不同经济阶段人民币汇率对通货膨胀的非对称传递效应——基于NARDL两步估计模型

通过构建NARDL两步估计框架,实证研究了经济周期的不同阶段中人民币汇率对通货膨胀传递的非对称性。研究结果表明:在模型优化方面,NARDL两步估计突破了单步估计的渐进奇异性问题,估计的精确性更高;在汇率非对称传递规律方面,整个样本期内汇率波动对通货膨胀水平的总体传递效应的非对称性主要集中在长期,人民币不管是升值还是贬值都会加剧中国的通货膨胀,且通货膨胀对汇率的贬值更为敏感;在经济周期的不同阶段,汇率贬值的影响仍然强于升值,但汇率升值传递效应在不同的宏观经济状况下表现出较大的波动幅度,且汇率变动在经济收缩阶段对通货膨胀呈现出更为强烈的传递效应。

The convergence ball and error analysis of the two-step Secant method

Under the assumption that the nonlinear operator has Lipschitz continuous divided differences for the first order,we obtain an estimate of the radius of the convergence ball for the two-step secant method.Moreover,we also provide an error estimate that matches the convergence order of the two-step secant method.At last,we give an application of the proposed theorem.

Whether the digital economy will successfully encourage the integration of urban and rural development: A case study in China

The digital economy has become an important driver for stimulating economic growth.The digital economy has now widely penetrated the fields of economy and society,providing new opportunities for the develop‐ment of urban-rural integration.Based on panel data for 30 provinces in China from 2011 to 2020,this study constructed an index system for the integration of the digital economy and the development of urban-rural areas and conducted a systematic measurement analysis.Additionally,we used a two-step system of GMM estimation to analyze the impact of the digital economy on the development of urban-rural integra‐tion.The findings demonstrate the significant imbalance paradox of China’s digital economy development,which is shown in a gradient where the eastern region is higher than the center and the central region is higher than the west.Urban-rural integration levels in China fluctuate and display geographical variance,typically displaying high levels in the east and low levels in the west.Urban-rural integration is significantly encouraged by the digital economy,yet it varies in variability between different areas and dimensions.Addi‐tionally,rural human capital moderates the favorable effects of the digital economy on urban-rural integra‐tion.As a result,in order to achieve the integrated development of urban and rural areas,it is imperative to fully exploit the active role of the digital economy,better support the development of rural revitalization,bridge the“digital divide”between urban and rural development,and build a strong foundation for the for‐mation of a digital urban-rural integrated development pattern with urban and rural areas and common con‐struction and sharing.

Does financial development moderate the link between technological innovation and environmental indicators?An advanced panel analysis

This study analyzes the role of financial development(FD)on the impact of technologi-cal innovation(TI)on six environmental quality indicators for the 25 economies that are part of the Organization for Economic Cooperation and Development for the period from 2000 to 2019.We use a two-step dynamic generalized method of moments approach to understand this relationship.The results show that FD augments the posi-tive effects of TI on four of the six environmental indicators,namely ecological foot-print,adjusted net savings,pressure on nature,and environmental performance.However,no significant effects on environmental sustainability and environmental vulnerability indices were found.When considering all of the environmental quality indicators,TI appears to enhance environmental quality.We find evidence to support the existence of the environmental Kuznets curve in the context of each environmen-tal indicator and economic growth.Moreover,FD and energy consumption appear to accelerate environmental degradation.Based on these results,FD should be viewed as an important parameter in designing policies for innovation to achieve the goal of net-zero carbon emissions.Highlights.Technological innovation and environmental quality nexus is studied.The moderating role of financial development is analyzed.Six different environmental quality indicators are used for OECD countries.Financial development intensifies the environmental benefits of innovation.•The EKC hypothesis is confirmed for all six environmental indicators.

Two-step Estimation for Longitudinal Data When the Working Correlation Matrix is a Linear Combination of Some Known Matrices

The generalized estimating equations(GEE) approach is perhaps one of the most widely used methods for longitudinal data analysis. While the GEE method guarantees the consistency of its estimators under working correlation structure misspecification, the corresponding efficiency can be severely affected. In this paper, we propose a new two-step estimation method in which the correlation matrix is assumed to be a linear combination of some known working matrices. Asymptotic properties of the new estimators are developed.Simulation studies are conducted to examine the performance of the proposed estimators. We illustrate the methodology with an epileptic data set.

Speech enhancement based on modified a priori SNR estimation

To solve the frame delay problem and match the previous frame,Plapous et al.[IEEE Transactions on Audio,Speech,and Language Processing,2006,14(6):2098–2108]introduced a novel approach called two-step noise reduction(TSNR)technique to improve the performance of the speech enhancement system.However,TSNR approach results in spectral peaks of short duration and the broken spectral outlier,which degrade the spectral characteristics of the speech.To solve this problem,a cepstral smoothing step is added in order to remove these spectral peaks brought by TSNR approach.Theory analysis shows that the proposed approach can effectively smooth the spectral peaks and keep the spectral outlier so as to protect the speech characteristics.Experiment results also show that the proposed approach can bring significant improvement compared to decision-directed(DD)and TSNR approaches,especially in non-stationary noisy environments.

A two-step method for estimating high-dimensional Gaussian graphical models

The problem of estimating high-dimensional Gaussian graphical models has gained much attention in recent years. Most existing methods can be considered as one-step approaches, being either regression-based or likelihood-based. In this paper, we propose a two-step method for estimating the high-dimensional Gaussian graphical model. Specifically, the first step serves as a screening step, in which many entries of the concentration matrix are identified as zeros and thus removed from further consideration. Then in the second step, we focus on the remaining entries of the concentration matrix and perform selection and estimation for nonzero entries of the concentration matrix. Since the dimension of the parameter space is effectively reduced by the screening step,the estimation accuracy of the estimated concentration matrix can be potentially improved. We show that the proposed method enjoys desirable asymptotic properties. Numerical comparisons of the proposed method with several existing methods indicate that the proposed method works well. We also apply the proposed method to a breast cancer microarray data set and obtain some biologically meaningful results.

Fully discrete two-step mixed element method for the symmetric regularized long wave equation

A numerical method based on the explicit two-step method in time direction and the mixed finite element method in spatial direction is presented for the symmetric regularized long wave(SRLW)equation.The optimal a priori error estimates(O((∆t)^(2)+h^(m+1)+h^(k+1)))for fully discrete explicit two-step mixed scheme are derived.Moreover,a numerical example is provided to confirm our theoretical results.