Unit Root Inference in Generally Trending and Cross-Correlated Fixed-T Panels

This paper proposes a new panel unit root test based on the generalized method of moments approach for panels with a possibly small number of time periods, T, and a large number of cross-sectional units, N. In the model that we consider the deterministic trend function is essentially unrestricted and the errors obey a multi-factor structure that allows for rich forms of unobserved heterogeneity. In spite of these allowances, the GMM estimator considered is shown to be asymptotically unbiased, $\sqrt{N}$-consistent and asymptotically normal for all values of the autoregressive (AR) coefficient, ρ, including unity, making it a natural candidate for unit root inference. Results from our Monte Carlo study suggest that the asymptotic properties are borne out well in small samples. The implementation is illustrated by using a large sample of US banking institutions to test Gibrat’s Law.Knut and Alice Wallenberg Foundation (Wallenberg Academy Fellowship)This is the author accepted manuscript. The final version is available from Taylor & Francis via http://dx.doi.org/10.1080/07350015.2016.119150

A Linear Estimator for Factor-Augmented Fixed-T Panels with Endogenous Regressors

Supplementary Materials: The supplementary appendix to this article provides additional results about the method developed in the present article. In particular, Section S1 analyses several extensions of the model analyzed in the main text, including unbalanced panels, observed factors, and consistency of the GMM estimator under an alternative set of assumptions, in which the factor loadings are treated as a sequence of constants. Section S2 provides descriptive statistics for the data used in the empirical illustration. Section S3 reports additional Monte Carlo results. Finally, Section S4 provides proofs of the main theoretical results put forward in the article. The supplemental materials are available online at: https://ndownloader.figstatic.com/files/22658501 .Copyright © 2020 The Authors.. A novel method-of-moments approach is proposed for the estimation of factor-augmented panel data models with endogenous regressors when T is fixed. The underlying methodology involves approximating the unobserved common factors using observed factor proxies. The resulting moment conditions are linear in the parameters. The proposed approach addresses several issues which arise with existing nonlinear estimators that are available in fixed T panels, such as local minima-related problems, a sensitivity to particular normalization schemes, and a potential lack of global identification. We apply our approach to a large panel of households and estimate the price elasticity of urban water demand. A simulation study confirms that our approach performs well in finite samples.NWO VENI grant number 451-17-002; Australian Research Council, under research grant number DP-170103135

Instrumental-variable estimation of large-T panel-data models with common factors

This is the final version. Available on open access from SAGE Publications via the DOI in this recordIn this article, we introduce the xtivdfreg command, which implements a general instrumental-variables (IV) approach for fitting panel-data models with many time-series observations, T, and unobserved common factors or interactive effects, as developed by Norkute et al. (2021, Journal of Econometrics 220: 416–446) and Cui et al. (2020a, ISER Discussion Paper 1101). The underlying idea of this approach is to project out the common factors from exogenous covariates using principal-components analysis and to run IV regression in both of two stages, using defactored covariates as instruments. The resulting two-stage IV estimator is valid for models with homogeneous or heterogeneous slope coefficients and has several advantages relative to existing popular approaches. In addition, the xtivdfreg command extends the two-stage IV approach in two major ways. First, the algorithm accommodates estimation of unbalanced panels. Second, the algorithm permits a flexible specification of instruments. We show that when one imposes zero factors, the xtivdfreg command can replicate the results of the popular Stata ivregress command. Notably, unlike ivregress, xtivdfreg permits estimation of the two-way error-components paneldata model with heterogeneous slope coefficients.Australian Research Council (ARC

New results on asymptotic properties of likelihood estimators with persistent data for small and large T

Data Availability Statement: Data sharing not applicable to this article as no datasets were generated or analyzed during the current study.Copyright © The Author(s) 2023. This paper revisits the panel autoregressive model, with a primary emphasis on the unit-root case. We study a class of misspecified Random effects Maximum Likelihood (mRML) estimators when T is either fixed or large, and N tends to infinity. We show that in the unit-root case, for any fixed value of T, the log-likelihood function of the mRML estimator has a single mode at unity as N→ ∞ . Furthermore, the Hessian matrix of the corresponding log-likelihood function is non-singular, unless the scaled variance of the initial condition is exactly zero. As a result, mRML is consistent and asymptotically normally distributed as N tends to infinity. In the large-T setup, it is shown that mRML is asymptotically equivalent to the bias-corrected FE estimator of Hahn and Kuersteiner (Econometrica 70(4):1639–1657, 2002). Moreover, under certain conditions, its Hessian matrix remains non-singular

Identification and Estimation of Differentiated Products Models using Cost Data

We propose a new methodology for estimating the demand and cost functions of differentiated products models when demand and cost data are available. The method deals with the endogeneity of prices to demand shocks and the endogeneity of outputs to cost shocks, by using variation in market size that does not need to be exogenous, and cost data. We establish nonparametric identification, consistency and asymptotic normality of our estimator. Using Monte-Carlo experiments, we show our method works well in contexts where instruments are correlated with demand and cost shocks, and where commonly-used instrumental variables estimators are biased and numerically unstable

