Factor-augmented Vector Autoregression Research Articles

North American trade and US monetary policy

This paper investigates how an increase in the United States Federal Fund rate affects the United States economy and how the effects are transmitted to the Canadian economy using the factor-augmented VAR (FAVAR) approach of Stock and Watson (2005) and Bernanke et al. (2005). A distinguishing feature of our model is the disaggregation of the traded goods sector where imports and exports are disaggregated into 12 and 13 industries, respectively. Extra information is provided on the domestic and international transmission mechanisms between the two countries. The factor-augmented VAR method allows impulse response functions to be generated for all the variables in the data set and so is able to provide a comprehensive description of the domestic and international transmission mechanisms between the United States and Canada.

The changing international transmission of U.S. monetary policy shocks: Is there evidence of contagion effect on OECD countries

We study the changing international transmission of U.S. monetary policy shocks to 14 OECD countries over the period 1981Q1–2010Q4. The U.S. monetary policy shock is defined as unexpected change in Effective Federal Funds Rate (FFR). We use a time varying parameter factor augmented VAR approach (TVP-FAVAR) to study the EFFR shocks together with a large data set of 265, major financial, macroeconomic and trade variables for U.S., Canada, France, Germany, Italy, UK, Japan, Australia, Spain, Norway, Sweden, Switzerland, Finland and New Zealand. Our main findings are as follows. First, negative U.S. monetary policy shocks have considerable negative impact on GDP growth in the U.S., Canada, Japan and Sweden while most of the other member countries benefits. Second, the transmission to GDP growth has increased in OECD countries since the early 1980s. We also detect a more depressed GDP over medium term in the U.S., Canada, Japan, Australia, Norway and Sweden over the recent global financial crisis. Third, the size of U.S. monetary policy shocks during financial turmoil periods were unusual than normal periods and varies overtime. The financial crisis (2008–2009) is evidenced by decline in residential investment in the U.S. and propagation of this shock to Canada, Germany, Japan, Switzerland and New Zealand over the recent period. U.S. monetary policy shocks reduce share prices in most of the OECD countries; this impact is more pronounced over the turmoil period. Asset prices, interest rates and trade channel seem to play major role in propagation of monetary policy shocks.

Changes in the effects of monetary policy on disaggregate price dynamics

Based on a time-varying factor-augmented vector autoregression, we demonstrate that the propagation mechanism of monetary policy disturbances differs across disaggregate components of personal consumption expenditures. While many disaggregate prices rise temporarily in response to a monetary tightening in the early part of the sample, there is no evidence of a price puzzle at the aggregate level. The share of disaggregate prices that exhibit the price puzzle diminishes from the early 1980s onwards. There also is evidence of a substantial decline in the dispersion of disaggregate price responses over time. This gradual decrease in cross-sectional heterogeneity of disaggregate price responses is associated with a dampening effect on aggregate real economic activity and a stronger effect on the aggregate price level. We illustrate by means of a multi-sector sticky-price model augmented by a cost channel how key structural parameters would have had to change to match this evolution of sectoral price dynamics.

Primary commodity prices: Co-movements, common factors and fundamentals

The behavior of commodities is critical for developing and developed countries alike. This paper contributes to the empirical evidence on the co-movement and determinants of commodity prices. Using nonstationary panel methods, we document a statistically significant degree of co-movement due to a common factor. Within a Factor Augmented VAR approach, real interest rate and uncertainty, as postulated by a simple asset pricing model, are both found to be negatively related to this common factor. This evidence is robust to the inclusion of demand and supply shocks, which both positively impact on the co-movement of commodity prices.

Employment responses to aggregate and sectoral technology shocks

This paper investigates the responses of sectoral employment in US manufacturing to a technology shock by its type: aggregate or sectoral. In order to distinguish between aggregate and sectoral shocks, we construct independent VAR models for identifying each shock separately: a factor-augmented vector autoregression (FAVAR) for aggregate shocks and a sectoral SVAR for sectoral shocks. Our aggregate model in particular extends the conventional small-scale VAR to the FAVAR framework of Bernanke et al. (2005) so that it can address the potential bias from omitted variables. The main findings are as follows: most industries exhibit negative employment responses to an aggregate technology shock while exhibiting positive responses to a sectoral technology shock. By comparing our FAVAR framework with Chang and Hong’s (2006) small-scale VAR, we show that applying the FAVAR results in significant differences in the estimated responses to an aggregate technology shock. Real rigidities (such as slow diffusion of new technology or frictional labor reallocation), rather than nominal rigidities (such as sticky prices), are crucial in accounting for the cross-industry difference in employment responses. In particular, the slow diffusion of new technology is closely related to the sluggish response of sectoral employment.

