Fiscal Pressure of Migration and Horizontal ... - Wiley Online Library

doi: 10.1111/imig.12536

Fiscal Pressure of Migration and Horizontal Fiscal Inequality: Evidence from Indian Experience Pinaki Chakraborty* and Shatakshi Garg*,**

ABSTRACT This article examines the patterns and trends in inter-State migration across the Indian States and observes that along with the demographic factors, migration is also affected by the fiscal profile of States. Controlling for the economic prosperity of States as reflected in their per capita Net State Domestic Product and the nature of fiscal policy stance, econometric estimation using the gravity model suggests that level of vertical federal transfers and its horizontal distribution is an important determinant of the pattern of inter State migration. To correct for the extant horizontal fiscal inequality across the Indian States, the article suggests a relatively more progressive transfer system and a developmental fiscal policy stance at the State level to reduce the pressure of out-migration to prosperous regions of the country.

INTRODUCTION In federal countries, migration is a common feature. Migration of people from low-income regions to the more prosperous regions of the country is a common feature of Indian federation too. This pattern of out-migration has resulted in political opposition in many States, demanding that migrants go back so that the resident population can avail themselves of the benefits of “local public goods” and economic prosperity of these regions.1 On the economic side, high-income regions are also wary of the fiscal condition of their States arising on account of the fiscal pressure of migration.2 In a federal system, the objective of fiscal transfers is to address the issue of fiscal inequality arising due to the differences in fiscal capacity. How does one find a solution to the problem of fiscal pressure arising out of migration in the high-income regions of the country is an important policy question, especially in a country like India with large-scale fiscal inequality among the States. This difference in fiscal inequality has also resulted in inequality in the provision of “local public goods” across regions, accentuating migration. This raises a further question, whether the fiscal behaviour of provincial governments in both high- and low-income regions of the country induces migration. These issues are addressed in this article, taking data on migration across provinces (inter-State migration), fiscal transfers, provincial government expenditure and own revenues of provinces for the years 1971, 1981, 1991 and 2001. At the outset, it is important to mention the motivation behind choosing the time period of our study, from 1971 to 2001. In India (post-independence), the Census is conducted every 10 years * National Institute of Public Finance and Policy, New Delhi ** Fifteenth Finance Commission of India, New Delhi © 2018 UNU-WIDER This is an open access article distributed under the terms of the Creative Commons Attribution IGO License https://creativecommons.org/ licenses/by/3.0/igo/legalcode which permits unrestricted use, distribution, and reproduction in any medium, provided that the original work is properly cited. In any reproduction of this article there should not be any suggestion that UNU or the article endorse any specific organization or products. The use of the UNU logo is not permitted. This notice should be preserved along with the article’s URL. Published by John Wiley & Sons Ltd. ISSN 0020-7985

2

Chakraborty and Garg

by the Registrar General and Census Commissioner of India under 1948 Census of India Act. After Indian Independence in 1947, the decennial Census of India has been conducted seven times – 1951, 1961, 1971, 1981, 1991, 2001 and 2011. Mapping migration data to the State of origin and destination was not feasible for all the census years due to reorganisation/bifurcation of States at different times. It is to be noted that the 29 States which form the Indian Union today are the result of a series of State creations/reorganizations that has happened over the years. The Constitution of India that was adopted in 1951 classified Indian States into four categories – Part A, Part B, Part C and Part D States. Ever since, strong demands to reorganize the States on linguistic basis led to the formation of several Committees and Commissions to look into the matter. Integrating linguistic and cultural homogeneity issues along with financial, economic and administrative considerations, as well as the motivation to preserve and strengthen the unity and security of the country, led to the creation/reorganization of States (abolishing the Part A – Part D States by the State Reorganization Act, 1956). Between 1951 and 1960, massive alterations to State boundaries were made, as a result of which there were then 14 States. Even though State reorganization continued after 1960, there were no one-stroke developments in a decade as had happened between 1950 and 1960. For this reason we have excluded inter-State migration data from the Census of 1951 and 1961. The time period of analysis has not been extended to 2011 because data on inter-State migration has not been released yet. Section 2 of the article examines in detail the revenue sharing principle and its likely implications for transfers to regions and thereby migration. Section 3 presents a brief review of literature on internal migration and some key findings on internal migration in India. Section 4 analyses the pattern of inter-State migration for the period from 1971 to 2001. Section 5 examines economic and demographic profiles of States during this period to understand the nature and pattern of migration. Section 6 analyses the fiscal profiles of States during this period. Section 7 presents the results of the empirical exercise on whether fiscal behaviour of States induces migration. Section 8 concludes the study.

INDIAN FISCAL TRANSFER SYSTEM AND INTERNAL MIGRATION: EXPLORING THE LINK AND POLICY GAPS Population in revenue sharing without factoring in migration: The policy constraint India is a federal country with three levels of government, namely the Union, State, and Local Government. Article 1 of the Constitution India adopted in 1950 described India as a “Union of States”, as a result of which India had a two-tier level of government until 1993. Post-1993, the federal structure of the country was further strengthened as a result of the 73rd and 74th Amendment Acts, and local bodies received constitutional recognition as the third tier of the government. It is important to note that although the Constitution provides for divided governmental functions and powers among the three levels of government, namely the Union, State, and Local Government (as laid out in Schedule VII, Schedule XI and Schedule XII of the Constitution), imbalances often arise between functional responsibilities and financial resources at different layers of the government often as part of the constitutional design (Bagchi, 2003a; Rao and Singh, 2004, 2006). The vertical and horizontal asymmetries arising in a federal polity as a result of differences in functional responsibilities and financial resources among the subnational governments have been studied extensively in the global context (Akerlof, 1969; Boadway, 1992; Oates, 1999; Weingast, 2009) as well in particular context of India (Rao and Chelliah, 1996; Bagchi, 2003b; Tillin, 2006; Singh, 2007). Economic asymmetry among the States in the Indian federation is evident from the wide disparities across the Indian States – to illustrate: in terms of area, the largest State, Rajasthan, is © 2018 UNU-WIDER