A method to evaluate the rank condition for CCE estimators

Copyright © 2023 The Author(s). We develop a binary classifier to evaluate whether the rank condition (RC) is satisfied or not for the Common Correlated Effects (CCE) estimator. The RC postulates that the number of unobserved factors, m, is not larger than the rank of the unobserved matrix of average factor loadings, ϱ. When this condition fails, the CCE estimator is inconsistent, in general. Despite its importance, to date this rank condition could not be verified. The difficulty lies in the fact that factor loadings are unobserved, such that ϱ cannot be directly determined. The key insight in this article is that ϱ can be consistently estimated with existing techniques through the matrix of cross-sectional averages of the data. Similarly, m can be estimated consistently from the data using existing methods. Thus, a binary classifier, constructed by comparing estimates of m and ϱ, correctly determines whether the RC is satisfied or not as (N,T)→∞. We illustrate the practical relevance of testing the RC by studying the effect of the Dodd-Frank Act on bank profitability. The RC classifier reveals that the rank condition fails for a subperiod of the sample, in which case the estimated effect of bank size on profitability appears to be biased upwards.Ignace De Vos acknowledges financial support from the Ghent University BOF research fund. Ignace De Vos and Gerdie Everaert further acknowledge financial support from the National Bank of Belgium

Meropenem vs standard of care for treatment of neonatal late onset sepsis (NeoMero1): A randomised controlled trial.

BACKGROUND: The early use of broad-spectrum antibiotics remains the cornerstone for the treatment of neonatal late onset sepsis (LOS). However, which antibiotics should be used is still debatable, as relevant studies were conducted more than 20 years ago, recruited in single centres or countries, evaluated antibiotics not in clinical use anymore and had variable inclusion/exclusion criteria and outcome measures. Moreover, antibiotic-resistant bacteria have become a major problem in many countries worldwide. We hypothesized that efficacy of meropenem as a broad-spectrum antibiotic is superior to standard of care regimens (SOC) in empiric treatment of LOS and aimed to compare meropenem to SOC in infants aged 44 weeks meeting the Goldstein criteria of sepsis, were randomized in a 1:1 ratio to receive meropenem or one of the two SOC regimens (ampicillin+gentamicin or cefotaxime+gentamicin) chosen by each site prior to the start of the study for 8-14 days. The primary outcome was treatment success (survival, no modification of allocated therapy, resolution/improvement of clinical and laboratory markers, no need of additional antibiotics and presumed/confirmed eradication of pathogens) at test-of-cure visit (TOC) in full analysis set. Stool samples were tested at baseline and Day 28 for meropenem-resistant Gram-negative organisms (CRGNO). The primary analysis was performed in all randomised patients and in patients with culture confirmed LOS. Proportions of participants with successful outcome were compared by using a logistic regression model adjusted for the stratification factors. From September 3, 2012 to November 30th 2014, total of 136 patients (instead of planned 275) in each arm were randomized; 140 (52%) were culture positive. Successful outcome at TOC was achieved in 44/136 (32%) in the meropenem arm vs. 31/135 (23%) in the SOC arm (p = 0.087). The respective numbers in patients with positive cultures were 17/63 (27%) vs. 10/77 (13%) (p = 0.022). The main reason of failure was modification of allocated therapy. Treatment emergent adverse events occurred in 72% and serious adverse events in 17% of patients, the Day 28 mortality was 6%. Cumulative acquisition of CRGNO by Day 28 occurred in 4% of patients in the meropenem and 12% in the SOC arm (p = 0.052). CONCLUSIONS: Within this study population, we found no evidence that meropenem was superior to SOC in terms of success at TOC, short term hearing disturbances, safety or mortality were similar in both treatment arms but the study was underpowered to detect the planned effect. Meropenem treatment did not select for colonization with CRGNOs. We suggest that meropenem as broad-spectrum antibiotic should be reserved for neonates who are more likely to have Gram-negative LOS, especially in NICUs where microorganisms producing extended spectrum- and AmpC type beta-lactamases are circulating

Pirfenidone in idiopathic pulmonary fibrosis:expert panel discussion on the management of drug-related adverse events

Pirfenidone is currently the only approved therapy for idiopathic pulmonary fibrosis, following studies demonstrating that treatment reduces the decline in lung function and improves progression-free survival. Although generally well tolerated, a minority of patients discontinue therapy due to gastrointestinal and skin-related adverse events (AEs). This review summarizes recommendations based on existing guidelines, research evidence, and consensus opinions of expert authors, with the aim of providing practicing physicians with the specific clinical information needed to educate the patient and better manage pirfenidone-related AEs with continued pirfenidone treatment. The main recommendations to help prevent and/or mitigate gastrointestinal and skin-related AEs include taking pirfenidone during (or after) a meal, avoiding sun exposure, wearing protective clothing, and applying a broad-spectrum sunscreen with high ultraviolet (UV) A and UVB protection. These measures can help optimize AE management, which is key to maintaining patients on an optimal treatment dose.Correction in: Advances in Therapy, Volume 31, Issue 5, pp 575-576 , doi: 10.1007/s12325-014-0118-8</p