Vector Autoregressive Approach Research Articles

Effects of Global Supply Chain Pressure on Sentiment, Expectation, and Uncertainty: A VAR Approach

This paper studies the relationship of global supply chain pressure with consumer sentiment, inflation expectation, and monetary policy uncertainty in the United States. A sample from January 1998 to January 2024 is used, and this paper uses a Vector Autoregression (VAR) approach based on the method proposed by Toda and Yamamoto (1995). The Granger causality test suggests that the predictions of inflation expectation based on its own past values and the past values of the global supply chain pressure are better predictions of inflation expectation than just using the past observations of inflation expectation. In contrast, Impulse Response Functions suggest that surprise increases in global supply chain pressure lead to increased inflation expectation and monetary policy uncertainty; this shock lasts up to two years. Meanwhile, the Impulse Response Functions suggest that surprise increases in the global supply chain pressure decrease consumer sentiment (confidence), lasting up to two and a half years. Afterward, the impact converges back to zero. Additionally, the Variance Decomposition results suggest that by the final period, the impulses of the global supply chain pressure explain over 22%, 7%, and 44% of the variation of consumer sentiment, monetary policy uncertainty, and inflation expectation, respectively.

Geopolitical Risk and Food Price Inflation: A GVAR Analysis of BRICS and the G7

ABSTRACT We investigate the influence of geopolitical risk on domestic food prices in 12 economies (BRICS and the G7) using a global vector autoregressive (GVAR) approach from 2003M1 to 2022M9. The results show that geopolitical risk shocks cause increases in international prices (oil, agricultural, and general commodity prices). We found that these shocks also provoke fluctuations in domestic food prices. The variance decomposition indicated that international prices and geopolitical risk contribute to the formation of domestic food prices. Finally, the estimates suggest relevant differences between the formation of domestic food prices in BRICS and G7 countries.

Crude oil price behavior and the adoption of sustainable measures in companies before and after COVID-19

The objectives achieved in the Paris Agreement to reduce greenhouse gas emissions and reduce dependence on fossil fuels have caused, in recent years, a growing importance on sustainability in companies in order to reduce Environmental, social and economic impacts. This study is focused on understanding how the variation in West Texas Intermediate crude oil prices affects the Dow Jones Sustainability Index, and therefore the companies included in it, and vice versa. The research aims to examine the statistical properties of both indices, using fractional integration methods, the fractional cointegration vector autoregressive (FCVAR) approach and the continuous wavelet transform (CWT) technique. The results warn of a change in trend, with the application of extraordinary measures being necessary to return to the original trend, while the analysis of cointegration and wavelet analysis measures reflect that an increase in those adopted based on sustainability by the different companies that make up the index imply a drop in the price of crude oil.

Oil price shocks and human capital channels in Nigeria

Nigeria faces persistent challenges of high unemployment and poverty, worsened by its over-reliance on the oil sector. While many studies have investigated the relationship between oil price volatility and human capital development, few have examined how this relationship impacts both basic and advanced human capital channels in developing economies; this study addresses that gap by using a Structural Vector Auto Regression (SVAR) approach to investigate how oil price shocks influence human capital channels. Co-integration tests reveal significant long-term relationships among the variables. For the basic channel, oil price shocks are negatively associated with secondary school enrollment but positively linked to primary school enrollment. In the advanced channel, oil price has a positive effect on government expenditure on tertiary education but negatively affects tertiary institution enrollment. The impulse response function confirms that oil price fluctuations significantly affect both basic and advanced channels of human capital. The findings show the detrimental impact of oil price shocks on Nigeria's human capital development, which may negatively affect sustainable development. The study emphasises the urgent need for economic diversification to reduce the economy's vulnerability to oil shocks and promote long-term growth and human capital development.

Assessing the sovereign-bank interdependence in Eurozone core countries

PurposeThe aim of this study is to determine whether financial contagion is transmitted through macroeconomic fundamentals, not only in weaker countries but also in strong European Monetary Union (EMU) economies.Design/methodology/approachThis study conducts, for the first time, an analysis of the spillover effects resulting from a shock to Italian sovereign risk on the banking systems and credit default swaps (CDS) of five EMU core countries during the period 2012–2018, employing a global vector autoregressive (GVAR) approach. Spatial interdependence is quantified through the cross-country distance in the deficit-to-gross domestic product (GDP) ratio.FindingsThe findings reveal the existence of both a “doom-loop” between banks and sovereign bonds and a “bad neighbours” effect. The susceptibility to spillovers is notably higher in economies displaying a larger deficit-to-GDP ratio. These results suggest that differences in fiscal fundamentals could drive financial contagion even within core countries, indicating a need for evaluating the stability of the entire EMU system.Originality/valueUnlike previous studies, we utilize the cross-country distance in the deficit-to-GDP ratio as a measure of fiscal fundamentals distance for the countries under investigation. To the best of our knowledge, our study is the first to analyse this matter in EMU core countries using a GVAR methodology.