Migration and Federalism

3

almost 90 times bigger than the smallest State, Goa; the State with the highest NSDP in the year 2001, Maharashtra, exceeded Mizoram’s NSDP by roughly 175 times; per capita NSDP of Goa (the highest in the country) was a massive nine times larger than the lowest per capita NSDP of Bihar. Needless to say, these staggering differences across States influence inter-State migration decisions of individuals and we will discuss this issue in detail in Section 6. The task of addressing of addressing fiscal inequalities across States is the Finance Commission’s3 responsibility and the (erstwhile) Planning Commission4 was responsible for financing development plan to address regional inequality. The Planning Commission has been replaced by the NITI Aayog. While determining inter-se share of federal taxes to provinces in India, the basic aim has been to correct differentials in revenue-raising capacity and cost disability factors across provinces (Chakraborty, 2003; Rao and Singh, 2003; Kumar and Managi, 2009). To achieve these goals, different Finance Commissions have followed principles of equity and efficiency. The criteria used by the Finance Commission for revenue sharing can be categorised as: (a) factors reflecting needs such as population and income; (b) cost disability indicators such as area and infrastructure backwardness, and, (c) fiscal efficiency indicators such as tax effort and fiscal discipline. To date, 14 Finance Commissions have been constituted that have each given their recommendations to address both, horizontal and vertical fiscal imbalances. Over these years, recommendations made by the Finance Commission, in general, and the efficacy of transfers in filling the vertical and horizontal gap, in particular, have been discussed extensively (Bagchi and Chakraborty, 2004; Sinha, 2004; Chakraborty, 2010; Rangarajan and Srivastava, 2011). Implications of the use of dated population for resource distribution There was a convention of using the latest Census figures to distribute the shareable proceeds of taxes to the States until the mid-1970s. However, since the early 1980s, it was mandated that the 1971 population be used for distributing federal tax proceeds to the States. It was the consequence of the 42nd Constitutional Amendment Act, which froze the seats in National Parliament and State legislative assemblies on the basis of the 1971 population until 2001. The implications of freezing the seats in National Parliament in influencing electoral federalism in the country were discussed extensively (McMillan, 2000, 2001; Sivaramakrishnan, 2000). This amendment was further extended by the 84th Constitutional Amendment Act until 2026. The basic argument given in its favour was that it would boost the family planning programme (FPP) for population control by providing an incentive to the States which were serious about implementing FPP. This was argued to provide a direct incentive to the lagging States in implementation of FPP effectively. However, the use of 1971- dated population data, in this case by design, has ignored migration as a factor reflecting the fiscal needs of a State in subsequent federal distribution of taxes and grants spanning over more than four decades. Over the time period of our study (1971–2001), we observe that the demographic composition of States has changed significantly. While the prosperous regions of the country have achieved replacement-level fertility, poorer States like Bihar, Uttar Pradesh, Madhya Pradesh, and Rajasthan have still very high TFR (total fertility rate). The dependency ratio5 has also been relatively higher for the poorer States. It is also observed that in recent years, due to fast growing urbanization, people are attracted to bigger cities in search of either a job or education. The larger influx of in-migrants to a place poses several challenges to public service delivery, resulting in additional administrative and other fiscal costs of financing public services. Since migration is an important factor affecting the population of the State apart from natural factors viz. fertility and mortality, and is affected by the ever-evolving demographic composition across the Indian States, the use of dated population data in the Indian federal system has been unable to take these factors into consideration in the distribution of resources. It may not be an exaggeration to argue that use of dated population data denied resources to the poorer regions, which in turn induced out-migration. In this study we have analysed the effect of the freezing of © 2018 UNU-WIDER

4


1971 population on the devolution of resources. It has been found that the use of dated population figures has resulted in the distortion in the allocation of the resources to the States, and penalized the States for having more than average growth rate of population and also for being poor. The Fourteenth Finance Commission (FFC) has, for the first time since the 42nd constitutional amendment, mandated to take the 1971 population as the base and also subsequent demographic changes as factors for determination of devolution of taxes and duties and grants-in-aid across States (Government of India, 2014).

