a new approach to multi step forecasting using dynamic stochastic general equilibrium models dsge models are of interest because they offer structural interpretations but are also increasingly used for forecasting estimation often proceeds by methods which involve building the likelihood by one step ahead h 1 prediction errors however in principle this can be done using different horizons where h 1 using the well known model of smets and wouters 2007 for h 1 classical ml parameter estimates are similar to those originally reported as h extends some estimated parameters change but not to an economically significant degree forecast performance is often improved in several cases significantly

euro dollar real exchange rate dynamics in an estimated two country model an assessment abstract several theoretical contributions using two country models have combined alternative forms of pricing under nominal rigidities with different asset market structures to explain real exchange rate dynamics we estimate a two country model using data for the united states and the euro area and study the importance of such alternative assumptions in fitting the data a model with local currency pricing and incomplete markets does a good job in explaining real exchange rate volatility and fits the dynamics of domestic variables well the complete markets assumption delivers a similar fit only when the structure of shocks is rich enough

exploiting the monthly data flow in structural forecasting a quarterly stochastic general equilibrium dsge model is combined with a now casting model designed to read timely monthly information as it becomes available this implies 1 mapping the structural quarterly dsge with a monthly version that maintains the same economic restrictions 2 augmenting the model with a richer data set and 3 updating the estimates of the dsge s structural shocks in real time following the publication calendar of the data our empirical results show that our methodology enhances the predictive accuracy in now casting an analysis of the great recession also shows that our framework would have helped tracing the dsge s structural shocks in real time obtaining for example a more timely account of the 2008 contraction

how robust are popular models of nominal frictions this paper analyzes three popular models of nominal price and wage frictions to determine which best ts post war u s data we construct a dynamic stochastic general equilibrium dsge model and use maximum likelihood to estimate each model s parameters because previous research nds that the conduct of monetary policy and the behavior of in ation changed in the early 1980s we examine two distinct sample periods using a bayesian pseudo odds measure as a means for comparison a sticky price and wage model with dynamic indexation best ts the data in the early sample period whereas either a sticky price and wage model with static indexation or a sticky information model best ts the data in the late sample period our results suggest that price and wage setting behavior may be sensitive to changes in the monetary policy regime if true the evaluation of alternative monetary policy rules may be even more complicated than previously believed

macro shocks and costly political action in non democracies this paper presents a theory of political instability in autocracies where the disenfranchised express their political preferences for a leadership replacement through costly political action we focus on the business regulatory environment as an arena for autocratic rent creation as a source of information asymmetry between the autocrat and the disenfranchised and as a potential political grievance for the disenfranchised within this context we revisit the role of macro shocks as a catalyst for political instability and propose a novel informational channel through which macro shocks may trigger costly political action when the autocrat chooses to create rents through regulation that deteriorates the mean macroeconomic outcome we then provide an empirical investigation of our theoretical hypotheses employing fixed effects panel regressions and an instrumental variable strategy over a sample of non democratic countries consistent with our theoretical hypotheses we demonstrate that adverse economic shocks increase the probability of mass protest episodes but that the magnitude of the effect depends on the extent to which business regulation is market distorting

when does a central bank s balance sheet require fiscal support abstract using a simple general equilibrium model we argue that it would be appropriate for a central bank with a large balance sheet composed of long duration nominal assets to have access to and be willing to ask for support for its balance sheet by the fiscal authority otherwise its ability to control inflation may be at risk this need for balance sheet support a within government transaction is distinct from the need for fiscal backing of inflation policy that arises even in models where the central bank s balance sheet is merged with that of the rest of the government

bridging dsge models and the raw data abstract a method to estimate dsge models using the raw data is proposed the approach links the observables to the model counterparts via a flexible specification which does not require the model based component to be located solely at business cycle frequencies allows the non model based component to take various time series patterns and permits certain types of model misspecification applying standard data transformations induces biases in structural estimates and distortions in the policy conclusions the proposed approach recovers important model based features in selected experimental designs two widely discussed issues are used to illustrate its practical use

