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Mr. Maxym Kryshko
When estimating DSGE models, the number of observable economic variables is usually kept small, and it is conveniently assumed that DSGE model variables are perfectly measured by a single data series. Building upon Boivin and Giannoni (2006), we relax these two assumptions and estimate a fairly simple monetary DSGE model on a richer data set. Using post-1983 U.S.data on real output, inflation, nominal interest rates, measures of inverse money velocity, and a large panel of informational series, we compare the data-rich DSGE model with the regular - few observables, perfect measurement - DSGE model in terms of deep parameter estimates, propagation of monetary policy and technology shocks and sources of business cycle fluctuations. We document that the data-rich DSGE model generates a higher implied duration of Calvo price contracts and a lower slope of the New Keynesian Phillips curve. To reduce the computational costs of the likelihood-based estimation, we employed a novel speedup as in Jungbacker and Koopman (2008) and achieved the time savings of 60 percent.
Ms. Izabela Karpowicz, Mr. Fabian Lipinsky, and Jongho Park

Front Matter Page Western Hemisphere Department Contents I. Overview II. A Closer Look at NFCs’ Balance Sheets III. Macroeconomic Consequences of Financial Shocks A. Risk Pricing and GDP B. DSGE Estimation IV. Conclusion References Appendix I. Data Sources for NFC Analysis Appendix II. Households Sector Balance Sheets Appendix III. DSGE Model

Ms. Izabela Karpowicz, Mr. Fabian Lipinsky, and Jongho Park
Understanding the interplay between firms’ balance sheets and the macro-economic environment is important for understanding of the Brazilian economy. A close examination of developments in the nonfinancial corporate sector up to the early 2015 reveals weak equity growth, declining profitability, and rising leverage. The empirical work suggests that adverse shocks to financial variables lead to weaker real GDP growth in Brazil through their effect on corporate leverage, borrowing costs, and default frequencies. An estimation based on a DSGE model with financial frictions indicates that the recent economic downturn in Brazil is largely driven by a decrease in total factor productivity and by negative financial shocks.
Ms. Izabela Karpowicz, Mr. Fabian Lipinsky, and Jongho Park

absence of the financial shock. The deterioration of GDP growth in response to an unanticipated increase in the corporate default index is most felt in the third quarter, but its trough effect on GDP growth is similar ( Figure 22 ). The Granger causality tests suggest that CEMBI and corporate EDFs help to predict real GDP growth, but real GDP growth does not have predictive power on these financial variables. 19 Figure 22. Brazil: Impulse Response Function of a Financial Shock (Percent) B. DSGE Estimation In this section we estimate a DSGE model with

Mr. Maxym Kryshko

average price markup to be in line with estimates from regular – few observables, perfect measurement – DSGE estimation. We find little evidence of dynamic indexation by intermediate goods firms in both versions of the model. The implied average duration of nominal price contracts is about 1/(1 − 0.797) = 4.9 quarters. On the one hand, this is close to what Aruoba and Schorfheide (2009) find in their money-in-the-utility specification of a DSGE model and what Del Negro and Schorfheide (2008) document under the “standard” agnostic prior about nominal price rigidities

Marzie Taheri Sanjani

Spread . Credit risk spread, BAA-FFR, is widely used in DSGE estimation literature as an observable for external finance premium (EFP). The VAR response of this proxy to a monetary policy shock is contrary to the prediction of DSGE models. The reason behind this puzzle is that BAA-FFR contains two types of risks, namely, default risk and maturity mismatch risk. I decomposed these two channels and use AAA-FFR as the proxy for the maturity mismatch channel and BAA-AAA as the proxy for the default risk channel. Both BAA and AAA contain bonds with long maturities. 2 In

Ali Alichi, Mr. Ippei Shibata, and Kadir Tanyeri
Government debt in many small states has risen beyond sustainable levels and some governments are considering fiscal consolidation. This paper estimates fiscal policy multipliers for small states using two distinct models: an empirical forecast error model with data from 23 small states across the world; and a Dynamic Stochastic General Equilibrium (DSGE) model calibrated to a hypothetical small state’s economy. The results suggest that fiscal policy using government current primary spending is ineffective, but using government investment is very potent in small states in affecting the level of their GDP over the medium term. These results are robust to different model specifications and characteristics of small states. Inability to affect GDP using current primary spending could be frustrating for policymakers when an expansionary policy is needed, but encouraging at the current juncture when many governments are considering fiscal consolidation. For the short term, however, multipliers for government current primary spending are larger and affected by imports as share of GDP, level of government debt, and position of the economy in the business cycle, among other factors.
Ali Alichi, Mr. Ippei Shibata, and Kadir Tanyeri

in the model and, since multiplier sizes are very small, could easily be ignored. Figure 14. GDP Cost of Fiscal Consolidation of 1 Percent of GDP, Temporary vs. Baseline (Percent; Effect on Level of GDP in Year 5) Source: Authors’ estimates. D. Multipliers following Natural Disasters While our baseline DSGE estimation of fiscal multipliers in the previous sections has assumed that the model economy starts at the steady state, many small states in reality are often hit by natural disasters (e.g. hurricanes) that take them well out of their

Marzie Taheri Sanjani
This paper investigates financial frictions in US postwar data to understand the interaction between the real business cycle and the credit market. A Bayesian estimation technique is used to estimate a large Vector Autoregression and New Keynesian models demonstrating how financial shocks can have a large and sluggish impact on the economy. I identify the default risk and the maturity mismatch channels of monetary policy transmission; I further employ a generalized-IRF to establish countercyclicality of risk spreads; and I show that the maturity mismatch shocks produce a stronger impact than the default risk shocks.
Mr. Maxym Kryshko

spending shock (GOV_T, g t ), money demand shock (CHI_T, χ t ), and neutral technology shock (Z_T, Z t ). Red line corresponds to the smoothed versions of the same variables in a regular DSGE model estimation derived by Kalman smoother at posterior mean of deep structural parameters (see notes to Table D3 in Kryshko (2011) for definition of “regular DSGE estimation”). Figure C3. Pure DFM (iid errors): Estimated Factors Notes: The figure plots the posterior means and 90% credible intervals of the latent empirical factors extracted by the empirical DFM (7