Structural Vector Autoregressive Model Research Articles

Household assets and business cycle fluctuations

AbstractThis paper shows that an increase in the ratio of household assets to gross domestic product (GDP) predicts higher GDP growth in the short term, but lower growth in the long term. It is also associated with lower consumption, investment, and employment rates in the future. The result is robust to controlling for various economic indicators including credit spreads, household debt to GDP ratio, and leverage ratio. Finally, we estimate a structural vector autoregressive model and find that an increase in the interest rate is associated with a decrease in the household assets to GDP ratio, in contrast to the findings of Galí and Gambetti (2015, American Economic Journal: Macroeconomics, 7(1), 233–257). This appears to support the conventional view of monetary policy.

Sudden stop: Supply and demand shocks in the German natural gas market

SummaryWe use a structural vector autoregressive (SVAR) model to study the German natural gas market and investigate the impact of the 2022 Russian supply stop on the German economy. Combining conventional and narrative sign restrictions, we find that gas supply and demand shocks have large and persistent price effects, while output effects tend to be moderate. The 2022 natural gas price spike was driven by adverse supply shocks and positive storage demand shocks, as Germany filled its inventories before the winter. Counterfactual simulations of an embargo on natural gas imports from Russia indicate similar positive price and negative output effects compared with what we observe in the data.

THE IMPACT OF THE RECIPROCAL RELATIONSHIP BETWEEN EXCHANGE RATES AND INTEREST RATES ON THE BOND MARKET USING THE SVAR MODEL FOR CHINA FOR THE PERIOD FROM (2000-2020)

This study aims to illustrate the effect of the reciprocal relationship between the exchange rates and interest rates on the bond market by using the SVAR model for China during (2000 -2020), this is to analyze and measure the relationship between exchange rates and interest rates and showing their impact through changes in the bond index and monitoring the changes that occur in their traded prices in the financial markets. This study is based on three standard model estimations. The first model includes the effect of interest rates and inflation on the exchange rates. The second model shows the effect of the exchange rates and money supply on the interest rate. The third model includes the effect of exchange and interest rates on the bond index. The Structural Vector Auto Regression Model (SVAR) was used to test the long-term relationship between the variables of the study, in addition to the variance Decomposition analysis and the analysis of the Impulse response functions (IRF). The results showed that the reciprocal relationship between the exchange rates and interest rates is a positive inverse relationship, and the effect is in both directions. In other words, when the prevailing interest rate rises in the country, it leads to an appreciation in the value of the currency due to the increase in demand for the currency of that country, resulting in a depreciation in its exchange rate and conversely. In addition, the results indicated that the bond index is sensitive to any shock or any unexpected change in exchange rate and interest rate and that these shocks manifest in the short term and stabilize in the long term.

Monetary policy and heterogeneous price effects in the United Kingdom

AbstractThis paper examines the heterogeneous effects of monetary policy on consumer prices in the United Kingdom. We estimate a proxy Structural Vector Autoregressive (SVAR) model, using extended high‐frequency monetary surprises from Cesa‐Bianchi et al. (European Economic Review, 123, 2020, 103375) to instrument shifts in UK monetary policy. We then analyze the impulse responses for various components of the UK Consumer Price Index. Our findings reveal that while monetary policy tightening leads to a persistent decline in aggregate consumer prices, the impact on disaggregated components is highly heterogeneous. Notably, we observe that energy price changes offset movements in food, beverage, and tobacco prices, resulting in identical responses of core and headline consumer CPIH inflation measures. The contrasting effects across different CPI components highlight the importance of examining disaggregated data when assessing the transmission of monetary policy to consumer prices.

US trade policy and the US dollar

We show that the US dollar response to trade policy uncertainty (TPU) is key to assessing the impact of US trade policy. Employing structural vector autoregressive models, we find that TPU shocks supported a multilateral USD appreciation during the 2018–19 trade tensions between the US and some of its major trading partners. We rationalize this in a two-country New Keynesian model with financial frictions that links the increase in TPU to rising demand for safe USD assets. Our findings suggest that the TPU-induced appreciation of the USD in 2018–19 significantly counteracted US trade policy attempts to raise US competitiveness.

