Vector Autoregressive Approach Research Articles

Defence Partnerships and Economic Dynamics: An Analysis in PESCO Countries

ABSTRACT This paper employs a panel vector autoregressive (PVAR) approach to investigate the relationship among military expenditure, investment, and economic growth, over the period after the enforcement of the Maastricht treaty (1994–2022) in 25 European countries that participate in the Permanent Structured Cooperation (PESCO). By using the Louvain community detection algorithm on the network links that have been established through defence partnerships in PESCO projects, two different country clusters emerge. Findings suggest that military expenditures can stimulate economic growth but the effects may not be common for all Member States, which might benefit from the involvement in joint defence projects to maximize the effectiveness of their defence spending.

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.

Oil Prices and Expectations: A Quantile Structural VAR Approach

Using a quantile structural vector autoregressive (QSVAR) approach, this study examines oil price reactions to consumer and business expectations. Unlike mean-based structural VARs, QSVAR analyses the full response distribution after an expectational shock. Findings indicate that the impact of expectation innovations on oil prices varies by quantile and agent. Positive business expectations increase oil prices via commodity demand, while consumer optimism mainly affects low oil prices. These insights aid policymakers in grasping how different agent expectations shape oil price distribution.

Green horizons: Enabling the energy transition through climate change policies

In response to the goals set by the COP21 Summit, the challenges brought about by the COVID-19 pandemic, and the ongoing conflict between Russia and Ukraine, this study aims to develop an effective policy framework to support the transition to sustainable energy. This framework considers key elements such as managing energy risks, leveraging green finance, navigating carbon markets, and evaluating three climate change policy indicators: the impact of climate change summits (CCS), government climate programs (CCGP), and climate change taxation (CCT). Utilizing the Quantile Vector Autoregressive (QVAR) approach and analyzing monthly data from the United States from August 1, 2014, to August 30, 2022, our research examines the influential role of these climate policy indicators. The results show that climate summits, governmental initiatives, and climate taxes are significant influencers, affecting both renewable and conventional energy sectors, carbon market movements, and green finance. The study underscores the importance of government initiatives and climate policies in driving the transition to renewable energy and fostering environmentally sustainable financial activities. Focused on advancing Sustainable Development Goals 7 (Affordable and Clean Energy) and 13 (Climate Action), this research contributes to shaping effective policy frameworks and enriching policy debates on sustainable energy transition.

UNVEILING THE IMPACT OF GEOPOLITICAL RISKS ON TURKISH ECONOMY AND FISCAL DYNAMICS

This research aims to examine the impact of geopolitical risks on Türkiye's trade openness, household consumption, investment, government debt, and budget deficit for the quarters 2006:I–2022:IV. There are no empirical studies in the literature that examine the relationship between geopolitical risks and Turkish fiscal policy. The vector autoregressive (VAR) approach is utilized to examine the relationships among the variables. Geopolitical risks contribute to a very serious increase in inflation in Türkiye. The increase in geopolitical risks negatively affects consumption and investment and increases budget deficits and government debt. Additionally, Türkiye's trade volume has also decreased as a result of rising geopolitical risks, according to the VAR model's results. These findings demonstrate how vulnerable the Turkish economy is to geopolitical risks. Succinctly, Türkiye's public finances and economy are negatively impacted by geopolitical risks according to the analysis's findings. As a matter of fact, taking precautionary fiscal policy measures against geopolitical risks is important in eliminating the fiscal and economic losses that may arise. In this respect, this study has the potential to make a new contribution to the fiscal policy literature and to guide fiscal policy makers.

Should Monetary Policy in South Africa Lean against the Wind by Targeting the Financial Cycle?

Recently, several studies have argued about the interactions of the real economy and financial system, as well as the importance of financial cycles in business cycle fluctuations. To date, there exists near consensus among central bankers, economists, and other scholars that the financial cycle is an important source of business cycle fluctuations. This has raised the question of whether monetary policy should respond to financial instability and/or imbalances. As a result, we asked the following questions: Should monetary policy lean against the wind by targeting the aggregate financial cycle in South Africa? And what is the role of monetary policy in minimizing financial imbalances and instabilities in South Africa? The present article aims to provide answers to the above-mentioned question. Through the adoption of a multiple-equation generalized method of moments and structural vector autoregressive approaches, this article simultaneously estimates and compares both the finance-augmented and the conventional Taylor rules. It is shown that the South African Reserve Bank has considered developments in the aggregate financial cycle in setting its policy rate. Overall, there is clear evidence to conclude that the South African Reserve Bank can lean against the wind by targeting the aggregate financial cycle, but only as a genuine augmentation not as a fully flagged objective. This article adds new evidence to the South African literature on the prevailing debate of whether monetary policy should respond to developments in the financial system.

