1,721,600 research outputs found
Sensitivity analysis and model evaluation in simulated dynamic general equilibrium economies
No full textAre seasonal patterns constant over time? A test for seasonal stability
No full textThis paper introduces Lagrange multiplier tests of the null hypothesis of no unit roots at seasonal frequencies against the alternative of a unit root at either a single seasonal frequency or a set of seasonal frequencies. The tests complement those of D. Dickey, D. Hasza, and W. Fuller (1984) and S. Hylleberg, et al. (1990), which examine the null of seasonal unit roots. The authors derive an asymptotic distribution theory for the tests and investigate their size and power with a Monte Carlo exercise. Application of three sets of seasonal variables shows that, in most cases, seasonality is nonstationary
Did Colonization matter for Growth? An Empirical Exploration into the Historical Causes of Africa's Underdevelopment
No full text
Multiple filtering devices for the estimation of cyclical DSGE models
Full text linkWe propose a method to estimate time invariant cyclical dynamic stochastic gen eral equilibrium models using the information provided by a variety of filters. We treat data filtered with alternative procedures as contaminated proxies of the relevant model-based quantities and estimate structural and nonstructural parameters jointly using a signal extraction approach. We employ simulated data to illustrate the properties of the procedure and compare our conclusions with those obtained when just one filter is used. We revisit the role of money in the transmission of monetary business cycles
The dynamics of US inflation : can monetary policy explain the changes?
No full textReceived 6 September 2006
Received in revised form
10 July 2010
Accepted 9 August 2011
Available online 9 November 2011We investigate the relationship between monetary policy and inflation dynamics in the US using a medium scale structural model. The specification is estimated with Bayesian techniques and fits the data reasonably well. Policy shocks account for a part of the decline in inflation volatility; they have been less effective in triggering inflation responses over time and qualitatively account for the rise and fall in the level of inflation. A number of structural parameter variations contribute to these patterns.http://www.sciencedirect.com/science/article/pii/S0304407611002399
Monetary policy in the euro area: lessons from five years of the ECB and implications for Turkey
No full textMonetary policy in the euro area: lessons from five years of the ECB and implications for Turke
Choosing the variables to estimate singular dsge models
No full textSUMMARY: We propose two methods to choose the variables to be used in the estimation of the structural parameters of a singular DSGE model. The first selects the vector of observables that optimizes parameter identification; the second selects the vector that minimizes the informational discrepancy between the singular and non-singular model. An application to a standard model is discussed and the estimation properties of different setups compared. Practical suggestions for applied researchers are provided
Mind the Gap! Stylized Dynamic Facts and Structural Models
Full text linkWe study what happens to identified shocks and to dynamic responses when the data generating process features q disturbances but q 1 < q variables are used in an empirical model. Identified shocks are linear combinations of current and past values of all structural disturbances and do not necessarily combine disturbances of the same type. Theory-based restrictions may be insufficient to obtain structural dynamics. We revisit the evidence regarding the transmission of house price and of uncertainty shocks. We provide suggestions on how to compare the dynamics of larger scale DSGEs models with smaller scale VARs
DETECTING AND ANALYZING THE EFFECTS OF TIME-VARYING PARAMETERS IN DSGE MODELS
No full textWe study how structural parameter variations affect the decision rules and economic inference. We provide diagnostics to detect parameter variations and to ascertain whether they are exogenous or endogenous. A constant parameter model poorly approximates a time-varying data generating process (DGP), except in a handful of relevant cases. Linear approximations do not produce time-varying decision rules; higher-order approximations can do this only if parameter disturbances are treated as decision rule coefficients. Structural responses are time invariant regardless of order of approximation. Adding endogenous variations to the parameter controlling leverage in Gertler and Karadi's model substantially improves the fit of the model
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