decomposing the declining volatility of long term inflation expectations abstract the level and volatility of survey based measures of long term inflation expectations have come down dramatically over the past several decades to capture these changes in inflation dynamics we embed both short and long term expectations into a medium scale var model with stochastic volatility the model estimates attribute most of the marked decline in the volatility of expectations to smaller shocks to long run inflation expectations according to our estimates the volatility of shocks plummeted in the early to mid 1980s moved to a somewhat higher level that prevailed for much of the 1990s and then declined to and remained at very low levels

debt regimes and the effectiveness of monetary policy abstract this paper develops a medium scale non linear model of the us economy our proposed model a threshold vector autoregression with stochastic volatility assumes that changes in government debt to gdp ratios drive the transition between regimes capturing low and high debt regimes the introduction of hierarchical priors enables us to flexibly shrink the empirical model towards the moments implied by a dynamic stochastic general equilibrium model in the empirical application we analyze regime specific monetary policy shocks our findings indicate that the effect of monetary policy is less pronounced in high debt regimes pointing towards differences in the underlying monetary policy transmission mechanisms forecast error variance decompositions enable us to shed further light on the relative importance of monetary policy shocks within different debt regimes in terms of explaining the variance of forecast errors

macroeconomic uncertainty through the lens of professional forecasters abstractwe analyze the evolution of macroeconomic uncertainty in the united states based on the forecast errors of consensus survey forecasts of various economic indicators comprehensive information contained in the survey forecasts enables us to capture a real time measure of uncertainty surrounding subjective forecasts in a simple framework we jointly model and estimate macroeconomic common and indicator specific uncertainties of four indicators using a factor stochastic volatility model our macroeconomic uncertainty estimates have three major spikes has three major spikes aligned with the 1973 1975 1980 and 2007 2009 recessions while other recessions were characterized by increases in indicator specific uncertainties we also show that the selection of data vintages affects the estimates and relative size of jumps in estimated uncertainty series finally our macroeconomic uncertainty has a persistent negative impact on real economic activity rather than producing wait and see dynamics

vacancies unemployment and the phillips curve abstract the canonical new keynesian phillips curve has become a standard component of models designed for monetary policy analysis however in the basic new keynesian model there is no unemployment all variation in labor input occurs along the intensive hours margin and the driving variable for inflation depends on workers marginal rates of substitution between leisure and consumption in this paper we incorporate a theory of unemployment into the new keynesian theory of inflation and empirically test its implications for inflation dynamics we show how a traditional phillips curve linking inflation and unemployment can be derived and how the elasticity of inflation with respect to unemployment depends on structural characteristics of the labor market such as the matching technology that pairs vacancies with unemployed workers we estimate on us data the phillips curve generated by the model while we can reject the baseline new keynesian phillips curve in favor of the search frictions specification we show it is still too stylized to fully describe the dynamics of firms marginal costs

sequential bayesian inference for vector autoregressions with stochastic volatility abstract we develop a sequential monte carlo smc algorithm for bayesian inference in vector autoregressions with stochastic volatility var sv the algorithm builds particle approximations to the sequence of the model s posteriors adapting the particles from one approximation to the next as the window of available data expands the parallelizability of the algorithm s computations allows the adaptations to occur rapidly our particular algorithm exploits the ability to marginalize many parameters from the posterior analytically and embeds a known markov chain monte carlo mcmc algorithm for the model as an effective mutation kernel for fighting particle degeneracy we show that relative to using mcmc alone our algorithm increases the precision of inference while reducing computing time by an order of magnitude when estimating a medium scale var sv model

real time density forecasts from bayesian vector autoregressions with stochastic volatility central banks and other forecasters are increasingly interested in various aspects of density forecasts however recent sharp changes in macroeconomic volatility including the great moderation and the more recent sharp rise in volatility associated with increased variation in energy prices and the deep global recession pose significant challenges to density forecasting accordingly this paper examines with real time data density forecasts of u s gdp growth unemployment inflation and the federal funds rate from bayesian vector autoregression bvar models with stochastic volatility the results indicate that adding stochastic volatility to bvars materially improves the real time accuracy of density forecasts this article has supplementary material online