Characterizing the dynamics, reactivity and controllability of moods in depression with a Kalman filter.

Mood disorders involve a complex interplay between multifaceted internal emotional states, and complex external inputs. Dynamical systems theory suggests that this interplay between aspects of moods and environmental stimuli may hence determine key psychopathological features of mood disorders, including the stability of mood states, the response to external inputs, how controllable mood states are, and what interventions are most likely to be effective. However, a comprehensive computational approach to all these aspects has not yet been undertaken. Here, we argue that the combination of ecological momentary assessments (EMA) with a well-established dynamical systems framework-the humble Kalman filter-enables a comprehensive account of all these aspects. We first introduce the key features of the Kalman filter and optimal control theory and their relationship to aspects of psychopathology. We then examine the psychometric and inferential properties of combining EMA data with Kalman filtering across realistic scenarios. Finally, we apply the Kalman filter to a series of EMA datasets comprising over 700 participants with and without symptoms of depression. The results show a naive Kalman filter approach performs favourably compared to the standard vector autoregressive approach frequently employed, capturing key aspects of the data better. Furthermore, it suggests that the depressed state involves alterations to interactions between moods; alterations to how moods responds to external inputs; and as a result an alteration in how controllable mood states are. We replicate these findings qualitatively across datasets and explore an extension to optimal control theory to guide therapeutic interventions. Mood dynamics are richly and profoundly altered in depressed states. The humble Kalman filter is a well-established, rich framework to characterise mood dynamics. Its application to EMA data is valid; straightforward; and likely to result in substantial novel insights both into mechanisms and treatments.

Term structures and firm dynamics: A FAVAR approach

This study employs a Factor-Augmented Vector Auto-Regression approach with Chinese bond markets and aggregated firm-level data to investigate the impact of term structure shocks on firm dynamics and aggregate firm-level variables. We address the potential endogenous issue using a novel instrumental variable based on textual analysis, and find that term structure shocks have long-run and persistent influences on several firm-level outcomes, and that firm dynamics play a critical role in the transmission of term structure shocks.

Time-frequency higher-order moment Co-movement and connectedness between Chinese stock and commodity markets

This study examines the higher-order moment co-movement and connectedness between China's stock and commodity markets across time and frequency domains. We propose wavelet decomposition to develop a multiscale time-varying parameter vector autoregression (TVP-VAR) approach for measuring higher-order moment connectedness. Our empirical findings are as follows: First, the co-movement of stock-commodity varies over time and across different frequencies, exhibiting heterogeneity at different moments. Stocks demonstrate robust co-movement with commodities over the medium- and long-term periods. Second, higher-order moment connectedness is stronger than return connectedness, whereas weaker than volatility connectedness. Finally, higher-order moment connectedness is highly event-dependent, peaking at COVID-19 onset. And long-run factors have the greatest effect on dynamic moment connectedness.

Evaluating the spatial mismatch between population and factor endowments: The case of the European Union

ABSTRACT Considerable research has been conducted on the trade-off between reducing regional inequality and promoting regional growth. However, there is a lack of empirical research exploring the relationship between this trade-off and the spatial mismatch between the distribution of regional populations and the spatial distribution of regional factor endowments. This paper assesses the existence of spatial mismatches between production factors and populations in European regions, with a focus on how these imbalances might affect regional disparities and growth. First, we compute spatial mismatch indices for capital stock and employment in relation to the distribution of population. Second, we use a vector autoregressive (VAR) approach to identify dynamic interactions in the short run. The results indicate that the spatial mismatch between population and labour plays a key role in the trade-off between European economic growth and regional inequality. The findings suggest that eliminating spatial mismatches between the spatial distribution of population and labour could lead to an increase in both economic growth and regional inequality. Moreover, the implementation of regional policies for resource allocation based on population-related criteria does not appear to mitigate regional economic inequality.

