Local Asymptotic Equivalence of the Bai and Ng (2004) and Moon and Perron (2004) Frameworks for Panel Unit Root Testing

This paper considers unit-root tests in large n and large T heterogeneous panels with cross-sectional dependence generated by unobserved factors. We reconsider the two prevalent approaches in the literature, that of Moon and Perron (2004) and the PANIC setup proposed in Bai and Ng (2004). While these have been considered as completely different setups, we show that, in case of Gaussian innovations, the frameworks are asymptotically equivalent in the sense that both experiments are locally asymptotically normal (LAN) with the same central sequence. Using Le Cam's theory of statistical experiments we determine the local asymptotic power envelope and derive an optimal test jointly in both setups. We show that the popular Moon and Perron (2004) and Bai and Ng (2010) tests only attain the power envelope in case there is no heterogeneity in the long-run variance of the idiosyncratic components. The new test is asymptotically uniformly most powerful irrespective of possible heterogeneity. Moreover, it turns out that for any test, satisfying a mild regularity condition, the size and local asymptotic power are the same under both data generating processes. Thus, applied researchers do not need to decide on one of the two frameworks to conduct unit root tests. Monte-Carlo simulations corroborate our asymptotic results and document significant gains in finite-sample power if the variances of the idiosyncratic shocks differ substantially among the cross sectional units

Local Asymptotic Equivalence of the Bai and Ng (2004) and Moon and Perron (2004) Frameworks for Panel Unit Root Testing

This paper considers unit-root tests in large n and large T heterogeneous panels with cross-sectional dependence generated by unobserved factors. We reconsider the two prevalent approaches in the literature, that of Moon and Perron (2004) and the PANIC setup proposed in Bai and Ng (2004). While these have been considered as completely different setups, we show that, in case of Gaussian innovations, the frameworks are asymptotically equivalent in the sense that both experiments are locally asymptotically normal (LAN) with the same central sequence. Using Le Cam's theory of statistical experiments we determine the local asymptotic power envelope and derive an optimal test jointly in both setups. We show that the popular Moon and Perron (2004) and Bai and Ng (2010) tests only attain the power envelope in case there is no heterogeneity in the long-run variance of the idiosyncratic components. The new test is asymptotically uniformly most powerful irrespective of possible heterogeneity. Moreover, it turns out that for any test, satisfying a mild regularity condition, the size and local asymptotic power are the same under both data generating processes. Thus, applied researchers do not need to decide on one of the two frameworks to conduct unit root tests. Monte-Carlo simulations corroborate our asymptotic results and document significant gains in finite-sample power if the variances of the idiosyncratic shocks differ substantially among the cross sectional units

Drug Prescription and Delirium in Older Inpatients: Results From the Nationwide Multicenter Italian Delirium Day 2015-2016

Objective: This study aimed to evaluate the association between polypharmacy and delirium, the association of specific drug categories with delirium, and the differences in drug-delirium association between medical and surgical units and according to dementia diagnosis. Methods: Data were collected during 2 waves of Delirium Day, a multicenter delirium prevalence study including patients (aged 65 years or older) admitted to acute and long-term care wards in Italy (2015-2016); in this study, only patients enrolled in acute hospital wards were selected (n = 4,133). Delirium was assessed according to score on the 4 "A's" Test. Prescriptions were classified by main drug categories; polypharmacy was defined as a prescription of drugs from 5 or more classes. Results: Of 4,133 participants, 969 (23.4%) had delirium. The general prevalence of polypharmacy was higher in patients with delirium (67.6% vs 63.0%, P =.009) but varied according to clinical settings. After adjustment for confounders, polypharmacy was associated with delirium only in patients admitted to surgical units (OR = 2.9; 95% CI, 1.4-6.1). Insulin, antibiotics, antiepileptics, antipsychotics, and atypical antidepressants were associated with delirium, whereas statins and angiotensin receptor blockers exhibited an inverse association. A stronger association was seen between typical and atypical antipsychotics and delirium in subjects free from dementia compared to individuals with dementia (typical: OR = 4.31; 95% CI, 2.94-6.31 without dementia vs OR = 1.64; 95% CI, 1.19-2.26 with dementia; atypical: OR = 5.32; 95% CI, 3.44-8.22 without dementia vs OR = 1.74; 95% CI, 1.26-2.40 with dementia). The absence of antipsychotics among the prescribed drugs was inversely associated with delirium in the whole sample and in both of the hospital settings, but only in patients without dementia. Conclusions: Polypharmacy is significantly associated with delirium only in surgical units, raising the issue of the relevance of medication review in different clinical settings. Specific drug classes are associated with delirium depending on the clinical setting and dementia diagnosis, suggesting the need to further explore this relationship

Drug prescription and delirium in older inpatients: Results from the nationwide multicenter Italian Delirium Day 2015-2016

Objective: This study aimed to evaluate the association between polypharmacy and delirium, the association of specific drug categories with delirium, and the differences in drug-delirium association between medical and surgical units and according to dementia diagnosis. Methods: Data were collected during 2 waves of Delirium Day, a multicenter delirium prevalence study including patients (aged 65 years or older) admitted to acute and long-term care wards in Italy (2015-2016); in this study, only patients enrolled in acute hospital wards were selected (n = 4,133). Delirium was assessed according to score on the 4 "A's" Test. Prescriptions were classified by main drug categories; polypharmacy was defined as a prescription of drugs from 5 or more classes. Results: Of 4,133 participants, 969 (23.4%) had delirium. The general prevalence of polypharmacy was higher in patients with delirium (67.6% vs 63.0%, P =.009) but varied according to clinical settings. After adjustment for confounders, polypharmacy was associated with delirium only in patients admitted to surgical units (OR = 2.9; 95% CI, 1.4-6.1). Insulin, antibiotics, antiepileptics, antipsychotics, and atypical antidepressants were associated with delirium, whereas statins and angiotensin receptor blockers exhibited an inverse association. A stronger association was seen between typical and atypical antipsychotics and delirium in subjects free from dementia compared to individuals with dementia (typical: OR = 4.31; 95% CI, 2.94-6.31 without dementia vs OR = 1.64; 95% CI, 1.19-2.26 with dementia; atypical: OR = 5.32; 95% CI, 3.44-8.22 without dementia vs OR = 1.74; 95% CI, 1.26-2.40 with dementia). The absence of antipsychotics among the prescribed drugs was inversely associated with delirium in the whole sample and in both of the hospital settings, but only in patients without dementia. Conclusions: Polypharmacy is significantly associated with delirium only in surgical units, raising the issue of the relevance of medication review in different clinical settings. Specific drug classes are associated with delirium depending on the clinical setting and dementia diagnosis, suggesting the need to further explore this relationship