Multivariate normal distribution approaches for dependently truncated data

Many statistical methods for truncated data rely on the independence assumption regarding the truncation variable. In many application studies, however, the dependence between a variable X of interest and its truncation variable L plays a fundamental role in modeling data structure. For truncated data, typical interest is in estimating the marginal distributions of (L, X) and often in examining the degree of the dependence between X and L. To relax the independence assumption, we present a method of fitting a parametric model on (L, X), which can easily incorporate the dependence structure on the truncation mechanisms. Focusing on a specific example for the bivariate normal distribution, the score equations and Fisher information matrix are provided. A robust procedure based on the bivariate t-distribution is also considered. Simulations are performed to examine finite-sample performances of the proposed method. Extension of the proposed method to doubly truncated data is briefly discussed.     

Improving on the sample covariance matrix for a complex elliptically contoured distribution

In this paper the problem of estimating the scale matrix in a complex elliptically contoured distribution (complex ECD) is addressed. An extended Haff–Stein identity for this model is derived. It is shown that the minimax estimators of the covariance matrix obtained under the complex normal model remain robust under the complex ECD model when the Stein loss function is employed.     

Financial literacy and anxiety about life in old age: evidence from the USA

This study examines whether financial literacy can help to reduce anxiety about life in old age. We hypothesized that financially literate people are more able to earn income and accumulate assets, leading them to have a less anxious life in old age. On the other hand, less financially literate people rely more on social security to secure themselves in the old age as they are not able to accumulate sufficient assets. By using US survey data, we provide evidence that assets significantly reduce anxiety about life in old age only for people who are more financially literate. For less financially literate people, social security plays an important role in reducing anxiety about life in old age. Besides these, having a child and doing regular exercise also reduced anxiety for all respondents but marital status reduced anxiety in respondents over 40 years of age. The results of our study are robust to measurement of financial literacy and endogeneity problems.     

Can concern for the long-term care of older parents explain son preference at birth in India?

This study examines whether concern for the long-term care of older parents is the primary reason for son preference in India. Controlling for important socioeconomic factors that are believed to affect son preference, we find that concern for long-term care is the principal cause of son preference in India. Sons serve as the primary caregivers to elderly parents, while daughters are mostly engaged in caring for parents-in-law. This trend is more acute in rural than in urban areas. Our study also finds a strong implication of the filial relationship for the long-term care of elderly parents.     

What makes people anxious about life after the age of 65? Evidence from international survey research in Japan,the United States,China, and India

This study investigated the causes of people’s anxieties about life after the age of 65 years, using household data from countries with different social contexts: Japan, the United States, China, and India. This research added contextual aspects to the literature on social security and precautionary savings. An ordered probit model was used to establish the causes of anxiety and a generalized structural equation model was used to check the robustness of the results. This study uncovered three major findings. First, anxiety levels about life at an older age partly depend on people’s views of the future. Second, high financial status lessens people’s anxiety levels only if prices are stable. Third, living with a child, contrary to expectations, does not necessarily lessen people’s concerns about life after 65.     

A note on biases of jackknife estimators of third central moments

In this paper we study the biases of jackknife estimators of central third moments which play an important role in improving the accuracy of the normal approximation. It has been found in simulation studies that the jackknife estimator of the skewness coefficient, into which the jackknife variance and third moment estimators are substituted, have downward biases. For the jackknife variance estimators, their asymptotic properties are precisely studied and their biases are discussed theoretically, Here we study the biases of the jackknife estimators of the central third moments for U-statistics theoretically, The results show that the biases are not always downward.     

Generalized Nelson–Siegel term structure model: do the second slope and curvature factors improve the in-sample fit and out-of-sample forecasts?

The dynamic Nelson–Siegel (DNS) model and even the Svensson generalization of the model have trouble in fitting the short maturity yields and fail to grasp the characteristics of the Japanese government bonds yield curve, which is flat at the short end and has multiple inflection points. Therefore, a closely related generalized dynamic Nelson–Siegel (GDNS) model that has two slopes and curvatures is considered and compared empirically to the traditional DNS in terms of in-sample fit as well as out-of-sample forecasts. Furthermore, the GDNS with time-varying volatility component, modeled as standard EGARCH process, is also considered to evaluate its performance in relation to the GDNS. The GDNS model unanimously outperforms the DNS in terms of in-sample fit as well as out-of-sample forecasts. Moreover, the extended model that accounts for time-varying volatility outpace the other models for fitting the yield curve and produce relatively more accurate 6- and 12-month ahead forecasts, while the GDNS model comes with more precise forecasts for very short forecast horizons.     

日本存款准备金制度的历史演进

日本于1959年引入了存款准备金制度.在金融自由化前,存款准备金制度与再贴现率操作共同发挥着金融调节手段的作用.随着金融自由化的发展,人们逐渐意识到该制度会对银行存款业务的竞争力带来很大影响,因此下调了存款准备金率.20世纪90年代以后存款准备金率基本保持不变.作为日本银行诱导短期利率的一种框架,存款准备金制度现在仍有重要作用.     

The Bootstrap and the Edgeworth Correction for Semiparametric Averaged Derivatives*

In a number of semiparametric models, smoothing seems necessary in order to obtain estimates of the parametric component which are asymptotically normal and converge at parametric rate. However, smoothing can inflate the error in the normal approximation, so that refined approximations are of interest, especially in sample sizes that are not enormous. We show that a bootstrap distribution achieves a valid Edgeworth correction in the case of density‐weighted averaged derivative estimates of semiparametric index models. Approaches to bias reduction are discussed. We also develop a higher‐order expansion to show that the bootstrap achieves a further reduction in size distortion in the case of two‐sided testing. The finite‐sample performance of the methods is investigated by means of Monte Carlo simulations from a Tobit model.