Reconsidering the philanthropic foundation minimum payout policy under a “new normal”

With the increasing salience of foundations in many policy fields, and recent changes in market conditions, policies towards foundations designed decades ago seem outdated. In this article we suggest reassessing foundation payout minimums. To examine the impact of payout rates on grantmaking foundations lifespan and performance under “new normal” economics, we simulate multiple foundations lifecycles using Monte Carlo methods in diverse capital market conditions, with varied investment and payout strategies.We find that while under past market regime perpetuity seems to be a given, under more probable future scenarios, foundations might face increasingly early mortality and endowment depletion, limiting their potential impact. Furthermore, lower payout rates allow for higher lifetime grantmaking, higher mean annual grantmaking, and lower giving volatility. Accordingly, we suggest a tiered payout policy, in line with foundations’ missions and proper financial planning.     

How much is too much: Does the size of income support transfers affect labor supply?

Cash transfer programs pursue mainly protective objectives, but can also impact rural livelihoods by inducing investments in productive activities and changing household labor allocation. We adopt a continuous treatment approach to quantify how households’ labor supply responds to transfer size. We find a shift from paid labor to own farm labor and find that the transfer size is well within a level that would have disincentive effects on time spent on own farm activities. The switch from paid to own farm labor occurs at lower levels of transfers for labor-constrained households, and at higher levels for non-labor constrained households.     

Market economies and pro-social behavior: Experimental evidence from Central Asia

This study seeks to extend the body of knowledge of pro-social behavior in comparative market settings by reporting on a high-stakes ultimatum game and revelation game experiments in two transition economies: Kazakhstan and Uzbekistan. While controlling for cultural differences and framing effects, we find statistically significant differences in fairness and honesty behavior between the two countries. Specifically, subjects in Uzbekistan (in an earlier stage of transition to a market economy) are fairer and more honest than their later-stage Kazakh counterparts. Our experimental findings have implications for the literature on pro-social behavior and market economies, and more generally, on the transmission process between formal and informal institutions.     

Exponentially weighted moving average charts for correlated multivariate Poisson processes

In this article, we study exponentially weighted moving average (EWMA) control schemes to monitor the multivariate Poisson distribution with a general covariance structure, so that the practitioner can simultaneously monitor multiple correlated attribute processes more effectively. The statistical performance of the charts is assessed in terms of the run length properties and compared against other mainstream attribute control schemes. The application of the proposed methods to real-life and simulated datasets is demonstrated.     

Bootstrap methods for multivariate hypothesis testing

The nonparametric and parametric bootstrap methods for multivariate hypothesis testing are developed. They are used to approximate the null distribution of the test statistics proposed by Duchesne and Francq (2015 Duchesne, P., Francq, C. (2015). Multivariate hypothesis testing using generalized and {2}-inverses—with applications. Statistics 49:475–496.[Taylor &; Francis Online], [Web of Science ®] , [Google Scholar]), resulting in bootstrap testing procedures. In the problem of testing for the mean vector of a multivariate distribution, the asymptotic validity of the bootstrap methods is proved. The finite sample performance of the new solutions is demonstrated by means of Monte Carlo simulation studies. They indicate that for small-sample size, the bootstrap tests provide a better finite sample properties than the asymptotic tests considered by Duchesne and Francq (2015 Duchesne, P., Francq, C. (2015). Multivariate hypothesis testing using generalized and {2}-inverses—with applications. Statistics 49:475–496.[Taylor &; Francis Online], [Web of Science ®] , [Google Scholar]).     