Weather-related disasters and inflation in the euro area

This article investigates the impact of weather-related disasters on inflation in the euro area over the period 1996–2021. Using a panel structural vector autoregression approach, we explore whether weather-related disasters have a significant and persistent effect on inflation, as well as the role that demand-side and supply-side channels play as drivers of inflation. We also analyse the heterogeneous effects of inflation on different product categories. Our results suggest that weather-related disasters have a positive, non-persistent effect on inflation. This reflects the prevalence of negative supply shock channels and positive demand shock channels over negative demand shock channels. We also find that weather-related disasters have more pronounced effects on the inflation of product categories that represent a higher proportion of the spending of low-income households, implying that disasters reinforce inflation inequality. Overall, our results suggest that, as the climate crisis deepens, it might become increasingly challenging for the European Central Bank to control inflation and its inequality effects.

Do Political Relations Colour Chinaʼs Trade With Southeast Asian Partners? A Vector Autoregression Approach

Do Political Relations Colour Chinaʼs Trade With Southeast Asian Partners? A Vector Autoregression Approach

Exploring the Interrelationship between Scientific Knowledge and Economic Growth in Serbia: Empirical Insights

The primary objective of this study is to examine the nature of the relationship between the production of scientific knowledge and economic growth in Serbia during the period 1996-2022. For this purpose, the Vector Autoregression approach, along with the impulse response function and forecast error variance decomposition, was employed. Results suggest an impact of economic growth on the production of scientific knowledge, while no impact in the opposite direction is detected. The Serbian government should persist in investing in science and work closely with the scientific community to overcome barriers to scientific knowledge's full contribution to economic prosperity.

Islamic cryptocurrency integration for enhanced sustainable finance: evidence from time-frequency volatility transmission investigation

ABSTRACT This study explores the potential of Islamic gold-backed cryptocurrencies in sustainable finance by focusing on volatility transmission between these cryptocurrencies and conventional digital assets like Bitcoin and PaxGold. Using a Time-Varying Parameter Vector Autoregression (TVP-VAR) approach, we analyze data from December 2019 to July 2023, including the COVID-19 pandemic period. Findings reveal a complex volatility network, with Bitcoin and HelloGold as major transmitters of spillover shocks, while X8X and PaxGold mainly serve as net recipients. Notable interactions between Bitcoin and Islamic gold-backed cryptocurrency markets show short-lived pairwise volatility interactions. Islamic gold-backed cryptocurrencies, net recipients of volatility, absorb market shocks, making them suitable for hedging against volatility. This can aid in diversifying portfolios, mitigating adverse market impacts, and informing risk management and regulatory approaches. Our research emphasizes the importance of Islamic finance in ethical and sustainable investment within the evolving cryptocurrency market.

Dynamic interactions between intellectual capital elements and productivity in the korean manufacturing industry: a panel vector autoregressive approach

Dynamic interactions between intellectual capital elements and productivity in the korean manufacturing industry: a panel vector autoregressive approach

Do climate change risks affect the systemic risk between the stocks of clean energy, electric vehicles, and critical minerals? Analysis under changing market conditions

This paper analyzes the impact of climate change risks—specifically from natural disasters, global warming, international summits, and U.S. climate policy—on the return connectedness (systemic risk) of a network consisting of the stocks of clean energy, electric vehicles, and critical minerals in bear, bull, and normal market conditions. Employing a quantile vector autoregression (QVAR) approach, we find significant temporal variations in the total connectedness index, with notable spikes during the COVID-19 pandemic and the Russia-Ukraine war. Total connectedness is higher but less variable under bear and bull market conditions. Concerns about global warming has a positive and significant impact on systemic risk during bear and normal market conditions while international summits have a negative impact during normal market conditions. However, the effects of these climate change risks are small in magnitude. Economic policy uncertainty and stock market volatility have the largest positive impacts on systemic risk under most market conditions. Our results reveal a nonlinear (inverted U-shaped) relationship between variable importance and systemic risk quantile, showing that the impact on connectedness is largest in magnitude under normal market conditions.

Macrofinancial interconnections in the Pacific Alliance: a quantile approach of stock markets and macroeconomic factors

ABSTRACT This study explores the macrofinancial interconnectedness within the Pacific Alliance (Chile, Colombia, Mexico, and Peru) by utilizing a Quantile Vector Autoregression (QVAR) approach to dissect the directional spillover effects between macroeconomic variables and MSCI stock indices. By employing autoencoder techniques for dimensionality reduction, the research decodes significant macroeconomic dimensions influencing stock market behaviours. The findings show patterns of spillover effects, highlighting the variable roles of these economies as transmitters and receivers of economic shocks, particularly after the Pacific Alliance agreement.

