The analysis of ranked data in blocked factorial experiments

A non-parametric method for the analysis of blocked factorial experiments, based on ranking within blocks, is proposed and shown to be equivalent to partitioning Friedman's test statistic into a set of contrasts reflecting polynomial components of the main effects and interaction. A slightly modified version of the procedure is suggested to partially overcome the problem of loss of power to detect one component when the model includes other components. This alternative procedure is shown to be equivalent to applying a standard normal theory analysis of variance to the ranks. The null distributions and power comparisons are investigated using simulation methods, and it is shown that the non-parametric methods are almost as powerful as the analysis of variance. Received: February 1999     

Granger causality in risk and detection of extreme risk spillover between financial markets

Controlling and monitoring extreme downside market risk are important for financial risk management and portfolio/investment diversification. In this paper, we introduce a new concept of Granger causality in risk and propose a class of kernel-based tests to detect extreme downside risk spillover between financial markets, where risk is measured by the left tail of the distribution or equivalently by the Value at Risk (VaR). The proposed tests have a convenient asymptotic standard normal distribution under the null hypothesis of no Granger causality in risk. They check a large number of lags and thus can detect risk spillover that occurs with a time lag or that has weak spillover at each lag but carries over a very long distributional lag. Usually, tests using a large number of lags may have low power against alternatives of practical importance, due to the loss of a large number of degrees of freedom. Such power loss is fortunately alleviated for our tests because our kernel approach naturally discounts higher order lags, which is consistent with the stylized fact that today’s financial markets are often more influenced by the recent events than the remote past events. A simulation study shows that the proposed tests have reasonable size and power against a variety of empirically plausible alternatives in finite samples, including the spillover from the dynamics in mean, variance, skewness and kurtosis respectively. In particular, nonuniform weighting delivers better power than uniform weighting and a Granger-type regression procedure. The proposed tests are useful in investigating large comovements between financial markets such as financial contagions. An application to the Eurodollar and Japanese Yen highlights the merits of our approach.     

A specification test for the propensity score using its distribution conditional on participation

Propensity score matching has become a popular method for the estimation of average treatment effects. In empirical applications, researchers almost always impose a parametric model for the propensity score. This practice raises the possibility that the model for the propensity score is misspecified and therefore the propensity score matching estimator of the average treatment effect may be inconsistent. We show that the common practice of calculating estimates of the densities of the propensity score conditional on the participation decision provides a means for examining whether the propensity score is misspecified. In particular, we derive a restriction between the density of the propensity score among participants and the density among nonparticipants. We show that this restriction between the two conditional densities is equivalent to a particular orthogonality restriction and derive a formal test based upon it. The resulting test is shown via a simulation study to have dramatically greater power than competing tests for many alternatives. The principal disadvantage of this approach is loss of power against some alternatives.     

Asymmetrical Factorial Designs Containing Clear Effects

The asymmetrical or mixed-level factorial design is a kind of important design in practice. There is a natural problem on how to choose an optimal (s ²)s ⁿ design for the practical need, where s is any prime or prime power. This paper considers the clear effects criterion for selecting good designs. It answers the questions of when an (s ²)s ⁿ design with fixed number of runs contains clear two-factor interaction (in brief 2fi) components and when it contains clear main effects or clear 2fis. It further gives the complete classification of (s ²)s ⁿ designs according to the clear 2fi components, main effects and 2fis they have.     

Manager replacement,employee protest,and corporate control

When faced with the replacement threat, incumbent managers look for support from employees by investing in a non-contractible employee–friendly relationship. Enjoying the relationship, employees help managers preserve their job by protesting against shareholders. When the benefits from the good employee–manager relationship are large enough to cover the loss of managerial inefficiency, shareholders prefer to share the influential power at the firm with employees.     

Co-employment of permanently and temporarily employed agents

One-shot interaction and repeated interaction often co-exist in the real world. We study possible behavioral effects of this co-existence in a principal-agent setting, in which a principal simultaneously employs a permanent and a temporary agent. Our experimental results indicate that there is “discrimination” between the two agents and that the available information for agents determines the extent of this discrimination, even though the theoretical solution of the game implies equal treatment of agents. Discrimination is, thus, a consequence of reciprocity. Agents that are discriminated against react negatively by withholding effort.     

