Panel VAR Research Articles

Influence mechanism between green finance and green innovation: Exploring regional policy intervention effects in China

The effective use of inclusive green finance is imperative for deriving green innovation, fostering sustainable economic transformation, and addressing climate change. Therefore, this study empirically tests the influence mechanism and policy intervention effects of inclusive green finance on green innovation by applying the difference-in-differences, mediation effects, and panel vector autoregression models using China's regional data from 2010 to 2019. The findings indicate that green finance significantly contributes to green innovation, and these effects remain consistent across alternative estimators. The results of policy intervention effects confirm that the Pilot Zones for green financial innovation and reform encourage green innovation and sustainable performance more pronouncedly than other regions. The mediating effects reveal that industrial structure, economic growth, and research and development investment are the core transmission channels through which green finance influences green innovation. These results offer valuable recommendations.

Co-inventions, uncertainties and global food security

This paper examines the effects of international collaborative efforts on climate-friendly agricultural technologies on global food security. In particular, we use patent data on environmental technological innovations for OECD countries and global food prices from the period 1990 to 2016. Also, we investigate the impact of uncertainties in weather conditions in terms of rising global temperature created by climate change using data on global surface temperature from the Energy Information Administration and the Goddard Institute for Space Studies (GISS) Surface Temperature Analysis of the National Aeronautics and Space Administration (NASA). We used both impulse response functions and variance error decomposition from a panel Vector Auto-Regressive (VAR) model to examine both the response of global food prices to shocks on the concerned variables and the decomposition of error variance in global food prices. First, our results show that international collaborative efforts on climate-friendly agricultural technologies reduce global food prices while increasing global surface temperature increases food prices. Regarding the variance decomposition of global food prices, results show that surface temperature followed by international collaborations in climate-friendly innovations and other environment-related technologies are the main drivers of forecast error variance in global food prices. The food price variance share associated with greenhouse gas emissions is less when compared to that of technological innovations.

Regional Integration and Decoupling in the Asia Pacific: A Bayesian Panel VAR Approach

Regional Integration and Decoupling in the Asia Pacific: A Bayesian Panel VAR Approach

Spatial Heterogeneity Impacts of Bilateral Foreign Direct Investment on Green Energy Efficiency in China

At present, green energy transformation and climate policy are increasingly connected. The need to improve national competitiveness and implement climate and energy strategies means that an energy-consuming country like China must rapidly enhance its green energy efficiency (GEE) and energy consumption structure. The following paper contributes to the existing literature by analyzing the effects of bilateral FDI on GEE from the perspective of spatial correlation. Based on data from 30 Chinese provinces between 2003 and 2020, this paper uses multiple undesired output indicators covering eight pollutants to measure GEE and then uses the coupling function to measure the coordinated development level of bilateral FDI (CDFDI). According to the Panel Vector Autoregression model, there is a coupling relationship between bilateral FDI. Both the global Moran index and the local Moran scatter plot shows that GEE and CDFDI are characterized by spatial aggregation. This paper adopts the dynamic Spatial Dubin Model for empirical analysis. Our results reveal a significant positive impact of CDFDI on GEE in local and nearby regions. The impact of CDFDI on GEE is moderated by technological diffusion, nationalization, and environmental regulation, resulting in differential impacts on GEE in local and nearby regions. Furthermore, CDFDI with different investment motives has a boosting effect on local GEE. Among them, the mutual investment portfolio between China and developed countries has a negative impact on the local GEE. By contrast, the complementary investment motivation portfolio can boost GEE in local and adjoining regions in any period. This is the first paper to study the spatial effects of green energy efficiency and the heterogeneity of investment incentives to help Chinese international investment policymakers better understand the contribution of CDFDI to improving GEE and inform supportive policies. To improve green energy efficiency, the government must strengthen the implementation of the opening-up policy and create international capital flows suitable for local needs.

