Economists seem to be adding to their technical vocabulary words like Southern Oscillation Index and Indian Ocean Dipole, causing much consternation (and probably merriment) among the policy hierarchy, lay public and investors worried about economic conditions. I have absolutely no idea of meteorology (having squandered half a maths paper on Dynamics in my then Calcutta University BSc Economics Honours ancillary course), save the vague understanding that Navier-Stokes equations used extensively in weather modelling are closely related to the Partial Differential equations that are a staple of economic dynamics, used in modelling the growth-inflation tradeoff. What also works is a fascination for the ‘Butterfly Effect’ where ocean temperatures half a hemisphere away influence precipitation in the Gangetic plains.
But the presumed links between global climatic conditions and Indian agricultural output have manifold implications: RBI response to future inflation and food prices, India’s GDP growth, policy responses to mitigate the impacts of rainfall volatility, including fiscal stabilisers, and a host of others. Although there is much to occupy RBI minds in calibrating policy, agricultural prospects will certainly be one, particularly given the hysteresis of recent memory of food inflation. Understand the phenomenon or not, it is worthwhile to check the effects (the output) of many of these arcane input conditions.
A little aside in defining the terms first, sourced from, where else, Wikipedia. El Nino is a band of anomalously warm ocean water temperatures that periodically develop off the Pacific coast of South America. Extreme climate change patterns, oscillations fluctuate across the Pacific Ocean which results in fluctuating droughts, floods and crop yields in varying regions of the world. La Nina is the opposite, the cold phase. The Southern Oscillation is the atmospheric component of El Nino. The capitalised term El Nino refers to the Christ child, Jesus, because periodic warming in the Pacific near South America is noticed around Christmas.
The first hypothesis is that El Nino conditions are correlated with the intensity and spatial spread of rainfall in India. The accompanying table (credit to Abhaysingh Chavan) is a crosstab of El Nino years (the horizontal bars) and rainfall intensity (columns). The abbreviations on the rows are the intensity of the El Nino/La Nina phenomena (S for strong, M for medium and W for weak), the classifications taken from the Australian Meteorological Bureau. The rainfall classification (and range) is of the Indian Meteorological Department.
Of the 64 years for which we have data (1951 to