macroeconomic forecasting and structural change the aim of this paper is to assess whether explicitly modeling structural change increases the accuracy of macroeconomic forecasts we produce real time out of sample forecasts for inflation the unemployment rate and the interest rate using a time varying coefficients var with stochastic volatility tv var for the us the model generates accurate predictions for the three variables in particular for inflation the tv var outperforms in terms of mean square forecast error all the competing models fixed coefficients vars time varying ars and the na ove random walk model these results are also shown to hold over the period commonly referred to as the great moderation

measuring uncertainty and its impact on the economy we propose a new framework for measuring uncertainty and its effects on the economy based on a large var model with errors whose stochastic volatility is driven by two common unobservable factors representing aggregate macroeconomic and financial uncertainty the uncertainty measures can also influence the levels of the variables so that contrary to most existing measures ours reflect changes in both the conditional mean and volatility of the variables and their impact on the economy can be assessed within the same framework moreover identification of the uncertainty shocks is simplified with respect to standard var based analysis in line with the favar approach and with heteroskedasticity based identification finally the model which is also applicable in other contexts is estimated with a new bayesian algorithm which is computationally efficient and allows for jointly modeling many variables while previous var models with stochastic volatility could only handle a handful of variables empirically we apply the method to estimate uncertainty and its effects using us data finding that there is indeed substantial commonality in uncertainty sizable effects of uncertainty on key macroeconomic and financial variables with responses in line with economic theory

evolving international inflation dynamics world and country specific factors inflation in the most industrialized economies of the world has an important international common component that accounts for the historical decline in the national rates country specific conditions explain the rise in inflation volatility of the late 1970s and early 1980s and the subsequent fall during the last decade the world contribution to the variance of inflation has become increasingly more important than national contributions monetary policy was a relevant source of country specific fluctuations our conclusions are based on a time varying dynamic factor model applied to a large panel of inflation indicators

real time macroeconomic forecasting with a heteroskedastic inversion copula there is a growing interest in allowing for asymmetry in the density forecasts of macroeconomic variables in multivariate time series this can be achieved with a copula model where both serial a

sectoral shifts and cyclical unemployment a substantial fraction of cyclical unemployment is better characterized as fluctuations of the frictional or natural rate than as deviations from some relatively stable natural rate shifts of employment demand between sectors of the economy necessitate continuous labor reallocation since it takes time for workers to find new jobs some unemployment is unavoidable this paper presents evidence that most of the unemployment fluctuations of the seventies unlike those in the sixties were induced by unusual structural shifts within the u s economy simple time series models of layoffs and unemployment are constructed that include a measure of structural shifts within the labor market these models are estimated and a derived natural rate series is constructed

forecasting government bond yields with large bayesian vector autoregressions abstract we propose a new approach to forecasting the term structure of interest rates which allows to efficiently extract the information contained in a large panel of yields in particular we use a large bayesian vector autoregression bvar with an optimal amount of shrinkage towards univariate ar models the optimal shrinkage is chosen by maximizing the marginal likelihood of the model focusing on the us we provide an extensive study on the forecasting performance of the proposed model relative to most of the existing alternative specifications while most of the existing evidence focuses on statistical measures of forecast accuracy we also consider alternative measures based on trading schemes and portfolio allocation we extensively check the robustness of our results using different datasets and monte carlo simulations we find that the proposed bvar approach produces competitive forecasts systematically more accurate than random walk forecasts even though the gains are small

macroeconomic forecasting performance under alternative specifications of time varying volatility summary this paper compares alternative models of time varying volatility on the basis of the accuracy of real time point and density forecasts of key macroeconomic time series for the usa we consider bayesian autoregressive and vector autoregressive models that incorporate some form of time varying volatility precisely random walk stochastic volatility stochastic volatility following a stationary ar process stochastic volatility coupled with fat tails garch and mixture of innovation models the results show that the ar and var specifications with conventional stochastic volatility dominate other volatility specifications in terms of point forecasting to some degree and density forecasting to a greater degree copyright 2014 john wiley sons ltd

