电商下乡促进了县域经济增长吗？

以电子商务为代表的现代化商品流通渠道建设是当前农村经济发展的新动能。利用2013—2018年县域数据,以“电子商务进农村综合示范县”为自然实验,采用多期PSM-DID方法探讨了电商下乡对县域经济增长的影响。研究结果显示,电商下乡对县域经济增长具有显著的促进作用。异质性分析表明,电商下乡对中部、西部和东北地区县域经济增长具有显著的正向影响,对经济发展落后、财政依赖度高、信息化水平低以及产业结构不合理的县域具有更加明显的经济拉动效应。进一步研究发现,电商下乡推动了县域第一产业和第二产业的发展,且主要通过提高地区农业生产率、吸引企业进入以及改善融资环境产生影响。因此,应加快推进电子商务在农村的发展,把以电子商务为代表的现代流通渠道建设与电商下乡试点地区的特色农业和制造业相结合,进一步探索县域传统产业与数字经济的融合方式,以促进县域经济增长。     

On a sequential subset selection procedure for the least probable multinomial cell

This paper studies a sequential procedure R for selecting a random size subset that contains the multinomial cell which has the smallest cell probability. The stopping rule of the proposed procedure R is the composite of the stopping rules of curtailed sampling, inverse sampling, and the Ramey-Alam sampling. A reslut on the worst configuration is shown and it is employed in computing the procedure parameters that guarantee certain probability requirements. Tables of these procedure parameters, the corresponding probability of correct selection, the expected sample size, and the expected subset size are given for comparison purpose.     

Semiparametric estimation for seasonal long-memory time series using generalized exponential models

We consider a generalized exponential (GEXP) model in the frequency domain for modeling seasonal long-memory time series. This model generalizes the fractional exponential (FEXP) model [Beran, J., 1993. Fitting long-memory models by generalized linear regression. Biometrika 80, 817–822] to allow the singularity in the spectral density occurring at an arbitrary frequency for modeling persistent seasonality and business cycles. Moreover, the short-memory structure of this model is characterized by the Bloomfield [1973. An exponential model for the spectrum of a scalar time series. Biometrika 60, 217–226] model, which has a fairly flexible semiparametric form. The proposed model includes fractionally integrated processes, Bloomfield models, FEXP models as well as GARMA models [Gray, H.L., Zhang, N.-F., Woodward, W.A., 1989. On generalized fractional processes. J. Time Ser. Anal. 10, 233–257] as special cases. We develop a simple regression method for estimating the seasonal long-memory parameter. The asymptotic bias and variance of the corresponding long-memory estimator are derived. Our methodology is applied to a sunspot data set and an Internet traffic data set for illustration.     

A Comparison of Selected Artificial Neural Networks that Help Auditors Evaluate Client Financial Viability

This study compares the performance of three artificial neural network (ANN) approaches—backpropagalion, categorical learning, and probabilistic neural network—as classification tools to assist and support auditor's judgment about a client's continued financial viability into the future (going concern status). ANN performance is compared on the basis of overall error rates and estimated relative costs of misclassificaticn (incorrectly classifying an insolvent firm as solvent versus classifying a solvent firm as insolvent). When only the overall error rate is considered, the probabilistic neural network is the most reliable in classification, followed by backpropagation and categorical learning network. When the estimated relative costs of misclassification are considered, the categorical learning network is the least costly, followed by backpropagation and probabilistic neural network.