Intra-regional Development Disparities Experiences and Policy Options

Introduction

For some time now, it has been said that the story of India is the story of her States including the disparities within them (Bakshi et al., 2015). Of late, intra-state regional disparities have come to the fore. Many state governments have set up committees to look into intra-regional disparities in their states. Here, we attempt to abstract the core approach that Dr Vijay Kelkar Committee followed in its analysis and proffering its recommendations. Generally, region, as well as disparities, has several connotations. These could be geographically demarcated with administrative jurisdictions at varied levels of government. Thus, regions could be the whole of continents nation-states or erstwhile provinces or could be states and one could move on to sub-state levels. Sometimes, moving away from the standard understanding of regions in the spatial sense alone, we may want to imagine regions based on attributes that render a collective of people particularly vulnerable and call for special attention. Similarly, disparities could mean socio-cultural political or indeed economic (which is of primary importance for us) again, measured severally. On the matter of unit of analysis, after due consideration, we have concluded that on balance, it is best to stick with the district as the unit of the regional analysis. After all, it is the primary construct of administration in India and optimally suited to be a relevant and meaningful unit of the regional analysis. Data are also typically available with some reliability at this level. Below this level, especially in rural India, the data on several variables of economic consequence are simply not available. At a higher level, aggregation is possible.

Since our interest is not purely academic or epistemic, a question like ‘Why do disparities arise?’ is of interest to us only to the extent that on the one hand, it establishes our position that at least beyond a point disparities are not desirable for various reasons, and an answer provides us clues about how one could go about reducing such disparities. We will only state here that disparities arise and are perpetrated over time due to historically induced path dependency, differences in human endowed capital, physical infrastructure, natural endowments, geographical features, and perhaps the rather nebulous, yet largely important for outcomes: social capital.

In studying and working out strategies of development processes related to human systems, it is well worth adopting the twin lenses of liveability and livelihoods in discerning the issues involved. These, to anticipate what comes a little later, provide the basis for the two tracks/pronged approach.

Prologue

We will recommend the adoption of a two-track multi-dimensional approach to tackle the issues here. From the start, we emphasize our argument that resources alone, while important in the outcomes we want to achieve, will not get us there. To prepare the ground, we will step back a bit and briefly deal with the overarching background. This overarching framework is provided by a good governance system. This is not something grandiose but rather is made of brick and mortar stuff and maybe simply be conceptualized as being made up of four basic components.

The governance system deals with incentive induced interactions by and between agents and agencies and comprises four components: (a) policy framework/design (not individual policies by themselves alone) which set the incentives for agents and agencies involved; (b) processes and protocols which could be modified to reduce transactions costs; (c) capacity building (data and skills to analyse and implement) which determine if and how decisions by the agents and agencies via the induced incentives lead to actions which in turn lead to outcomes and (d) independent evaluation office (IEO) which helps to monitor the entire process above and help to tweak and redesign/reform the above components.

The basic mantra is the policy framework creates incentives that prompt action plans that based on capacity lead to actual implementation and further outcomes. So, if one is not satisfied with outcomes, it is well to take a look at the policy design or capacity.

Given that all economic institutions primarily are driven by the objective to reduce transaction costs, one important way to do it is through leveraging ICT. Smart Governance which is in vogue is all of the above with the proviso that it should be inclusive in the sense that it should lead to the creation of an ecosystem where the Government, Academia, Private Sector and the Civil Society agencies are in continuous dialogue and data/information sharing mode in the process of taking any decision.

The policy framework provides a macro-parametric environment but the fleshing out of the capacity remains an important task in the attainment of optimal outcomes. For example, where individuals need to voluntarily join to form a group the principle of imputation which incentivizes coalition formation comes into play. Thus, we need to go a little farther than the matter at hand to create such a microenvironment that will enable the individual agents to develop a stake in coalition formation (the imputation problem in Microeconomics 101). This requires taking a top-down as well as a bottom-up approach. Thus, it requires organizational as well as institutional building to flesh out the action elements by absorbing policy/estimating resources and moving towards meaningful implementation. In the tunnel-like, we must drill from both sides and achieve alignment as the two sides meet creating a clear pathway.

Core

Apart from being analytical, participatory, knowledgeable-based and realistic, it is an approach informed by basic principles. It may be good to begin to flag some of the core beliefs or principles which we believe ought to be satisfied.

Incentives matter: In the matter of policy design, it is important to keep this in mind. This recognition allows for a policy design that has a self-enforcing character and does not require supervisors to oversee by the way opening up the possibility of nepotism and corruption (side payments). This implicitly means that we are arguing for incentive-compatible mechanisms to be intrinsic to all optimal system/design efforts.

