Not surprisingly, the agricultural output co-varies quite closely with rainfall as you can see in Panel A. But if you see Panel B, after 1995 the covariance with overall GDP shows reduction. This simply reflects the fact that the Indian economy seems to have diversified after the economic reforms of 1991.Important questions arise out of these pictures: Post liberalization, agriculture output continues to be at mercy of nature’s vagaries. This sector still employs significant proportion of working population (58%) compared to the non-agricultural sector(42%). If the overall GDP shows less sensitivity to rainfall shocks after 1995, then a relatively smaller section of working population seems to be insured from these shocks. This inequality in terms of insuring against real shocks and its implications for effective policy design are definitely worth exploring.

According to me, this doubled growth rate is a clear evidence that people in India responded to changed incentives and institutions.  Clearly, the rules and regulations we see now are more successful in fostering growth than the ones that were in place prior to 1980. Before 1980, the Indian economy was still characterized by the License Raj that was the result of the socialist (Nehruvian) policies. But later, the economy was slowly liberalized and moved towards a more market based economy. Thus, calling the lower growth rate as Hindu growth rate seems to be a misnomer as the people under the both regimes are still the same. I think it is high time we change the nomenclature to “Nehruvian growth rate” or ” a Socialist growth rate”!

It seems the only way out is to think hard about the real reforms that are required to reduce the severity of supply shocks and not ask the monetary policy to do all the work through its limited monetary policy tools. Food price inflation is not going to reduce unless the food grains policy is reformed and unless this happens RBI will not be able to do its job of managing money supply and its effects on inflation.The next important question is will the propose retail reforms help in any way to correct the food grain policy failures and ease food inflation?

The solution seems to be more long term than immediate. What is apparent from the above discussion is the limits on RBI’s ability to tame inflation and manage the exchange rate simultaneously. Food inflation being this limiting factor, it has become important to completely rethink the way the system of food grain policy is managed. Basu (2011b) makes a persuasive argument for one such solution. As a part of the solution, he suggests establishing a Standard Operating Procedure allowing intervention in the food market based on the current market price. As such policy is a rule based policy, it avoids the pitfalls of setting policy by discretion ( the famous rules vs. discretion debate) and hence stands strong on the grounds of economic efficiency. There are many other details of the policy which form an integral part of it, but an important point to note is that in itself poor storage facilities do not seem to be the primary reason for food price inflation. According to Basu, the reason why the FCI interventions do not seem to be effective is because they have a dampening effect on the food oftake which does not go well in case of shortage.

Given this analysis, would allowing foreign retailers with 51 % equity help reduce inflation? The requirement of back end investment in storage facilities may reduce wastage and hence have a somewhat favorable effect on the prices (at least the ones which farmers receive). How much of these efficiency gains would be passed on to the consumers will depend on the degree of competition between these retailers. So it seems the consumers as well as to some extent small farmers would stand to benefit from their entry. Also, because the government still would have the right to procure food grains, it would still be in the position to even out the market price fluctuations.  What about the small traders? There would obviously be some restructuring in the retail sector. However, it is hard to imagine the small traders completely vanishing.

Many of these small traders provide short term credit to buyers. This is important when there are many who would not qualify for a standard credit card. Secondly, labor being cheaply available, these shops are in a much better position to provide incentives like home delivery to buyers. Big retailers tend to require more space and have significantly less number of branches per consumer. Whereas small traders are numerous and hence would score much higher in terms of accessibility than the retail counter parts. I am sure one could think of numerous other such reasons, but the point is that there will not be a significant effect on number of small traders after the foreign players are allowed in. If at all there seems to be a strong argument for retail reforms being complimentary to government’s efforts towards controlling food inflation. I think RBI would certainly like that!

Basu Kaushik, India’s Food Grain policy, Economic and Political Weekly, February 29 2011b.

Basu Kaushik, Understanding Inflation and Controlling it, Economic and Political Weekly, October 8, 2011a.

Gokarn Subir, Food Inflation: This Time it’s Different, Kale Memorial Lecture, Gokhale Institute of Politics and Economics, Decemebr 9, 2011

http://mpra.ub.uni-muenchen.de/31564/

Yet another way of looking at the impact of the colonial rule is tie it to the current outcomes of different regions or countries. Lakshmi Iyer’s recent article belongs to this category. It “compares economic outcomes across areas in India that were under direct British rule with areas that were under indirect colonial rule.” She finds that areas that experienced direct rule have significantly lower levels of access to schools, health centers, and roads in the post colonial period.

Iyer Lakshmi, Direct versus Indirect Colonial Rule in India: Long-Term Consequences, The Review of Economics and Statistics, 92(4), November 2010, 693-713.

Abstract:

The new trade theory emphasizes the role of market-share reallocations across firms (“stealing”) in driving productivity growth, while the older literature focused on average productivity improvements (“learning”). We use comprehensive, firm-level data from India’s organized manufacturing sector to show that market-share reallocations did play an important role in aggregate productivity gains immediately following the start of India’s trade reforms in 1991. However, aggregate productivity gains during the overall 20-year period from 1985 to 2004 were driven largely by improvements in average productivity. By exploiting the variation in reforms across industries, we document that the average productivity increases can be attributed to India’s trade liberalization and FDI reforms. Finally, we construct a panel dataset that allows us to track firms during this time period; our results suggest that while within-firm productivity improvements were important, much of the increase in average productivity also occured because of firm entry and exit.

