Sufficient Statistics Research Articles

Fiscal Capacity: An Asset Pricing Perspective

This review revisits the literature on fiscal capacity using modern tools from asset pricing. We find that properly accounting for aggregate risk substantially reduces fiscal capacity. In this environment, the gap between the risk-free rate and the expected growth rate is not a sufficient statistic for fiscal capacity. To borrow at the risk-free rate when aggregate growth is risky, governments need to ask taxpayers to insure bondholders against aggregate risk, but governments in advanced economies tend to insure taxpayers against aggregate risk. We use this asset pricing perspective to review alternative mechanisms to boost fiscal capacity that have been explored in the literature.

Penerapan Nilai-Nilai Moderasi Beragama Berdasarkan Al-Qur’an Dan Hadist Di MAN 2 Pesisir Selatan

This research aims to analyze the implementation of religious moderation values in the subjects of Islamic Education and Character at MAN 2 Pesisir Selatan based on the Qur'an and Hadith. This study uses a qualitative descriptive method. Primary data was obtained from Islamic Education and Character teachers through interviews and observations, while secondary data was collected through documentation from student and teacher books, lesson plans, and syllabi of Islamic Education and Character subjects under the Merdeka Belajar Curriculum. The research findings indicate that the application of religious moderation values by teachers in the subjects of Islamic Education and Character is done through the use of an additive approach and the development of indicators for achieving the Basic Competencies stated in the lesson plans and syllabi, taking into account the principles of relevance, consistency, and sufficiency. The study also found that the implementation of religious moderation values is carried out through the exemplary behavior of teachers in the school and the community.

Polynomial-Time Constrained Message Passing for Exact MAP Inference on Discrete Models with Global Dependencies

Considering the worst-case scenario, the junction-tree algorithm remains the most general solution for exact MAP inference with polynomial run-time guarantees. Unfortunately, its main tractability assumption requires the treewidth of a corresponding MRF to be bounded, strongly limiting the range of admissible applications. In fact, many practical problems in the area of structured prediction require modeling global dependencies by either directly introducing global factors or enforcing global constraints on the prediction variables. However, this always results in a fully-connected graph, making exact inferences by means of this algorithm intractable. Previous works focusing on the problem of loss-augmented inference have demonstrated how efficient inference can be performed on models with specific global factors representing non-decomposable loss functions within the training regime of SSVMs. Making the observation that the same fundamental idea can be applied to solve a broader class of computational problems, in this paper, we adjust the framework for an efficient exact inference to allow much finer interactions between the energy of the core model and the sufficient statistics of the global terms. As a result, we greatly increase the range of admissible applications and strongly improve upon the theoretical guarantees of computational efficiency. We illustrate the applicability of our method in several use cases, including one that is not covered by the previous problem formulation. Furthermore, we propose a new graph transformation technique via node cloning, which ensures a polynomial run-time for solving our target problem. In particular, the overall computational complexity of our constrained message-passing algorithm depends only on form-independent quantities such as the treewidth of a corresponding graph (without global connections) and image size of the sufficient statistics of the global terms.

Evolution of the EUROFER97 microstructure during thermal treatment up to 122,000 h

Detailed knowledge of the microstructural evolution of reduce activation ferritic-martensitic steel EUROFER97 after exposure at high temperatures is essential for determining its applications potential. For this proposal, EUROFER97 was annealed in the temperature range between 450 °C and 650 °C for up to 122,000 h (≈14 years) and subsequently analyzed using transmission electron microscopy (TEM) including high resolution TEM and two-dimensional energy dispersive X-ray (EDX) mapping. The study demonstrates the effects of thermal treatment on the size and composition of the precipitates and allows conclusions about their stability. Application of the extraction replication technique was used to analyze composition and morphology of four particle types present in the untreated EUROFER97: M23C6, VN, TaC and TiN with sufficient statistics. The rapid coarsening of the M23C6 precipitates was observed at 650 °C, while the MX particles were found to be more stable upon thermal treatment. It has been proved that new Laves (WFe2) and modified Z-phases (Cr(V,Ta)N) precipitates are formed in the temperature range from 500 °C to 600 °C. The detailed analysis allows the drawing a time–temperature formation diagram for these two phases, which could be valid for alloys with composition similar to EUROFER97.

