Unlacing hypercube percolation: a survey

The purpose of this note is twofold. First, we survey the study of the percolation phase transition on the Hamming hypercube $\{0,1\}^{m}$ obtained in the series of papers (Borgs et al. in Random Struct Algorithms 27:137–184, 2005; Borgs et al. in Ann Probab 33:1886–1944, 2005; Borgs et al. in Combinatorica 26:395–410, 2006; van der Hofstad and Nachmias in Hypercube percolation, Preprint 2012). Secondly, we explain how this study can be performed without the use of the so-called “lace expansion” technique. To that aim, we provide a novel simple proof that the triangle condition holds at the critical probability.     

Many ways of qualitative contrast in probabilistic theories of causality

Hitchcock (Synthese 97:335–364, 1993) argues that the ternary probabilistic theory of causality meets two problems due to the problem of disjunctive factors, while arguing that the unanimity probabilistic theory of causality, which is founded on the binary contrast, does not meet them. Hitchcock also argues that only the ternary theory conveys the information about complex relations of causal relevance. In this paper, I show that Eells’ solution (Probabilistic causality, Cambridge University Press, Cambridge, 1991), which is founded on the unanimity theory, meet the two problems. I also show that the unanimity theory too reveals complex relations of causal relevance. I conclude that the two probabilistic theories of causality carve up the same causal structure in two formally different and conceptually consistent ways. Hitchcock’s ternary theory inspires several major philosophers (Maslen, Causation and counterfactuals, pp. 341–357. MIT Press, Cambridge, 2004; Schaffer, Philos Rev 114, 297–328, 2005; Northcott, Phil Stud 139, 111–123, 2007; Hausman, The place of probability in science: In honor of Eelleys Eells (1953–2006), pp. 47–64, Springer, Dordrecht, 2010) who have recently developed the ternary theory or the quaternary theory. This paper leads them to reconsider the relation between the ternary theory and the binary theory.     

Employee Mental Illness: Managing the Hidden Epidemic

While the high prevalence of mental illness in workplaces is more readily documented in the literature than it was ten or so years ago, it continues to remain largely within the medical and health sciences fields. This may account for the lack of information about mental illness in workplaces (Dewa et al. Healthcare Papers 5:12–25, 2004) by operational managers and human resource departments even though such illnesses effect on average 17 % to 20 % of employees in any 12-month period (MHCC 2012; SAMHSA 2010; ABS 2007). As symptoms of mental illness have the capacity to impact negatively on employee work performance and/or attendance, the ramifications on employee performance management systems can be significant, particularly when employees choose to deliberately conceal their illness, such that any work concerns appear to derive from issues other than illness (Dewa et al. Healthcare Papers 5:12–25, 2004; De Lorenzo 2003). When employee non-disclosure of a mental illness impacts negatively in the workplace, it presents a very challenging issue in relation to performance management for both operational managers and human resource staff. Without documented medical evidence to show that impaired work performance and/or attendance is attributable to a mental illness, the issue of performance management arises. Currently, when there is no documented medical illness, performance management policies are often brought into place to improve employee performance and/or attendance by establishing achievable employee targets. Yet, given that in any twelve-month period at least a fifth of the workforce sustains a mental illness (MHCC 2012; SAMHSA 2010; ABS 2007), and that non-disclosure is significant (Barney et al. BMC Public Health 9:1–11, 2009; Munir et al. Social Science & Medicine 60:1397–1407, 2005) such targets may be unachievable for employees with a hidden mental illness. It is for these reasons that this paper reviews the incidence of mental illness in western economies, its costs, and the reasons why it is often concealed and proposes the adoption of what are termed ‘Buffer Stage’ policies as an added tool that organisations may wish to utilise in the management of hidden medical illnesses such as mental illness.     

