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year". The choice of the base year used to compute the real GDP index is important. Relative prices in the base
year tend to reflect relative production costs at that time. As GDP and GDP components are computed for peri-
ods further away from the base year, the accuracy deteriorates. Going forward from a base year, estimates of
real GDP growth tend to be biased upward, with the bias rising as time passes. This occurs because the relative
price of goods that embody rapid technical innovations, such as computers, falls, while relative prices of low-
tech goods like coffee cups rise. And production moves with relative prices. Computers are a rising share of
GDP while coffee cups are a falling share. So using a fixed base year that holds relative production technology
constant results in an upward bias in the estimated production costs of high-tech goods in GDP.
The United States revises its base year about every five years. The base year for real GDP was recently
moved up from 1982 to 1987. As a result "real" GDP growth over the eighties was revised down slightly. The
Soviet Union took much longer to revise its base year. Until the sixties the Soviets used 1928 as the base year
for computing "real" GDP. Therefore, published data on growth rates were biased upward by a large percent-
age, and the underlying weakness in the Soviet economy was obscured. The Bureau of Economic Analysis
(BEA) plans to publish a measure of real GDP and major components using a shifting base year. This measure
will provide a more accurate representation of growth in years far from the 1987 base period. I strongly rec-
ommend sliding base (or "chain") measures in studies using a decade or more of real GDP data.
In practice BEA first uses the raw data on production to make estimates of nominal GDP, or GDP in cur-
rent dollars. It then adjusts these data for inflation to arrive at real GDP. But BEA also uses the nominal GDP
figures to produce the "income side" of GDP in double-entry book-keeping. For every dollar of GDP there is a
dollar of income. The income numbers inform us about overall trends in the income of corporations and individu-
als. Other agencies and private sources report bits and pieces of the income data, but the income data associated
with the GDP provide a comprehensive and consistent set of income figures for the United States. These data can
be used to address important and controversial issues such as the level and growth of disposable income per cap-
ita, the return on investment, and the level of saving.
In fact, just about all empirical issues in macroeconomics turn on the GDP data. The government uses the
data to define emerging economic problems, devise appropriate policies, and judge results. Businesses use the
data to forecast sales and adjust production and investment. Individuals watch GDP as an indicator of well-
being and adjust their voting and investment decisions accordingly. This is not to say that the GDP data are al-
ways used or used wisely. Often they are not. Nor are the GDP data perfect. But ignoring the GDP data is as
close as one can come in macroeconomics to ignoring the facts. And that is a perilous practice.
HYPERINFLATION
By Michael K. Salemi
Inflation is a sustained increase in the aggregate price level. Hyperinflation is a very high inflation. Al-
though the threshold is arbitrary, economists generally reserve the term hyperinflation to describe episodes
where the monthly inflation rate is greater than 50 per cent. At a monthly rate of 50 per cent, an item that cost
$1 on January 1 would cost $130 on January 1 of the following year.
Hyperinflations are largely a twentieth-century phenomenon. The most widely studied hyperinflation oc-
curred in Germany after World War I. The ratio of the German price index in November 1923 to the price index
in August 1922 – just fifteen months earlier – was 1.02 × 1010. This huge number amounts to a monthly infla-
tion rate of 322 per cent. On average, prices quadrupled each month during the sixteen months of hyperinfla-
tion.
While the German hyperinflation is better known, a much larger hyperinflation occurred in Hungary after
World War II. Between August 1945 and July 1946 the general level of prices rose at the astounding rate of
over 19,000 per cent per month, or 19 per cent per day.
Even these very large numbers understate the rates of inflation experienced during the worst days of the
hyperinflations. In October 1923, German prices rose at the rate of 41 per cent per day. And in July 1946, Hun-
garian prices more than tripled each day.
What causes hyperinflations? No one-time shock, no matter how severe, can explain sustained (i.e. con-
tinuously rapid) price growth. The world wars themselves did not cause the hyperinflations in Germany and
Hungary. The destruction of resources during the wars can explain why prices in Germany and Hungary would
be higher after them than before. But the wars themselves cannot explain why prices would continuously rise at
rapid rates during the hyperinflation periods.
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