The influence path and dynamic relationship between economic development, industrial structure upgrading, urbanization, urban–rural income gap, and electricity consumption in China

AbstractConsidering China's goal of carbon neutrality, understanding the influence path and dynamic correlation between electricity consumption and relevant factors is essential for formulating a reasonable electricity development strategy and promoting high‐quality socio‐economic development. Based on panel data of 30 provinces in China from 2000 to 2019, this study adopts the panel VAR model for research, with four notable findings. (1) Economic development, urbanization, and the urban–rural income gap directly affect electricity consumption. Industrial structure upgrading can affect electricity consumption through economic development and urbanization. Electricity consumption only directly affects economic development, whereas the effect on the other three variables could be transmitted through economic development. (2) Electricity consumption first inhibits and then promotes industrial structure upgrading, and it inhibits the urban–rural income gap. (3) Industrial structure upgrading first promotes and then inhibits electricity consumption. The urban–rural income gap inhibits electricity consumption. (4) Industrial structure upgrading and the widening income gap might hinder economic development through the adverse effect on electricity consumption. Based on these findings, several policy suggestions are proposed.

Analysis of the Spatial and Temporal Characteristics and Dynamic Effects of Urban-Rural Integration Development in the Yangtze River Delta Region

Urban-rural integration has been found to be an inevitable trend in the development of urban-rural relations and a vital measure to tackle the unbalanced and uncoordinated development between urban and rural areas. Most existing studies on the development of urban-rural integration have only estimated its level and factors and compared the heterogeneity of cities in sample regions. Few studies have focused on the interactions between different categories of urban-rural integration levels. Accordingly, to fill the above research gap, an evaluation index system of the development of urban-rural integration is built in this study from four economic-social-spatial-ecological dimensions, the spatial and temporal evolution characteristics of the development of urban-rural integration in 27 central cities in the Yangtze River Delta region between 2003 and 2020 are analyzed, and the intrinsic dynamic shock effects are empirically investigated using a panel vector autoregression (PVAR) model. This study suggests the following points: (1) the development of urban-rural integration in the Yangtze River Delta region tends to increase while fluctuating and experiences an evolutionary process of “severe dysfunction–moderate dysfunction–mild dysfunction”, with an overall positive development trend. (2) In the study period, the agglomeration effect of the level of the development of urban-rural integration in the Yangtze River Delta has been strengthened continuously, and the overall spatial distribution pattern has changed from “low level, low gap” to “high level, high gap”, showing the characteristics of decreasing class distribution step by step, with Shanghai and Anqing as the markers from east to west. (3) All the endogenous variables of the development of urban-rural integration show a continuous positive response to their own shocks, thus suggesting that the respective variable has a certain path dependence on itself. Shocks of urban-rural ecological integration are capable of boosting the improvement of urban-rural economic integration and urban-rural social integration development, and shocks of urban-rural social integration contribute to the improvement of urban-rural ecological integration. The important policy implication of this study is that an intra-regional linkage and coordination mechanism should be built in the future, while the focus should be placed on the heterogeneity of regional development, and policies and measures regarding development of urban-rural integration in a disaggregated manner should be developed, so as to facilitate the improvement of the level of regional development of urban-rural integration.

Structural Compressed Panel VAR with Stochastic Volatility: A Robust Bayesian Model Averaging Procedure

This paper improves the existing literature on the shrinkage of high dimensional model and parameter spaces through Bayesian priors and Markov Chains algorithms. A hierarchical semiparametric Bayes approach is developed to overtake limits and misspecificity involved in compressed regression models. Methodologically, a multicountry large structural Panel Vector Autoregression is compressed through a robust model averaging to select the best subset across all possible combinations of predictors, where robust stands for the use of mixtures of proper conjugate priors. Concerning dynamic analysis, volatility changes and conditional density forecasts are addressed ensuring accurate predictive performance and capability. An empirical and simulated experiment are developed to highlight and discuss the functioning of the estimating procedure and forecasting accuracy.

