2011
DOI: 10.2139/ssrn.1816139
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SOEPL 2009 - An Estimated Dynamic Stochastic General Equilibrium Model for Policy Analysis and Forecasting

Abstract: Warsaw 2011 N a t i o n a l B a n k o f P o l a n d 2 Design: Oliwka s.c.

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Cited by 13 publications
(11 citation statements)
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References 69 publications
(61 reference statements)
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“…Interest rate smoothing is stronger in Poland; however, in Romania, the central bank is marginally more aggressive with respect to inflation. This behavior is again in opposition to Grigoraș (2010) and Grabek et al (2011), who obtained …”
Section: Resultscontrasting
confidence: 73%
“…Interest rate smoothing is stronger in Poland; however, in Romania, the central bank is marginally more aggressive with respect to inflation. This behavior is again in opposition to Grigoraș (2010) and Grabek et al (2011), who obtained …”
Section: Resultscontrasting
confidence: 73%
“…Calvo probabilities are generally higher in the eurozone than in Poland, both in price and wage setting, indicating more stickiness in the eurozone. The results provided by Kolasa (2009) are consistent with ours only with respect to wage stickiness (Polish labour market is generally characterized as less rigid in the literature, but product market not necessarily, see also Grabek et al, 2011), but the micro-literature based on ECB's Wage Dynamics Network Project (see, Druant et al, 2009) seems to point that the frequency of price and wage changes is higher in Poland than in the average of eurozone economies. 20 The degree of price indexation to past inflation is similar in both economies in case of setting prices to foreign markets and in the wage setting, but the indexation is more pronounced in Poland in case of pricing to local markets, which is in line with the results of Kolasa (2009).…”
supporting
confidence: 80%
“…20 Also the results by Przystupa and Wro´bel (2009) on exchange rate pass-through show that Polish companies respond much faster to exchange rate movements than the eurozone ones, pointing to less price stickiness in case of Poland. 21 The estimates for the Polish economy are in line with the results obtained in Grabek et al (2011) and the ones for the eurozone -with Smets and Wouters (2003). economies, we compared the theoretical moments generated by the model against the moments of the data, see Table 3.…”
Section: Model's Data Fitsupporting
confidence: 62%
“…A companion paper, Andrle and others (2013), uses a structural model to investigate the role of external shocks for Poland and reaches similar conclusions to our VAR analysis -foreign shocks explain roughly 50 percent of the cyclical volatility in output. Recently, an estimated DSGE model for Poland by Grabek, Klos, and Koloch (2009) attributes to foreign shocks only up to 15 percent of the output volatility and 15-57 percent to interest rate volatility. Further, Demchuk and others (2012) analyze monetary policy transmission in Poland using a structural VAR, but ignores completely the effect of foreign variables.…”
Section: Relationship To the Existing Literaturementioning
confidence: 99%