Having the above as backdrop and as points of reference, let us dive straight into the matter at hand. We start with the twin lens of livelihoods and liveability again. These give us the basic two tracks underlying our approach. Given the two tracks, we need two things, one, indicators that are easily measurable for which region-level data will be available and two, they are minimalist in number but cover the essential basic requirements of decent civic living as well as provide the basis for productive activities to be encouraged. Every element/component indicator variable doubles up with twin facets. Of course, the specific indicator that proxies it and hence will be measured will be different. Then, a combination of these indicators that are reasonably few but sufficient to capture the underlying dimension will have to be identified. This then forms the necessary elements of the formula which will prescribe the essential regional allocations.

Alternatively, and perhaps more correctly following the Tinbergen principle, we need two different formulae reflecting two objectives of liveability and livelihoods further calling for, minimally, two sets of instruments. These would best be designed and implemented by two different organizations and perhaps with different institutional structures.

In any case, the formulaic allocations are only the beginning: the larger and perchance the more difficult part yet remains. This involves issues of overall and specific vision with a sense of prioritization in a cross-sectional as well as temporal sense. Then, with this as the backdrop, we will need to design appropriate policy with an eye on extant capacity and hence the capacity-building efforts. More importantly with the contemporary sensibilities, we need to evolve pathways for meaningful private sector participation. All of this will require special and specific efforts in the realm of good governance (in particular decentralisation) in a multidimensional sense.

On to the basic strategy now. We strategise in a multi-dimensional two-track mode.

The first track related to liveability has to do with the axiom of equality that every citizen is entitled to a certain amount of benchmarked public goods and services. The list of such goods and services will have to be identified and the quantum-related benchmarks decided. This will lead to a vector of basic goods and services that must minimally be provided by the appropriate level of government. This vector will have to be indexed which becomes a basic development entitlement norm. It is empirically possible to work out the deficit or distance from this norm in any given region and appropriately used for allocating resources. The underlying cost structure of supplying such public goods and services then provides some clues about the requisite resource requirements in total. Given a realistic assessment of the currently available resource envelope allows us to assess the realism of our recommendations as also set priorities for attainment. Two caveats need to be entered. One, although simply stated neither the indexation nor the latter calculation is as simple as we have put it. Two, the first one suffers generically from some arbitrariness, and the second calls for granular level data that are reliable and consistent. We merely recognise this without apology and move on.

Moving to the second track. This is guided by the principle of equity. Now, by definition, the backward regions relatively lack directly productive infrastructure. So, we need to provide/facilitate it through public as well private efforts. Now, generally, infrastructure is an umbrella term that is contingent on the specificities of a region. Thus, a thoughtful empirical study identifying the strengths (comparative advantage) will have to be carried out keeping an eye on path dependencies and the other on current and future possibilities. The actual estimation of infrastructure deficit and the allocative prescriptions will follow as explained in track one mutatis mutandis and need not detain us here. We need to underline here that given the current macroeconomic ethos, the design of incentive-compatible policy design is extremely crucial for attracting private capital. The role of the public sector investment will be largely confined to providing such components that will help crowding-in by the private sector. Infusion of relevant investment will lead to growth acceleration in the lagging regions leading to convergence and rectification of regional imbalance. The equity aspect needs to be reflected in the sense that since one size does not fit all, we need to avoid mimicking and grafting ‘what has worked elsewhere’ blindly. It also implies that given the initial conditions there is a limit to the absorptive capacity of a region in a given time. This latter especially requires that the political leadership in managing optics and credibility come to the fore.

Apart from the obvious geographically determined regional disparities, there are some other significant disparities which arise simply from being a member of the society with a particular identity say a woman, child or a tribal. On the other hand, particularly harsh geographies or endowments thereof could also present severe cases of vulnerability. Such cases (which may include water-stressed regions or hilly tracks) could be of concern while at the issue of tackling regional disparities. These create pockets of vulnerabilities that, while they are crucial to the overall development and social cohesion, may not be amenable to the general treatment outlined above. They call for a customised mission mode response with not inconsiderable understanding and ingenuity.

Divergences in economic prosperity often perpetuate for too long a period and breed a perception of deliberate political neglect, maligning and hindering any political attempt to ameliorate the disparity.

On the other hand, pre-existing distinct political identities emphasise disparity (potential or extant) and resent prospects of any regional integration. Similar chasms due to political legacy or history can as well be portrayed in terms of alleged economic discrimination.