INTERNAL MIGRATION A brief review of literature The UNDP Human Development Report 2009 estimated that internal migrants were almost four times as many as those who have moved internationally. The Report shed new light on the common misconception that migration is heavily concentrated from developing to developed countries. The findings in the Report suggested that migration from one developing economy to another was much more common and that most migrants moved within their own country rather than going abroad (UNDP, 2009). Inter-state migration has been studied extensively in literature, with much focus on understanding the determinants of migration and the influence of migration as an equilibrating mechanism in a changing economy. Todaro (1980: 361) noted that one of the earlier studies on internal migration argued that “rapid internal migration was thought to be a desirable process by which surplus rural labour was withdrawn from traditional agriculture to provide cheap manpower to fuel a growing modern industrial complex (Lewis, 1954; Fei and Ranis, 1961)”. The basic proposition of the theoretical Todaro (1969) model and the Harris and Todaro (1970) model that migration proceeds primarily in response to differences in “expected” urban and rural real incomes has been used extensively in literature to understand inter-state migration. Thus, income differentials across regions have been commonly used as determinants to understand inter-state migration. Coupled with this, there have been a lot of studies on understanding migration and the fiscal state of the provinces. Buchanan (1950) suggested that differences in fiscal capacity across regions provide an incentive for migration because if states are not identical in fiscal capacity, the people in the low-capacity (low-income) states must be subjected to greater fiscal pressure (higher taxation and/or lower value of public services) than people in high-capacity states. Bird and Smart (2002) argued that the rationale of transfers from the Centre to the states should be to enable even the smallest and poorest governments to provide all basic local services to their residents so as to check for out-migration from the poorer regions. Shaw (1986) in a comparative study pre-1971 and post-1971 using data on Canada’s 17 Census Metropolitan Areas found that the influence of traditional market variables (wage, employment and changes in business cycle) diminished over time, and that fiscal variables like unemployed insurance, federal government equalization and related transfers to provinces, and natural resource revenues, have had unintended consequences in influencing migration. Barro and Sala-i-Martin (1992), in their comparative study on regional growth and migration in the USA and Japan, found that while reaction of migration to regional income differentials in both countries was significantly positive, the reaction was slow and exogenous changes in migration seemed to be unimportant in explaining the process of interregional convergence. Internal migration in India is also driven by regional disparities across the Indian States. Kurian (2000), Srivastava and Sasikumar (2003), Joe et al. (2009), Srivastava (2011) and Das and Saha (2013) have used various socio-economic indicators to establish that, in general, migrants move from less-developed regions of the country to relatively more-developed regions of the country. Over time, the role of urbanization in influencing the spatial pattern of internal migration in India has been studied extensively in literature along with the ensuing policy challenges of correcting © 2018 UNU-WIDER


5

regional imbalances in development (Yadava and Yadava, 1995; Mukherji, 2001; Bhagat and Mohanty, 2009; Srivastava, 2011). One of the few studies on migration and fiscal variables in India has been by Cashin and Sahay (1996). In their study on 20 Indian States during the period 1961– 1991, they found evidence of absolute regional convergence among the Indian States, and that the poorer States received more transfers from the Central government than their richer counterparts. They also found migration to have only little effect on convergence of per capita income across States as significant social, economic and cultural barriers resulted in net migration from poor to rich States, responding only weakly to cross-State income differentials. However, there is no study in the Indian context on the impact of transfers on inter-State migration. Since population is a key determinant of individual State’s share in resource devolved by the Finance Commission, the use of dated 1971 population data by the Finance Commission might have impacted migration across States. We then empirically test for the influence of intergovernmental transfers in determining migration across the 28 Indian States for the time period 1971 to 2001. Internal migration in India: A brief review Before we begin to analyse inter-State migration in India and its determinants, we discuss a few features of internal migration. In India, as in most developing countries, there is vast incidence of temporary or seasonal migration in search of better employment opportunities. Bhagat (2010) suggests that with the exception of Kerala, “seasonal and temporary migration seem to be highest in the States where a high level of intra- and inter-State socio-economic inequalities is observed”. Other micro studies also suggest similar results of people migrating temporarily from poorer to prosperous regions of the country for economic gains. However, correctly estimating the extent of temporary or seasonal migration in India is an arduous task. Keshri and Bhagat (2011) point out that “. . .Although the census covers the entire population, it fails to provide information on shortterm and temporary migration (Bhagat and Mohanty, 2009; Kundu, 2009; Skeldon, 2002).” Thus, most studies rely on sample studies conducted by the National Sample Survey. They also point out that there is no consensus among researchers and statisticians on the definition of temporary migration. Nevertheless, seasonal migration is an important livelihood strategy adopted by the poor individuals to enhance their economic status. While the limitation of data (Census does not provide data on seasonal migration) constrains us on undertaking this issue in depth, we examine the role of distress in influencing inter-State migration decisions of an individual. Since temporary migration is also perceived as a transitional step before a permanent change of residence (Pham and Hill, 2008), we try to empirically estimate if it is a determinant of migration across States in India. Another interesting aspect of internal migration in India is the role played by State borders in determining individuals’ decisions to migrate across States. Kone et al. (2017) find that despite there being no legal restrictions on movement across State borders in India, “average migration between neighbouring districts in the same state is at least 50 per cent larger than neighbouring districts on different sides of a state border”. Using empirical evidence, they argue that this is due to “non-portability across state borders of social welfare benefits, such as access to subsidized food or issuance of PDS ration cards”. This probably explains the low volume of inter-State migrants in India, as we shall discuss shortly. Using gravity model, we also empirically estimate if State borders are a deterrent to individuals’ decisions to migrate across States in Section 7 of the article. Now we examine the composition of internal migration in India and the stated reasons for migration. Data on internal migration is reported in the Census using two criteria – “Place of Birth” and “Place of Last Residence”.6 If the place of birth/last residence is different from the place of enumeration, the respondent is reported as a migrant. Internal migration consists of intra-State and inter-State migration – intra-State migration is studied by analysing data reported under the heading “Within the State of enumeration but outside the place of enumeration”; data on inter-State migration is studied from the heading “States in India beyond the State of enumeration”. Internal © 2018 UNU-WIDER

