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.

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.

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.

Semi-Varying Coefficient Panel Data Model with Technical Indicators Predicts Stock Returns in Financial Market

Accurately predicting stock returns is a conundrum in financial market.Solving this conundrum can bring huge economic benefits for investors and also attract the attention of all circles of people.In this paper the authors combine semi-varying coefficient model with technical analysis and statistical learning,and propose semi-varying coefficient panel data model with individual effects to explore the dynamic relations between the stock returns from five companies:CVX,DFS,EMN,LYB,and MET and five technical indicators:CCI,EMV,MOM,ln ATR,ln RSI as well as closing price(ln CP),combine semi-parametric fixed effects estimator,semi-parametric random effects estimator with the testing procedure to distinguish fixed effects(FE) from random effects(RE),and finally apply the estimated dynamic relations and the testing set to predict stock returns in December 2020 for the five companies.The proposed method can accommodate the varying relationship and the interactive relationship between the different technical indicators,and further enhance the prediction accuracy to stock returns.

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.

Tea Production Response to Seasonal Rainfall Variability: Evidence from Rwanda

Tea is a very important cash crop in Rwanda, as it provides crucial income and employment for farmers in poor rural areas. From 2017 to 2020, this study was intended to determine the impact of seasonal rainfall on tea output in Rwanda while still considering temperature, plot size (land), and fertiliser for tea plantations in three of Rwanda’s western, southern, and northern provinces, western province with “Gisovu” and “Nyabihu”, southern with “Kitabi”, and northern with “Mulindi” tea company. The study tested the level of statistical significance of all considered variables in different formulation of panel data models to assess individual behaviour of independent variables that would affect tea production. According to this study, a positive change in rainfall of 1 mm will increase tea production by 0.215 percentage points of tons of fresh leaves. Rainfall is a statistically significant variable among all variables with a positive impact on tea output Qitin Rwanda’s Western, Southern, and Northern provinces. Rainfall availability favourably affects tea output and supports our claim. Therefore, there is a need for collaboration efforts towards developing sustainable adaptation and mitigation options against climate change, targeting tea farming and the government to ensure that tea policy reforms are targeted towards raising the competitiveness of Rwandan tea at local and global market.

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.

Direct energy rebound effect for road transportation in China

The enhancement of energy efficiency stands as the principal avenue for attaining energy conservation and emissions reduction objectives within the realm of road transportation.Nevertheless,it is imperative to acknowledge that these objectives may,in part or in entirety,be offset by the phenomenon known as the energy rebound effect(ERE).To quantify the long-term EREs and short-term EREs specific to China’s road transportation,this study employed panel cointegration and panel error correction models,accounting for asymmetric price effects.The findings reveal the following:The long-term EREs observed in road passenger transportation and road freight transportation range from 13%to 25%and 14%to 48%,respectively;in contrast,the short-term EREs in road passenger transportation and road freight transportation span from 36%to 41%and 3.9%to 32%,respectively.It is noteworthy that the EREs associated with road passenger transportation and road freight transportation represent a partial rebound effect,falling short of reaching the magnitude of a counterproductive backfire effect.This leads to the inference that the upsurge in energy consumption within the road transportation sector cannot be solely attributed to advancements in energy efficiency.Instead,various factors,including income levels,the scale of commodity trade,and industrial structure,exert more substantial facilitating influences.Furthermore,the escalation of fuel prices fails to dampen the demand for energy services,whether in the domain of road passenger transportation or road freight transportation.In light of these conclusions,recommendations are proffered for the formulation of energy efficiency policies pertinent to road transportation.

Uncovering the Relationship between FDI,Human Capital and Technological Progress in Chinese High-technology Industries

Using a panel dataset for 28 sub-industries from 5 Chinese industries from 1995 to 2006, this paper examines the impact of human capital, R＆D expenditure and FD1 spillover on the productivity improvement of Chinese high-technology industries. The whole industry sample results suggest that human capital promotes total factor productivity, technical change and technical efficiency change, but that FDI lowers all of these factors in Chinese high-technology industry. When we distinguish between types of ownership structure in the industries, we find that human capital improves technical change but lowers technical efficiency change, whereas FDI only improves technical efficiency change in state-owned and state-controlled enterprises but reduces technical change in state-owned and state-controlled enterprises and joint ventures.

How does Bank Capital Affect Bank Profitability and Risk？ Evidence from China＇s WTO Accession

This paper examines how bank capital affects bank profitability and risk in China, and how its impact differed before and after the nation entered the WTO. Our study uses the dynamic generalized method of moments approach with a panel database containing 171 Chinese commercial banks. We ftnd that bank capital has significant influence on bank profitability and risk, but its impact has declined since China joined the WTO in 2001. For different sized groups, the impact of capital on profitability exhibits a distinct trend. The effects of capital on bank risk are different for large and small banks depending on the risk variables used for the Chinese banking industry.

Inter-industry Technology Spillover Effects in China:Evidence from 35 Industrial Sectors

The present paper calculates 35 industrial sectors similarity matrices for the period of 1997-2008 using China s input-output tables for 1997, 2002 and 2007, and uses these to measure inter-industry technology spillover to analyze the spillover effects on industrial sectors lahor productivity. The empirical analysis shows that inter-industry technology spillover has a significant positive effect on the labor productivity of each industry. The elasticity of productivity effects of inter-industry technology spillover is not only larger than that of direct R＆D input, but also increases over time. We group the industries into four major categories and find that the inter-industry technology spillover effect within the categories is, on average, greater than that between the four categories, indicating that technology spillover occurs more easily between similar industries. This research shows that the interindustry technology spillover effect in China has begun to increase, and the government should take advantage of this effect.

Chinese decentralization and income inequality between urban and rural residents--An empirical study based on the dual dimensions of internal and external budget

The paper firstly explains the mechanism of decentralization on income inequality from two theoretical dimensions of internal and external budget.Based on the re-measurement of income Gini coefficient and Chinese decentralization level,this paper establishes panel data model from national and regional perspective to empirically investigate the impact of Chinese decentralization on income inequality between urban and rural residents.Firstly,the promotion of budgetary income decentralization is conductive to reduce income inequality of urban and rural residents whether it is from the national or sub regional.Second,although the promotion of budgetary expenditure decentralization exacerbates the urban-rural income inequality in the national level,it could obviously reduce the urban-rural income inequality in the midwest with relatively low level of budgetary expenditure decentralization.Thirdly,the impact of extra-budgetary decentralization on income inequality is consistent,no matter in the whole country,in eastern or in western regions.This means that the extra-budgetary income decentralization makes the income inequality between urban and rural residents worse while the extra-budgetary expenditure decentralization reduces the income inequality between urban and rural residents with different degrees.Fourthly,the transfer payment,years of schooling and urban unemployment rate are conductive to narrow the income inequality between urban and rural residents while the impacts of economic development,urbanization and opening degree are obviously different in different regions.The above conclusions can not only be used for reference to further perfecting and reshaping the fair efficiency mechanism of Chinese decentralization,but also indicates the direction of the new fiscal and tax system reform.