Accounting for heterogeneous technologies in the banking industry: a time-varying stochastic frontier model with threshold effects

This paper investigates the existence of heterogeneous technologies in the US commercial banking industry through the nondynamic panel threshold effects estimation technique proposed by Hansen (Econometrica 64:413–430, 1999, Econometrica 68:575–603, 2000a). We employ the total assets as a threshold variable, which is typically considered as a proxy for bank’s size in the banking literature. We modify the threshold effects model to allow for time-varying effects, wherein these are modeled by a time polynomial of degree two as in Cornwell et al. (J Econom 46:185–200, 1990) model. Threshold effects estimation allows us to sort banks into discrete groups based on their size in a structural and consistent manner. We determine seven such distinct technology-groups within which banks are allowed to share the same technology parameters. We provide estimates of individual and group efficiency scores, as well as of those of returns to scale and measures of technological change for each group. The presence of the threshold(s) is tested via bootstrap procedure outlined in Hansen (Econometrica 64:413–430, 1999) and the relationship between bank size and efficiency ratios is investigated.     

An unbiased model comparison test using cross-validation

Social scientists often consider multiple empirical models of the same process. When these models are parametric and non-nested, the null hypothesis that two models fit the data equally well is commonly tested using methods introduced by Vuong (Econometrica 57(2):307–333, 1989) and Clarke (Am J Political Sci 45(3):724–744, 2001; J Confl Resolut 47(1):72–93, 2003; Political Anal 15(3):347–363, 2007). The objective of each is to compare the Kullback–Leibler Divergence (KLD) of the two models from the true model that generated the data. Here we show that both of these tests are based upon a biased estimator of the KLD, the individual log-likelihood contributions, and that the Clarke test is not proven to be consistent for the difference in KLDs. As a solution, we derive a test based upon cross-validated log-likelihood contributions, which represent an unbiased KLD estimate. We demonstrate the CVDM test’s superior performance via simulation, then apply it to two empirical examples from political science. We find that the test’s selection can diverge from those of the Vuong and Clarke tests and that this can ultimately lead to differences in substantive conclusions.     

Modeling and simulation of the quality’s entropy

The aim of the present study is to define quality entropy as well as to illustrate some of its properties. The simulation of the mathematical model for quality entropy shall be performed by means of specialized software for mathematical problem simulation, such as Microsoft Excel that we have employed for this particular study. Our aim is to prove that quality entropy may be expanded to the notions of Markov source of quality and Bernoulli source of quality, by analogy with the Markov and Bernoulli sources employed in information theory. Likewise, the present study delineates some aspects regarding tolerance to quality entropy. The subject of entropy and its application of the management of quality has been approached by other authors as well (Dinu and Vod?, Revista Calitatea-acces la succes, anul 8(4): 60–61, 2007; Dinu, Revista Calitatea-acces la succes, anul 8(5): 62–63, 2007; Georgescu-Roegen, Legea Entropiei ?i Procesul Economic, 1979; Stamatiu, Proceedings of the 7th International Conference on Quality, Reability and Maintainabilty, 2000; Stamatiu, Proceeding of the 18th International Conference on Quality, Reliability and Maintainability, 2002). Through our transdisciplinary approach, we would like to contribute to the development of this subject.     

Human capital contributions to explain productivity differences

This paper develops a parametric decomposition framework of labor productivity growth relaxing the assumption of labor-specific efficiency. The decomposition analysis is applied to a sample of 121 developed and developing countries during the 1970–2007 period drawn from the recently updated Penn World Tables and Barro and Lee (A new data set of educational attainment in the world 1950–2010. NBER Working Paper No. 15902, 2010) educational databases. A generalized Cobb–Douglas functional specification is used taking into account differences in technological structures across groups of countries to approximate aggregate production technology using Jorgenson and Nishimizu (Econ J 88:707–726, 1978) bilateral model of production. The measurement of labor efficiency is based on Kopp’s (Quart J Econ 96:477–503, 1981) orthogonal non-radial index of factor-specific efficiency modified in a parametric frontier framework. The empirical results indicate that the weighted average annual rate of labor productivity growth was 1.239 % over the period analyzed. Technical change was found to be the driving force of labor productivity, while improvements in human capital and factor intensities account for the 19.5 and 12.4 % of that productivity growth, respectively. Finally, labor efficiency improvements contributed by 9.8 % to measured labor productivity growth.     