Speculation in the Oil Market

The run-up in oil prices since 2004 coincided with growing investment in commodity markets and increased price comovement among different commodities. We assess whether speculation in the oil market played a role in driving this salient empirical pattern. We identify oil shocks from a large dataset using a factor-augmented vector autoregressive (FAVAR) model. This method is motivated by the fact that a small scale VAR is not infomationally sufficient to identify the shocks. The main results are as follows: (i) While global demand shocks account for the largest share of oil price fluctuations, speculative shocks are the second most important driver. (ii) The comovement between oil prices and the prices of other commodities is mainly explained by global demand shocks. (iii) The increase in oil prices over the last decade is mainly driven by the strength of global demand. However, speculation played a significant role in the oil price increase between 2004 and 2008 and its subsequent collapse. Our results support the view that the recent oil price increase is mainly driven by the strength of global demand but that the financialization process of commodity markets also played a role.

Monetary Policy Analysis Based on Lasso-Assisted Vector Autoregression (Lavar)

Measuring the quantitative effects of monetary policy on the economy has been playing a central role in promoting economic growth and stability. However, in the presence of numerous macroeconomic variables, traditional vector autoregression (VAR) could only accommodate a few data series, and thus may ignore the information set which is actually observed by central banks and financial market participants. In this paper, we propose a novel VAR model with the aid of new developments in high-dimensional statistical inference. Our approach could handle hundreds of observed data series simultaneously, and increase the prediction accuracy as well as the robustness of monetary policy analysis in a data-rich environment. It has been shown that our model outperforms factor-augmented VAR in terms of in-sample-fit and out-of-sample forecasts. Moreover, impulse responses are observed for all macroeconomic variables, where “price puzzle”, a commonly observed empirical anomaly, is resolved.

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

AbstractThis 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.

What Drives Oil Prices? Emerging Versus Developed Economies

We analyze the importance of demand from emerging and developed economies as drivers of the real price of oil over the last two decades. Using a factor-augmented vector autoregressive (FAVAR) model that allows us to distinguish between different groups of countries, we find that demand from emerging economies (most notably from Asian countries) is more than twice as important as demand from developed countries in accounting for the fluctuations in the real price of oil and in oil production. Furthermore, we find that different geographical regions respond differently to oil supply shocks and oilspecific demand shocks that drive up oil prices, with Europe and North America being more negatively affected than emerging economies in Asia and South America. We demonstrate that this heterogeneity in responses is not only attributable to differences in energy intensity in production across regions but also to degree of openness and the investment share in GDP.

Is there a Swiss price puzzle?

Summary This paper estimates the response of consumer prices to a monetary policy shock in Switzerland. We find that there is no evidence of a price puzzle at the aggregate level. This is because our factor-augmented vector autoregression (FAVAR) avoids misspecification by including more information than a traditional VAR. However, the response is still delayed by at least four quarters, partly because there is a price puzzle in some sectors. In particular, rents tend to rise after a monetary policy tightening because there are legal provisions in Switzerland which link them to interest rates. But durable goods prices also rise, which is consistent with the existence of a cost channel of monetary policy.

The Spillover Effects of a Downturn in China’s Real Estate Investment

Real estate investment accounts for a quarter of total fixed asset investment (FAI) in China. The real estate sector’s extensive industrial and financial linkages make it a special type of economic activity, especially where the credit creation process relies primarily on collateral, like in China. As a result, the impact on economic activity of a collapse in real estate investment in China—though a low-probability event—would be sizable, with large spillovers to a number of China’s trading partners. Using a two-region factor-augmented vector autoregression model that allows for interaction between China and the rest of the G20 economies, we find that a 1-percent decline in China’s real estate investment would shave about 0.1 percent off China’s real GDP within the first year, with negative spillover impacts to China’s G20 trading partners that would cause global output to decline by roughly 0.05 percent from baseline. Japan, Korea, and Germany would be among the hardest hit. In that event, commodity prices, especially metal prices, could fall by as much as 0.8–2.2 percent below baseline one year after the shock.

The Spillover Effects of a Downturn in China's Real Estate Investment

Real estate investment accounts for a quarter of total fixed asset investment (FAI) in China. The real estate sector's extensive industrial and financial linkages make it a special type of economic activity, especially where the credit creation process relies primarily on collateral, like in China. As a result, the impact on economic activity of a collapse in real estate investment in China ”though a low-probability event” would be sizable, with large spillovers to a number of China's trading partners. Using a two-region factor-augmented vector autoregression model that allows for interaction between China and the rest of the G20 economies, we find that a 1-percent decline in China's real estate investment would shave about 0.1 percent off China's real GDP within the first year, with negative spillover impacts to China's G20 trading partners that would cause global output to decline by roughly 0.05 percent from baseline. Japan, Korea, and Germany would be among the hardest hit. In that event, commodity prices, especially metal prices, could fall by as much as 0.8“2.2 percent below baseline one year after the shock.

Real Wages and Monetary Policy Transmission in the Euro Area

We use the Factor-Augmented Vector Autoregression (FAVAR) approach of Bernanke, Boivin and Eliasz (2005) to estimate the effects of monetary policy shocks on wages and employment in the euro area. The use of a large data set comprising country, sectoral and euro area-wide data allows us to better identify common monetary policy shocks in the euro area and their effects on labor market outcomes. At the same time the FAVAR approach gives us estimates of how relative wages and employment in the various countries and sectors respond to these common shocks. The ultimate objective of our work is to relate the estimated cross-country differences in wage and employment responses to differences in labor market institutions and sectoral composition.

