China at the Crossroad:Creating the Asian Single Currency or Internationalizing RMB

I am going to concentrate my concern on the discussion of the diversification of the existing world currency system, because in the view of the majority of Chinese economists it is closely linked to the future directions and destinations of China’s domestic financial reform, to China’s policies regarding Asia’s financial collaborations, and to the positioning of RMB in the world in the coming years. It is almost commonly accepted among Chinese economists that China is on the way to form its international financial strategies that contain three objectives: properly re-visiting the Bretton Woods system in today’s context, actively pushing foreward the region-wide financial cooperation of an Asian single currency as a core, and gradually internalizing RMB.international financial crisis; financial system reform; RMB inter¬nationalization; exchange rate

Normalized Power Prior Bayesian Analysis

The elicitation of power prior distributions is based on the availability of historical data, and is realized by raising the likelihood function of the historical data to a fractional power. However, an arbitrary positive constant before the like- lihood function of the historical data could change the inferential results when one uses the original power prior. This raises a question that which likelihood function should be used, one from raw data, or one from a su±cient-statistics. We propose a normalized power prior that can better utilize the power parameter in quantifying the heterogeneity between current and historical data. Furthermore, when the power parameter is random, the optimality of the normalized power priors is shown in the sense of maximizing Shannon's mutual information. Some comparisons between the original and the normalized power prior approaches are made and a water-quality monitoring data is used to show that the normalized power prior is more sensible.Bayesian analysis, historical data, normalized power prior, power prior, prior elicitation, Shannon's mutual information.

Robust Estimation of High-Dimensional Mean Regression

Data subject to heavy-tailed errors are commonly encountered in various scientific fields, especially in the modern era with explosion of massive data. To address this problem, procedures based on quantile regression and Least Absolute Deviation (LAD) regression have been devel- oped in recent years. These methods essentially estimate the conditional median (or quantile) function. They can be very different from the conditional mean functions when distributions are asymmetric and heteroscedastic. How can we efficiently estimate the mean regression functions in ultra-high dimensional setting with existence of only the second moment? To solve this problem, we propose a penalized Huber loss with diverging parameter to reduce biases created by the traditional Huber loss. Such a penalized robust approximate quadratic (RA-quadratic) loss will be called RA-Lasso. In the ultra-high dimensional setting, where the dimensionality can grow exponentially with the sample size, our results reveal that the RA-lasso estimator produces a consistent estimator at the same rate as the optimal rate under the light-tail situation. We further study the computational convergence of RA-Lasso and show that the composite gradient descent algorithm indeed produces a solution that admits the same optimal rate after sufficient iterations. As a byproduct, we also establish the concentration inequality for estimat- ing population mean when there exists only the second moment. We compare RA-Lasso with other regularized robust estimators based on quantile regression and LAD regression. Extensive simulation studies demonstrate the satisfactory finite-sample performance of RA-Lasso

Economic valuation of development projects : a case study of a non-motorized transport project in India

One of the major difficulties in doing cost-benefit analysis of a development project is to estimate the total economic value of project benefits, which are usually multi-dimensional andinclude goods and services that are not traded in the market. Challenges also arise in aggregating the values of different benefits, which may not be mutually exclusive. This paper uses a contingent valuation approach to estimate the economic value of a non-motorized transport project in Pune, India, across beneficiaries. The heads of households which are potentially affected by the project are presented with a detailed description of the project, and then are asked to vote on whether such a project should be undertaken given different specifications of costs to the households. The total value of the project is then derived from the survey answers. Econometric analysis indicates that the survey responses provide generally reasonable valuation estimates.Transport Economics Policy&Planning,Environmental Economics&Policies,Roads&Highways,Housing&Human Habitats,Economic Theory&Research

SCORE EQUATING BETWEEN AEPS-2 AND AEPS-3 FOR 0-3 YEAR OLDS

Over the past two decades, the emphasis on educational equity in early childhood education (ECE) and early childhood special education (ECSE) has highlighted the importance of assessment through policies and regulations. Ensuring accurate assessment scores is a fundamental aspect of this trend. The release of the Assessment, Evaluation, and Programming System for Infants and Children, Third Edition (AEPS-3) in December 2021 led to a shift from the Second Edition (AEPS-2) in child development scoring. In order to harmonize the previous and updated assessment versions for children aged 0-3 across six developmental domains, a common item non-equivalent design, featuring fixed parameter calibration equating (known as \u27anchoring\u27), is utilized within the Rasch framework. A total of 18,411 cases from the AEPS-2 Test Level I and 317 cases from the AEPS-3 Test were utilized to assess scale quality. The psychometric properties of both assessment versions were evaluated using the rating scale Rasch model, revealing a good model-data fit. Two sets of anchor items, selected based on either identical or functional matching methods, were determined using the cosine similarity coefficient and subsequently validated through expert content analysis. These anchor item sets demonstrated acceptable quality. The research then examined the impact of different anchor sets on person parameter estimation during the anchoring process. Ultimately, the study produced person measure and observed score conversion tables between AEPS-2 and AEPS-3. The resulting conversion tables provide valuable insights into the relationship between the old and updated assessment versions. These findings contribute to equating methodology, ECE/ECSE, and education policy. As an early implementation of functional matching anchoring equating in the ECSE field, this study provides a practical model for score equating transformation that can be applied across both early childhood education and special education sectors. In the early childhood education area, it supports the ongoing refinement of assessment tools in early childhood education, helping practitioners make more informed decisions about child development. By leveraging the psychometric model, the research contributes to improving the quality of assessment tools for early childhood education practitioners, leading to better outcomes for children in these critical developmental stages. Another important contribution of this study is that it reflects the assessment requirements in special education and connects education policy with research goals. This ensures that assessments remain consistent, fair, and accurate, enabling educators and specialists to effectively track and support children\u27s development over time, ultimately improving educational equity