6


migration in India is mostly on account of intra-State migration, which is roughly four-fifth of the total migration within the country. However, the focus of this study is on inter-State migration and not intra-State migration, for reasons discussed below. The Census of 1981 for the first time included questions on the reasons for migration7 (2001). It is to be noted that intra-State migration in the country is mostly female migration – in the four decades till 2001, over 60 per cent of migrants within the State boundaries have been females. A closer examination of data on stated reasons for migration reveals that more than half of females migrated for marriage – almost 70 per cent of females migrated in 1981 for marriage and even in 2001, 50.21 per cent females stated marriage to be the reason for migration within a State of the country. Thus, it is evident that the higher proportions of females migrating within the State for marriage purposes (which have social and cultural reasons) increase the intra-State migration figures. If these migration figures are adjusted for marriage, the volume of intra-State migrants would be lower. On the other hand, male migration across the States of the country for employment, business and education related reasons has been on a constant rise – from 46.39 per cent in 1981 to 54.20 per cent in 2001.8 The share of inter-State female migrants migrating because of economic reasons, albeit small, has also risen from 1981 to 2001 (Sekhar, 1982; Padamanabha, 1988; Vijayanunni, 1998; Registrar General and Census Commissioner, 2001). Hence we focus on inter-State migration which has been rising over the years, mostly for economic reasons, and examine States’ fiscal behaviour in impacting pattern of inter-State migration. (See Figure 1.) The study of inter-State migration is thus of significance given the relative increase in the share of inter-State migrants and the huge magnitude of inter-State migrants in the country. Inter-State migrants have almost doubled from 1971 to 2001 – there were 10.5 million inter-State migrants in 1971 and the 2001 Census reported 19.8 million inter-State migrants. Though this amounted to an increase in the share of inter-State migrants from 11.96 per cent to 13.84 per cent in the corresponding period, the rate of growth of inter-State migrants far exceeded the growth rate of intra-State and total internal migrants in the country. What is most significant is the change in the inter-State migration pattern during the last two decades, where people migrated from rural regions to urban areas, mostly motivated by economic reasons (Srivastava, 1998; Mahapatro, 2012). As a result, this increase in inter-state migration is significant as a share of urban population of destination States. For instance, net in-migrants in Maharashtra, one of the most prosperous States of India, have more than doubled between 1991 and 2001 – from 2.5 million to 5.7 million respectively. As a proportion of Maharashtra’s urban population this amounts to an increase from 8.2 per cent in 1991 to 13.9 per cent in 2001.

INTER-STATE MIGRATION IN INDIA: TRENDS AND PATTERNS Net migration to a State is computed by subtracting out-migration from a State from in-migration to a State. In our study, we have used Census data on migration based on a “Place of birth” criterion for the time periods 1971, 1981, 1991 and 2001. From the Census data for the years 1971, 1981, 1991 and 2001, we observe that three States, namely Maharashtra, West Bengal and Madhya Pradesh, have the most net in-migrants, although the relative shares of these States in total net inmigrants has changed over the years (Refer Figure A1 in Appendix). A close examination of the data related to net in-migration reveals that net in-migration has reduced sharply over the decades in both Madhya Pradesh and West Bengal. On the other hand, Gujarat and Punjab that initially had more out-migrants than in-migrants in 1971, gradually had more migrants coming in those States.9 We now examine the pattern of out-migration and in-migration, and the reasons behind such interState migration patterns. It is interesting to note that five Indian States namely, Uttar Pradesh, Bihar, Rajasthan, Kerala and Andhra Pradesh constitute more than four-fifth of total out-migrants in the country of the States where out-migrants exceed in-migrants. The share of out-migrants from these © 2018 UNU-WIDER

7


FIGURE 1 STATED REASONS FOR MIGRATION (A) REASONS FOR MIGRATION - TOTAL POPULATION (FIGURES IN %), (B) REASON FOR INTER-STATE MIGRATION – EMPLOYMENT, EDUCATION AND BUSINESS (FIGURES IN %), (C) REASON FOR INTRA-STATE MIGRATION - MARRIAGE (FIGURES IN %)

(A)

45.00 40.00 35.00 30.00 25.00 20.00 15.00 10.00 5.00 0.00

(B)

Reasons for Migration - Total Population 60.00

Reason for Inter-State Migration Employment, Education and Business

50.00 40.00 30.00 20.00 10.00 Economic 1981

Family moved

Marriage 1991

0.00

Others

Inter-State Male Migrants

Inter-State Total Migrants

2001 1981

1991

2001

(C)

80.00

Reasons for Intra-State Migration Marriage

70.00 60.00 50.00 40.00 30.00 20.00 10.00 0.00 Intra-State Female Migrants 1981

Intra-State Total Migrants 1991

2001

Source: (Basic Data), Census of India (various years)

5 States has been 84.65 per cent, 87.96 per cent, 88.97 per cent and 88.95 per cent for the years 1971, 1981, 1991 and 2001 respectively. While Uttar Pradesh continues to have the highest share at around 40 per cent of the total, the share of out-migrants from Kerala and Andhra Pradesh respectively has declined from 13.31 per cent and 6.72 per cent in 1971 to 6.52 per cent and 5 per cent in 2001 (see Figure 2). It is to be noted that Uttar Pradesh, Bihar and Rajasthan are the poorest regions of the country and remain at the bottom of the ladder, as evident from their per capita income. On the other hand, in-migration is concentrated in six Indian States, namely Gujarat, Haryana, Punjab, Madhya Pradesh, Maharashtra and West Bengal. Among the States where in-migrants exceed out-migrants, the share of in-migrants in these States has remained at around 90 per cent from 1971 to 2001. Migration across States, however, has changed significantly. While Maharashtra continues to have the highest share of in-migrants in the country, the share of West Bengal and Madhya Pradesh among the States where in-migrants exceed out-migrants has dropped significantly. Their respective shares of in-migrants have slipped from 27.03 per cent and 16.41 per cent in 1971 to 8.50 per cent and 2.31 per cent in 2001. A contrasting increase in the share of in-migrants has happened in the States of Haryana, Gujarat and Punjab (see Figure 3). In fact, Gujarat in 1981 Census and © 2018 UNU-WIDER

