Health diagnosis of ultrahigh arch dam performance using heterogeneous spatial panel vector model

Currently,more than ten ultrahigh arch dams have been constructed or are being constructed in China.Safety control is essential to long-term operation of these dams.This study employed the flexibility coefficient and plastic complementary energy norm to assess the structural safety of arch dams.A comprehensive analysis was conducted,focusing on differences among conventional methods in characterizing the structural behavior of the Xiaowan arch dam in China.Subsequently,the spatiotemporal characteristics of the measured performance of the Xiaowan dam were explored,including periodicity,convergence,and time-effect characteristics.These findings revealed the governing mechanism of main factors.Furthermore,a heterogeneous spatial panel vector model was developed,considering both common factors and specific factors affecting the safety and performance of arch dams.This model aims to comprehensively illustrate spatial heterogeneity between the entire structure and local regions,introducing a specific effect quantity to characterize local deformation differences.Ultimately,the proposed model was applied to the Xiaowan arch dam,accurately quantifying the spatiotemporal heterogeneity of dam performance.Additionally,the spatiotemporal distri-bution characteristics of environmental load effects on different parts of the dam were reasonably interpreted.Validation of the model prediction enhances its credibility,leading to the formulation of health diagnosis criteria for future long-term operation of the Xiaowan dam.The findings not only enhance the predictive ability and timely control of ultrahigh arch dams'performance but also provide a crucial basis for assessing the effectiveness of engineering treatment measures.

How R&D investment promotes green technology innovation in the context of digitalization?-An empirical analysis based on provincial panel data

Green technology innovation is an important driving force and source to promote my country’s high-quality development,and it is the core path to achieve sustainable development.This paper uses my country’s provincial panel data from 2016 to 2019 to study the impact mechanism of R&D investment on green technology innovation,and introduces the level of digitization,using the panel threshold model to discuss its role in the impact mechanism of R&D investment on green technology innovation.The study found that when the level of digitalization in a region is low,increasing R&D investment does not necessarily improve the ability of green technology innovation;when the level of digitalization is relatively high,R&D investment has a positive role in promoting green technology innovation.Therefore,it is necessary to improve policies to encourage enterprises to increase investment in research and development;at the same time,it is necessary to promote the coordinated development of digital foundation,digital investment,digital literacy,digital economy and digital application,and promote the deep integration of digitalization and green technology innovation.

A Study on the Relationship Between Land Finance and Housing Price in Urbanization Process: An Empirical Analysis of 182 Cities in China Based on Threshold Panel Models

Scholars have a variety of theoretical explanations for housing price growth. However, few scholars have studied the internal influence mechanism among urbanization, land finance, and housing price. Based on the data of 182 prefecture-level cities from 2009 to 2016, this paper studies the influence of land finance on housing price under different urbanization rate levels. The study finds that with the increase of urbanization rate, the effect of land finance on housing price presents a "U" shape.Specifically, an increase in land finance by 1% results in a corresponding increase in average housing price by 0.18%, with relatively low urbanization rate, 0.06% with medium level of urbanization rate,and 0.38% with high level of urbanization rate.

Panel data models with cross-sectional dependence: a selective review

In this review, we highlight some recent methodological and theoretical develop- ments in estimation and testing of large panel data models with cross-sectional dependence. The paper begins with a discussion of issues of cross-sectional dependence, and introduces the concepts of weak and strong cross-sectional dependence. Then, the main attention is primarily paid to spatial and factor approaches for modeling cross-sectional dependence for both linear and nonlinear （nonparametric and semiparametric） panel data models. Finally, we conclude with some speculations on future research directions.

Empirical Research on the Relationship between Education Poverty Alleviation and Rural Revitalization—Spatial Panel Simultaneous Equation Model Based on Provincial Panel Data

On the basis of using entropy weight method to measure China’s education poverty alleviation and rural revitalization evaluation indicators, using the panel data of 30 provinces in China (excluding Xizang, Hong Kong, Macao and Taiwan) from 2012 to 2021, a spatial panel simultaneous equation model is constructed based on adjacency matrix, geographical distance matrix and economic geographical distance matrix deeply study the interaction mechanism and spatial spillover effects between education poverty alleviation and rural revitalization through the generalized spatial three-stage least squares method (GS3SLS). The results indicate that there is a significant spatial spillover effect and a positive spatial correlation between education poverty alleviation and rural revitalization, and there is a significant interactive effect between the two variables, while promoting each other positively. Therefore, the government should clarify the deep relationship between education poverty alleviation and rural revitalization based on the current background, and better consolidate and expand the effective connection between the achievements of education poverty alleviation and rural revitalization.

