Summary Phillips and Sul (Journal of Applied Econometrics 2009, 24, 1153–1185) provide an algorithm to identify convergence clubs in a dynamic factor model of economic transition and growth. We provide a narrow replication of their key results, using the open source R software instead of the original GAUSS routines. We are able to exactly replicate their results on convergence clubs, corresponding point estimates and standard errors. We comment on minor differences between their reported results and their clustering algorithm. We propose simple adjustments of the original algorithm to make manual intervention unnecessary. The adjustments allow automated application of the algorithm to other data. Copyright © 2016 John Wiley & Sons, Ltd.

Recently, using data on Canadian housing, Parmeter, Henderson, and Kumbhakar (2007) found that a nonparametric approach for estimating hedonic prices is superior to formerly suggested parametric and semiparametric specifications. We carefully analyze this data set by applying a nonparametric specification test and simulation based forecast comparisons. For the case at issue our results suggest that a previously proposed parametric specification cannot be rejected.

Data analyses by classical ordinary least squares (OLS) regression techniques often employ unrealistic assumptions, fail to recognize the source and nature of heterogeneity, and are vulnerable to extreme observations. Therefore, this article compares robust and non-robust M-estimator regressions in a statistical demonstration study. Data from the Erlangen-Nuremberg Development and Prevention Project are used to model risk factors for physical punishment by fathers of 485 elementary school children. The Corporal Punishment Scale of the Alabama Parenting Questionnaire was the dependent variable. Fathers’ aggressiveness, dysfunctional parent-child relations, various other parenting characteristics, and socio-demographic variables served as predictors. Robustness diagnostics suggested the use of trimming procedures and outlier diagnostics suggested the use of robust estimators as an alternative to OLS. However, a quantile regression analysis provided more detailed insights beyond the measures of central tendency and detected sources of considerable heterogeneity in the risk structure of father’s corporal punishment. Advantages of this method are discussed with regard to methodological and content issues.

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SUMMARYSemiparametric quantile regression is employed to flexibly estimate sales response for frequently purchased consumer goods. Using retail store-level data, we compare the performance of models with and without monotonic smoothing for fit and prediction accuracy. We find that (a) flexible models with monotonicity constraints imposed on price effects dominate both in-sample and out-of-sample comparisons while being robust even at the boundaries of the price distribution when data is sparse; (b) quantile-based confidence intervals are much more accurate compared to least-squares-based intervals; (c) specifications reflecting that managers may not have exact knowledge about future competitive pricing perform extremely well.