The Impact of Tax Pressure on Long-Term Economic Growth in Morocco

Despite the tax reform in the 1980s, the Moroccan tax system still suffers from structural vulnerabilities that have led to inefficient tax policies and increasing sectoral disparities, which have led to an increase in the tax pressure rates between 1990 and 2020. To overcome these vulnerabilities, and according to the recommendations of the 2019 National Tax Conference, the Moroccan tax system has been recently restructured, with the aim of strengthening the principles of equity and tax efficiency. The main objective of this paper is to determine the impact of the tax pressure on long-term economic growth in Morocco from 1990 to 2020. To do so, the methodology adopted in this work consists of verifying the effect of the tax pressure on economic growth through a quantitative methodology based on two vector autoregression approaches: the vector autoregression model (VAR) and the vector error correction model (VECM). The results of this study confirm that the effect of fiscal pressure on economic growth in Morocco is not significant in the long run, and therefore, we can deduce that taxation is not yet a well-mastered instrument for the state to act on the economic sphere. The results show a complex relationship between tax pressures and economic growth in Morocco, underlining the importance of tax reform. However, the research is limited by the specific models and the need to explore other determinants. The contribution of this paper lies in its in-depth empirical analysis of fiscal pressure and its influence on long-term economic growth in Morocco, as based on VAR and VECM modeling. This econometric approach makes it possible to isolate the dynamic effects and responses of economic variables over time, offering an understanding of the interactions between tax policy and long-term economic growth. By focusing specifically on the Moroccan context, this study offers an original perspective and helps to fill the gap in the empirical research in this area while providing a valuable analytical framework for assessing fiscal policies and their impact on long-term economic growth.

The Effect of Crime on Foreign Investment and Economic Development in Sub-Saharan Africa: A Panel Data Analysis

This study investigates the effect of crime on economic development in 22 sub-Saharan African countries between 2000 and 2020, using data from global sources. The study utilized a panel vector autoregression (VAR) approach to analyze the dynamic correlations between variables. This was achieved through the examination of impulse response functions and error variance decomposition. The study established a definitive cause-and-effect connection between the crime rate and growth indicators. The panel vector autoregression (VAR) technique resolves the issue of endogeneity by permitting endogenous interaction among the variables in the system. The findings indicate that the crime rate has a significant effect on economic growth in sub-Saharan countries, though with very low magnitude. The economic prosperity of most sub-Saharan African countries may be attributed to the abundant availability of natural resources in the region. The causality test findings indicate a diverse causal connection between the crime rate and growth indicators. While there is no direct causal relationship between economic growth and the crime rate, there is a one-way causality between economic growth and foreign investment. This means that economic growth can enhance foreign investment, suggesting that in sub-Saharan countries, economic growth plays a crucial role in improving foreign investment. However, as indicated by the findings, there exists a bidirectional causal relationship between foreign investment and crime rates. In summary, it is clear that the crime rate in sub-Saharan African nations has a significant impact. In the future, countries with higher crime rates are likely to see slow economic growth and less foreign investment.

Conflict or coordination? The cross-departmental interaction in local environmental governance of China

Organizational coordination has been regarded as a vital factor to determine the environmental governance efficiency of local authority, while existing empirical studies mainly discuss the vertical decentralization but largely ignore the horizontal cross-departmental interaction within single government. Based on the data of 31 Chinese provinces from 2003 to 2017, this paper uses a panel vector autoregression (PVAR) approach, two-way fixed-effect models and dynamic panel regression with system generalized method of moments estimation (SYS-GMM) to investigate the environmental strategic interaction between two representative departments (finance department and environmental protection department) within local governments. The results indicate, on the whole, their environmental governance strategies show a significantly co-directional coordination. However, the cross-departmental interaction obviously varied in different periods and regions (even showed as conflict sometimes), and was synchronized with the dynamic trade-off between economic and environmental targets of China. This research helps understand the inner logic of environmental governance of Chinese government, and can be valuable guidance for other countries to accomplish multi-departmental sustainable development goal.

Dynamic Returns Connectedness: Portfolio Hedging Implications During the COVID‐19 Pandemic and the Russia–Ukraine War

ABSTRACTWe apply a Time‐Varying Parameter Vector Auto Regressive (TVP‐VAR) connectedness approach on global assets to investigate time‐varying dynamic connectedness, portfolio performance, and hedge effectiveness during COVID‐19 and the Russia–Ukraine war. With increased connectedness and the changing role of energy and soft commodities during these two events, we find the minimum correlation (connectedness) portfolio performing better during COVID‐19 and the Russia–Ukraine war and that cumulative returns of portfolios are higher during COVID‐19. Additionally, we find varying (stable) hedge effectiveness of equity market indices and soft commodities (cryptocurrencies). This paper provides specific insights to investors about using optimal portfolios and hedging during pandemics and military conflicts.