Brent vs.West Texas Intermediate in the US petro derivatives price formation

In this paper,we apply the spatial panel model to explore the relationship between the dynamic of two types of crude oil prices(WTI and Brent crude oil)and their refined products over time.Considering the turbulent months of 2011,when Cushing Oklahoma had reached capacity and the crude oil export ban removal in 2015 as breakpoints,we apply this method both in the full sample and the three resultant regimes.First,results suggest our results show that both WTI and Brent display very similar behaviour with the refined products.Second,when attending to each regime,results derived from the first and third regimes are quite similar to the full sample results.Therefore,during the second regime,Brent crude oil became the benchmark in the petrol market,and it influenced the distillate products.Furthermore,our model can let us determine the price-setters and price-followers in the price formation mechanism through refined products.These results possess important considerations to policymakers and the market participants and the price formation.

Impacts of agri-food e-commerce on traditional wholesale industry:Evidence from China

Rapidly expanding studies investigate the effects of e-commerce on company operations in the retail market.However,the interaction between agri-food e-commerce(AEC)and the traditional agri-food wholesale industry(AWI)has not received enough attention in the existing literature.Based on the provincial panel data from 2013 to 2020 in China,this paper examines the effect of AEC on AWI,comprising three dimensions:digitalization(DIGITAL),agrifood e-commerce infrastructure and supporting services(AECI),and agri-food e-commerce economy(AECE).First,AWI and AEC are measured using an entropy-based combination of indicators.The results indicate that for China as a whole,AWI has remained practically unchanged,whereas AEC exhibits a significant rising trend.Second,the findings of the fixed-effect regression reveal that DIGITAL and AECE tend to raise AWI,whereas AECI negatively affects AWI.Third,threshold regression results indicate that AECI tends to diminish AWI with three-stage inhibitory intensity,which manifests as a first increase and then a drop in the inhibition degree.These results suggest that with the introduction of e-commerce for agricultural product circulation,digital development will have catfish effects that tend to stimulate the vitality of the conventional wholesale industry and promote technical progress.Furthermore,the traditional wholesale industry benefits financially from e-commerce even while it diverts part of the traditional wholesale circulation for agricultural products.

Spatiotemporal characteristics of cultivated land use eco-efficiency and its influencing factors in China from 2000 to 2020

Improving cultivated land use eco-efficiency(CLUE)can effectively promote agricultural sustainability,particularly in developing countries where CLUE is generally low.This study used provincial-level data from China to evaluate the spatiotemporal evolution of CLUE from 2000 to 2020 and identified the influencing factors of CLUE by using a panel Tobit model.In addition,given the undesirable outputs of agricultural production,we incorporated carbon emissions and nonpoint source pollution into the global benchmark-undesirable output-super efficiency-slacks-based measure(GB-US-SBM)model,which combines global benchmark technology,undesirable output,super efficiency,and slacks-based measure.The results indicated that there was an upward trend in CLUE in China from 2000 to 2020,with an increase rate of 2.62%.The temporal evolution of CLUE in China could be classified into three distinct stages:a period of fluctuating decrease(2000-2007),a phase of gradual increase(2008-2014),and a period of rapid growth(2015-2020).The major grain-producing areas(MPAs)had a lower CLUE than their counterparts,namely,non-major grain-production areas(non-MPAs).The spatial agglomeration effect followed a northeast-southwest strip distribution;and the movement path of barycentre revealed a"P"shape,with Luoyang City,Henan Province,as the centre.In terms of influencing factors of CLUE,investment in science and technology played the most vital role in improving CLUE,while irrigation index had the most negative effect.It should be noted that these two influencing factors had different impacts on MPAs and non-MPAs.Therefore,relevant departments should formulate policies to enhance the level of science and technology,improve irrigation condition,and promote sustainable utilization of cultivated land.

A review of mid-frequency vibro-acoustic modelling for highspeed train extruded aluminium panels as well as the most recent developments in hybrid modelling techniques

The present paper reviews the vibro-acoustic modelling of extruded aluminium train floor structures including the state-of-the-art of its industrial applications, as well as the most recent developments on mid-frequency mod- elling techniques in general. With the common purpose to predict mid-frequency vibro-acoustic responses of stiffened panel structures to an acceptable accuracy at a reasonable computational cost, relevant techniques are mainly based on one of the following three types of mid-frequency vibro- acoustic modelling principles： （1） enhanced deterministic methods, （2） enhanced statistical methods, and （3） hybrid deterministic/statistical methods. It is shown that, although recent developments have led to a significant step forward in industrial applicability, mature and adequate prediction tech- niques, however, are still very much required for solving sound transmission through, and radiation from, extruded aluminium panels used on high-speed trains. Due to their great potentials for predicting mid-frequency vibro-acoustics of stiffened panel structures, two of recently developed mid-frequency modelling approaches, i.e. the so-called hybrid finite element-statistical energy analysis （FE-SEA） and hybrid wave-based method- statistical energy analysis （WBM-SEA）, are then recapitulated.

