Impulse Response Analysis Research Articles

Sounds from a Mountain. Acoustics at La Peña de los Enamorados (Antequera, Spain), a Neolithic sanctuary

La Peña de los Enamorados, a limestone massif located in Antequera, Spain, is a famous landmark since (at least) the Middle Ages on account of its marked anthropomorphic silhouette and geographic position right at the crossroads of Andalucía’s two main communication routes (connecting Málaga and Córdoba, in a South-North direction, and Sevilla and Granada in a West-East direction). In the last fifteen years, archaeological research has revealed substantial evidence of intense Late Neolithic, Copper Age and Early Bronze Age activity (spanning from the mid-4th to the early 2nd millennia BC) on its northern sector. This includes various loci of activity: (i) the Matacabras shelter, with schematic-style rock art, which is located at the foot of Tajo Colorado, a 100 m-high rocky wall that forms the mountain’s ‘chin’; (ii) the recently discovered Piedras Blancas megalithic grave; (iii) and several remains of activity, including Locus 4, on the steep glacis at the foot of Tajo Colorado. In this paper, we examine the acoustic behaviour of Tajo Colorado, Matacabras and Locus 4. Signals produced by means of a blank-shot pistol were recorded at each reception point by means of a high-quality audio recorder via a microphone condenser mic while controlling background noise levels. The study included impulse response analysis based on its temporal and frequency behaviour, through Schroeder decay curves, Envelop-Time Curves, spectrograms and spectrum curves. The results show good acoustic conditions, not unlike some ancient theatres, which reinforces the interpretation of the area as a major Neolithic open-air sanctuary.

Investigating the dynamics of crude oil and clean energy markets in times of geopolitical tensions

This study examines how adverse geopolitical events influence the dynamics of crude oil and clean energy markets. A vector smooth transition regression model is implemented to capture the presence of regime shifts due to geopolitical conflicts. The impulse response analyses reveal that the crude oil market is non-responsive to all geopolitical events. A significant spike in oil prices arises only if risks associated with geopolitical tensions surpass a certain threshold level. The green equity market responds differently, showing an adverse reaction during episodes of higher geopolitical uncertainty. Moreover, our empirical results point out a decoupling between traditional and clean energy sectors in times of geopolitical stress. Our findings contrast with the conventional wisdom that a surge in oil prices would foster a shift toward alternative energies. While the observed disconnection would offer better diversification benefits, it is challenging for policymakers to encourage investors to maintain low-carbon portfolios.

The impact of international commodity price shocks on macroeconomic fundamentals: Evidence from the US and China

In light of the increased volatility in international commodity markets, we aim to investigate the effects of international commodity price shocks on the macroeconomic fundamentals of the United States and China. We expand upon existing literature by employing the Dynamic Hierarchical Factor Model (DHFM) to analyze commodities across different sectors. This approach allows us to uncover the heterogeneity and specific synergies among various commodity categories. Furthermore, we construct the Factor Augmented Vector Autoregression Model (FAVAR) and the Time-varying Parameter FAVAR model, utilizing the common factors extracted and monthly data on fundamental macroeconomic variables from the US and China. By conducting impulse response analysis, we empirically demonstrate the impact of international commodity price shocks on key macroeconomic indicators, including industrial production, CPI, interest rates, stock prices, and exchange rates. Moreover, we provide evidence that these impacts exhibit significant variations over time, particularly in response to major global events such as the 2008 Global Financial Crisis, the 2020 COVID-19 pandemic, and the 2022 Russia-Ukraine conflict crisis. Our findings yield valuable insights for investors, researchers, and policymakers seeking to understand the influence of international commodity prices on macroeconomic conditions.