Double symmetry model and its decompositions in square contingency tables having ordered categories

In this paper, we have employed the non-standard log-linear models to fit the double symmetry models and some of its decompositions to square contingency tables having ordered categories. SAS PROC GENMOD was employed to fit these models although we could similarly have used GENLOG in SPSS or GLM in STATA. A SAS macro generates the factor or scalar variables required to fit these models. Two sets of \(4 \times 4\) unaided distance vision data that have been previously analyzed in (Tahata and Tomizawa, Journal of the Japan Statistical Society 36:91–106, 2006) were employed for verification of results. We also extend the approach to the Danish \(5 \times 5\) Mobility data as well as to the \(3 \times 3\) Danish longitudinal study data of subjective health, firstly reported in (Andersen, The Statistical Analysis of Categorical Data, Springer:Berlin, 1994) and analyzed in (Tahata and Tomizawa, Statistical Methods and Applications 19:307–318, 2010). Results obtained agree with those published in previous literature on the subject. The approaches suggest here eliminate any programming that might be required in order to apply these class of models to square contingency tables.     

Estimation and inference in parametric deterministic frontier models

In this paper we consider parametric deterministic frontier models. For example, the production frontier may be linear in the inputs, and the error is purely one-sided, with a known distribution such as exponential or half-normal. The literature contains many negative results for this model. Schmidt (Rev Econ Stat 58:238–239, 1976) showed that the Aigner and Chu (Am Econ Rev 58:826–839, 1968) linear programming estimator was the exponential MLE, but that this was a non-regular problem in which the statistical properties of the MLE were uncertain. Richmond (Int Econ Rev 15:515–521, 1974) and Greene (J Econom 13:27–56, 1980) showed how the model could be estimated by two different versions of corrected OLS, but this did not lead to methods of inference for the inefficiencies. Greene (J Econom 13:27–56, 1980) considered conditions on the distribution of inefficiency that make this a regular estimation problem, but many distributions that would be assumed do not satisfy these conditions. In this paper we show that exact (finite sample) inference is possible when the frontier and the distribution of the one-sided error are known up to the values of some parameters. We give a number of analytical results for the case of intercept only with exponential errors. In other cases that include regressors or error distributions other than exponential, exact inference is still possible but simulation is needed to calculate the critical values. We also discuss the case that the distribution of the error is unknown. In this case asymptotically valid inference is possible using subsampling methods.     

Investing equally in risk

Classical optimal strategies are notorious for producing remarkably volatile portfolio weights over time when applied with parameters estimated from data. This is predominantly explained by the difficulty to estimate expected returns accurately. In Lindberg (Bernoulli 15:464–474, 2009), a new parameterization of the drift rates was proposed with the aim to circumventing this difficulty, and a continuous time mean–variance optimal portfolio problem was solved. This approach was further developed in Alp and Korn (Decis Econ Finance 34:21–40, 2011a) to a jump-diffusion setting. In the present paper, we solve a different portfolio problem under the market parameterization in Lindberg (Bernoulli 15:464–474, 2009). Here, the admissible investment strategies are given as the amounts of money to be held in each stock and are allowed to be adapted stochastic processes. In the references above, the admissible strategies are the deterministic and bounded fractions of the total wealth. The optimal strategy we derive is not the same as in Lindberg (Bernoulli 15:464–474, 2009), but it can still be viewed as investing equally in each of the n Brownian motions in the model. As a consequence of the problem assumptions, the optimal final wealth can become non-negative. The present portfolio problem is solved also in Alp and Korn (Submitted, 2011b), using the L ²-projection approach of Schweizer (Ann Probab 22:1536–1575, 1995). However, our method of proof is direct and much easier accessible.     

