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The purpose of this paper is to test whether households with members that experience job loss shocks are able to protect their previous level of consumption. The paper also tests whether consumption protection is affected when spells persist through time.

The paper estimates an intertemporal consumption model, where households try to smooth their marginal utility over time. For that purpose it analyses Spanish household budget surveys that span a long period, 1999-2012, including the Great Recession. Unlike most consumption datasets, this microdata is designed as a panel and provides detailed information for all consumption categories as well as household members’ labour status.

The paper finds that consumption smoothing is dependent on the household member facing the unemployment transition. In particular, only main breadwinner’s unemployment transitions affects consumption smoothing. It also shows that the consumption drop persists beyond the period of the job loss for ongoing spells, although it follows a decreasing pattern. Finally, the estimation results are stable over the business cycle.

The results suggest that Spanish households are not capable of fully insuring against main breadwinner’s unemployment shocks. Further, the results show that this effect remains up to two years for ongoing unemployment spells. Thus these results highlight a welfare loss by Spanish households with unemployed members.

The paper extends the usual analysis of job loss shocks by the main breadwinner to include the cases of both the spouse and the rest of household members, who tend to account for most unemployment. Further, it tests for unemployment persistence. Finally, it checks the sensitivity of the results to the business cycle, including the Great Recession.

This study analyses how the socio-demographic profile of the tourist, trip-related characteristics, distance, and economic conditions in the source country affect pleasure tourists' length of stay behaviours in Barbados.

The study uses “biggish” data (over 3.6 million observations), parametric models (OLS) and statistical learning models (regression trees) to develop a length of stay decision rule to segment pleasure tourists' length of stay. Our sample period is January 2004 to March 2013.

The analysis revealed a great deal of heterogeneity in the impact of the predictors across segments, which would be typically hidden from simple parametric approaches often used to model length of stay (such as OLS).

The main implication is that conventional models of length of stay should be complemented with segmentation analyses to shed some light on the heterogeneous length of stay behaviours of specific market segments.

Many studies on small tourism-specialising states focus on modelling aggregate arrivals. By modelling micro-data for Barbados, we provide insights on this aspect of tourism demand for small states. Second, very few studies use classification tools to analyse length of stay. The study contributes to the literature through its methodological approach.