Analysis of the Impact of Aging on Factors Affecting Economic Dynamism

Population aging is one of the biggest demographic challenges facing China in the 21st century. Its impact on the economy cannot be ignored. This study employs empirical research to illustrate how population aging affects China's economic development. It is mainly explained from the perspectives of the labor force, savings rate, GDP, and pension insurance participation. According to the relevant data and the definition standard of the United Nations on aging society, the relevant data from 2002 to 2020 are selected for empirical analysis. The conclusion is obtained through the ADF test, determination of optimal lag order, the AR characteristic root test, and impulse response analysis. The results display that from the perspective of GDP and savings rate, population aging has an inhibitory effect on the economy, and has a lasting negative impact on the labor force. These results suggest that some measures should be taken to deal with the effects of aging in order to counteract its negative impacts on the economy and society.

The Dynamic Relationship between the NFT Index and Macroeconomic Factors in Korea

Purpose – This study attempts to analyze the dynamic relationship between the NFT index and macroeconomic factors, and make effective suggestions using research methods in the field of management finance. Design/Methodology/Approach – The study sample was from January 2020 to March 2023. The variables used in the analysis were based on monthly time series data, measured on the basis of the Metaverse–NFT Index (MVNX) index released by Wavebridge Limited in Korea to reflect the growth trend of the NFT market, money supply, US dollar–won exchange rate, gross domestic product, consumer price index, and other macroeconomic indicators. The analytical tools in this study included a unit root test based on the VAR model, the Johansen cointegration Test, Granger causality test, impulse response analysis, and variance decomposition. These methods are very effective in analyzing time series data. Findings – The results of the analysis show that macroeconomic factors, such as money supply, exchange rate, GDP, and consumer price index are important sources of information in predicting the NFT index. Research Implications – The results of this study are expected to provide practical information for NFT users, virtual asset trading platforms, investors, and policymakers related to NFT ecology. Furthermore, this study’s findings are of great significance, being the first global study to explore the relationship between NFTs and macroeconomic factors.

The Vertical Price Transmission in Pork Meat Production in the Czech Republic

The paper aims at vertical price transmission of the agri-food market in the Czech Republic. It is focused on the analysis of price transmission in pork meat by investigating the short-run and long-run relationships within the product and the speed of establishing the equilibrium relationship. For this purpose, there is employed specially VECM (Vector Error Correction Model), impulse-response analysis, and decomposition of variance of VECM, which show the system’s reaction. The applied approach considers five alternatives in the Johansen approach. The results suggest that there is an existence of the equilibrium relationship in vertical markets and this relationship is simultaneous and demand-driven. The impulse-response analyses show the response of the processing price to one standard deviation shock to the agriculture price from approximately 15–20 periods reaching long-run equilibrium. The response of the agriculture price to one standard deviation shock to the processing price reaching long-run equilibrium is also from approximately 15–20 periods.

Analysis of the Correlation between Gold-Oil Ratio and Capital Market

Based on the phenomenon that the ratio of gold to oil soared to 200, this paper selects the CSI 300 index and the S&P 500 index as the representatives of the Chinese and American capital markets, respectively. Specifically, VAR model is used for empirical analysis. Through unit root test, confirmation of lag order, impulse response analysis and Granger causality test, it is concluded that there exists a correlation between gold-oil price and Chinese and American capital markets. At the same time, the fluctuation of gold - oil price has a hysteretic effect on Chinese and American capital markets. Therefore, investors can predict the risks of the capital market according to the fluctuation of the ratio of gold to oil, so as to formulate or change the investment strategy to reasonably avoid risks.

An empirical study on the economic linkage characteristics of Yangtze River port cities based on discrete second-order derivatives

Abstract Rapid economic development cannot be achieved without a well-developed trade in goods of various forms, so it depends on the construction and development of coastal or inland ports. How to coordinate the relationship between ports and cities in the development process is of great significance to the sustainable development of port cities, and is also an important part of the current research on ports. This paper uses gray correlation model to study the correlation between city economic development indexes and port development indexes, and finds that the correlation between GDP and gross industrial output value and port cargo throughput is the largest, and on the basis of gray correlation analysis, the impulse response analysis finds that the growth of total economic volume and gross industrial output value of port cities has an obvious promotion effect on the development of ports in the short term. The research results show that the value added of Nanjing’s tertiary industry drives the port logistics of Nanjing port most significantly; the growth rate stabilizes at 0.006 after the 11th period. The growth of Nanjing port container throughput on the value added of Nanjing’s secondary industry changes most significantly and finally stabilizes at 0.0035.