federal reserve information and the behavior of interest rates this paper tests for the existence of asymmetric information between the federal reserve and the public by examining federal reserve and commercial inflation forecasts it demonstrates that the federal reserve has considerable information about inflation beyond what is known to commercial forecasters it also shows that monetary policy actions provide signals of the federal reserve s information and that commercial forecasters modify their forecasts in response to those signals these findings may explain why long term interest rates typically rise in response to shifts to tighter monetary policy jel e52 e43 d82 asymmetric information between the federal reserve and the public is a phenomenon that is often posited but rarely tested numerous models of central bank behavior for example show that the existence of asymmetric information has important implications for the effectiveness of policy and the consequences of dynamic inconsistency yet there

common and country specific economic uncertainty abstract we use a factor model with stochastic volatility to decompose the time varying variance of macroeconomic and financial variables into contributions from country specific uncertainty and uncertainty common to all countries we find that the common component plays an important role in driving the time varying volatility of nominal and financial variables the cross country co movement in volatility of real and financial variables has increased over time with the common component becoming more important over the last decade simulations from a two country dsge model featuring epstein zin preferences suggest that increased globalisation and trade openness may be the driving force behind the increased cross country correlation in volatility

common drifting volatility in large bayesian vars the general pattern of estimated volatilities of macroeconomic and financial variables is often broadly similar we propose two models in which conditional volatilities feature comovement and study them using u s macroeconomic data the first model specifies the conditional volatilities as driven by a single common unobserved factor plus an idiosyncratic component we label this model bvar with general factor stochastic volatility bvar gfsv and we show that the loss in terms of marginal likelihood from assuming a common factor for volatility is moderate the second model which we label bvar with common stochastic volatility bvar csv is a special case of the bvar gfsv in which the idiosyncratic component is eliminated and the loadings to the factor are set to 1 for all the conditional volatilities such restrictions permit a convenient kronecker structure for the posterior variance of the var coefficients which in turn permits estimating the model even with large datasets while perhaps misspecifi

the changing transmission of uncertainty shocks in the u s this article investigates if the impact of uncertainty shocks on the u s economy has changed over time to this end we develop an extended factor augmented vector autoregression var model that simultaneously allows the estimation of a measure of uncertainty and its time varying impact on a range of variables we find that the impact of uncertainty shocks on real activity and financial variables has declined systematically over time in contrast the response of inflation and the short term interest rate to this shock has remained fairly stable simulations from a nonlinear dynamic stochastic general equilibrium dsge model suggest that these empirical results are consistent with an increase in the monetary authorities antiinflation stance and a flattening of the phillips curve supplementary materials for this article are available online

unemployment and vacancies with sectoral shifts recent analyses of unemployment vacancy series suggest that aggregate shocks rather than sectoral shocks are the primary factors responsible for unemployment fluctuations this inference follows from two widely held beliefs sectoral shocks induce only positive unemployment vacancy comovements while negative comovements are necessarily the result of aggregate demand shocks this paper describes an equilibrium matching model that identifies plausible circumstances in which neither assumption is correct thus suggesting that unemployment vacancy data are inconclusive interestingly this model s novel results are due to standard features in the contracting literature firms experience relative price shocks and negotiate contracts that prescribe temporary layoffs copyright 1994 by american economic association

labor market search the taylor principle and indeterminacy abstract in a sticky price model with labor market search and matching frictions forecast based interest rate policy almost always induces indeterminacy when it is strictly inflation targeting and satisfies the taylor principle indeterminacy is due to a vacancy channel of monetary policy that makes inflation expectations self fulfilling the effect of this channel strengthens as the sluggishness of the adjustment of employment relative to that of consumption increases when this relative sluggishness is high the taylor principle fails to ensure determinacy regardless of whether the policy is forecast based or outcome based whether it is strictly or flexibly inflation targeting or contains policy rate smoothing

