A Theory of Optimal Inheritance Taxation

This paper derives optimal inheritance tax formulas that capture the key equity‐efficiency trade‐off, are expressed in terms of estimable sufficient statistics, and are robust to the underlying structure of preferences. We consider dynamic stochastic models with general and heterogeneous bequest tastes and labor productivities. We limit ourselves to simple but realistic linear or two‐bracket tax structures to obtain tractable formulas. We show that long‐run optimal inheritance tax rates can always be expressed in terms of aggregate earnings and bequest elasticities with respect to tax rates, distributional parameters, and social preferences for redistribution. Those results carry over with tractable modifications to (a) the case with social discounting (instead of steady‐state welfare maximization), (b) the case with partly accidental bequests, (c) the standard Barro–Becker dynastic model. The optimal tax rate is positive and quantitatively large if the elasticity of bequests to the tax rate is low, bequest concentration is high, and society cares mostly about those receiving little inheritance. We propose a calibration using micro‐data for France and the United States. We find that, for realistic parameters, the optimal inheritance tax rate might be as large as 50%–60%—or even higher for top bequests, in line with historical experience.     

Investigation of mixed model repeated measures analyses and non‐linear random coefficient models in the context of long‐term efficacy data

The longitudinal data from 2 published clinical trials in adult subjects with upper limb spasticity (a randomized placebo‐controlled study [NCT01313299] and its long‐term open‐label extension [NCT01313312]) were combined. Their study designs involved repeat intramuscular injections of abobotulinumtoxinA (Dysport®), and efficacy endpoints were collected accordingly. With the objective of characterizing the pattern of response across cycles, Mixed Model Repeated Measures analyses and Non‐Linear Random Coefficient (NLRC) analyses were performed and their results compared. The Mixed Model Repeated Measures analyses, commonly used in the context of repeated measures with missing dependent data, did not involve any parametric shape for the curve of changes over time. Based on clinical expectations, the NLRC included a negative exponential function of the number of treatment cycles, with its asymptote and rate included as random coefficients in the model. Our analysis focused on 2 specific efficacy parameters reflecting complementary aspects of efficacy in the study population. A simulation study based on a similar study design was also performed to further assess the performance of each method under different patterns of response over time. This highlighted a gain of precision with the NLRC model, and most importantly the need for its assumptions to be verified to avoid potentially biased estimates. These analyses describe a typical situation and the conditions under which non‐linear mixed modeling can provide additional insights on the behavior of efficacy parameters over time. Indeed, the resulting estimates from the negative exponential NLRC can help determine the expected maximal effect and the treatment duration required to reach it.     

Middle Managers’ Work in Recession and Austerity: A Longitudinal Study

Although researchers have explored the impacts of structural changes on managerial work, few insights have been generated into whether the turbulent economic environment induced by a recession and/or an extended period of austerity accelerate known changes to managerial work and/or whether recession/austerity are revealing or causing previously unknown effects. This paper explores and analyses middle managers’ reflections on how, if at all, their work is fundamentally changed by economic pressures such as recession and/or by choices of executives to impose such pressures during and post recession (commonly referred to as ‘austerity measures’). The findings suggest that middle managers responded to the recession and ongoing economic austerity in a differentiated manner, with the initial responses being largely positive. Responses became negative over time, with examples of disillusionment and cynicism, as middle managers believed that their superiors were using the disguise of recession and austerity to introduce changes that impacted profoundly on their working lives and those of their subordinates.     

A Bayesian approach for misclassified ordinal response data

ABSTRACT

Motivated by a longitudinal oral health study, the Signal-Tandmobiel^® study, a Bayesian approach has been developed to model misclassified ordinal response data. Two regression models have been considered to incorporate misclassification in the categorical response. Specifically, probit and logit models have been developed. The computational difficulties have been avoided by using data augmentation. This idea is exploited to derive efficient Markov chain Monte Carlo methods. Although the method is proposed for ordered categories, it can also be implemented for unordered ones in a simple way. The model performance is shown through a simulation-based example and the analysis of the motivating study.     