Energy consumption and economic growth: evidence from non-OPEC oil producing states

According to the US EIA (2009, www.eia.doe.gov), out of the 15 largest oil producing nations in the world, 7 are not OPEC members, namely Brazil, Canada, China, Mexico, Norway, the Russian Federation, and the United States of America (USA). This paper investigates the causal relationship between energy consumption and economic growth for these non-OPEC oil producing countries. Real GDP per capita is used to measure economic growth; whereas; energy consumption is represented by four sub-variables (electric power, oil, natural gas, and coal energy). Using a panel data covering (1969–2009), this study employs the Pedroni (Econometric Theory, 20, 597–627, 2004) approach to determine cointegration and the (Econometrica, 55, 251–276, 1987) two-step procedure to explore short and long run causal effects. The results suggest that there are long run relationships between the real GDP, labour force, real capital, oil consumption, electricity consumption, gas consumption and coal consumption. Further analyses show that real GDP and oil consumption Granger cause real gross capital formation in the short run; real gross fixed capital and electricity consumption cause oil consumption in the short run; and also oil consumption and gas consumption cause electricity consumption in the short run.     

Imputation methods of missing data for estimating the population mean using simple random sampling with known correlation coefficient

This paper considers three ratio estimators of the population mean using known correlation coefficient between the study and auxiliary variables in simple random sample when some sample observations are missing. The suggested estimators are compared with the estimators of Singh and Horn (Metrika 51:267–276, 2000), Singh and Deo (Stat Pap 44:555–579, 2003) and Kadilar and Cingi (Commun Stat Theory Methods 37:2226–2236, 2008). They are compared with other imputation estimators based on the mean or a ratio. It is found that the suggested estimators are approximately unbiased for the population mean. Also, it turns out that the suggested estimators perform well when compared with the other estimators considered in this study.     

Asymptotic infimum coverage probability for interval estimation of proportions

In this paper, we discuss asymptotic infimum coverage probability (ICP) of eight widely used confidence intervals for proportions, including the Agresti–Coull (A–C) interval (Am Stat 52:119–126, 1998) and the Clopper–Pearson (C–P) interval (Biometrika 26:404–413, 1934). For the A–C interval, a sharp upper bound for its asymptotic ICP is derived. It is less than nominal for the commonly applied nominal values of 0.99, 0.95 and 0.9 and is equal to zero when the nominal level is below 0.4802. The \(1-\alpha \) C–P interval is known to be conservative. However, we show through a brief numerical study that the C–P interval with a given average coverage probability \(1-\gamma \) typically has a similar or larger ICP and a smaller average expected length than the corresponding A–C interval, and its ICP approaches to \(1-\gamma \) when the sample size goes large. All mathematical proofs and R-codes for computation in the paper are given in Supplementary Materials.     

Six Sigma failures: An escalation model

Despite the pervasiveness of Six Sigma programs, there is rising concern regarding the failure of many Six Sigma programs. One explanation for many Six Sigma failures could be escalation of commitment. Escalation of commitment refers to the propensity of decision-makers to continue investing in a failing course of action. Many researchers have applied escalation of commitment to explain the behavior of individuals, groups, companies, and nations. Using the escalation of commitment model (Staw and Ross 1987a; Ross and Staw Acad. Manag. J. 36:701–732 1993) as a basis, this research describes a Six Sigma failure in an electrical components company. In documenting this failure, this research contributes in two ways, both in the practice and in the theory of Six Sigma. First, while examining the Six Sigma failure, this research uncovers important factors for successful implementation, which should improve the practice of Six Sigma. Second, academic research (e.g., Schroeder et al. J. Oper. Manag, 26:536–554 2008; Zu et al. J. Oper. Manag, 26:630–650 2008) is engaged in uncovering the definition of Six Sigma, and its differences from other improvement programs. This research provides a new direction to academic research and has the potential to impact the theory of Six Sigma.     

An examination of ex-ante factors and their influence on equity carve-out long-term performance

This study examines the influence of several ex-ante factors on three-year market-adjusted returns of two-stage carve-out combinations from 1988 to 2006. We observe that several factors maintain their significance over a three-year period after equity carve-out ex-dates. Also, we report that, contrary to Vijh (J Bus 75(1):153–190, 1999), negative three-year carve-out returns are statistically significant. In addition, we note that negative combination carve-out/spin-off three-year returns are higher than those of carve-outs acquired by third parties or reacquired by their parents. Moreover, we observe that our independent variables explain 14.56% of the multiple regression three-year returns for carve-outs. Also, our negative correlation of three-year returns with initial period returns supports the “leaning against the wind” hypothesis of Loughran and Ritter (Rev Financ Stud 15(2):413–443, 2002). In addition, our results for the post-bubble period (2001–2006) provide an extension of the changing issuer objective function noted by Loughran and Ritter (Financ Manage 35(3):23–51, 2004) for IPOs and Hogan and Olson (J Financ Res 27(4):521–537, 2004) for equity carve-outs.     