8


FIGURE 2 SHARE OF STATES WHERE OUT-MIGRATION EXCEEDS IN-MIGRATION (FIGURES IN %)

Share of top states 100.00 80.00 60.00 40.00 20.00 0.00 1971 Uttar Pradesh

1981 Bihar

Kerala

1991 Rajasthan

Andhra Pradesh

2001 Others

Source: Computed from Census of India (various years)

Punjab in 1991 Census for the first time had positive net in-migrants that is. in-migrants exceeded out-migrants in these States. It is to be noted that both Maharashtra and Gujarat are the prosperous regions of the country and these States are the high income per capita States.

INTER-STATE MIGRATION AND ECONOMIC AND DEMOGRAPHIC PROFILE OF STATES IN INDIA Having observed the broad pattern of inter-State migration since 1971, it is important to examine the economic and demographic profile of these States in order to explore whether migration is affected by economic performance and demographic composition of the States. We consider four variables namely, Per Capita State Domestic Product (NSDP pc) reflecting economic prosperity, total fertility rate (TFR),10 Dependency Ratio (DR)11 and Urbanization. From Figure 4 we observe that while Punjab, Haryana, Gujarat and Maharashtra are prosperous States, Bihar, Madhya Pradesh, Uttar Pradesh and Rajasthan have lower per capita NSDP. This clearly shows that migration within India is from the poorer regions to the richer regions of the country. We now observe TFR and dependency ratio. From Figure 5 it is clear that while TFR has come down for all the States from 1971 to 2001, the States having a higher share of out-migrants are the ones whose TFR is much higher than the replacement level. While Kerala, Andhra Pradesh, Maharashtra and Gujarat have attained the replacement level of 2.1, the high TFR in Uttar Pradesh, Rajasthan, Madhya Pradesh and Bihar continue to pull up the all-India average figure. Higher fertility (as seen from TFR) combined with a higher dependency ratio can further exacerbate the situation as the pressure on the working population to meet the requirements of the dependent population can induce outward migration from the State in absence of inadequate economic opportunities in the home State. It is evident from Figure 6 that dependency ratio continues to be high for the poorer States (which are also the States with a higher share of out-migrants and higher TFR). The dependency ratio has been more than 85 per cent for Bihar, Rajasthan and Uttar © 2018 UNU-WIDER

9


FIGURE 3 SHARE OF STATES WHERE IN-MIGRATION EXCEEDS OUT-MIGRATION (FIGURES IN %)

Share of top states 100.00 80.00 60.00 40.00 20.00 0.00 1971 Maharashtra

1981 West Bengal

Madhya Pradesh

1991 Haryana

Gujarat

2001 Punjab

Others

Source: Computed from Census of India (various years)

Pradesh, even in 2011 when the average for all India came down to 73.4 per cent. On the other hand, for most of the prosperous States the ratio came down to around 65 per cent in 2011 from as high as around 90 per cent in 1971. We now examine the share of urban population in the total population of the States. Growing urbanization is a pull factor for migration as people are attracted to bigger cities in search of either better education and/or employment opportunities. Since 1971, urbanization has been increasing in India but it has been spatially unequal. It is evident that the States that have a higher share of outmigrants have lower urban population (see Figure 7). It is also interesting to note that out-migration from the relatively prosperous States of Kerala and Andhra Pradesh could be on account of the low level of urbanization in these States. Additionally, a State like Haryana that has high TFR as well as high dependency ratio attracts more in-migrants from the country probably on account of the fast increasing pace of urbanization in the State over the years. From the above analysis, we observe that a combination of push and pull factors on account of the varying (and evolving) demographic and economic profile of the States are influencing the pattern of in-migration and out-migration in Indian States. But use of the 1971 population in determining the share of divisible pool of resources to States means that the resource sharing formula used by successive Finance Commissions has failed to account for the later dynamism in demographic profile. As mentioned earlier, however, the FFC (constituted in 2014 to give recommendations on devolution of resources to States for the 5-year period 2015-16 to 2019-20) while deciding on the devolution of funds to States recognised the need to consider the demographic changes across States since 1971, the obvious ones being the change in the composition of population and also migration,. As a result, the Commission assigned a 10 per cent weight to the 2011 population that would capture the demographic changes since 1971, both in terms of migration and age structure. Before we empirically estimate whether funds transfers from the Finance Commission to State governments determine the pattern of inter-State migration in the country, we examine States’ fiscal profile to understand how the fiscal situation of a State influences individuals’ migration decisions.

