Structural Vector Autoregressive Model Research Articles

Contemporaneous Spillovers Across Foreign Exchange Markets

ABSTRACTThe study of financial shock propagation across markets has motivated numerous researchers to investigate the mechanisms of return and volatility spillovers in order to prevent harmful shock transmission. This article studies the contemporaneous spillovers by employing a structural vector autoregressive (SVAR) model with Markov switching covariance matrix to solve the identification problem. The proposed method offers a smooth convergence that handles several drawbacks of existing procedures. Moreover, this article develops a new framework to analyse the contemporaneous asymmetric volatility spillovers, which adds a great deal of knowledge by separating the effects of good news and bad news on shock transmissions. Application on major exchange rate returns and volatilities shows that the contemporaneous effects have different intensities for all pairwise currencies. Furthermore, the asymmetric analysis reveals that good (bad) volatility has a contemporaneous positive effect on good (bad) volatility, while the risk due to good (bad) news negatively affects the risk due to an opposite shock.

Do economic shocks matter to U.S. farm income?

ABSTRACT Analysing the effect of economic shocks on farm profitability is crucial for determining the U.S. farm economy’s vulnerability to macroeconomic changes. Using a structural vector autoregressive model and over five decades of data, we examine the impact and importance of external economic shocks to the U.S. farm economy. Specifically, we measure the short-term and long-term volatility spillover effects on U.S. farm income from shocks in energy markets, exchange rates, and agricultural markets. We find that volatility in exchange rates significantly affects US net farm income fluctuations in the short term. Results also suggest that shocks in the exchange rate are more important than other economic shocks, explaining about 47% of the short-run fluctuation in U.S. net farm income. These results highlight the importance of accounting for macroeconomic shocks to enhance the stability of the U.S. agricultural sector and to improve the accuracy of USDA short-term forecasts and long-term projections of farm income components.

연구개발 투자 및 보조금의 지역 거시경제 효과성 분석

This study empirically analyzes the impacts of regional R&D investment and government subsidies on regional economic growth and economic disparities between capital and non-capital regions, by utilizing regional yearly panel data. In particular, this study introduces structural vector auto-regression(SVAR) model based on conditional convergence of neoclassical growth theory, considering econometrical issues related to conventional growth regression analyses. The study finds that the increase in R&D investment of non-capital areas measured by its ratio to GRDP accelerates regional economic growth and mitigates the economic disparities between capital and non-capital areas. However, government R&D subsidy to those regions shows no empirically significant effect on regional economic growth or economic disparity between capital and non-capital areas. On the aspects of reducing regional disparity between capital and non-capital area, this study’s empirical finding is an indicative of the existence of less ‘opportunity cost-effective’ portions in government R&D subsidy programs, and thus further micro-level analyses on the policy effectiveness of government R&D subsidy programs is required.

Weather Shocks in The Gambia: Macroeconomic Effects and Households Vulnerability

Abstract Climate change is increasing the frequency of weather shocks, which poses a significant challenge for agriculture-dependent economies such as those of sub-Saharan African countries. In this study, we present an innovative framework that combines empirical and theoretical procedures to investigate the propagation mechanism of weather shocks in The Gambia. We first document the propagation mechanism of a weather shock using a Structural Vector Auto-regressive (SVAR) model on the Gambia data. We construct and estimate a Dynamic Stochastic General Equilibrium (DSGE) model to elucidate this mechanism. This model is enhanced to encapsulate the weather-dependent agricultural sector, the heterogeneity of households in terms of access to financial markets and the inflow of remittances. Our findings reveal that weather shocks in The Gambia (i) account for approximately 10% of GDP and agricultural output in the short run, (ii) significantly contribute to long-term consumption volatility,(iii) critically increase the volatility of Ricardian households’ consumption and (iv) stimulate an increase in the direct inflow of remittances to vulnerable households.

Do disaggregated oil price shocks drive the Chinese non-ferrous metal market across different time horizons and quantiles?

ABSTRACT This study uses a wavelet-based quantile approach to document the effects of disaggregated oil shocks on the Chinese non-ferrous metal market under various time horizons and quantiles. Oil shocks are decomposed into supply, aggregate demand, and oil-specific demand shocks based on a structural vector autoregressive model. Empirical results suggest that oil shocks have notable impacts on the Chinese non-ferrous metal market in the middle and long term, whereas the impacts in the short term are not significant. The impacts remain remarkably heterogeneous across quantile levels in the long term. Oil supply shocks significantly affect the non-ferrous metal market positively, but only at higher quantiles. The positive effect of aggregate demand shocks and the negative effect of oil-specific demand shocks are significant at lower quantiles. Moreover, copper is susceptible to oil shocks, compared with aluminium. These findings provide several implications for policymakers and investors.