Incentive regulation and performance measurement of Taiwan’s incineration plants: an application of the four-stage DEA method

The aim of this paper is to provide a technical efficiency assessment of Taiwan’s incineration plants as the basis of incentive regulation schemes. We integrate the four-stage approach with Simar and Wilson’s (in J Econom 136:31–64, 2007) double bootstrapping to filter out the impacts of external variables in the efficiency measurement. Empirical results show that there is room for 15 % cost reductions and capacity, ownership, location and experience are all influential in improving the performance of these plants. We also demonstrate how the results can be applied to modify a yardstick incentive scheme.     

Symmetry and Bates’ rule in Ornstein–Uhlenbeck stochastic volatility models

We find necessary and sufficient conditions for the market symmetry property, introduced by Fajardo and Mordecki (Quant Finance 6(3):219–227, 2006), to hold in the Ornstein–Uhlenbeck stochastic volatility model, henceforth OU–SV. In particular, we address the non-Gaussian OU–SV model proposed by Barndorff-Nielsen and Shephard (J R Stat Soc B 63(Part 2):167–241, 2001). Also, we prove the Bates’ rule for these models.     

Some results on constructing general minimum lower order confounding 2^{n-m} designs for n\le 2^{n-m-2}

Zhang et al. (Stat Sinica 18:1689–1705, 2008) introduced an aliased effect-number pattern for two-level regular designs and proposed a general minimum lower-order confounding (GMC) criterion for choosing optimal designs. All the GMC \(2^{n-m}\) designs with \(N/4+1\le n\le N-1\) were constructed by Li et al. (Stat Sinica 21:1571–1589, 2011), Zhang and Cheng (J Stat Plan Inference 140:1719–1730, 2010) and Cheng and Zhang (J Stat Plan Inference 140:2384–2394, 2010), where \(N=2^{n-m}\) is run number and \(n\) is factor number. In this paper, we first study some further properties of GMC design, then we construct all the GMC \(2^{n-m}\) designs respectively with the three parameter cases of \(n\le N-1\) : (i) \(m\le 4\) , (ii) \(m\ge 5\) and \(n=(2^m-1)u+r\) for \(u>0\) and \(r=0,1,2\) , and (iii) \(m\ge 5\) and \(n=(2^m-1)u+r\) for \(u\ge 0\) and \(r=2^m-3,2^m-2\) .     

On simplifying the calculations leading to designs with general minimum lower-order confounding

Motivated by the effect hierarchy principle, Zhang et al. (Stat Sinica 18:1689–1705, 2008) introduced an aliased effect number pattern (AENP) for regular fractional factorial designs and based on the new pattern proposed a general minimum lower-order confounding (GMC) criterion for choosing optimal $2^{n-m}$ designs. Zhang et al. (Stat Sinica 18:1689–1705, 2008) proved that most existing criteria can be obtained by functions of the AENP. In this paper we propose a simple method for the calculation of AENP. The method is much easier than before since the calculation only makes use of the design matrix. All 128-run GMC designs with the number of factors ranging from 8 to 32 are provided for practical use.     

On Kullback–Leibler information of order statistics in terms of the relative risk

The representation of the entropy in terms of the hazard function and its extensions have been studied by many authors including Teitler et al. (IEEE Trans Reliab 35:391–395, 1986). In this paper, we consider a representation of the Kullback–Leibler information of the first \(r\) order statistics in terms of the relative risk (Park and Shin in Statistics, 2012), the ratio of hazard functions, and extend it to the progressively Type II censored data. Then we study the change in Kullback–Leibler information of the first \(r\) order statistics according to \(r\) and discuss its relation with Fisher information in order statistics.