Explaining Yield Curve Dynamics

Yield curve dynamics are usually analyzed in terms of the unobservable components—level, slope, and curvature. The factor-augmented vector autoregression (FAVAR) framework applied in this article has become increasingly popular for forecasting interest rates. To link these two strands of research, the authors operate in the space of latent yield and latent macroeconomic factors to analyze the relationship between the term structure of interest rates and the macroeconomic aggregates. They predict the yield curve dynamics by directly forecasting the unobservable yield curve factors. They use the FAVAR methodology to encompass a data-rich environment and to identify dynamic responses of the yield curve to the macroeconomic variables. The empirical results suggest that parsimonious FAVAR models with a few latent macroeconomic factors and a reduced lag order show superior short-horizon forecast performance over simple VAR systems and univariate autoregressions. <b>TOPICS:</b>Fixed-income portfolio management, statistical methods, factor-based models

Global commodity cycles and linkages: a FAVAR approach

In this article, we examine linkages across non-energy commodity price developments by means of a factor-augmented VAR model (FAVAR). From a set of non-energy commodity price series, we extract two factors, which we identify as common trends in metals and food prices. These factors are included in a FAVAR model together with selected macroeconomic variables, which have been associated with developments in commodity prices. Impulse response functions confirm that exchange rates and economic activity affect individual non-energy commodity prices, but we fail to find strong spillovers from oil to non-oil commodity prices or an impact of the interest rate. In addition, we find that individual commodity prices are affected by common trends captured by the food and metals factors.

International Transmission of Shocks: A Time-Varying Factor-Augmented VAR Approach to the Open Economy

A growing literature has documented changes to the dynamics of key macroeconomic variables in industrialized countries and highlighted the possibility that these variables may react differently to structural shocks over time. However, existing empirical work on the international transmission of shocks largely abstracts from the possibility of changes to the international transmission mechanism across time. In addition, the literature has largely employed small-scale models with limited number of variables. This paper introduces an empirical model which allows the estimation of time-varying response of a large set of domestic variables to foreign money supply, demand and supply shocks. The key results show that a foreign monetary policy tightening resembles the classic beggar-thy-neighbour scenario for the United Kingdom in the period 1975-90. In more recent periods, the response is negative but largely insignificant.

Sectoral Price Facts in a Sticky-Price Model

We develop a multi-sector sticky-price DSGE (dynamic stochastic general equilibrium) model that can endogenously deliver differential responses of prices to aggregate and sectoral shocks. Input-output production linkages induce across-sector pricing complementarities that contribute to a slow response of prices to aggregate shocks. In turn, input-market segmentation at the sectoral level induces within-sector pricing substitutability, which helps the model deliver a fast response of prices to sector-specific shocks. Estimating the factor-augmented vector autoregression specification of Boivin, Giannoni, and Mihov (2009) on data generated by a parameterized version of our model, we find results that resemble what they obtain with disaggregated data for the U.S. economy. We then employ Bayesian methods to estimate the model using aggregate and sectoral data, and find that it accounts extremely well for a wide range of sectoral price facts.

Large Datasets, Factor-augmented and Factor-only Vector Autoregressive Models, and the Economic Consequences of Mrs Thatcher

We investigate methods of capturing the salient characteristics of very large datasets in an investigation of UK and US macroeconomic policy, using factor-augmented VAR (FAVAR) models. We also estimate structural factor-only VAR (FOVAR) models and examine the impact of aggregate demand and aggregate supply. In a further empirical application, we find that while there is some evidence of increased macroeconomic flexibility in the USA as well as the UK since the late 1980s, the speed of macroeconomic adjustment is more marked in the UK economy post-1987, possibly reflecting the UK labour market reforms of the Thatcher government in the 1980s.

Forward Rates, Monetary Policy and the Economic Cycle

The short end of the yield curve incorporates essential pieces of information to forecast the next decisions of Central Banks, but in a biased manner. I therefore propose a new method to forecast the Fed and the ECB decision rate by correcting the swap rates for their cyclical economic premium, using an affine term structure model. The corrected yields offer a higher out-of-sample forecasting power than the yields themselves. They also deliver forecast that are either comparable or better than those obtained with a Factor Augmented VAR, underlying the fact that yields are likely to contain at least as much information regarding monetary policy as in a pure economic dataset.

ASSESSING MONETARY POLICY IN SOUTH AFRICA IN A DATA‐RICH ENVIRONMENT

AbstractThis paper examines the efficacy of monetary policy in the South African economy using a data‐rich framework. We use the Factor‐Augmented Vector Autoregressive (FAVAR) methodology, which contains 110 monthly variables for the period 1985:02‐2007:11. The results, based on impulse‐response functions, provide no evidence of the price puzzle observed in traditional Structural Vector Autoregressive analysis and confirm that monetary policy in South Africa is effective in stabilising prices. Unlike the traditional vector autoregressive approach, the FAVAR methodology allows further analysis of a large number of variables. Variables from real and financial variables react negatively to a contractionary monetary policy shock. Finally, we find evidence of the importance of a confidence channel transmission following a monetary policy shock.