Indian experience in this regard has been sufficiently diverse. These range from region-specific constitutional provisions (e.g., Article 371) to constituting new states consisting of contagious regarding districts. Several states continue to grapple with the question of intra-state regional imbalances (e.g., Saurashtra Kutch within Gujarat, Vidarbha and Marathwada in Maharashtra, Seemandhra in newly constituted Andhra Pradesh).

In 2005, planning commission published ‘Report of Inter-ministry task group on Readdressing Growing regional imbalances’. This report identified 170 backward districts including 55 extremely affected backward districts.

Many of the studies including the inter-ministry task group report have used districts as a unit for measuring backwardness. The choice of the district as a unit of analysis is partly dictated due to the nature of the database ordinarily operative together with administrative viability and partly due to usual sensible statistical considerations of ‘optimal’ stratification. There are certain facets of natural resource endowments in which political-cum-administrative units such as ‘district’ does not make much economic sense (e.g., access to water is more well defined by river-basin) and may need to be separately addressed as far as possible. In some cases, the role played by the third tier of the federal arrangements needs to be dealt with specific conditions related to the case in point (e.g., villages not well connected to urban economic centres as against those which are more cohesively linked with urban economic centres).

A very large number of studies based on available data rely on the extant district unit-based data and usually get confined to measuring extant economic distances through some type of indicators (Dholakia, 1985; Bhattacharya & Sakthivel, 2004; Das & Mishra, 2009). Their preliminary descriptive usefulness notwithstanding such portrayals based on such diverse indicators need to be aggregated and weights used in such aggregation continue to be a statistically unending exercise. Moreover, very few reports have dealt with reshaping long-/medium-term economic strategy for the acceleration of region-specific growth as a panacea for breaking the vicious circle of backwardness.

The state of Maharashtra was formed in the converse of reorganisation of erstwhile based on linguistic homogeneity. The Marathi speaking districts from CP and Berar and Nizam ruled Hyderabad state where they joined Marathi speaking districts of Bombay province. Many of the leaders and political organisations from Vidarbha (Berar) had resented this reorganization. After prolonged debate and negotiation districts of Berar were merged into the new state. The incorporation of these districts was facilitated by the constitutional provision namely 371 ‘Special provision concerning the States of Maharashtra and Gujarat’.

Apart from relative economic under-development, there were some other political factors as well. The cast and community composition of Vidarbha are different from the Marathi speaking districts of Bombay province. This aspect is reflected in the inaugural speech of first chief minister Yashwantrao Chavan. He emphatically said, ‘the new state will be a “Marathi speaking” state and not “Maratha state”’. This is also reflected in the choice of a non-Maratha Vidarbha leader as a chief minister of newly formed Maharashtra (1962–1974).

Let us now turn to the political representation within Maharashtra, followed by noting the peculiar characteristics of Vidarbha as well as the backwardness of Marathwada. This will be followed by a reflection on the two committee reports that were appointed by the Government of Maharashtra to look into the regional balance/backwardness within the State. As in the case of our emphasis on the Kelkar committee in laying down the abstract/theoretical framework for conceptualizing the problem, here too, we shall pay greater attention to the Kelkar committee report which is the latest attempt to have a go at the issue.

