Showing results 1 to 10 of approximately 28.(refine search)
Global Asset Prices and Taper Tantrum Revisited
Global asset market developments during the summer of 2013 have been attributed to changes in the outlook for U.S. monetary policy, starting with former Chairman Bernanke’s May 22 comments concerning future curtailing of the Federal Reserve’s asset purchase programs. A previous post found that the signal of a possible change in U.S. monetary policy coincided with an increase in global risk aversion which put downward pressure on global asset prices. This post revisits this episode by measuring the impact of changes in Fed’s expected policy rate path and in the economic outlook on the ...
Model selection criteria for factor-augmented regressions
In a factor-augmented regression, the forecast of a variable depends on a few factors estimated from a large number of predictors. But how does one determine the appropriate number of factors relevant for such a regression? Existing work has focused on criteria that can consistently estimate the appropriate number of factors in a large-dimensional panel of explanatory variables. However, not all of these factors are necessarily relevant for modeling a specific dependent variable within a factor-augmented regression. This paper develops a number of theoretical conditions that selection ...
Lower Oil Prices and U.S. Economic Activity
After a period of stability, oil prices started to decline in mid-2015, and this downward trend continued into early 2016. As we noted in an earlier post, it is important to assess whether these price declines reflect demand shocks or supply shocks, since the two types of shocks have different implications for the U.S. economic outlook. In this post, we again use correlations of weekly oil price changes with a broad array of financial variables to quantify the drivers of oil price movements, finding that the decline since mid-2015 is due to a mix of weaker demand and increased supply. Given ...
A New Barometer of Global Supply Chain Pressures
Supply chain disruptions have become a major challenge for the global economy since the start of the COVID-19 pandemic. Factory shutdowns (particularly in Asia) and widespread lockdowns and mobility restrictions have resulted in disruptions across logistics networks, increases in shipping costs, and longer delivery times. Several measures have been used to gauge these disruptions, although those measures tend to focus on selected dimensions of global supply chains. In this post, we propose a new gauge, the Global Supply Chain Pressure Index (GSCPI), which integrates a number of commonly used ...
The GSCPI: A New Barometer of Global Supply Chain Pressures
We propose a novel indicator to capture pressures that arise at the global supply chain level, the Global Supply Chain Pressure Index (GSCPI). The GSCPI provides a new monitoring tool to gauge global supply chain conditions. We assess the index’s capacity to explain inflation outcomes, using the local projection method. Our analysis shows that recent inflationary pressures are closely related to the behavior of the GSCPI, especially at the level of producer price inflation in the United States and the euro area.
Revisiting useful approaches to data-rich macroeconomic forecasting
This paper analyzes the properties of a number of data-rich methods that are widely used in macroeconomic forecasting, in particular principal components (PC) and Bayesian regressions, as well as a lesser-known alternative, partial least squares (PLS) regression. In the latter method, linear, orthogonal combinations of a large number of predictor variables are constructed such that the covariance between a target variable and these common components is maximized. Existing studies have focused on modelling the target variable as a function of a finite set of unobserved common factors that ...
Alternative Indicators for Chinese Economic Activity Using Sparse PLS Regression
Official Chinese GDP growth rates have been remarkably smooth over the past decade, in contrast with alternative Chinese economic data. To better identify Chinese business cycles, we construct a sparse partial least squares (PLS) factor from a wide array of Chinese higher-frequency data, targeted toward variables that are highly correlated with important aspects of the Chinese economy. Our resulting alternative growth indicator clearly identifies Chinese business cycle fluctuations and it performs well both in out-of-sample testing for China as well as when applied to other economies. Using ...
Creating a History of U.S. Inflation Expectations
Central bankers closely monitor inflation expectations because they?re an important determinant of actual inflation. Treasury inflation-protected securities (TIPS) are commonly used to measure bond market inflation expectations. Unfortunately, they were only introduced in 1997, so historical data are limited. We propose a solution to this problem by using the relationship between TIPS yields and other data with a longer history to construct synthetic TIPS rates going back to 1971.
Global Supply Chain Pressure Index: May 2022 Update
Supply chain disruptions continue to be a major challenge as the world economy recovers from the COVID-19 pandemic. Furthermore, recent developments related to geopolitics and the pandemic (particularly in China) could put further strains on global supply chains. In a January post, we first presented the Global Supply Chain Pressure Index (GSCPI), a parsimonious global measure designed to capture supply chain disruptions using a range of indicators. We revisited our index in March, and today we are launching the GSCPI as a standalone product, with new readings to be published each month. In ...
Commodity prices, commodity currencies, and global economic developments
In this paper, we seek to produce forecasts of commodity price movements that can systematically improve on naive statistical benchmarks. We revisit how well changes in commodity currencies perform as potential efficient predictors of commodity prices, a view emphasized in the recent literature. In addition, we consider different types of factor-augmented models that use information from a large data set containing a variety of indicators of supply and demand conditions across major developed and developing countries. These factor-augmented models use either standard principal components or ...