Spatial spillover effects of official development assistance on environmental pressure in sub-Saharan African(SSA)countries

Impoverished sub-Saharan Africa(SSA)is under increasing environmental pressure from global environmental changes.It is now generally accepted in academic circles that economic development in SSA countries can cause environmental pressure in other countries.However,there is research gap on the impact of economic assistance on environmental pressure in SSA countries and whether economic assistance causes spatial spillovers of environ-mental pressure between SSA countries.To better understand the impact of economic assistance on environmental pressures in SSA,a dynamic spatial Dubin panel model was developed.It helped us explore the spatial spillover effects of economic assistance on environmental pressures in recipient countries based on the panel data from 34 SSA countries.The results show that economic assistance had a positive stimulating effect on environmen-tal pressures of recipient countries,which means that the degree of human disturbance to the environment has deepened.Due to the regional correlation effect,neighboring countries were saddled with environmental pres-sures from the target country.Moreover,environmental pressures have time inertia,which can easily produce a snowball effect.The decomposition of effects shows that the impact of economic assistance on environmental pressures is relatively minor.Environmental pressures have spillover effects,so to deal with diffuse risks,joint regional prevention and control policies should be developed.

An Empirical Study of the Relationship among Population Mobility Industrial Structure Upgrading, and Economic Growth-Based on the SPVAR Model

Based on the inter-provincial panel data for 31 provinces in China from 2000 to 2019,and incorporating geospatial factors,a spatial panel vector autoregressive(SPVAR)model consisting of population mobility,industrial structure upgrading,and economic growth is constructed.The space-time impulse response function is used to analyze the space-time conduction of exogenous variables on the impact of three endogenous variables.The study found that first,the population influx barely benefited the industrial structure upgrading and economic growth.Second,the upgrading of the industrial structure would aggravate the population mobility in the province,causing low-level laborers to leave the province in shortterm,but in long-term,there would be influx of talents.Third,the economic growth in developed regions plays a significant role in promoting the industrial development of their province and population-rich provinces,but it has less impact on provinces with high-level industrial structure.Finally,policy recommendations are provided in regard to the benign interaction among population mobility,industrial structure upgrading,and economic growth in addition to clarifying the idea of economic development,implementing correct population policies,and promoting the coordinated regional development.

Dynamic change of agricultural energy efficiency and its influencing factors in China

In order to practice the concept of‘lucid waters and lush mountains are invaluable assets’and promote the green development of agriculture,it is necessary to improve the efficiency of agricultural energy utilization.Based on the panel data of 28 provinces from 1995 to 2018,this paper calculated China’s agricultural energy input from two categories of direct energy and indirect energy,and used EBM(Epsilon-based Measure)mixed distance function model to measure the energy efficiency of agriculture in China.The nuclear density function and spatial autocorrelation were used to analyze the dynamic evolution of agricultural energy efficiency,and the dynamic panel model was used to analyze the influencing factors of agricultural energy efficiency.The results showed that:①From 1995 to 2018,the total agricultural energy input had increased year by year in China,with an average annual growth rate of 2%.Energy input structure changed from indirect energy-based to direct energy-based.Agricultural energy efficiency showed an evolutionary trend of‘rising-stagnating-rising rapidly’in China.The agricultural energy efficiency was generally low in China,and there was a large space for improvement in agricultural energy efficiency.②From 1995 to 2018,the average annual growth rate of agricultural energy efficiency in the eastern,central and western regions was 2.7%,1.9%and 1.4%respectively.In 2018,the agricultural energy efficiency in the eastern,central and western regions was 0.81,0.71 and 0.59 respectively.The gap between regions was expanding rapidly,and the agricultural energy efficiency in the central and western regions needed to be improved.③From 1995 to 2018,the agricultural energy efficiency of each province was polarized and the absolute gap was widened.There was obvious improvement in agricultural energy efficiency in Guangdong,Shandong,Jiangxi,Jiangsu,Liaoning and Tianjin,while the agricultural energy efficiency of Xinjiang,Guizhou,Zhejiang,Shanghai,and Inner Mongolia deteriorated.④From 1995 to 2018,there was no global spatial correlation of China’s agricultural energy efficiency.However,local‘high-high’concentration gradually appeared in the eastern region since 2010.⑤The first lag of energy efficiency had a significant positive impact on agricultural energy efficiency,and agricultural energy efficiency improvement had a time lag.The level of human capital,per capita net income of farmers and the level of urbanizaton had a significant positive impact on agricultural energy efficiency.The disaster rate,the level of development of secondary and tertiary industries,and the level of opening up had a significant negative impact on agricultural energy efficiency.In the implementation of the strategy of rural revitalization,we should focus on the central and western regions,take the cultivation of professional farmers as the key,focus on improving agricultural production conditions,enhance the level of cooperation between regions,exert the leading role of the secondary and tertiary industries,and enhance the ability of agricultural disaster prevention and mitigation.

