Robust influence diagnostics for generalized linear models with continuous responses

This article introduces two parametric robust diagnostic methods for detecting influential observations in the setting of generalized linear models with continuous responses. The legitimacy of the two proposed methods requires no knowledge of the true underlying distributions so long as their second moments exist. The performance of the two proposed influence diagnostic tools is investigated through limited simulation studies and the analyses of an illustration.     

A critical overview of privacy-preserving approaches for collaborative forecasting

Cooperation between different data owners may lead to an improvement in forecast quality—for instance, by benefiting from spatiotemporal dependencies in geographically distributed time series. Due to business competitive factors and personal data protection concerns, however, said data owners might be unwilling to share their data. Interest in collaborative privacy-preserving forecasting is thus increasing. This paper analyzes the state-of-the-art and unveils several shortcomings of existing methods in guaranteeing data privacy when employing vector autoregressive models. The methods are divided into three groups: data transformation, secure multi-party computations, and decomposition methods. The analysis shows that state-of-the-art techniques have limitations in preserving data privacy, such as (i) the necessary trade-off between privacy and forecasting accuracy, empirically evaluated through simulations and real-world experiments based on solar data; and (ii) iterative model fitting processes, which reveal data after a number of iterations.     

Relevance of the disposition effect on the options market: New evidence

A moneyness‐based propensity to sell (MPS) measure, at the aggregate level, determines the propensity of option holders to exercise their winning relative to losing positions. Using data on individual stock and S&P 500 Index options, we find that the MPS measure has significant predictive power over the cross section of delta‐hedged option returns. We test the disposition effect in the options market based on a long–short strategy that exploits price distortions induced by the disposition bias. More pronounced evidence of the disposition bias is found for individual at‐the‐money call options than put options where the significance of abnormal returns remains robust across different subsamples even after we control for the portfolio option greeks and market‐based risk factors. The profitability of the long–short strategy is related to limit‐to‐arbitrage proxies suggesting that behavioral explanations help explain the positive relation between the MPS measure and delta‐hedged option returns.     

Lost in intervention. The Harrod–Balassa–Samuelson effect on the peseta/dollar real exchange rate (1870–1998)

We have decomposed the peseta/dollar real exchange rate (1870–1998) into its trend and cyclical components and used the former to proxy its time-varying equilibrium. Then, we have compared changes in the equilibrium with changes in the Spanish and the USA productivity differentials to identify years that do not fit with the Harrod–Balassa–Samuelson (HBS) hypothesis. The greatest maladjustment is found in the 1940s and 1950s, decades of strong exchange rate intervention in Spain. Conversely, the link between equilibrium and differentials adjusts to the hypothesis when using the non-intervened peseta/dollar exchange rate on the Tangier black market. These contrasting results back up the idea that exchange rate intervention, so common in developing countries, might explain their scanter evidence in favour of the HBS effect.     

The Effect of Explicit Communication on pricing: Evidence from the Collapse of a Gasoline Cartel

We study the collapse of collusion in Québec's retail gasoline market following a Competition Bureau investigation, and show that it involved two empirical regularities: high margins, and asymmetric price adjustments. Using weekly, station‐level prices we test whether collusion was successful, and whether asymmetric adjustments were part of the cartel's strategy. We do so in the markets targeted by the investigation, and in markets throughout the province with similar pre‐collapse pricing (cyclical markets). Our results suggest that stations in both target and cyclical markets adjusted pricing following the announcement: margins fell (by 30%/15% in target/cyclical markets), and adjustments became more symmetric.     

Timing the Start of Material Substitution Projects: Creating Switching Options under Volatile Material Prices

Firms developing new products often face the challenge of making investment decisions under uncertain input–cost conditions due to the price volatilities of the materials they use. These decisions need to be made long before the final products are launched on the market. Therefore, firms that invest in the opportunity to switch materials in a timely manner will have the flexibility to react to material price changes and realize competitive advantages. However, volatile material prices may also cause a firm to delay investment. Using real‐options reasoning, this paper studies the influence of input‐cost fluctuations on the timing decision to start new product development (NPD) and thus create the follow‐on opportunity to later replace an existing product. A model that combines waiting and switching options to derive influencing factors of the flexibility value that triggers the investment is developed and tested on a sample of material substitution projects from manufacturing firms. The results show how price uncertainty of the new and the old material, their joint price development, the expected project duration, and competitive preemption are related to the propensity to delay the start of NPD. The findings provide new insights on how timing in adopting materials can be used to hedge exposure to volatile material prices. The insights are relevant for adopters and producers of new materials, as well as for policy makers who strive for supporting the diffusion of new materials.     

