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Fiscal readjustments in the United States: a nonlinear time-series analysis.

Article Excerpt
I. INTRODUCTION

The recent deterioration in U.S. budget deficit has raised serious concerns about the long-run sustainability of U.S. fiscal policy. In addressing this issue, many studies have examined whether U.S. fiscal policy respects the intertemporal government budget constraint. This constraint implies that Ponzi games in which the government rolls over its debt in full every period by borrowing to cover both principal and interest payments are ruled out as a viable option for government finances. The no-Ponzi game restriction, which is regarded as synonymous with sustainability, requires that today's government debt is matched by an excess of future primary surpluses over primary deficits in present value terms. This condition imposes testable restrictions on the time-series properties of key fiscal measures such as the stock of public debt, the budget deficit, and the long-run relationship between government expenditures and revenues.

In a seminal article, Hamilton and Flavin (1986) suggest that a sufficient condition for the intertemporal budget constraint to hold is for the deficit inclusive of interest payments to be stationary. Wilcox (1989) extends the work of Hamilton and Flavin by allowing stochastic interest rates and nonstationarity in the noninterest surplus. He shows that when the sustainability condition holds, the present value of the stock of public debt should be stationary and has an unconditional mean of zero. Trehan and Walsh (1988) generalize the Hamilton and Flavin result and show that if debt and deficits are integrated of order 1, and if interest rates are constant, then a necessary and sufficient condition for sustainability is that debt and primary balances (net-of-interest deficits) are cointegrated. Other studies examine the time-series properties of government spending and revenues. For instance, Hakkio and Rush (1991) show that a necessary condition for intertemporal budget constraint is the existence of cointegration between government expenditure (inclusive of interest payments) and government revenues. Quintos (1995) expands on Hakkio and Rush (1991) and introduces the concept of strong sustainability condition, which implies that the undiscounted public debt is finite in the long run.

More recent work has emphasized the importance of nonlinearity in the U.S. fiscal policy. This nonlinearity may arise if we expect fiscal authorities to react differently to whether the deficit has reached a certain threshold deemed to be unacceptable or unsustainable. Bertola and Drazen (1993) develop a framework that allows for trigger points in the process of fiscal adjustment such that significant adjustments in budget deficit may take place only when the ratio of deficit to output reaches a certain threshold. This may reflect the existence of political constraints that block deficit cuts, which are relaxed only when the deficit reaches a sufficiently high level deemed to be unsustainable (Alesina and Drazen 1991; Bertola and Drazen 1993).

Recent studies have found strong evidence of nonlinearity in U.S. fiscal policy. Using an exponential smooth transition autoregressive model and long-span data set starting from 1916, Sarno (2001) provides evidence of nonlinear mean reversion in the U.S. debt-to-gross domestic product (GDP) ratio. By using a threshold autoregressive model, Arestis, Cipollini, and Fattouh (2004) provide evidence of threshold effects such that policymakers will intervene to reduce per capita deficit only when it reaches a certain threshold.

In line with the above studies, we provide new evidence of strong nonlinearity in the U.S. fiscal policy. We contribute to the existing literature by extending the analysis of U.S. fiscal adjustment from a single-equation setting to a multivariate one using a nonlinear vector error correction model (VECM). This extension adds value both in terms of our economic understanding of the fiscal adjustment process in the United States and assessing the forecasting power of the model. First, using a multivariate threshold cointegration model, we are able to identify whether the government's solvency constraint in the United States is achieved through tax increases, spending cuts, or a combination of both. The issue of which specific item of the budget ensures fiscal readjustments has received considerable attention among U.S. policymakers and has been recently the focus of much heated debate. For instance, Rubin, Orszag, and Sinai (2004) argue that "balancing the budget for the longer term will require a combination of expenditure restraint and revenue increases." The authors believe that "the single most important act Congress and the Administration could take at this point to rein the budget over the next decade would be to re-establish the budget rules that existed in the 1990s. These put caps on discretionary spending and required that reductions in taxes or increases in mandatory spending be paid for with other tax increases or spending cuts." A study by the Congressional Budget Office (2003) also cautioned that "economic growth alone is unlikely to bring the nation's long term fiscal position into balance."

The contribution of the academic literature to this debate has been very limited. Alesina and Perotti (1995) find evidence that for fiscal adjustment to be permanent and effective, the focus must be on the level of expenditure rather than on taxation. (1) They argue that tax increases ease fiscal problems only temporarily. Temporary tax increases may also be very difficult to reverse, and as such, tax-driven deficit cuts may induce high tax ratios. Furthermore, raising taxes is unpopular, and there are doubts whether such a strategy can in fact increase government revenues. Bohn (1991) and Crowder (1997) rely on the government's intertemporal solvency condition to analyze the performance of fiscal stabilization plans over a long-term data span. Specifically, the budget item series showing most of the error-correcting dynamics is the one bearing most of the fiscal readjustment burden. Crowder (1997) shows that the large U.S. deficits in the 1980s and early 1990s have been primarily caused by increases in government spending rather than falls in tax revenues. Thus, in order to restore the intertemporal budget constraint, the bulk of fiscal readjustment should occur through government spending cuts rather than increases in tax revenues. Bohn (1991) shows that regardless of the shock that caused the high budget deficit, historically these deficits have been corrected by combination of both spending cuts and tax increases. Auerbach (2000) finds that both components of U.S. fiscal policy have been responsive to fluctuations in the deficit although the response from government spending has been much more important.

Our results reveal the following important findings. They provide support for the existence of trigger points in U.S. fiscal policy. Specifically, we find strong evidence of nonlinearity in the fiscal process where adjustment occurs only when the real deficit per capita reaches a certain threshold. Below this threshold, there seem to be no significant error correction effects, which may suggest that policymakers become sensitive to large deficits only when the deficit reaches the very "high" level deemed to be unacceptable or unsustainable. More importantly, we find that government expenditure shows the strongest error-correcting dynamics, and hence, the bulk of fiscal adjustment seems to occur through spending cuts rather than increases in tax revenue.

In addition to gaining better understanding of the U.S. fiscal adjustment process, we evaluate the out-of-sample density forecast and probability forecast performance of the estimated model. Our results highlight an additional advantage from generalizing the model from a single-equation to a multivariate setting. Specifically, the results of out-of-sample density forecast and probability forecasts suggest that there is an improvement in forecast performance when we move from a univariate autoregressive (AR) model to a multivariate model. We also compare the out-of-sample forecast performance of the linear and threshold models. In a recent...

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