Marco J. Lombardi

The Impact of Monetary Policy Shocks on Commodity Prices

Global monetary conditions are often cited as a driver of commodity prices. This paper investigates the empirical relationship between US monetary policy and commodity prices by means of a standard VAR system, commonly used in analysing the effects of monetary policy shocks. The results suggest that expansionary US monetary policy shocks drive up the broad commodity price index and all of its components. While these effects are significant, they do not, however, appear to be overwhelmingly large. This finding is confirmed under different identification strategies for the monetary policy shock.

Do Financial Investors Destabilize the Oil Price

We assess whether and to what extent ?nancial activity in the oil futures markets has contributed to destabilize oil prices in recent years. We de?ne a destabilizing ?nancial shock as a shift in oil prices that is not related to current and expected fun- damentals, and thereby distorts e¢ cient pricing in the oil market. Using a structural VAR model identi?ed with sign restrictions, we disentangle this non-fundamental ?- nancial shock from fundamental shocks to oil supply and demand to determine their relative importance. We ?nd that shocks to oil demand and supply remain the main drivers of oil price swings. Financial investors in the futures market can however destabilize oil spot prices, although only in the short run. Moreover, ?nancial ac- tivity appears to have exacerbated gyrations in the oil market over the past decade, particularly in 2007-2009.

Forecasting Economic Growth in the Euro Area During the Great Moderation and the Great Recession

We evaluate forecasts for the euro area in data-rich and ‘data-lean’ environments by comparing three different approaches: a simple PMI model based on Purchasing Managers’ Indices (PMIs), a dynamic factor model with euro area data, and a dynamic factor model with data from the euro plus data from national economies (pseudo-real time data). We estimate backcasts, nowcasts and forecasts for GDP, components of GDP, and GDP of all individual euro area members, and examine forecasts for periods of low and high economic volatility (more specifically, we consider 2002-2007, which falls into the ‘Great Moderation’, and the ‘Great Recession’ 2008-2009). We find that all models consistently beat naive AR benchmarks, and overall, the dynamic factor model tends to outperform the PMI model (at times by a wide margin). However, accuracy of the dynamic factor model can be uneven (forecasts for some countries have large errors), with the PMI model dominating clearly for some countries or over some horizons. This is particularly pronounced over the Great Recession, where the dynamic factor model dominates the PMI model for backcasts, but has considerable difficulties beating the PMI model for nowcasts. This suggests that survey-based measures can have considerable advantages in responding to changes during very volatile periods, whereas factor models tend to be more sluggish to adjust. JEL Classification: C50, C53, E37, E47

Oil price density forecasts: Exploring the linkages with stock markets

In the recent years several commentators hinted at an increase of the correlation between equity and commodity prices, and blamed investment in commodity-related products for this. First, this paper investigates such claims by looking at various measures of correlation. Next, we assess to what extent correlations between oil and equity prices can be exploited for asset allocation. We develop a time-varying Bayesian Dynamic Conditional Correlation model for volatilities and correlations and find that joint modelling of oil and equity prices produces more accurate point and density forecasts for oil which lead to substantial benefits in portfolio wealth.

Key Elements of Global Inflation

Against the background of large fluctuations in world commodity prices and global growth, combined with ongoing structural changes relating to globalization, this paper examines some of the key factors affecting global inflation. The paper empirically investigates various relative price and structural impacts on global inflation by: estimating a GVAR to examine how oil price shocks feed through to core and headline inflation; calculating the impact of increased imports from low-cost countries on manufacturing import prices; estimating Phillips curves in order to shed light on whether the inflationary process in the OECD countries has changed over time, particularly with respect to the roles of import prices, unit labour costs and the output gap. Overall, the paper finds that there seem to be various significant pressures on global trade prices and labour markets associated with structural factors possibly partly due to globalisation which, in addition to monetary policy, seem to be behind some of the changes in the inflation process over the period examined in this paper.

Monetary policy and the oil futures market

We assess the transmission of monetary policy shocks on oil prices using a VAR model. We identify monetary policy and financial activity shocks disentangled from demand and oil supply shocks using sign restrictions. We obtain the following main findings. (i) Monetary policy and financial activity shocks both have a significant effect on the oil price. (ii) Monetary policy has made large positive contributions to oil price growth in 2008. (iii) Monetary policy affects the oil price primarily through fundamental (supply and demand) channels rather than through financial activity.

The use of payment systems data as early indicators of economic activity

Payment system data are available with virtually no time lag and could therefore help in tracking the evolution of GDP in real time. Using data from the Spanish national system for retail payments, we compare the performance of GDP nowcasts against that of alternative indicators. The main result is that payment system data can make a significant contribution to nowcasting GDP and they can also improve the performance of simple models that are currently based only on purchasing managers indices (PMIs).