callable bonds a risk reducing signalling mechanism a comment the existence of callable bonds has been somewhat of a puzzle the call feature provides firms with a valuable interest rate option but the value of this option should be exactly offset by the creditor s demand for a higher interest rate as compensation one explanation for the call provision from myers 4 bodie and taggart 3 and barnea haugen and senbet 2 is that callable bonds may be used to reduce some agency costs another explanation from robbins and schatzberg 5 is that callable bonds can signal a firm s better prospects in the presence of asymmetric information one possible problem with the agency cost and signalling explanations of callable bonds is that short term debt may serve the same functions in all four studies indeed short term debt is equivalent to long term debt in the theoretical sections of the agency cost studies however robbins and schatzberg hereafter rs suggest that short term debt fails to provide the risk sharing opportunities inherent in callable bonds thus they suggest that a signalling explanation provides a unique role for callable bonds one limitation of rs s results is that they are based on an example that makes a series of strong assumptions about a two stage lottery faced by good news and bad news firms in order for their model to have general applicability it would be desirable to demonstrate that their results hold under more general assumptions the results of this study suggest that their findings cannot be generalized without further assumptions callable bonds do not yield a separating equilibrium result when only a minor change is made in two of the lottery probabilities suggesting that their results are far from robust to minor changes in assumptions moreover callable bonds may fail to generate a separating equilibrium even for some good news firms that conform to rs s original model because bad news firms that do not meet their assumptions may attempt to mimic good news firms that do the risk sharing result is also very sensitive to the specific assumptions made by robbins and schatzberg specifically callable bonds increase the risk borne by management if one change is made in the numeric values of one of the lottery payouts the paper begins with a review of the relevant portions of robbins and schatzberg s model section ii provides a counterexample in which callable bonds fail to provide a separating equilibrium section iii provides a counterexample in which callable bonds fail to provide risk sharing debt and the paper concludes with a summary

callable bonds a risk reducing signalling mechanism a reply robbins and schatzberg 3 hereafter rs argued that callable bonds constitute a risk reducing signalling mechanism wall 6 hereafter wall responds that there exist examples quite similar to the one presented in rs for which short term debt proves to be a superior instrument in wall s first example short term debt can signal good prospects although callable bonds cannot a second example purports to show strictly superior risk reduction capabilities when either short term debt or callable bonds can signal wall contends therefore that the class of problems for which callable bonds serve as a risk reducing signalling mechanism lacks generality in this reply we restrict our notion of what it means for securities offering to be risk reducing at the same time that it signals in doing so we find that wall s first example is one from a broad class of problems for which it is impossible both to reduce risk and to signal the fact that callable bonds are not optimal for this problem is thus quite consistent with the idea that callable bonds constitute a risk reducing signalling mechanism furthermore we demonstrate that no power should be ascribed to wall s second example for it rests upon failure to note a subtle point in rs short term debt is strictly superior in the second example only if we do not allow the firm to overcapitalize its investment project if as in rs we do allow securities offerings that raise excess capital the excess to be placed in a riskless investment opportunity we can obtain a callable bonds contract that equals the performance of short term debt if we introduce new corporate strategic behavior that seeks additional enhancement of the corporate manager s decision making namely selling off risky projects once information about prospects becomes symmetric callable bonds prove strictly superior before providing these results we begin by demonstrating that wall s assertions are automatically questionable because short term debt is equivalent to a degenerate subclass of callable bonds

