Impulse Response Analysis Research Articles

Assessing the baseline model of WTI oil and stock returns under financial volatility and spillover effects

Do financial volatility shocks matter for WTI oil and stock markets? They should since world economic activity responds to volatility. To investigate this question, we revisit two empirical frameworks widely used in the literature. Our baseline involves the standard identification of oil shocks in structural vector autoregressions (SVAR) with (world) oil supply, demand, and real oil prices. We then propose a global vector autoregressive (GVAR) model integrating 14 major world economies. We introduce the volatility measure (VIX), various stock markets, and compare two oil demand proxies: real economic activity (REA) based on commodity prices and world industrial production (WIP). The results of the impulse response analysis do not indicate major differences across models. However, when measuring the share of oil price variance explained by shocks to VIX (or to U.S. high-bond corporate yield) SVAR overestimates the influence of VIX. We find (world) demand shocks explain a larger part of the variance of oil and stock markets compared to supply shocks. In SVAR, new information coming from a one standard deviation shock to VIX is incorporated negatively and instantaneously on real oil prices: −1.6 for REA and −1.4 for WIP. In GVAR these are reduced slightly to −1.2 from VIX and to −0.6 if coming from corporate bond yield shocks. Our study highlights the sensitivity of econometric results to distinct approaches: one that identifies shocks and another that captures spillover effects.

Exploring the nexus of decent work, financial inclusion, and economic growth: A study aligned with SDG 8

We investigate the potential influence of fair employment practices and financial inclusion on economic growth, focusing on aligning our analysis with the United Nations Sustainable Development Goal 8 (SDG 8). Our study encompasses various countries, including 26 low-income, 20 middle-income, and 15 high-income nations. Utilizing a dynamic fixed-effect panel data approach and employing the Generalized Method of Moments from 2010 to 2021, our findings reveal that conducive environments for decent work and enhanced access to digital financial services positively impact economic growth. This synergistic effect of SDG 8 components is particularly pronounced in high-income countries, suggesting the potential for accelerated economic growth rates. Conversely, our analysis finds no discernible impact on the economic growth of low-income countries. For middle-income countries, nuanced coefficient outcomes provide a more intricate understanding of their economic dynamics. Through extensive impulse-response analysis using a Panel Vector Autoregression model, we illustrate the distinct effects of shocks related to decent work and financial inclusion across various income categories. Our results are robust to multiple sensitivity tests, underscoring their reliability and signaling significant policy implications for acknowledging the critical role of decent work and financial inclusion in fostering economic growth.

Effectiveness of hierarchical medical system and economic growth: based on China's urban vs. rural health perspectives.

The hierarchical medical system is an important measure to promote equitable healthcare and sustain economic development. As the population's consumption level rises, the demand for healthcare services also increases. Based on urban and rural perspectives in China, this study aims to investigate the effectiveness of the hierarchical medical system and its relationship with economic development in China. The study analyses panel data collected from Chinese government authorities, covering the period from 2009 to 2022. According to China's regional development policy, China is divided into the following regions: Eastern, Middle, Western, and Northeastern. Urban and rural component factors were downscaled using principal component analysis (PCA). The factor score formula combined with Urban-rural disparity rate (ΔD) were utilized to construct models for evaluating the effectiveness of the hierarchical medical system from an urban-rural perspective. A Vector Autoregression model is then constructed to analyze the dynamic relationship between the effects of the hierarchical medical system and economic growth, and to predict potential future changes. Three principal factors were extracted. The contributions of the three principal factors were 38.132, 27.662, and 23.028%. In 2021, the hierarchical medical systems worked well in Henan (F = 47245.887), Shandong (F = 45999.640), and Guangdong (F = 42856.163). The Northeast (ΔDmax = 18.77%) and Eastern region (ΔDmax = 26.04%) had smaller disparities than the Middle (ΔDmax = 49.25%) and Western region (ΔDmax = 56.70%). Vector autoregression model reveals a long-term cointegration relationship between economic development and the healthcare burden for both urban and rural residents (βurban = 3.09, βrural = 3.66), as well as the number of individuals receiving health education (β = -0.3492). Both the Granger causality test and impulse response analysis validate the existence of a substantial time lag between the impact of the hierarchical medical system and economic growth. Residents in urban areas are more affected by economic factors, while those in rural areas are more influenced by time considerations. The urban rural disparity in the hierarchical medical system is associated with the level of economic development of the region. When formulating policies for economically relevant hierarchical medical systems, it is important to consider the impact of longer lags.