Exploring the impact of online news sentiment and relevance on stock market risks: A signalling theory perspective

AbstractBased on the frame theory and signalling theory, this article uses financial technology (fintech) to analyse online news sentiment and proposes the relevant hypothesis of the influence of news relevance on stock market risk, and conducts an empirical study on the VAR model of the stock return rate by using the news relevance and news sentiment data of the Uqer database. The results show a two‐way Granger causality between news sentiment and stock returns. News relevance is not Granger causality of yield but Granger causality of news sentiment. In addition, combined with the impulse response, variance decomposition, and relevance analysis, it is found that the news relevance degree positively affects news sentiment and then indirectly affects the stock return rate. Our findings indicate that news relevance is an essential variable in analysing online text sentiment and stock market volatility, and online news will increase the volatility of stock market risk. These results contribute to the financialization literature and guide fintech enterprises to balance market risk by combining signalling and frame theory to improve news relevance.

Differences in impact of official development assistance on foreign direct investment by aid types

This study examined the impact of Official Development Assistance (ODA) on Foreign Direct Investment (FDI) by aid type, which has been largely overlooked in previous studies. Using the Generalized Method of Moments with a gravity model, five major donor countries (France, Germany, Japan, the United Kingdom, and the United States) and 63 recipient country pairs from 1996 to 2020 were analyzed. Granger causality tests, impulse response analyses and variance decomposition analyses using a panel vector autoregressive model were conducted to identify causal relationships in the time series and to quantitatively capture the impact. The results suggest that ODA Loans from Germany, Japan, and the United Kingdom promote FDI. Their ODA Loans have a high proportion of economic infrastructure and productive-sector support. Hence, their ODA Loans may attract FDI to recipient countries by developing infrastructure in recipient countries such as transportation, telecommunications, energy, and finance. This study contributes to an academic community by highlighting the differences of aid type in attracting FDI and provides practical implications for policymakers and practitioners in the field of international development.

Regime Change Operation in Pakistan: Examining Yield as a Behavioral Pattern of Microblogging rumors during the Political-Obsessed Period

<p><big>In the behavioral domain, this study discloses the pattern between microblogging-opinionated information and yields on the investment. This phenomenon is particularly related to the political instability in the Pakistan’s economy through the multivariate techniques. Pre-political crisis, the pessimistic sentiments were priced in yields on the investment. In environments of political instability, the intensity of decline in yields was more responsive against an incline in the negative opinions. Meanwhile, the intensity of increase in returns was less responsive against an incline in the positive opinions. The findings were further supported by the Bayesian approach. Before the political instability takes place in the Pakistan’s economy, the occurrence of yields was noted in response to the bearish market period. Post-political instability, there was a higher posterior probability for occurrence of returns against the bearish market period. Conversely, a higher posterior likelihood was noted for occurrence of investment’s yields in response to the bullish market period, but this relevance was not completely probable. From the impulse response analysis, the response of returns was reported against the standard deviation shocks in the microblogging sentiment indicators. The analysis may have potential implications in terms of disclosing the investors’ behavior from a political perspective.</big></p>

Asymmetric linkage between copper-cobalt productions and economic growth: Evidence from Republic Democratic of Congo

