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Mr. Boll ino is an economist in the Research Department of the Bank of Italy, Rome; Mr. Rossi was an economist in the Fiscal Affairs Department of the Fund. This is a revised version of a paper presented at the seminar, “Surviving with a High Public Debt: Lessons from the Italian Experience,” in Castelgandolf, Rome, June 15-16, 1987, and will be forthcoming under the title “Public Debt and Households’ Demand for Monetary Assets in Italy, 1970-86,” in Surviving with a High Public Debt: Lessons from the Italian Experience, edited by F. Giavazzi and L. Spaventa. The authors would like to thank the participants in the seminar (especially J.A. Frankel, G. Galli, and A. Giovannini) and I. Angeloni, F. Cesarano, C. Cottarelli, and G. Marotta for many helpful comments and suggestions. Any opinions expressed are the authors’ own and do not necessarily reflect those of their institutions of affiliation.
See Banca d’Italia (1986a) and Commissione per lo Studio della Evoluzione della Ricchezza Finanziaria (1987), Appendix 1.A, where the methodological aspects of the estimation of sectoral wealth are also discussed.
Indexed CCTs are debentures whose yield is linked to the BOT rate. Given the present indexation system and the maturity characteristics of the two instruments, they should not necessarily be considered perfect substitutes.
For a complete survey of the main features and causes of financial innovations in Italy during the last decade, see Caranza and Cottarelli (1986).
We do not address here the more general, and sometimes neglected, issue of the role of sample information versus prior information in empirical analysis.
In a stochastic framework, closed-form solutions to the consumer’s control problem remain intractable for even a very simple representation of preferences such as those considered in Poterba and Rotemberg (1986). Therefore, in order to study the effects of changes in, say, interest rates and inflation on consumption and holding of assets, they need to revert to a deterministic environment.
If the direct taxation takes into account all interest income, then Vi = p [(R - rj)(1 - τ)]/[1 + R(1 - τ)], where τ is the marginal income tax rate. Given the present Italian system of taxation, we disregard this correction and consider net rates of return in the empirical part of this work.
In principle, μi can be made dependent on past history in several ways, such as weighted average of all lagged quantities and highest peak attained in the past. Notice that while the habit-formation hypothesis relies on the interpretation of equation (7) as a model of changing preferences whereby agents gradually learn from past experience, if omitted variables correlated with lagged quantities exist, the significance of λi may indeed reveal misspecification of the original demand system, rather than evidence of dynamic adjustment.
Although some data were seasonally adjusted, seasonal dummies were included in the regression to pick up any residual seasonality.
Banca d’Italia is the source for all data used in this paper. The only exception is given by the general (consumer) price index, pt, derived from the Instituto Céntrale di Statistica (ISTAT), Bollettino Mensile, various issues.
Basically, this implies computing the return on long-term bonds in R as the nominal one-period holding yield plus the ex post rate of capital gains as proxied by the rate of change of the average bond price (as estimated in Galli (1985)).
As usual, an additive error term has been appended to equation (8) and has been assumed to be normal, independently and identically distributed with contemporaneous singular covariance matrix, in observance of the adding-up constraint. Estimation and hypothesis testing has been carried out by means of the 4.0 Version of Time Series Processor (TSP).
It is interesting to note that the same evidence can also be inferred from a preliminary analysis of the Banca Nazionale del Lavoro’s Survey on Households’ Finances, based on a sample of its customers. We would like to thank M. Morciano and G. Raimondi for kindly providing us with the data.
Basically, we test whether the quantities
are jointly zero. This corresponds to the well-known implication of weak separability, i.e., the ratio of cross-price elasticities of assets i and j with respect to asset k is equal to the ratio of their expenditure elasticities.
The choice of computing price elasticities for a given total short-term financial wealth was made mainly to allow comparability with other portfolio studies. Other exercises were conducted by computing compensated and uncompensated price responses, which are available from the authors upon request. In assessing these figures, the obvious interactions among rates of return should be kept in mind (see Banca d’Italia (1986b)).