Leaning into the Wind: A Structural VAR Investigation of UK Monetary Policy*

This paper adapts Uhlig's [Journal of Monetary Economics (2005) forthcoming] sign restriction identification methodology to investigate the effects of UK monetary policy using a structural vector autoregression (VAR). It shows that shocks which can reasonably be described as monetary policy shocks have played only a small role in the total variation of UK monetary and macroeconomic variables. Most of the variation in UK monetary variables has been due to their systematic reaction to other macroeconomic shocks, namely non‐monetary aggregate demand, aggregate supply, and oil price shocks. We also find, without imposing any long run identifying restrictions, that aggregate supply shocks have permanent effects on output.     

The sources of unemployment fluctuations: an empirical application to the Italian case

The paper analyses the rise in Italian unemployment in a small structural VAR (sVAR) based on a Layard–Nickell framework. Unemployment is driven by fully permanent and long-lived but temporary shocks. The unemployment component due to demand shocks appears sizeable, with swings amounting to 4 percentage points, and quite persistent, showing an almost continuous increase since the beginning of the 1980s. Nonetheless, the bulk of unemployment rises is attributed to non-demand factors: temporary (productivity and labour supply) and permanent (labelled as shocks to wage bargaining). The latter explain a 2.5-point rise during the 1970s, but showing no further increases since then.     

PERMANENT AND TRANSITORY SHOCKS,AND THE UK BUSINESS CYCLE

In this paper the business cycle properties of UK data are investigated using a VAR technique. A Real Business Cycle (RBC) model is formulated. The model includes both permanent and transitory shocks to technology. The business cycle properties of the data and the model are investigated by deriving the expected changes over various forecast horizons from a VAR model. It is found, contrary to evidence in Rotemberg and Woodford (1996), that the model can account for many features of the data and that temporary shocks are pertinent in order to explain the business cycle moments. The main difference between theory and data is present in hours worked. © 1997 by John Wiley & Sons, Ltd.     

Long‐run neutrality of demand shocks: Revisiting Blanchard and Quah (1989) with independent structural shocks

With reference to a stylized theoretical macromodel, Blanchard and Quah (American Economic Review, 1989, 79, 655–673) identify empirical aggregate supply (e.g., productivity) and demand shocks by assuming that the latter are neutral for economic activity in the long run. Taking advantage of recent contributions to the structural VAR literature and data‐based identification, we find that effects of unique independent non‐Gaussian structural shocks support this assumption. Moreover, unlike the results in Blanchard and Quah, statistically identified supply shocks exhibit (insignificantly) opposite impacts on gross domestic product and unemployment in the short run. In comparison with benchmark results obtained under assumed long‐run neutrality, statistical identification points to a stronger role of aggregate supply shocks for shaping temporary profiles of US unemployment during the recessionary period 1973:Q3–1975:Q1.     

The relationship between the Beveridge–Nelson decomposition and other permanent–transitory decompositions that are popular in economics

The Beveridge–Nelson (BN) decomposition is a model-based method for decomposing time series into permanent and transitory components. When constructed from an ARIMA model, it is closely related to decompositions based on unobserved components (UC) models with random walk trends and covariance stationary cycles. The decomposition when extended to I(2)$I\left(2\right)$ models can also be related to non-model-based signal extraction filters such as the HP filter. We show that the BN decomposition provides information on the correlation between the permanent and transitory shocks in a certain class of UC models. The correlation between components is known to determine the smoothed estimates of components from UC models. The BN decomposition can also be used to evaluate the efficacy of alternative methods. We also demonstrate, contrary to popular belief, that the BN decomposition can produce smooth cycles if the reduced form forecasting model is appropriately specified.     

