The asymmetric impact of exchange rate changes on bilateral trade balance: evidence from China and its trade partners

The purpose of this paper is to re-examine the impact of exchange rate changes on the trade balance of China and its major trading partners. In the past, many studies have been focussed on the linear effect of exchange rate change, but in this paper, a non-linear Autoregressive Distribution Lag (NARDL) model is proposed. Empirical results show that there are nonlinear and asymmetric effects on the trade balance of exchange rate. In particular, the effect of exchange rate appreciation on Sino-US trade balance is more significant than that of depreciation. A genuine devaluation of the domestic currency would improve the balance of the domestic trade. However, the opposite effect is found in the case of Sino- Japan and the Euro, and the depreciation of the currency will make the trade balance worse. These results provide a solid basis for understanding the relation of exchange rate variation and trade balance. In terms of economic reality, it is also a useful reference for adjusting exchange rate and commercial policy

Designing Fully Distributed Consensus Protocols for Linear Multi-agent Systems with Directed Graphs

This paper addresses the distributed consensus protocol design problem for multi-agent systems with general linear dynamics and directed communication graphs. Existing works usually design consensus protocols using the smallest real part of the nonzero eigenvalues of the Laplacian matrix associated with the communication graph, which however is global information. In this paper, based on only the agent dynamics and the relative states of neighboring agents, a distributed adaptive consensus protocol is designed to achieve leader-follower consensus for any communication graph containing a directed spanning tree with the leader as the root node. The proposed adaptive protocol is independent of any global information of the communication graph and thereby is fully distributed. Extensions to the case with multiple leaders are further studied.Comment: 16 page, 3 figures. To appear in IEEE Transactions on Automatic Contro

Estimating Cumulative Treatment Effects in the Presence of Nonproportional Hazards

Often in medical studies of time to an event, the treatment effect is not constant over time. In the context of Cox regression modeling, the most frequent solution is to apply a model that assumes the treatment effect is either piecewise constant or varies smoothly over time, i.e., the Cox nonproportional hazards model. This approach has at least two major limitations. First, it is generally difficult to assess whether the parametric form chosen for the treatment effect is correct. Second, in the presence of nonproportional hazards, investigators are usually more interested in the cumulative than the instantaneous treatment effect (e.g., determining if and when the survival functions cross). Therefore, we propose an estimator for the aggregate treatment effect in the presence of nonproportional hazards. Our estimator is based on the treatment-specific baseline cumulative hazards estimated under a stratified Cox model. No functional form for the nonproportionality need be assumed. Asymptotic properties of the proposed estimators are derived, and the finite-sample properties are assessed in simulation studies. Pointwise and simultaneous confidence bands of the estimator can be computed. The proposed method is applied to data from a national organ failure registry.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/65785/1/j.1541-0420.2007.00947.x.pd

Compost Process and Organic Fertilizers Application in China

Composting is an inexpensive and sustainable treatment for solid wastes. The composting industry has been growing rapidly because of a boom in the animal industry in China over the past decades. In this chapter, we introduce composting process and status in China, especially in Jiangsu Province. Meanwhile, the developed novel spectroscopy techniques are also introduced, which are more suitable for assessment of compost maturity than the conventional techniques in view of ease of sample preparation, rapid spectrum acquisition, and nondestructive nature of the analysis. These novel spectroscopy techniques include near-infrared reflectance spectroscopy (NIRS)––partial least squares (PLS) analysis and fluorescence excitation–emission matrix (EEM) spectroscopy––parallel factor (PARAFAC) analysis. In addition, organic fertilizer amendments can not only improve soil fertility but also offset chemical fertilizers’ nanoscale changes. Emerging cutting-edge technologies of synchrotron-based X-ray absorption fine structure (XAFS) spectroscopy and nanoscale secondary ion mass spectrometry (NanoSIMS) were used to identify the composition of organic carbon and minerals and their correlations, respectively. Recently, investigators have shown that organic fertilizer amendments could enhance the production of highly reactive minerals, for example, allophane, imogolite, and ferrihydrite, which further benefit for soil carbon storage and soil fertility improvement

Analysis of Automobile Data Flow

The trend of automobile development is safety, energy saving and environmental protection. Due to the developmentand application of new technologies such as electronic technology, computer technology and information technology,the electronic control of automobile has made great progress in the control precision, scope, adaptability andintelligence and realized the fully optimized operation of the automobile. Therefore, in the reduction of emissions,reduce fuel consumption, improve safety and comfort and many other aspects of electronic control technology hasobvious advantages. This is bound to require a large number of sensors in the car. These miniature sensors are smallenough to enable a wide range of new features, high-volume and high-precision production, low cost and easy to formlarge-scale and multi-function arrays that make them ideal for automotive applications

Semiparametric Methods for Estimating Cumulative Treatment Effects in the Presence of Non-proportional Hazards and Dependent Censoring.

The research in this thesis focuses on methods for estimating the cumulative treatment effect on time to an event in the setting when the treatment-specific hazards are not proportional. In clinical studies of time to event data, non-proportional hazards are very common. The Cox model is frequently used, assuming that the treatment effect is constant or a specific function of time. However, it is often difficult to assess whether the functional form chosen for the treatment effect is correct. Even if the correct form is chosen, the cumulative (as opposed to the instantaneous) treatment effect is preferred in many applications. For example, the investigator may be interested in the contrast in 5-year survival between the treatment groups. We propose three novel methods for estimating cumulative treatment effects. In Method I, we propose a treatment-stratified Cox model. The ratio of cumulative hazards comparing treatment categories is proposed to estimate the cumulative treatment effect. This measure has a hazard ratio interpretation when proportional hazard holds. In Method II, we consider the setting where, in addition to the treatment effect, the effect of the adjustment covariates may be non-proportional. We propose an inverse probability of treatment weighting (IPTW) method to balance the distribution of adjustment covariates among treatment groups. The ratio of cumulative hazards, relative risk and difference in restricted mean lifetime are proposed as measures of the cumulative treatment effect for Method II. Method III deals with the setting where the event time and censoring time are dependent. We employ double inverse weighting, with an inverse probability of censoring weight (IPCW) to counteract the dependent censoring from time-varying covariates, and IPTW to adjust for baseline covariates. Each of Methods I, II and III is applied to organ failure data.Ph.D.BiostatisticsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/61786/1/ghwei_1.pd

Suitability analysis for implementing wind and solar farms based AHP method: Case study in Inner Mongolia, China

As important green energy, wind power and photovoltaic power have great development prospects. The suitability evaluation of wind and solar power plants is a popular research field, which is related to the sustainable and healthy development of wind and solar power generation. In this paper, based on multiple dimensions such as land types, climatic conditions, topographic features and policy environment, we selected 10 indicators and combined (analytical hierarchy process) AHP method to build a suitability assessment model for evaluating the suitability of solar and wind power in Inner Mongolia, China. The findings revealed that, Inner Mongolia has a great potential to generate wind and solar electricity, for wind power, the category of ‘excellent’ regions covers 83855 km2 and represents 7.10% of the total surface area; for solar power, 7.66% (nearly 90420 km2) are classified as ‘excellent’. The suitability of both solar and wind energy in the western region is considered to have the most suitable development region, parts of Alxa League and Bayannur City have great potential for combined wind and solar power generation. The research results could provide important technical and data support for capacity evaluation and power station location decision