This paper studies nonparametric estimation of conditional moment restrictions in which the generalized residual functions can be nonsmooth in the unknown functions of endogenous variables. This is a ...nonparametric nonlinear instrumental variables (IV) problem. We propose a class of penalized sieve minimum distance (PSMD) estimators, which are minimizers of a penalized empirical minimum distance criterion over a collection of sieve spaces that are dense in the infinite-dimensional function parameter space. Some of the PSMD procedures use slowly growing finite-dimensional sieves with flexible penalties or without any penalty; others use large dimensional sieves with lower semicompact and/or convex penalties. We establish their consistency and the convergence rates in Banach space norms (such as a sup-norm or a root mean squared norm), allowing for possibly noncompact infinite-dimensional parameter spaces. For both mildly and severely ill-posed nonlinear inverse problems, our convergence rates in Hubert space norms (such as a root mean squared norm) achieve the known minimax optimal rate for the nonparametric mean IV regression. We illustrate the theory with a nonparametric additive quantile IV regression. We present a simulation study and an empirical application of estimating nonparametric quantile IV Engel curves.
The improvement of regional eco-efficiency is a significant approach to achieve coordinated development of China's economic development and environmental protection, and an effective environmental ...regulation system is a crucial driver to the improvement of regional eco-efficiency. Based on the panel data of China's 30 provinces during 2000–2013, this paper divides environmental regulation into three types: command-and-control regulation, market-based regulation and voluntary regulation. STIRPAT model is employed to test the effects of these three environmental regulations on eco-efficiency in the eastern, central and western regions of China. Research results turn out that: (1) in the eastern region, market-based and voluntary environmental regulation have a positive impact on eco-efficiency improvement while command-and-control environmental regulation has no significant impact, and (2) in the central region, command-and-control and market-based environmental regulation can promote eco-efficiency more significantly compared with voluntary environmental regulation, and (3) in the western region, command-and-control environmental regulation plays a positive role in eco-efficiency improvement whilst market-based and voluntary environmental regulation have no significant impacts. These findings indicate that the effects of different types of environmental regulation on eco-efficiency apparently differ in regions. Finally, to optimize and adjust the environmental regulation tools, policy recommendations targeting different regions are concluded.
•The different effects of three types of environmental regulation on China's regional eco-efficiency are analyzed.•The effect of environmental regulation displays regional difference.•Environmental regulation has a dynamic impact on regional eco-efficiency.
The (2+1)-dimensional Lax integrable equation is decomposed into solvable ordinary differential equations with the help of known (1+1)-dimensional soliton equations associated with the ...Ablowitz-Kaup-Newell-Segur soliton hierarchy. Then, based on the finite-order expansion of the Lax matrix, a hyperelliptic Riemann surface and Abel-Jacobi coordinates are introduced to straighten out the associated flows, from which the algebro-geometric solutions of the (2+1)-dimensional integrable equation are proposed by means of the Riemann θ functions.
The current study provides and tests an integrated model that examines two relationship quality constructs (overall customer satisfaction, customer-company identification) as mediating variables ...between Chinese tourists' lodging service quality perceptions and two outcomes (repurchase intentions, subjective well-being). The results of a study with domestic Chinese hotel guests (n = 451) provide support for the proposed model. Specifically, the results indicate that overall customer satisfaction fully mediates the relationship between perceived service quality and repurchase intentions and subjective well-being, respectively. Customer-company identification partially mediates the relationship between perceived service quality and repurchase intentions and subjective wellbeing, respectively. We provide empirical validation that customers do, indeed, identify with hospitality providers, and this, in-turn, provides positive consequences for both the service provider (i.e., repurchase intentions) and the customer (i.e., subjective well-being). Managerial implications are provided, limitations noted, and future research directions suggested.
•We propose and test an integrated model with domestic Chinese hotel guests.•Satisfaction fully mediates antecedent and outcome relationships.•Identification partially mediates antecedent and outcome relationships.•Hospitality firms can help satisfy self-definitional needs.•Identification provides positive consequences.
Simultaneous-source shooting can help tremendously shorten the acquisition period and improve the quality of seismic data for better subsalt seismic imaging, but at the expense of introducing strong ...interference (blending noise) to the acquired seismic data. We propose to use a structural-oriented median filter to attenuate the blending noise along the structural direction of seismic profiles. The principle of the proposed approach is to first flatten the seismic record in local spatial windows and then to apply a traditional median filter (MF) to the third flattened dimension. The key component of the proposed approach is the estimation of the local slope, which can be calculated by first scanning the NMO velocity and then transferring the velocity to the local slope. Both synthetic and field data examples show that the proposed approach can successfully separate the simultaneous-source data into individual sources. We provide an open-source toy example to better demonstratethe proposed methodology.
•We propose a novel structural-oriented median filter to attenuate the blending noise.•We flatten the seismic record in local spatial windows followed by MF in flattened dimension.•The local slope can be accurately estimated from velocity-slope transformation.•Several simulated synthetic and field data examples show the successful performance.•An open-source toy example to better demonstrate the proposed methodology.
•The residential indirect CO2 emissions display regional difference.•We decompose the urbanization variable from the SDA model.•Urbanization increases residential indirect CO2 emissions in ...China.•Consumption structure increases residential indirect CO2 emissions in China.
