Factor-augmented Vector Autoregression Research Articles

Role of Global Uncertainty: Evidence from COVID-19 Pandemic

This paper investigates the role of global uncertainty, measured as VIX or common stock market volatility across a wide range of countries, on global financial asset prices after the outbreak of COVID-19 pandemic. I estimate a factor-augmented vector autoregression model that consists of multiple financial variables, based on daily frequency, where global uncertainty shocks are identified through recursive restriction. I report three main results. First, the global uncertainty shock has played a key role in the developments in financial asset prices and oil prices, explaining over a third of total variations in the variables. Second, in line with the findings in earlier studies, the uncertainty shocks are in nature global demand shocks; the shocks were associated with significant decline in global stock prices, implied inflation, interest rates, and oil prices. Third, the results further suggest that the negative impact uncertainty shocks induced by the pandemic seem to be two to four times as sizeable as whit is assessed based on data before the outbreak of COVID-19. Finally, the results are robust to alternative identification strategies, alternative data transformation, and alternative measures of financial asset prices.

Monetary policy shock and industrial production: industry-level evidence from the US

PurposeThis paper investigates the impact of a monetary policy shock on the production of a sample of 312 industries in manufacturing, mining and utilities in the United States using a factor-augmented vector autoregression (FAVAR) model.Design/methodology/approachThe authors use a FAVAR model that builds on Bernanke et al. (2005) and Boivin et al. (2009). The main assumption in this model is that the dynamics of a large set of macro variables are captured by some observed and unobserved common factors. The unobserved factors are extracted from a large set of macroeconomic data. The key advantage of using this model is that it allows extracting the impulse responses of a wide range of macroeconomic variables to structural shocks in the federal funds rate.FindingsThe results indicate that industries exhibit differential responses to an unanticipated monetary policy tightening. In general, manufacturing industries appear to be more sensitive compared to mining, and utility industries and durable manufacturing industries are found to be more sensitive than those within nondurable and other manufacturing industries to a monetary policy shock. While all industries respond to the policy shock, most of the responses are reversed between 12 and 22 months.Research limitations/implicationsThe implication of our results is that monetary policy can be used to impact most US industries for four years and beyond. The existence of disparate responses across industries underscores the difficulty of implementing a monetary policy that will generate the same impact across industries. As the effects of the policy are distinct, policymakers may want to attend to the unique impacts and implement industry-specific policy.Practical implicationsThe study is important in the context of the current challenges in the US economy caused by the spread of coronavirus. For example, to tackle the current pandemic, the researchers are trying to come up with cures for COVID-19. A considerable response of the chemical industry that provides materials to pharmaceutical and medicine manufacturing to the monetary policy shock implies that an expansionary monetary policy may facilitate an invention and adequate supply of the cure later on. The same policy may not effectively stimulate production in apparel or leather product industries that are being hard hit by the pandemic.Originality/valueThe study contributes to the literature in broadly two aspects. First, to the best of our knowledge, this is the first paper that investigates the impact of a monetary policy shock on a sample of 312 industries in manufacturing, mining and utilities in the US. Second, to identify structural shocks and investigate the effects of monetary policy shocks on economic activity, the authors diverge from the literature's traditional approach, i.e. the vector autoregression (VAR) method and use a FAVAR method. The FAVAR provides a comprehensive description of the impact of a monetary policy innovation on different industries.

The Impact of Banking Policies to the Macroprudential Policy

The interaction between banks and macroeconomics is of crucial importance to financial stability. This study aims to answer the question of how macroeconomic shocks are transmitted to banking variables or vice versa. The study investigated the impact of the banking policies, the principal component of analysis (PCA) of banking quality indicators (CAMEL), and BI's rate to the aggregate of GDP and GDP priority sectors. The methodology used is the Factor Augmented Vector Autoregressive (FAVAR) model to observe the endogeneity of the observed variables. The results show that there is substantial heterogeneity in the transmission of macroeconomic shocks, caused by CAR, CAMEL and BI rate. In the short run, we find that the impulse response functions of aggregate GDP and GDP per sector of priority to the shock of the CAR decrease and close to zero in the long term. Our findings align with the expected effects that the CAMEL has implications to the decline of GDP of priority sector. Finally, we find that the impulse response of aggregate GDP and GDP of the priority sector to monetary policy shock decreases in the short run and near to zero in the more extended period

