Sampling Returns for Realized Variance Calculations: Tick Time or Transaction Time?

This article introduces a new model for transaction prices in the presence of market microstructure noise in order to study the properties of the price process on two different time scales, namely, transaction time where prices are sampled with every transaction and tick time where prices are sampled with every price change. Both sampling schemes have been used in the literature on realized variance, but a formal investigation into their properties has been lacking. Our empirical and theoretical results indicate that the return dynamics in transaction time are very different from those in tick time and the choice of sampling scheme can therefore have an important impact on the properties of realized variance. For RV we find that tick time sampling is superior to transaction time sampling in terms of mean-squared-error, especially when the level of noise, number of ticks, or the arrival frequency of efficient price moves is low. Importantly, we show that while the microstructure noise may appear close to IID in transaction time, in tick time it is highly dependent. As a result, bias correction procedures that rely on the noise being independent, can fail in tick time and are better implemented in transaction time.     

The Impact of Taking Parental Leave on Fathers’ Participation In Childcare And Relationships With Children: Lessons from Sweden

In Sweden, government-mandated paid parental leave has been available to both mothers and fathers since 1974. By 2006, each parent had two non-transferable leave months and nine additional months to share. From the beginning, parental leave was presented as a policy designed to promote gender equality, with women and men having equal opportunities and responsibilities to contribute economically to the family and care for children. Sweden thus provides a unique setting to explore whether social policy can be an important instrument for changing the gender contract. Analysing survey data from 356 fathers working in large private companies, we found that the amount of parental leave days taken had positive effects on several aspects of fathers’ participation in childcare and on their satisfaction with contact with children, controlling for other factors contributing to fathers’ participation in childcare. Our findings suggest that the full potential of Sweden's parental leave policy for degendering the division of labour for childcare will not likely be met until fathers are strongly encouraged by social policy to take a more equal portion of parental leave.     

New imperfect rankings models for ranked set sampling

Ranked set sampling is a sampling approach that leads to improved statistical inference in situations where the units to be sampled can be ranked relative to each other prior to formal measurement. This ranking may be done either by subjective judgment or according to an auxiliary variable, and it need not be completely accurate. In fact, results in the literature have shown that no matter how poor the quality of the ranking, procedures based on ranked set sampling tend to be at least as efficient as procedures based on simple random sampling. However, efforts to quantify the gains in efficiency for ranked set sampling procedures have been hampered by a shortage of available models for imperfect rankings. In this paper, we introduce a new class of models for imperfect rankings, and we provide a rigorous proof that essentially any reasonable model for imperfect rankings is a limit of models in this class. We then describe a specific, easily applied method for selecting an appropriate imperfect rankings model from the class.     

A qualitative comparative analysis of strategies for an ageing society, with special reference to pension and employment policies

The primary purpose of this study is to typify the respondent strategies of the OECD countries based on the interconnected structure of income and employment guarantees. More specifically, this article seeks to typify welfare policies into four types (welfare-to-work, welfare emphasis, labour emphasis, market emphasis) based on the leniency of the pension system and active state intervention in employment security. With the resultant four types, this article then places them as the dependent variable while incorporating per capita GDP, aged dependency ratio, pension maturity level, union density, constitutional structure index and degree of decommodification as causal variables. Through this process, this article aims to derive the decisive variable for each type through qualitative comparative analysis.     

Nonresponse weighting adjustment using estimated response probability

To reduce nonresponse bias in sample surveys, a method of nonresponse weighting adjustment is often used which consists of multiplying the sampling weight of the respondent by the inverse of the estimated response probability. The authors examine the asymptotic properties of this estimator. They prove that it is generally more efficient than an estimator which uses the true response probability, provided that the parameters which govern this probability are estimated by maximum likelihood. The authors discuss variance estimation methods that account for the effect of using the estimated response probability; they compare their performances in a small simulation study. They also discuss extensions to the regression estimator.     

A strategy for third-party logistics systems: A case analysis using the blue ocean strategy

One of today's most frequently discussed topics in the business world is how to escape from the intense Red Ocean and how to create an uncontested Blue Ocean. However, because there are few practical guidelines available on this topic, we will introduce a case study of a third-party logistics (3PL) provider, CJ-Global Logistics Service (CJ-GLS), to show how it aspires to be a leader in the newly introduced 3PL industry in South Korea. CJ-GLS is a latecomer in the logistics industry, and its resources, such as the number of trucks and warehouses, are relatively small in comparison to those of established companies. But, it has achieved a distinct competitive advantage through innovative information technology (i.e., RFID—radio frequency identification), which has enabled it to create an uncontested market space, electronic logistics business. One remarkable fact about CJ-GLS is that its swift growth comes not from attracting competitors’ customers from the existing Red Ocean market but from creating a Blue Ocean market (3PL market), which previously existing incumbents ignored, and also from constructing a new business model founded on a RFID-based, ubiquitous-oriented 3PL system. Analyzed through a Four Actions Framework and characterized as Blue Ocean, this case study provides valuable information on how a company reinforces its competitive advantage from the Red Ocean while it transitions into a Blue Ocean by utilizing advanced information communication technologies.     

Data skeletons: simultaneous estimation of multiple quantiles for massive streaming datasets with applications to density estimation

We consider the problem of density estimation when the data is in the form of a continuous stream with no fixed length. In this setting, implementations of the usual methods of density estimation such as kernel density estimation are problematic. We propose a method of density estimation for massive datasets that is based upon taking the derivative of a smooth curve that has been fit through a set of quantile estimates. To achieve this, a low-storage, single-pass, sequential method is proposed for simultaneous estimation of multiple quantiles for massive datasets that form the basis of this method of density estimation. For comparison, we also consider a sequential kernel density estimator. The proposed methods are shown through simulation study to perform well and to have several distinct advantages over existing methods.     

Consistent maximum likelihood estimation of a unimodal density using shape restrictions

It is well known that the unimodal maximum likelihood estimator of a density is consistent everywhere but at the mode. The authors review various ways to solve this problem and propose a new estimator that is concave over an interval containing the mode; this interval may be chosen by the user or through an algorithm. The authors show how to implement their solution and compare it to other approaches through simulations. They show that the new estimator is consistent everywhere and determine its rate of convergence in the Hellinger metric.