European Central Bank

Using a Bayesian likelihood approach, we estimate a dynamic stochastic general equilibrium model for the US economy using seven macroeconomic time series. The model incorporates many types of real and nominal frictions and seven types of structural shocks. We show that this model is able to compete with Bayesian Vector Autoregression models in out-of-sample prediction. We investigate the relative empirical importance of the various frictions. Finally, using the estimated model, we address a number of key issues in business cycle analysis: What are the sources of business cycle fluctuations? Can the model explain the cross correlation between output and inflation? What are the effects of productivity on hours worked? What are the sources of the “Great Moderation”? (JEL D58, E23, E31, E32)

Journal Article An Estimated Dynamic Stochastic General Equilibrium Model of the Euro Area Get access Frank Smets, Frank Smets 1European Central Bank and CEPR Search for other works by this author on: Oxford Academic Google Scholar Raf Wouters Raf Wouters 2National Bank of Belgium Search for other works by this author on: Oxford Academic Google Scholar Journal of the European Economic Association, Volume 1, Issue 5, 1 September 2003, Pages 1123–1175, https://doi.org/10.1162/154247603770383415 Published: 01 September 2003

Value at risk (VaR) is the standard measure of market risk used by financial institutions. Interpreting the VaR as the quantile of future portfolio values conditional on current information, the conditional autoregressive value at risk (CAViaR) model specifies the evolution of the quantile over time using an autoregressive process and estimates the parameters with regression quantiles. Utilizing the criterion that each period the probability of exceeding the VaR must be independent of all the past information, we introduce a new test of model adequacy, the dynamic quantile test. Applications to real data provide empirical support to this methodology.

Output Fluctuations in the United States: What Has Changed since the Early 1980's? by Margaret M. McConnell and Gabriel Perez-Quiros. Published in volume 90, issue 5, pages 1464-1476 of American Economic Review, December 2000

This paper proposes a new generalized autoregressive conditionally heteroskedastic (GARCH) process, the asymmetric generalized dynamic conditional correlation (AG-DCC) model. The AG-DCC process extends previous specifications along two dimensions: it allows for series-specific news impact and smoothing parameters and permits conditional asymmetries in correlation dynamics. The AG-DCC specification is well suited to examine correlation dynamics among different asset classes and investigate the presence of asymmetric responses in conditional variances and correlations to negative returns. We employ the AG-DCC model to analyze the behavior of international equities and government bonds. While equity returns show strong evidence of asymmetries in conditional volatility, little is found for bond returns. However, both equities and bonds exhibit asymmetries in conditional correlations, with equities responding stronger than bonds to joint bad news. The article also finds that, during periods of financial turmoil, equity market volatilities show important linkages, and conditional equity correlations among regional groups increase dramatically. Furthermore, in January 1999 with the introduction of the euro, we document significant evidence of a structural break in correlation although not in volatility. The introduction of a fixed exchange rate regime leads to near-perfect correlation among bond returns within the European Monetary Union (EMU) countries, which is not surprising when considering the harmonization in monetary policy. However, the increase in return correlation is not restricted to bond returns in EMU countries: equity return correlation both within and outside the EMU also increases.

We provide evidence on the transmission of monetary policy shocks in a setting with both economic and financial variables. We first show that shocks identified using high frequency surprises around policy announcements as external instruments produce responses in output and inflation that are typical in monetary VAR analysis. We also find, however, that the resulting “modest” movements in short rates lead to “large” movements in credit costs, which are due mainly to the reaction of both term premia and credit spreads. Finally, we show that forward guidance is important to the overall strength of policy transmission. (JEL E31, E32, E43, E44, E52, G01)

Over the last two decades, communication has become an increasingly important aspect of monetary policy. These real-world developments have spawned a huge new scholarly literature on central bank communication—mostly empirical, and almost all of it written in this decade. We survey this ever-growing literature. The evidence suggests that communication can be an important and powerful part of the central bank's toolkit since it has the ability to move financial markets, to enhance the predictability of monetary policy decisions, and potentially to help achieve central banks' macroeconomic objectives. However, the large variation in communication strategies across central banks suggests that a consensus has yet to emerge on what constitutes an optimal communication strategy.