Connectedness Between Gold-Backed Cryptocurrencies and the G7 Stock Market Indices During Global Crises: Evidence From the Quantile Vector Autoregression Approach

Connectedness Between Gold-Backed Cryptocurrencies and the G7 Stock Market Indices During Global Crises: Evidence From the Quantile Vector Autoregression Approach

Spillover dynamics in DeFi, G7 banks, and equity markets during global crises: A TVP-VAR analysis

Decentralized finance (DeFi) has become of significant interest for investors in both the financial and digital sectors. We use a time-varying parameter vector autoregression (TVP-VAR) approach to estimate the static and dynamic connections between and within DeFi, G7 banking, and equity markets. We focus on critical events such as the COVID-19 pandemic, the cryptocurrency bubble, and the Russia-Ukraine conflict. The results highlight interconnectedness and significant spillovers within and between the markets, especially during the COVID-19 pandemic. Notably, there were significant spillover effects from the G7 banking and equity markets to Japan and DeFi assets. The findings demonstrate a robust connection between DeFi platforms, G7 banking, and stock markets throughout these tumultuous periods. Policymakers, investors, and entrepreneurs are recommended to keep a close eye on changes in traditional banking and equity markets to adjust the risk of DeFi assets.

Exchange rate, external reserves and current account balance nexus in oil-dependent countries: A Toda-Yamomoto-based Panel Vector Autoregressive (PVAR) approach

The international monetary authorities have been consistently advising oil-dependent countries to change their exchange rate policy from a fixed to a floating exchange rate regime. While some of these countries including Nigeria have announced their adoption of a free-floating exchange rate system, evidence shows that the majority are suffering from “fear of floating”, hence operating an abridged exchange rate system. This study employs the Toda-Yamomoto-based Panel Vector Autoregressive (PVAR) model to use the causality approach to determine the exchange rate system that best explains the de facto exchange rate policy system operating in these countries. This is explained by the dynamic causality between exchange rates and foreign reserves. The dynamic causality between the exchange rate and current account balance also explains the potential effect of devaluation to improve the external trade balance, which implies the J-curve and Marshall Lerner condition. The results show that there is no significant causality from foreign reserves and trade balance to the exchange rate, suggesting that oil-dependent countries are more aligned to a fixed exchange rate regime than a floating exchange rate regime. We also find significant negative causality from the exchange rate to foreign reserves, while foreign reserves have a positive causal effect on the current account balance. This implies that the expected devaluation gains that may be prompting oil-dependent countries to stick to fixed exchange rate regimes are not there, as currency devaluation tends to worsen trade performance and foreign reserves rather than improve them. While oil-dependent countries are not benefiting much from a fixed exchange rate system, it is recommended that appropriate policy to boost private sector generation of foreign exchange should be put in place before the adoption of a full-fledged floating exchange rate system.

Revisiting the role of climate change on crop production: evidence from Mediterranean countries

AbstractThe Mediterranean region is an important agricultural center and is expected to be most affected by climate change due to its location. In this study, the role of climate change on agriculture is examined for eight South European countries on the Mediterranean coast for the period of 1996–2016. Carbon dioxide emissions, temperature and precipitation values are used as the indicators of climate change while cereal production is taken as a proxy for agricultural production. Results of the panel vector autoregression approach reveal that an increase in the carbon dioxide emissions and temperature have a negative impact on the cereal production. However, this effect is statistically significant only in the initial periods. On the other hand, an increase in rainfall has a statistically significant positive effect on crop production only in one period. However, eventually this effect turns to negative as expected, since excessive rainfall has a negative effect on agriculture as much as drought. In conclusion, the importance of bringing the policies and strategies to the forefront in ensuring the sustainability of agriculture and minimizing the negative effects of climate change in the region are discussed.

