On Causality in Economics

This post tries to unsettle some of the methods used in economics today ‘ Regression analysis and Granger causality. Apart from this objective, the post also tries to understand the meaning (rather, meanings) of causality. Do we economists mistake correlation for causality’ Can we have a single method for capturing causality’

Causation is defined in the following ways:

-the action of causing or producing.

-the relation of cause to effect; causality

-anything that produces an effect; cause [Dictionary.com]

And the definition of Correlation is:

-mutual relation of two or more things, parts, etc. [Dictionary.com]

I once asked a professor who had offered to give a lecture for our Advanced Economic Theory class this: ‘Sir, is it possible to establish causation conclusively” He replied ‘That is simple. There are these tests- Granger test, Sims test, Sargent test, McClave-Hsiao test, Haugh-Pierce test, etc.’ And he wrote the names of these so-called ‘scientific’ tests on our black board.

What we often forget is that, there is no single and simple understanding of causation. There are various kinds of causality like epistemic, conceptual, factual, counterfactual etc. Causality in economics also are of different natures- poverty is causing unemployment, increased demand for oil has resulted in oil price rise, supply constraints are hiking up the price, etc. For instance, conceptually we know that poverty causes unemployment (vicious cycle of poverty) and that increased demand causes a concomitant price rise. In economics, it is important to have an account of both conceptual as well as factual causality.

For causality to be present between two variables A and B, it is necessary for them to be related in some way. This relationship among them can be of a linear nature or a non-linear one. If it is linear in nature, then it is called correlation. [Note that regression analysis (OLS) is based on correlation and is linear in nature.] But, correlation alone does not imply causation. Hence, all those who think that causation and correlation are the same make an inductive leap ‘ from correlation to that of causation.

As R G D Allen writes in his Statistics for Economics: ‘This statistical concept of correlation is quite neutral as regards causation. One of the variables may be ’caused’ by the other, but this can only be known from other than statistical considerations.’ Usually, causal hypotheses are derived from economic theory, because ‘data does not speak on its own’. We need to pass data through theory in order to make sense of it.

However, economic theory (like any other theory) contains a lot of assumptions, mostly unrealistic. What happens to causality then’ Causality, then is dependent on these assumptions. Hence, drawing inferences from such theoretical models for practical purposes should be undertaken with caution.

It is this caution that seems to be missing amongst econometricians. This will be evident after looking into the workings of Granger causality. Granger causality analyses probabilistic causality. However, this per se is not a limitation of the test. For, in social sciences, it is exceedingly difficult to talk about deterministic causes in real-world scenario- especially, in a macroeconomic environment.

Granger causality
If X and Y are probabilistically dependent and X precedes Y, then X causes Y.

And, in actual testing, Y is regressed on X (t) and also on X (t-1). If the latter regression is found to be more significant, then X is said to Granger-cause Y. In actual practice, there are economists who forget the prefix. That is, again, some sort of correlation analysis is carried out between Y and X (t-1). In any case, the concept of causation is a problem-ridden one. And as economists who contribute to policy-making, one ought to be on their toes all the time.

On Disguised Unemployment: Some Issues

This post discusses some of the broad theoretical issues underlying the category of ‘disguised unemployment’. The discussion is made clear by closely examining the hypothesis that Indian agriculture is plagued by the presence of high disguised unemployment.

Let us take a glimpse at the Economics textbook for class XI published by the NCERT. (NCERT 2006, p 131, Indian Economic Development)

‘Economists call unemployment prevailing in Indian farms as disguised unemployment. What is disguised unemployment’ Suppose a farmer has four acres of land and he actually needs only two workers and himself to carry out various operations on his farm in a year, but if he employs five workers and his family members such as his wife and children, this situation is known as disguised unemployment. One study conducted in the late 1950s showed about one-third of agricultural workers in India as disguisedly unemployed.’ (italics mine)

Is disguised unemployment unemployment’

A thought experiment. Suppose A and B are two similar countries ‘ both are equally populated. Now, a study has estimated disguised unemployment in country A to be 30% and in country B to be 10%. This implies that employment in country A is more than that of country B. Should this be of concern’ Must we try and reduce disguised unemployment in country A’

If so, what is the basis of ‘disguised unemployment” Do we see the principle of allocative efficiency present in disguise’ Disguised unemployment means that ‘labour’ is ‘inefficiently’ utilised. Attestation of this claim is done by showing the high share of workers employed in agriculture alongside the low contribution of agriculture to GDP.