Mortgage credit volumes and monetary policy after the Great Recession

We study how the Federal Reserve's normalization plan influences interconnected mortgage credit markets that bridge the traditional and shadow banking sectors. Over key time periods (2006, 2009, 2015) in a time-varying factor-augmented vector autoregression with stochastic volatility, we document that increases in the shadow policy rate used to proxy the normalization plan lead to falls in bank mortgages partially offset by rises in nonbank mortgages. Monetary policy changes affect funding opportunities in securitized mortgage markets, lenders' willingness to lend, and economic conditions impacting mortgage demand that determine lenders' financial condition and numbers of mortgages extended. Banks, hampered by regulations, internalize a monetary policy contraction into fewer mortgages. Nonbanks take advantage and continue to meet mortgage demand through funding in agency securitized mortgages markets. Our findings suggest that the unintended increase in nonbank mortgages may threaten financial stability from more highly leveraged nonbanks becoming more vulnerable to adverse shocks.

Mining and Energy Commodity Price Effects on Colombian Economy

The Colombian economy has a strong dependence on the export of commodities. Different studies show that the prices of these products are exogenous, which have originated direct effects on the national economic activity. Therefore, this paper studies the shock effects produced by mining and energy commodity price variations like oil, coal and nickel on Colombian economy. We used 129 variables for 2001-2016 period and estimated a FAVAR model (Factor Augmented VAR) to observe commodity price effects on different economic aggregates, the results show that price fluctuations have significant effects on variables such as economic activity, investment, the trade balance, the real exchange rate and external debt.

The heterogeneous impact of monetary policy on the US labor market

We empirically investigate the role of central banks in the context of heterogeneous labor markets, jobless recoveries and job polarization. Specifically, we estimate the effect of monetary policy on the US labor market using disaggregated time series based on large scale survey data. The impact of interest rate changes on unemployment in 32 occupation groups is explored in a Bayesian factor-augmented vector autoregression framework. The results suggest largely heterogeneous impacts across various occupation groups. This heterogeneity can be explained by differential task profiles of the workers in their respective occupations. Workers with tasks that are easily automated or offshored as well as workers at the bottom of the skill distribution are disproportionately affected following a monetary policy shock. This implies that labor market participants that are highly vulnerable to structural developments such as skill-biased technological change and the globalization of labor markets are also most sensitive to conventional monetary policy measures. From a policy perspective, we conclude that central banks are unlikely to be able to take on a stabilizing role in the context of labor market polarization.

The impacts of oil price shocks in Turkey: sectoral evidence from the FAVAR approach

This paper investigates the effects of crude oil price shocks on the Turkish economy from 2005:01 to 2018:04 using a relatively new technique: the factor-augmented vector autoregressive (FAVAR) approach. The findings indicate the importance of crude oil prices to inflation, sectoral growth, and monetary policy. The main results of the impulse response analyses are as follows: (1) Oil price shocks did not explain changes in industrial production growth or its subsectors; (2) the responses of different price indices to positive oil price shocks are statistically significant and persistent. The largest number of price increases occurs in the transportation and food and beverage sectors; (3) monetary policy does not respond to oil price shocks. One can claim that the interest rate does not respond to oil price and allow the prices to adjust. Afterward, the price adjustment neutralizes the production effects of the oil price shocks.

Testing for the Effectiveness of Inflation Targeting in India: A Factor Augmented Vector Autoregression (FAVAR) Approach

Abstract Employing Factor Augmented Vector Autoregression (FAVAR) model where factors are obtained using the principal component analysis (PCA) and the parameters of the model are estimated using Vector Autoregression framework, we analyse how changes in monetary policy variables impact inflation, output, money supply, and the financial sector in India. Our results for the period 2001:04 to 2016:03 show that the benchmark FAVAR model showed more reliable results than baseline VAR model. Benchmark FAVAR model shows the existence of weak ‘liquidity puzzle’ in India. The impulse responses from the FAVAR approach reveal that monetary policy is more efficient in explaining the variations in inflation rather than stimulating output indicating its effectiveness in attaining the objective of price stability.

