Alesina, Alberto, Alessandro Prati, and Guido Tabellini, “Public Confidence and Debt Management: A Model and a Case Study of Italy,” NBER Working Paper 3135 (Cambridge, Massachusetts: National Bureau of Economic Research, October 1989).
Cottarelli, Carlo, and Mauro Mecagni, “The Risk Premium on Italian Government Debt, 1976–88,” IMF Working Paper 90/38 (Washington: International Monetary Fund, April 1990).
Giavazzi, Francesco, and Marco Pagano, “Confidence Crises and Public Debt Management,” CEPR Discussion Paper 318 (London: Centre for Economic Policy Research, May 1989).
Modigliani, F., and T. Jappelli, “The Determinants of Interest Rates in the Italian Economy,” paper presented at the Conference on “Debito pubblico, struttura produttiva e disoccupazione” (Rome: Consiglio Nazionale delie Ricerche, June 1988).
Carlo Cottarelli is an Economist in the Southern European Division of the European Department. He is a graduate of the University of Siena and holds a graduate degree from the London School of Economics and Political Science. Mauro Mecagni, an Economist in the Southern European Division of the European Department, is a graduate of Bocconi University in Milan. He received his doctorate from the University of Pennsylvania. The authors are grateful to Pierluigi Ciocca, Giampaolo Galli, Giampiero Gallo, Manuel Guitián, Lazaros Molho, Alessandro Penati, William Perraudin, Erich Spitäller, and Ignazio Visco for helpful comments. The reader is referred to Cottarelli and Mecagni (1990) for a detailed discussion of theoretical and empirical issues related to this paper.
Indeed, if Ricardian equivalence does not hold, an increase in the deficit (and/or the debt) will tend to increase aggregate demand and the real interest rate for given resources and/or money. In addition, increasing deficits and debt could affect real rates by increasing the “currency-specific” risk premium; an accumulation of debt may increase the likelihood of future monetization and inflation and may push up interest rates on all assets (public and private) denominated in the risky currency.
SCIs are financial intermediaries specializing in long-term credit for industrial and real estate investment. Although many of these institutions are public entities, they are largely independent from the government and have their own capital endowment and legal status; their assets are represented mainly by loans to the private sector, and their bonds are rated independently of those of the government.
The hypothesis that BTPs and SCI bonds behaved as imperfect substitutes during the period under consideration is sustained here by three arguments. First, during most of the period, a portfolio investment requirement forced banks to purchase SCI bonds, thus reducing their yield and, possibly, their yield variance. Second, although the relative default risk may not have changed in the period, a constant difference in the level of risk is in itself sufficient to induce imperfect substitutability. Third, and most important, the imperfections of Italian bond markets are likely to have deeply influenced the relative liquidity of the two assets and the variance-covariance matrix of their returns, particularly their yield correlation.
The expected yield differential δe required by the market increases with qg. This increase will henceforth be referred to as “relative supply effect,” although, in a mean-variance context it should be interpreted as a risk premium, since it corresponds to the increase in the expected yield differential required to move investors away from the minimum-variance portfolio—that is, to accept a higher risk; indeed, δe is zero only when the relative market supply of the two assets corresponds to the minimum-variance portfolio.
The regulation on the investment requirement changed over time and became progressively less relevant. In equation (1) the effect of the constraint is considered to be larger, the larger is the investment requirement in relation to the total demand of SCI bonds by banks (P*/Pb) and in relation to the size of the bond market (P*/B).
Intuitively, the increase in the coefficients occurs because the demand curves for BTPs and SCI bonds become less elastic to changes in the yield differential; consequently, a larger change in the differential is required to accommodate a shift in supply composition.
This is a reasonable assumption, since the profitability and capital adequacy of SCIs remained satisfactory throughout the period.
In this context, the probability of a “confidence crisis” is higher when the maturity of the debt is short and when a larger amount of debt comes to maturity in each period.
We have already observed that what we call “relative supply effect” could be seen as a component of the risk premium; strictly speaking, what we call “risk factors” should be seen as factors affecting the expected return of government bonds, not the variance (that is, the portfolio risk).
Although the term “maturity” will be used here for brevity, the average residual life was considered to allow for different amortization plans of BTPs and SCI bonds. The following procedure was used to derive the maturity-adjusted yield differentials: the yield of individual SCI bonds and BTPs was first collected on a quarterly basis from 1976 to 1988. A linear interpolation of SCI bond yields was then computed for each quarter. This interpolation served two purposes: first, it provided an estimate or SCI bond yields for maturities for which no SCI issue was outstanding; second, it helped to remove the high “noise” in individual SCI bond yields probably connected to market imperfections and to the small outstanding amount of each SCI bond issue. The differentials between the yield on each BTP issue and the corresponding interpolated yield were computed: thus, for each quarter, the number of available observations on the yield differential is equal to the number of outstanding BTP issues.