non stationary hours in a dsge model the time series fit of dynamic stochastic general equilibrium dsge models often suffers from restrictions on the long run dynamics that are at odds with the data using bayesian methods we estimate a stochastic growth model in which hours worked are stationary and a modified version with permanent labor supply shocks if firms can freely adjust labor inputs the data support the latter specification once we introduce frictions in terms of labor adjustment costs the overall time series fit improves and the model specification in which labor supply shocks and hours worked are stationary is preferred

how much should inflation targeters care about the exchange rate abstract a dsge model is used to examine whether including the exchange rate in the central bank s policy rule can improve economic performance smoothing the exchange rate helps both financially robust economies and financially vulnerable emerging economies in handling risk premium shocks and given a small weight placed on the exchange rate the effects on inflation and output volatility are minimal with demand and cost push shocks financially vulnerable economies are especially likely to benefit from exchange rate smoothing due to perverse movements of the exchange rate they experience when hit by demand shocks and being more prone to risk premium shocks

does local financial development matter we study the effects of differences in local financial development within an integrated financial market we construct a new indicator of financial development by estimating a regional effect on the probability that ceteris paribus a household is shut off from the credit market by using this indicator we find that financial development enhances the probability an individual starts his own business favors entry of new firms increases competition and promotes growth as predicted by theory these effects are weaker for larger firms which can more easily raise funds outside of the local area these effects are present even when we instrument our indicator with the structure of the local banking markets in 1936 which because of regulatory reasons affected the supply of credit in the following 50 years overall the results suggest local financial development is an important determinant of the economic success of an area even in an environment where there are no frictions to capital movements

comparing dsge var forecasting models how big are the differences abstract i generate priors for a vector autoregression var from a standard real business cycle rbc model an rbc model with capital adjustment costs and habit formation and a sticky price model with an unaccommodating monetary authority the response of hours worked to a tfp shock differs sharply across these models i compare the accuracy of forecasts made from each of the resulting dynamic stochastic general equilibrium vector autoregression dsge var models despite having different structural characteristics the dsge vars are comparable in terms of forecasting performance as in previous work dsge vars compare favorably with atheoretical vars

supplanting the minnesota prior forecasting macroeconomic time series using real business cycle model priors abstract although general equilibrium models are in wide use in the theoretical macroeconomic literature their empirical relevance is uncertain we develop procedures for using dynamic general equilibrium models to aid in analyzing the observed time series relationships among macroeconomic variables our strategy is based on that developed by doan litterman and sims 1984 who constructed a procedure for improving time series forecasts by shrinking vector autoregression coefficient estimates toward a prior view that vector time series are well described as collections of independent random walks in our case the prior is derived from a fully specified general equilibrium model we demonstrate that like the atheoretical random walk priors real business cycle model priors can aid in forecasting

economic fluctuations in the u s and euro area quantifying the contribution of technical change this article aims at quantifying the contribution of technical change to cyclical fluctuations in the u s and euro area we distinguish technical progress in labor augmenting and capital augmenting change to this end we derive and estimate a new keynesian dsge model embodying a constant elasticity of substitution ces production function for both areas our main findings are i capital augmenting progress is the main source of technical change volatility ii labor augmenting shocks give a negligible contribution to the variance of output iii technical change of both types explains more economic fluctuations in the u s than in the euro area and iv historical decomposition of gdp growth over our sample period 1980 2008 shows that capital augmenting progress is one of the key drivers of the business cycle

frequentist evaluation of small dsge models this article proposes a new evaluation approach for the class of small scale hybrid new keynesian dynamic stochastic general equilibrium nk dsge models typically used in monetary policy and business cycle analysis the empirical assessment of the nk dsge model is based on a conditional sequence of likelihood based tests conducted in a vector autoregressive var system in which both the low and high frequency implications of the model are addressed in a coherent framework if the low frequency behavior of the original time series of the model can be approximated by nonstationary processes stationarity must be imposed by removing the stochastic trends this gives rise to a set of recoverable unit roots cointegration restrictions in addition to the short run cross equation restrictions the procedure is based on the sequence lr1 lr2 lr3 where lr1 is the cointegration rank test lr2 is the cointegration matrix test and lr3 is the cross equation restrictions test lr2 is computed conditional on lr