Child Psychology in the Dance Classroom

Child psychology is a discipline that studies the laws of children’s mental activities, and with the improvement of social standards, the application of psychology in children’s education is becoming more and more widespread. This paper takes children’s psychological development as a fulcrum to gain deep insight into children’s psychological characteristics in dance teaching. Taking children as the research object, it studies the specific application of psychology in the process of children’s dance teaching through its own teaching practice

Reasoning About Frame Properties in Object-oriented Programs

Framing is important for specification and verification of object-oriented programs. This dissertation develops the local reasoning approach for framing in the presence of data structures with unrestricted sharing and subtyping. It can verify shared data structures specified in a concise way by unifying fine-grained region logic and separation logic. Then the fine-grained region logic is extended to reason about subtyping. First, fine-grained region logic is adapted from region logic to express regions at the granularity of individual fields. Conditional region expressions are introduced; not only does this allow one to specify more precise frame conditions, it also has the ability to express footprints of separation logic assertions. Second, fine-grained region logic is generalized to a new logic called unified fine-grained region logic by allowing the logic to restrict the heap in which a program runs. This feature allows one to express specifications in separation logic. Third, both fine-grained region logic and separation logic can be encoded to unified fine-grained region logic. This result allows the proof system to reason about programs specified in both styles. Finally, fine-grained region logic is extended to reason about a programming language that is similar to Java. To reason about inheritance locally, a frame condition for behavioral subtyping is defined and proved sound

Fear and Compliance: A Study of Antecedents, Mediators and Benefits of Paternalistic Leadership in China

Paternalistic leadership has been suggested as one prevalent leadership style in China. However, empirical research is limited in investigating the predictive factors as well as its correlations with organisational outcome measures. Drawing upon a total sample of 850 leader-subordinate dyads from mainland China, this research attempts to depict a comprehensive picture of paternalistic leadership, by examining its antecedents, outcomes, mediators, and moderators. Included are three independent empirical studies. Study 1 investigates the antecedents of paternalistic leadership. By examining a cross-lagged model, it is found that followers’ trust-in-supervisor can impact their ratings of leader paternalistic leadership across time, and such impact is further moderated by individual external locus of control by powerful others. In Study 2, by testing a three-way interaction model, it is found that authoritarian leadership has a positive impact on employees’ culture-specific organisational citizenship behaviour; and benevolent leadership and employee resource dependence jointly play critical roles for authoritarian leadership in generating such positive impact. Finally, in Study 3, by investigating a moderated mediation model, authoritarian leadership has been found to negatively impact on followers’ job performance via followers’ fear of their supervisors. This mediation effect is also moderated by follower gender, which demonstrates that the mediation effect only takes place in female followers, but not in male followers. Theoretical and practical limitations and directions for follow-up research are discussed. Overall, the assessment of both antecedents and outcomes of paternalistic leadership in this thesis is essential for the emerging research on paternalistic leadership. Keywords: paternalistic leadership, trust-in-supervisor, fear, resource dependence, job performance, organisational citizenship behaviour

Exploitation of Robust AoA Estimation and Low Overhead Beamforming in mmWave MIMO System

The limited spectral resource for wireless communications and dramatic proliferation of new applications and services directly necessitate the exploitation of millimeter wave (mmWave) communications. One critical enabling technology for mmWave communications is multi-input multi-output (MIMO), which enables other important physical layer techniques, specifically beamforming and antenna array based angle of arrival (AoA) estimation. Deployment of beamforming and AoA estimation has many challenges. Significant training and feedback overhead is required for beamforming, while conventional AoA estimation methods are not fast or robust. Thus, in this thesis, new algorithms are designed for low overhead beamforming, and robust AoA estimation with significantly reduced signal samples (snapshots). The basic principle behind the proposed low overhead beamforming algorithm in time-division duplex (TDD) systems is to increase the beam serving period for the reduction of the feedback frequency. With the knowledge of location and speed of each candidate user equipment (UE), the codeword can be selected from the designed multi-pattern codebook, and the corresponding serving period can be estimated. The UEs with long serving period and low interference are selected and served simultaneously. This algorithm is proved to be effective in keeping the high data rate of conventional codebook-based beamforming, while the feedback required for codeword selection can be cut down. A fast and robust AoA estimation algorithm is proposed as the basis of the low overhead beamforming for frequency-division duplex (FDD) systems. This algorithm utilizes uplink transmission signals to estimate the real-time AoA for angle-based beamforming in environments with different signal to noise ratios (SNR). Two-step neural network models are designed for AoA estimation. Within the angular group classified by the first model, the second model further estimates AoA with high accuracy. It is proved that these AoA estimation models work well with few signal snapshots, and are robust to applications in low SNR environments. The proposed AoA estimation algorithm based beamforming generates beams without using reference signals. Therefore, the low overhead beamforming can be achieved in FDD systems. With the support of proposed algorithms, the mmWave resource can be leveraged to meet challenging requirements of new applications and services in wireless communication systems