The Hindu Business Line : Business cycle is `alive and well' and winning Nobel too

BUSINESS cycles attracted attention this week because Finn Kydland and Edward Prescott won this year's Nobel economics prize for their `highly innovative' analysis of economic policy and the driving forces behind business cycles. So, I pick to read Business Cycles and Economic Growth, edited by Pami Dua and published by Oxford University Press (www.oup.com) .

What are business cycles? They are "a type of fluctuation found in the aggregate economic activity of nations that organise their work mainly in business enterprises," explains a quote of Burns and Mitchell, in the intro. Much like sphincter muscles, "A cycle consists of expansions occurring at about the same time in many economic activities, followed by similarly general recessions, contractions and revivals which merge into the expansion phase of the next cycle."

Business cycle is `very much alive and well', notes Dua, putting together 16 papers on measuring, monitoring and forecasting economic activity, as a tribute to Geoffrey H. Moore, "the father of leading indicators, who devoted his lifetime to better understand and predict business cycles." Moore wrote in a poem: "User-friendly indicators, you've come a long way/ Since we charted by hand and punched cards the whole day." A rare feat for an economist to be poetic.

The first paper by Ernst A. Boehm on `economic indicator analysis' observes that in the absence of an ideal single monthly measure of real GDP, "we select roughly coincident indicators which, when combined into a combined index," will approximately reflect aggregate economic activity.

It concludes with a pitch for the Economic Cycle Research Institute (ECRI) that furnishes "up-to-date readings of the current state of the business cycle and its prospects for the US and 16 other market-oriented countries."

Victor Zarnowitz studies the `anatomy' of recent cycles and speaks of a challenge in tracking and forecasting — the need to distinguish `signal from noise in time series'. "The irregular component is to a large extent unpredictable random noise, and is often dominant in the short run." Philip A. Klein makes a case for lagging indicators: "Confirming what has happened is never as newsworthy as anticipating what is about to happen." Lagging signs can make good news leads, therefore.

On the turning points in the financial services industry, Lorene Hiris writes how past recessions began in the `goods-producing sector'. Now, "weakness in the growth of the increasingly important services sector can also contribute markedly to cyclical downswings in the economy." So, you need "an innovative set of coincident and leading indexes" for the service economy. When thinking of financial services industry, think of FIRE — finance, insurance, and real estate.

Michael P. Niemira introduces you to `time-variant component weighting in business cycle indicators', where he speaks of analytic hierarchy process methodology, which is "a direct method for deriving component weights based on predetermined criteria, such as a magnitude-of-move criterion."

Then I move to Andrew J. Filardo's paper on the 2001 US recession. There's the NBER Dating Committee, quite a suggestive name but it does something mundane, "dating the initial month of the recession". Economists never agree on dates, even after recession is over; so "the advance warning from different recession prediction models could vary considerably."

In dating business cycles, output alone is not enough, argue Allan P. Layton and Anirvan Banerji: "At the core of the matter is the philosophical notion of what defines an economy."

Mehdi Mostaghimi studies the performance of the new US composite leading economic indicators in predicting recession. The CLI was an index that was developed by the US Department of Commerce "by combining several major leading economic indicators, with the objective of maximising the predictability of a turning point in the business cycle from an expansion to recession and vice versa." In politics, this is called coalition.

In John B. Guerard, Jr's paper, you can read about random walk with drift (RWD) models, auto-regressive integrated moving average (ARIMA), difference-stationarity (DS), no-change (NoCH), and root mean square error (RMSE). He concludes thus: "If one uses a rolling 32 quarter estimation period and a one-period ahead forecasting RMSE calculation, the LEI forecasting errors are not significantly lower than those for the univariate ARIMA model forecasts." NoCH in your understanding?

Roy Batchelor writes about `confident indexes and the probability of recession: a Markov switching model' where he asks whether there is relationship between what people really feel about the economy as shown in `consumer and business confidence survey' responses, and the likelihood of recession. hen should we care about consumer sentiment, ask Detelina Ivanova and Kajal Lahiri. "Benefits from including consumer sentiment in models of consumption are the largest in periods when conflicting economics and socio-political factors cause high overall uncertainty and wide swings in near-term expectations of real personal income and, hence, wide changes in discretionary consumer spending."

Nobel laureate Lawrence R. Klein declares when writing on possibilities for indicator analysis: "Our long-standing conviction remains intact that detailed structural model building is the best kind of system for understanding the macro economy through its causal dynamic relationships, specified by received economic analysis." He talks of `quadruple-entry book keeping' in the `flow-of-funds (F/F) accounts', important for `financial market clearing'.

Vikas Chitre explores recessions and revivals in India during three decades from 1951, and talks of growth cycle in India's non-agricultural income moving "with a lag but contra-cyclically to the industrial cycle in the market economies of the world".

Dua joins Anirvan Banerji to write about monitoring and predicting business and growth rate cycles in the Indian economy, and hopes that leading index and its components "will successfully anticipate future cycles" in the current liberalised scenario. In another paper, the duo performs a sectoral analysis to predict improvement in the exports "with India moving into the cyclically sensitive (investment-driven) high-tech areas."

A business book to read in your errant sleep cycle, for good purpose.

Economics@TheHindu.co.in