This study analyzed the nonlinear asymmetric link between copper-cobalt productions on economic development, and to which extent these variables exert growth concerning capital and labor in the Democratic Republic of Congo (DRC) for 26 years. Correlation, unit root, and cointegration tests were used for the testing framework, while nonlinear Autoregressive Distributed Lags, causality test, variance decomposition, and impulse response analysis were employed for the estimation framework. The main findings showed a strong correlation between variables, and selected variables integrated in 1st order, indicate the availability of long-run cointegration relations. The long-run nonlinear asymmetric relationships were noted between economic growth and both shocks (positive and negative) to copper and negative shock to cobalt production. Capital has the highest extent of economic growth, copper contributes more than cobalt, while labor is the least contributor to economic growth in terms of variations. This study suggested the potential policy implications, which can reflect on the possible cause-led nonlinear and negative impact of the mining sector on economic growth, and strengthen the link between copper and cobalt production and growth concerning micro-economic indicators.

Research on Stock Price of Two Listed Ship Companies

The development of the manufacturing industries is crucial to the countrys economic growth and technological development. In this study, the stock price return rate of two listed companies (JIANIANHUA and JIALEIBI) are selected as data, and the VAR model is established to conduct impulse response analysis and variance decomposition analysis on the data. We may also find the economic relations by analysing the 2 ship companiess stock under covid. Through the analysis of the results, the following findings can be given: first, VAR model indicates that the companies shows significant impact on each other. Second, in the cruise ship industry, both JIANIANHUA and JIALEIBIs stock price have strong self-adjustment ability. Third, JIANIANHUAs rate of return is less influenced by the rate of return of JIALEBI, while JIALEBIs rate of return is much highly influenced by JIANIANHUA. The papers findings might be helpful to related investors interested in the cruise ship industry.

Estimation, Inference, and Empirical Analysis for Time-Varying VAR Models

Vector autoregressive (VAR) models are widely used in practical studies, for example, forecasting, modeling policy transmission mechanism, and measuring connection of economic agents. To better capture the dynamics, this article introduces a new class of time-varying VAR models in which the coefficients and covariance matrix of the error innovations are allowed to change smoothly over time. Accordingly, we establish a set of asymptotic properties including the impulse response analyses subject to structural VAR identification conditions, an information criterion to select the optimal lag, and a Wald-type test to determine the constant coefficients. Simulation studies are conducted to evaluate the theoretical findings. Finally, we demonstrate the empirical relevance and usefulness of the proposed methods through an application on U.S. government spending multipliers.

An Innovative Approach to Analyze Financial Contagion Using Causality-Based Complex Network and Value at Risk

In this paper, we propose a new approach to analyze financial contagion using a causality-based complex network and value-at-risk (VaR). We innovatively combine the use of VaR and an expected shortfall (ES)-based causality network with impulse response analysis to discover features of financial contagion. We improve the current research methods by building a Granger causality network on VaR and ES and using conclusions drawn from network analysis as a foundational step before impulse response analysis. First of all, we select 30 stock indices that are very well-known globally and collect their trading data. After calculating the risk indicators of VaR and ES, we perform the Granger causality test on them and then build networks based on their respective Granger causality square matrix. Next, we examine the networks’ topological features to discover different degrees of risk transmission among all stock indices in the system. Lastly, we identify the most and the least active stock indices in the risk transmission network and conduct impulse response analysis on them. We discover that BSESN (India S&P BSE SENSEX) is the most risk-sensitive stock index as its VaR significantly increases by 0.03–0.04% and its ES jumps even more, by 0.07–0.08%, in response to an impulse from a few key stock indices. We also find that either PSI20 or XU100 is the most risk-proof stock index, depending on whether we choose VaR or ES as a risk indicator.

How do carbon, stock, and renewable energy markets interact: Evidence from Europe

In a low-carbon context, the connectedness among carbon, stock, and renewable energy markets has been strengthening. This study examines the effect of Brexit, the launch of the European Green Deal and the COVID-19 pandemic on the connectedness among carbon, stock, and renewable energy markets by employing Time Varying Parameter -Vector Auto Regression (TVP-VAR). First, equal interval impulse response analysis shows that in the short term, the renewable energy market suffers from a positive shock from the carbon market and this shock gradually decreases from the initial 1.6×10−3. In the long run, the connectivity between the carbon market and the stock market, and between the carbon market and the renewable energy market is almost 0. Second, we can conclude that the positive connectivity between stock market to carbon market and renewable energy market to carbon market is enhanced by COVID-19 in the short term, with values of 7.5×10−3 and 3.6×10−3 respectively. Finally, renewable energy market received a greater negative impact from the carbon market during COVID-19 than during the release of the European Green Deal, while Brexit allowed positive carbon price spillover to renewable energy price.

