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Working Paper
Searching for Hysteresis
We search for the presence of hysteresis, which we dene as aggregate demand shocks that have a permanent impact on real GDP, in the U.S., the Euro Area, and the U.K. Working with cointegrated structural VARs, we nd essentially no evidence of such effects. Within a Classical statistical framework, it is virtually impossible to detect such shocks. Within a Bayesian context, the presence of these shocks can be mechanically imposed upon the data. However, unless a researcher is willing to impose the restriction that the sign of their long-run impact on GDP is the same for all draws, which amounts ...
Working Paper
Real-Time Forecasting with a Large, Mixed Frequency, Bayesian VAR
We assess point and density forecasts from a mixed-frequency vector autoregression (VAR) to obtain intra-quarter forecasts of output growth as new information becomes available. The econometric model is specified at the lowest sampling frequency; high frequency observations are treated as different economic series occurring at the low frequency. We impose restrictions on the VAR to account explicitly for the temporal ordering of the data releases. Because this type of data stacking results in a high-dimensional system, we rely on Bayesian shrinkage to mitigate parameter proliferation. The ...
Working Paper
Estimating the Effects of Demographics on Interest Rates: A Robust Bayesian Perspective
There are a vast range of estimates for the effect of demographics on interest rates. I show that these magnitudes are not well-identified without data on capital and life-cycle consumption. However, these data are often omitted. Using nonparametric prior sensitivity analysis for an overlapping generations model estimated through Bayesian methods, I show that without these data, small changes in the prior for the discount rate, intertemporal elasticity of substitution, and capital depreciation rate can shift the posterior quantiles for the effects of demographics by up to 1.5 percentage ...
Working Paper
Using stochastic hierarchical aggregation constraints to nowcast regional economic aggregates
Recent decades have seen advances in using econometric methods to produce more timely and higher-frequency estimates of economic activity at the national level, enabling better tracking of the economy in real time. These advances have not generally been replicated at the sub–national level, likely because of the empirical challenges that nowcasting at a regional level presents, notably, the short time series of available data, changes in data frequency over time, and the hierarchical structure of the data. This paper develops a mixed– frequency Bayesian VAR model to address common ...
Working Paper
A Generalized Approach to Indeterminacy in Linear Rational Expectations Models
We propose a novel approach to deal with the problem of indeterminacy in Linear Rational Expectations models. The method consists of augmenting the original state space with a set of auxiliary exogenous equations to provide the adequate number of explosive roots in presence of indeterminacy. The solution in this expanded state space, if it exists, is always determinate, and is identical to the indeterminate solution of the original model. The proposed approach accommodates determinacy and any degree of indeterminacy, and it can be implemented even when the boundaries of the determinacy region ...
Working Paper
Reconciled Estimates of Monthly GDP in the US
In the US, income and expenditure-side estimates of GDP (GDPI and GDPE) measure "true" GDP with error and are available at a quarterly frequency. Methods exist for using these proxies to produce reconciled quarterly estimates of true GDP. In this paper, we extend these methods to provide reconciled historical true GDP estimates at a monthly frequency. We do this using a Bayesian mixed frequency vector autoregression (MF-VAR) involving GDPE, GDPI, unobserved true GDP, and monthly indicators of short-term economic activity. Our MF-VAR imposes restrictions that reflect a measurement-error ...
Working Paper
Financial Frictions, Financial Shocks, and Aggregate Volatility
I revisit the Great Inflation and the Great Moderation. I document an immoderation in corporate balance sheet variables so that the Great Moderation is best described as a period of divergent patterns in volatilities for real, nominal and financial variables. A model with time-varying financial frictions and financial shocks allowing for structural breaks in the size of shocks and the institutional framework is estimated. The paper shows that (i) while the Great Inflation was driven by bad luck, the Great Moderation is mostly due to better institutions; (ii) the slowdown in credit spreads is ...
Working Paper
Specification Choices in Quantile Regression for Empirical Macroeconomics
Quantile regression has become widely used in empirical macroeconomics, in particular for estimating and forecasting tail risks to macroeconomic indicators. In this paper we examine various choices in the specification of quantile regressions for macro applications, for example, choices related to how and to what extent to include shrinkage, and whether to apply shrinkage in a classical or Bayesian framework. We focus on forecasting accuracy, using for evaluation both quantile scores and quantile-weighted continuous ranked probability scores at a range of quantiles spanning from the left to ...
Working Paper
Real-Time Forecasting and Scenario Analysis using a Large Mixed-Frequency Bayesian VAR
We use a mixed-frequency vector autoregression to obtain intraquarter point and density forecasts as new, high frequency information becomes available. This model, delineated in Ghysels (2016), is specified at the lowest sampling frequency; high frequency observations are treated as different economic series occurring at the low frequency. As this type of data stacking results in a high-dimensional system, we rely on Bayesian shrinkage to mitigate parameter proliferation. We obtain high-frequency updates to forecasts by treating new data releases as conditioning information. The same ...
Report
Recent changes in the U.S. business cycle
The U.S. business cycle expansion that started in March 1991 is the longest on record. This paper uses statistical techniques to examine whether this expansion is a onetime unique event or whether its length is a result of a change in the stability of the U.S. economy. Bayesian methods are used to estimate a common factor model that allows for structural breaks in the dynamics of a wide range of macroeconomic variables. We find strong evidence that a reduction in volatility is common to the series examined. Further, the reduction in volatility implies that future expansions will be ...