Signal Property Information-Based Target Detection with Dual-Output Neural Network in Complex Environments

The performance of traditional model-based constant false-alarm ratio (CFAR) detection algorithms can suffer in complex environments, particularly in scenarios involving multiple targets (MT) and clutter edges (CE) due to an imprecise estimation of background noise power level. Furthermore, the fixed threshold mechanism that is commonly used in the single-input single-output neural network can result in performance degradation due to changes in the scene. To overcome these challenges and limitations, this paper proposes a novel approach, a single-input dual-output network detector (SIDOND) using data-driven deep neural networks (DNN). One output is used for signal property information (SPI)-based estimation of the detection sufficient statistic, while the other is utilized to establish a dynamic-intelligent threshold mechanism based on the threshold impact factor (TIF), where the TIF is a simplified description of the target and background environment information. Experimental results demonstrate that SIDOND is more robust and performs better than model-based and single-output network detectors. Moreover, the visual explanation technique is employed to explain the working of SIDOND.

Bayes-optimal prediction with frequentist coverage control

This article illustrates how indirect or prior information can be optimally used to construct a prediction region that maintains a target frequentist coverage rate. If the indirect information is accurate, the volume of the prediction region is lower on average than that of other regions with the same coverage rate. Even if the indirect information is inaccurate, the resulting region still maintains the target coverage rate. Such a prediction region can be constructed for models that have a complete sufficient statistic, which includes many widely-used parametric and nonparametric models. Particular examples include a Bayes-optimal conformal prediction procedure that maintains a constant coverage rate across distributions in a nonparametric model, as well as a prediction procedure for the normal linear regression model that can utilize a regularizing prior distribution, yet maintain a frequentist coverage rate that is constant as a function of the model parameters and explanatory variables. No results in this article rely on asymptotic approximations.

Dexter: An R Package to Manage and Analyze Test Data

In this study, we present a package for R that is intended as a professional tool for the management and analysis of data from educational tests and useful both in high-stakes assessment programs and survey research. Focused on psychometric models based on the sum score as the scoring rule and having sufficient statistics for their parameters, dexter fully exploits the many theoretical and practical advantages of this choice: lack of unnecessary assumptions, stable and fast estimation, and powerful and sensible diagnostic techniques. It includes an easy to use data management system tailored to the structure of test data and compatible with the current paradigm of tidy data. Companion packages currently include a graphical user interface and support for multi-stage testing.

Enforcement of Labor Wages Below the Minimum Standard Reviewed from Government Regulation (PP) Number 36 of 2021 concerning Wages and Islamic Law

The implementation of labor wages should be adjusted to the minimum wage set by the government, but the implementation of labor wages below the minimum standard carried out by several companies is interesting to study the implementation of labor wages below the minimum standard that is justified, considering that wages are an important aspect for workers to be able to live a decent life. The suspension of the minimum wage is a way out for companies that have not been able to meet the minimum wage payments. This applies before the passing of the Job Creation Law, where companies can apply for suspension of minimum wage payments to the local Governor/Regional Head. Then in order to ensure the ability and sustainability of a company, Law Number 11 of 2020 concerning Job Creation which was later clarified by PP Number 36 of 2021 concerning Wages contains new provisions, namely that the minimum wage is excluded for micro and small businesses with certain provisions and criteria. In the regulation, it is explained that companies are required to provide wages as the minimum wage that has been determined and there are sanctions for companies that do not run it.Regarding wages in Islamic law, the determination of wages (ujrah) of workers strictly upholds the principles of justice and sufficiency. The main principle of justice lies in the clarity of the contract (transaction) and commitment on the basis of willingness to do it (from the contractor). Therefore, Islam strongly prioritizes the principle of justice in all aspects including economic aspects, especially in determining wages for workers or laborers, so it is necessary to have a work agreement between workers and employers so that there is no arbitrariness of employers against their workers. The provision of time in work determined, as well as the amount of the wage payment system and the reference amount of wages that must be issued, is a very striking general difference from the concept used in Islamic Law and Government Regulation Number 36 of 2021 concerning Wages. Keywords: Wage, Labor, Government Regulation (PP), Islamic Law

Fairness and the Sufficiency Turn in Urban Transport

This commentary considers the research and policy implications of applying the sufficiency principle to urban transport. It explores “enoughness” against a backdrop of increasing carbon emissions in the transport sector, inevitable ceilings for resource intense movement, and the essential requirement of providing access to opportunities in cities. Given the relative lack of progress, increasingly polarizing political debate and urgent requirement for change, this commentary advocates for a more direct and open engagement with a sufficiency turn in urban transport. Most importantly, fundamental questions about a fair distribution of remaining emissions and finite street space within the transport sector must be considered. This engagement can build on the emerging field of transport equity while joining up social justice perspectives of the here and now with sustainability justice recognizing global society, future generations, and nature. While acknowledging the political risks of embracing sufficiency in urban transport, this commentary builds on this rationale and directly engages with the idea of establishing budgets for transport-related carbon emissions and space consumption. It encourages further exploration and presents critical questions for future research and policy practice based on Martens et al.’s (2019) three transport equity components of considering mobility benefits and burdens, considering the disaggregation of social groups, and determining the distribution principle.