The Spillover Effects of Chinese Shocks on the Belt and Road Initiative Economies: New Evidence Using Panel Vector Autoregression

This paper investigates the spillover effects of Chinese real and monetary sector shocks on the Belt Road Initiative (BRI) economies. The study adopted a panel vector autoregression (PVAR) estimation technique to analyse the dynamic propagation of Chinese shocks in the real sector (gross domestic product (GDP) and trade openness (OPEN)) and monetary sector (nominal interest rate (NIR)) for a sample of 50 BRI countries from 2000 to 2017. The main results revealed that Chinese income shocks positively spill over to all macroeconomic variables except BRI countries’ consumer price index (CPI). However, the Chinese trade openness shock only has a temporary positive spillover to BRI international trade and a temporary negative spillover on its monetary policy. In addition, the Chinese monetary policy shock has a negative spillover on GDP and a positive spillover on CPI in BRI economies. Chinese shocks, however, do not constitute a significant source of variation in any interest variable. As explained by the Chinese income shock, the BRI interest rate is the highest percentage of variable variation accumulated over time. Further, the highest variation of Chinese trade shock is BRI trade openness, and lastly, the highest variation of Chinese interest rate shock is CPI in BRI economies. The beggar-thy-neighbour effect may dominate the positive trade effect and is a negative impact of the Chinese shocks. Hence, BRI economies should alleviate the adverse shocks since the upcoming rapid growth from the Chinese has disturbed the BRI economies. Our results reveal the importance of Chinese development on BRI partners’ economies and the significance of Chinese shocks in real and monetary sectors in assisting policymakers in designing international and monetary policy for BRI economies.

Investor sentiments and stock markets during the COVID-19 pandemic

This study examines the relationship between positive and negative investor sentiments and stock market returns and volatility in Group of 20 countries using various methods, including panel regression with fixed effects, panel quantile regressions, a panel vector autoregression (PVAR) model, and country-specific regressions. We proxy for negative and positive investor sentiments using the Google Search Volume Index for terms related to the coronavirus disease (COVID-19) and COVID-19 vaccine, respectively. Using weekly data from March 2020 to May 2021, we document significant relationships between positive and negative investor sentiments and stock market returns and volatility. Specifically, an increase in positive investor sentiment leads to an increase in stock returns while negative investor sentiment decreases stock returns at lower quantiles. The effect of investor sentiment on volatility is consistent across the distribution: negative sentiment increases volatility, whereas positive sentiment reduces volatility. These results are robust as they are corroborated by Granger causality tests and a PVAR model. The findings may have portfolio implications as they indicate that proxies for positive and negative investor sentiments seem to be good predictors of stock returns and volatility during the pandemic.

Decomposing the role of mobility restrictions in controlling COVID-19 outcomes: a regional level study of the Philippines

PurposeThis paper aims to explore empirically the interactions between the coronavirus disease 2019 (COVID-19) pandemic, economic mobility and containment policy to test the effectiveness of mobility restrictions in controlling the spread of the disease.Design/methodology/approachThis study used weekly regional data for the 17 Philippine regions and estimated the effect of shocks using a panel vector autoregression (VAR) model.FindingsThe authors conclude that COVID-19 deaths and incidence primarily respond to shocks that affect the lethality and transmissibility of the disease, and mobility restrictions and strict quarantine levels do not seem to have any impact on these outcomes. The movement of people during this pandemic period, on the other hand, seems to respond more to economic factors and government restrictions and less to the presence of and the characteristics of the disease.Originality/valueSince the pandemic is a public bad, community cooperation is a must to address it. Clear government messaging that dispels doubts on the safety of the newly developed vaccines and that encourages public acceptance and trust might be a better nudge compared to a heavy-handed and threatening approach.

Foreign Exchange and Global Monetary Shocks: The Asymmetric Effects of Advanced Economies’ Quantitative Easing on Exchange Rate Volatility in Emerging Markets

This research assesses the impact of global monetary shocks stemming from quantitative easing policies in advanced economies on exchange rate volatility in emerging markets. Using panel ARDL (Autoregressive Distributed Lag) model, an asymmetric effect is detected showing that increases in quantitative easing have a significant impact on exchange rate volatility, whereas subsequent tapering does not. Moreover, the Fragile Five economies experience spikes in exchange rate volatility that are more than double what is detected in other emerging markets. Finally, the impact of foreign exchange intervention to offset the effect on volatility is significant across emerging markets and is, once again, larger in the Fragile Five economies. The results are supported using panel VAR (Vector Autoregression) estimations.

