基于指数平滑转移模型的价格泡沫检验方法

蒙特卡洛分析显示,Phillips,Wu和Yu（2011）提出的sup ADF泡沫检验方法对扰动项的异方差较为敏感,尤其是当扰动项方差接近非平稳时存在严重的尺度扭曲,倾向于过度拒绝不存在泡沫的原假设。同时,对于Evans（1991）周期性破灭的泡沫,当泡沫破灭的概率增加时,sup ADF检验的检验势下降较快。本文结合Kapetanios,Shin和Snell（2003）单位根检验的思想,在指数平滑转移模型的框架下提出了一种新的泡沫检验方法（sup KSS检验）。与sup ADF检验相比,sup KSS检验对于扰动项的异方差有一定的改进,同时对于周期性破灭的泡沫和指数平滑转移泡沫具有较稳健的检验势。     

Survey Estimates by Calibration on Complex Auxiliary Information

In the last decade, calibration estimation has developed into an important field of research in survey sampling. Calibration is now an important methodological instrument in the production of statistics. Several national statistical agencies have developed software designed to compute calibrated weights based on auxiliary information available in population registers and other sources. This paper reviews some recent progress and offers some new perspectives. Calibration estimation can be used to advantage in a range of different survey conditions. This paper examines several situations, including estimation for domains in one‐phase sampling, estimation for two‐phase sampling, and estimation for two‐stage sampling with integrated weighting. Typical of those situations is complex auxiliary information, a term that we use for information made up of several components. An example occurs when a two‐stage sample survey has information both for units and for clusters of units, or when estimation for domains relies on information from different parts of the population. Complex auxiliary information opens up more than one way of computing the final calibrated weights to be used in estimation. They may be computed in a single step or in two or more successive steps. Depending on the approach, the resulting estimates do differ to some degree. All significant parts of the total information should be reflected in the final weights. The effectiveness of the complex information is mirrored by the variance of the resulting calibration estimator. Its exact variance is not presentable in simple form. Close approximation is possible via the corresponding linearized statistic. We define and use automated linearization as a shortcut in finding the linearized statistic. Its variance is easy to state, to interpret and to estimate. The variance components are expressed in terms of residuals, similar to those of standard regression theory. Visual inspection of the residuals reveals how the different components of the complex auxiliary information interact and work together toward reducing the variance.     

Remittance and financial inclusion in refugee migrants: inverse probability of treatment weighting using the propensity score

ABSTRACT

This paper investigates the impact on remittances on financial inclusion of refugee migrants. While financial inclusion is gaining traction in the humanitarian and development literature, the linkage with the potential to improve the wellbeing of refugees, who are part of an upward spiral in numbers, has not been tackled. We examine World Bank survey data of 1041 Syrian refugees, using the inverse probability of treatment weighting propensity score analysis (IPTW). The method minimises the influence of outliers and addresses unobservable and missing data biases, which can plague survey based data. We observe that common indicators of financial inclusion when applied to refugees, given their limited access to formal financial services, may introduce a bias as the informal financial sector and excluded formal financial sector services do contribute to inclusiveness. We adopt a broader protocol for our data, measuring financial inclusion through six metrics stemming from G20 proposals. Overall, there is an opportunity to deepen financial inclusion for refugees who receive or send remittances. The possibility of expanding the financial inclusion options, and for this to percolate through to greater social inclusion, proffers practical commercial steps and policy enabling actions.     

基于博弈论组合赋权的地市绿色产业评价

利用偏相关-基尼系数法构建了能综合反映绿色生产、绿色消费和绿色环境的地市绿色产业评价指标体系。借鉴博弈论思想,在基于AHP法得到的主观权重和基于余弦夹角法得到的客观权重之间寻找一致或妥协,通过极小化主、客观权重之间的偏差,求解绿色产业评价指标的组合权重,进而计算地市绿色产业评价得分。对2014年陕西省10地市的绿色产业发展状况进行了实证分析。结果表明:陕西的绿色产业发展呈"关中→陕南→陕北"递减的特征;绿色生产与绿色消费紧密相关;绿色环境是制约西安绿色产业发展的"瓶颈"因素,绿色生产是制约咸阳和宝鸡绿色产业发展的主要因素。     