Vidarbha as a region has a very distinct history from what is now referred to as the ‘Rest of Maharashtra’ which is by and large western Maharashtra including Mumbai, Thane, etc. Culturally, in terms of community and caste composition is a very distinct region. It consists of eight districts with 62 MLAs (Table 1). There is another region, which is probably the most backward region again consisting of eight districts, which is Marathwada, which has got 46 MLAs (Table 2) and all the rest out of 288 are in fact from what is called the rest of Maharashtra is 180 (Table 3). The two districts Mumbai and Thane elects 60 lawmakers and if Raigad is included then the entire region elects 67 lawmakers (Table 4). Repeatedly Maharashtra politics has witnessed the demand for a separate Vidarbha. It has also witnessed the demand for re-carving out states to avoid the excessive domination both in terms of the social, administrative and political attention, that rest of Maharashtra (that is excluding Vidarbha and Marathwada districts) have got, and therefore, this state of the political representation in the legislative assembly that one should be kept in mind (Table 5). There are many sources and reasons for the regional disparity (Mathur, 1983; Borooah & Dubey, 2007; Bhattacharya & Sakthivel, 2004; Jain et al.,1988). Part of them is the historical path of development or the course of development that occurred, part of them are also due to the differences in the human capital, which the region has, part of them are also predominantly due to the natural endowments that the regions have and physical infrastructure, geographical features and social capital. In all these respects, there are very stark differences between these three regions and there have been at least two committees, they are prominent committees, the first committee that was appointed was chaired by Dr V.M. Dandekar and his committee tried to deal with this issue in a manner which took to measure the development disparity which was intraregional, which he did not take this as a region, but instead, committee measured it in terms of distress and wanted to emphasise the development disparities in terms of physical indicators like for example how many number of schools are there, teachers are there, what is the enrolment or may be the level of irrigation and so on, but for that the unit that they had chosen for predominantly except irrigation was that of district by and large because the nature of data that were available in those times were mostly district based data and having defined that, their primary solution that the ‘Fact Finding Committee’ (Government of Maharashtra, 1983) was trying to in fact suggest was that measure the nature of gaps that exist and in order to reduce these gaps, whatever is the expenditure and in those times, good part of that used to be called as a plan expenditure they must be primarily allocated to these districts (Roy, 2012). One of the major lacunae in the way in which this suggestion and the policy formulations were made was the number of years that would require if one were to catch up even with the then prevailing average it was an inordinately high kind of a period. For example, S.M. Vidwans, Former Director, Directorate of Economics and Statistics, himself a member of ‘Fact-Finding Committee’ later wrote a paper indicating this flaw and saying that probably if one follows then even for the education, say primary education, it might take something like 45–60 years. Therefore, this method did not account for how much time it would take to catch-up even with the average for the districts that were lagging when measured from the state average. Another major problem that Fact-Finding Committee’s recommendations created was that it talked about gaps in physical indicators, but then they naturally tried to multiply it with the financial provisions that would be needed and on that basis, they called the term, which is called a financial backlog. This term stuck and so much so that the entire question of regional disparity is even today by and large being discussed in terms of how much amount of backlog has been cumulated and whether those kinds of funds could be made, transferred to the regions of Vidarbha and Marathwada. While one may be critical of the committee’s approaches, it must be remembered that they were products of their times. The public sector was then prominent in economic matters, and the overall development was lacking not to mention the fact that the macroeconomic ethos was still dominated by socialist fervour. Much of this had changed 25 years later when yet another committee was appointed: ‘High-Level Committee on Balanced Regional Development Issues in Maharashtra’ chaired by Dr Vijay Kelkar. This committee took a fresh view of the issues relevant to the times and made very important deviations from the previous approach that had been taken. First, the committee did not measure the development disparities in terms of districts; but instead, it measured them in terms of regions. Of course, the degree of disparity that existed in terms of certain kinds of indicators and the Kelkar committee took an approach where the equalisation was sought to be achieved, as explained theoretically in the earlier section, in terms of two major two paths in the strategy, one was equalisation in terms of what committee called as the public goods or publicly provided goods, maybe some of them are private goods or merit goods, there should be equalisation, which is achieved across all districts as well of course, therefore, all regions and they measured the development distance primarily in terms of those indicators. Water, education, health, connectivity, power, law, order and security, credit and per capita income (PCI) are the indicators suggested by Kelkar Committee for restoring and sustaining regional balance. (Kelkar Committee Report, Government of Maharashtra, 2013). An important feature of the Kelkar committee report was in their approach, they emphasised how it should be understood, in the sense that something which can be policy-wise delivered and designed to cause equalisation, and at the same time, there must be an economic strategic thinking, which captures and triggers the nature of sectors which would have the so-called regional comparative advantage revealed and materialised as fast and as early as possible. Another important innovation, which the Kelkar committee made for which, the Dandekar committee again had said that the inequalities and disparities exist across all sectors and all districts therefore confining it to the region may not be right, but what Kelkar committee as an innovation suggested and this conference is going to have a separate session on that, the Kelkar committee suggested that apart from these regions, we should also think of something that can be called as imagined or the virtual regions which primarily consist of tribal region. The tribal region in Maharashtra is pretty significant, and it is partly significant in the most advanced part of Maharashtra namely the rest of Maharashtra. For example, in Nashik and Thane districts on the one hand and also there is a significant tribal population in Vidarbha, which is Gadchiroli, Chandrapur, parts of Bhandara and so on. So how to treat, these kinds of virtual regions which have a very special feature where the disparity is even more, as also the incidence of backwardness is even more was a question that needed to be addressed. Another major region/reason, which affects Maharashtra across all the three major regions is water scarcity. The water-stressed districts or the water stress regions in the basins of Maharashtra’s major rivers for example Godavari, Krishna and so on, that is something, which caused a huge amount of economic disparity and this is something, which cannot be measured in terms of district per se. This is because the rivers have their basins, which are spread across many districts and the availability and access to water not only for drinking, which is treated by the Kelkar committee as the publicly provided good having equalisation as rightful access. This means increased use of water both in agriculture as well as in non-agricultural activities even during industrialisation. This is one of the major features of the recognition that it is not confined to agriculture as industrialization grows, the demand for water from an industry sometimes grows much more than it would in agriculture. So how to establish a mechanism of access to water, not necessarily as a public good, but also for economic purposes were the question, which needed to be handled and tackled differently; therefore, the water-stressed regions in Maharashtra had to be treated specially, whether they fell in rest of Maharashtra or Vidarbha or Marathwada. This is something which is a very unique chapter in this report that deals with the question of access to water and the use of water for different purposes, and that is not necessarily adhering or confining itself to the geographic boundaries or geographic definitions of the regions. So, water-stressed regions on the one hand and the tribal regions on the other are the two virtual or the imagined kind of regions that the Kelkar committee has introduced as an important way of looking at different complexities and dimensions of intra-regional disparity. In what follows we will very briefly present the kind of disparity that has existed measured in terms of per capita income. We have re-estimated something which has already been there partly up to 2012, and we can notice that if we measure the development distance between different districts of Maharashtra without bothering about which region they fall.