中国P2P网络借贷信用风险的测量

分析中国P2P网络借贷信用风险的生成机理,借鉴商业银行典型个人信用风险测量理论基础与方法,构建基于涵盖借款人软信息的P2P网络借贷信用风险评级指标体系。通过向在银行从事信贷工作的专业人员发放调查问卷,确定具体指标,使用AHP(层次分析法)与DEMATEL(决策实验室法)相结合的方法综合确定指标体系权重,最后评级结果以百分制数值给出,并换算成具体的信用等级,有效解决了平台对借款人信用等级测量问题。     

India's demand for international reserve and monetary disequilibrium: Reserve adequacy under floating regime

The main aim of this study is to investigate India's demand for international reserve by focusing on the role of national monetary disequilibrium and to present new benchmarks for assessing the adequacy of international reserves. We assessed India's position in terms of reserve adequacy and found that India is well placed and has sufficient stock of international reserves to meet the minimum adequacy requirements. Also, the results reveal that the central bank is holding substantial excess reserves and the related opportunity cost (1.5% of GDP) appears to be quite considerable. Further, the estimates of reserve demand function suggest that scale of foreign trade, uncertainty and profitability considerations play significant role in determining India's long-term reserve demand policies. More importantly, validating the monetary approach to balance of payment, our results show that national monetary disequilibrium does play a crucial role in short-run reserve movements. An excess of money demand (supply) induces an inflow (outflow) of international reserves with an elasticity of 0.56 which also implies that Reserve Bank of India responds to correct the domestic money market disequilibrium; and did not just leave it completely on the mercy of reserve inflows.     

A Semiparametric Regression Model for Longitudinal Data with Non‐stationary Errors

Motivated by the need to analyze the National Longitudinal Surveys data, we propose a new semiparametric longitudinal mean‐covariance model in which the effects on dependent variable of some explanatory variables are linear and others are non‐linear, while the within‐subject correlations are modelled by a non‐stationary autoregressive error structure. We develop an estimation machinery based on least squares technique by approximating non‐parametric functions via B‐spline expansions and establish the asymptotic normality of parametric estimators as well as the rate of convergence for the non‐parametric estimators. We further advocate a new model selection strategy in the varying‐coefficient model framework, for distinguishing whether a component is significant and subsequently whether it is linear or non‐linear. Besides, the proposed method can also be employed for identifying the true order of lagged terms consistently. Monte Carlo studies are conducted to examine the finite sample performance of our approach, and an application of real data is also illustrated.     

A powerful and efficient algorithm for breaking the links between aliased effects in asymmetric designs

Fractional factorial (FF) designs are no doubt the most widely used designs in experimental investigations due to their efficient use of experimental runs. One price we pay for using FF designs is, clearly, our inability to obtain estimates of some important effects (main effects or second order interactions) that are separate from estimates of other effects (usually higher order interactions). When the estimate of an effect also includes the influence of one or more other effects the effects are said to be aliased. Folding over an FF design is a method for breaking the links between aliased effects in a design. The question is, how do we define the foldover structure for asymmetric FF designs, whether regular or nonregular? How do we choose the optimal foldover plan? How do we use optimal foldover plans to construct combined designs which have better capability of estimating lower order effects? The main objective of the present paper is to provide answers to these questions. Using the new results in this paper as benchmarks, we can implement a powerful and efficient algorithm for finding optimal foldover plans which can be used to break links between aliased effects.     

Rank and response: A field experiment on peer information and water use behavior

Perception of peer rank, or how we perform relative to our peers, can be a powerful motivator. While research exists on the effect of social information on decision making, there is less work on how ranked comparisons with our peers influence our behavior. This paper outlines a field experiment conducted with 3896 households in Castro Valley, California, which uses household mailers with various forms of social information and peer rank messaging to motivate water conservation. The experiment tests the effect of a visible peer rank on water use, and how the competitive framing of rank information influences behavioral response. The results show that households with relatively low or high water use in the pre-treatment period responded differently to how rank information was framed. I find that a neutrally-framed peer rank caused a small “boomerang effect” (i.e., an increase in average water use) for low water use households, but this effect was eliminated by competitive framing. At the same time, a competitively-framed peer rank demotivated high water use households, increasing their average water use over the full period of the experiment. This result is supported by evidence that the competitive frame on rank information increased water use for households who ranked “last” in the peer group – a detrimental “last place effect” from competitively-framed rankings.