“First, not all policy choices are choices between alternative policy rules, and some  choices may merely represent alternative values of policy variables within a given policy rule, and these need not affect behaviour.  For this class of policy choices, Tinbergen models are no more subject to the Lucas critique than the models based on the ‘deep’ micro-foundation variables that he recommended.”

The reason why I say it stands out is because it betrays a half correct interpretation of the Lucas critique. What the authors are essentially saying is that not all changes in policy variables constitutes a change in  policy regime and hence an eventual change in the way people respond to such change.  So now the question is what constitutes a policy regime change and hence warrants the application of Lucas critique? Lets say that current policy rule is something like M2-M1=600 + 0.3 (Y2-Y1).  Let us say that people also know this rule and hence any change in money supply for a given change in output is going to be judged by this rule. If the change in money supply falls short or is more than what the rule predicts what would people think? They would think that something fundamentally has changed and hence they will revise their expectations implying a changed rule. What Lucas critique says is that now you cannot use the first rule to predict the effects of change in money supply which is out of sync with earlier policy rule. Any such change is bound to have effect on peoples’ expectations and hence the way they respond to changes in policy variables.

The above example demonstrates that if the money keeps on changing according to the rule that every one has come to expect then we could very well engage in policy analysis based in Tinbergen kind of models. But if the changes are not in sync with the rule then Lucas critique applies and we cannot use such policy analysis.  So using Tinbegrgen models for analysis without a test of regime change implies that the authors beleive that all the data for the given period has been generated by one policy regime. Is this assumption valid? The authors do not address this issue.

On another note, I did find a paper which engages in a DSGE analysis of the Indian economy and the model includes an informal sector too! You can find that paper here.

There are many valid arguments for not believing the DSGE modeling exercise completely. One of them is the considerable evidence that real decision making does not follow the text book model of rational decision making. Financial crisis also brought forth the network effects in people’s decision making. For a critique based on these lines see my earlier post.

1. Bardhan, Pranab, and Dilip Mookherjee. 2010. “Determinants of Redistributive Politics: An Empirical Analysis of Land Reforms in West Bengal, India.” American Economic Review, 100(4): 1572–1600.

Abstract:

We investigate political determinants of land reform implementation in the Indian state of West Bengal. Using a village panel spanning 1974-1998, we do not find evidence supporting the hypothesis that land reforms were positively and monotonically related to control of local governments by a Left Front coalition vis-à-vis the right-centrist Congress party, combined with lack of commitment to policy platforms. Instead, the evidence is consistent with a quasi-Downsian theory stressing the role of opportunism (reelection concerns) and electoral competition. (JEL D72, O13, O17, Q15)

2.  Donaldson Dave (2010),  Railroads of the Raj: Estimating the Impact of Transportation Infrastructure, NBER Working Paper no. 16487.

Abstract:

How large are the benefits of transportation infrastructure projects, and what explains these benefits? To shed new light on these questions, this paper uses archival data from colonial India to investigate the impact of India’s vast railroad network. Guided by four predictions from a general equilibrium trade model, I find that railroads: (1) decreased trade costs and interregional price gaps; (2) increased interregional and international trade; (3) increased real income levels; and (4), that a sufficient statistic for the effect of railroads on welfare in the model (an effect that is purely due to newly exploited gains from trade) accounts for virtually all of the observed reduced-form impact of railroads on real income in the data. I find no spurious effects from over 40,000 km of lines that were approved but – for four different reasons – were never built.

Railroads of the Raj: Estimating the Impact of Transportation Infrastructure

Use a mirror (883 K)

Dave Donaldson NBER Working Paper No. 16487 Issued in October 2010

Recently, I came across one such interesting exercise by Comin, Easterly and Gong (2010) . These authors ask an interesting question- was wealth of nations determined in 1000 BC? In other words are the inter country differences in development a result of historical (ancient) differences of some sort?

Technological improvement and adoption are one of the important determinants of nation’s growth and development. Hence, these authors ask if the historical differences in technological adoption determine the world distribution of growth levels today. It is certainly an ambitious exercise given that it starts with data from 1000BC and has to control for the massive human migrations that have happened over such long period of time. With all the caveats in place, the conclusion is definitely interesting. It is not the level of technological adoption in 1000BC that determines today’s inter-country differences but the level in 1500 AD.

According to the to the measures used in the paper, China always was a leader in technological adoption since 1000BC to 1500AD. India and Western Europe were lagging behind equally around 1000BC, seemed to have caught up around 0 AD and then Western Europe surpasses all the civilizations in 1500 AD. Currently Western Europe seems to be far ahead of China and India and this somewhat corresponds closely to the differences between these civilizations in 1500 AD than earlier periods. The regressions and robustness analysis confirm this interpretation.

There are variety of limitations one could think about while critiquing such exercise. One is that the historical data is not accurate and is subject to frequent revisions.  More research has been done on the Western Europe’s history than any other place in the world and hence there is an inherent eurocentric bias in all such data analysis and narratives. However, in spite of these limitations the analysis in this paper is pertinent and paves the way for further research in historical determinants of development today. It also widens the set of questions asked about inter-country differences in development to those beyond the differences in geography and institutions . In doing so,  it definitely underscores the importance of history’s importance in current outcomes.