Dutch Personal Income Tax Reform 2001: An Exceptional Position for Owner-occupied Housing

This paper examines how personal income taxation has changed across countries and whether and how this has affected the taxation of owner-occupied dwellings. It presents a partial analysis as it focuses on imputed rent taxation and the mortgage interest deduction. Furthermore, the paper places housing taxation in a wider context by describing different benchmarks which could be used to assess the taxation of owner-occupied housing in different types of personal income tax. These international and theoretical points-of-departure are used to evaluate the taxation of owner-occupied housing in the Netherlands. The paper concludes that all along political arguments have conquered theoretical premises to the advantage of the owner occupier in comparison to the private landlord. It also concludes that the theoretical base in 2001 has become so weak that owner-occupied housing is in an exceptional position in comparison with other private wealth thus becoming an easy victim for future tax savings.     

Equilibrium between interest payments and income in the housing market

The literature on housing markets suggests that house prices in almost all western economies can be explained by short-run demand-oriented variables and a long-run term. The basic principles of the theory are that the short-run fluctuations, which are based on recent price developments (shocks), occur due to market imperfection, while over the long term, causality with such fundamentals as income will recover. Nonetheless, many of the interesting questions in housing economics concern adjustments toward equilibrium. This paper seeks to identify a long-run equilibrium between interest payments and household income (interest-to-income ratio) instead of between house prices and income (price-to-income ratio).

Total project cost: a simplified model for decision makers

A simplified model for total project cost is developed in this paper to meet the numerous requests from decision makers for a model that can be used to estimate the total project cost from the estimated cash flows and, more importantly, to check the accuracy of the project cost estimates in feasibility studies that require prudent decisions. It begins with a base cost estimate in constant dollars and discrete cash flows with discrete inflation rates as practised by the construction industry. The discrete inflation rates are used to estimate the current dollar costs of the project. The effects of inflation are estimated as escalation during construction. Using the future value concept, interest during construction is estimated, in a simplified approach, to estimate the total project cost. Data from an actual feasibility study is used to highlight the strengths and weaknesses of the simplified model. The model is extended to treat discrete cash flows with continuous inflation rates.     

乡村振兴背景下农村土地开发困境与路径优化研究 ——基于公共、集体和个人利益比较视角

乡村振兴战略下我国农村土地开发面临 着多元主体利益冲突与协调困境。以四川省3个村 庄作为研究对象,采用多案例对比、多主体分析 的研究思路,分别解析政府主导、市场主导、村 集体主导三种村庄土地开发路径的开发过程与 驱动机制,并总结其在利益分配方面的困境或不 足。研究结果表明,在公共利益、集体利益和个 人利益的博弈中,开发主体及行为动机差异是造 成利益冲突困境的根本原因。其中,政府和市场 主导的村庄土地开发存在较多的利益分配不协调 问题,而村集体主导能够较好地协调公共、集体 和个人利益的关系。在农村土地开发过程中协调 处理好利益主体的相互关系是解决问题的关键, 应当通过开发主体限制、平台构建、利益联结和 协商机制的确立,实现可持续的农村土地开发与 乡村振兴战略的全面推进。     

Spectral Analysis Combining a Bartlett Window With an Associated Inner Window

Usual methods of spectrum estimation allow very strong frequencies to affect the spectrum estimates at distant frequencies, because the weighting function (spectrum window) cannot be made identically zero over the rejected range of frequencies. To give bounds for this error, a pair of windows, one with positive side lobes (Bartlett), the other with negative side lobes (modified Bartlett), are used simultaneously. Thus we demonstrate the error reduction achieved by detrending and prewhitening an example economic time series. The details of the spectrum windows, and a discussion of confidence limits for the spectrum, are given in the appendix. A program for the IBM 650 is available.     

Micro-expression recognition from local facial regions

MiE is a facial involuntary reaction that reflects the real emotion and thoughts of a human being. It is very difficult for a normal human to detect a Micro-Expression (MiE), since it is a very fast and local face reaction with low intensity. As a consequence, it is a challenging task for researchers to build an automatic system for MiE recognition. Previous works for MiE recognition have attempted to use the whole face, yet a facial MiE appears in a small region of the face, which makes the extraction of relevant features a hard task. In this paper, we propose a novel deep learning approach that leverages the locality aspect of MiEs by learning spatio-temporal features from local facial regions using a composite architecture of Convolutional Neural Network (CNN) and Long Short Term Memory (LSTM). The proposed solution succeeds to extract relevant local features for MiEs recognition. Experimental results on benchmark datasets demonstrate the highest recognition accuracy of our solution with respect to state-of-the-art methods.     

A partial binary tree DEA-DA cyclic classification model for decision makers in complex multi-attribute large-group interval-valued intuitionistic fuzzy decision-making problems

This paper proposes the idea of combining “interest groups” with the practical decision information to classify the decision makers (DMs) in complex multi-attribute large-group decision-making (CMALGDM) problems in interval-valued intuitionistic fuzzy (IVIF) environment. It constructs a partial binary tree DEA-DA cyclic classification model to achieve the multiple groups’ classification of DMs. Not only does this method provide references for the classification of DMs when the decision information is known, but it also lays foundations for DMs’ effective weight determination and the aggregation of decision information. First, this paper normalizes all of the cost attributes into benefit attributes to avoid the wrong decision result. Second, it employs the C-OWA operator to transform IVIF number (IVIFN) samples into single-valued samples. With respect to this transformation, this paper provides the corresponding BUM functions of DMs according to their risk attitudes; therefore, the preference information of DMs can be more objectively aggregated. Third, this paper adopts the partial binary tree DEA-DA cyclic classification model to present an accurate classification of DMs. Thus, for each interest group, group members with different interest preferences can be distinguished and distributed to the appropriate groups. Finally, to show the feasibility and validity of the model, we give an illustrative example.     

Algorithmic estimation of risk factors in financial markets with stochastic drift

We assume a financial market governed by a diffusion process reverting to a stochastic mean which is itself governed by an unobservable ergodic diffusion, similar to those observed in electricity and other energy markets. We develop a moment method algorithm for the estimation of the parameters of both the observable process and the unobservable stochastic mean. Our approach is contrasted with other methods for parameter estimation of partially observed diffusions, and applications to the modelling of interest rates and commodity prices are discussed.     

计算机辅助教学在化学课堂教学中的功能分析

通过计算机辅助教学的介绍，对计算机辅助教学在化学课堂教学中的功能进行了分析，这些功能包括：课堂直观性好，化抽象为具体；丰富课堂内容，开阔学生视野；化学实验演示，一目了然；利用计算机设计课堂练习。抓住重点，突出难点；通过网络教学，激发学生学习的兴趣。