The first draft of National Employment Policy (2008) reads thus: ‘Over half the workforce continues to depend on the agriculture even though it accounts for less than a fifth of the total GDP. This implies a vast gap in incomes and productivity between agriculture and non-agriculture sectors. This is mainly due to inadequate growth of productive employment opportunities outside agriculture.’ Is employment the need of the hour or is it contribution to GDP’ Which variable (employment or GDP) should be the criterion’ Why not improve the quality of employment in agriculture’ To attain quality, provision of infrastructural support is absolutely essential- credit facilities, good roads and increased railroad connectivity, storage houses, institutions so as to enable the farmers get a ‘decent’ price for their produce, etc.

In 1960-61, the share of agriculture, forestry and fishing in total GDP was 53% (at 1993-94 prices). This came down by around 30 percentage points to 22% in 2002-03. On the other hand, the share of agriculture, forestry and fishing in total employment was 75.9% in 1961; by 1999-2000, it had come down to 59.9%. [The Oxford Companion to Economics in India, ed Kaushik Basu, OUP: New Delhi, 2007, p. 11]

The above discussion attains significance when we view agricultural workers as those who are trying to make a livelihood out of various jobs ‘ farm and non-farm employment and self-employed and casual labour. ‘Employment’ mainly refers to wage employment. In India, out of total employment, the share of self-employment is the highest. As Amit Bhaduri writes, the economic activities predominant in the agricultural sector (or rural or informal) can be called as ‘survival strategies’. [Bhaduri 2006, Employment and Livelihood, in Employment and Development: Essays from an Orthodox Perspective] He cautions the policy makers on the use of dual-sector models in framing development policies for India owing to the heterogeneity prevalent in rural India and also because of the specificities present in the unorganised agricultural sector. Hence, the notion of ‘surplus labour’ loses much of its weight. In turn, we need to carefully look at ‘disguised unemployment’ for it disguises a lot of specificities of rural India.

2009 (Nobel) Prize in Economics

The Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel was established in 1968. Technically, there is no ‘Nobel’ prize in Economics; on the website of Nobel foundation, amongst Nobel Prize in Physics, Chemistry, Medicine, Literature and the Nobel Peace Prize, we have our ‘Prize in Economics’. The prize will be announced on the following Monday, the 12th of October. As always, consensus is impossible, for economics has given birth to too many sub-disciplines in the past few decades.

A brief round-up on the web seems to suggest/predict the following winners:

1) Thomson Reuters has predicted 6 winners- William D Nordhaus and Martin L Weitzman being two of the predicted winners. I have highlighted them, for it is their work in ‘environmental economics’ which is considered to be pioneering. The other economists who are mentioned have contributed to behavioral economics and monetary economics. Amol Agrawal at Mostly Economics, provides his views on the Reuters prediction.

2) Eugene Fama ‘ for his ‘contributions’ to portfolio theory and asset pricing. It has to be a joke! (See the Wall Street Journal and Chris F. Masse at Midas Oracle, a blog about ‘predictions’.)

3) Inflation Targeting, according to Ajay Shah is path-breaking, and if given a chance, he would vote for J B Taylor and M Woodford.

4) And, comments on blog posts that discuss the ‘Nobel’ prize in economics show that each commenter wants/feels a particular economist should win the Prize, which is natural. Not much is spoken about Jagdish Bhagwati this time.

5) Robert Vienneau writes that Luigi Pasinetti and Paul Davidson should win the Prize, but they wont. For it is not surprising that Nobel prizes have not been awarded to heterodox economists. Yes, the prize winners in Economics have mostly worked within the Neoclassical framework, although, they have extended and utilized microeconomics and neoclassical general equilibrium by modifying it to a variety of problems – health, environment, behaviour, neuroscience, geography, etc. Hence, economics now is not only related to employment and poverty, but also to issues of climate change, complexities in human behaviour, legal theory (via law and economics) and so on and so forth.