© 2018 UNU-WIDER

10


FIGURE 4 STATE-WISE NSDP PER CAPITA (FIGURES IN RS LAKHS)

NSDP per capita

40000 30000 20000 10000 0

1971-72

1981-1982

1991-1992

2001-2002

Source: (Basic Data), EPWRF (various years) FIGURE 5 STATE-WISE TOTAL FERTILITY RATES

Total Fertility Ratio 6 5 4 3 2 1 0

1991

2001


INTER-STATE MIGRATION AND FISCAL PROFILE OF STATES IN INDIA The horizontal imbalances present in the Indian federation, as evident from States’ varying performances on various social and economic indicators, are a cause of concern. In this context, it is important to examine States’ fiscal positions, as they are a major determinant of States’ ability to provide various public services which determine their performance on socio-economic development indicators. For this purpose, we examine the fiscal profile of both origin and destination States of © 2018 UNU-WIDER

11


FIGURE 6 STATE-WISE DEPENDENCY RATIO

400

Dependency Ratio

300 200 100 0

1971

1981

1991

2001


migration. The origin States are the ones where out-migration exceeds in-migration, and destination States are the ones where in-migrants exceed out-migrants. We consider the following State finance variables: Transfers from the Finance Commission, Own Revenue of States and Government Spending of States. Transfers from the Finance Commission constitute of Share in Union Taxes and Grants from the Union government (also called intergovernmental transfers); Own Revenue comprises of Own Tax Revenue and Own Non-Tax Revenue, Government Spending constitutes of Capital and Revenue Expenditure (it could also be disaggregated as Development and Non-Development Expenditure). We observe that the States with a higher share of out-migrants have a relatively lower share of Own Revenue and higher share of intergovernmental transfers (IGT) (devolved by the Finance Commission) in their total Revenue Receipts. This implies that States that have a higher share of out-migrants have depended more on transfers from the Finance Commission to meet their expenditure requirements while their own revenue from tax and non-tax collection have been relatively lower than the States with net in-migrants (See Figures 8 and 9). Government Expenditure as a percentage of GSDP has increased for all the States from 1971 to 2001 but we observe that, over time, there is no marked difference between the government spending across the out-migrant and in-migrant States (See Figure 10). While government expenditure (as a percentage of NSDP) does not vary across the States, it is interesting to note the difference in its financing pattern. As was mentioned earlier, the poorer States, which have a relatively higher share of out-migrants, have received more transfers. So it could be argued that while the financing of government expenditure has been from the share of central transfers for the poorer States (which have received a relatively higher share of transfers), the richer States which have more in-migrants have higher own revenues to finance the growing government expenditure. In other words, States with higher fiscal autonomy12 also are the destination States for in-migrants. On the other hand, States with a lower share of own revenues have deficient public service delivery that has incentivised more out-migration from these States. It is evident that fiscal inequalities in Indian federation are significant and have influenced the pattern of inter-State migration in the country, as suggested by Buchanan (1950). The role of © 2018 UNU-WIDER

12


FIGURE 7 STATE-WISE URBANIZATION TO TOTAL POPULATION RATIO: 1971 TO 2001 (FIGURES IN %)

Urbanization - 1971

Urbanization - 1981

Maharashtra

Maharashtra

Gujrat

Gujrat

West Bengal

Punjab

Punjab

West Bengal

All India

All India

Andhra Pradesh

Andhra Pradesh

Haryana

Haryana

Rajasthan

Rajasthan

Madhya Pradesh

Madhya Pradesh

Kerala

Kerala

Uttar Pradesh

Uttar Pradesh

Bihar

Bihar 0

10

20

30

40

0

Urbanization - 1991

10

20

30

40

Urbanization - 2001

Maharashtra

Maharashtra

Gujrat

Gujrat

Punjab

Punjab

West Bengal

Haryana

Andhra Pradesh

All India

Kerala

West Bengal

All India

Andhra Pradesh

Haryana

Madhya Pradesh

Madhya Pradesh

Kerala

Rajasthan

Rajasthan

Uttar Pradesh

Uttar Pradesh

Bihar

Bihar 0

10

20

30

40

50

0

10

20

30

40

50


federal transfers in determining these fiscal inequalities is critical, more so since these transfers have historically used the dated 1971 population as a criterion for determining States’ share in the divisible pool of resources – ignoring the changing demographic changes that have happened in the four decades post 1971. In this context, we now empirically estimate how States’ fiscal profiles, especially their share in federal transfers, influence inter-State migration in India.

EMPIRICAL ESTIMATION – PANEL DATA REGRESSION Based on the explanatory data analysis, it is evident that there is a link between fiscal profile and pattern of migration across States in India. In this section, we examine econometrically how the fiscal behaviour of provinces induced migration, using the gravity model. © 2018 UNU-WIDER

13


FIGURE 8 STATE-WISE OWN REVENUE TO TOTAL REVENUE RECEIPTS RATIO: 1971 TO 2001 (FIGURES IN %)

OR/RR - 1971

OR/RR - 1981

Haryana Punjab Gujarat Maharashtra Madhya Pradesh West Bengal Kerala Andhra Pradesh Rajasthan Uttar Pradesh Bihar

Punjab Haryana Maharashtra Gujarat Kerala Andhra Pradesh West Bengal Madhya Pradesh Rajasthan Uttar Pradesh Bihar

0.00

20.00 40.00 60.00 80.00

0.00 20.00 40.00 60.00 80.00100.00

OR/RR - 1991

OR/RR - 2001 Haryana Punjab Maharashtra Gujarat Kerala Andhra Pradesh Rajasthan Madhya Pradesh West Bengal Uttar Pradesh Bihar

Gujarat Haryana Maharashtra Punjab Kerala Andhra Pradesh West Bengal Madhya… Rajasthan Uttar Pradesh Bihar 0.00

50.00

100.00

0.00 20.00 40.00 60.00 80.00100.00

Source: (Basic Data), EPWRF (various years)

The traditional gravity model of migration, based on analogy with Newton’s Law of Gravitation, specifies that a stock of migrants from origin i to destination j can be explained by economic forces at the origin and destination, and the economic forces either aiding or resisting the movement of immigrants from origin to destination. While population is usually taken as a proxy of the economic force at origin and destination, distance is considered to be the cost of migration. In particular, migration stocks or flows between two countries are supposed to increase with their size and decay with the distance between the two countries (Ramos Lobo and Suri~ nach Caralt, 2013). While the use of traditional gravity model for migration is traced back to the work of Ravenstein in the 19th century, over time researchers have refined the model by incorporating the theoretical foundations of gravity to accurately estimate and interpret the spatial relations described by gravity (Anderson, 1979). As a result, the gravity equation has been long recognized for its consistent empirical success in explaining many different types of flows, such as migration, commuting, tourism and commodity shipping (Bergstrand, 1985). Hence, we use a gravity model to estimate the determinants of inter-State migration in India.