A FAVAR modeling approach to credit risk stress testing and its application to the Hong Kong banking industry

In October 2018, the Basel Committee on Banking Supervision (BCBS) published its stress testing principles. One of these principles is about stress testing model validation, aided by business interpretation, benchmark comparison and backtesting. In this paper, a credit risk stress testing model based on the factor-augmented vector autoregressive (FAVAR) approach is proposed to project credit risk loss under stressed scenarios. Inherited from both factor analysis (FA) and the vector autoregressive (VAR) model, the FAVAR approach ensures that the proposed model has many appealing features. First, a large number of model input variables can be reduced to a handful of latent common factors to avoid the curse of dimensionality. Second, the dynamic interrelationship among macroeconomic variables and credit risk loss measures can be studied without exogeneity assumptions. Moreover, the application of the impulse response function facilitates the multiperiod projection of credit risk loss in response to macroeconomic shocks. All of these features make the proposed modeling framework a potentially handy solution to fulfilling the BCBS requirement of quantitative adequacy assessment of banks’ internal stress testing results with a benchmark model. The scope of its application can also extend to impairment modeling for International Financial Reporting Standard 9, which requires the projection of credit risk losses over consecutive periods under different macroeconomic scenarios.

The Role of a Latent Value-Relevant Measure in Tracking and Predicting Stock Returns: A FAVAR Approach

This paper attempts to estimate and study the role of 'other information', as posited in the residual income valuation model of Ohlson (1995), for tracking and predicting future returns of the S&P 500. 'Other information' is an unobserved variable and defined as a summary of value-relevant information about events and their effect on future profitability, which is captured in a company's current stock price and returns, but not yet reflected in a company's current financial statements. This suggests a potential to predict subsequent returns. Previous literature has found that traditional valuation metrics (e.g. B/P, E/P, and D/P ratios) have poor predictive power. In this study, we apply a factor augmented vector autoregression (FAVAR) to estimate this value-relevant latent variable and assess its predictive performance. The FAVAR is a suitable model because it enables us to analyze and quantify the linkages of stock market value, profitability, and unobserved factors that are broadly captured by big data. We use a two-step principal components estimation approach to extract the unobserved factors of 78 informational variables from financial market, accounting, investor and consumer sentiment, and macroeconomic data. Our analysis shows that, in comparison to competing measures, the estimated latent value-relevant variable can track contemporaneous stock returns and has statistically reliable power to predict both future real stock returns and excess returns over a Treasury Bill rate, both in- and out-of-sample.

Monetary policy and systemic risk-taking in the Euro area investment fund industry: A structural factor-augmented vector autoregression analysis

Abundant references to threats to financial stability likely posed by systemic risk-taking in the euro area investment fund industry in an era of persistent low interest rates have not been accompanied by robust supportive empirical evidence. This is the first study that assesses the effects of euro area conventional and unconventional monetary policy shocks on coherent systemic risk measures applied to the investment fund industry. This research finds evidence of systemic risk-taking notably in the forms of contagion and increased vulnerability. It seems more material following conventional than unconventional monetary policy shocks. There is heterogeneity in the results, as the investment focus is important for assessing investment funds’ contribution to systemic risk. Fund types most affected by significant systemic risk-taking are bond funds, mixed funds and real estate funds. Some evidence of heightened vulnerability in equity funds is also present. Increase in leverage is part of the risk-taking mechanism. A key policy implication is that persistently accommodative monetary policy geared toward preserving price stability may face an intertemporal trade-off with financial stability, making it necessary to coordinate monetary and macroprudential policies.

Inflation and exchange rate pass-through

This paper investigates exchange rate pass-through into consumer prices by considering the nature of the shock triggering currency movements. By individually estimating structural factor-augmented vector autoregression models for 55 countries, monetary policy shocks are shown to be associated with higher exchange rate pass-through measures compared to other domestic shocks, while global shocks have widely different effects across countries. Pass-through measures tend to be lower in countries that combine flexible exchange rate regimes and credible inflation targets, where central bank independence can greatly facilitate the task of stabilizing inflation by using the exchange rate as a buffer against external shocks. It is implied that exchange rate pass-through should be investigated by considering the nature of the shock that triggers currency movements and country characteristics that affect the response of prices.

