International risk-sharing and lessons for EMU

Carnegie-Rochester Conference Series on Public Policy 51 (1999) 189-193 North-Holland www.elsevier.nl/locate/econbase

International risk-sharing and lessons for E M U A comment Tamim Bayoumi International Monetary Fund

This interesting paper looks in detail at an important set of results about the mechanisms by which risk-sharing occurs in the United States first discussed by Asdrubali, SCrensen, and Yosha. M@litz and Zumer first look at the impact on the U.S. results of some changes to the methodology, apply the same approach to some other countries, look at international risk-sharing using the same approach, and end up with some conclusions about EMU. I will discuss each of these issues in turn, but first it may be worth outlining the basic methodological approach taken by Asdrubali, SCrensen, and Yosha and this paper. The basic intuition for this work is the perfect insurance hypothesis, which says that in a world with full contingent markets consumption across individuals with similar utility functions consumption should move identically across all individuals, and hence also regions and countries. The intuition can be taken from the Lucas coconuts' model, in which the equilibrium involves all individuals holding a balanced portfolio of shares in all coconut trees. Dividends, and hence both income and consumption, are identical across all individuals. Asdrubali, SCrensen, and Yosha recognize that, in practice, such incomesmoothing is partial, and study the methods by which income and consumption are (or are not) smoothed across U.S. states. To do this they start with an identity associating gross state product (Y) with consumption (C) Y=

Y SI DI --C SI DI C

through various income processes: where S I is state personal income (i.e., income excluding corporate transactions), D I is disposable income, and C is consumption. Asdrubali, SCrensen, and Yosha transform this identity by taking logs, first differencing, dividing through by log(y), calculating expectations, and dividing by the right-hand side. They then note that the terms on the right-hand side are simply the OLS coefficients from regressions of the 0167-2231/99/$ - see front matter© 1999 Publishedby ElsevierScienceB.V. All rights reserved. PlI: SO167-2231(00)00009-9

change in the log of the various RHS components on the change in the log of output. The system is over-identified, in that the coefficients necessarily add to unity. This means that one only has to estimate three of the equations, leaving the fourth coefficient (and its standard error) to be inferred from the other estimation. It is, of course, possible that the choice of which equation to miss out could affect the standard errors, and they complicate things by using panel estimation rather than OLS and adding time dummies, but otherwise the logic is flawless. As with any identity, it is the interpretation which is more problematic. Asdrubali, S~rensen, and Yosha make a number of strong assumptions about this equation. The first is that output is exogenous of the rest of the model, so that one can use OLS to estimate structural coefficients. If not, as M@litz and Zumer note, there are simultaneity biases, an issue to which I will return in a moment. Second, while they make references to issues such as the corporate veil, they still tend to assume the coefficients are "structural," in the sense that they are independent of each other. To see why this might not be the case, assume for the moment that individuals do indeed see through the corporate veil. In this case, the effects of corporate saving and personal saving are offsetting, so that although each coefficient can be estimated, the results are not meaningful, in that any change in one coefficient will be offset by an offsetting change in the other coefficient. Even partial effects of this type will tend to undermine the structural nature of the results. Similar issues might be thought to occur with respect to the fiscal variable, although here they are careful to limit themselves to federal transactions. As relative federal transactions are offsetting, the Ricardian effects are probably small. A third assumption is that they generally attribute all smoothing achieved by corporations (the move from Y to SI) to cross-ownership of capital, and then compare it with the impact of government taxes and transfers (the move from SI to DI) and borrowing or lending by individuals (going from DI to C). With some caveats about the data (such as the treatment of capital gains and losses), steps 2 and 3 appear reasonable. But, as M@litz and Zumer point out, step one disregards the fact that corporations can both change their expenditure (i.e., investment) and borrow and lend. To be fair, the problem is that U.S. state-by-state data are essentially limited to gross state product and personal income, so the corporate side is always going to be a black box. Also, and nontrivially, the consumption numbers are based on retail sales data, which may overstate the fluctuations in consumption as durable goods are more important in retail sales than in overall consumption. In principle, however, if one had the data one could extend the identity to take account of these factors by simply adding to the 190

identity chain. In an ideal world, one could (for example) add the following: Y GNP (GNP-I) y = m G N P ( G N P - I) SI

