Bayesian VAR Model Research Articles

Labour at risk

We propose a Bayesian VAR model with stochastic volatility and time varying skewness to estimate the degree of labour at risk in the euro area and in the United States. We model the asymmetry of the shocks to changes in the unemployment rate as a function of real activity and financial risk factors. We find that the conditional distribution of the changes in the unemployment rate displays time-varying volatility and skewness, with peaks coinciding with the Global Financial Crisis and the COVID-19 pandemic, in both areas. We also take advantage of the multivariate nature of our parametric model to measure the joint risk of large increases in the unemployment rate together with large annual rates of inflation, a proxy for “stagflation” risks. The model captures an increase of the risk of stagflation with the surge in inflation that followed the recent energy crisis in 2022. Nevertheless, stagflation risks were contained by the resilient performance of the labour market in both areas. Labour at risk is therefore important for the assessment of the inflation-unemployment trade-off.

Public debt determinants: A time-varying analysis of core and peripheral Euro area countries

This study employs a Bayesian Interacted Panel VAR model to estimate time-varying Generalized Forecast Error Variance Decomposition, analyzing how key determinants affect debt in Core and Peripheral Euro Area countries. Results highlight varying effects of determinants across periods and subgroups.

Fiscal multipliers in recession and expansion. An analysis for the Italian regions

This paper estimates the multipliers of two types of government spending in the 20 Italian administrative regions throughout 1960–2017, distinguishing between phases of expansion and recession. We derive regime- and region-specific multipliers through a nonlinear Bayesian heterogeneous panel threshold VAR model and provide a wide-ranging sensitivity analysis. We find that both government consumption and government investment multipliers are higher in recession than in expansion. In almost every region, government investment multipliers exceed unity in recession phases and are generally higher than their government consumption counterparts regardless of the business cycle. An exploratory analysis of the region-specific multipliers suggests that the difference between the region-specific multipliers in recession and expansion is positively associated with structural labour slack and negatively associated with trade openness. Factors related to the quality of local institutions, such as corruption and the relative size of the informal economy, also have a negative impact.

Energy shocks in the Euro area: Disentangling the pass-through from oil and gas prices to inflation

We develop a Bayesian Structural VAR model to study the relationship between different energy shocks and inflation dynamics in Europe. Specifically, we model the endogenous transmission from shocks identified by the global market of crude oil and the European natural gas market to two target macroeconomic variables, i.e. inflation expectations and realized headline inflation rate. Our results demonstrate that, since the post-pandemic recovery, inflation in the Euro area is mostly driven by energy price shocks and aggregate supply factors. In particular, the high peaks of the Eurozone inflation are mostly associated with natural gas supply shocks.

China's monetary policy framework and global commodity prices

This paper examines the effects of China's monetary policy on global commodity prices over the quarterly period 1996:Q1–2021:Q4. Using a Bayesian Structural VAR model, we evaluate the impact of interest rate shocks (as a price rule) and shocks to the monetary aggregate (M2) (as a quantity rule) on those commodity prices. Our main findings are fourfold. First, a positive interest rate shock has a negative and persistent effect on commodity prices, with beverages and metals commodity prices falling the most in response to such shock. Second, a positive shock to the growth rate of M2 has a strong impact on the prices of non-fuel commodities, agricultural raw materials, and metals. Still, the highly volatile food and fuel (energy) commodity prices are less affected. Third, while both the growth rate of M2 and the interest rate seem relevant macroeconomic stabilizers, the quantity instrument appears more effective than the price instrument in explaining commodity prices. Finally, while interest rate hikes are linked with a persistent rise in world uncertainty, monetary expansions lead to a long-lived fall in this variable. All in all, our study provides new evidence about the impact of China's monetary policy on global commodity prices using a rich dataset and an econometric setup that accounts for uncertainty.

Balance sheet expansionary policies in the euro area: Macroeconomic impacts and a vulnerable versus non-vulnerable comparison

This paper investigates the impacts and heterogeneity of the ECB's large-scale asset purchasing programs of sovereign securities on real GDP, inflation, long-term sovereign bond yields, systemic stress, and the unemployment rate. A structural Bayesian VAR model with six endogenous variables was estimated for 11 euro area countries over the period 2012:M1 to 2023:M12. To provide robustness to the results, a structural panel BVAR model is estimated, enabling a straightforward comparison of impulse responses of vulnerable and non-vulnerable countries. The results suggest that the magnitudes of impulse responses were more favorable in countries that were more economically and financially vulnerable. These findings underscore that financial and economic distress was a source of heterogeneity in the responses to large scale asset purchases within the euro area.