We augment a standard monetary dynamic general equilibrium model to include a Bernanke-Gertler-Gilchrist financial accelerator mechanism. We fit the model to US data, allowing the volatility of cross-sectional idiosyncratic uncertainty to fluctuate over time. We refer to this measure of volatility as risk. We find that fluctuations in risk are the most important shock driving the business cycle. (JEL D81, D82, E32, E44, L26)

Abstract This paper shows that vector auto regression (VAR) with Bayesian shrinkage is an appropriate tool for large dynamic models. We build on the results of De Mol and co‐workers (2008) and show that, when the degree of shrinkage is set in relation to the cross‐sectional dimension, the forecasting performance of small monetary VARs can be improved by adding additional macroeconomic variables and sectoral information. In addition, we show that large VARs with shrinkage produce credible impulse responses and are suitable for structural analysis. Copyright © 2009 John Wiley & Sons, Ltd.

Using bank-level data, we apply the Panzar and Rosse (1987) methodology to estimate the extent to which changes in input prices are reflected in revenues earned by specific banks in 50 countries' banking systems. We then relate this competitiveness measure to indicators of countries' banking system structures and regulatory regimes. We find systems with greater foreign bank entry and fewer entry and activity restrictions to be more competitive. We find no evidence that our competitiveness measure negatively relates to banking system concentration. Our findings confirm that contestability determines effective competition especially by allowing (foreign) bank entry and reducing activity restrictions on banks.

This paper provides a minimalist derivation of the gravity equation and uses it to identify three common errors in the literature, what we call the gold, silver and bronze medal errors. The paper provides estimates of the size of the biases taking the currency union trade effect as an example. We generalize Anderson-Van Wincoop's multilateral trade resistance factor (which only works with cross section data) to allow for panel data and then show that it can be dealt with using time-varying country dummies with omitted determinants of bilateral trade being dealt with by time-invariant pair dummies.

This paper presents a model in which price setting firms decide what to pay attention to, subject to a constraint on information flow. When idiosyncratic conditions are more variable or more important than aggregate conditions, firms pay more attention to idiosyncratic conditions than to aggregate conditions. When we calibrate the model to match the large average absolute size of price changes observed in micro data, prices react fast and by large amounts to idiosyncratic shocks, but only slowly and by small amounts to nominal shocks. Nominal shocks have strong and persistent real effects. (JEL D21, D83, E31, E52)

Abstract This paper presents a quarterly global model combining individual country vector error‐correcting models in which the domestic variables are related to the country‐specific foreign variables. The global VAR (GVAR) model is estimated for 26 countries, the euro area being treated as a single economy, over the period 1979–2003. It advances research in this area in a number of directions. In particular, it provides a theoretical framework where the GVAR is derived as an approximation to a global unobserved common factor model. Using average pair‐wise cross‐section error correlations, the GVAR approach is shown to be quite effective in dealing with the common factor interdependencies and international co‐movements of business cycles. It develops a sieve bootstrap procedure for simulation of the GVAR as a whole, which is then used in testing the structural stability of the parameters, and for establishing bootstrap confidence bounds for the impulse responses. Finally, in addition to generalized impulse responses, the current paper considers the use of the GVAR for ‘structural’ impulse response analysis with focus on external shocks for the euro area economy, particularly in response to shocks to the US. Copyright © 2007 John Wiley & Sons, Ltd.

This study assesses empirically the effects of oil price shocks on the real economic activity of the main industrialized countries. Multivariate VAR analysis is carried out using both linear and non-linear models. The latter category includes three approaches employed in the literature, namely, the asymmetric, scaled and net specifications. Evidence of a non-linear impact of oil prices on real GDP is found. In particular, oil price increases are found to have an impact on GDP growth of a larger magnitude than that of oil price declines, with the latter being statistically insignificant in most cases. Among oil importing countries, oil price increases are found to have a negative impact on economic activity in all cases but Japan. Moreover, the effect of oil shocks on GDP growth differs between the two oil exporting countries in the sample, with the UK being negatively affected by an oil price increase and Norway benefiting from it.