Macroeconomic responses to financial stress shocks: Evidence from the US and the Eurozone

This paper investigates the macroeconomic effects of an unexpected financial stress shock in the United States and the Eurozone, focusing mainly on the effect on unemployment and the response of monetary policy. First, we estimate Impulse Response Functions (IRFs) based on a Structural Vector Autoregression (SVAR) model with short-run restrictions according to economic theory. Next, we perform panel data analysis shedding light on the factors that affect unemployment in the two regions. Our findings indicate a significant impact of financial stress shocks on the macroeconomic environment, but with different policy responses from the Federal Reserve (Fed) and the European Central Bank (ECB). The impact of higher financial stress on economic activity and employment is negative in both regions, but the duration of the impact on unemployment is shorter in the US, suggesting a quicker recovery in the US labor market compared to the Eurozone. The faster recovery of the US labor market is primarily due to the superior institutional and regulatory performance in the US. These findings provide policymakers with valuable lessons about the importance of continuous monitoring and quick action to mitigate the negative effects of financial instability on economic activity.

Uneven effects of monetary policy: Sectoral disparities in credit card spending

This paper investigates the effects of monetary policy on the credit card spending on different sectors. The investigation is based on a structural vector autoregression model, where sector-specific real credit card spending data (adjusted for inflation) representing an overall country, Türkiye, are used. The empirical results (in the long run) suggest that a positive shock to the monetary policy rate reduces real credit card spending in cars, health, insurance, and shopping in a statistically significant way, whereas it increases real credit card spending on airlines and travel. Monetary policy shocks contribute to the volatility of credit card spending by up to 36% for insurance, 26% for markets and shopping centers, and 22% for travel sectors, whereas this contribution is only about 3% for contractor services and about 4% for car rentals, jewelry, and casino sectors. It is implied that there are uneven effects of monetary policy across sector-specific credit card spendings. These results are robust to the consideration of changes in unemployment rate, inflation rate, nominal effective exchange rate, and the number of credit card transactions as well as alternative model specifications with different numbers of lags, different variables, and different estimation strategies. Important suggestions follow for monetary, fiscal, and macroprudential policies to mitigate the uneven effects of monetary policy across sectors.

Oil price shocks and bond risk premia: Evidence from a Panel of 15 Countries

We study the effect of oil price shocks on bond risk premia. Based on Baumeister and Hamilton (2019), we identify the different sources of oil price shocks using a structural vector autoregressive (SVAR) model of the global market for crude oil. These structural factors are then used as unspanned factors in an affine term structure model based on the representation of Joslin et al. (2014). This is done for a total of 15 countries. Unspanned factors are responsible for most of the variability in bond risk premia for short holding periods, while spanned factors dominate the variance decomposition for longer holding periods. In both cases, global oil supply and global economic activity are clearly the most important unspanned shocks. A historical decomposition around the outbreak of the COVID-19 crisis shows the clear influence of global economic activity shocks during the months of February and March 2020, increasing bond risk premia significantly.

Monetary shocks and house prices in Europe

PurposeThe aim of this study is to analyse the effect of conventional and unconventional monetary policy shocks on housing price dynamics in Europe (2000–2020). We propose a pan-European comparative analysis at a city market level, contrary to the previous literature.Design/methodology/approachWe build a quarterly market dataset for 13 European cities (Paris, Lyon, Marseille, Berlin, Munich, Frankfurt, Amsterdam, Madrid, Barcelona, Seville, London, Birmingham and Manchester). We proceed in two steps. First, we develop a structural VAR (vector autoregression) model. Second, we conduct a forecast error variance decomposition analysis.FindingsWe show that a contractionary policy rate has a negative influence on house prices with relevant differences. A balance sheet shock displays a heterogeneous effect on housing prices. Globally, we observe that a conventional monetary policy shock explains a larger share of total housing price variance than an unconventional monetary policy shock. Finally, our results report that conventional and unconventional monetary policy shocks have a greater impact in more liberalized credit markets.Originality/valueWe develop a pan-European analysis of house prices at a market level for a sample of 13 European cities. A parsimonious structural VAR model is used to study the dynamics of conventional and unconventional monetary policies on house prices in major European markets: Paris, Lyon, Marseille, Berlin, Munich, Frankfurt, Amsterdam, Madrid, Barcelona, Seville, London, Birmingham and Manchester. Our results highlighting the relative importance of conventional and unconventional monetary shocks, identify the existence of heterogeneous effects of monetary policies in European city markets.