investment shocks and business cycles abstract the origins of business cycles are still controversial among macroeconomists this paper contributes to this debate by studying the driving forces of fluctuations in an estimated new neoclassical synthesis model of the u s economy in this model most of the variability of output and hours at business cycle frequencies is due to shocks to the marginal efficiency of investment imperfect competition and to a lesser extent technological frictions are the key to their transmission although labor supply shocks explain a large fraction of the fluctuations in hours at very low frequencies they are irrelevant over the business cycle this finding is important because the microfoundations of these disturbances are widely regarded as unappealing

monetary policy analysis with potentially misspecified models abstract the paper proposes a novel method for conducting policy analysis with potentially misspecified dynamic stochastic general equilibrium dsge models and applies it to a new keynesian dsge model along the lines of christiano eichenbaum and evans jpe 2005 and smets and wouters jeea 2003 we first quantify the degree of model misspecification and then illustrate its implications for the performance of different interest rate feedback rules we find that many of the prescriptions derived from the dsge model are robust to model misspecification jel classification c32 key words bayesian analysis dsge models model misspecification 1 introduction the quantitative evaluation of monetary policy rules plays an important role in the design of stabilization policies much of the recent debate about optimal monetary policy rules has been carried out with new keynesian dynamic stochastic general equilibrium dsge models see woodford 2003 dsge models have the advantage that one can explicitly assess the effect of policy regime changes on expectation formation and decision rules of private agents yet until recently these models were scarcely used by central banks because they were perceived as being inferior to less structural model in terms of fit recent work by christiano eichenbaum and evans 2005 and smets and wouters 2003 has changed this perception these papers show that the fit of large scale new keynesian dsge models is comparable to that of more heavily parameterized models as a consequence a number of central banks have begun to show interest in these models as tools for quantitative policy analysis despite the success in improving the empirical performance of dsge models misspecification remains a concern as shown in del negro schorfheide smets and wouters 2004 accounting for misspecification and model uncertainty in general is an important aspect of the assessment of monetary policies after all it has long been recognized that model and parameter uncertainty affects optimal policies e g brainard 1967 chow 1975 and craine 1979 1 this paper proposes a new method for taking model misspecification into account when assessing the performance of alternative interest rate feedback rules we apply this approach to evaluate different policies in the context of a new keynesian dsge model including the estimated volcker greenspan rule a natural approach in the presence of model uncertainty is to evaluate policy rules within all the model specifications that are under consideration in choosing the best performing rule one can either follow a bayesian route assigning probabilities to models and minimizing the overall posterior expected loss alternatively one can follow a minimax strategy by adopting a policy that minimizes the worst case loss across models the literature contains numerous applications of these ideas e g mccallum 1988 levin wieland and williams 1999 2003 rudebusch 2001 2003 onatski and stock 2002 onatski and williams 2003 brock durlauf and west 2004 cogley and sargent 2005 and hansen and sargent 2005 all these papers differ with regard to the type of models included in the model set and the formulation of the decision problem that leads to the choice of a preferred policy our analysis differs from previous work with respect to the method that is used to construct a model set and assign probabilities to these models so that a bayesian calculation of posterior expected performance is possible we start from a dsge model in which monetary policy is modelled through an interest rate feedback rule the dsge model imposes cross coefficient restrictions on a vector autoregressive representation of the data while we are assuming that the data obey a vector autoregressive law of motion we allow for potential deviations from the cross coefficient restrictions at the same time we maintain the assumption that monetary policy follows the same interest rate rule as in the dsge model

the time varying volatility of macroeconomic fluctuations we investigate the sources of the important shifts in the volatility of us mac roeconomic variables in the postwar period to this end we propose the esti mation of dsge models allowing for time variation in the volatility of the structural innovations we apply our estimation strategy to a large scale model of the business cycle and find that shocks specific to the equilibrium condition of investment account for most of the sharp decline in volatility of the last two decades jel c51 e32

news shocks and labour market dynamics in matching models we enrich a baseline real business cycle rbc model with search and matching frictions on the labour market and real frictions that are helpful in accounting for the response of macroeconomic aggregates to shocks the analysis allows shocks to have an unanticipated and a news i e anticipated component the bayesian estimation of the model reveals that the model that includes news shocks on macroeconomic aggregates produces a remarkable fit of the data news shocks in stationary and non stationary tfp investment specific productivity and preference shocks significantly affect labour market variables and explain a sizeable fraction of macroeconomic fluctuations at medium and long run horizons historically news shocks have played a relevant role for output but they have had a limited influence on unemployment

