On the estimation of the Lorenz curve under complex sampling designs

Statistical Methods & Applications - This paper focuses on the estimation of the concentration curve of a finite population, when data are collected according to a complex sampling design with...     

BETWEEN SCYLLA AND CHARYBDIS: INCOME DISTRIBUTION,CONSUMER CREDIT,AND BUSINESS CYCLES

We introduce a macroeconomic model with heterogeneous households and an aggregate banking sector in order to analyze the impact of rising income inequality under different credit scenarios. Growing inequality produces debt‐led consumption boom dynamics when the banking sector is characterized by a lower capital requirement and a higher willingness to lend. Instead, when inequality rises but the banking sector is highly regulated, aggregate demand and output fall. Our results also yield new insights on the appropriate fiscal policy reaction to stabilize the economy: acting on the progressivity of the tax system seems more effective than a proactive countercyclical fiscal policy. (JEL C63, D31, E62, G01)     

Psychological Distress in Older Portuguese Gay and Bisexual Men: The Mediating Role of LGBT Community Connectedness

Abstract

Objectives: Examining Psychological Distress (PD) among older Portuguese gay and bisexual men (GBM), and the mediator role of LGBT community connectedness (LGBTCC) of minority stress variables on PD. Methods: We performed a mediation analysis with LGBTCC as mediator between minority stress variables and PD with a sample of 110 elderly GBM. Results: We found moderate PD levels; LGBTCC was a significant mediator between concealment of sexual orientation and PD, but not between internalized stigma and expectations of rejection and PD. Conclusions: More attention is needed to Older Portuguese GBM’s mental health. LGBTCC is an important ameliorating factor for older GBM.     

Older and Wiser: How CEOs’ Time Perspective Influences Long‐Term Investments in Environmentally Responsible Technologies

Most theories of corporate governance argue that chief executive officers (CEOs) take less risk as they near the end of their career, and therefore are less likely to make major investments. This prediction is based on decisions related to firm‐specific benefits; however, it may not be generalizable to decisions that involve broad societal goals. In terms of societal investments, CEOs with a longer time perspective may be more likely, rather than less likely, to invest. In this paper, we argue that a CEO's future time perspective is fostered by shorter career horizons, longer tenures, higher organizational ownership and less short‐term compensation. We test these hypotheses on 150 observations from the US investor‐owned electric power generation sector over a three‐year unbalanced sample (64.3% of the population). We applied random‐effects generalized least squares (GLS) estimations to test our hypotheses, and found support for three out of four hypothesized relationships.     

A Bernoulli autoregressive moving average model applied to rainfall occurrence

Abstract

In this article, we propose a new model for binary time series involving an autoregressive moving average structure. The proposed model, which is an extension of the GARMA model, can be used for calculating the forecast probability of an occurrence of an event of interest in cases where these probabilities are dependent on previous observations in the near term. The proposed model is used to analyze a real dataset involving a series that contains only data 0 and 1, indicating the absence or presence of rain in a city located in the central region of São Paulo state, Brazil.     

speed of covergence to the extreme value distributions on their probability ploting parers

The speed of convergence of the distribution of the normalized maximum, of a sample of independent and identically distributed random variables, to its asymptotic distribution is considered in this article. Assuming that the cumulative distribution function of the random variables is known, the error committed replacing the actual distribution of the normalized maximum by its asympotic distribution is studied. Instead of using the arithmetical scale of probabilities, we measure the difference between the actual and asympotic distribution in terms of the double-log scale used for building the probability plotting paper for the the latter. We demonstrate that the difference between the double-log values corresponding to two probabilities in the upper tail is almost exactly equal to the logarithm of the distribution may not be uniform in this double-log scale and that the difference between the actual and asymptotic distributions, on the probebility plotting paper, may be a logarithmic, power, or even exponential function in the upper tail when the latter distribution is of Fisher-Tippett type I, but that difference is at most logarithmic in the upper tail for type II and III distributions. This fact is exploited to obtain transformed variables that converge tothe asymptotic distribution faster than the original variable on the probabilites plotting paper     

Problem structuring methods as intervention tools: Reflections from their use with multi-organisational teams

Problem structuring methods (PSMs), also known as soft OR approaches, are most commonly employed with teams formed by members who tend to operate within an overall framework of authority and accountability, and most of whom have the ‘power to act’ on their recommendations. However, other PSM users include teams whose members are drawn from different organisational settings to work on a problem of common interest. The multi-organisational nature of such multi-organisational teams (MOTs) adds further complexity to the PSM modelling and facilitation processes by increasing the potential for conflict regarding the problem. In addition, members of MOTs tend not to operate within an overall framework of authority and accountability and, therefore, do not necessarily have full authority to commit themselves to their joint agreements. This paper reports on the design and application of a PSM-based methodology with three such groups, within the context of a multi-organisational collaboration in the UK construction industry. The paper reflects on the apparent success of the intervention, discusses the appropriateness of PSMs in this particular intervention context, as well as the generalisibility of the findings to other PSMs and/or multi-organisational contexts. Directions for the research and practice of PSMs with MOTs are also presented.     

A Note on Whittle's Likelihood

The approximate likelihood function introduced by Whittle has been used to estimate the spectral density and certain parameters of a variety of time series models. In this note we attempt to empirically quantify the loss of efficiency of Whittle's method in nonstandard settings. A recently developed representation of some first-order non-Gaussian stationary autoregressive process allows a direct comparison of the true likelihood function with that of Whittle. The conclusion is that Whittle's likelihood can produce unreliable estimates in the non-Gaussian case, even for moderate sample sizes. Moreover, for small samples, and if the autocorrelation of the process is high, Whittle's approximation is not efficient even in the Gaussian case. While these facts are known to some extent, the present study sheds more light on the degree of efficiency loss incurred by using Whittle's likelihood, in both Gaussian and non-Gaussian cases.     

ERRATA CORRIGE: “ARE MUSLIM IMMIGRANTS DIFFERENT IN TERMS OF CULTURAL INTEGRATION?”

We are thankful to Michael Lundholm and Mahmood Arai for pointing us towards a coding error which invalidates the regressions in our paper. Correcting the code leads to a decrease in sample sizes, though much smaller than Arai et al. (2011) claim based on their “replication”. An appropriate redefinition of the variables and of the model specification allows us to reproduce the substance of the empirical analysis in our original published paper. Although the results are now less clear‐cut, our analysis remains essentially unchanged.     

Degradation modeling based on gamma process models with random effects

The random effects in a gamma process are introduced in terms of its scale parameter. However, the scale parameter affects both its mean and variance. Hence, the variation of the degradation rates and the within degradation increments are expected to be large. For some products, the random effects affect just the rate or just the volatility of the process. Thus, two modifications of the parameters' structure of the gamma process are proposed. One implies that the random effects affect just the volatility and the second just the rate. A Bayesian estimation approach is provided and implemented in two case studies.