Abstract

The driving motivations behind the conference on Federal Fiscal Responsibility were an interest, in the reasons for and a concern about the long-term consequences of a dramatic shift in the pattern of American fiscal history that occurred during the second quarter of this century. Before the 1930s, budget surpluses were the dominant state of affairs; budget deficits have since come to dominate our fiscal life. The budget surpluses that were so normal prior to the Great Depression of the 1930s were used to amortize the federal debt that was created during times of war and recession. The federal government customarily resorted to deficit finance to pay for wars and to offset declining taxes during recessionary periods, but during normal periods the government redeemed this debt with surpluses of taxes over expenditures. In the years immediately following the creation of the American Republic, the federal budget was nearly always in deficit. As this tumultuous period drew to a close, the nation found itself saddled with a debt of $83.8 million, quite a substantial sum for those days. In response, Congress enacted the Sinking Fund Act of 1795. This act provided for budget surpluses to be generated, with the proceeds used to retire the national debt. Budget deficits once again ensued following the Panic of 1837, but with budget surpluses generally resulting thereafter until the Civil War. Between the Civil War and World War I, surpluses once again dominated budgetary policy, with the proceeds being used to reduce the national debt. And debt reduction prevailed after World War I until the onset of the Great Depression. With the Great Depression, this uniform, recurring pattern of fiscal history — deficits created during recessions and wars, with surpluses created during normal times to amortize the national debt — ceased.KeywordsFiscal PolicyPublic DebtBudget DeficitEconomic OrderBalance BudgetThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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