A Test of the Cross-Sectional Robustness of the Arbitrage Pricing Model Using Foreign Exchange Rates*

This paper tests the cross-sectional robustness of the arbitrage pricing theory (APT) model using foreign exchange rate data to determine if the model is robust with respect to the various random samples and various factor analytic techniques. Factor scores are developed using various samples and factor analytic techniques to explain the returns for other samples and groupings. The APT model is found to be robust across samples and techniques.     

Home Visitor Relationship Security: Association With Perceptions of Work,Satisfaction, and Turnover

Home visiting is widely used to improve outcomes in families at risk for poor parenting. Impact is modest and variable, owing in part to poor fidelity. Attachment theory suggests that home visitors' relationship security influences fidelity because establishing a trusting relationship with parents is central to service delivery. This study describes paraprofessional home visitors' relationship security and relates it to demographics, psychological attributes, and work perceptions and intentions. Home visitors (n = 62) varied widely on the two major domains of relationship security: anxiety and avoidance. Relationship security was stable over time. Relationship anxiety and avoidance were associated with psychological and work constructs in theoretically predicted ways. Relationship anxiety was negatively associated with self-efficacy and positively associated with negative affect and indicators of burnout. Relationship avoidance was negatively associated with self-efficacy, job satisfaction, and tenure as a home visitor. Implications for research and practice are discussed.     

Lability of prenatal stress during the COVID-19 pandemic links to negative affect in infancy

The association between prenatal stress and children's socioemotional development is well established. The COVID-19 pandemic has been a particularly stressful period, which may impact the gestational environment. However, most studies to-date have examined prenatal stress at a single time point, potentially masking the natural variation in stress that occurs over time, especially during a time as uncertain as the pandemic. This study leveraged dense ecological momentary assessments from a prenatal randomized control trial to examine patterns of prenatal stress over a 14-week period (up to four assessments/day) in a U.S. sample of 72 mothers and infants. We first examined whether varied features of stress exposure (lability, mean, and baseline stress) differed depending on whether mothers reported on their stress before or during the pandemic. We next examined which features of stress were associated with 3-month-old infants' negative affect. We did not find differences in stress patterns before and during the pandemic. However, greater stress lability, accounting for baseline and mean stress, was associated with higher infant negative affect. These findings suggest that pathways from prenatal stress exposure to infant socioemotional development are complex, and close attention to stress patterns over time will be important for explicating these pathways.     

Estimating DEA confidence intervals with statistical panel data analysis

This paper describes a statistical method for estimating data envelopment analysis (DEA) score confidence intervals for individual organizations or other entities. This method applies statistical panel data analysis, which provides proven and powerful methodologies for diagnostic testing and for estimation of confidence intervals. DEA scores are tested for violations of the standard statistical assumptions including contemporaneous correlation, serial correlation, heteroskedasticity and the absence of a normal distribution. Generalized least squares statistical models are used to adjust for violations that are present and to estimate valid confidence intervals within which the true efficiency of each individual decision-making unit occurs. This method is illustrated with two sets of panel data, one from large US urban transit systems and the other from a group of US hospital pharmacies.     

Comparison of Nonparametric and Parametric Methods in Repeated Measures Designs - A Simulation Study

This study investigates the performance of parametric and nonparametric tests to analyze repeated measures designs. Both multivariate normal and exponential distributions were simulated for varying values of the correlation and ten or twenty subjects within each cell. For multivariate normal distributions, the type I error rates were lower than the usual 0.05 level for nonparametric tests, whereas the parametric tests without the Greenhouse-Geisser or the Huynh-Feldt adjustment produced slightly higher type I error rates. Type I error rates for nonparametric tests, for multivariate exponential distributions, were more stable than parametric, Greenhouse-Geisser or Huynh-Feldt adjusted tests. For ten subjects within each cell, the parametric tests were more powerful than nonparametric tests. For twenty subjects per cell, the power of the nonparametric and parametric tests was comparable.     

Confidence in Domestic Money and Currency Substitution

This article studies currency substitution in a model where domestic money suffers from lack of confidence. When agents' confidence is exogenous and constant, there is a unique but unstable dual-money steady state. However, when agents' confidence is updated endogenously, the dynamics of currency substitution are driven by agents' evolving beliefs, and the economy always converges to an equilibrium where both monies circulate. Therefore, the economy under endogenous beliefs exhibits both persistence in currency substitution and tenacity of domestic money. Furthermore, in general, there are multiple steady states, which can be Pareto ranked by the degree of currency substitution.