Consumer misperceptions,uncertain fundamentals,and the business cycle

This paper estimates the importance of shocks to consumer misperceptions “noise shocks” for U.S. business cycle fluctuations. I embed imperfect information as in Lorenzoni (2009) into a Smets and Wouters (2007)-type DSGE model. Agents only observe aggregate productivity and a signal about the permanent component contaminated with noise. Based on this information agents form beliefs about the temporary and the permanent component of productivity. Shocks to the signal (noise shocks) trigger aggregate fluctuations unrelated to changes in productivity. Bayesian estimation shows that noise shocks explain up to 14 percent of output and up to 25 percent of consumption fluctuations. Nominal rigidities and the specification of the monetary policy rule are crucial for the importance of noise shocks. These features help to resolve conflicting results in the previous literature.     

Temperature shocks and welfare costs

This paper examines the welfare implications of rising temperatures. Using a standard VAR, we empirically show that a temperature shock has a sizable, negative and statistically significant impact on TFP, output, and labor productivity. We rationalize these findings within a production economy featuring long-run temperature risk. In the model, macro-aggregates drop in response to a temperature shock, consistent with the novel evidence in the data. Such adverse effects are long-lasting. Over a 50-year horizon, a one-standard deviation temperature shock lowers both cumulative output and labor productivity growth by 1.4 percentage points. Based on the model, we also show that temperature risk is associated with non-negligible welfare costs which amount to 18.4% of the agent’s lifetime utility and grow exponentially with the size of the impact of temperature on TFP. Finally, we show that faster adaptation to temperature shocks results in lower welfare costs. These welfare benefits become substantially higher in the presence of permanent improvements in the speed of adaptation.     

Assessing the Transmission of Monetary Policy Using Time‐varying Parameter Dynamic Factor Models*

This article extends the current literature which questions the stability of the monetary transmission mechanism, by proposing a factor‐augmented vector autoregressive (VAR) model with time‐varying coefficients and stochastic volatility. The VAR coefficients and error covariances may change gradually in every period or be subject to abrupt breaks. The model is applied to 143 post‐World War II quarterly variables fully describing the US economy. I show that both endogenous and exogenous shocks to the US economy resulted in the high inflation volatility during the 1970s and early 1980s. The time‐varying factor augmented VAR produces impulse responses of inflation which significantly reduce the price puzzle. Impulse responses of other indicators of the economy show that the most notable changes in the transmission of unanticipated monetary policy shocks occurred for gross domestic product, investment, exchange rates and money.     

Stochastic trends and economic fluctuations in a small open economy

In this paper we describe how restricted vector autoregressions can be employed to examine the sources of macroeconomic fluctuations. We show how cointegration restrictions can be used to identify a VAR system with common stochastic trends subject to transitory and permanent changes in average growth, and how we may investigate the system's responses to permanent shocks, i.e. to innovations to the trends. Theoretical cointegration vectors are derived from a small open economy growth model for terms of trade, real GDP, real consumption, and real investments. Applying these methods to Swedish annual data (1875–1986) we find that permanent real (supply) shocks account for most of the fluctuations in GDP, even in the short run.     

The puzzling effects of monetary policy in VARs: Invalid identification or missing information?

Standard vector autoregressions (VARs) often find puzzling effects of monetary policy shocks. Is this due to an invalid (recursive) identification scheme, or because the underlying small‐scale VAR neglects important information? I employ factor methods and external instruments to answer this question and provide evidence that the root cause is missing information. In particular, while a recursively identified dynamic factor model yields conventional monetary policy effects across the board, a small‐scale VAR identified via external instruments does not. Importantly, the discrepancy between both models largely disappears once the information set of the VAR is augmented via factors. This finding is comforting news for the recent monetary literature. Two leading empirical advances with different underlying assumptions—namely external instruments (applied to a factor‐augmented VAR) and dynamic factor models (identified recursively)—find very similar effects of monetary policy shocks, cross‐verifying each other.     

The non‐linear dynamics of output and unemployment in the U.S.