Estimating and interpreting internal migration flows in Russia by accounting for network effects

The present article follows two objectives. First, to apply a recently developed spatial interaction model and discuss its power in explaining social developments. Second, to obtain information on internal migration's determinants in Russia by taking into account that its eastern and western regions differ in many respects. Two alternative panel specifications are considered, labelled “spatial interaction specification with exogenous spatial lags” and “gravity-type specification with network effects”. While both specifications are designed to capture the impacts of neighbouring regions in migration dynamics, they differ with respect to the implementation of fixed effects. It is argued that neighbourhood impacts manifest themselves either as spillover effects, which amplify a variable's impact, or competition effects, which attenuate them. The results show that variables indeed differ from each other in these respects, demonstrating how migration patterns are subject to events beyond the directly involved regions, and that these are furthermore influenced by the distances between regions. In addition, the results provide further evidence that migration determinants differ for Eastern and Western Russia.     

Forecast Evaluation Under Asymmetric Loss: A Monte Carlo Analysis of the EKT Method

This paper contributes to the literature on forecast evaluation by conducting an extensive Monte Carlo experiment using the evaluation procedure proposed by Elliott, Komunjer and Timmermann. We consider recent developments in weighting matrices for GMM estimation and testing. We pay special attention to the size and power properties of variants of the J‐test of forecast rationality. Proceeding from a baseline scenario to a more realistic setting, our results show that the approach leads to precise estimates of the degree of asymmetry of the loss function. For correctly specified models, we find the size of the J‐tests to be close to the nominal size, while the tests have high power against misspecified models. These findings are quite robust to inducing fat tails, serial correlation and outliers.     

Cross-industry asset allocation with the spatial interaction on multiple risk transmission channels

Taking into consideration the real link and information risk transmission channels, we used a spatial econometric approach to construct an economic distance-based spatial weight matrix, which can capture the spatial interaction across industries, and built a return estimation model with spatial interaction using the matrix. On this basis, we derived the covariance matrix and constructed the cross-industry asset allocation model. The empirical results showed that 1) the spatial interaction has a strong explanatory power to return and integrating the spatial interaction on multiple risk transmission channels can improve the effectiveness of the return estimation model; 2) the covariance matrix includes unsystematic risk (idiosyncratic risk) and systematic risk (market risk and cross-industry spillover risk); 3) the asset allocation model with spatial interaction can improve the performance of the portfolio and provide a valuable reference for investors' risk management and investment decision.     

Measure for Measure: Exact F Tests and the Mixed Models Controversy

We consider exact F tests for the hypothesis of null random factor effect in the presence of interaction under the two factor mixed models involved in the mixed models controversy. We show that under the constrained parameter ( CP ) model, even in unbalanced data situations, MSB/MSE (in the usual ANOVA notation) follows an exact F distribution when the null hypothesis holds. We also obtain an exact F test for what is generally (and erroneously) assumed to be an equivalent hypothesis under the unconstrained parameter ( UP ) model. For unbalanced data, such a corresponding test statistic does not coincide with MSB/MSAB (the test statistic advocated for balanced data cases). We compute the power of the exact test under different imbalance patterns and show that although the loss of power increases with the degree of imbalance, it still remains reasonable from a practical point of view.     

The role of executives in hostile takeover attempts

This paper proposes a two-stage game theoretic model where the discretionary power of executives acts as an implicit defense against hostile takeovers. Following managerial enterprise models, this paper analyzes the effects of discretionary power of target’s executives over R&D and advertising expenditures in defeating hostile takeover attempts. It is shown that in vertically differentiated industries, in equilibrium, target’s executives keep low level of R&D and advertising expenditures to make their firm an unattractive target for hostile takeovers. The model reveals that executives are influenced by their self-interest of monetary and non-monetary benefits and this self-interest makes the industry more differentiated.     

A Note on the Power of Money-Output Causality Tests

This study suggests that some empirical findings against money-output causality can be the consequence of ignoring autoregressive conditional heteroskedastic (ARCH) errors. Monte Carlo results confirm that ARCH effects drastically reduce the power of the standard causality test. The maximum likelihood approach allowing for ARCH effects, on the other hand, provides a good power performance. Using different specifications and sample period, Friedman and Kuttner (1993) and Thomas (1994) report limited evidence of money causing output. We detect significant ARCH effects in the models considered by these studies. Once ARCH effects are explicitly accounted for, we find that the monetary effect is significant though its magnitude is quite small.     

The Moderating Effect of CEO Power on the Board Composition–Firm Performance Relationship*

abstract Prior studies of the relationship between the composition of boards of directors and firm performance offer equivocal results. Drawing on agency and power circulation theories, we attempt to reduce this equivocality by asserting that CEO power moderates the relationship. Specifically, an outside director dominated board is needed to check a powerful CEO, but monitoring by other executives provides sufficient constraints on CEOs with low power. We used event study methodology to test the effects of the interaction between board composition and CEO power on stock market reaction to 73 unexpected CEO deaths. We found support for our theorizing among two of three sources of CEO power. Thus, although regulatory trends increasingly support outside director dominated boards, our findings indicate that this may not always benefit shareholders and that CEO power should be considered when constructing boards.     