Assessing the extent and persistence of major crisis events in the crude oil market and economy: evidence from the past 30 years

This study investigates the extent and persistence of major crisis events in the crude oil market and economy and searches for general rules of event impact. Although the short-term effects of such crises may quickly become evident, their long-term implications can be challenging to uncover. To this end, we analyzed 50 major crisis events across four categories using a Proxy structural vector autoregressive (Proxy-SVAR) model. The results show that these events substantially impacted crude oil production, world crude oil prices, and inflation in China and the United States. Generally speaking, major crisis events have a more severe impact on the crude oil market, but their impact on the economy lasts longer. Notably, geopolitical conflicts have led to a sharp decline in S&P500, resulting in a simultaneous reduction in the industrial production indices of the world, China, and the US. Among the different types of crises, the financial crisis had the most prolonged impact, persisting for approximately four years. The public health emergency represented by COVID-19 resulted in a decline in actual oil prices, with its impact on the oil market continuing for over three years. Considering our findings, we suggest four policy measures to enhance economic resilience.

Terrorism and Economic Growth in Nigeria

Terrorism has emerged as a significant threat to global security and economic stability, with Nigeria experiencing its detrimental effects. This empirical study investigated the relationship between terrorism and economic growth in Nigeria. The study focused on the impact of terrorism on productivity in Nigeria, examining various aspects including economic growth, trade, foreign direct investment (FDI), manufacturing output, and other key indicators but with specific focus on economic growth. It highlighted the pervasive nature of terrorism in Nigeria, with various groups such as Boko Haram, ISIS, Fulani herdsmen, and Niger Delta militants contributing to violence and insecurity. The study reviews both empirical and theoretical literature on terrorism and its economic consequences, emphasizing the negative relationship between terrorism and economic growth. Using a positivist research paradigm, the study employed a Structural Vector Autoregression (SVAR) approach to analyze the impact of terrorism on economic variables in Nigeria. The SVAR model incorporated endogenous variables such as economic growth, capital, terrorism, and trade. Data covering a 42-year period from 1980 to 2021 were utilized, and they were sourced from the World Bank and World Development Indicators. The estimation and results section includes discussions on lag length selection criteria and impulse response analyses to understand the dynamic effects of terrorism on economic variables over time. In conclusion, the study underscored the detrimental impact of terrorism on productivity and economic growth in Nigeria, highlighting the need for effective counter-terrorism measures to mitigate these effects. It provides valuable insights for policymakers and researchers aiming to address the complex challenges posed by terrorism in the country.

Unravelling the devaluation puzzle: Empirical insights into the transmission channel on balance of payments and output in Ethiopia

Background Empirical studies on the impact of devaluation in developing countries, including Ethiopia, have revealed diverse and mixed results. The effects can be positive or negative depending on the specific economic context and policies in place.This study addresses the devaluation puzzle by providing a more comprehensive and nuanced understanding of how devaluation affects the balance of payments and output. Methods To achieve this, we employ a recursive structural vector autoregressive (SVAR) model focusing on Ethiopia from 2001Q1 to 2023Q4. Results The findings reveal that exchange rate shocks negatively affect the balance of payments in both the short and long run, with a greater impact observed in the short run. Shocks in other variables, such as foreign exchange rate reserves, inflation, and interest rates, exert a stronger influence on the balance of payments than the exchange rate itself in the long run. In addition, shocks in the exchange rate significantly impact foreign exchange rate reserves in the long run, highlighting the complex dynamics of exchange rates and the indirect nature of the exchange rate channel. Exchange rate shocks also negatively impact output growth in both the short and long run. Conclusion The study concludes that devaluation has a contractionary effect through various channels. Devaluation increases the money supply, leading to inflationary pressures and a decline in output. It also increases interest rates, which further reduces output. In addition, devaluation reduces foreign exchange reserves, resulting in a fall in the balance of payments and a decrease in output. We suggest policymakers prioritize exchange rate stability through practical monetary and fiscal policies. In general, International financial institutions, particularly the National Bank of Ethiopia, should reconsider their devaluation-focused policies, considering the complexities and potential negative consequences associated with devaluation.

Effect of fuel prices on sailing speeds in short-sea shipping

ABSTRACT In this paper, we estimate fuel price elasticities of sailing speed for general cargo vessels using data covering the Baltic Sea and Norwegian coastal areas during the years 2007–2018. To disentangle the correlation between fuel prices and freight rates arising from changes in global demand, we instrument fuel prices on price changes triggered by supply shocks. The shocks are derived from the structural vector autoregressive (SVAR) model proposed by Kilian (2009). In a sensitivity analysis, we use unanticipated oil supply shocks derived from oil supply outages as an alternative instrument for fuel prices. We find that disregarding the correlation between fuel prices and freight rates yields biased parameter estimates, which can partly explain the mixed results in the previous literature. Our preferred estimate for the fuel price elasticity of speed is −0.08.

The relations between European capital market and ECB monetary policy

Euro Area monetary policy and capital markets mutually affect each other’s indicators. In the frame of this research, we aimed to analyse and forecast the European Central Bank’s monetary policy influence on capital market segments. We based our study on structural vector autoregressive model methodology. Employing different scenarios, we forecasted the values of the government bond, corporate bond and stock market indicators in Euro Area, in response to the ECB monetary policy changes.