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Table 1.

Total Legislative Assembly Members in Vidarbha.

Districts	Number of MLA
Buldhana	7
Akola	5
Washim	3
Amravati	8
Yavatmal	7
Amravati division	30
Wardha	4
Nagpur	12
Bhandara	3
Gondia	4
Chandrapur	6
Gadchiroli	3
Nagpur division	32
Total MLA in Vidarbha	62

Source: http://mls.org.in/

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Table 2.

Total Legislative Assembly Members in Marathwada.

Districts	Number of MLA
Aurangabad	9
Jalna	5
Parbhani	4
Hingoli	3
Beed	6
Nanded	9
Osmanabad	4
Latur	6
Total MLA in Marathwada	46

Source: http://mls.org.in/

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Table 3.

Rest of Maharashtra Legislative Assembly Members.

Rest of Maharashtra Total MLA	Konkan Division	Nashik Division	Pune Division	Total
Total	75	47	58	180

Source: http://mls.org.in/

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Table 4.

Mumbai Region Legislative Assembly Members.

Mumbai	Thane	Total	Raigad	Total
36	24	60	7	67

Source: http://mls.org.in/

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Table 5.

Rest of Maharashtra Division-wise Legislative Assembly Members.

Konkan Division	Number of MLA	Nashik Division	Number of MLA	Pune Division	Number of MLA
Mumbai	36	Nashik	15	Pune	21
Thane	24	Dhule	5	Satara	8
Raigad	7	Nandurbar	4	Sangli	8
Ratnagiri	5	Jalgaon	11	Solapur	11
Sindhudurg	3	Ahmednagar	12	Kolhapur	10
Total MLA Konkan division	75	Total MLA Nashik division	47	Total MLA Pune division	58

Source: http://mls.org.in/

So, what we did was instead of measuring it from the state average, we grouped the districts in terms of what can be called something like discriminant function or rather cluster analysis, and three kinds of clusters can be found, which are presented here and one notices that even within the decade of 2011 to 2019–2020 (Table 6), the ranking or the grouping of the districts in terms of those which are highest per capita income, the second highest per capita income and the third category where the per capita income on the average is low, remains more or less same. The intra-cluster disparity also has increased significantly (Tables 7, 8 and 9). So, even among the most advanced districts which primarily consist of the four major districts where per capita income happens to be highest and that happens to be the first cluster consists of Thane, Raigad, Pune and Nagpur and this is something that you are seeing as how their per capita incomes have moved between the first 5 years and the later 5 years of this decade. And this is something, which is a common feature that intra-cluster disparity has gone up almost in all the sectors. Of course, following standard practice, we have excluded Mumbai from the analysis as including it creates statistical distortion as is well known.

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Table 6.

Disparity Clusters.