The role of environmental tax on the environmental quality in EU counties: evidence from panel vector autoregression approach

This study intends to analyze the influence of environmental taxes on pollution in EU-27 nations. Furthermore, energy from renewable sources consumption and urbanization are employed to clarify CO2 emissions in this study that tests the EKC hypothesis. According to the findings, an increase in environmental taxes reduces CO2 emissions by 0.14%. Also, the data supported the validity of the EKC concept. The findings of the causality test demonstrated that there is a bidirectional causal link between CO2 emissions and environmental taxes. These results reflect that environmental tax revenues contribute to sustainability as an effective policy tool in EU countries. Policies regarding environmental tax enforcement come to the fore in terms of both keeping the balance in economic activities and serving sustainability.

The role of artificial intelligence and fintech in promoting eco-friendly investments and non-greenwashing practices in the US market

This study explores the intricate connections among financial technology (FinTech), artificial intelligence (AI), and eco-friendly markets in the US, shedding light on their dynamic interplay and implications for sustainable investment and policy strategies. Specifically, our research delves into the transformative roles of FinTech and AI in broadening financial access, fostering green financing initiatives, and aligning financial practices with environmentally conscious objectives. We also investigate market reactions among the AI, FinTech, non-greenwashing, and eco-friendly markets during exogenous shocks, offering valuable insights into these markets' interconnectedness. An innovative connectedness approach, the R2 decomposed measures, is employed to capture the contemporaneous and lagged spillover effects using daily data from December 19, 2017, to November 1, 2023. We also focus on constructing a minimum connectedness portfolio using the time-varying parameter vector autoregressive approach. The findings reveal significant volatility connectivity within these intergroups, emphasizing the need for sustainable tech finance policies and real-time monitoring systems to address market fluctuations. Overall, this study contributes to an underexplored area by providing empirical evidence and valuable implications for scholars and policymakers, and can help in guiding sustainable investment and policy strategies aligned with zero-emissions agendas.

Output, employment, and price effects of U.S. narrative tax changes: a factor-augmented vector autoregression approach

Output, employment, and price effects of U.S. narrative tax changes: a factor-augmented vector autoregression approach

Dynamic connectedness, portfolio performance, and hedging effectiveness of the hydrogen economy, renewable energy, equity, and commodity markets: Insights from the COVID-19 pandemic and the Russia-Ukraine war

This study employs a Time-Varying Parameter Vector Auto Regressive (TVP-VAR) connectedness approach to investigate the dynamic interconnections, portfolio performance, and hedging effectiveness across hydrogen economy, renewable energy markets, equities, and energy commodities amidst the backdrop of the COVID-19 pandemic and the Russia-Ukraine conflict. Our findings reveal a consistent level of average connectedness during both black swan events, with dynamic connectedness reaching its peak during the COVID-19 crisis. While some assets (hydrogen economy index, renewable, solar and clean technology index) persistently function as net transmitters, the others (geothermal index, crude oil, natural gas, biofuel, and gold) consistently act as net receivers. We also find that the role of equity indices (wind energy, fuel cell, FTSE_100, and S&P 500) as net transmitters or receivers changes over time. The network plot results show that the hydrogen economy typically functions as shock transmitters for equity market indices and commodities. Portfolio analysis underscores the superior risk-adjusted performance of the minimum variance (connectedness) portfolio during the COVID-19 crisis in comparison to the Russia-Ukraine conflict. Furthermore, our examination of effective hedge and portfolio strategies demonstrates that managed collateralized portfolio weights of hydrogen economy and renewable energy assets (equities) in the minimum variance portfolio increase (decrease) from 7% to 12% (53%–41%) during the COVID-19 crisis, and subsequently decline (rise) further to 6% (53%) amidst the Russia-Ukraine conflict. These findings suggest a preference for hydrogen economy and renewable energy assets as hedging instruments in health-related financial crises over crises precipitated by military conflicts.