I think it would be a right time to award the prize to a heterodox economist. There seems to be some problem (a lot of problems) with mainstream theory ‘ a version of neoclassical theory. However, awarding it to an economist who has pointed out (and who still point out like Davidson, Garegnani, Pasinetti and many others) logical inconsistencies or unrealistic assumptions will be a bad move; as it will undermine the entire research programme of neoclassical economics. Hence, the award could go to an economist who uses neoclassical tools more or less, but in an unconventional way. For instance, for contributions to a theory of technical progress (Paul Romer), for research conducted in green accounting (William Nordhaus), using neuroscience to understand economic (read human) behaviour ‘ neuroeconomics (Ernst Fehr), etc.

What is a Laureate’
A Laureate is a recipient of honour or recognition for achievement in an art or science. [FAQ, Nobelprize.org]

Achievement: Is there an ‘objective’ way of deciding’ No. Note that most of the predictions made are based on citations of the economists’ works. In any case, let us see what Monday brings forth!

More on Nobel Prize in Economics

G Omkarnath, Nobel Economics, The Hindu, 2003.

Jayati Ghosh, The Nobel prize for economics may need its own bailout, Guardian.co.uk, 2009.

On the Unorganised Sector in India

This post very briefly touches some aspects of the informal sector in India. Since, this sector is not organised strictly on the lines of capitalist systems, theoretical models find it difficult to accommodate them. And owing to the wide cultural and social differences in India, the informal sector is to that extent heterogeneous and differentiated. But, the first step is to identify such a sector and to broadly identify similarities, especially with respect to the production process and the organisation of the production process. It should be noted that the existence of a large ‘unorganised sector’ is not a problem; rather, it is a peculiar characteristic of the Indian Economy. And theory is supposed to be made in accordance with specificities of an economy and not the other way around.

The significance of the unorganized sector is seen when one takes a look at the NSS survey 1999-2000 ‘ around 92% the Indian workforce (around 370 million workers) is employed in the unorganised sector. This is an extremely large section of India. Hence, any macroeconomic analysis (fiscal policy, monetary policy, international trade, etc) ought to look at this section of the Indian society.

The unorganized sector consists of small economic entities which are diverse and differentiated in nature. This sector (a.k.a. informal sector) is larger than the organized sector in terms of the relative share in GDP as well as the workforce. Moreover, the unorganised sector produces about 60 per cent of India’s GDP and also provides livelihood to nearly 93 per cent of the work force. [Kabra 2003] Whereas a report by National Commission for Enterprises in the Unorganised Sector (NCEUS) ‘estimated the un-organised/informal sector workers as comprising about 86% of work force in the Indian economy in 2004-2005 and informal employment both in the organised and unorganised sector as 92%.’ How can any macroeconomic analysis/model leave this sector out’

Now, let us move on to how data is generated for this sector. As the ‘establishments’ in the informal sector are not governed by any legal provisions, no regular data is available such as that of the corporate (organised) sector. The Annual Survey of Industries (ASI) ‘provides statistical information to assess and evaluate, objectively and realistically, the changes in the growth, composition and structure of organised manufacturing sector comprising activities related to manufacturing processes, repair services, gas and water supply and cold storage’ pertaining to the organised sector. [ASI 2005-06] Based on the Population Census (PC), the Economic Census (EC) is prepared which forms the reference for carrying out surveys to capture the informal sector. These surveys are conducted by the NSSO and are called as enterprise surveys.

To sum up, it is evident that the informal sector is an important contributor towards GDP as well as in terms of providing ‘livelihood’ to a large section of the Indian populace. And, we have data sources such as NSSO data which try to capture the process of production in the informal sector and their economic characteristics, which need to be looked at urgently. For any development process that does not explicitly address the informal sector will be blind towards the Indian reality!

References:

Kabra, Kamal Nayan (2003), The Unorganised Sector in India: Some Issues Bearing on the Search For Alternatives, Social Scientist, Vol. 31, No. 11/12 (Nov. – Dec., 2003), pp. 23-46.

ASI 2005-06, Introduction, Accessed at http://www.mospi.nic.in/stat_act_t3.htm on 26th September, 2009.