Impact of fossil fuels and renewable energy consumption on economic growth in Paris Club Countries

The relationship between economic growth (in terms of GDP) and renewable energy (RE) and nonrenewable energy (NRE) consumption was investigated in 20 countries featured on the Renewable Energy Country Attractiveness Index list, also known as the Paris Club. The effect of both RE and NRE consumption on economic growth is discussed in the growth model based on the neoclassical production function. Labor and capital, which are important dynamics of growth, are also considered in the model. Granger causality and panel vector autoregression analysis are performed for the period 1991–2016. The results show that neither RE nor NRE consumption has a positive effect on economic growth. In reality, a 1% increase in RE consumption will reduce the GDP growth by 0.14%. For the effect of GDP growth on energy types, if growth increases by 1%, NRE consumption increases by 5.54%. If economic growth increases by 1%, a reduction of 1.73% occurs in RE consumption. In contrast, a causal link between both types of energy to growth has not been determined. There is no statistically significant coefficient of NRE and capital factors on GDP. A mutually positive and statistically significant relationship was determined between labor and growth. According to the results of variance decomposition, the basic dynamic of growth is itself: over a ten-year period, growth was affected by itself by 98%.

Panel VAR study on the effects of technical efficiency, market competition, and firm value on environmental performance

This study provides evidence on the interactions among four interconnected firm performance profiles: environmental performance (environmental score and pollutant emissions), production technical efficiency, firm market power, and firm market value. We employ two sophisticated econometric methodologies to a sample of almost 2500 observations covering about 430 US-listed manufacturing firms from 2002 to 2020. First, stochastic frontier analysis allows us to estimate time-varying technical efficiency in firm production; next, we apply an atheoretical model, the panel vector autoregression model , to identify the dynamic and causal relationships between the corporate profiles’ performance. Our results show that inefficiency is the weak point of the environmental score for the listed US manufacturing firms. Moreover, monopolistic rents enact a detrimental externality on firms’ ecological awareness. Finally, market dominance appears be a Pareto inefficiency condition. • This study provides evidence on the interactions among four interconnected firm performance profiles. • Inefficiency is the weak point of the environmental score for the listed U.S. manufacturing firms. • Monopolistic rents enact a detrimental externality on firms’ ecological awareness. • Market dominance appears be a Pareto inefficiency condition.

The Effects of Demographic Dynamics on Economic Growth in EU Economies: a Panel Vector Autoregressive Approach

This study estimates the effects of demographic dynamics on economic growth, with a focus on the working-age population and life expectancy in 19 European Union economies for 1970–2020 and 2020–2050, using a panel vector autoregressive (PVAR) model as the analytical methodology. The main findings are as follows. First, the PVAR estimation identifies positive effects of the growth of the working-age population share and the extension of life expectancy on economic growth. Second, the contribution ratio of the demographic effects to economic growth for past population bonus periods is approximately 15% on average in this study, which is comparable to the ratios found in previous studies. Third, the projection for 2020–2050 shows that the magnitude of the negative demographic effect on annual economic growth due to the population onus is −0.385 on average among all sample economies. The main policy implication of this study is that the EU economies that have already entered the population onus phase of the demographic transition need to mitigate the negative effects of the decline in the working-age population share.

Analysis of the Dynamic Relationship between Green Economy Efficiency and Urban Land Development Intensity in China.

The improvement of green economic efficiency (GEE) should be realized under reasonable urban land development intensity (ULDI). Improving GEE can also help alleviate the negative externalities of excessive or unreasonable ULDI. Clarifying the interactive response mechanism between GEE and ULDI is a key link in regional sustainable development. Therefore, this paper uses the super-efficiency slack-based model (SBM) method, panel entropy method, and panel vector auto regression model to comprehensively analyze the interactive response relationship between GEE and ULDI in 283 prefecture-level cities in China from 2003 to 2019. This paper finds that: (1) during the research period, both the GEE and ULDI showed a relatively obvious upward trend, which is manifested in the fact that ULDI increased year by year while GEE overall increased in volatility. The growth and evolution trend of ULDI and GEE has the characteristics of interaction and coordination; (2) there is a two-way interactive Granger causality between ULDI and GEE, showing a positive interactive response effect; and (3) both ULDI and GEE have positive inertial growth and self-enhancement mechanisms. In the long run, GEE has a greater impact on the change of ULDI.