Calendar synchronization of gasoline price increases

In many retail gasoline markets with Edgeworth price cycles, large and regular price increases occur on the same day of the week every week, that is, they are calendar synchronized. In this article, I test whether calendar synchronization leads to higher or lower consumer expenditures on gasoline compared to a world with cycles but without calendar synchronization. On one hand, firms may attempt to trigger price increases just prior to periods of normally high demand. On the other, consumers may be better able to predict and shift purchases to low price days of the cycle. Using high‐frequency gasoline volume data and matching it to high‐frequency price data, I find that the latter effect dominates. All else equal, consumer expenditures on gasoline fall with calendar synchronization in the study markets. I also calculate intertemporal price elasticities and find them to be high.     

Evolutionary stability of prospect theory preferences

We demonstrate that in simple 2×2 games (cumulative) prospect theory preferences can be (semi-)evolutionarily stable, in particular, a population of players with prospect theory preferences is stable against more rational players, i.e. players with a smaller degree of probability weighting. We also show that in a typical game with infinitely many strategies, the “war of attrition”, probability weighting is (semi-)evolutionarily stable. Finally, we generalize to other notions of stability. Our results may help to explain why probability weighting is generally observed in humans, although it is not optimal in usual decision problems.     

Tests for location-scale families based on the empirical characteristic function

A class of procedures is presented for using random samples to test the fit of location-scale families—distributions F(·;θ₁,θ₂) such that Z=(X−θ₁)/θ₂ has distribution Working with empirically standardized data, the test statistic is a measure of distance between the empirical characteristic function, and the c.f. of Z under the null hypothesis, ϕ₀(t). The closed-form test statistic is derived by integrating over the product of a weight function times Using as weight function for each location-scale family the squared modulus of ϕ₀ itself presents a unified test procedure. Included as special cases are well-known tests for normal and Cauchy laws. Small-sample powers are compared with those of Anderson-Darling tests for each of seven univariate location-scale families.     

UMP unbiased tests for multiparameter testing problems with restricted alternatives

Applications of the standard theory of UMP unbiased tests depends on conditions which in general are difficult to verify. In the present paper, however, we suggest more simple rules for applying this theory for regular exponential families of distributions. This approach leads to UMP unbiased tests for various multiparameter testing problems with restricted alternatives, and is shown to give justification for conditional tests for testing symmetry, diagonals-parameter symmetry and independence in two-way contingency tables. The derived tests are shown to possess attractive small sample properties. Received: June 1998     

Game contingent claims in complete and incomplete markets

A game contingent claim is a contract which enables both the buyer and the seller to terminate it before maturity. For complete markets Kifer [Finance and Stochastics 4 (2000) 443–463] shows a connection to a (zero-sum) Dynkin game whose value is the unique no-arbitrage price of the claim. But, for incomplete markets one needs a more general approach. We interpret the contract as a generalized non-zero-sum stopping game. For the complete case this leads to the same results as in Kifer [Finance and Stochastics 4 (2000) 443–463]. For the general case we show the existence of an equilibrium point under the condition that both the seller and the buyer have an exponential utility function. For other utility functions such a point need not exist in the context of incomplete markets.     

Model combinations through revised base rates

Standard selection criteria for forecasting models focus on information that is calculated for each series independently, disregarding the general tendencies and performance of the candidate models. In this paper, we propose a new way to perform statistical model selection and model combination that incorporates the base rates of the candidate forecasting models, which are then revised so that the per-series information is taken into account. We examine two schemes that are based on the precision and sensitivity information from the contingency table of the base rates. We apply our approach on pools of either exponential smoothing or ARMA models, considering both simulated and real time series, and show that our schemes work better than standard statistical benchmarks. We test the significance and sensitivity of our results, discuss the connection of our approach to other cross-learning approaches, and offer insights regarding implications for theory and practice.