Based on analysis of input–output energy and household expenditure data (IO-EA-expenditure), this paper calculates China’s indirect carbon emissions from residential consumption in 2002 and 2007, by region. Then a new Structural Decomposition Analysis (SDA) model is proposed to investigate the regional variations of impacts of urbanization, consumption ratio and consumption structure on residential indirect CO2 emissions in China during 2002–2007. As the results suggest, expansion of urbanization and upgrade of consumption structure play important roles in the growth of residential indirect emissions. Transformation of consumption ratio, contributing the most to emissions in the eastern region, reduces indirect emissions in all regions to a certain extent. The persistent decline of carbon emission intensity still contributes significantly to the decrease in emissions and the rise of per capita consumption plays a dominant role in the growth of residential indirect emissions. Based on empirical results, this article provides policy suggestions which can help reduce China’s residential indirect CO2 emissions.
By employing China’s provincial panel data covering period 2001–2016, the present study empirically investigates the impact of ICT on CO
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emission intensity. Specifically, this paper utilizes ...Internet penetration and mobile phone penetration as proxies to measure ICT respectively and employs quantile regression method to estimate the benchmark model at five quantiles (0.1, 0.25, 0.5, 0.75, and 0.9). It is demonstrated that Internet penetration at the national level has a significant negative effect on the CO
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emission intensity for all quantiles. In addition, Internet penetration has a significant negative effect on CO
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emission intensity at all quantiles except for 0.1 quantile for China’s eastern provinces and has a significant negative effect on CO
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emission intensity at all quantiles for China’s central provinces, whereas Internet penetration has no significant negative impact on CO
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emission intensity at all quantiles for China’s western provinces. By comparison, the reduction effect of Internet penetration on CO
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emission intensity in China’s eastern and central provinces is more obvious and in contrast with the reduction effect of Internet penetration on CO
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emission intensity in China’s eastern provinces, it is greater in China’s central provinces. Finally, the impact of mobile phone penetration on CO
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emission intensity is generally consistent with the impact of Internet penetration. This study provides further evidence that developing countries can simultaneously achieve economic development and reduce carbon emissions through ICT.
SUMMARY
In seismic data processing, the median filter is usually applied along the structural direction of seismic data in order to attenuate erratic or spike-like noise. The performance of a ...structure-oriented median filter highly depends on the accuracy of the estimated local slope from the noisy data. When local slope contains significant error, which is usually the case for noisy data, the structure-oriented median filter will still cause severe damages to useful energy. We propose a type of structure-oriented median filter that can effectively attenuate spike-like noise even when the local slope is not accurately estimated, which we call structure-oriented space-varying median filter. A structure-oriented space-varying median filter can adaptively squeeze and stretch the window length of the median filter when applied in the locally flattened dimension of an input seismic data in order to deal with the dipping events caused by inaccurate slope estimation. We show the key difference among different types of median filters in detail and demonstrate the principle of the structure-oriented space-varying median filter method. We apply the structure-oriented space-varying median filter method to remove the spike-like blending noise arising from the simultaneous source acquisition. Synthetic and real data examples show that structure-oriented space-varying median filter can significantly improve the signal preserving performance for curving events in the seismic data. The structure-oriented space-varying median filter can also be easily embedded into an iterative deblending procedure based on the shaping regularization framework and can help obtain much improved deblending performance.
•A novel approach to flood risk assessment based on random forest (RF).•The approach can be used to estimate the contribution of each risk index.•Proposed approach is shown to be effective by a case ...study.
Floods, natural disasters that occur worldwide, have become more and more frequent in recent decades. Flooding is often unavoidable and unexpected; however, it can be controlled through appropriate measures to minimize losses and damage. Flood hazard risk assessment, a holistic approach that involves numerous evaluation indices in river catchments, is an increasingly effective and sustainable practice, but the complicated, non-linear relationship between evaluation indices and risk levels pose a significant challenge to accurate assessment. An intelligent learning machine called random forest (RF) can run efficiently on large databases and provide estimates regarding the importance of specific variables in the classification. This lends RF a considerable advantage in solving the non-linear problems inherent to risk assessment, as well as estimating the importance degree of each index. As such, in this study, an assessment model based on RF was adopted to evaluate regional flood hazard risk. The proposed flood hazard risk assessment method was implemented in Dongjiang River Basin, China. Eleven risk indices were selected and five thousand samples were created for training and testing. The support vector machine (SVM) was used for risk assessment as a comparison, as well as an analysis of index importance degree. Results show that (1) both the training and testing error rate of RF can be reduced by increasing the sample size and the number of classification trees, (2) the higher and highest-risk zones occupy approximately 19.09% of the total, and are primarily located in Baoan, Longgang, Huiyang, Huidong, the western area of Boluo, and the southern part of Dongguang, and (3) the indices maximum three-day precipitation (M3PD), runoff depth (RD), typhoon frequency (TF), digital elevation model (DEM), and topographic wetness index (TWI) are the top five most important out of the eleven risk indices, occupying 71.11% of the total risk; but normalized difference vegetation index (NDVI), stream power index (SPI), soil texture (ST), distance to the river (DR), slope (SL), and land use pattern (LUP) indices are less consequential, at only 28.89%. This study shows the potential to provide a novel and highly successful approach to flood hazard risk assessment. Evaluation results provide a reference for flood risk management, prevention, and reduction of natural disasters in the study basin.
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