Case Number	2011–2012 to 2014–2015			Case Number	2015–2016 to 2019–2020
	District	Cluster	Distance		District	Cluster	Distance
1	Thane	1	17,849.52	1	Thane	1	22,374.61	5.91
2	Raigad	1	16,960.27	2	Raigad	1	20,086.58	6.38
3	Ratnagiri	2	1,304.864	3	Ratnagiri	2	1,329.636	6.07
4	Sindhudurg	2	8,257.49	4	Sindhudurg	2	10,305.02	5.68
5	Nashik	2	5,751.095	5	Nashik	2	5,941.973	5.72
6	Dhule	3	11,159.08	6	Dhule	3	15,312.5	5.32
7	Nandurbar	3	13,866.78	7	Nandurbar	3	17,352.04	5.00
8	Jalgaon	3	8,735.247	8	Jalgaon	3	10,608	4.94
9	Ahmednagar	2	5,866.824	9	Ahmednagar	2	8,943.745	5.74
10	Pune	1	9,572.601	10	Pune	1	10,962.93	5.91
11	Satara	2	3,403.673	11	Satara	2	3,773.631	5.92
12	Sangli	2	3,747.304	12	Sangli	2	1,853.366	5.36
13	Solapur	2	2,115.975	13	Solapur	2	1,839.415	5.71
14	Kolhapur	2	17,336.13	14	Kolhapur	2	21,169.03	5.55
15	Aurangabad	2	4,809.795	15	Aurangabad	2	5,567.552	5.88
16	Jalna	3	4,994.506	16	Jalna	3	591.708	3.81
17	Parbhani	3	4,685.862	17	Parbhani	3	2,118.196	4.16
18	Hingoli	3	9,073.363	18	Hingoli	3	15,465.42	4.41
19	Beed	3	3,486.3	19	Beed	3	4,724.342	4.67
20	Nanded	3	529.422	20	Nanded	3	2,491.436	5.69
21	Osmanabad	3	4,067.468	21	Osmanabad	3	2,165.585	3.36
22	Latur	3	7,787.88	22	Latur	3	10,022.15	5.18
23	Buldhana	3	13,191.26	23	Buldhana	3	16,132.69	5.02
24	Akola	3	10,684.05	24	Akola	3	17,192.13	5.72
25	Washim	3	11,743.2	25	Washim	3	14,158.32	4.93
26	Amravati	3	6,134.494	26	Amravati	3	14,233.93	6.26
27	Yavatmal	3	6,141.631	27	Yavatmal	3	3,182.969	5.60
28	Wardha	2	12,219.82	28	Wardha	2	10,974.82	6.53
29	Nagpur	1	10,461.85	29	Nagpur	1	13,250.96	6.03
30	Bhandara	3	5,827.555	30	Bhandara	3	8,514.178	5.15
31	Gondia	3	3,292.672	31	Gondia	3	6,103.961	5.28
32	Chandrapur	2	12,212.75	32	Chandrapur	2	13,178.69	6.31
33	Gadchiroli	3	9,336.846	33	Gadchiroli	3	14,006.82	4.03

Source: The authors.

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Table 7.

Cluster Analysis Cluster 1.

Cluster 1
	2011–2012 to 2014–2015						2015–2016 to 2019–2020
	2011–2012 to 2014–2015	Mean	Distance from Mean	Standard Deviation	CV		2015–2016 to 2019–2020	Mean	Distance from Mean	Standard Deviation	CV
Thane	154558.28	136709	17849.52	16404.68	12	Thane	203486.76	181112	22374.61	19998.89	11.04
Raigad	119748.48		−16960.27			Raigad	161025.57		−20086.58
Pune	146281.35		9572.6			Pune	192075.08		10962.93
Nagpur	126246.90		−10461.85			Nagpur	167861.19		−13250.96

Source: The authors.

Note: Bold values indicate that distance is less than mean.

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Table 8.

Cluster Analysis Cluster 2.

Cluster 2
	2011–2012 to 2014–2015						2015–2016 to 2019–2020
	2011–2012 to 2014–2015	Mean	Distance from Mean	Standard Deviation	CV		2015–2016 to 2019–2020	Mean	Distance from Mean	Standard Deviation	CV
Ratnagiri	95145.70	93840.8	1304.86	8886.16	9.47	Ratnagiri	124196.06	122866	1329.64	10087.45	8.21
Sindhudurg	102098.33		8257.49			Sindhudurg	133171.45		10305.02
Nashik	99591.93		5751.1			Nashik	128808.40		5941.97
Ahmednagar	87974.01		−5866.82			Ahmednagar	113922.68		−8943.75
Satara	90437.16		−3403.67			Satara	119092.79		−3773.63
Sangli	97588.14		3747.3			Sangli	124719.79		1853.37
Solapur	95956.81		2115.98			Solapur	124705.84		1839.42
Kolhapur	111176.97		17336.13			Kolhapur	144035.45		21169.02
Aurangabad	89031.04		−4809.8			Aurangabad	117298.87		−5567.55
Wardha	81621.02		−12219.82			Wardha	111891.60		−10974.82
Chandrapur	81628.09		−12212.75			Chandrapur	109687.74		−13178.69

Source: The authors.