Government spending and heterogeneous consumption dynamics

What is the effect of government spending on consumption? Neoclassical and new Keynesian models deliver opposing predictions and empirical studies differ in their conclusions. This paper takes a data-driven approach and exploits information from over 200 variables via a Bayesian factor-augmented VAR model. I use sign restrictions for identifying effects that both classes of models agree upon. This approach imposes a minimal set of restrictions on the empirical model, leaving the sign and magnitude of the effect of government spending on consumption free to be determined by the data. I find that: (i) government spending increases aggregate consumption; (ii) the estimated spending multiplier is close to 2; (iii) there exists heterogeneity even within durable, nondurable, and service consumption variables which is undocumented in the literature. Finally, I show that my identified structural shocks are not predictable by economic agents and are uncorrelated with traditional monetary policy shocks, suggesting that these effects are not confounded by monetary policy.

On interaction between carbon spot prices and Czech steel industry

Environmental policy in the European Union is a frequent topic when speaking about a strategic development of national economies, their sectors, or companies. This paper is focused on transmissions between the European carbon market and the Czech steel industry. This relationship is worth exploring for two main reasons – first, iron and steel industry is responsible for a substantial part of CO2 pollution covered by the European Union emissions trading system (EU ETS) and, second, this sector is a traditional and vital industry in the Czech Republic. We use the dynamic Factor Augmented Vector Autoregression (FAVAR) model and Granger causality analysis to identify and assess the interactions between the factors of the EU ETS (prices of emission allowances and grandfathering), and factors of the steel industry like prices and amounts of production. To the best of our knowledge, this is the first application of the FAVAR model to analyse an industrial sector, and it is also the first analysis of the given topic where so many influencing factors are involved (this is allowed by the FAVAR model). The main results show that steel companies in the Czech Republic pass through the emission costs to customers.

The Effectiveness of China’s Monetary Policy: Based on the Mixed-Frequency Data

After the period of rapid growth, the Chinese economy has entered the “new normal” stage. This is a sign of the expected slowdown in economic growth. In the course of development, has the effectiveness of China’s monetary policy changed? Which of quantity and price rule monetary policies is more suitable for China’s economy? Very few researches focus on these questions, and this paper constructed a novel Mixed-Frequency Bayesian Factor Augmented Vector AutoRegression (MF-BFAVAR for short) model by combining the dynamic factor model, mixed-frequency spirit, Bayesian estimation, and factor augmented vector autoregression to find the answer. And we applied three different frequencies of data, in order to get the best estimated results. The conclusion is that price rule monetary policy is suitable for the period of steady development, and when economic growth suffers fluctuations, quantity rule monetary policy has better performance. Therefore, monetary policymakers should formulate the most effective policy based on different situations.

Peripheral Banking System Fragility and its Effect on EMU Monetary Policy Transmission Mechanism

This article evaluates the transmission through intermediaries taking into consideration the dichotomy between peripheral and core banking systems with regards to the ECB’s standard and non- standard measures of monetary policy by the use of “shadow rate” as an indicator of the monetary policy stance. Bank sector is represented by lending surveys data (BLS) which contain robust quarterly information on changes in loan terms, conditions and standards for both firms and households. By using a Factor Augmented VAR (FAVAR) methodology, we conclude that our model performs well, but it only contradicts the predictions of theory as far as it concerns the credit volume impulse responses functions (IRFs). Selecting a sample of core and peripheral banking systems to apply our methodology, we find the theoretical predictions are confirmed only when the peripheral banking systems are neutralized, indicating that the erratic behaviour of IRFs results from the periphery’s banking system inclusion. We conclude that dislocation in the peripheral segment of European banking system impairs seriously the monetary policy transmission mechanism and, importantly, steps should be undertaken towards risk-sharing in EMU and risk reduction in peripheral banking systems to cure banking system imbalances in the context of EMU.