Post-Processing of Iterative Estimation and Cancellation Scheme for Clipping Noise in OFDM Systems

Clipping is an efficient and simple method that can reduce the peak-to-average power ratio (PAPR) of orthogonal frequency division multiplexing (OFDM) signals. However, clipping causes in-band distortion referred to as clipping noise. To resolve this problem, a novel iterative estimation and cancellation (IEC) scheme for clipping noise is one of the most popular schemes because it can significantly improve the performance of clipped OFDM systems. However, IEC exploits detected symbols at the receiver to estimate the clipping noise in principle and the detected symbols are not the sufficient statistic in terms of estimation theory. In this paper, we propose the post-processing technique of IEC, which fully exploits given sufficient statistic at the receiver and thus further enhances the performance of a clipped OFDM system as verified by simulations.

Gains from trade liberalization with flexible extensive margin adjustment

We propose a sufficient statistic to measure the ex-post welfare gains from trade in CES models featuring any productivity distribution and any pattern of selection into production and exporting. This statistic is based on a single data moment, the change in the market share of continuing domestic producers, and a single structural parameter, the elasticity of substitution between products. We apply our statistic to measure Canada's gains from the Canada-US Free Trade Agreement using data on observed firm selection. We find that welfare gains can substantially deviate from welfare estimates implied by formulas that assume a constant extensive margin trade elasticity.

Online Smooth Backfitting for Generalized Additive Models

We propose an online smoothing backfitting method for generalized additive models coupled with local linear estimation. The idea can be extended to general nonlinear optimization problems. The strategy is to use an appropriate-order expansion to approximate the nonlinear equations and store the coefficients as sufficient statistics which can be updated in an online manner by the dynamic candidate bandwidth method. We investigate the statistical and algorithmic convergences of the proposed method. By defining the relative statistical efficiency and computational cost, we further establish a framework to characterize the tradeoff between estimation performance and computation performance. Simulations and real data examples are provided to illustrate the proposed method and algorithm. Supplementary materials for this article are available online.

Share of polluting input as a sufficient statistic for burden sharing

By investigating the general equilibrium effects with theoretical analysis and computational experiments, we observe that the value share of polluting input is a sufficient statistic for the welfare incidence of a quantity-based policy in a competitive economy for short-term and commonly implemented mitigation policy. This result is robust with respect to the sectoral, regional disaggregation and consumer preference. In contrast, with a given pollution tax, the imputed welfare incidence could vary under economies with different production technologies and consumer preferences. The quantity-based policy instrument leads to a more explicit welfare incidence than the price instrument. On this basis, outcome-based criteria used in pollution reduction burden sharing across regions can simply choose the value share of polluting input as a reference base for allocation.

Електронні докази - дієві інструменти доказування у кримінальному провадженні

The process of proving is carried out by competent participants of criminal trial in order to establish the truth in criminal proceedings and is an important component of the proceeding. Proving is carried out in compliance with the statutory procedure for criminal proceedings in general, the order of the execution of certain procedural actions and the adoption of procedural decisions, that is within the limits of the criminal procedural form. The modern concept of criminal proceedings is aimed at establishing additional guarantees of observance of the participants’ rights at each stage. The process of proving should be clearly regulated by criminal procedure legislation to ensure the rights of a person in criminal proceedings. The rapid development of the latest information technologies and a significant increase in the number of legal relations in the plane of the information space objectively affected the features of the criminal process. In particular, this applies to such an important category as sources of evidence. In modern conditions of widespread use of information technologies, electronic media are an important and informative source of evidence in criminal proceedings. From theoretical and practical perspectives an important task for scholars is to regulate at the legislative level the methods and procedural proceedings for the legal collection of digital information relevant to criminal proceedings and its further use in compliance with the principles of relevance, admissibility, reliability and sufficiency. The peculiarities of collecting, processing and recording digital evidence are analyzed in the article. It is emphasized that the collection of evidence contained on electronic media can be done by removing the media or information system and by copying the information stored on the corresponding electronic media. The advantages and disadvantages of using digital evidence collection methods are analyzed. Emphasis is placed on the importance of observing the procedural and technical aspects of obtaining information stored on electronic media in order to ensure the possibility of using such information as evidence during criminal proceedings.