In this respect, the main reason for the inclusion of an error term in equation (6) is associated with the existence of a random disturbance in the demand for Government bonds. Therefore, unless the relative supply of government bonds (qg) is independent of demand conditions, qg in equation (6) is likely to be correlated with ηnt. Since qg = G/(P + G), even if we assume that G (the supply of BTPs) is exogenous, P (the supply of SCI bonds) is likely to be affected by the level of interest rates; finally, when the portfolio model of Section I is included in a macroeconomic model of the economy, it is clear that the interest rate levels, the yield differential, and P (and hence, qg) are determined simultaneously, and that qg is therefore likely to be correlated with ηnt. In what follows, however, we assume that at the quarterly level considered here, the composition of supply is not affected by the level of interest rates and that a random shock in the demand for government bonds is therefore entirely reflected in changes in the yield differential. This assumption is sustained by the long lags characterizing the supply response of SCI bonds to changes in the level of interest rates, due to the lagged response of investments and lengthy administrative procedures in the issue of SCI bonds.
To improve efficiency in finite samples, an iterative estimation procedure was implemented. The variance-covariance matrix, initially obtained from ordinary-least-square s (OLS) residuals, was re-estimated based on the GLS estimates, producing residuals then used in a second GLS estimate; all results in Table 1 refer to the tenth iteration. Seasonal dummies were included because of the seasonality of some regressors, A dummy on the differential on one BTP issue between 1981:1 and 1982:2 was also included. The coefficient on this dummy turned out to be very high (between 200 and 300 basis points in all specifications) and was probably due to a measurement error, which was removed in the third quarter of 1982.
As mentioned above, the coefficient onfnt (the maturity of the BTP on which the differential is computed) cannot be signed a priori; the fact that this coefficient is always negative in the estimates implies that the term of structure of interest rates, in the sample average, rises more steeply (or declines more gradually) for SCI bonds than for BTPs. This feature may be connected to differences in the relative supply of BTPs and SCI bonds along the maturity axis. Indeed, the supply of BTPs was always relatively larger on shorter maturities.
There are n, residuals for each period, but it is not clear what should be considered the lagged value of each residual: the residual on an interest rate differential of the same maturity in the previous period would be economically meaningful but is almost never observed, while the use of the residual on the same BTP issue observed in the previous period (that is, on the residual on the BTP characterized by a specific serial number) could hardly be explained in economic terms.
In order to check for the possibility that the autocorrelation of the residuals could be a symptom of spurious regression among nonstationary variables, Phillips-Perron unit root tests were applied to the variables used in the GLS estimation procedures. For all weighted time series, the presence of a unit root was always decisively rejected.
In equation (I) the response parameter of the real interest rate differential to the debt-to-GDP ratio was not statistically different from zero in samples until approximately the end of 1983; with the addition of the most recent information, the parameter increased in value and precision. Similarly, in equation (H), the increasing sample size coincided with a gradual increase in value of the relative supply parameter.
To allow, at least partially, for time dependence of the parameters, equation (I) was re-estimated on aggregate data by entering the debt ratio in a nonlinear fashion. Indeed, the perception of risk may be connected nonlinearly to public imbalance indicators: increases in the debt-to-GDP ratio may be considered irrelevant when the ratio is low but may attract attention when the ratio is already high. In order to explore this possibility, the response parameter of the debt-to-GDP ratio was allowed to vary according to a logistic function of the level of the ratio itself. The results did not improve upon those presented in Table 2. The significance of relative supply and of the portfolio constraint was confirmed, but the estimates for the debt ratio parameter and for the parameters of the logistic curve were statistically insignificant and nonrobust to selected starting values in sensitivity analysis. Although informative, this attempt to model nonlinearities is by no means conclusive; more attention will have to be dedicated in future research to alternative estimation methods involving switching regimes.
The estimate of the effect of changes in the relative supply may appear large and would imply low substitutability between BTPs and SCI bonds of the same maturity. However, as already mentioned, the estimates presented in this paper reflect the dominance in the sample of the portfolio constraint that reduced the substitutability between the two types of bonds; as a consequence, the estimates presented here tend to overestimate the effect on the yield differential of changes in relative supply (and indeed of risk factors as well) in the absence of a portfolio constraint. For a better appreciation of the relative importance of relative supply and risk factors in explaining the movements in the yield differential, the decomposition of the change in the differential between the beginning and the end of the sample period was also computed. Again, all specifications agreed that the overall effect of supply and risk factors was close to 400 basis points; when risk factors were present, they were estimated to account for one third of the overall effect, mainly as a consequence of the increase in the debt ratio. The effect on the yield differential of supply and risk factors was largely offset by the removal of the portfolio constraint, which allowed a decline in the yield differential of over 300 basis points.