This paper studies the joint dynamics of U.S. output and unemployment rate in a non‐linear VAR model. The non‐linearity is introduced through a feedback variable that endogenously augments the output lags of the VAR in recessionary phases. Sufficient conditions for the ergodicity of the model, potentially applying to a larger class of threshold models, are provided. The linear specification is rejected in favour of our threshold VAR. However, in the estimation the feedback is found to be statistically significant only on unemployment, while it transmits to output through its cross‐correlation. This feedback effect from recessions generates important asymmetries in the propagation of shocks, a possible key to interpret the divergence in the measures of persistence in the literature. The regime‐dependent persistence also explains the finding that the feedback from recession exerts a positive effect on the long‐run growth rate of the economy, an empirical validation of the Schumpeterian macroeconomic theories. Copyright © 2001 John Wiley & Sons, Ltd.     

Correlated income shocks and excess smoothness of consumption

In the literature, econometricians typically assume that household income is the sum of a random walk permanent component and a transitory component, with uncorrelated permanent and transitory shocks. Using data on realized individual incomes and individual expectations of future incomes from the Survey of Italian Households׳ Income and Wealth, I find that permanent and transitory shocks are negatively correlated. Relaxing the assumption of no correlation between the shocks, I explore the effects of correlated income shocks on the estimated consumption insurance against permanent and transitory shocks, and consumption smoothness using a life-cycle model with self-insurance calibrated to U.S. data. Negatively correlated income shocks result in smoother consumption, and upward-biased estimates of the insurance against transitory (and permanent when borrowing constraints are not tight) income shocks. While the life-cycle model with negatively correlated shocks fits well the sensitivity of consumption to current income shocks observed in U.S. data, it falls short of explaining the sensitivity of consumption to income shocks cumulated over a longer horizon.     

In Search of the Transmission Mechanism of Fiscal Policy in the Euro Area

This paper applies the DSGE‐VAR methodology to assess the size of fiscal multipliers in the data and the relative contributions of two transmission mechanisms of government spending shocks, namely hand‐to‐mouth consumers and Edgeworth complementarity. Econometric experiments show that a DSGE model with Edgeworth complementarity is a better representation of the transmission mechanism of fiscal policy as it yields dynamic responses close to those obtained with the flexible DSGE‐VAR model (i.e. an impact output multiplier larger than one and a crowding‐in of private consumption). The estimated share of hand‐to‐mouth consumers is too small to replicate the positive response of private consumption. Copyright © 2016 John Wiley & Sons, Ltd.     

Detecting Co‐Movements in Non‐Causal Time Series

This paper introduces the notion of common non‐causal features and proposes tools to detect them in multivariate time series models. We argue that the existence of co‐movements might not be detected using the conventional stationary vector autoregressive (VAR) model as the common dynamics are present in the non‐causal (i.e. forward‐looking) component of the series. We show that the presence of a reduced rank structure allows to identify purely causal and non‐causal VAR processes of order P>1 even in the Gaussian likelihood framework. Hence, usual test statistics and canonical correlation analysis can be applied, where either lags or leads are used as instruments to determine whether the common features are present in either the backward‐ or forward‐looking dynamics of the series. The proposed definitions of co‐movements are also valid for the mixed causal—non‐causal VAR, with the exception that a non‐Gaussian maximum likelihood estimator is necessary. This means however that one loses the benefits of the simple tools proposed. An empirical analysis on Brent and West Texas Intermediate oil prices illustrates the findings. No short run co‐movements are found in a conventional causal VAR, but they are detected when considering a purely non‐causal VAR.     

CO‐INTEGRATING VAR MODELS AND ECONOMIC POLICY

This paper surveys some relevant contributions to the economic literature on co‐integrating vector autoregressive (VAR) models [vector error correction mechanisms (VECMs)], emphasizing their usefulness for economic policy. It further discusses some theoretical aspects that are necessary for a complete understanding of their potential. The theoretical introduction of the co‐integrating VAR model is followed by an illustration of its applications to monetary policy, fiscal policy and exchanges rates as well as in establishing the effects of structural bilateral shocks between countries (the so‐called global VAR, or GVAR, models). Special attention is paid to the VECM capacities of being used in conjunction with dynamic stochastic general equilibrium models and of jointly specifying the short‐ and long‐run dynamics, thus representing the steady‐state of economic systems (by means of the co‐integration relations) and the short‐run dynamics around it.     