Note: Bold values indicate that distance is less than mean.

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Table 9.

Cluster Analysis Cluster 3.

Cluster 3
	2011–2012 to 2014–2015						2015–2016 to 2019–2020
	2011–2012 to 2014–2015	Mean	Distance from Mean	Standard Deviation	CV		2015–2016 to 2019–2020	Mean	Distance from Mean	Standard Deviation	CV
Dhule	76988.38	65829.3	11159.08	8559.02	13	Dhule	97868.71	82556.2	15312.5	11633.47	14.09
Nandurbar	51962.52		−13866.78			Nandurbar	65204.18		−17352.04
Jalgaon	74564.55		8735.25			Jalgaon	93164.21		10608
Jalna	70823.81		4994.51			Jalna	83147.92		591.71
Parbhani	70515.17		4685.86			Parbhani	84674.41		2118.2
Hingoli	56755.94		−9073.36			Hingoli	67090.80		−15465.42
Beed	62343.00		−3486.3			Beed	77831.87		−4724.34
Nanded	65299.88		−529.42			Nanded	85047.65		2491.44
Osmanabad	69896.77		4067.47			Osmanabad	80390.63		−2165.58
Latur	73617.18		7787.88			Latur	92578.37		10022.15
Buldhana	52638.04		−13191.26			Buldhana	66423.52		−16132.69
Akola	76513.35		10684.05			Akola	99748.35		17192.13
Washim	54086.10		−11743.2			Washim	68397.90		−14158.32
Amravati	71963.80		6134.49			Amravati	96790.14		14233.93
Yavatmal	59687.67		−6141.63			Yavatmal	79373.25		−3182.97
Bhandara	71656.86		5827.55			Bhandara	91070.39		8514.18
Gondia	69121.98		3292.67			Gondia	88660.18		6103.96
Gadchiroli	56492.46		−9336.85			Gadchiroli	68549.40		−14006.82

Source: The authors.

Note: Bold values indicate that distance is less than mean.

The most curious thing is there is no movement across the cluster, which means something, which has been a part of three has moved to two or something which is two has moved to three, no such movement has been noticed. So, the nature of disparity in terms of their ranking and their grouping based on per capita income measured of course in constant prices have more or less remained the same (Table 10). So after the Kelkar committee report when was submitted in 2013, there have been some policy initiatives. One of the major and significant recommendations of the Kelkar committee was like infrastructure provision in terms of roads, in terms of access to electricity, needs to be equalised. These are the two important indicators of five major indicators that were chosen to measure the development distance across the regions. The question is has there been any significant movement in that direction? Again, the answer seems to be not so, except probably for one project. Kelkar committee report emphasises one physical infrastructure namely road connectivity. While the connectivity of different has been discussed, road connectivity happens to be very significant because it connects markets, changes the migration patterns, it makes the movement of both goods as well as people and services across the regions a lot easier and a lot more flexible and that is likely to be one of the major triggers for ushering in development in the region. In particular, Maharashtra faces a peculiar problem in that its east-west connectivity happens to be much lower. In terms of three regions, the rest of Maharashtra, Marathwada and Vidarbha, if one takes the one-rupee worth of income in the rest of Maharashtra, Vidarbha gets 25% less, its income would be roughly 75 paise, whereas Marathwada is the poorest region, comprising eight districts, and it gets something like 66 paise. So, this reflects the disparity in the level of development as measured in terms of the access, in terms of facilitation, in terms of focus or the attention of the government policies. By all counts, by almost every indicator that one can imagine and choose, the Marathwada region remains the most backward economically and also politically. Strangely, the Marathwada region finds itself much closer to the rest of Maharashtra from a political perspective, in that the demand for a separate state predominantly originates from Vidarbha. So, it is the erstwhile legacy of political identity being different for the Vidarbha continues even when in terms of the degree of inequality faced by Vidarbha is relatively less than that of Marathwada. So, if one asks where the pockets of the most underdevelopment, by and large, exist in Maharashtra if one measures it on a regional basis, it happens to be predominantly in Marathwada and the picture has not changed except for one major scheme that was launched in 2014–2015 onwards, and that is something which is called Samruddhi Mahamarg, which connects the two points, one at the Nagpur to Mumbai and it covers a considerable amount of districts from Khandesh, Vidarbha and some parts of Marathwada. Except for this scheme, again if you find out the number of development schemes of the infrastructural type that were granted in the same regime of, say BJP regime of 2014–2019, where the chief minister himself happened to be from the Vidarbha the number is negligible. Ironically, one finds that a good part of the infrastructure projects that were sanctioned, implemented and are getting implemented happen to be located in fact in Mumbai. This is something which resonates with what Dandekar had sarcastically said, ‘whosever happens to be whether it is from Karad, that is Western Maharashtra, or from Varhad, that is from Vidarbha what gets developed in Mumbai’. It is this kind of political bias which has been the major complaint within this whole debate about the intraregional parity or the disparity in Maharashtra. It is once again reasserted and revalidated in form of the last 5 years’ experience as well. Indeed, again in the last 2 years, while we were affected by corona, there is no significant movement that one can see which would address this issue of regional development except probably for continuing the schemes, that were launched in the earlier regime. Thus, the situation even after two major committee reports (although neither of these committee reports was officially adopted, that is, accepted in terms of its policy recommendations) nothing appears to have changed. Most recommendations were never taken seriously or were never attempted to be implemented, except maybe after a dozen years, the development boards were floated. The experience of the development board as a panacea or remedy for addressing this issue as far as Maharashtra is concerned is hardly encouraging. The Vidarbha or Marathwada leaders opine that development boards are not reliable and credible kind of a mechanism or a solution to address the nature of disparity and discrimination that they are suffering from. So, this in brief is the experience of Maharashtra.

