Asymptotic Variance Estimator for Two-Step Semiparametric Estimators

The goal of this paper is to develop techniques to simplify semiparametric inference. We do this by deriving a number of numerical equivalence results. These illustrate that in many cases, one can obtain estimates of semiparametric variances using standard formulas derived in the already-well-known parametric literature. This means that for computational purposes, an empirical researcher can ignore the semiparametric nature of the problem and do all calculations "as if" it were a parametric situation. We hope that this simplicity will promote the use of semiparametric procedures.Two-step semiparametrics

A Practical Asymptotic Variance Estimator for Two-Step Semiparametric Estimators

The goal of this paper is to develop techniques to simplify semiparametric inference. We do this by deriving a number of numerical equivalence results. These illustrate that in many cases, one can obtain estimates of semiparametric variances using standard formulas derived in the already-well-known parametric literature. This means that for computational purposes, an empirical researcher can ignore the semiparametric nature of the problem and do all calculations “as if” it were a parametric situation. We hope that this simplicity will promote the use of semiparametric procedures

Asymptotic Efficiency of Semiparametric Two-step GMM

In this note, we characterize the semiparametric efficiency bound for a class of semiparametric models in which the unknown nuisance functions are identified via nonparametric conditional moment restrictions with possibly non-nested or over-lapping conditioning sets, and the finite dimensional parameters are potentially over-identified via unconditional moment restrictions involving the nuisance functions. We discover a surprising result that semiparametric two-step optimally weighted GMM estimators achieve the efficiency bound, where the nuisance functions could be estimated via any consistent nonparametric procedures in the first step. Regardless of whether the efficiency bound has a closed form expression or not, we provide easy-to-compute sieve based optimal weight matrices that lead to asymptotically efficient two-step GMM estimators

Experimental Assessment on the Hysteretic Behavior of a Full-Scale Traditional Chinese Timber Structure Using a Synchronous Loading Technique

In traditional Chinese timber structures, few tie beams were used between columns, and the column base was placed directly on a stone base. In order to study the hysteretic behavior of such structures, a full-scale model was established. The model size was determined according to the requirements of an eighth grade material system specified in the architectural treatise Ying-zao-fa-shi written during the Song Dynasty. In light of the vertical lift and drop of the test model during horizontal reciprocating motions, the horizontal low-cycle reciprocating loading experiments were conducted using a synchronous loading technique. By analyzing the load-displacement hysteresis curves, envelope curves, deformation capacity, energy dissipation, and change in stiffness under different vertical loads, it is found that the timber frame exhibits obvious signs of self-restoring and favorable plastic deformation capacity. As the horizontal displacement increases, the equivalent viscous damping coefficient generally declines first and then increases. At the same time, the stiffness degrades rapidly first and then decreases slowly. Increasing vertical loading will improve the deformation, energy-dissipation capacity, and stiffness of the timber frame

Metric-based Few-shot Classification in Remote Sensing Image

Target recognition based on deep learning relies on a large quantity of samples, but in some specific remote sensing scenes, the samples are very rare. Currently, few-shot learning can obtain high-performance target classification models using only a few samples, but most researches are based on the natural scene. Therefore, this paper proposes a metric-based few-shot classification technology in remote sensing. First, we constructed a dataset (RSD-FSC) for few-shot classification in remote sensing, which contained 21 classes typical target sample slices of remote sensing images. Second, based on metric learning, a k-nearest neighbor classification network is proposed, to find multiple training samples similar to the testing target, and then the similarity between the testing target and multiple similar samples is calculated to classify the testing target. Finally, the 5-way 1-shot, 5-way 5-shot and 5-way 10-shot experiments are conducted to improve the generalization of the model on few-shot classification tasks. The experimental results show that for the newly emerged classes few-shot samples, when the number of training samples is 1, 5 and 10, the average accuracy of target recognition can reach 59.134%, 82.553% and 87.796%, respectively. It demonstrates that our proposed method can resolve fewshot classification in remote sensing image and perform better than other few-shot classification methods

The effect of the revision of intangible assets accounting standards on enterprise technology innovation

Against the institutional background of building an innovative country, this article constructs the influence mechanism of the accounting standards for intangible assets for enterprise technology innovation. We select panel data from the Shanghai Stock Exchange and Shenzhen Stock Exchange from 2002 to 2015. We focus on the two dimensions of innovation input and innovation output and use Poisson regression, negative binomial regression, zero expansion regression, and other methods to examine the effects of the revision of the intangible assets accounting standards on enterprise technology innovation. Our research reveals the following: (1) In general, the revision of the intangible assets accounting standards can promote enterprises’ technological innovation activities; (2) This effect is heterogeneous by ownership: before the revision of accounting standards for intangible assets, state-owned enterprises had more innovation input than non-state-owned enterprises, but the innovation output of nonstate-owned enterprises has become greater than that of stateowned enterprises even though the policy only significantly improved the innovation output of the latter; and (3) The system lacks a continuous effect. The revision of the intangible assets accounting standards has only a one-year lag effect on the incentive effect of enterprise innovation input activities, mainly because enterprise innovation input has only a one- to two-year lag effect on output. The implementation of this system has not changed the status quo that Chinese patent rights are based on applied short-term technology research and development. Based on the findings, this article proposes some pertinent policy suggestions