CAN EXCHANGE RATE CONTROL IN TURKEY HELP THE CENTRAL BANK EVALUATIONS WITHIN THE FRAMEWORK OF THE TAYLOR RULE

This paper tests the validity of the Augmented Taylor rule in the Turkish economy for the period between February 2011 and February 2024 with the structural vector autoregression model. It is found that the central bank did not use the policy rate against deviations from inflation in the relevant period. On the other hand, the policy rate moves within expectations against deviations in the output gap and the real exchange rate. According to the structural impulse-response functions, the output gap and the inflation gap respond positively to a one-unit shock to the policy rate, while the real exchange rate reacts negatively. According to the results of structural variance decomposition, the most influential variable on changes in the policy rate is the real exchange rate deficit. In conclusion, the policy rate in the Turkish economy takes into account the output gap and the real exchange rate gap. However, it ignores the inflation gap.

SIGNIFICANCE OF MONETARY INSTRUMENTS IN REGULATING THE ACTIVITIES OF BANKS

In this article, the impact of monetary policy instruments on the activity of commercial banks, in particular on bank liquidity, loan percentage and loan portfolio, is analyzed on the basis of econometric models. He used two different models in the econometric analysis assessing the impact of monetary policy instruments on commercial banks. The first model is a least square model, while the second is a structural vector autoregression model. In studying the impact of the monetary policy of the Central Bank on the activity of commercial banks, it analyzed two different types of banks.

Global Supply Chain Disruptions, Commodity Price Shocks and Inflation in Japan

In recent years, the concurrent occurrences of the COVID-19 pandemic and the Russian invasion of Ukraine have led to global disruptions in supply chains and a surge in commodity prices. Major advanced economies have experienced an increase in inflation rates and a decline in economic activity. Against this economic backdrop, this paper aims to address the strained condition of supply chains by employing the Global Supply Chain Pressure Index (GSCPI) alongside commodity price indices. Furthermore, it seeks to examine how fluctuations in these variables affect Japan’s macroeconomic landscape through local projection and structural Vector Autoregression (VAR). In the local projection analysis, it has been observed that the strain on supply chains induces sustained increases in consumer and producer prices, further contributing to long-term declines in production. Within the structural VAR model framework, the identification of structural shocks is conducted through sign restrictions, affirming the significance of supply chain shocks and energy and food price shocks as crucial factors contributing to recent price increases. This confirmation is supported by variance decomposition and historical decomposition analyses.

Analysis and forecasting of the dry bulk shipping market: structural VAR models using FFA-spot-time charter rates

ABSTRACT This study investigates dynamic interactive patterns of the dry bulk shipping markets through the lens of structural vector autoregression (VAR) models. There are two distinct hypotheses in the extant literature. One is that asymmetry between spot and forward freight agreement (FFA) markets causes FFA prices to respond more rapidly to new information than spot prices, termed the Physical-Paper Hypothesis in this paper. The other hypothesis is that there are some diverse shocks with different propagation mechanisms, termed the Shock-Diversity Hypothesis. This paper combines these two seemingly separate hypotheses at one time in two illustrative structural VAR models, based on a dataset of weekly spot, FFA, and time charter (TC) rates in the dry bulk shipping markets. The two structural VAR models show that spot, FFA, and TC rates have different, particularly dynamic responses to identified permanent shocks. Furthermore, they show that the reduced-form tri-variate FFA-Spot-TC VAR model produces more accurate forecasts of future spot rates than the bi-variate FFA-Spot and TC-Spot VAR models. Therefore, market participants can use VAR models as an information-processing tool for understanding of (e.g. data descriptions and structural inferences), and forecasting in, dry bulk shipping markets.

Efficacy of Monetary Policy Transmission During the Flexible Inflation Targeting Regime in India

This article builds a Structural Vector Autoregressive model and employs non-recursive identification restrictions to examine the effectiveness of the Monetary policy transmission mechanism in India during the Flexible Inflation Targeting regime (2016–2023). The results indicate that policy rate shocks have a significant negative impact on domestic output and prices during this regime. The findings further, reveal evidence of an exchange rate puzzle during the Flexible Inflation Targeting regime. Our results give credence to the RBI’s move towards a Flexible indicator targeting approach as all the macroeconomic variables of interest, that is, Domestic output and inflation produce plausible estimates in response to a monetary policy shock. JEL Classification: C32, E52, E5, E52, F41