learning in an estimated medium scale dsge model in this paper we evaluate the empirical relevance of learning by private agents in an estimated medium scale dsge model we replace the standard rational expectation assumption in the smets and wouters 2007 model by a constant gain learning mechanism if agents know the correct structure of the model and only learn about the parameters both expectation mechanisms resultin asimilarfit and onlythetransition dynamicsthatare generated byspecific initial beliefs can distinguish the two approaches if in addition agents use only a reduced information set in forming the perceived law of motion the implied model dynamics change and for some initial beliefs the marginal likelihood of the model is further improved however the estimated gain parameter is estimated to be small which suggests a crucial role for the initial beliefs to explain the improved fit the learning models with the highest posterior probabilities add some additional persistence to the dsge model that reduce the gap between the irfs of the dsge model and the more data driven dsge var model however the additional dynamics that are introduced by the learning process do not systematically alter the estimated structural parameters related to the nominal and real frictions in the dsge model jel codes c11 d84 e30 e52

are daily financial data useful for forecasting gdp evidence from mexico this article evaluates the use of financial data sampled at high frequencies to improve short term forecasts of quarterly gdp for mexico the model uses both quarterly and daily sampling frequencies while remaining parsimonious in particular the mixed data sampling midas regression model is employed to deal with the multi frequency problem to preserve parsimony factor analysis and forecast combination techniques are used to summarize the information contained in a data set containing 392 daily financial series our findings suggest that the midas model incorporating daily financial data leads to improvements in quarterly forecasts of gdp growth over traditional models that either rely only on quarterly macroeconomic data or average daily frequency data the evidence suggests that this methodology improves the forecasts for the mexican gdp notwithstanding its higher volatility relative to that of developed countries furthermore we explore the ability of the midas model to provide forecast updates for gdp growth nowcasting

signalling effects of monetary policy we develop a dynamic general equilibrium model in which the policy rate signals the central bank s view about macroeconomic developments to price setters the model is estimated with likelihood methods on a u s data set that includes the survey of professional forecasters as a measure of price setters inflation expectations this model improves upon existing perfect information models in explaining why in the data inflation expectations respond with delays to monetary impulses and remain disanchored for years in the 1970s u s monetary policy is found to signal persistent inflationary shocks explaining why inflation and inflation expectations were so persistently heightened the signalling effects of monetary policy also explain why inflation expectations adjusted more sluggishly than inflation after the robust monetary tightening of the 1980s

has monetary policy become more effective we investigate the implications of changes in the structure of the u s economy for monetary policy effectiveness estimating a vector autoregression over the pre and post 1980 periods we provide evidence of a reduced effect of monetary policy shocks in the latter period we estimate a structural model that replicates well the economy s response in both periods and perform counterfactual experiments to determine the source of the change in the monetary transmission mechanism and in the economy s volatility we find that by responding more strongly to inflation expectations monetary policy has stabilized the economy more effectively in the post 1980 period

estimation of dsge models when the data are persistent dynamic stochastic general equilibrium dsge models are often solved and estimated under specific assumptions as to whether the exogenous variables are difference or trend stationary however even mild departures of the data generating process from these assumptions can severely bias the estimates of the model parameters this paper proposes new estimators that do not require researchers to take a stand on whether shocks have permanent or transitory effects these procedures have two key features first the same filter is applied to both the data and the model variables second the filtered variables are stationary when evaluated at the true parameter vector the estimators are approximately normally distributed not only when the shocks are mildly persistent but also when they have near or exact unit roots simulations show that these robust estimators perform well especially when the shocks are highly persistent yet stationary in such cases linear detrending and first differencing are shown to yield biased or imprecise estimates

identification issues in limited information bayesian analysis of structural macroeconomic models the likelihood of the parameters in structural macroeconomic models typically has non identification regions over which it is constant when sufficiently diffuse priors are used the posterior piles up in such non identification regions use of informative priors can lead to the opposite so both can generate spurious inference we propose priors posteriors on the structural parameters that are implied by priors posteriors on the parameters of an embedding reduced form model an example of such a prior is the jeffreys prior we use it to conduct bayesian limited information inference on the new keynesian phillips curve with a var reduced form for us data