Micro-and macro-level evidence indicates that fluctuations in idiosyncratic uncertainty have a large effect on investment; the impact of uncertainty on investment occurs primarily through changes in credit spreads; and innovations in credit spreads have a strong effect on investment, irrespective of the level of uncertainty. These findings raise a question regarding the economic significance of the traditional "wait-and-see" effect of uncertainty shocks and point to financial distortions as the main mechanism through which fluctuations in uncertainty affect macroeconomic outcomes. The relative importance of these two mechanisms is analyzed within a quantitative general equilibrium model, featuring heterogeneous firms that face time-varying idiosyncratic uncertainty, irreversibility, nonconvex capital adjustment costs, and financial frictions. The model successfully replicates the stylized facts concerning the macroeconomic implications of uncertainty and financial shocks. By influencing the effective supply of credit, both types of shocks exert a powerful effect on investment and generate countercyclical credit spreads and procyclical leverage, dynamics consistent with the data and counter to those implied by the technology-driven real business cycle models.

This book discusses the changing role of government finance in the twentieth century. It documents the enormous increase in government spending throughout the 1900s across all industrialized countries. However, the authors find that the growth of the welfare state over the past thirty-five years has not brought about much additional social and economic welfare. This suggests that public spending in industrialized countries could be much smaller than today without sacrificing important policy objectives. For this to happen, governments need to refocus their role on setting the 'rules of the game', and the study provides a blueprint for institutional and expenditure policy reform. After a detailed account of reform experiences in several countries and the public debate regarding government reform, the study closes with an outlook on the future role of the state, which is crucial in that globalization may require and people want much 'leaner' but not 'meaner' states.

Vector autoregressions (VARs) are flexible time series models that can capture complex dynamic interrelationships among macroeconomic variables. However, their dense parameterization leads to unstable inference and inaccurate out-of-sample forecasts, particularly for models with many variables. A solution to this problem is to use informative priors in order to shrink the richly parameterized unrestricted model toward a parsimonious naıve benchmark, and thus reduce estimation uncertainty. This paper studies the optimal choice of the informativeness of these priors, which we treat as additional parameters, in the spirit of hierarchical modeling. This approach, theoretically grounded and easy to implement, greatly reduces the number and importance of subjective choices in the setting of the prior. Moreover, it performs very well in terms of both out-of-sample forecasting—as well as factor models—and accuracy in the estimation of impulse response functions.

This paper introduces the concepts of time‐specific weak and strong cross‐section dependence, and investigates how these notions are related to the concepts of weak, strong and semi‐strong common factors, frequently used for modelling residual cross‐section correlations in panel data models. It then focuses on the problems of estimating slope coefficients in large panels, where cross‐section units are subject to possibly a large number of unobserved common factors. It is established that the common correlated effects (CCE) estimator introduced by Pesaran remains asymptotically normal under certain conditions on factor loadings of an infinite factor error structure, including cases where methods relying on principal components fail. The paper concludes with a set of Monte Carlo experiments where the small sample properties of estimators based on principal components and CCE estimators are investigated and compared under various assumptions on the nature of the unobserved common effects.

ABSTRACT We analyze the transmission of the 2007 to 2009 financial crisis to 415 country‐industry equity portfolios. We use a factor model to predict crisis returns, defining unexplained increases in factor loadings and residual correlations as indicative of contagion. While we find evidence of contagion from the United States and the global financial sector, the effects are small. By contrast, there has been substantial contagion from domestic markets to individual domestic portfolios, with its severity inversely related to the quality of countries’ economic fundamentals. This confirms the “wake‐up call” hypothesis, with markets focusing more on country‐specific characteristics during the crisis.

We study the effects of electoral institutions on the size and composition of public expenditure in OECD and Latin American countries. We emphasize the distinction between purchases of goods and services, which are easier to target geographically, and transfers, which are easier to target across social groups. We present a theoretical model in which voters anticipating government policy-making under different electoral systems have an incentive to elect representatives more prone to transfer (public good) spending in proportional (majoritarian) systems. The model also predicts higher total primary spending in proportional (majoritarian) systems when the share of transfer spending is high (low). After defining rigorous measures of proportionality to be used in the empirical investigation, we find considerable support for our predictions.