The Impact of Quantitative Easing on Stock Prices in the U.S. Stock Market - Structural VAR Model Analysis

In an effort for future investment implications, the current study examined the relationship between historical Quantitative Easing (QE) programs and the stock market. This study analyzed weekly basis data in the United States between 2007 and 2023. Through a Vector auto-regression (VAR) model, a significant rise following a quick drop in stock prices to a positive shock in QE was discovered, indicating lagged response. Further robustness check proved the validation of relationship, by sectioning the whole data set into 4 periods corresponding to four QE programs, except relatively insignificant effects in QE2 and QE3 periods. These lagged responses were pointed out firstly in this paper and connected with policy motivations and contemporaneous economy environment across programs. The findings may enable investors to anticipate market movements and generate respectable returns in the event of such unconventional money shocks.

Geopolitical risk, supply chains, and global inflation

AbstractThis paper investigates the effects of global geopolitical risks and global supply chain pressures on global inflation for the monthly period of 1999M1–2022M12. The investigation is based on a structural vector autoregression model, where the effects of global oil prices and global monetary policy are controlled for. Four alternative measures of inflation are used, including headline, core, food, and energy inflation. The empirical results show that disruptions in global supply chains are the main drivers of global inflation in the long run as the corresponding shocks explain the lion's share of volatilities in headline inflation (by 32%), core inflation (by 30%), and food inflation (by 22%), followed by oil price shocks and policy rate shocks. In comparison, energy inflation is explained the most by oil price shocks (by 55%) followed by supply chain shocks and policy rate shocks. Positive supply chain pressure and oil price shocks have positive and statistically significant effects on headline inflation even after five years, whereas positive policy rate shocks have negative and statistically significant effects on headline inflation in the long run. In contrast, positive shocks to geopolitical risk result in higher headline inflation only up to one year, with insignificant effects in the long run. Several policy implications follow.

The effect of structural oil shocks on stock returns of Indian renewable energy companies across market conditions

Purpose This study aims to evaluate the structural oil shocks effect on stock returns of Indian renewable energy companies across market conditions. Design/methodology/approach This study applies the structural vector autoregression model to estimate sources of oil shocks such as oil supply shock, aggregate demand shock and oil price-specific demand shock. In the next step, the panel quantile regression model estimates the effect of these oil shocks on stock return across market conditions. Monthly data are collected from January 2009 to December 2019. All renewable energy companies listed on the National Stock Exchange of India are considered for the analysis. Findings In the whole sample analysis, this study finds that oil shocks negatively affect stock returns in most of the market conditions except oil price-specific demand shock. In sub-groups, oil shocks driven by supply and aggregate demand also negatively affect stock return in most market conditions. This study finds the positive interaction of oil price-specific demand shock. A majority of these positive interactions happen in bearish market conditions. In the whole sample, the asymmetric effects of shocks driven from oil supply and oil price-specific demand are seen in most quantiles or market conditions. At the same time, aggregate demand shock does not affect asymmetrically. In the sub-group analysis, standalone renewable energy companies stock returns are least asymmetrically affected by these oil shocks. The asymmetries of oil supply-driven shock on stock returns of the renewable energy sub-group companies are found in most quantiles. Originality/value First, this is a company-level study of the stock returns response to the structural oil shocks in the renewable energy sector. Second, to the best of the authors’ knowledge, this type of study is the first in the Indian context. Third using panel quantile regression model along with capital asset pricing model framework, the authors investigate these effects across market conditions.

Fiscal Policy, Government Ideology, and Economic Activity: Evidence from OECD Countries

AbstractThis study explores the role played by a country's political environment in the origin and effect of government spending. Using a rich data set that contains time‐varying ideological party positions, I show that both government ideology and the timing of elections are key determinants of government spending shocks and Granger‐cause government spending shocks estimated from traditional structural vector autoregressive (SVAR) models that ignore political considerations. I find that the magnitude of the spending multiplier depends on the political context: highly polarized countries have smaller multipliers relative to countries with a low degree of polarization, and established democracies have smaller multipliers than younger democracies.

Do higher global oil and wheat prices matter for the wheat flour price in Lebanon?

AbstractThis article investigates the effect of global oil and wheat prices, and local price shocks on the real price of wheat flour in Lebanon. We estimate a structural vector autoregressive model with exogenous variables (SVARX) using Bayesian methods. We then compute the impulse response functions and find that global commodity price shocks play a trivial role. Meanwhile, local gasoline price and wheat flour price‐specific shocks trigger large increases in the Lebanese wheat flour price on impact. Furthermore, since 2020, local gasoline price and wheat flour price‐specific shocks have contributed the most to the historical variation in the Lebanese wheat flour price.