Macroeconomic impacts of monetary and fiscal policy in the euro area in times of shifting policies: A SVAR approach

This paper analyses the impacts of monetary and fiscal policy of the euro area on output and inflation between 2005 and 2022 using a structural vector autoregressive (SVAR) approach. We employ three alternative indicators of monetary policy, alongside government spending and revenue as fiscal variables to estimate the effects across different subperiods. The findings reveal that monetary policy tightening produces a negative and delayed effect on both output and inflation, with the effects differing across alternative monetary policy indicators in terms of duration and magnitude. A fiscal revenue shock is found to be inflationary, whereas a fiscal spending shock initially has a negative effect on growth that later turns positive, but is short-lived. The effects of fiscal policy shocks are more substantial than the effects of monetary policy shocks. The results also suggest that the effects may differ across subperiods, depending on the nature and intensity of the policy shifts.

ANALISIS TRANSMISSION OF MONETERY POLICY TERHADAP PERTUMBUHAN EKONOMI DAN KEUANGAN PASCA PEMULIHAN EKONOMI IN FIVE APEC COUNTRIES

The aim of this research is to determine and investigate how the global economic crisis in 2020 affected financial and economic growth after the Covid-19 crisis and the economic recovery that followed. Secondary data covering the period 2013 to 2023 was used in this research. Money supply, real interest rates, exchange rates, investment, inflation, and gross domestic product are the variables taken into account. This research examines the short-term and long-term impacts of monetary policy on financial and economic growth in five Asia Pacific Economic Cooperation (APEC) countries using the Structural Vector Autoregressive (SVAR) approach. Three variables investment, reallinteresttrates, and moneyxsupplyido not significantly influence1economicxor financial growth, according to the study's findings, while two variables inflation and exchange rates have a positive impact on economic and financial growth.

Extreme connectedness between cryptocurrencies and non-fungible tokens: portfolio implications

We analyze the connectedness between major cryptocurrencies and nonfungible tokens (NFTs) for different quantiles employing a time-varying parameter vector autoregression approach. We find that lower and upper quantile spillovers are higher than those at the median, meaning that connectedness augments at extremes. For normal, bearish, and bullish markets, Bitcoin Cash, Bitcoin, Ethereum, and Litecoin consistently remain net transmitters, while NFTs receive innovations. However, spillover topology at both extremes becomes simpler—from cryptocurrencies to NFTs. We find no markets useful for mitigating BTC risks, whereas BTC is capable of reducing the risk of other digital assets, which is a valuable insight for market players and investors.

Aversion and ambiguity: On the robustness of the macroeconomic uncertainty measure framework

The economic literature has focused on the role of uncertainty in the real economy, employing both measures of risk aversion and ambiguity aversion in structural models. In this connection, concerns about the measures for VIX and EPU, have been raised about whether or not they both measure and identify similar type of uncertainty. Using a structural vector autoregressive (SVAR) approach, we examine the relationship between VIX and EPU, their impact on the real economy and whether, and under which conditions, they can be distinguished between measures of risk aversion and ambiguity aversion. Specifically, we analyse the impact of uncertainty shocks of VIX and EPU on the industrial production, unemployment, and consumer credit in the US. Our main finding is that given their fundamental differences, the two measures are capturing different dimensions of uncertainty, VIX is a measure of risk aversion and EPU is a measure of ambiguity aversion. As such, our results are very important in terms of trading decision strategies to be implemented by investors and portfolio managers as it may help explain the two central behavioral traits affecting economic lifecycle problems, such as production, unemployment and consummation.

Fiscal and Monetary Policy Interaction Post Indonesian Institutional Transformation: Vector Autoregression Approach

Fiscal and Monetary Policy Interaction Post Indonesian Institutional Transformation: Vector Autoregression Approach

What drives currency connectedness? Evidence from the BRICS currencies

ABSTRACT With the rapid growth of the BRICS countries, their currencies have attracted wide attention. This study examines the dynamic connectedness of BRICS currencies and identifies the drivers of currency connectedness using a time-varying vector autoregressive (VAR) approach and a modified dynamic model averaging method. Our results indicate that dramatic changes in the currencies’ total and net connectedness are related to influential economic, financial, and political events. ZAR is a consistent net transmitter, INR and CNY are consistent net recipients, whereas BRL and RUB switched roles frequently. The risk and uncertainty indices, especially the VIX and SKEW, were the most pronounced drivers affecting the total and net connectedness among the selected drivers. The remaining factors (i.e. commodity prices, asset markets, and leading global currencies) generally had limited effects but played important roles in certain influential events.