Peripheral Banking System Fragility and its Effect on EMU Monetary Policy Transmission Mechanism

This article evaluates the transmission through intermediaries taking into consideration the dichotomy between peripheral and core banking systems with regards to the ECB’s standard and non- standard measures of monetary policy by the use of “shadow rate” as an indicator of the monetary policy stance. Bank sector is represented by lending surveys data (BLS) which contain robust quarterly information on changes in loan terms, conditions and standards for both firms and households. By using a Factor Augmented VAR (FAVAR) methodology, we conclude that our model performs well, but it only contradicts the predictions of theory as far as it concerns the credit volume impulse responses functions (IRFs). Selecting a sample of core and peripheral banking systems to apply our methodology, we find the theoretical predictions are confirmed only when the peripheral banking systems are neutralized, indicating that the erratic behaviour of IRFs results from the periphery’s banking system inclusion. We conclude that dislocation in the peripheral segment of European banking system impairs seriously the monetary policy transmission mechanism and, importantly, steps should be undertaken towards risk-sharing in EMU and risk reduction in peripheral banking systems to cure banking system imbalances in the context of EMU.

Exchange Rate Dynamics and Global Monetary Policy Spillovers: Time-Varying Dynamic Causal Effects

We show how to study time-varying dynamic causal effects of structural shocks using external instruments in a generalized Factor-Augmented-VAR(FAVAR) model with time-varying parameters and stochastic volatility. Specifically, we employ the Bayesian MCMC estimation methodology and focus on global factors of outputs, inflation rates, interest rates, and exchange rates in five representative advanced economies, namely the United States, Canada, Germany, Japan, and the United Kingdom, to study time-varying impacts of an exogenous U.S. monetary policy shock on these open economies. We find uniformly strong evidence over time in support of Dornbusch's theoretical prediction of the exchange rate overshooting in response to an exogenous monetary policy shock. The delayed overshooting puzzle commonly documented in the literature disappears, likely thanks to the better identification of the exogenous U.S. monetary policy shock via external instruments. We also find that the U.S. monetary policy shock has significant contributions to the dynamics of the exchange rates overall, and the contributions were particularly large during the period of global financial crisis in 2007-2008. We document a great deal of time variations of impacts of the U.S. monetary policy shock on global factors of all other economic variables including interest rates, inflation rates, and outputs. These empirical results lend strong support to the extension of the baseline model to the more general model with time-varying parameters and stochastic volatility.

Oil Shocks and the U.S. Economy: Evidence from a FAVAR Model

We investigate the economic effects of three separate types of oil price shocks on the U.S. economy using a factor augmented vector autoregression framework and 185 monthly macroeconomic indicators from 1978 to 2017. We find that while increases in the price of crude oil triggered by oil supply shocks and oil demand shocks lead to a significant and permanent increase in the U.S. price level, the main drivers of fluctuations in the price of crude oil and the U.S. price level are oil-specific precautionary demand shocks. Further, while increases in the price of oil triggered by oil supply shocks are recessionary and lower U.S. economic activity, those triggered by oil demand shocks driven by global economic activity are associated with increased U.S. economic activity. We also find evidence that monetary policy-makers tighten monetary policy in response to oil demand shocks to mitigate inflationary effects, however we find no such evidence for oil supply shocks. Finally, we find the U.S. dollar real exchange rate depreciates in response to increases in the price of oil caused by both oil demand and supply shocks, however the effects from oil supply shocks are more permanent.

Global Confidence, Uncertainty, and Business Cycles

This paper investigates the role of global confidence cycles, measured as the common factor across a wide range of survey-based business or consumer confidence indicators on global macroeconomic fluctuations. I estimate a factor-augmented vector autoregression model, where global confidence shocks are identified through recursive restriction. I report three main results. First, the global confidence cycle, in particular that of consumer confidence, has played a key role in global business cycle fluctuations, explaining over a third and over a half, respectively, of total variation in global industrial production and employment over 1985-2019. Second, the results suggest that while global business confidence or uncertainty shocks are in nature demand-driven, global consumer confidence seems to reflect macroeconomic shocks in both demand and supply sides, in line with “animal spirit” and “news” views on the relation between confidence and economic activities. Third, the empirical results suggest that the plunges in economic confidence caused by the COVID-19 pandemic have led to around 25 percent decline in global industrial production by the end of 2020. The results are robust to the ordering of variables or alternative identifying schemes that include external instrument identification.