Nowcasting Vietnam's Export Growth with Mixed Frequency Data

Purpose: The primary objective of this study is to investigate and employ a practical and meaningful nowcasting model to predict Vietnam's export growth based on factors of export supply and demand alongside relevant financial indicators. Theoretical Framework: This study employs the concepts and theories of nowcasting model with mixed frequency data to create the conceptual framework. Methodology: This study employs four commonly-used models in nowcasting: the bridge equation model (BEQ), Bayesian VAR model (BVAR), mixed frequency vector autoregressive model (MFVAR), and mixed data sampling regression (MIDAS). Findings: According to the experimental findings, the mixed frequency data models outperformed the models utilizing the same frequency data in nowcasting Vietnam's export growth. Additionally, this model demonstrated effectiveness in instantaneous and short-term forecasting. MIDAS emerged as the most suitable choice for nowcasting Vietnam's export growth among the models examined. Implication of Research: using data with mixed frequency along with corrresponding methods is the good way for nowcasting. Originality/Value: This study used macroeconomics factors to nowcast the export growth in Vietnam. It applied four different models including BEQ, BVAR, MFVAR, and MIDAS. The study reveals the roles of data and the potential capability in nowcasting of MIDAS model.

Tips and tricks for Bayesian VAR models in gretl

Tips and tricks for Bayesian VAR models in gretl

Unravelling the credit market shocks and investment dynamics: A theoretical and empirical perspective

This paper investigates the underlying credit market shocks that historically affected business investment in the Slovenian economy. In contrast to the existing literature, we explore more profound structural shocks beneath the credit demand and supply shocks. For the purpose of structural identification, we propose a theoretical model of the credit market that reveals the credit market imperfections on the side of credit supply as well as liquidity demand. The theoretical structure justifies our set of identifying restrictions, further evaluated with the structural Bayesian VAR model. Our results confirm the relevance of loan supply shocks for the business investment activity, suggesting the existence of credit market imperfections. Furthermore, business investment is strongly conditioned by liquidity demand shocks, which explain a significant part of the variation in investment activity. Even though loan supply shocks constrained the investment activity in Slovenia during the financial crisis, the results of our analysis suggest that banks predominantly reacted to the increasing financial risk as opposed to the changes in their profit functions. Based on the results, we may conclude that in the common monetary area, fiscal policy should implement country-specific measures to effectively address the business sector's expectations regarding the economy's medium- and long-term development.

Effect of conventional and unconventional monetary policy shocks on housing prices in Canada

This paper investigates the relative importance and effect of conventional and unconventional Canadian monetary policy surprises on housing prices. Using a credible approach to identify structural monetary policy shocks in Canada and a comprehensive Bayesian VAR model to analyze their effects on financial and macroeconomic variables, we find that both conventional monetary policy and quantitative easing shocks have a significant and persistent effect on housing prices in Canada. However, the inflationary effect of a quantitative easing shock is more pronounced than that of an easing target monetary policy surprise. Specifically, the peak effect of a 25-basis point expansionary conventional monetary policy shock is a 2.30% increase in real housing prices while a comparable quantitative easing surprise leads to a peak of 4.56% increase in real housing prices. We conclude that expansionary monetary policy in various forms has had significant inflationary effects on Canadian housing prices. But quantitative easing surprises stand out as the most prominent contributory factor to the escalating Canadian real estate price. Quantitative easing impact consistently outweighs the effects of forward guidance and conventional monetary policy shocks.

A note on the dynamic effects of supply and demand shocks in the crude oil market

ABSTRACT In this paper, we investigate whether key relations in the crude oil market have been stable over time. This is done by estimating hybrid time-varying parameter structural Bayesian VAR models using monthly data ranging from February 1973 to May 2023. Model selection suggests that while stochastic volatility is preferred over homoscedasticity, the dynamics of the model are best described by constant parameters in all equations.

Fiscal and Monetary Policies Interaction in Crisis: An Insight Into Japan

In this study, we explore the interaction between fiscal and monetary policies in Japan over a period including the Global Financial Crisis (GFC) and a phase of the Covid-19 pandemic under the presupposition that policy regimes are fixed and there are random switches between the two regimes. Using the Regime switching model, the results show that fiscal policy is more active in Japan than monetary policy, especially during the GFC and the Covid-19 pandemic. By using the Bayesian VAR model, we continue to further analyze the response of macroeconomic factors to an expansionary fiscal policy to verify the above findings once again. The results indicate that government expenditure helps boost the economy in the short-run. The positive impact of a government expenditure shock on GDP, PPI, and Investment lasts about three to four quarters, while private consumption only increases in one next quarter. These positive responses can increase the inflation rate and make the local currency overvalued, reflected in the increase in the effective exchange rate. A fiscal policy shock does not have much impact on the monetary policy, specifically, the money supply and interest rates of long-term government bonds still tended to decrease as expected by Japan. This is the basis for studying policy implications for some countries pursuing similar policies to Japan. JEL Classification: C23, C54, E42, E62, E63

Variational Inference for Bayesian Panel VAR Models

Variational Inference for Bayesian Panel VAR Models

The impact of ECB’s Quantitative Easing on cryptocurrency markets during times of crisis

