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

2009 ◽  
Author(s):  
Frank Schorfheide ◽  
Keith Sill ◽  
Maxym Kryshko
Keyword(s):  
Dsge Model ◽  
Model Based

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 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

scholarly journals DSGE Model-Based Forecasting

2013 ◽  
pp. 57-140 ◽  
Author(s):  
Marco Del Negro ◽  
Frank Schorfheide
Keyword(s):  
Dsge Model ◽  
Model Based

A DSGE Model-Based Analysis of the Indian Slowdown

2020 ◽  
Vol 11 (01) ◽  
pp. 2050004
Author(s):  
Ashima Goyal ◽  
Abhishek Kumar
Keyword(s):  
Kalman Filter ◽  
Interest Rate ◽  
Output Gap ◽  
Monetary Shocks ◽  
Technology Shocks ◽  
Dsge Model ◽  
Habit Persistence ◽  
Model Based ◽  
Interest Rate Shocks ◽  
The Us

A New Keynesian Dynamic Stochastic General Equilibrium (DSGE) model with habit persistence used to examine the US slowdown is also used to analyze the contribution of basic demand and supply shocks to the Indian slowdown. Kalman filter-based maximum likelihood estimation is undertaken with Indian output, inflation and interest rate data. First, our model based output gap tracks the statistical Hodrick–Prescott filter-based output gap well. Second, comparison of estimated parameters, impulse responses and forecast error variance decomposition between India and the US brings out the differences in policy responses, the structure of the two economies and their inflationary processes. There is a higher impact of interest rate shocks on output and inflation, and lower impact of technology shocks on output but higher on inflation in comparison to US. The former indicates monetary policy over-reaction and the latter validates a supply curve that technology shocks shift and inadequate adjustment of actual to potential output. Habit persistence is higher, markup and interest rate shocks are more volatile in India. Markup shocks play a much larger role in determination of Indian inflation again pointing to the importance of supply side factors. Third, smoothed states obtained from the Kalman filter to create counterfactual paths of output and inflation (during 2009:Q4 to 2013:Q2) in the presence of a given shock, show monetary shocks imposed significant output cost. The output gap was negative post the 2011 slowdown and in 2016.

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