Effect of China’s technology spillovers on energy intensity in Africa

Empirical studies on the effects of China-African economic relations on energy intensity in Africa are scarce.To fill the gap in the literature,this study investigates the technology spillover effects of the China-Africa trade and investment relations on energy intensity.It uses both linear and nonlinear dynamic panel estimation methods for 42 African countries from 2003 to 2015.The results show that China's technology spillover through imports significantly reduces energy intensity in Africa.The findings are consistent across specifications and sample groups.Moreover,the technology spillover coming from foreign direct investment(FDI)improves energy intensity,particularly in lower-middle-income African countries.The dynamic threshold estimation results show that countries'absorptive ability is important for technology spillover effects of FDI and imports on energy intensity.The results suggest that countries'absorptive capacity should be increased to maximize the benefits of trade and investment technology spillovers.

Estimate on spillover effect of environmental pollution between peripheral areas

Interaction of environmental pollution between peripheral areas has become a central topic in the field of resources and environment but little is known about the actual impact on peripheral areas in the current literature.This paper sets out a simultaneous equation model to investigate the spillover effect of environmental pollution between China's peripheral areas utilizing the panel data of 218 cities in China.Making use of indicators for measuring the impact on environmental pollution,it identifies that environmental pollution between cities of China has a significant two-way spillover effect.After standardization of variables,it is found that the spillover effect of peripheral areas on urban environmental pollution cannot be neglected.Nearly,a third of the environmental pollution level in a city is induced by the environmental pollution in peripheral areas.If the indicator of environmental pollution in peripheral areas is missing,wrong conclusions will be drawn.Therefore,government should shift the emphasis of environmental regulation from local to global,and improve the overall environmental quality through coordinated management of regional environment.

Global Risk Appetite,US Economic Policy Uncertainties and Cross-Border Capital Flow

Based on the global asset portfolio model,this paper created a panel threshold model using EPFR fund data to empirically test the non-linear spillover effects of US economic policy uncertainties on cross-border capital flow for emerging economies.Our study led to the following findings:(1)When the level of global investor risk tolerance is high,rising US EPU will induce a capital inflow into emerging economies,as manifested in the“portfolio rebalancing effect.”When the level of global investor risk tolerance is below a critical threshold,this gives rise to risk aversion and emerging economies will experience net capital outflow,i.e.the“flight to quality effect”.(2)Equity fund investors have a lower risk tolerance threshold than bond fund investors.(3)According to our heterogeneity analysis,more attention should be paid to monitoring capital flow through actively managed funds,ETF funds,and retail investor funds.The economy should increase financial efficiency and economic resiliency to mitigate capital outflow pressures from the external environment.

Spatial transmission and meteorological determinants of tuberculosis incidence in Qinghai Province,China:a spatial clustering panel analysis

Background:Tuberculosis(TB)is the notifiable infectious disease with the second highest incidence in the Qinghai province,a province with poor primary health care infrastructure.Understanding the spatial distribution of TB and related environmental factors is necessary for developing effective strategies to control and further eliminate TB.Methods:Our TB incidence data and meteorological data were extracted from the China Information System of Disease Control and Prevention and statistical yearbooks,respectively.We calculated the global and local Moran’s I by using spatial autocorrelation analysis to detect the spatial clustering of TB incidence each year.A spatial panel data model was applied to examine the associations of meteorological factors with TB incidence after adjustment of spatial individual effects and spatial autocorrelation.Results:The Local Moran’s I method detected 11 counties with a significantly high-high spatial clustering(average annual incidence:294/100000)and 17 counties with a significantly low-low spatial clustering(average annual incidence:68/100000)of TB annual incidence within the examined five-year period;the global Moran’s I values ranged from 0.40 to 0.58(all P-values<0.05).The TB incidence was positively associated with the temperature,precipitation,and wind speed(all P-values<0.05),which were confirmed by the spatial panel data model.Each 10°C,2 cm,and 1 m/s increase in temperature,precipitation,and wind speed associated with 9%and 3%decrements and a 7%increment in the TB incidence,respectively.Conclusions:High TB incidence areas were mainly concentrated in south-western Qinghai,while low TB incidence areas clustered in eastern and north-western Qinghai.Areas with low temperature and precipitation and with strong wind speeds tended to have higher TB incidences.

