Forecasting Hong Kong economy using factor augmented vector autoregression

This work applies the FAVAR model to forecast GDP growth rate, unemployment rate and inflation rate of the Hong Kong economy. There is no factor model forecasting literature on the Hong Kong economy. The objective is to find out whether factor forecasting of using a large dataset can improve forecast performance of the Hong Kong economy. To avoid misspecification of the number of factors in the FAVAR, combination forecasts are constructed. It is found that forecasts from FAVAR model overall outperform simple VAR and AR models, especially when forecasting horizon increases. Generally, combination forecasts solve the misspecification problem.Hong Kong; forecasting; Factor Model; Factor Augmented VAR; FAVAR

The Bank Lending Channel: a FAVAR Analysis

We examine the role of commercial banks in monetary transmission in a factor-augmented vector autoregression (FAVAR). A FAVAR exploits a large number of macroeconomic indicators to identify monetary policy shocks, and we add commonly used lending aggregates and lending data at the bank level. While our results suggest that the bank lending channel (BLC) is stronger than previously thought, this feature is not robust. In addition, our results indicate a diffuse response to monetary innovations when individual banks are grouped according to asset sizes and loan components. This suggests that other bank characteristics could improve the identification of the BLC.Bank Lending Channel, FAVAR, Monetary Policy

What are the driving factors behind the rise of spreads and CDSs of Euro-area sovereign bonds? A FAVAR model for Greece and Ireland

This paper examines the underlying dynamics of selected euro-area sovereign bonds by employing a factor-augmenting vector autoregressive (FAVAR) model for the first time in the literature. This methodology allows for identifying the underlying transmission mechanisms of several factors; in particular, market liquidity and credit risk. Departing from the classical structural vector autoregressive (VAR) models, it allows us to relax limitations regarding the choice of variables that could drive spreads and credit default swaps (CDSs) of euro-area sovereign debts. The results show that liquidity, credit risk, and flight to quality drive both spreads and CDSs of five years’ maturity over swaps for Greece and Ireland in recent years. Greece, in particular, is facing an elastic demand for its sovereign bonds that further stretches liquidity. Moreover, in current illiquid market conditions spreads will continue to follow a steep upward trend, with certain adverse financial stability implications. In addition, we observe a negative feedback effect from counterparty credit risk

Measuring the effects of monetary policy in Pakistan: A factor augmented vector autoregressive approach

This paper examines the effects of monetary policy in Pakistan economy using a data rich environment. We used the Factor Augmented Vector Autoregressive (FAVAR) methodology, which contains 115 monthly variables for the period 1992:01 to 2010:12. We compare the results of VAR and FAVAR model and the results showed that FAVAR model explains the effects of monetary policy which are consistent with theory and better than VAR model. VAR model shows the existence of price puzzle and liquidity puzzle in Pakistan while FAVAR model did not provide any evidence of puzzles. FAVAR model supports the effectiveness of interest rate channel in Pakistan.Monetary Policy, VAR, FAVAR

Global commodity cycles and linkages a FAVAR approach

In this paper 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 a 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 of economic activity affect individual nonenergy 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. JEL Classification: E3, F3commodity prices, Exchange Rates, FAVAR, Globalisation, Oil Price

The credit supply channel of monetary policy: evidence from a FAVAR model with sign restrictions

We test whether the credit channel of the monetary policy was present in the United States' economy from January 2001 to April 2016. To this end, we use a factor-augmented vector autoregression, and we impose sensible theoretical sign restrictions in our structural identification scheme. We use the expected substitution effect between bank commercial loans and commercial papers to identify the credit supply channel. We found that the credit channel appears to have operated in the US economy during the sample period. However, when we split the sample, we found that the credit channel did not operate after the subprime crisis (close to the Zero Lower Bound of the interest rate). This result is robust to changing the sign restriction horizons. It supports current views in the literature regarding the ineffectiveness of the credit channel as a means to foster real economic activity during crises episodes

On the interaction between market and credit risk: a factor-augmented vector autoregressive (FAVAR) approach

The aim of the paper is to understand the interaction between market and credit risk. Using a comprehensive set of Italian data, we apply a factor model to identify the common sources of risk driving fluctuations in the real and financial sectors. The common latent factors are then inserted in a VAR framework via a Factor Augmented Vector Autoregressive (FAVAR) approach to analyse the role of risk interactions with monetary policy shocks. We find that the impact of a restrictive monetary policy shock on credit risk is amplified when considering the feedback effect deriving from macroeconomic and equity market risk. Thus, neglecting dynamic interactions among risks may lead to biased estimates of the overall risk measure. The approach provides a framework for modelling macro and financial feedback dynamics, shedding some light on the complex interdependence between the financial sector and the real economy.FAVAR approach, credit risk, market risk, factor model

Placing the Czech shadow banking sector under the light

The size of the shadow banking sector (SBS) has more than doubled in the Czech Republic over the last decade. This places a potential burden on policy makers. On the one hand, the SBS complements regular banking by expanding access to credit and investments, enabling better risk sharing and maturity transformation, and supporting market liquidity. On the other hand, SBS activities can put the stability of the financial system at risk and amplify its procyclicality by exacerbating the buildup of leverage and asset price bubbles. We implement a FAVAR model of the Czech economy to determine the impact of macroeconomic factors on the SBS. We find that the SBS: (i) is sensitive to changes in market interest rates and term spread; (ii) exhibits great procyclicality; (iii) can act as a complement to regular banking and satisfy some additional demand for credit. We also define some potential risks of continued growth of the SBS, linked to our empirical evidence.Web of Science29128

Measuring the Effects of Monetary Policy: A Factor-Augmented Vector Autoregressive (FAVAR) Approach

Structural vector autoregressions (VARs) are widely used to trace out the effect of monetary policy innovations on the economy. However, the sparse information sets typically used in these empirical models lead to at least two potential problems with the results. First, to the extent that central banks and the private sector have information not reflected in the VAR, the measurement of policy innovations is likely to be contaminated. A second problem is that impulse responses can be observed only for the included variables, which generally constitute only a small subset of the variables that the researcher and policymaker care about. In this paper we investigate one potential solution to this limited information problem, which combines the standard structural VAR analysis with recent developments in factor analysis for large data sets. We find that the information that our factor-augmented VAR (FAVAR) methodology exploits is indeed important to properly identify the monetary transmission mechanism. Overall, our results provide a comprehensive and coherent picture of the effect of monetary policy on the economy.