comparing shocks and frictions in us and euro area business cycles a bayesian dsge approach this paper estimates a dsge model with many types of shocks and frictions for both the us and the euro area economy over a common sample period 1974 2002 the structural estimation methodology allows us to investigate whether differences in business cycle behaviour are due to differences in the type of shocks that affect the two economies differences in the propagation mechanism of those shocks or differences in the way the central bank responds to those economic developments our main conclusion is that each of these characteristics is remarkably similar across both currency areas copyright 2005 john wiley sons ltd

testing the implications of long run neutrality for monetary business cycle models this paper compares sample fluctuations of the us business cycle with those predicted by a class of equilibrium monetary business cycle models the predictions of the models are generated using the longrun neutrality restrictions implicit in the models by imposing these restrictions on sample data tests of the ability of the models to replicate the dynamics of the us business cycle are constructed although the predictions of the models for real side variables are rejected there is evidence that the nominal side predictions of the models are not rejected

long run implications of investment specific technological change an attempt is made to disentangle its effects from the more traditional hicksneutral form of technological progress the balanced growth path for the model is characterized and calibrated to u s national income and product account nipa data the quantitative analysis suggests that investment specific technological change accounts for the major part of growth jel e13 030 041 047

real time forecasting with a mixed frequency var this article develops a vector autoregression var for time series which are observed at mixed frequencies quarterly and monthly the model is cast in state space form and estimated with bayesian methods under a minnesota style prior we show how to evaluate the marginal data density to implement a data driven hyperparameter selection using a real time dataset we evaluate forecasts from the mixed frequency var and compare them to standard quarterly frequency var and to forecasts from midas regressions we document the extent to which information that becomes available within the quarter improves the forecasts in real time this article has online supplementary materials

inflation dynamics the role of public debt and policy regimes abstract in a passive monetary and active fiscal policy regime changes in the value of public debt generate wealth effects on households then in contrast to the active monetary and passive fiscal policy regime inflation moves oppositely from the inflation target and a stronger reaction of interest rates to inflation increases the response of inflation to shocks moreover a higher level of public debt increases the response of inflation while a weaker reaction of taxes to debt decreases the response of inflation to shocks in a passive monetary and passive fiscal policy regime both monetary and fiscal policy parameters affect inflation

priors from general equilibrium models for vars abstract this paper uses a simple new keynesian dynamic stochastic general equilibrium model as a prior for a vector autoregression shows that the resulting model is competitive with standard benchmarks in terms of forecasting and can be used for policy analysis jel classification c11 c32 c53 key words bayesian analysis dsge models forecasting vector autoregressions 1 introduction dynamic stochastic general equilibrium dsge models are popular nowadays in macroeconomics they are taught in virtually every economics ph d program and represent a predominant share of publications in the field yet when it comes to policy making these models are scarcely used at least from a quantitative point of view the main quantitative workhorse for policy making at the federal reserve system is frb us a macro econometric model built in the cowles foundation tradition a style of macroeconomics that is no longer taught in many ph d programs 1 in their decision process fed policy makers rely heavily on forecasting they want to know the expected path of inflation in the next few quarters and by how much a 50 basis point increase in the federal funds rate would affect that path frb us offers answers to these questions answers that many macroeconomists would regard with suspicion given both the lucas 1976 critique and the fact that in general the restrictions imposed by cowles foundation models are at odds with dynamic general equilibrium macroeconomics sims 1980 general equilibrium models on the other hand have a hard time providing alternative answers the fact that these models are perceived to do badly in terms of forecasting as they are scarcely parameterized is perhaps one of the reasons why they are not at the forefront of policy making while progress is being made in the development of dsge models that deliver acceptable forecasts e g smets and wouters 2003 this paper proposes an approach that combines a stylized general equilibrium model with a vector autoregression var to obtain a specification that both forecasts well and is usable for policy analysis specifically the approach involves using prior information coming from a dsge model in the estimation of a vector autoregression loosely speaking this prior can be thought of as the result of the following exercise i simulate time series data from the dsge model ii fit a var to these data in practice we replace the sample moments of the simulated data by population moments computed from the dsge model solution since the dsge model depends on unknown structural parameters we use a hierarchical prior in our analysis by placing a distribution on the dsge model parameters a tightness parameter controls the weight of the dsge model prior relative to the weight of the actual sample markov chain monte carlo methods are used to generate draws from the joint posterior distribution of the var and dsge model parameters the paper shows that the approach makes even a fairly stylized new keynesian dsge model competitive with standard benchmarks in terms of forecasting real output growth inflation and the nominal interest rate the three variables that are of most interest to policy makers 2 up to this point our procedure borrows from the work of dejong ingram and whiteman 1993 and ingram and whiteman 1994 who are the first to use priors from dsge models for vars ingram and whiteman showed that prior information from the bare bones stochastic growth model of king plosser and rebelo 1988 is helpful in forecasting real economic activity such as output consumption investment and hours worked in addition to documenting the forecasting performance of a trivariate var with a prior derived from a monetary dsge model this paper makes two contributions that significantly extend the earlier work first we show formally how posterior inference for the var parameters can be translated into posterior inference for dsge model parameters