Volatility Spillover Benefits of the Hang Seng Index and Shanghai Composite Index: A Vector Autoregressive (VAR) Model and Granger Causality Test Analysis

This study aims to explore the volatility spillover benefits between two major stock markets in Hong Kong and Shanghai, namely the Hang Seng Index and the Shanghai Composite Index. Empirical analysis is conducted using a Vector Autoregressive (VAR) model and Granger causality test based on daily return data from 2013 to 2023. The research finds a significant volatility interaction between the Hang Seng Index and the Shanghai Composite Index, which is more pronounced during periods of global economic instability. Impulse response analysis reveals that positive shocks in Hang Seng Index lead to increased volatility in the short term for the Shanghai Composite Index but gradually weaken to a weak negative effect in the long term. Conversely, positive shocks in the Shanghai Composite Index have a short-term inhibitory effect on the Hang Seng Index but transform into a weak promoting effect in the long term. These findings have important implications for investors and policymakers in risk management, forecasting future stock market trends, and capital allocation.

Research on the Linkage between RMB Interest Rate and Exchange Rate

This study uses a vector autoregressive (VAR) model to investigate the relationship between the exchange rate (EX) and RMB interest rate (I). The research starts with a review of pertinent theoretical frameworks and then conducts an empirical analysis with historical data to determine the long-term interactions between these two macroeconomic factors in the Chinese market. The empirical findings demonstrate the extent to which the I affects EX as well as the reciprocal relationship between EX and I The stability of the linkage is further explored using variance decomposition and impulse response analysis. In addition to offering policymakers a foundation for regulating monetary policy, this study offers a fresh viewpoint on the macroeconomic dynamics of China.

The impact of household registration system reform: evidence from China

ABSTRACT We construct a DSGE model with three sectors: households which are divided into urban registered residents and non-urban residents, firm, and government, calibrate and estimate the model with data of China. This study aims to evaluate the impact of household registration system (HRS) reform of China, and provides a theoretical thought to understand this reform. Impulse response analysis and counterfactual simulation show the short-term and long-term effects of the reform on output, consumption, and labour supply. The shock (1%) in public goods consumption increases labour supply and private consumption of non-urban registered residents by 0.21% and 0.42%, decreases by about 0.13% and 0.14% in urban registered residents, and increases in overall labour supply, consumption, and output levels by approximately 0.08%, 0.26% and 0.36%, respectively. While the impact of wage level increases labour supply and private consumption of non-urban registered residents by about 0.03% and 0.6%, about 0.03% and 0.25% of urban registered residents. This leads to increases of overall labour supply, consumption, and output levels by approximately 0.03%, 0.28% and 0.12%, respectively. Transfer payment shocks has a very weak effect. Overall, the economic effects of the household registration system reform policy are significant.

Water Resource Utilization Assessment in China Based on the Dynamic Relationship between Economic Growth and Water Use

Water scarcity has significantly hampered China’s economic, social, and environmental development. Ensuring sustainable water utilization is crucial given the mounting water stress accompanying continuous economic growth. A quantitative water resource forewarning model was constructed using the vector autoregressive (VAR) model. By analyzing the key indicators related to water systems and GDP data from 2001 to 2022, the VAR model revealed the long-term dynamic correlation between water consumption and economic growth using generalized impulse response, co-integration, and predictive variance decomposition analyses. The results revealed the presence of a long-term equilibrium between water consumption and economic growth, with a stable co-integration relationship and an optimal lag period of one year. The positive impact of water consumption on economic development increased during the 2001–2022 period, indicating a rising dependence of GDP on water resources. Water usage rose with economic development, while the water resource carrying capacity remained high and continued to grow. Based on the generalized impulse response, co-integration, and predictive variance decomposition analyses, this study predicted water-use-related indicators, providing vital early warnings for China’s water environment carrying capacity from 2023 to 2050. This enabled informed decision-making and fostered sustainable water management practices for the future.

Financial conditions, macroeconomic uncertainty, and macroeconomic tail risks

This paper investigates how financial conditions and macroeconomic uncertainty jointly affect macroeconomic tail risks. We first document that tight financial conditions decrease all conditional quantiles of future output growth in the near term, while high macroeconomic uncertainty only stretches the interquartile range. Because financial conditions and uncertainty comove substantially, the conditional means and variances shift simultaneously in the opposite direction. Consequently, the downside risk varies much more than the upside risk. A quantile impulse response analysis indicates that both financial and uncertainty shocks are responsible for the asymmetric behaviors in the downside and upside risks.