Internal migration dynamics of native and foreign workers: an impulse–response analysis of perturbation and resilience by means of a spatial vector autoregressive model

ABSTRACT Why are certain labour markets more resilient to economic shocks? Why are some economies deeply affected by migration? Modern migration theory remains based on simplistic neo-classical utility maximizing assumptions, despite a failure to fully answer real-world migration questions. The aim of this paper is to show that neo-classical dynamics are differentiated between subpopulations that make up the workforce. Using disaggregated data from Germany and a dynamic spatial vector autoregressive model that allows for spillovers, the paper teases out several aspects of regional labour market resilience. Results highlight that regions stand to benefit from supporting place-specific policies tailored to local circumstances.

Connectedness and risk spillovers between crude oil and clean energy stock markets

This research investigates the relationship between clean energy stock and oil market returns utilizing Granger predictability in distribution and quantile impulse response analysis. We find that clean energy stock returns Granger predict oil price returns during “normal times” based on the distribution’s center, but not vice versa. During bullish market episodes, there is bidirectional Granger predictability between the returns of clean energy stocks and oil market returns. Nonetheless, we find that clean energy stock returns Granger predict oil returns in bearish markets without any evidence of the contrary. This indicates that oil returns cannot be used to hedge the downside risk associated with renewable energy company purchases. Quantile impulse responses for the relationship between clean energy stocks and the crude oil market reveal bidirectional and significant responses, where a negative shock during an extremely down market reveals a negative response in the other market and a positive shock during an extremely up market reveals a significant positive response. This shows that neither market can be utilized to offset risks in the other market.

Characteristics and mechanisms of the U.S. stock market spillover effects on the Chinese A-share market: Evidence from 6 A-share broad-based and 31 sector indices

This study investigated the NYSE and NASDAQ composite indices' return and volatility spillover on 37 Chinese A-share indices. We used data from 2010 to 2022 with Multiplicative-Heteroskedasticity-GARCHX and rolling window analysis. We also applied a vector autoregression and impulse response analysis to study the relationship between the spillover effect and market return or volume condition. We found that: (1) the spillover effect of U.S. stocks can be quickly and mostly absorbed by the A-share market in the next trading day; (2) the dissimilarity of constituents among A-share indices contributes to the differences in the NYSE and NASDAQ spillover effects; (3) the spillover becomes more significant and prominent when the market performance is poor or when some special events occurred.

Integration of Bond Markets and Portfolio Diversification : Evidence from the 2008 Global Financial Crisis

Purpose : This study aimed to examine the integration between the bond markets of the MSCI Emerging Markets and the USA concerning the 2008 financial crisis. Methodology : Granger causality and correlation tests were used to assess the short-term integration of the bond markets. The long-term integration was examined using the Johansen co-integration test and VAR analysis. Findings : Post-crisis, bond markets became more correlated with each other. Due to a lack of market integration in both periods, different portfolio combinations offered the chance for portfolio diversity. The MSCI Emerging Asian markets and US market integration increased with the global financial crisis of 2008. The results of the VAR analysis and impulse response analysis found that innovations in the markets of the USA and China affected the Indian market the most; whereas, the rest of the market had a nominal impact. Practical Implications : The study has practical implications in the sense that based on the integration, investors might diversify their holdings to achieve a better risk-return balance. The investors can design their investment portfolio accordingly to have an optimal portfolio. Originality : This study focused on building portfolio diversification with fixed-income securities.