Temporal discounting of gains and losses of time: An experimental investigation

This paper investigates “asymmetries” between non-monetary gains and losses in intertemporal choice. We considered gains and losses of spare/working time with respect to a reference duration defined in a working contract. Specifically, we elicited a behavioral model of intertemporal choice that accounts for a gain/loss-dependent discounting function and a reference-dependent utility. Additionally, we did not impose preference for the present (positive discounting) and allowed for both decreasing and increasing impatience. While our results are standard regarding the discount of money (our baseline treatment), our subjects heavily discounted gains of time. More patience was observed for losses of time and a sizable portion of subjects even exhibited negative discounting, i.e. they preferred to expedite losses of time. Our econometric estimations also reveal a much larger heterogeneity of behavior in terms of both utility and discounting for gains and losses of spare time as compared to money.     

Permutation Tests for Comparing Inequality Measures

ABSTRACT

Asymptotic and bootstrap tests for inequality measures are known to perform poorly in finite samples when the underlying distribution is heavy-tailed. We propose Monte Carlo permutation and bootstrap methods for the problem of testing the equality of inequality measures between two samples. Results cover the Generalized Entropy class, which includes Theil’s index, the Atkinson class of indices, and the Gini index. We analyze finite-sample and asymptotic conditions for the validity of the proposed methods, and we introduce a convenient rescaling to improve finite-sample performance. Simulation results show that size correct inference can be obtained with our proposed methods despite heavy tails if the underlying distributions are sufficiently close in the upper tails. Substantial reduction in size distortion is achieved more generally. Studentized rescaled Monte Carlo permutation tests outperform the competing methods we consider in terms of power.     

An R Package for Value at Risk and Expected Shortfall

Value at risk and expected shortfall are the two most popular measures of financial risk. But the available R packages for their computation are limited. Here, we introduce an R contributed package written by the authors. It computes the two measures for over 100 parametric distributions, including all commonly known distributions. We expect that the R package could be useful to researchers and to the financial community.     

The construction,composition and rationale of immigrants’ network: The support strategies of Ghanaian immigrants in Toronto,Canada

In this article, we investigate the construction, composition and rationale behind the personal networks of recent immigrants to Canada. Drawing on egocentric-network analysis and interviews with 172 Ghanaian immigrants in Toronto, we reveal their networking strategies during their integration. First, we identify social locations that help create ties with different groups: workplaces and schools offer access to ties with non-immigrants and other immigrants alike, while religious and ethnic organizations facilitate ties to co-nationals (i.e., Ghanaians). Second, most individuals within immigrants’ network are co-nationals whose relationship began in Canada, followed by sustained transnational ties in the origin and diaspora and few ties with the non-immigrant. The nature of this network is explained by examining the migration project of immigrants together with the context of reception in Canada, which suggests a desire by immigrants to stay in Canada and make Canada their second home. The implications of these findings are discussed.     

Is there a causal relationship between oil prices and tourist arrivals?

This application note investigates the causal relationship between oil price and tourist arrivals to further explain the impact of oil price volatility on tourism-related economic activities. The analysis itself considers the time domain, frequency domain and information theory domain perspectives. Data relating to US and nine European countries are exploited in this paper with causality tests which include time domain, frequency domain, and Convergent Cross Mapping (CCM). The CCM approach is nonparametric and therefore not restricted by assumptions. We contribute to existing research through the successful and introductory application of an advanced method, and via the uncovering of significant causal links from oil prices to tourist arrivals.     

Correction to: Inequality in Education and Wealth in Tanzania: A 25-Year Perspective

Social Indicators Research - The article Inequality in Education and Wealth in Tanzania: A 25-Year Perspective, written Emmanuel Maliti, was originally published electronically on the...