OPEN IN VIEWER

Table 10.

District Growth Rate.

District	Growth Rate for 2011–2012 to 2019–2020	Growth Rate for 2011–2012 to 2014–2015	Growth Rate for 2016–2017 to 2018–2019
Thane	5.91	4.03	2.74
Raigad	6.38	4.93	2.75
Ratnagiri	6.07	6.84	1.61
Sindhudurg	5.68	2.93	2.32
Nashik	5.72	4.52	2.77
Dhule	5.32	4.85	2.35
Nandurbar	5.00	1.57	3.07
Jalgaon	4.94	3.71	1.59
Ahmednagar	5.74	3.98	2.89
Pune	5.91	4.02	3.09
Satara	5.92	3.17	3.45
Sangli	5.36	3.08	2.62
Solapur	5.71	4.11	3.22
Kolhapur	5.55	3.42	2.60
Aurangabad	5.88	3.22	2.65
Jalna	3.81	−0.37	2.29
Parbhani	4.16	2.39	0.45
Hingoli	4.41	5.14	3.56
Beed	4.67	0.99	1.52
Nanded	5.69	1.56	2.91
Osmanabad	3.36	−2.09	3.98
Latur	5.18	1.25	2.77
Buldhana	5.02	1.03	1.92
Akola	5.72	2.84	2.29
Washim	4.93	−1.97	1.98
Amravati	6.26	4.91	0.78
Yavatmal	5.60	1.99	0.54
Wardha	6.53	3.10	2.22
Nagpur	6.03	4.01	2.35
Bhandara	5.15	3.39	1.82
Gondia	5.28	3.71	1.80
Chandrapur	6.31	3.49	2.95
Gadchiroli	4.03	1.04	3.13

Source: The authors.

Epilogue

What is attempted here is to create a template of a strategic framework for approaching the issues of regional disparities as they arise in varied forms and magnitude. To that extent, it falls short of a neat step-by-step prescription as expected in a tool kit in a cut and dried form. It only prescribes the things to consider in determining the allocative formula along the two tracks and hints at several commensurate measures that are needed to accompany them. It never suggests that addressing regional disparities is easily done. We began by stressing that the matter is far more than mere concern related to deficient resources. The fleshing out will require huge effort toward efficient public financial management so that allocations get translated into actual expenditures in relevant areas. Furthermore, the other elephant in the room has to do with the huge effort that will be required towards capacity building. This includes the creation of both a reliable database and, more importantly, the human capital endowment at an appropriate level to understand the final outputs and outcomes aimed at as well as to undertake the action plan comprising relevant steps. And then, there is the political economy filter. Given that the path may be messy, we have vested a great deal in the values of participatory democracy of a particular form. The political masters will and must have the final say in decisions (of course they also take the risks involved). In creating formulae for allocative rules, enough room must be left for political play. This is something that is to be importantly kept in mind in our expert formulations and prescriptions. After all, political players as policymakers not unlike nature are guided by the tenet: Natura non facit saltus!