Hedging Housing Risk in London

This paper investigates the benefits of allowing households to compensate the portfolio distortion due to their housing consumption through investments in housing price derivatives. Focusing on the London market, we show that a major loss from over-investment in housing is that households are forced to hold a very risky portfolio. However, the strong performance of the London housing market means that little is lost in terms of expected returns. Even households with limited wealth are better off owning their home rather than renting and investing in financial assets, as long as they are willing to face the financial risk involved. In this context, access to housing price derivatives would benefit most poor homeowners looking to limit their risk exposure. It would also benefit wealthier investors looking for the high returns provided by housing investments without the costs of direct ownership of properties. Comparisons with French, Swedish and U.S. data provide a broader perspective on our findings.     

Gender Differences in Financial Education: Evidence from Primary School

Today, financial and economic education is a primary issue in academia and among policy makers, and there is great interest towards programmes that are able to boost it. In this paper, we test whether a programme (“treatment”) of financial education on savings, targeted to children aged 8 and 9 is effective and to what extent. We measure the interest rate required by the children before and after the treatment to accept postponing a reward, computing its variation and comparing this with that of a control group. We find evidence that the overall initiative is helpful in decreasing the level of impatience of children and the number of inconsistent choices of boys. Our findings invite to reflect on the gender neutrality of programmes of financial education.     

Likelihood evaluation of models with occasionally binding constraints

Applied researchers interested in estimating key parameters of dynamic stochastic general equilibrium models face an array of choices regarding numerical solution and estimation methods. We focus on the likelihood evaluation of models with occasionally binding constraints. We document how solution approximation errors and likelihood misspecification, related to the treatment of measurement errors, can interact and compound each other.     

The Euro — A Tale of 20 Years: What Are the Priorities Going Forward?

Intereconomics - First, we need to recall the initial objectives set for the euro and how these have changed over time, notably due to the weaknesses that came to the fore throughout the recent...     

Analyzing online reviews in hospitality: data-driven opportunities for predicting the sharing of negative emotional content

Hospitality is one of the sectors that are nowadays most heavily characterized by consumers’ tendency to share online reviews on dedicated digital platforms. While most past work has focused on understanding the effect of online reviews and ratings on consumers’ evaluation and purchase decisions, this research tackles the issue of what drives the sharing of certain types of online content. Specifically, we investigate the sharing of user-generated content characterized by negative emotional valence, and study the effect of two factors on the extent to which user-generated content contains negative emotions. One such factor is reviewer's expertise, while the other is hotel quality. Our analysis of 1200 TripAdvisor reviews on Italian hotels located in three major Italian cities confirm our hypothesis that expert reviewers might share reviews containing less intense negative emotional content compared to less expert reviewers especially when the hotel is of high quality. To support our hypothesis, we build on the research on psychological antecedents of word-of-mouth behaviour suggesting that expert consumers are particularly reluctant to share negative word-of-mouth to avoid projecting a negative image of themselves in social contexts, thus possibly damaging their reputation.     

Identification of monetary policy in SVAR models: a data-oriented perspective

In the literature using short-run timing restrictions to identify monetary policy shocks in vector-auto-regressions (VAR) there is a debate on whether (i) contemporaneous real activity and prices or (ii) only data typically observed with high frequency should be assumed to be in the information set of the central bank when the interest rate decision is taken. This paper applies graphical modeling theory, a data-based tool, in a small-scale VAR of the US economy to shed light on this issue. Results corroborate the second type of assumption.