주식시장 수익률과 개인 투자자의 매매 성향

This study examines the relationship between individual investors and the KOSPI stock market using long-term data spanning 25 years from 1999 to 2023. However, this study analyzes the relationship between individual investors' net buys and KOSPI returns by dividing the entire period into five sun-periods of five years and applying two-sided regression and structural vector autoregressive (SVAR) models. The main findings are as follows: First, compared to foreign investors, both institutional and individual investors exhibit relatively higher turnover ratios. Second, cross-sectional analysis shows that KOSPI returns decrease monotonically with the individuals' net buys. Third, the results of the two-sided regressions indicate a Granger causality, where past returns negatively influence individual investors' net buys. In addition, today's individual net buys negatively Granger cause future returns. Fourth, the SVAR analysis also shows that KOSPI returns have a strong negative effect on individual net buys. Finally, according to the results of SVAR impulse response function, net buys response negatively to KOSPI shocks, and this response dissipates almost entirely by the third day. In summary, individual investors tend to engage in net selling in response to positive news in the KOSPI market, and this tendency may be a key reason for their lower performance.

This is going to hurt: Weather anomalies, supply chain pressures and inflation

As climate change accelerates, the frequency and severity of extreme weather events are expected to worsen and have greater adverse consequences for ecosystems, physical infrastructure, and economic activity across the world. This paper investigates how weather anomalies affect global supply chains and inflation dynamics. Using monthly data for six large and well-diversified economies (China, the Euro area, Japan, Korea, the United Kingdom, and the United States) over the period 1997–2021, we implement a structural vector autoregressive model and document that weather anomalies could disrupt supply chains and subsequently lead to inflationary pressures. Our results—based on the monthly data and robust to alternative estimation methodologies—show that these effects vary across countries, depending on the severity of weather shocks and vulnerability to supply chain disruptions. The impact of weather shocks on supply chains and inflation dynamics is likely to become more pronounced with accelerating climate change that can have heterogeneous effects. These findings have important policy implications. Central bankers should consider the impact of weather anomalies on supply chains and inflation dynamics to prevent entrenching second-round effects and de-anchoring of inflation expectations. More directly, however, governments can invest more for climate change adaptation to strengthen critical infrastructure and thereby minimize supply chain disruptions.

Determinants of Household and Professional Forecasters’ Inflation Expectations in India

ABSTRACTThis study analyses and compares the determinants of inflation expectations among households and professional forecasters in India. To this end, we utilize quarterly survey data from the Reserve Bank of India (RBI), specifically the Inflation Expectations Survey of Households (IESH) and the Professional Forecasters’ Survey (SPF). The analysis employs a non‐recursive structural vector autoregressive (SVAR) model to explore the relationships between variables. The impulse response function and variance decomposition analysis shed light on the response of inflation expectations to macroeconomic shocks. Our findings indicate that apart from conventional macroeconomic factors like realized inflation and monetary policy, exogenous factors such as oil prices significantly shape inflation expectations. Comparing IESH and SPF, we found out that household expectations are more sensitive to shocks related to food prices, reflecting the influence of food expenses on household decision‐making. Conversely, professional forecasters’ expectations are more influenced by core inflation. Finally, we observed that inflation expectations adjust more quickly than realized inflation in response to macroeconomic shocks, suggesting a leading role. This study is novel with the contribution to the existing literature as it provides a comparative analysis of determinants of inflation expectations between households and professional forecasters in India, while also considering inflation targeting as a significant factor.