forecasting with medium and large bayesian vars this paper is motivated by the recent interest in the use of bayesian vars for forecasting even in cases where the number of dependent variables is large in such cases factor methods have been traditionally used but recent work using a particular prior suggests that bayesian var methods can forecast better in this paper we consider a range of alternative priors which have been used with small vars discuss the issues which arise when they are used with medium and large vars and examine their forecast performance using a us macroeconomic dataset containing 168 variables we find that bayesian vars do tend to forecast better than factor methods and provide an extensive comparison of the strengths and weaknesses of various approaches typically we find that the simple minnesota prior forecasts well in medium and large vars which makes this prior attractive relative to computationally more demanding alternatives our empirical results show the importance of using forecast metrics based on the entire predictive density instead of relying solely on those based on point forecasts

reallocation shocks persistence and nominal rigidities abstract we reconsider the role of reallocation shocks in a simple new keynesian model with search and matching frictions the sign of the conditional correlation between unemployment and vacancies depends on the degree of price rigidity and on the persistence of the shock therefore a non negligible role for reallocation shocks in driving business cycle fluctuations cannot be ruled out on theoretical grounds

business cycles and labor market search the quantitative implications of labor market search for economic fluctuations are evaluated in the context of a real business cycle model incorporating labor market search into the model is found to improve its empirical performance along several dimensions in particular hours now fluctuate substantially more than wages and the contemporaneous correlation between hours and productivity falls in addition the model replicates the observation that output growth displays positive autocorrelation at short horizons overall the empirical results suggest that the labor market search environment embodies a quantitatively important propagation mechanism copyright 1996 by american economic association

bayesian methods for dynamic multivariate models if dynamic multivariate models are to be used to guide decisionmaking it is important that probability assessments of forecasts or policy projections be provided when identified bayesian vector autoregression var models are presented with error bands in the existing literature both conceptual and numerical problems have not been dealt with in an internally consistent way in this paper the authors develop methods to introduce prior information in both reduced form and structural var models without introducing substantial new computational burdens their approach makes it feasible to use a single large dynamic framework for example twenty variable models for tasks of policy projections copyright 1998 by economics department of the university of pennsylvania and the osaka university institute of social and economic research association

modeling time varying uncertainty of multiple horizon forecast errors we estimate uncertainty measures for point forecasts obtained from survey data pooling information embedded in observed forecast errors for different forecast horizons to track time varying uncer

constructing optimal density forecasts from point forecast combinations summary decision makers often observe point forecasts of the same variable computed for instance by commercial banks imf and the world bank but the econometric models used by such institutions are frequently unknown this paper shows how to use the information available on point forecasts to compute optimal density forecasts our idea builds upon the combination of point forecasts under general loss functions and unknown forecast error distributions we use real time data to forecast the density of us inflation the results indicate that the proposed method materially improves the real time accuracy of density forecasts vis a vis those from the unknown individual econometric models copyright 2013 john wiley sons ltd

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

assessing international commonality in macroeconomic uncertainty and its effects this paper uses a large vector autoregression var to measure international macroeconomic uncertainty and its effects on major economies using two datasets one with gdp growth rates for 19 industrialized countries and the other with a larger set of macroeconomic indicators for the u s euro area and u k using basic factor model diagnostics we first provide evidence of significant commonality in international macroeconomic volatility with one common factor accounting for strong comovement across economies and variables we then turn to measuring uncertainty and its effects with a large var in which the error volatilities evolve over time according to a factor structure the volatility of each variable in the system reflects time varying common global components and idiosyncratic components in this model global uncertainty is allowed to contemporaneously affect the macroeconomies of the included nations both the levels and volatilities of the included variables in this setup uncertainty and its effects are estimated in a single step within the same model our estimates yield new measures of international macroeconomic uncertainty and indicate that uncertainty shocks surprise increases lower gdp and many of its components adversely affect labor market conditions lower stock prices and in some economies lead to an easing of monetary policy

sectoral versus aggregate shocks a structural factor analysis of industrial production using factor methods we decompose industrial production ip into components arising from aggregate and sector specific shocks an approximate factor model finds that nearly all of ip variability is associated with common factors we then use a multisector growth model to adjust for the effects of input output linkages in the factor analysis thus a structural factor analysis indicates that the great moderation was characterized by a fall in the importance of aggregate shocks while the volatility of sectoral shocks was essentially unchanged consequently the role of idiosyncratic shocks increased considerably after the mid 1980s explaining half of the quarterly variation in ip

