Michele Lenza

EXPLAINING THE GREAT MODERATION: IT IS NOT THE SHOCKS

This paper shows that the explanation of the decline in the volatility of GDP growth since the mid-eighties is not the decline in the volatility of exogenous shocks but rather a change in their propagation mechanism.

The ECB and the Interbank Market

This paper analyses the impact on the macroeconomy of the ECB’s non-standard monetary policy implemented in the aftermath of the collapse of Lehman Brothers in the Fall of 2008. We study in particular the effect of the expansion of the intermediation of transactions across central bank balance sheets as dysfunctional financial markets seize up, which we regard as a key channel of transmission for non-standard monetary policy measures. Our approach is similar to Lenza et al., 2009 but we introduce the important innovation of distinguishing between private intermediation of interbank transactions in the money market and central bank intermediation of bank-to-bank transactions across the Eurosystem balance sheet. We do this by exploiting data drawn from the aggregate Monetary and Financial Institutions (MFI) balance sheet which allows us to construct a new measure of the ‘policy shock’ represented by the ECB’s increasing role as a financial intermediary. We find that bank loans to households and, in particular, to non-financial corporations are higher than would have been the case without the ECB’s intervention. In turn, the ECB’s support has a significant impact on economic activity: two and a half years after the failure of Lehman Brothers, the level of industrial production is estimated to be 2% higher, and the unemployment rate 0.6 percentage points lower, than would have been the case in the absence of the ECB’s non-standard monetary policy measures.

Non-Standard Monetary Policy Measures and Monetary Developments

Standard accounts of the Great Depression attribute an important causal role to monetary policy errors in accounting for the catastrophic collapse in economic activity observed in the early 1930s. While views vary on the relative importance of money versus credit contraction in the propagation of this policy error to the wider economy and ultimately price developments, a broad consensus exists in the economics profession around the view that the collapse in financial intermediation was a crucial intermediary step. What lessons have monetary policy makers taken from this episode? And how have they informed the conduct of monetary policy by leading central banks in recent times? This paper sets out to address these questions, in the context of the financial crisis of 2008-09 and with application to the euro area.

A Factor Model for Euro-area Short-term Inflation Analysis

Summary This paper develops a factor model for forecasting inflation in the euro area. The model can handle variables with different timeliness, sample size and frequency. We show that the forecasts based on the factor model outperform naïve random walk forecasts, a hard to beat benchmark for euro area inflation forecasts in recent years, at horizons of and beyond nine months ahead. They are also comparable, in terms of accuracy, to the judgemental forecasts prepared in the context of the Eurosystem macroeconomic projection exercises. The factor model is therefore a very suitable tool to extract the signal on current and future euro area inflation from new data releases.

Priors for the Long Run

ABSTRACT We propose a class of prior distributions that discipline the long-run behavior of vector autoregressions (VARs). These priors can be naturally elicited using economic theory, which provides guidance on the joint dynamics of macroeconomic time series in the long run. Our priors for the long run are conjugate, and can thus be easily implemented using dummy observations and combined with other popular priors. In VARs with standard macroeconomic variables, a prior based on the long-run predictions of a wide class of theoretical models yields substantial improvements in the forecasting performance. Supplementary materials for this article, including a standardized description of the materials available for reproducing the work, are available as an online supplement.

Nowcasting business cycles: A Bayesian approach to dynamic heterogeneous factor models

We develop a framework for measuring and monitoring business cycles in real time. Following a long tradition in macroeconometrics, inference is based on a variety of indicators of economic activity, treated as imperfect measures of an underlying index of business cycle conditions. We extend existing approaches by permitting for heterogenous lead–lag patterns of the various indicators along the business cycles. The framework is well suited for high-frequency monitoring of current economic conditions in real time – nowcasting – since inference can be conducted in the presence of mixed frequency data and irregular patterns of data availability. Our assessment of the underlying index of business cycle conditions is accurate and more timely than popular alternatives, including the Chicago Fed National Activity Index (CFNAI). A formal real-time forecasting evaluation shows that the framework produces well-calibrated probability nowcasts that resemble the consensus assessment of the Survey of Professional Forecasters.

Nowcasting Business Cycles: a Bayesian Approach to Dynamic Heterogeneous Factor Models

We develop a framework for measuring and monitoring business cycles in real time. Following a long tradition in macroeconometrics, inference is based on a variety of indicators of economic activity, treated as imperfect measures of an underlying index of business cycle conditions. We extend existing approaches by permitting for heterogenous lead-lag patterns of the various indicators along the business cycles. The framework is well suited for high-frequency monitoring of current economic conditions in real time - nowcasting - since inference can be conducted in presence of mixed frequency data and irregular patterns of data availability. Our assessment of the underlying index of business cycle conditions is accurate and more timely than popular alternatives, including the Chicago Fed National Activity Index (CFNAI). A formal real-time forecasting evaluation shows that the framework produces well-calibrated probability nowcasts that resemble the consensus assessment of t he Survey of Professional Forecasters.