The difference between output and GNP reflects factor flows, and represents the impact of ownership of capital (as well as diversification of labor income), the subtraction of investment shows the impact of changes in corporate spending, while the difference between GNP less corporate spending and total personal income would reflect the impact of corporate borrowing and lending. Indeed, there is almost no limit on the sub-channels one could add if one so wished; for example, differentiating between personal-sector borrowing (the difference between D I and C) and personal-sector changes in expenditure (the difference between C and consumption of nondurables, to which the theory really applies). Indeed, in each type of saving (corporate, government, and personal) one could differentiate between the roles of spending and borrowing in determining the smoothing of income. Having set the scene, let me return to the M~litz and Zumer paper. The paper starts by expressing concern about the assumption that output is independent of consumption, and tries to adjust for this by subtracting consumption from both sides. When estimating the full system without dropping one of the equations does not work, they take the U.S. framework pretty much as given, but change the method of estimation and add some additional variables which allow the coefficients to be changed by external circumstances. In some cases, these changes are sensible. They save degrees of freedom and allow the addition of national variables (such as the real interest rate) by measuring the data relative to the national average. They endogenize the impact of persistence of shocks on the coefficients, which Asdrubali, Sorensen, and Yosha discuss in a less formal manner. They discover some interesting relationships between the cycle and the coefficients, which lead them to speculate that changes in spending may be important in corporate income-smoothing. In the absence of direct evidence of investment spending, this is sensible. However, more can surely be done to differentiate the mechanisms that M61itz and Zumer wish to identify. For example, the state income data also provide details of income from interest, dividends, and rent (i.e., capital) to individuals. As this is the source of smoothing through capital, these receipts provide some upper limit on the smoothing from this source. In 1997, such receipts were about $1.1 trillion out of a $8.1 trillion economy. Hence, even if all of this represented income-smoothing (and Andy Atkeson and I in a study we did some years ago found that state-by-state receipts were very heavily correlated with national receipts), the maximum smoothing from this source would seem to be 1.1/8.1, or about 15 percent. At least one of their other choices is somewhat odd. They are unwilling to 191

accept the consequences of the identity and the implication that the system is over-determined so that one of the coefficients needs to be inferred. Instead of using this approach, they insist on estimating the smoothing coefficient exogenously using levels data (undifferenced), rather than first-differences of logs. Their justification for this is that if consumption is not perfectly smoothed, the model is misspecified. However, I do not understand why their approach solves this problem. In a subsequent paper by two of the Asdrubali, Scrensen, and Yosha authors (S¢rensen and Yosha, 1998, referenced in the paper) note that if consumption shocks are uncorrelated with income, but rather reflect changes in tastes, this does not bias the coefficients because the errors are in the dependent variable. Hence, all this noise does is to make the coefficient estimates less accurate. Luckily, the coefficients calculated by M@litz and Zumer are similar to those of Asdrubali, S0rensen, and Yosha in most cases, so this aspect of their approach has little impact. The exception is when they do a cross-sectional regression, when their estimates provide for large amounts of insurance, while the Asdrubali, Scrensen, and Yosha approach provides for very little. Here, surely Asdrubali, Scrensen, and Yosha are correct. What they are stating is that if (say) output per capita in Texas grows 1 percent faster than output in Pennsylvania for 34 years, consumption per capita will grow about 0.8 percent faster. The implication of the M@litz and Zumer calculation is that consumption would grow 0.3 percent faster, which to my mind is simply not plausible given the importance of wages in overall income. Incidentally, if simultaneity is an issue, the usual way of solving it is with instrumental variables. The equation used by Asdrubali, Scrensen, and Yosha to estimate the proportion of consumption which is not smoothed is: Ac = at + f l a y which looks very much like a Campbell-Mankiw regression estimating the proportion of liquidity-constrained consumers. However, when estimated by Campbell and Mankiw the coefficient on income is instrumented to get rid of simultaneity bias. In this approach, as output is assumed exogenous, this is not done. If one did not want to assume that output was exogenous, however, one could simply instrument the entire set of equations--i.e., run three-stage least squares. This would solve the problem of assuming that output is exogenous. The next thing M@litz and Zumer do is to apply the same framework to data on three other countries--Canada, the United Kingdom, and Italy. The model only works for Canada, which is a source for concern, although it may simply reflect the smaller data sets. What is surprising about this part of the paper, however, is less what they do than what they do not do. As the data include the spending side of the national accounts, one 192

could perfectly easily include more detail of corporate spending in such a regression. Indeed, Canada would seem to be the ideal candidate for doing the calculation correctly given it seems to have all of the data (except possibly provincial GNP). M@litz and Zumer then look at international data. They find much less consumption smoothing, but still decompose what there is into various channels. Here, however, they switch from using income data (as in the US case) to mixing data on expenditure and income. More precisely, they use the following identity: GDP .

GDP GNP C + I . . . C. GNP C + I C

The move from GDP to GNP represents factor flows plus government transfers (potentially important in the EC). GNP to total spending would then represent the impact of borrowing and lending (the current account). Finally, total spending to consumption measures the impact of business spending (Scrensen and Yosha do something very similar in the paper mentioned above). Both papers conclude that factor income has virtually no impact, although international governmental transfers do provide some cushioning. Most, however, is provided by government and corporate saving. Both papers also find that this movement in saving is dominated by changes in investment, not by borrowing and lending. The conclusion I come to is that co-ownership of factors of production and borrowing and lending are relatively unimportant currently across countries, while personal borrowing and lending are important for the United States. What does all of this have to do with EMU? Interestingly, here the paper by Scrensen and Yosha completely splits company with M@litz and Zumer. The former think that the lack of smoothing is a problems in a new Europe, given the lack of the exchange-rate instrument. M~litz and Zumer, on the other hand, argue that new insurance mechanisms will be created, and hence that all of this is good for EMU. My own view is somewhere in the middle. M@litz and Zumer have convinced me that the current account is not an important equilibrating force (would this be true in real terms, I wonder?). But monetary policy affects more than the current account; it also affects output directly, so that EMU may increase the variance of output. On the other hand, at least over time, more integrated capital markets will surely increase insurance and hence the ability of countries to cope with such shocks. It is what happens in the intervening period that will be interesting to watch.

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