Geopolitical risks and energy uncertainty: Implications for global and domestic energy prices

This paper investigates the interaction between global geopolitical risks and global energy uncertainty by focusing on their implications for global and domestic energy prices of 157 countries. The empirical investigation is based on a structural vector autoregression model covering the monthly sample period between 1996 m1-2022m10, where global real economic activity is controlled for. The results show that a unit shock to global geopolitical risk (normalized to one standard deviation) results in about 1.13 units of an increase in global energy uncertainty (normalized to one standard deviation) in the long run (after two years), whereas the corresponding effects on global energy prices are statistically insignificant. In contrast, a unit shock to global energy uncertainty results in about 52 % (57 %) of a reduction in global energy prices (global economic activity), acting like negative global demand shocks. When statistically significant country-specific results are considered in the long run, a positive shock to the global geopolitical risk affects domestic energy prices positively (negatively) in 10 % (10 %) of oil producing countries, 32.1 % (19.7 %) of non-oil producing countries, 47.2 % (0 %) of advanced economies, 55 % (0 %) of euro area countries, 25 % (22.4 %) of emerging markets, and 22.2 % (26.7 %) of developing countries. In comparison, a positive shock to the global energy uncertainty affects domestic energy prices positively (negatively) in 5 % (40 %) of oil producing countries, 3.6 % (54 %) of non-oil producing countries, 0 % (61.1 %) of advanced economies, 0 % (50 %) of euro area countries, 3.9 % (56.6 %) of emerging markets, and 6.7 % (37.8 %) of developing countries. Important policy implications follow regarding the energy security of countries.

Financial and market risks of bitcoin adoption as legal tender: evidence from El Salvador

Bitcoin adoption as a legal tender threatens a financial crisis because of the lack of regulatory frameworks and systems for exchanging Bitcoin into local currencies. This study analyzes monthly data from 2010 to 2022 using a structural vector autoregressive model, estimating Bitcoin’s pass-through into remittance, money multiplier, the US Dollar index, and gold price. The results show that Bitcoin prices decrease the money multiplier and gold prices in both the short and long run, while remittances moderately increase in the long run. The implication of these results suggests the potential for international business opportunities to stimulate the credit, savings, and investment monetary policy channel. The results are robust to alternative SVAR identification strategies.

A Structural Vector Autoregression Exploration of South Africa’s Monetary and Macroprudential Policy Interactions

Interactions between monetary and macroprudential policy are crucial in safeguarding price and financial stability. This study investigates the macroeconomic and financial impacts of monetary and macroprudential policy interactions in South Africa, a leading African economy in developing macroprudential frameworks. The existing literature largely focuses on the effectiveness of these policies independently, leaving a gap in understanding how their interaction affects their overall efficacy. Employing a Structural Vector Autoregression (SVAR) model and utilizing data from 1980 to 2023, this study uniquely incorporates the financial cycle to represent financial developments. The results reveal significant effects of both policies on key variables such as output, the financial cycle, and the price level. Specifically, policy contractions reduce output and the financial cycle but increase the price level, illustrating the ‘price puzzle’. This study further identifies an endogenous response between the two policies: monetary policy reacts by rising to reduce price levels following a macroprudential shock, while macroprudential policy rises to stimulate financial activity after a monetary shock. These findings underscore the importance of using both policies in conjunction but in opposite directions to balance their effects and achieve price and financial stability. This study suggests that an optimal combination of monetary and macroprudential policies is critical for maintaining macroeconomic equilibrium.

Macroeconomic adjustments to Russia–Ukraine war‐induced energy prices shocks in sub‐Saharan Africa: Effects based on countries' resource status

AbstractThe Russia–Ukraine crisis has significantly disrupted global supply chains, leading to sharp oil and natural gas price increases. These energy price surges have impacted productivity in sub‐Saharan Africa (SSA), with potential long‐term effects on purchasing power and economic growth. Additionally, the crisis has highlighted varying impacts of commodity price shocks across the region due to country‐specific conditions, which prompted this study to examine how energy price shocks influence macroeconomic performance in SSA based on countries' resource status. This study utilised a quarterly dataset of macroeconomic variables—real gross domestic product (GDP) (rGDP), inflation and exchange rates—across 21 SSA countries, along with crude oil and natural gas prices. The Bootstrap Granger Causality test confirmed a long‐run relationship between energy prices and these macroeconomic variables. Furthermore, the Panel Structural Vector Autoregressive model demonstrated varying spillover effects based on countries' resource status. The results indicate that resource status significantly affects the magnitude and nature of energy price shocks on macroeconomic variables. Specifically, oil‐rich nations experience the most intense effects, followed by other resource‐endowed countries. These findings offer a nuanced understanding of the complex dynamics triggered by the Russia–Ukraine crisis in the SSA region, highlighting the critical role of resource endowment in shaping economic resilience.