A Characterization of Most(More) Powerful Test Statistics with Simple Nonparametric Applications

Data-driven most powerful tests are statistical hypothesis decision-making tools that deliver the greatest power against a fixed null hypothesis among all corresponding data-based tests of a given size. When the underlying data distributions are known, the likelihood ratio principle can be applied to conduct most powerful tests. Reversing this notion, we consider the following questions. (a) Assuming a test statistic, say T, is given, how can we transform T to improve the power of the test? (b) Can T be used to generate the most powerful test? (c) How does one compare test statistics with respect to an attribute of the desired most powerful decision-making procedure? To examine these questions, we propose one-to-one mapping of the term “most powerful” to the distribution properties of a given test statistic via matching characterization. This form of characterization has practical applicability and aligns well with the general principle of sufficiency. Findings indicate that to improve a given test, we can employ relevant ancillary statistics that do not have changes in their distributions with respect to tested hypotheses. As an example, the present method is illustrated by modifying the usual t-test under nonparametric settings. Numerical studies based on generated data and a real-data set confirm that the proposed approach can be useful in practice.

Analyzing Linear DSGE models: the Method of Undetermined Markov States

I show that a class of Linear DSGE models with one endogenous state variable can be represented as a three-state Markov chain. I develop a new analytical solution method based on this representation, which amounts to solving for a vector of Markov states and one transition probability. These two objects constitute sufficient statistics to compute in closed form objects that have routinely been computed numerically: impulse response function, cumulative sum, present discount value multiplier. I apply the method to a standard New Keynesian model that features optimal monetary policy with commitment.

Micro-mechanisms of deformation accommodation in AA7050 alloy in the presence of hydrogen

The interaction of hydrogen with dislocations in AA 7050 alloy heat treated to produce different matrix precipitates is studied using interrupted micro-tensile tests of pre-charged specimens and electron back scattered diffraction (EBSD). Hydrogen promoted slip planarity as well as sub-grain formation in the overaged condition having incoherent ƞ (MgZn2) precipitates, while it enhanced dislocation looping and pitting in case of higher density Mg-Zn precipitates (GP II) dominated alloy. For the first time, a semi-quantitative analysis on the extent of the effect of hydrogen on micro-mechanisms of deformation evolution is carried out using sufficient statistics through large area scans in EBSD. It is shown that the interaction of pre-charged hydrogen with the microstructure was unaffected by recrystallization as well as texture till 6% strain.

Modelling the large and dynamically growing bipartite network of German patents and inventors

Abstract To explore the driving forces behind innovation, we analyse the dynamic bipartite network of all inventors and patents registered within the field of electrical engineering in Germany in the past two decades. To deal with the sheer size of the data, we decompose the network by exploiting the fact that most inventors tend to only stay active for a relatively short period. We thus propose a Temporal Exponential Random Graph Model with time-varying actor set and sufficient statistics mirroring substantial expectations for our analysis. Our results corroborate that inventor characteristics and team formation are essential to the dynamics of invention.

Mechanism for assessing the effects of strategic partnership for the sustainable digital development of transport structures and transportation companies

Aim. The presented study aims to develop methodological approaches to assessing the effects of strategic partnership for the sustainable digital development of transport structures and transportation enterprises.Tasks. The author defines approaches to the sustainable development of entrepreneurial structures, namely: determines the features of the used model of sustainable industrial development and formulates the principles of ensuring sustainability in accordance with the nature of the inter-entrepreneurial infrastructural digital interaction of transport structures and transportation enterprises.Methods. This study uses general scientific methods of cognition in various aspects to investigate approaches to assessing the effects of strategic partnership, identify shortcomings, and propose methodological approaches to managing the formation of a mechanism for assessing the effects of strategic partnership for sustainable digital development of transport structures and transportation enterprises.Results. The author proposes using the principles of management of the formation of a mechanism for assessing the effects of strategic partnership, including the principle of consistent hierarchical ordering of management actions, the principle of resource sufficiency for management actions, and the principle of digital technological accessibility of management actions. The author considers the factors of comprehensive stability (external and internal collective stability), contributing to the identification of resource redundancy and demand, as the main factors determining the vector of management actions within the framework of the mechanism for assessing the effects of strategic partnership within the structure of the synergetic matrix of inter-entrepreneurial interaction.Conclusions. The author proposes to build the process of managing the formation of a mechanism for assessing the effects of strategic partnership for sustainable digital development of transport structures and transportation enterprises around the principles of sustainability, in accordance with the parameters of sustainable digital development and with allowance for the elements of the mechanism for assessing the effects of strategic partnership in ensuring sustainable digital development in the form of strategic partnership.

The Two-Margin Problem in Insurance Markets.

Insurance markets often feature consumer sorting along both an extensive margin (whether to buy) and an intensive margin (which plan to buy). We present a new graphical theoretical framework that extends a workhorse model to incorporate both selection margins simultaneously. A key insight from our framework is that policies aimed at addressing one margin of selection often involve an economically meaningful trade-off on the other margin in terms of prices, enrollment, and welfare. Using data from Massachusetts, we illustrate these trade-offs in an empirical sufficient statistics approach that is tightly linked to the graphical framework we develop.