© 2018 UNU-WIDER

14


FIGURE 9 STATE-WISE INTERGOVERNMENTAL TRANSFERS TO TOTAL REVENUE RECEIPTS RATIO: 1971 TO 2001 (FIGURES IN %)

IGT/RR - 1971

IGT/RR - 1981

Bihar Uttar Pradesh Rajasthan Andhra Pradesh Kerala West Bengal Madhya Pradesh Maharashtra Gujarat Punjab Haryana

Bihar Uttar Pradesh Rajasthan Madhya Pradesh West Bengal Andhra Pradesh Kerala Gujarat Maharashtra Punjab Haryana

0.00 20.00 40.00 60.00 80.00

0.00 20.00 40.00 60.00 80.00

IGT/RR - 1991

IGT/RR - 2001

Bihar Rajasthan Madhya Pradesh Uttar Pradesh Haryana Andhra Pradesh Maharashtra West Bengal Kerala Punjab Gujarat 0.00

Bihar Uttar Pradesh West Bengal Madhya Pradesh Rajasthan Andhra Pradesh Kerala Gujarat Maharashtra Punjab Haryana 20.00

40.00

60.00

0.00 20.00 40.00 60.00 80.00


Most gravity models of migration have the following model specification: logðMijt Þ ¼ b1 : logðPopit Þ þ b2 : logðPopjt Þ þ b3 : logðDistij Þ þ b4 :Xij þ uijt

ð1Þ

where, log(Mijt) denotes the logarithm of the immigrants from country i (origin) in country j (destination) at time t. log(Popit) and log (Popjt) denote respectively, the logarithm of the population in the origin (i) and destination (j) countries at time t. log(Distij) is the logarithm of geographical distance between capital cities of countries i and j. Xij represents other control variables (including dummies) that influence migration decisions of individuals – for instance, contiguity, common official language, etc., while uijt denotes a random error term. Gravity models of immigration often also use the relative size of GDP per capita of the destination and origin at time t as another determinant of the model (Lewer and Van den Berg, 2008). The expected signs of the coefficients are b1 > 0, b2 < 0, b3 > 0 and a positive sign for the relative differences in GDP per capita, suggesting that better economic opportunities positively affect migration. © 2018 UNU-WIDER

15


FIGURE 10 STATE-WISE GOVERNMENT EXPENDITURE TO NSDP RATIO: 1971 AND 2001 (FIGURES IN %)

GovEx/NSDP - 1971

GovEx/NSDP - 2001

25.00

Bihar

Gujarat

Rajasthan

Madhya Pradesh

Punjab

Uttar Pradesh

Andhra Pradesh

Rajasthan

Kerala

Maharashtra

Uttar Pradesh

Madhya Pradesh

Bihar

Haryana

Punjab

Andhra Pradesh

Gujarat

West Bengal

0.00

Kerala

5.00

Maharashtra

10.00

Haryana

15.00

West Bengal

30.00 25.00 20.00 15.00 10.00 5.00 0.00

20.00


Given that central idea of the article is to explore whether States’ fiscal behaviour induces interState migration in the country, we estimate the following three models, their specification being similar to Equation (1): Model 1: log(migijt) = b1.log(nsdp_pcit) + b2.log(nsdp_pcjt) + b3.log(distij) + b4.log(igtit) + b5.log (igtjt) + uijt Model 2: log(migijt) = b1.log(nsdp_pcit) + b2.log(nsdp_pcjt) + b3.log(distij) + b4.log(igtit) + b5.log (igtjt)+ b6.log(Borderij) + b7.log(Powerit) + b8.Distressit + uijt Model 3: log(migijt) = b1.log(nsdp_pcit) + b2.log(nsdp_pcjt) + b3.log(distij) + b4.log(devexit) + b5.log(devexjt) + b6.Borderij + b7.log(Powerit) + b8.Distressit + uijt where, migijt : Migrants from origin i to destination j at time t; nsdp_pci(j)t : NSDP per capita of i(j) at time t; igti(j)t : Transfers from the Finance Commission as a percentage of NSDP of i(j) at time t; distij : Distance between capital cities of i and j13 ; devexi(j)t : Development Expenditure14 as a percentage of NSDP of i(j) at time t; borderij : Dummy that takes value 1 if i and j share a common boundary, 0 otherwise; powerjt : Per capita consumption of power (in kilowatt hour) in origin i at time t; distressit : Dummy that takes value 1 if actual rainfall was less than normal rainfall in origin i at time t. Since Maharashtra has historically received the highest share of migrants in the country, we have considered Maharashtra as the destination State (j) and the other 27 Indian States as the origin States (i). The gravity model we use will thus determine the role of fiscal forces at origin and destination States and determine the flow of migrants to Maharashtra from the rest of the States. The gravity model is estimated using census data points for migration for 27 Indian States and for the time periods 1971, 1981, 1991 and 2001 in a panel data framework.15 A priori, we expect negative sign for nsdp_pcit (and devexit) and positive sign for nsdp_pcjt (and devexjt) to indicate that economic prosperity at the destination (j) acts as a pull factor for individuals in origin States (i) (where lower nsdpc_pc acts as a push factor for the individuals). A negative sign for igtit would imply that a progressive transfer mechanism could bring down the rate of out-migration from those States. Since longer distance between origin and destination entails higher economic cost, distij is expected to have a negative sign. We consider three controls in Model 2 and 3 namely, borderij, powerit and distressit. A priori, a positive sign is expected for borderij as contiguity aids in higher migration. © 2018 UNU-WIDER

