This paper shows that the stabilization of the unemployment rate between the pre-1930 and post-1948 eras is an artifact of improvements in data collection procedures. Prewar methods are used to construct postwar unemployment data that are consistent with the historical data. The constructed postwar series is nearly as volatile as the pre-1930 unemployment data. The constructed postwar data are systematically more volatile than the actual postwar data because the cyclical behavior of the labor force and productivity are misspecified in the construction procedures. The relationship between the actual and constructed postwar unemployment series is used to construct new historical data.

Traditional estimates of prewar GNP exaggerate the size of cycles because they are based on the assumption that GNP moves approximately one for one with commodity output valued in producer prices. This paper derives new estimates of GNP for 1869-1908 using an estimate of the actual relationship between GNP and commodity output. This estimated relationship is allowed to be time-varying and is derived from a regression covering the periods 1909-28 and 1947-85. The new estimates of GNP indicate that there has been much less stabilization between the prewar and postwar eras than is conventionally believed.

This study of output data for the periods 1866-1914 and 1947-82 shows that much of the apparent stabilization of the postwar economy is an artifact of the way the historical data are constructed. When the methods used to form the historical index of industrial production are replicated for the postwar era, the consistent data show less than half the stabilization apparent in modern data. The excess volatility of thehistorical data is due to the overrepresentation of materials and intermediate goods in the early indexes of total industrial production.

This paper argues that the collapse of stock prices in October 1929 generated temporary uncertainty about future income which led consumers to forgo purchases of durable goods. That the Great Crash generated uncertainty is evidenced by the decline in surety expressed by contemporary forecasters. That this uncertainty affected consumer behavior is shown by the fact that spending on consumer durables declined drastically in late 1929, while spending on perishable goods rose slightly. This effect is confirmed by the fact that there is a significant negative relationship between stock market variability and the production of consumer durables in the prewar era. "Uncertainty is worse than knowing the truth, no matter how bad"

This paper shows that the stabilization of the unemployment rate between the pre-1930 and post-1948 eras is an artifact of improvements in data collection procedures. Prewar methods are used to construct postwar unemployment data that are consistent with the historical data. The constructed postwar series is nearly as volatile as the pre-1930 unemployment data. The constructed postwar data are systematically more volatile than the actual postwar data because the cyclical behavior of the labor force and productivity are misspecified in the construction procedures. The relationship between the actual and constructed postwar unemployment series is used to construct new historical data.

This paper shows that the existing estimates of prewar gross national product exaggerate the size of cyclical fluctuations. The source of the exaggeration is that the original Kuznets estimates are based on the assumption that GNP moves one-for-one with commodity output valued at producer prices. New estimates of GNP for 1869-1918 are derived using the estimated aggregate relationship between GNP and commodity output for the interwar and postwar eras. The new estimates of GNP indicate that the business cycle is only slightly more severe in the pre-Worid War I era than in the post-World War II era.

There is a tendency to think of official government statistics as unambiguous measures of economic activity. In truth, however, nearly all of the available series are based heavily on assumptions, and are sensitive to the estimation techniques used. Furthermore, many of these assumptions and estimation techniques have been refined and improved over time. Whether these underlying assumptions are reasonable and whether the refinement of assumptions over time has been useful depends crucially on the questions one is trying to answer. For example, an estimate of consumption derived from data on retail sales may be perfectly adequate for planning future production, or setting government budgets, but may be disastrous for testing a subtle economic theory. Similarly, gathering more genuine consumption data might improve our current estimates of consumption, but a series that reflects retail sales for one era and genuine consumption for another could wreak havoc when used in estimating a time-series rela

The narrative approach to macroeconomic identification uses qualitative sources, such as newspapers or government records, to provide information that can help establish causal relationships. This paper discusses the requirements for rigorous narrative analysis using fresh research on the impact of monetary policy as the focal application. We read the historical Minutes and Transcripts of Federal Reserve policymaking meetings to identify significant contractionary and expansionary changes in monetary policy not taken in response to current or prospective developments in real activity for the period 1946 to 2016. We find that such monetary shocks have large and significant effects on unemployment, output, and inflation in the expected directions. Analysis of available policy records suggests that a contractionary monetary shock likely occurred in 2022. Based on the empirical estimates of the effect of previous shocks, one would expect substantial negative impacts on real GDP and inflation in 2023 and 2024.