on the fit of new keynesian models this article provides new tools for the evaluation of dynamic stochastic general equilibrium dsge models and applies them to a large scale new keynesian model we approximate the dsge model by a vector autoregression and then systematically relax the implied cross equation restrictions and document how the model fit changes we also compare the dsge model s impulse responses to structural shocks with those obtained after relaxing its restrictions we find that the degree of misspecification in this large scale dsge model is no longer so large as to prevent its use in day to day policy analysis yet is not small enough to be ignored

on the precision of calvo parameter estimates in structural nkpc models abstract we study the extent of empirical information that can be obtained from alternative structural new keynesian inflation equations concerning the average duration of prices in the united states given that such specifications may be hard to identify using four different indexation and real wage rigidity based models in conjunction with identification robust econometric methods we evaluate the precision of calvo parameter estimates while results are sensitive to calibration and instrument selection we find confidence bounds on the average duration of prices that line up with available micro founded studies statistically significant coefficients for the forcing variables and non zero estimates on the coefficient of lagged inflation

monetary policy trade offs in an estimated open economy dsge model this paper studies the trade offs between stabilizing cpi inflation and alternative measures of the output gap in ramses the riksbank s estimated dynamic stochastic general equilibrium dsge mode

combining var and dsge forecast densities a popular macroeconomic forecasting strategy utilizes many models to hedge against instabilities of unknown timing see among others stock and watson 2004 clark and mccracken 2010 and jore et al 2010 existing studies of this forecasting strategy exclude dynamic stochastic general equilibrium dsge models despite the widespread use of these models by monetary policymakers in this paper we use the linear opinion pool to combine inflation forecast densities from many vector autoregressions vars and a policymaking dsge model the dsge receives a substantial weight in the pool at short horizons provided the var components exclude structural breaks in this case the inflation forecast densities exhibit calibration failure allowing for structural breaks in the vars reduces the weight on the dsge considerably but produces well calibrated forecast densities for inflation

on the informational role of term structure in the us monetary policy rule abstract this paper uses a structural approach based on the indirect inference principle to estimate a standard version of the new keynesian monetary nkm model augmented with term structure using both revised and real time data the estimation results show that the term spread and policy inertia are both important determinants of the us estimated monetary policy rule whereas the persistence of shocks plays a small but significant role when revised and real time data of output and inflation are both considered more importantly the relative importance of term spread and persistent shocks in the policy rule and the shock transmission mechanism drastically change when it is taken into account that real time data are not well behaved

identifying the sources of instabilities in macroeconomic fluctuations abstract this paper investigates the sources of the substantial decrease in output growth volatility in the mid 1980s by identifying which of the structural parameters in a representative new keynesian and structural var models changed overturning conventional wisdom we show that the great moderation was due not only to changes in shock volatilities but also to changes in monetary policy parameters as well as in the private sector s parameters the great moderation was previously attributed to good luck because the alternative sources of instabilities appear to have offsetting effects on output volatility and therefore were impossible to detect using existing techniques