
Dynamic Stochastic

In this paper, we develop a dynamic stochastic general equilibrium (DSGE) model to study how water resilience affects economic growth and dynamic welfare with special reference to South Africa. While water may become a limiting factor for future development in general, as a drought prone and water poor country with rapid population growth, South Africa may face more serious challenges for sustainable development. Analyzing the DSGE model, we conduct numerical simulations for different parameter configurations with varying discount rate, climate change scenario, and the degree of uncertainty in future precipitation. We find that with sufficient capital accumulation, development may still be sustainable despite increased future water scarcity and decreased long-run sustainable welfare. While stochastic variation in precipitation has a negative effect on water resilience and the expected dynamic welfare, the effect is mitigated by persistence in the precipitation pattern. With heavier time discounting and lower capital formation, however, the current welfare may not be sustained.

scholarly journals DSGE model-based forecasting of non-modelled variables

2010 ◽  
Vol 26 (2) ◽  
pp. 348-373 ◽  
Author(s):  
Frank Schorfheide ◽  
Keith Sill ◽  
Maxym Kryshko
Keyword(s):  
Dsge Model ◽  
Model Based

scholarly journals DSGE Model-Based Forecasting of Non-Modelled Variables

2008 ◽  
Author(s):  
Frank Schorfheide ◽  
Keith Sill ◽  
Maxym Kryshko
Keyword(s):  
Dsge Model ◽  
Model Based

scholarly journals DSGE Model-Based Forecasting

2012 ◽  
Author(s):  
Marco Del Negro ◽  
Frank Schorfheide
Keyword(s):  
Dsge Model ◽  
Model Based
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