Empirical analysis of the development relationship between Shanghai shipping industry and primary industry based on VAR model

This study employs the Vector Autoregression (VAR) model to conduct an in-depth empirical analysis of the dynamic relationship between Shanghai’s shipping industry and the development of the primary sector from 2002 to 2022. The findings reveal that, as a globally significant maritime hub, the development of Shanghai’s shipping industry has a notable positive impact on the growth of the primary sector, particularly in agriculture and fisheries. Through ADF unit root tests, cointegration tests, and Granger causality tests, a stable long-term relationship was identified between shipping industry indicators, such as container throughput and total waterborne cargo transport volume, and the output value of the primary sector. Impulse response analysis and variance decomposition further reveal the critical roles and mechanisms through which the shipping industry influences the development of the primary sector. Based on these insights, the paper proposes policy recommendations aimed at strengthening the integrated development of shipping and the primary sector, promoting technological innovation in the shipping industry, optimizing the policy environment, enhancing environmental protection measures, and bolstering international cooperation. These strategies are intended to foster synergistic development between the two sectors and drive sustainable economic growth.

Adaptive potential of Russian economic growth in the context of decline in foreign direct investment

This study analyses the adaptive potential of Russia’s economic growth in the context of decline in foreign direct investment (hereinafter referred to as FDI). In light of today’s geopolitical environment, marked by increased trade tension and protectionist measures, understanding the impact of FDI on Russia’s gross domestic product (hereinafter referred to as GDP) becomes critical for policy-making and economic planning. The study employs a vector autoregression modeling approach (hereinafter referred to as VAR) to analyse the dynamics of Russia’s GDP and FDI inflows with consideration to various economic and geopolitical factors. Besides, an extensive dataset is used covering the period from 1996 to 2021 which includes relevant macroeconomic indicators and geopolitical events. The VAR model allows to study short- and long-term correlations between variables reflecting dynamic interaction and feedback effects. In addition, impulse response analysis is used to estimate the magnitude and sustainability of economic growth under conditions of economic instability. The results of the study contribute to understanding the adaptative potential of Russia’s economic growth in the context of FDI restrictions from Western countries. The analysis provides insight into the significance of FDI inflows for the Russian GDP with consideration to the impact of various economic and geopolitical factors.

Profitability and Expanding Collection Period in Bangladesh

In this article, the authors investigate the relationship between profitability and receivables management of DSE listed non-financial firms in Bangladesh for the years 2000-2017. A cointegration model is used to examine the relationship between average collection period (ACP), return on assets (ROA), firm size, and debt ratio of firms. Impulse response analysis indicates that while the other variables quickly return to equilibrium, a shock to ACP or profitability seems to have a significant and durable impact on the relationship. A GMM model has also been used to estimate a regression that shows the impact of increasing ACP on profitability. The results strongly point to a cointegrating relationship and the critical role of receivables management on profitability. The article contributes to the existing literature by providing strong evidence that the average collection period is the most critical variable in addressing control of working capital management. However, this variable is the most difficult variable to manage, especially after there is an indication that it is worsening.

Integrating FinTech with Industry 4.0 for sustainable mineral resource management: Exploring the interplay of technology, regulation, and economic dynamics

In the field of global geology, the intricate relationship between Earth’s mineral resources and their pivotal role in fostering sustainable human development is a fundamental area of scholarly investigation. This research thoroughly explores the complex dynamics between technological progress, financial innovations, and regulatory structures in the context of sustainable management of mineral resources. Covering the period from 2000 to 2022 and including key international stakeholders in the mineral industry, the study employs a Panel Autoregressive Distributed Lag (ARDL) approach to assess the effects of Industry 4.0 technologies (IND), Financial Technology (FinTech), Regulatory Quality (RQ), Energy Efficiency (EF), and per capita Gross Domestic Product (GDP) on Mineral Resource Capital (MRC). The results reveal a substantial, positive long-term influence of Industry 4.0 on Mineral Resource Capital, underscoring the essential role of technology. Conversely, FinTech exhibits a nuanced association with Mineral Resource Capital, indicating the necessity for its careful incorporation. The analysis highlights the significance of regulatory quality in the sustainable management of resources, while the negative impact of energy efficiency points towards the need for more sustainable industrial practices. Through variance decomposition and impulse response analysis, the study delineates the responsiveness of Mineral Resource Capital to various economic fluctuations, with Granger causality tests offering additional insight into these complex interactions. This investigation contributes significantly to the existing scholarly literature and offers crucial perspectives for policy-makers and industry participants, advocating for a cohesive strategy that effectively harnesses technological and financial innovations to enhance sustainability and economic resilience in the mineral sector.