Healthcare costs of stroke and major bleeding in patients with atrial fibrillation treated with non-vitamin K antagonist oral anticoagulants

Objective: To assess long-term healthcare costs related to ischemic stroke and systemic embolism (stroke/SE) and major bleeding (MB) events in patients with non-valvular atrial fibrillation (NVAF) treated with non-vitamin K antagonist oral anticoagulants (NOACs).

Materials and methods: Optum’s Clinformatics Data Mart database from 1/2009–12/2016 was analyzed. Adult patients with ≥1 stroke/SE hospitalization (index date) were matched 1:1 to patients without stroke/SE (random index date), based on propensity scores. Patients with an MB event were matched to patients without MB. All patients had an NOAC dispensing overlapping index date, ≥12?months of eligibility pre-index date, and ≥1 NVAF diagnosis. The observation period spanned from the index date until the earliest date of death, switch to warfarin, end of insurance coverage, or end of data availability. Mean costs were evaluated: (1) per-patient-per-year (PPPY) and (2) at 1, 2, 3, and 4?years using Lin's method.

Results: The cost differences were, respectively, $48,807 and $28,298 PPPY for NOAC users with stroke/SE (n?=?1,340) and those with MB (n?=?3,774) events compared to controls. Cost differences of patients with vs without stroke/SE were $49,876, $51,627, $57,822, and $60,691 at 1, 2, 3, and 4?years post-index, respectively (p?p?Limitations: Limitations include unobserved confounders, coding and/or billing inaccuracies, limited sample sizes over longer follow-up, and the under-reporting of mortality for deaths occurring after 2011.

Conclusions: The incremental healthcare costs incurred by patients with vs without stroke/SE was nearly twice as high as those of patients with vs without MB. Moreover, each additional year up to 4?years after the first event was associated with an incremental cost for patients with a stroke/SE or MB event compared to those without an event.     

Effects of Firm Size,Financial Leverage and R&D Expenditures on Firm Earnings: An Analysis Using Quantile Regression Approach

As documented in the literature, the effects of firm size, financial leverage, and R&D expenditures on firm earnings are inclusive. Our hypothesis is that the inconsistent empirical results of such effects may be driven by the regression models implemented in data analysis. Using the quantile regression (QR) approach developed by Koenker and Basset (1978), this study analyses S&P 500 firms from 1996 to 2005. We find that the effects of firm size, financial leverage and R&D expenditures on firm earnings differ considerably across earnings quantiles. Comparing the results from the QR approach with those from the ordinary least squares (OLS) and least absolute deviation (LAD) methods, this study further explains the puzzling relationship between firm size, financial leverage, R&D expenditures and firm earnings.     

Regime shifts in stock–flow I(2)–I(1) systems: the case of US fiscal sustainability

In the last two decades, fiscal sustainability has been tested through the use of non‐stationary time series analysis. Two different approximations can be found in the literature: first, a univariate approach that has focused on the stochastic properties of the stock of debt and, second, a multivariate one that has focused on the long‐run properties of the flows of expenditures and revenues, i.e., in the stochastic properties of the deficit. In this paper we unify these approaches considering the stock–flow system that fiscal variables configure. Our approach involves working in an I(2) stochastic processes framework. Given the possibility of the existence of regime shifts in the sustainability of US deficit that the literature has pointed out, we develop a new statistic that can be applied to test several types of I(2) cointegration and multicointegration relationships allowing for regime shifts. To test for these kinds of changing long‐run relationships we propose the use of a residual‐based Dickey–Fuller class of statistic that accounts for one structural break. We show that consistent estimates of the break fraction can be obtained through the minimization of the sum of squared residuals when there is I(2) cointegration. The finite sample performance of the proposed statistic is investigated by Monte Carlo simulations. The econometric methodology is applied to assess whether the US fiscal deficit and debt are sustainable. Copyright © 2010 John Wiley & Sons, Ltd.