Structural FECM: Cointegration in large‐scale structural FAVAR models

Starting from the dynamic factor model for nonstationary data we derive the factor‐augmented error correction model (FECM) and its moving‐average representation. The latter is used for the identification of structural shocks and their propagation mechanisms. We show how to implement classical identification schemes based on long‐run restrictions in the case of large panels. The importance of the error correction mechanism for impulse response analysis is analyzed by means of both empirical examples and simulation experiments. Our results show that the bias in estimated impulse responses in a factor‐augmented vector autoregressive (FAVAR) model is positively related to the strength of the error correction mechanism and the cross‐section dimension of the panel. We observe empirically in a large panel of US data that these features have a substantial effect on the responses of several variables to the identified permanent real (productivity) and monetary policy shocks.     

Modelling Inflation Volatility

This paper discusses estimation of US inflation volatility using time‐varying parameter models, in particular whether it should be modelled as a stationary or random walk stochastic process. Specifying inflation volatility as an unbounded process, as implied by the random walk, conflicts with priors beliefs, yet a stationary process cannot capture the low‐frequency behaviour commonly observed in estimates of volatility. We therefore propose an alternative model with a change‐point process in the volatility that allows for switches between stationary models to capture changes in the level and dynamics over the past 40 years. To accommodate the stationarity restriction, we develop a new representation that is equivalent to our model but is computationally more efficient. All models produce effectively identical estimates of volatility, but the change‐point model provides more information on the level and persistence of volatility and the probabilities of changes. For example, we find a few well‐defined switches in the volatility process and, interestingly, these switches line up well with economic slowdowns or changes of the Federal Reserve Chair. Moreover, a decomposition of inflation shocks into permanent and transitory components shows that a spike in volatility in the late 2000s was entirely on the transitory side and characterized by a rise above its long‐run mean level during a period of higher persistence. Copyright © 2015 John Wiley & Sons, Ltd.     

Keynesian impulses versus Solow residuals: identifying sources of business cycle fluctuations

We employ a neoclassical business‐cycle model to study two sources of business‐cycle fluctuations: marginal efficiency of investment shocks, and total factor productivity shocks. The parameters of the model are estimated using a Bayesian procedure that accommodates prior uncertainty about their magnitudes; from these estimates, posterior distributions of the two shocks are obtained. The postwar US experience suggests that both shocks are important in understanding fluctuations, but that total factor productivity shocks are primarily responsible for beginning and ending recessions. Copyright © 2000 John Wiley & Sons, Ltd.     

IDENTIFICATION METHODS IN VECTOR‐ERROR CORRECTION MODELS: EQUIVALENCE RESULTS

In a structural vector‐error correction (VEC) model, it is possible to decompose the shocks into those with permanent and transitory effects on the levels of the variables. Pagan and Pesaran derive the restrictions which the permanent–transitory decomposition of the shocks imposes on the structural VEC model. This paper shows that these restrictions are equivalent to a set of restrictions that are applied in the methods of Gonzalo and Ng and King et al. (KPSW). Using this result, it is shown that the Pagan and Pesaran method can be used to recover the structural shocks with permanent effects identically to those from the Gonzalo and Ng and KPSW methods. In the former case, this is illustrated in the context of Lettau and Ludvigson's consumption model and in the latter case in KPSW's six variable model. There are also two other methods for which the Pagan and Pesaran approach can deliver identical permanent shocks which are also discussed.     

The response of asset prices to monetary policy shocks: Stronger than thought

Standard macroeconomic theory predicts rapid responses of asset prices to monetary policy shocks. Small‐scale vector autoregressions (VARs), however, often find sluggish and insignificant impact effects. Using the same high‐frequency instrument to identify monetary policy shocks, we show that a large‐scale dynamic factor model finds overall stronger and quicker asset price reactions compared to a benchmark VAR, both on euro area and US data. Our results suggest that incorporating a sufficiently large information set is crucial to estimate monetary policy effects.