A dynamic panel data approach and HCW's method:Assessing the effect of China(Shanghai)Free Trade Zone on local GDP

We propose a simple-to-implement dynamic panel data method to evaluate the impacts of place-based policies.The idea is to exploit both the cross sectional dependence and the serial correlation within a panel and implement a semi difference-in-difference decomposition.Different from the method by Hsiao et al.(2012),the proposed model is easy to implement statistical inferences and can incorporate multiple treated groups at different time thresholds.We use the proposed method to explore the effect of the Free Trade Zone(FTZ)policy implemented in Shanghai at the end of 2013 on local GDP growth rate and compare it with that from Hsiao et al.(2012).The empirical results show that the FTZ does have a positive effect on the local GDP growth rate and it adds 1:21:8 percent point to the growth rate of the GDP per capita for Shanghai in 2014 which is about one fourth to one third of the total GDP growth rate per capita.This effect largely comes from the growth of the tertiary sector.The results lend support to the duplication of FTZ policy to other cities and provinces in China.

A Fluctuation Test for Structural Change Detection in Heterogeneous Panel Data Models

Structural change in panel data is a widespread phenomena. This paper proposes a fluctuation test to detect a structural change at an unknown date in heterogeneous panel data models with or without common correlated effects. The asymptotic properties of the fluctuation statistics in two cases are developed under the null and local alternative hypothesis. Furthermore, the consistency of the change point estimator is proven. Monte Carlo simulation shows that the fluctuation test can control the probability of type I error in most cases, and the empirical power is high in case of small and moderate sample sizes. An application of the procedure to a real data is presented.

Macro Debt Burden and Consumption Expansion:An Analysis Based on Panel Model and Panel Quantile Regression Model

As the level of social credit burden rises,to ease the liquidity constraint for residents is currently an important way to boost the domestic demand in China.This paper uses the panel data of Chinese provincial-level administrative units in 2007−2017 and adopts the panel regression model and panel quantile regression model to empirically analyze the relationship between debt burden level and average propensity to consume(APC).The result shows that increase in the level of macro debt burden can significantly improve the APC of residents;the marginal promoting effect of macro debt burden for the APC is in a V-shaped structure;such marginal influence differs evidently in different areas,with the marginal promoting effect turning out most prominent in the northeast of China.Accordingly,it’s suggested for government to keep refining the credit market,increase residents’income in multiple means,guide supply of liquidity towards the real economy and promote equalization of basic public services,so as to realize the expansion and upgrade of consumption.

Decomposing the drivers of residential space cooling energy consumption in EU-28 countries using a panel data approach

While space cooling currently represents less than 1%of final energy use in the residential sector of the Euro-pean Union(EU-28),it was the fastest growing end-use during the 2000-15 period with a mean annual growth rate of 6%per year.Currently,little is known about factors which have driven regional air-conditioning(AC)energy consumption over time,since the literature is limited to cross-sectional studies that lack differentiation between climatic and non-climatic influences.Future projections for the EU’s electricity sector may therefore neglect the potential implications of rapidly growing AC demand.We develop a novel decomposition framework,which breaks down residential space cooling energy consumption in EU-28 countries into the effect of different components from 2000 to 2015.Decomposition is extended to panel data models identifying specific drivers of space cooling’s climate-sensitive components.Finally,we explore scenarios of residential AC energy consumption up to 2050 and evaluate their impact on summer time peak loads.AC diffusion was found to be the key driver of space cooling energy consumption,but this effect was partly counterbalanced by efficiency gains.While weather influences AC equipment ownership rate in EU-28 households,personal income has a larger marginal effect.In baseline scenarios,AC diffusion saturates by 2050,while modestly increasing sectoral final energy use.Still,our range of scenario values for space cooling energy consumption in 2050 exceed the majority of those originat-ing from recently published projections.In a future renewables-driven electricity system,energy security risks may emerge from a scenario of fast AC up-take in new and renovated buildings,especially for colder European countries where modelled peak cooling electricity demand is shown to outgrow the projected expansion of solar capacity.These findings have important implications for the EU’s strategy to decarbonise energy supply.