Growth in India under NDA and UPA Governments: The Role of Luck vs. Skill


How well did the recent Indian governments manage the economy? In order to answer this question, several aspects of economic management, e.g., poverty reduction, export promotion, etc., should be considered. For this article, I only consider the growth story in India under the last three governments- NDA 3 (1999-2004), UPA 1 (2004-2009), and UPA 2 (2009-2014). All of these governments completed a full term in office and therefore we have enough information to judge their performance.

Economic growth measures the increase in average income in an economy. Income can be measured either in nominal terms or in terms of affordability. I am not interested in the nominal value of income because this does not tell us much about the standard of living. Instead, my primary interest is in measuring the amount of goods and services an average person can afford. This can be measured using the concept of GDP per capita in terms of Purchasing Power Parity (PPP) (World Economic Outlook 2016 by IMF).

During the time of the NDA 3 government, GDP per capita grew at an average rate of 6.1% which is undoubtedly a good rate. However, the economy performed much better during the time of the UPA governments; during UPA 1’s rule, the average growth rate was 9.4% while during UPA 2’s rule the average growth rate was 7.4%. Therefore, on the face of it, the growth rate was higher under the UPA governments and some commentators have indeed pointed that out in the past (Ghatak et al. 2014).

Does it necessarily mean that the UPA government was a better manager of the economy? We cannot draw any conclusion based upon just this much evidence. Let us think of an analogy. Suppose, we want to evaluate two workers and find out who is the better one. Merely looking at the output of each worker is not enough because output depends upon a worker’s skill as well as his luck. To the extent possible, we would want to determine who is more skilful because skill is replicable but luck is not. The same principle applies to the performance evaluation of governments too.

At different points of time, a country can be affected (either beneficially or adversely) by factors beyond its control- these are the elements of luck. For example, a country that depends on tourism may be adversely affected if there is an outbreak of a contagious disease such as Ebola in that country. A relative evaluation of different governments without adjusting for these external factors would mix up elements of luck and skill. As much as possible, we should filter out the elements of luck in order to have a better idea of the skill of a governing coalition in managing the economy.  Table 1 has a list of three external factors that potentially can affect the Indian economy. Each of them is an element of luck since they do not depend upon any policy choice of the Indian government.

Avg. Indian Growth Rate 6.1 9.4 7.4
Avg. U.S. Growth Rate 3.8 4.1 1.8
Avg. Annual Precipitation 977 1091 1111
Price of Crude Oil $33 $76 $99

Table 1: Average values for growth rate in India and potential external factors (Growth rate of U.S. is measured in percentages and is derived from data on its GDP per capita in PPP.  Annual precipitation is measured in mms. The price of crude oil is measured in terms of 2014 $ per barrell. Sources: U.S. GDP: World Economic Outlook 2016 by IMF; Precipitation: CRU, University of East Anglia; Price of Crude Oil: BP.)

The first external factor is the growth rate of the U.S. economy. For many years now, the U.S. is the largest export market for India. The reasons are quite obvious: India depends too much on the IT & ITES (Information Technology & Information Technology enabled services) industry, and the U.S. is clearly the largest market for these services. The U.S. used to account for slightly above 20% of Indian exports in 1998, exposing the Indian economy to the ebb and flow of the American economy (World Integrated Trade Solution Database). 

By 2014, that proportion reduced to 13% but this is still quite high.  As a result, if the American economy sneezes, then the Indian economy catches cold. We can see from Table 1 that the U.S. economy performed quite well during the time of UPA 1 and did quite badly during the time of UPA 2 because of the housing crisis. During the time of the NDA 3, there was a crisis in the tech industry which affected the U.S. growth rates in 2001 and 2002. We would expect that these troubles in the U.S. economy would hurt the UPA 2 government the most followed by the NDA 3 government.

The second external factor is the amount of rainfall. India still being an agricultural country depends significantly on the rains. As Table 1 shows, annual precipitation was substantially less (slightly over 10%) during the time of the NDA 3 government. It is quite natural to expect that this would hinder the growth rate of the Indian economy during this time. The third external factor is the price of crude oil. High oil prices force consumers to reduce their consumption of other goods. Since India is an oil importer, therefore such a substitution reduces demand for products that are made in India. As we can see from Table 1, oil prices were the highest during the time of UPA 2.

In order to have a better idea of the skill of a government, one needs to filter out these elements of luck. Therefore to implement this idea, I ran a statistical model (a “regression”) that controls for these three external factors and the identities of these governments. It turns out that the predicted growth rates from even such a simple model closely follow the observed growth rates (Figure 1).


Figure 1: Plot of Observed and Predicted Growth Rates (1981-2014)

Interestingly, when the external factors are controlled for, then the statistical evidence is clear that there is no perceptible difference in the performance of these three governments.

In the regression model, I estimate the coefficients of the three external factors and three dummy variables for these governments. Then I check if the coefficients of the dummy variables are pairwise different from each other. The differences are not significant even at the 10% level. So neither was the UPA 1 government the star performer nor was the NDA 3 government the laggard as it seems from the growth rates alone. The NDA 3 government was adversely affected by poor rainfall and there is strong evidence that this factor indeed lowers the growth rate of the Indian economy. The other two external factors do not seem to have a significant effect. 

Why is there no perceptible difference in the performance of the three governments? The UPA 1 government ruled at a time when external conditions were unusually favorable. For example, rainfall was normal in most of the years, the U.S. economy was doing well, and oil prices were at a moderate level. Hence, it was simply riding its luck. During the time of the UPA 2 government, its luck gave away and the economy’s performance declined even though many of the same people were at the helm of the government. The average growth rate of 7.4% is therefore a better reflector of the skills of the UPA regime because it was achieved under harsher conditions. However, compared to the NDA 3 government, the UPA 2 government still benefitted from favorable rainfall. Now consider how the results would have changed if average rainfall during NDA 3’s rule was same as the average rainfall during UPA 2’s rule. In that case, growth during NDA 3’s rule would have been approximately about 1.3% more than what was observed. Once this is added to NDA 3’s average growth rate of 6.1%, then the difference between the NDA and UPA governments almost vanish. In conclusion, once we account for these three external factors, the evidence is that both of these coalitions had approximately the same amount of skill in managing the economy.

For Reference: Ghatak, M., P. Ghosh and A. Kotwal. 2014. Myths and Reality: Growth in the Time of UPA. Economic and Political Weekly 49(16): 34-49

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Aniruddha Bagchi is an Associate Professor of Economics at the Coles College of Business, Kennesaw State University, GA, USA. He received his Ph.D. in Economics from Vanderbilt University. One of his areas of research is Industrial Economics. In particular, he is interested in examining the processes and institutions that encourage innovative activity. He has also written on the effect of regulation and economic outcomes.