Verbal attacks on terrorist groups increase violence against civilians

Abstract Terrorists and other transnational extremist groups are responsible for thousands of civilian deaths. In confronting extremists, governments have relied heavily on threats, demands, denunciations, and other forms of verbal conflict. Do these efforts at verbal coercion have any effect on terrorist behavior? This analysis focuses on the Islamic State in Iraq and Syria (ISIS), which continues to be the world's deadliest terrorist group and was responsible for recent high-profile attacks in Baghdad, Vienna, Kabul, and Russia. We use Bayesian structural vector autoregression models to analyze daily event data on interactions between ISIS and foreign governments for the 2014–2020 period. We find that verbal conflict initiated by governments not only failed to deter ISIS but in fact increased the frequency of ISIS's attacks on civilians. Additional empirical analyses, combined with evidence from ISIS's publications and public statements, suggest that this effect resulted from a perceived credibility deficit. Extremists use terror attacks to signal that they have the capabilities and willingness to inflict pain and suffering on civilian targets. Government attempts to coerce extremist groups verbally, rather than militarily, reflect an underestimation of the group's capabilities and resolve. In an effort to solidify their reputations, extremists engage in further violence toward civilians, thus leading to worse humanitarian consequences. We extend the analysis to Al-Qaeda in Iraq and Boko Haram and find similar results.

Analysis of the Combined Impact of Socio-Economic Factors on House Price Volatility in the Housing Market

As an important variable in China’s economic system, real estate price is a key point closely linked to the country’s economy and people’s livelihood. It is of great practical significance to study the impact of socio-economic factors in the housing market on China’s house prices and its transmission mechanism, so as to put forward corresponding policy recommendations for stabilizing house prices and preventing real estate market and financial risks. Taking China’s time series data from 2014 to 2023 as a sample, this paper empirically investigates the law of the relationship between socio-economic factors in the housing market and house price fluctuations by constructing a structural vector autoregressive model, and employs impulse response function and variance decomposition to analyze the relationship between the two dynamically. The study shows that the 15-period variance decomposition effect of itself and residents’ disposable income are the main influencing factors of house price fluctuation, and the degree of explanation of its fluctuation is 55.5% and 23.2% respectively. In a market economy, real estate prices fluctuate up and down around their value due to the law of value. Therefore, real estate prices cannot rise indefinitely, and the final result should be stabilized within a reasonable level.

Global economic policy uncertainty and oil price uncertainty: Which is more important for global economic activity?

Using monthly data spanning from January 1997 to November 2022, this paper investigates the influence of global economic policy uncertainty (GEPU) and oil price uncertainty (OPU) on global economic activity using a structural vector autoregressive (SVAR) model. The findings from the baseline model reveal the adverse effects of both GEPU and OPU shocks on the global economy. The counterfactual analysis highlights that the negative impact of OPU shocks primarily stems from direct effects, while approximately half of the adverse impact of GEPU shocks is indirectly transmitted through amplifying OPU. Further examination of the indirect effects of these shocks uncovers that lagged effects primarily drive the indirect impact of OPU, whereas the indirect impact of GEPU is mainly driven by common shocks. These findings suggest a more substantial and independent impact of OPU shocks compared to GEPU shocks. Additionally, employing a time-varying vector autoregressive with stochastic volatility (TVP-VAR-SV) model, this paper explores the same dataset. The results of time-varying impulse responses illustrate a diminishing effect of GEPU shocks over the sample period, whereas the impact of OPU shocks initially decreases before subsequently increasing.

Do petrol prices affect inflation and inflation expectations? Evidence from New Zealand

Due to their high visibility, petrol prices shape households' inflation expectations. This paper investigates the dynamic effects of petrol price shocks on one- and five-year inflation expectations in New Zealand; effects on headline and core inflation are also analyzed. Estimating partially identified structural vector autoregression models using Bayesian techniques, we show that petrol price shocks had a slightly delayed but persistent effect on one-year inflation expectations, whereas five-year inflation expectations were largely insensitive to these shocks. We also show that headline inflation increased immediately in response to petrol price shocks, while core inflation remained unaffected. Counterfactual analysis reveals that inflation and inflation expectations would have been higher in the absence of petrol price shocks during the second half of 2020. The results underscore the importance of petrol prices in influencing households' short-term inflation expectations, offering valuable insights for policymakers focused on managing the cost of living and inflation expectations in New Zealand.