fragility and the effect of international uncertainty shocks abstract when economic systems are fragile even modest shocks for example a shock to international capital movements can have strong negative effects on key macroeconomic fundamentals this paper proposes a large scale bayesian vector autoregression with factor stochastic volatility to investigate the macroeconomic consequences of international uncertainty shocks in g7 countries and shows that uncertainty increases fragility the factor structure enables us to identify an international uncertainty shock by assuming that it is the joint volatility process that determines the dynamics of the variance covariance matrix of the common factors to allow for first and second moment shocks we moreover assume that the uncertainty factor enters the var equation as an additional regressor our findings suggest that an international uncertainty shock has negative effects across all economies and variables under consideration leading to strong declines in output prices exports interest rates and equity prices the precise degree of fragility varies across countries a simple correlation exercise suggests that structural differences may be partially responsible for the observed differences

callable bonds a risk reducing signalling mechanism the theory of financial economics has failed to distinguish advantages of callable bonds from those of short term debt this paper shows that either type of borrowing can signal a firm s better prospects but that short term debt does so at the cost of weakened risk sharing with capital markets by issuing either equity or long term non callable debt a firm with poor investment opportunities will not pool its prospects with those of a better firm but equity produces superior risk sharing perhaps this explains the almr ost complete absence of long term non callable bonds from observed corporate capital structures financial theory has found only moderate success in explaining the routine inclusion of call provisions among the covenants of corporate bonds in the absence of market imperfections or incompleteness the incremental compensation promised to bondholders should exactly offset the value of the call provision retained by equityholders indifference should obtain 1 nevertheless it is hard to accept indifference as an explanation given the near universality of call provisions in corporate bond contracts in this paper we argue that in the presence of asymmetric information about investment quality corporate managers can signal their firm s better prospects by issuing bonds that include call provisions our major result shows that this signalling mechanism can be more attractive to risk averse managers than would be the choice of short term debt which could also serve to signal furthermore we demonstrate that non callable corporate debt is a dominated security that is both it and equity signal bad news but equity provides risk sharing this finding helps to explain the relative absence of long term non callable debt from corporate financial markets previous attempts to explain the prevalence of call provisions in corporate bond contracts fall into four categories two categories involve pure wealth transfers from bondholders to stockholders in these constant sum environments a gain to one group constitutes a loss to the other in the first category managers possess private information with regard to future interest rate movements issuing callable bonds will capture gains for stockholders when anticipated drops

mismatch shocks and unemployment during the great recession summary we investigate the macroeconomic consequences of fluctuations in the effectiveness of the labor market matching process with a focus on the great recession we conduct our analysis in the context of an estimated medium scale dynamic stochastic general equilibrium model with sticky prices and equilibrium search unemployment that features a shock to the matching efficiency or mismatch shock we find that this shock is not important for unemployment fluctuations in normal times however it plays a somewhat larger role during the great recession when it contributes to raise the actual unemployment rate by around 1 3 percentage points and the natural rate by around 2 percentage points the mismatch shock is the dominant driver of the natural rate of unemployment and explains part of the recent shift of the beveridge curve copyright 2016 john wiley sons ltd

time varying impact of uncertainty shocks on the us housing market abstract this paper investigates the impact of uncertainty shocks on the housing market of the united states using the time varying parameter factor augmented vector autoregression tvp favar we use a comprehensive quarterly time series dataset on real economic activity price and financial variables besides housing market variables covering the period 1963 q1 to 2014 q3 in addition to housing prices we also consider variables related to home sales permits and starts in general the results of the cumulative response of housing variables to a one standard deviation positive uncertainty shock at the one four eight and twelve quarter horizon tends to change over time both in terms of sign and magnitude with the uncertainty shock primarily negatively affecting the housing variables in particular prices permits and starts in longer runs i e two and three years ahead horizons