Modeling Rwanda
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985998%3A_____%2F11%3A00426534" target="_blank" >RIV/67985998:_____/11:00426534 - isvavai.cz</a>
Výsledek na webu
—
DOI - Digital Object Identifier
—
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Modeling Rwanda
Popis výsledku v původním jazyce
The report consists of four chapters. Chapter 1 assesses the historical performance of forecasts for Rwanda. Historical forecasts since January 2010 are compared with the actual data as well as with projections of other institutions. Chapter 2 presents the structural macroeconomic model, its changes compared to the December 2009 version, and its properties captured by impulse-response functions and by variance decompositions of model?s variables in terms of the model shocks. Important is the part on themodel-consistent interpretation of the recent economic Rwanda history. The section describing Bayesian vector autoregressions used for the near-term forecasting concludes. Chapter 3 evaluates how the models perform empirically. On the contrary to Chapter 1, the forecasting power is assessed both in the sample as well as by using an out-of-thesample comparison with the standard random-walk benchmark. We conclude that the FPAS performs satisfactorily in this comparison. The last chapter g
Název v anglickém jazyce
Modeling Rwanda
Popis výsledku anglicky
The report consists of four chapters. Chapter 1 assesses the historical performance of forecasts for Rwanda. Historical forecasts since January 2010 are compared with the actual data as well as with projections of other institutions. Chapter 2 presents the structural macroeconomic model, its changes compared to the December 2009 version, and its properties captured by impulse-response functions and by variance decompositions of model?s variables in terms of the model shocks. Important is the part on themodel-consistent interpretation of the recent economic Rwanda history. The section describing Bayesian vector autoregressions used for the near-term forecasting concludes. Chapter 3 evaluates how the models perform empirically. On the contrary to Chapter 1, the forecasting power is assessed both in the sample as well as by using an out-of-thesample comparison with the standard random-walk benchmark. We conclude that the FPAS performs satisfactorily in this comparison. The last chapter g
Klasifikace
Druh
O - Ostatní výsledky
CEP obor
AH - Ekonomie
OECD FORD obor
—
Návaznosti výsledku
Projekt
<a href="/cs/project/LF11018" target="_blank" >LF11018: Internetový portál a makroekonomické modely pro prognózování a měnověpolitickou analýzu v rozvojových zemích</a><br>
Návaznosti
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Ostatní
Rok uplatnění
2011
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů