Robust Dickey–Fuller tests based on ranks for time series with additive outliers

In this paper the unit root tests proposed by Dickey and Fuller (DF) and their rank counterpart suggested by Breitung and Gouriéroux (J Econom 81(1): 7–27, 1997) (BG) are analytically investigated under the presence of additive outlier (AO) contaminations. The results show that the limiting distribution of the former test is outlier dependent, while the latter one is outlier free. The finite sample size properties of these tests are also investigated under different scenarios of testing contaminated unit root processes. In the empirical study, the alternative DF rank test suggested in Granger and Hallman (J Time Ser Anal 12(3): 207–224, 1991) (GH) is also considered. In Fotopoulos and Ahn (J Time Ser Anal 24(6): 647–662, 2003), these unit root rank tests were analytically and empirically investigated and compared to the DF test, but with outlier-free processes. Thus, the results provided in this paper complement the studies of the previous works, but in the context of time series with additive outliers. Equivalently to DF and Granger and Hallman (J Time Ser Anal 12(3): 207–224, 1991) unit root tests, the BG test shows to be sensitive to AO contaminations, but with less severity. In practical situations where there would be a suspicion of additive outlier, the general conclusion is that the DF and Granger and Hallman (J Time Ser Anal 12(3): 207–224, 1991) unit root tests should be avoided, however, the BG approach can still be used.     

Spanning tests in return and stochastic discount factor mean–variance frontiers: A unifying approach

We propose new spanning tests that assess if the initial and additional assets share the economically meaningful cost and mean representing portfolios. We prove their asymptotic equivalence to existing tests under local alternatives. We also show that unlike two-step or iterated procedures, single-step methods such as continuously updated GMM yield numerically identical overidentifying restrictions test, so there is arguably a single spanning test. To prove these results, we extend optimal GMM inference to deal with singularities in the long run second moment matrix of the influence functions. Finally, we test for spanning using size and book-to-market sorted US stock portfolios.     

Beta-product dependent Pitman–Yor processes for Bayesian inference

Multiple time series data may exhibit clustering over time and the clustering effect may change across different series. This paper is motivated by the Bayesian non-parametric modelling of the dependence between clustering effects in multiple time series analysis. We follow a Dirichlet process mixture approach and define a new class of multivariate dependent Pitman–Yor processes (DPY). The proposed DPY are represented in terms of vectors of stick-breaking processes which determine dependent clustering structures in the time series. We follow a hierarchical specification of the DPY base measure to account for various degrees of information pooling across the series. We discuss some theoretical properties of the DPY and use them to define Bayesian non-parametric repeated measurement and vector autoregressive models. We provide efficient Monte Carlo Markov Chain algorithms for posterior computation of the proposed models and illustrate the effectiveness of the method with a simulation study and an application to the United States and the European Union business cycle.     

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.     

Statistical estimation of multivariate Ornstein–Uhlenbeck processes and applications to co-integration

Ornstein–Uhlenbeck models are continuous-time processes which have broad applications in finance as, e.g., volatility processes in stochastic volatility models or spread models in spread options and pairs trading. The paper presents a least squares estimator for the model parameter in a multivariate Ornstein–Uhlenbeck model driven by a multivariate regularly varying Lévy process with infinite variance. We show that the estimator is consistent. Moreover, we derive its asymptotic behavior and test statistics. The results are compared to the finite variance case. For the proof we require some new results on multivariate regular variation of products of random vectors and central limit theorems. Furthermore, we embed this model in the setup of a co-integrated model in continuous time.     

Capture–recapture estimation based upon the geometric distribution allowing for heterogeneity

Capture–Recapture methods aim to estimate the size of an elusive target population. Each member of the target population carries a count of identifications by some identifying mechanism—the number of times it has been identified during the observational period. Only positive counts are observed and inference needs to be based on the observed count distribution. A widely used assumption for the count distribution is a Poisson mixture. If the mixing distribution can be described by an exponential density, the geometric distribution arises as the marginal. This note discusses population size estimation on the basis of the zero-truncated geometric (a geometric again itself). In addition, population heterogeneity is considered for the geometric. Chao’s estimator is developed for the mixture of geometric distributions and provides a lower bound estimator which is valid under arbitrary mixing on the parameter of the geometric. However, Chao’s estimator is also known for its relatively large variance (if compared to the maximum likelihood estimator). Another estimator based on a censored geometric likelihood is suggested which uses the entire sample information but is less affected by model misspecifications. Simulation studies illustrate that the proposed censored estimator comprises a good compromise between the maximum likelihood estimator and Chao’s estimator, e.g. between efficiency and bias.     

Consistent estimator for basis selection based on a proxy of the Kullback–Leibler distance

Given a random sample from a continuous and positive density f$f$, the logistic transformation is applied and a log density estimate is provided by using basis functions approach. The number of basis functions acts as the smoothing parameter and it is estimated by minimizing a penalized proxy of the Kullback–Leibler distance which includes as particular cases AIC and BIC criteria. We prove that this estimator is consistent.     

An iterative computational scheme for solving the coupled Hamilton–Jacobi–Isaacs equations in nonzero-sum differential games of affine nonlinear systems

In this paper, we present iterative or successive approximation methods for solving the coupled Hamilton–Jacobi–Isaacs equations (HJIEs) arising in nonzero-sum differential game for affine nonlinear systems. We particularly consider the ones arising in mixed \({\mathcal H}_{2}/{\mathcal H}_{\infty }\) control. However, the approach is perfectly general and can be applied to any others including those arising in the N-player case. The convergence of the method is established under fairly mild assumptions, and examples are solved to demonstrate the utility of the method. The results are also specialized to the coupled algebraic Riccati equations arising typically in mixed \({\mathcal H}_{2}/{\mathcal H}_{\infty }\) linear control. In this case, a bound within which the optimal solution lies is established. Finally, based on the iterative approach developed, a local existence result for the solution of the coupled-HJIEs is also established.     

The time-varying correlation between output and prices in the United States over the period 1800–2014

In this study, we examine the time-varying correlations between output and prices, while controlling for the impact of the monetary policy stance and output and inflation uncertainties over the period 1800–2014. The results of the empirical analysis reveal that the dynamic correlations of output and prices were typically negative, suggesting a countercyclical behaviour of prices, apart from the early 1840s and from the beginning until the middle of the 20th century, when the correlation was positive, indicating a procyclicality of prices. A historical decomposition analysis based on a sign-restricted structural vector autoregressive model is able to relate the procyclical and countercyclical behaviour to the predominance of aggregate supply and aggregate demand and/or monetary policy shocks, respectively. Moreover, inflation uncertainty (monetary policy stance) was found to have a positive (negative) effect on inflation over the last 215 years.     

Input–output linkages and the propagation of domestic productivity shocks: assessing alternative theories with stochastic simulation

Relatively small sectoral productivity shocks could lead to sizable macroeconomic variability. Whereas most contributions in the literature analyze the issue of aggregate sensitivity using simple general equilibrium models, a novel approach is proposed in this paper, based on stochastic simulations with a global computable general equilibrium model. We find that the variability of the GDP, induced by sectoral shocks, is basically determined by the degree of industrial concentration as measured by the Herfindahl index of industrial value added. The degree of centrality in inter-industrial connectivity, measured by the standard deviation of second-order degrees, is mildly significant, but it is also correlated with the industrial concentration index. After controlling for the correlation effect, we find that connectivity turns out to be statistically significant, although less so than granularity.     

A low quality–high cost–low satisfaction trap in public health care: a model and an efficiency-quality-welfare improving stochastic resolution

This paper develops an applied stochastic model of public health care and shows that the public health care sector in Turkey is plagued by a low quality–high cost–low satisfaction trap which has been persistent over time. The values in question are shown to be stochastically stable. We formulate an efficiency-quality-welfare improving stochastic policy rule, which helps the sector to reach a selected target and which stabilizes quality, cost and welfare around that target.     

Forecasting sales using online review and search engine data: A method based on PCA–DSFOA–BPNN

Traditional sales forecasting methods are mainly based on historical sales data, which result in a certain lag. The relationship between sales volume and its influencing factors is intricate and often non-linear. In view of this, we propose a novel product forecasting method using online reviews and search engine data. Firstly, a dictionary-based sentiment analysis method is developed to convert the textual review concerning each attribute of the product into the corresponding sentiment score. And by combining the prospect theory and relevant online review data, sentiment indices in each period are calculated. Subsequently, data of product-related Baidu search words with different lag orders are collected and screened by time difference correlation analysis. Finally, the forecast model, PCA–DSFOA–BPNN, is constructed by combining the principal component analysis (PCA), the back propagation neural network (BPNN), and the improved fruit fly optimization algorithm (DSFOA), in which sentiment indices, Baidu search data, and historical sales volume are input data. Taking the monthly sales forecast of 14 automobile models as a case study, we observe that the proposed forecast method can effectively improve the forecast accuracy with good robustness.     

Predictors and processes of satisfaction with work–family balance: Examining the role of personal,work, and family resources and conflict and enrichment

Drawing from resource-based theories, we conduct two studies to investigate the unique and relative importance of personal (e.g., resilience, proactive health behaviors), work, and family resources (i.e., enriched job and family roles, work and family support) to balance satisfaction, and the mediating roles of conflict and enrichment. We test our hypotheses in Study 1 using a cross-sectional survey of 216 employees and in Study 2 using a time-lagged survey over 3 months with 220 employees. Across both studies, work and family resources (e.g., enriched job and family characteristics, work and family support) were positively related to balance satisfaction. In general, work resources were more relevant to balance satisfaction than were personal or family resources. In terms of processes, work resources relate to less work-to-family conflict and greater work-to-family enrichment which in turn, relate to greater balance. In contrast, the family-to-work directions of conflict and enrichment were just weakly related to balance. Across the two studies, findings regarding the role of personal resources were mixed. We discuss how these findings expand our understanding of work–family balance and the practical implications for human resource practitioners.     

A network approach for assembling and linking input–output models

Input–output (IO) models, describing trade between different sectors and regions, are widely used to study the environmental repercussions of human activities. A frequent challenge in assembling an IO model or linking several such models is the absence of flow data with the same level of detail for all components. Such problems can be addressed using proportional allocation, which is a form of algebraic transformations. In this paper, we propose a novel approach whereby the IO system is viewed as a network, the topology of which is transformed with the addition of virtual nodes so that available empirical flow data can be mapped directly to existing links, with no additional estimation required, and no impact on results. As IO systems become increasingly disaggregated, and coupled to adjacent databases and models, the adaptability of IO frameworks becomes increasingly important. We show that topological transformations also offer large advantages in terms of transparency, modularity and increasingly importantly for global IO models, efficiency. We illustrate the results in the context of trade linking, multi-scale integration and other applications.     

Searching for a balance: work–family practices,work–team design,and organizational performance

The crucial impact of work–family issues on employee's well-being has been recognized and responded with a variety of research in field of organizational behavior. However, few studies examine the impact of how work–family practices affect productivity at firm-level. Following the research stream of strategic human resource management, we proposed that work–family may form the norm of reciprocity, which is a more sophisticated and more critical, internal social-structure component to enable organizational performance. We also examine the contingent effect, work–team structure – on the extent to which the work–family practices are appreciated by employees – and then create complementarities. We conduct a longitudinal study and utilize a data set of 204 Taiwanese public-traded firms to test our hypotheses. The results show that, contrary to our prediction, utilizing work–family practices does not have a significant positive impact on organizational productivity. However, the most important finding of this study is that there are synergies between work–family practices and work–team design on organizational productivity. Work–team design is an important situation in which the returns of work–family practices can be enhanced.     

Spatial and sectoral characteristics of China’s international and interregional virtual water flows – based on multi-regional input–output model

This paper provides a systematic analysis of spatial and sectoral characteristics and changes in virtual water flows associated with China’s interregional and international trade based on the China interregional input–output tables of 2002 and 2007. The results show significant improvement in water use efficiency between 2002 and 2007. However, the general spatial patterns and sectoral components of virtual water flows have more or less remained during the period. Almost all Chinese provinces are net exporters of virtual water in international trade. In interregional trade, the dominant direction of virtual water flow is from peripheral provinces to eastern coastal provinces. The agricultural sector plays an important role in shaping this direction and has significant impacts on water uses in exporting provinces, some of which are water scarce. The results of this study clarify some confusions concerning mismatches between regional water endowments and virtual water trade within China and with other countries.     

Dual sources of support for dual roles: how mentoring and work–family culture influence work–family conflict and job attitudes

This study examines the influence of mentoring support and perceptions of a supportive work–family culture on the level of work–family conflict (WFC), job satisfaction and affective commitment reported by employees in a Fortune 100 professional services organization. Main effects and interaction effects between mentoring and work–family culture were explored. Results indicate that the presence of a mentor is significantly related to affective commitment while a supportive work–family culture was associated with less WFC – both family interference with work and work interference with family – and greater job satisfaction and affective commitment. For both job satisfaction and affective commitment, there is an interaction effect that suggests a synergy between direct and contextual support. Implications for practice and future research are discussed.