In this paper, we investigate non-linear linkages between Bitcoin and the unconventional monetary policies of the European Central Bank (ECB). In particular, we examine whether a low-interest rate environment resulting from QE indirectly encourages investors to move towards Bitcoin. Using a Bayesian VAR model with time-varying coefficients and stochastic volatility (TVP-BVAR-SV model), we compare Bitcoin’s responses to the shadow rate shocks during the pre-and post-COVID-19 periods. Moreover, despite the high uncertainty and the low-interest rate environment, Bitcoin's response during the COVID-19 period reveals a steeper drop compared to the pre-COVID-19 period. That said, investors did not resort to Bitcoin for safety and higher returns. Our findings can be attributed to the unprecedented nature of the crisis, the investor reluctance and pessimism, and the changing behavior of Bitcoin, which is no longer perceived as a safe haven.

Financial Condition Indices in an Incomplete Data Environment

Abstract We construct a Financial Conditions Index (FCI) for the United States using a dataset that features many missing observations. The novel combination of probabilistic principal component techniques and a Bayesian factor-augmented VAR model resolves the challenges posed by data points being unavailable within a high-frequency dataset. Even with up to 62 % of the data missing, the new approach yields a less noisy FCI that tracks the movement of 22 underlying financial variables more accurately both in-sample and out-of-sample.

The Effects of Demographic Change on GDP Growth: Research Focus on Russia

There has been a downward trend in economic growth in several economies over the past few decades, with the slowdown trend particularly evident in the case of Russia. These records estimate how much of this growth slowdown can be accounted for by demographic changes. Specifically, this study estimated how a changing age structure of the population (between four groups-ages 0-14, 15-64, and 65+) has affected GDP growth using annual time series data for Russia. The analysis is applied using the Bayesian VAR model. The data for the study are obtained from the World Bank. It was found that demographic changes account for a significant portion of the downward trend in the economic growth of Russia during the past decade. Moreover, the continuation of the demographic shift toward an older population is likely a valuable factor that has increased GDP growth in Russia over the last couple of decades. The research results point out that during the last decade; demographic effects have not had any significant influence on the change of GDP growth levels in Russia. Therefore, the research study contributes in a way indicating that future growth of GDP in Russia will depend much more on the growth of structural productivity, new technologies and worker profitability and much less on demographic changes.

How does climate policy uncertainty affect financial markets? Evidence from Europe

This study analyzes the time-varying effect of climate policy uncertainty (CPU) on the stock market and clean energy indices in the European context. For this purpose, we use the Bayesian time-varying parameter VAR model. The empirical results show that CPU shocks have a significant effect on the financial indexes. Returns on clean energy (crude oil) stocks increase (decrease) in response to heightened climate risk. Moreover, the COVID-19 pandemic is a relevant tipping point in CPU dynamics. These results offer important implications for European investors and policymakers in the context of the European climate-energy crisis.

Has the Fed Responded to House and Stock Prices? A Time-Varying Analysis

Abstract We investigate whether the Federal Reserve has responded systematically to house and stock prices and whether this response has changed over time using a Bayesian structural VAR model with time-varying parameters and stochastic volatility. To recover the systematic component of monetary policy, we interpret the interest rate equation in the VAR as an extended monetary policy rule responding to inflation, the output gap, house prices, and stock prices. Our results indicate that the systematic component of monetary policy in the United States responded to real stock price growth significantly but episodically, mainly around recessions and periods of financial instability, and took real house price growth into account only in the years preceding the Great Recession. Around half of the estimated response captures the predictor role of asset prices for future inflation and real economic activity, while the remaining component reflects a direct response to stock prices and house prices.

A note of caution on the relation between money growth and inflation

AbstractWe assess the bivariate relation between money growth and inflation in the euro area and the United States using hybrid time‐varying parameter Bayesian VAR models. Model selection based on marginal likelihoods suggests that the relation is statistically unstable across time in both regions. The effect of money growth on inflation weakened notably after the 1980s before strengthening after 2020. There is evidence that this time variation is related to the pace of price changes, as we find that the maximum impact of money growth on inflation is increasing in the trend level of inflation. These results caution against asserting a simple, time‐invariant relationship when modeling the joint dynamics of monetary aggregates and consumer prices.

House Bubbles, global imbalances and monetary policy in the US

This paper examines the factors driving housing price exuberance in the United States, specifically the influence of expansionary monetary policies and the global saving glut. We employ medium scale Bayesian VAR and time-varying VAR models to estimate the effects of monetary policy and global saving glut shocks on US housing bubbles. We find that, prior to the Global Financial Crisis, the impact of the saving glut shock is more enduring, powerful, and rapid in generating housing bubbles compared to monetary policy shocks. However, the recent housing boom that commenced in 2019 demonstrates a different pattern. Our results suggest that both monetary policy and the global saving glut contribute to the increase in house prices. Counterfactual policy experiments validate this conclusion.