중국의 토지 공급 정책이 부동산 시장에 미치는 영향

Purpose - This study aims to explore the relationship between housing and land prices, with a specific emphasis on the impact of government policies on these factors such as land supply quantity and the ratio of residential land to total land supplied. The goal is to identify the most effective government intervention strategies for controlling both housing and land prices. Design/methodology/approach - Data from 70 primary and medium-sized cities in China spanning from 2003 to 2017 are utilized in this research. The analysis employs a panel vector autoregressive (PVAR) model, with a primary focus on examining the relationships among housing prices, land prices, and government intervention policies. Findings - Housing and land prices are influenced by various factors. Through impulse response analysis and variance decomposition, it is observed that both housing and land prices are predominantly influenced by their internal dynamics, with comparatively weaker effects attributed to policy interventions. Research implications or Originality - By investigating the impact of government policies on housing and land prices, This study establishes a foundation for effective price control measures. Our study advocates for a comprehensive examination of China's land supply mechanism to enhance understanding of the pathways through which government policies influence the markets.

주택순환국면에 따른 주택가격 및 거래량 간의 인과성 분석

It will be useful information to analyze using past housing market’s data can be predicted future direction. It will be very interesting information for market participants if the direction of prices and transaction volume can be predicted. Therefore, the purpose of this study is to identify the housing circulation phase by dividing it by period, focusing on the Seoul housing market, which is the center of price fluctuations in the current housing market, and to compare and analyze the correlation between housing prices and trading in each circulation phase. To analyze the correlation between the two variables, Granger causality test, vector autoregression model (VAR), and impulse response analysis were used. As a result of the study, the housing circulation phase is subdivided into four phases, and the direction of prices and transaction volume is analyzed differently for each phase. There is a positive correlation between price and trading and prices affect transaction volume in the short term, but the influence of transaction volume on prices is insignificant. However, it has been proven that one of the two variables has predictive power for the other. Although there is a limitation in that it is not possible to analyze the direct factors affecting the variables, it is believed that it can be used as useful information for housing participants and government policy officials.

Exploring price level trajectory in India: Does it validate the fiscal theory of price level?

The fiscal policy’s impact on the price level is theorized as the Fiscal Theory of Price Level (FTPL) and has been popularized since the 1980 s. Developing countries often face the problem of prolonged deficits in fiscal management and depend on public debt. Studies on the FTPL in these countries are pertinent but scarce. This paper explores the price level trajectory in the Indian economy for 1985–2019 on the premise of FTPL. Empirical assessment involves both fiscal variables (deficit, debt, public spending) and money supply. The results of the cointegrated vector autoregression model followed by an impulse response analysis reveal that fiscal deficit stimulates the price level, while public spending has a stabilizing impact. Public debt is rather inflationary, but its impact is not robust. Besides, the money supply amplifies the price level. In the price level trajectory, neither the fiscal dominance nor the monetary dominance, that is, indeterminacy, is ascertained. The proactive role of fiscal and monetary policies in the price level trajectory suggests that if the Reserve Bank of India’s stance on price-level stabilization is abreast, the fiscal authority might accomplish the appropriate strategy.

Natural resource development, economic policy uncertainty and urban residents’ consumption in China: a nonlinear ARDL and time-varying parameter vector autoregressive with stochastic volatility approach

