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57
McFadden were also honoured for sharpening econometrics, the statis-
tical methods with which economic data are analysed.
Mr Engle and Mr Granger have crafted techniques that demand
even greater virtuosity at maths, but which are nevertheless crucial in
separating wheat from chaff. Mr Engle's work has helped build the
foundations for measuring and avoiding myriad types of risks in the
modern economy. He has studied the volatility – the severity of swings
– of time series ranging from inflation to the prices of securities. Any-
one who watches the stockmarkets knows that they undergo periods of
wild adolescent swings as well as times of geriatric languor. Until Mr
Engle came along, people interested in such things-financial types,
mostly, but also regulators-used crude measures of historical volatility,
looking back over a year, say, to see what the average of the swings
was. They would then use this as a gauge of likely future volatility.
Mr Engle's approach, ARCH (for autoregressive conditional het-
eroscedasticity, should you insist on knowing) gave researchers the
power to test whether and how volatility in one period is related to
volatility in earlier times. There often is a link, as casual observation
suggests. After several days of stockmarket upheaval, there may be
several days of calm. A 3 % rise or fall in shares is often heralded by
increasing volatility, much as an earthquake is preceded by tremors. Mr
Engle's high-powered maths has made market risk easier to forecast.
Thus banks and investors who use "value at risk" techniques to analyse
their portfolios owe much to Mr Engle. So does the Basel committee
which is drawing up new rules for banks' capital requirements.
Mr Granger's research was aimed more at coming to grips with
longer-term swings in economic growth, inflation and currencies than
with shorter bouts of risk and volatility. Macroeconomic data often
share some common features. GDP per head, for example, has tended
to grow over time (at least for as long as it has been reliably measured).
But the "trend" rate of growth discussed by forecasters – and, yes, by
journalists – is never as fixed as they make it seem: it can be influenced
by shocks like rising oil prices or wars.
This may obscure deeper relationships hidden in the data, posing
tricky problems for statisticians. Using standard statistical tools – de-
rived from things that do not change much over time, such as the dis-
tribution of people's heights – can be misleading. An economist using
58
these tools might conclude that a casual relationship existed where
none really does, and thus be fooled by a statistical mirage.
Mr Granger devised a clever solution to this, called co-integra-
tion. He made use of the notion of economic equilibrium- the idea that
variables tend to move towards particular values, and thus in a predict-
able direction. He found that when two sets of economic data are com-
pared, for example inflation and exchange rates, they can often be
treated with standard techniques. In collaboration with Mr Engle, he
worked to create tests for economists to ensure that they were getting
reliable results when making such comparisons.
Despite these sophisticated techniques, which economists now
apply as a matter of course, the analysis of economic data remains
messy. "Driving a Mercedes down a cow-track" is how Thomas Mayer,
an American academic economist, once described the application of
fancy tools to real-world phenomena that are not easy to model, much
less to measure.
Even so, the place of econometricians at the centre of economics
is now confirmed. Indeed, there now seems to be a dearth of the grand
theorists of days past. Specialisation – to use an economists' term – is
the order of the day. But then a good plumber is in greater demand than
any poet.
McFadden were also honoured for sharpening econometrics, the statis- these tools might conclude that a casual relationship existed where
tical methods with which economic data are analysed. none really does, and thus be fooled by a statistical mirage.
Mr Engle and Mr Granger have crafted techniques that demand Mr Granger devised a clever solution to this, called co-integra-
even greater virtuosity at maths, but which are nevertheless crucial in tion. He made use of the notion of economic equilibrium- the idea that
separating wheat from chaff. Mr Engle's work has helped build the variables tend to move towards particular values, and thus in a predict-
foundations for measuring and avoiding myriad types of risks in the able direction. He found that when two sets of economic data are com-
modern economy. He has studied the volatility – the severity of swings pared, for example inflation and exchange rates, they can often be
– of time series ranging from inflation to the prices of securities. Any- treated with standard techniques. In collaboration with Mr Engle, he
one who watches the stockmarkets knows that they undergo periods of worked to create tests for economists to ensure that they were getting
wild adolescent swings as well as times of geriatric languor. Until Mr reliable results when making such comparisons.
Engle came along, people interested in such things-financial types, Despite these sophisticated techniques, which economists now
mostly, but also regulators-used crude measures of historical volatility, apply as a matter of course, the analysis of economic data remains
looking back over a year, say, to see what the average of the swings messy. "Driving a Mercedes down a cow-track" is how Thomas Mayer,
was. They would then use this as a gauge of likely future volatility. an American academic economist, once described the application of
Mr Engle's approach, ARCH (for autoregressive conditional het- fancy tools to real-world phenomena that are not easy to model, much
eroscedasticity, should you insist on knowing) gave researchers the less to measure.
power to test whether and how volatility in one period is related to Even so, the place of econometricians at the centre of economics
volatility in earlier times. There often is a link, as casual observation is now confirmed. Indeed, there now seems to be a dearth of the grand
suggests. After several days of stockmarket upheaval, there may be theorists of days past. Specialisation – to use an economists' term – is
several days of calm. A 3 % rise or fall in shares is often heralded by the order of the day. But then a good plumber is in greater demand than
increasing volatility, much as an earthquake is preceded by tremors. Mr any poet.
Engle's high-powered maths has made market risk easier to forecast.
Thus banks and investors who use "value at risk" techniques to analyse
their portfolios owe much to Mr Engle. So does the Basel committee
which is drawing up new rules for banks' capital requirements.
Mr Granger's research was aimed more at coming to grips with
longer-term swings in economic growth, inflation and currencies than
with shorter bouts of risk and volatility. Macroeconomic data often
share some common features. GDP per head, for example, has tended
to grow over time (at least for as long as it has been reliably measured).
But the "trend" rate of growth discussed by forecasters – and, yes, by
journalists – is never as fixed as they make it seem: it can be influenced
by shocks like rising oil prices or wars.
This may obscure deeper relationships hidden in the data, posing
tricky problems for statisticians. Using standard statistical tools – de-
rived from things that do not change much over time, such as the dis-
tribution of people's heights – can be misleading. An economist using
57 58
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