The dynamic effects of debt and equity inflows: Evidence from emerging and developing countries

This paper shows that inflows of foreign debt and equity have different (asymmetric) effects on consumption, investment, and GDP growth in emerging and developing economies. By using panel VAR analysis based on quarterly macroeconomic data from 1995Q1 to 2015Q4, my results indicate that debt inflows increase consumption, investment and GDP growth on impact, but decrease investment and GDP growth in later periods (i.e., after around a year) for several quarters. Equity inflows, on the other hand, do not have a significant impact on consumption, investment, and GDP growth in emerging and developing countries on average. I also account for cross-country heterogeneity by splitting my sample into two groups based on their (i) real GDP per capita and (ii) governance quality. I find that countries with lower governance quality benefit from debt inflows in terms of increased consumption, investment and GDP growth in the short run, but are hurt by reduction in all of these indicators in the medium run. The findings regarding equity inflows indicate that, although their effects are not so much destabilizing as those of debt inflows, policymakers in higher income emerging countries might still need to be attentive, since an equity inflow shock in these countries seems to have a somewhat negative effect on investment and GDP growth in later periods following a positive impact effect on consumption and GDP growth.

Penalized estimation of panel vector autoregressive models: A panel LASSO approach

This paper proposes LASSO estimation specific for panel vector autoregressive (PVAR) models. The penalty term allows for shrinkage for different lags, for shrinkage towards homogeneous coefficients across panel units, for penalization of lags of variables belonging to another cross-sectional unit, and for varying penalization across equations. The penalty parameters therefore build on time series and cross-sectional properties that are commonly found in PVAR models. Simulation results point towards advantages of using the proposed LASSO for PVAR models over ordinary least squares in terms of forecast accuracy. An empirical forecasting application including 20 countries supports these findings.

Examining macroprudential policy and its macroeconomic effects – Some new evidence

In this paper, we provide empirical evidence about the response of macroprudential policy to financial risks, as well as the broader macroeconomic effects of macroprudential policy and the underlying transmission mechanism. To this end, we use structural panel vector autoregressions and a dataset covering 32 advanced and emerging economies. We find that positive credit shocks are generally met with tighter macroprudential policy. Moreover, whereas macroprudential policy shocks mostly affect residential investment and household credit, monetary policy shocks have more widespread effects on the economy. We also show that macro-financial country characteristics such as the exchange rate regime and the level of financial development affect both the policy response to credit shocks and the macroeconomic effects of macroprudential policy.

Dynamic Shocks of Crude Oil Price and Exchange Rate on Food Prices in Emerging Countries of Southeast Asia: A Panel Vector Autoregression Model

This paper empirically analyzes food price responses to shocks from crude oil price and exchange rate volatility in five emerging Southeast Asian nations between 2000 and 2020 using impulse response functions and variance decomposition analysis of the dynamic panel Vector Autoregression approach. Based on the findings of the impulse response functions analysis, food prices respond positively to both oil price and exchange rate shocks. Meanwhile, the results of variance decomposition analysis show that food prices account for a significant portion of volatility in its own shock. The contribution of oil price shock to food price volatility is found to be greater than the contribution of exchange rate shock. Hence, the study recommends that policymakers in these nations should be vigilant about the impacts of oil price and exchange rate shocks on food prices since these factors may undermine price stability and exacerbate food security.

Understanding the dynamic relationship between smart city implementation and urban sustainability

Understanding the dynamic relationship between Smart City Implementation (SCI) and urban sustainability can provide an effective reference for future SCI for urban sustainability. This study explored this relationship using data from 77 smart cities in China from 2012 to 2017. The coupling coordination degree model was used to evaluate coordinated development levels of smartness and sustainability, and the Panel Vector Auto-Regression (PVAR) model was adopted to explore how three dimensions of smartness, Information and Communication Technologies (ICT), human capital, and smart governance, dynamically influence urban sustainability. Further, the 77 smart cities were classified according to SCI status, economic development level, and population density to conduct the PVAR model. Results showed that the two subsystems of urban smartness and sustainability are coordinated, and coordinated degrees exhibited an upward trend. The impacts of ICT, human capital, and smart governance on urban sustainability differed in smart cities with different contexts. ICT and smart governance had a long-term positive impact on urban sustainability, while human capital did not have an overall significantly positive impact. Policy implications are proposed to better implement smart city initiatives for urban sustainability.