The Home Bias in Equities and Distribution Costs

We show that incorporating distribution costs into a general equilibrium model of international portfolio choice helps to explain the home bias in international equity investment. Our model is able to replicate observed investment positions for a wide range of parameter values, even if agents have an incentive to hedge labor income risk by purchasing foreign equity. This is because the existence of a retail sector affects both the correlation of domestic returns with the domestic price level and the correlation between financial and non‐financial income.     

Overconfidence and optimism: The effect of national culture on capital structure

This study assesses whether variations in capital structure across countries can be explained by cultural traits. We analyze capital structure choices of firms in 42 countries and provide evidence that these decisions are affected by the degree of individualism of the country where the firm is located. We assert that managers in countries with high level of individualism exhibit strong optimism and overconfidence which cause an upward bias in perception of supportable debt ratios. Our results are robust to controlling for other firm- and country specific determinants of capital structure choices and to using alternative model specifications and estimation techniques.     

When do MNCs fail to learn from prior failure experience?

Do multinational corporations (MNCs) learn from their prior failures in international joint ventures (IJVs)? When does decision makers’ cognitive inability hinder MNCs from learning through their prior failure experiences? In the context of IJV survival in subsequent IJV entries, this study compares predictions made from two distinct theoretical perspectives, both of which belong to the behavioural school in strategy literature. According to the performance feedback perspective, MNCs may effectively learn from their prior failure experiences gained in familiar decision‐making contexts. On the other hand, according to the cognitive bias perspective, MNCs may not be able to effectively learn from their prior failure experiences if they inaccurately interpret the causes of their prior failures. The results provide partial support for the notion that MNC decision makers may not be able to effectively learn from their prior failures because of their cognitive biases. Copyright © 2015 ASAC. Published by John Wiley & Sons, Ltd.     

Kernel-type estimators for the distortion risk premiums of heavy-tailed distributions

A new kernel-type estimator for the distortion risk premiums of heavy-tailed losses is introduced. Using a least-squares approach, a bias-reduced version of this estimator is proposed. Under suitable assumptions, the asymptotic normality of the given estimators is established. A small simulation study, to illustrate the performance of our method, is carried out.     

Asymptotic comparison at optimal levels of reduced‐bias extreme value index estimators

In this article we are interested in the asymptotic comparison, at optimal levels, of a set of semi‐parametric reduced‐bias extreme value (EV) index estimators, valid for a wide class of heavy‐tailed models, underlying the available data. Again, as in the classical case, there is not any estimator that can always dominate the alternatives, but interesting clear‐cut patterns are found. Consequently, and in practice, a suitable choice of a set of EV index estimators will jointly enable us to better estimate the EV index γ, the primary parameter of extreme events.     

Sample bias in contingent valuation: A comparison of the correction methods

Abstract

This article compares various methods for correcting contingent valuation aggregate benefits when the sample is known to be biased. A sample is defined as the population, and response rates are simulated on the basis of a measure of salience. The simulated response rates suffer from nonresponse bias and selection bias. Coefficient and benefit estimates that result from weighting and self‐selection correction approaches are compared with the true coefficient and benefit estimates. Our results indicate that at both low and high response rates the standard approach leads to bias, and either correction approach will reduce the bias in coefficient and benefit estimates.     

Is cognitive bias really present in analyst forecasts? The role of investor sentiment

This paper analyses four key markets within the European context. In this context, where the level of analyst coverage is lower than in the US setting, we aim to ascertain whether the origin of optimism in analyst forecasts in these markets is mainly strategic or whether it also contains an element of cognitive bias. Despite the fact that forecast errors lack the explanatory power to account for a significant percentage of the relationship between market sentiment and future stock returns, our new tests based on selection bias (SB1 and SB2), in conjunction with an analysis of abnormal trading volume, confirm the presence of both cognitive bias and strategic behaviour in analyst forecasts. This shows that, although regulation can reduce analyst optimism bias, the benefits are constrained by the fact that optimism bias is partly associated with cognitive bias.     

The impact of production offshoring on the skill composition of manufacturing firms: evidence from Italy

In this work we explore how the international outsourcing of production impacts the skill composition of employment within Italian manufacturing firms. In particular, our aim is to assess whether the choice to offshore production activities to cheap‐labour countries implies a bias in the employment of skilled workers relative to unskilled ones.

Using a balanced panel of firms covering the period 1995–2003, we set up a counterfactual analysis in which, by using a difference‐in‐differences propensity score matching estimator, we compare the dynamics of skill demand for treated and control firms while addressing the possible problem of selection bias.

Our results identify a ‘potential’ skill bias effect of production offshoring. In particular, we find that treated firms tend to show an upward shift in the skill ratio with respect to the counterfactual sample, but coefficients are not significantly different from zero. When we look at the elements of the skill ratio separately, we find that the skill bias is driven by a fall in the employment of production workers (blue collars), rather than by the increase in the employment of non‐production workers (white collars), thus providing further evidence on the unskilled labour‐saving nature of international outsourcing.     

Who votes for public environmental goods in California?: Evidence from a spatial analysis of voting for environmental ballot measures

Voting referenda provide direct evidence of the demand for public goods. A number of previous studies have used referenda to analyze the support for public environmental goods. These studies have used aggregate data from large jurisdictional units (usually counties) and summary income measures such as the mean or median, and have usually found that higher income areas offer greater support for environmental propositions. We examine environmental referenda voting in California using census block group data, spatial dependence controls, and detailed income distribution data. We find that household income has a negative marginal effect on environmental referenda voting for most of the income range when using census block data. In addition, controls for spatial dependence significantly reduce the magnitude of most coefficients. This suggests that OLS estimates of referenda determinants are biased. We also show that county level data may be subject to severe aggregation bias and might not be appropriate for referenda studies.