DP7702 Durable consumption and asset management with transaction and observation costs
|Author(s):||Fernando Alvarez, Luigi Guiso, Francesco Lippi|
|Publication Date:||February 2010|
|Keyword(s):||attention costs, durable goods, household finance, liquidity choice|
|JEL(s):||D14, D83, D91|
|Programme Areas:||Financial Economics|
|Link to this Page:||cepr.org/active/publications/discussion_papers/dp.php?dpno=7702|
The empirical evidence on rational inattention lags far behind the theoretical developments: micro evidence on the most immediate consequence of observation costs - the infrequent observation of state variables - is not available in standard datasets. We contribute to filling the gap with two novel household surveys that record the frequency with which investors observe the value of their financial investments, as well as the frequency with which they trade in financial assets and durable goods. We use these data to test some predictions of existing models and show that to match the patterns in the data we need to modify these models by shifting the focus from non-durable to durable consumption. The model we develop features both observation and transaction costs and implies a mixture of time-dependent and state-dependent rules, where the importance of each rule depends on the ratio of the observation to the transaction cost. Numerical simulations show that the model can produce frequency of portfolio observations and asset trading comparable to that of the median investor (about 4 and 0.4 per year, respectively) with small observation costs (about 1 basis point of financial wealth) and larger transaction costs (about 30 basis points of financial wealth). In spite of its small size the observation cost gives rise to infrequent information gathering (between monthly and quarterly). A quantitative assessment of the relevance of the observation costs shows that the behavior of the investors is essentially unchanged compared to the one produced by a model with transaction but no observation cost. We test a novel prediction of the model on the relationship between assets trades and durable-goods trades and find that it is aligned with the data.