Relative Efficiency of the Fuzzy p-Value Approach to Hypothesis Testing

In missing data problems, it is often the case that there is a natural test statistic for testing a statistical hypothesis had all the data been observed. A fuzzy  p -value approach to hypothesis testing has recently been proposed which is implemented by imputing the missing values in the "complete data" test statistic by values simulated from the conditional null distribution given the observed data. We argue that imputing data in this way will inevitably lead to loss in power. For the case of scalar parameter, we show that the asymptotic efficiency of the score test based on the imputed "complete data" relative to the score test based on the observed data is given by the ratio of the observed data information to the complete data information. Three examples involving probit regression, normal random effects model, and unidentified paired data are used for illustration. For testing linkage disequilibrium based on pooled genotype data, simulation results show that the imputed Neyman Pearson and Fisher exact tests are less powerful than a Wald-type test based on the observed data maximum likelihood estimator. In conclusion, we caution against the routine use of the fuzzy  p -value approach in latent variable or missing data problems and suggest some viable alternatives.     

降低供电线路电压损耗的方法研究

随着经济的快速发展,社会用电需求不断增加,生活供电线路电压损耗大,影响社会资源消耗,不容忽视。因此,论文研究了降低供电线路电压损耗的方法,以期减少常规供电线路的电压损耗,促进能源节约,减少资源浪费,提高能源使用效率,为我国降低供电线路电压损耗提供相应的对策,进而提高供电效率。     

抽油机井井下功率损失计算方法的优化

为了有效的降低有杆抽油系统井下功率损耗及提高抽油机井系统效率,对抽油机井井下功率损失的计算方法进行优化,建立了计算井下功率损耗的新的机制。该机制将抽油杆柱与液柱的摩擦损失划分到液柱与油管摩擦损失一类,组成液柱粘滞摩擦损失功率,以液柱为研究对象,采用丹斯若斯方法在得到微元段摩阻压差的基础上计算出整体液柱粘滞摩阻损失。同时利用静力有限元方法计算出油管对杆柱的支反力,在满足工程误差许可的条件下,采用简化计算的方法求得杆管滑动摩擦功率损失。上述两个关键功率损失的计算既能满足能耗计算精度要求,又进行了适当的近似简化,为井下能耗损失的计算提供了明确的理论支持。     

Input Suppliers,Differential Pricing,and Information Sharing Agreements

It is common for firms to systematically share information with their input suppliers. Although such agreements with horizontal rivals have been analyzed, there has been little work examining vertical sharing, and that analysis has focused on suppliers that set uniform prices. However, there has been a systematic change in the US policy toward vertical relationships in the past decades: both FTC inaction and courts rulings have curtailed the effect of Robinson‐Patman, a law meant to prevent differential pricing. Furthermore, it is not clear if differential pricing reflects the suppliers' or the buyers' power. The interaction of these effects is examined.     

On the detectability of different forms of interaction in regression models

We consider the ability to detect interaction structure from data in a regression context. We derive an asymptotic power function for a likelihood-based test for interaction in a regression model, with possibly misspecified alternative distribution. This allows a general investigation of different types of interactions which are poorly or well detected via data. Principally we contrast pairwise-interaction models with ‘diffuse interaction models’ as introduced in Gustafson et al. (Stat Med 24:2089–2104, 2005).     

Analyst following,disclosure quality,and discretionary impairments: Evidence from China

Financial statement preparers’ discretion in fair value measurements is integral to asset impairment accounting. Firms may misuse this discretion to report more or less impairment loss than is warranted by underlying economic circumstances. Using data from a sample of publicly listed firms in China, this study finds that analyst following reduces abnormal impairment loss, the portion of reported impairment loss that cannot be explained by corporate economic circumstances and that this effect is more pronounced for firms with lower information disclosure quality. However, the reducing effects of analyst following and its interaction with disclosure quality are greater for income‐decreasing than for income‐increasing abnormal impairment loss. Additional analyses support the argument that these differences are attributable to the dominance of accounting’s contracting role over its informational role. Overall, the findings indicate that the influence of analyst following on discretionary impairment accounting decisions is moderated by disclosure quality and by the relative importance of accounting’s contracting and informational roles in an emerging market setting.     

岩滩水电厂机组进相运行存在问题及电能损失分析

章针对岩滩水电厂建成投运发电历史数据,全面分析了岩滩水电厂302.5MW(单机容量)发电机组进相运行对机组的负面影响、存在问题及对电能损失情况,为今后妥善解决这类问题提供依据和参考。