Increased risks of economic policy uncertainty and overexploitation of natural resources exist in China. At the same time, the growth rate of urban residents’ consumption has generally declined. The paper analyses the role of economic policy uncertainty (EPU) and natural resource exploitation on the urban residents’ consumption in China. Based on the data from the first quarter of 2002 to the third quarter of 2021, the paper uses a nonlinear autoregressive distributed lag model to verify the asymmetric effects. Then the paper constructs a time-varying parameter vector autoregressive model with stochastic volatility term to analyze the nonlinear responses. Impulse response analysis was used to further explain the relationship between the three. The negative impact of rising EPU on urban residents’ consumption is larger than its reduction. Negative shocks to natural resource development increase the urban residents’ consumption. Positive shocks reduce the urban residents’ consumption. There is a time-varying non-linear effect of EPU and natural resource development on urban residents’ consumption in China. The negative impact of EPU on urban consumption has been further exacerbated by major crises such as the financial crisis, COVID-19 and the post-crisis period. The negative impact of natural resource development diminished after the government introduced industrial upgrading policies and environmental regulations. This study provides constructive suggestions for the optimization of economic policies and the improvement of urban consumption. This study also enriches consumer theory and provides new evidence for the resource curse hypothesis.

Decent work, financial inclusion, and economic growth: Analysis under the SDG 8

We investigate the potential influence of decent work and financial inclusion on economic growth, aligning our analysis with the United Nations Sustainable Development Goal 8 (SDG 8). Analyzing a diverse set of 26 low-income, 20 middle-income, and 15 high-income countries, we utilize a dynamic fixed-effect panel data approach and apply the Generalized Method of Moments from 2010 to 2021. The findings highlight that favorable conditions for decent work and increased access to digital financial services contribute positively to economic growth. The synergistic effect of these SDG 8 components is notably pronounced in high-income countries, with greater potential for elevated economic growth rates. Conversely, no discernible impact is observed on the economic growth of low-income countries. The results for middle-income countries present nuanced coefficient outcomes, offering a more intricate interpretation of their economic dynamics. An extensive impulse-response analysis, conducted using a Panel Vector Autoregression model, demonstrates distinct impacts of shocks related to decent work and financial inclusion across various income categories of countries. Our findings pass various robustness checks, affirming their reliability and suggesting significant policy implications for recognizing the crucial role of decent work and financial inclusion in fostering economic growth.

Does geopolitical uncertainty matter for the diffusion of clean energy?

This study revisits the determinants of renewable energy (RE) deployment, with an emphasis on the role of recent adverse geopolitical events. We implement a panel vector autoregressive model where different techniques and tools are available to trace the dynamic interdependence between RE and its main drivers. The impulse response analysis indicates that geopolitical uncertainty exerts a positive impact on the clean energy sector in advanced countries. However, geopolitical shocks do not appear to stimulate the transition toward alternative sources of energy in emerging and developing economies. The forecast-error variance decomposition confirms the importance of adverse geopolitical shocks in explaining the dissemination of renewables in advanced economies. Policymakers in less developed countries are urged to continue supporting RE initiatives and infrastructure, which are key to successful mitigation strategies.

The Effect of COVID-19 Confirmed Case and COVID-19 Containment and Health Index on the Domestic Tourism Expenditure Using Impulse Response Analysis

The Effect of COVID-19 Confirmed Case and COVID-19 Containment and Health Index on the Domestic Tourism Expenditure Using Impulse Response Analysis

High Public Debt in Japan: The Institutional Quality Perspective

This study aims to look at the long-term and short-term links between institutions' quality and public debt. The analysis seeks to shed light on two key aspects: firstly, the influence of country-level institutional quality on public debt, and secondly, the duration of the effects or shocks caused by this relationship. This research employs time-series data spanning from 1996 to 2017 to examine the relationship between institutional quality at the country level and public debt in Japan. Various econometric techniques were employed to analyse the determinants of public debt in Japan, including ’The Unit Root Test, Johansen's Co-integration Analysis, Vector Error Correction (VEC) Model, Variance Decomposition, Impulse Response Analysis, Pairwise Granger Causality Test, and The Toda-Yamamoto Model’. The results of the estimation demonstrate a statistically significant correlation between country-level institutional quality and public debt, both in the long and short term. The evidence indicates that factors such as Voice and Accountability (VA), Political Stability (PS), Government Effectiveness (GE), and Regulatory Quality (RQ) have a negative and statistically significant impact on public debt. Conversely, the Rule of Law (RL) and Control of Corruption (CC) exhibit a positive and statistically significant influence on public debt. The occurrence of public debt can frequently be attributed to the insufficient focus of policymakers, which can be attributed to governance deficiencies. Hence, the implementation of public debt management is necessary to mitigate the possibility of default. The findings indicate that it would be advisable for Japan to enact comprehensive policies aimed at mitigating public debt.