16


The first control variable powerit is used to capture the standard of living in origin States and a negative sign would convey that lower per capita consumption in origin States are a push factor for residents of those States to migrate. The second control variable, distressit, helps identify if climatic distress induced temporary migration is a determinant of migration from the State of origin. The results for the three models are presented in Table 1 below. In Model 1, as expected, the positive sign of nsdp_pcjt and negative sign of nsdp_pcit corroborate the theoretical finding that Maharashtra’s higher per capita NSDP has attracted migrants from the less prosperous regions of the country. The negative and significant coefficients of igtit imply that for the origin States, an increase in funds devolved by the Finance Commission would significantly reduce the influx of out-migration. The higher magnitude of igtit in comparison to igtjt also suggests that the impact of additional funds devolved by the Finance Commission is larger at the point of origin than at the destination in determining the volume of migrants between these States. Distance, as expected, is negatively correlated to the dependent variable. Model 2 reports similar results for the key fiscal variables – per capita NSDP and transfers, and for distance between the origin and destination States. Borderij has a negative sign – a plausible explanation could be the non-portability of certain State specific schemes and programmes, as discussed in Section III (ii) – but is insignificant. While lower per capita power consumption at origin act as a push factor for residents of those States, it is not a significant variable. On the other hand, distress at the origin is associated with higher influx of in-migrants at the destination.16 Model 3 is a variant of Model 2, where the key fiscal variables along with nsdp_pc is devex. It is to be noted that igt was not included in Model 3 because of high correlation between Finance Commission transfers and government (and development) expenditure. In fact, it is interesting to note that the coefficient of devex in Model 3 implicitly captures the impact of Finance Commission transfers to the State governments, in the sense that transfers to the States are used to finance government TABLE 1 REGRESSION RESULTS

nsdp_pcit nsdp_pcjt igtit igtjt distij

Model 1

Model 2

Model 3

1.697*** (0.610) +2.134 *** (0.605) 0.957 *** (0.192) +0.550 *** (0.138) 3.322 *** (0.521)

1.220*** (0.515) +1.795*** (0.531) 0.769*** (0.188) +0.656*** (0.159) 4.925*** (1.085)

1.777*** (0.474) +2.093*** (0.446)

devexit devexjt 1.810 (1.341) 0.277 (0.183) 0.185* (0.108)

borderij powerit distressit

4.402*** (1.055) 1.498*** (0.353) +1.643*** (0.361) 1.213 (1.206) 0.086 (0.188) 0.140 (0.102)

Note: All variables except border and distress are in log form; Robust standard errors are reported in parentheses; All models are Random Effects Model – obtained after running Hausman Test. ***p < 0.01; **p < 0.05; *p < 0.1. Source: Authors’ computation © 2018 UNU-WIDER


17

expenditure in general and development expenditure in particular. While the positive sign of the coefficient of devexjt suggests a higher share of development expenditure in the destination State attracts more migrants from the origin States, the larger coefficient (in absolute terms) of devexj(i)t than igtj(i)t suggests that if spent as a development expenditure, additional funds devolved to the origin States (destination State) are more effective in controlling out-migration (attracting more migrants). We also ran variants of these models where own revenues (public debt) of origin and destination States were considered as the key fiscal variables, and obtained similar results that the higher share of own revenues (lower share of public debt) in destination State’s NSDP acted as a pull factor (push factor) for migrants. To sum up, States’ fiscal behaviour have played a key role in determining the pattern of migration across States.17 Moreover, the study of bilateral fiscal variables using the gravity model helps identify that a relatively more progressive transfer system that devolves more funds will have a stronger impact at the point of origin (than destination) in controlling out-migration from these States.

CONCLUSION To conclude, the significant relation between share of transfers in both origin and destination States’ NSDP and the migration between these States corroborates the main argument of our article: that the fiscal transfer system has a key role to play in deciding the pattern of migration in the Indian federal system. Despite the fact that the net out-migrant States identified in our study received a higher share of central transfers, the regression returned a negative coefficient for transfers received by origin States. This suggests that, ceteris paribus, a relatively more progressive transfer system has the potential of reducing pressure of out-migration from these States. However, it is also to be noted that while higher transfers are needed to stop the flow of out-migrants from relatively poorer States, these States also need to boost their own revenues in order to increase their fiscal space on development expenditure, which has a negative impact on out-migration. A major change has happened with the award of the FFC. The use of 2011 population data for the horizontal devolution of resources by the FFC has helped in assessing a State’s need based on current population. However, given the level of fiscal inequality in Indian federal system, the degree of progressivity would depend on the overall resource envelope of the Union government, irrespective of the level of need of individual States.

ACKNOWLEDGEMENTS This article is part of a larger research project on Intergovernmental Fiscal Relations in India. This work was carried out with the aid of a grant from the International Development Research Centre, Ottawa, Canada, under the Think Tank Initiative. I would like to thank Rachel Gisselquist and Finn Tarp for their comments on an earlier version of this article, and the anonymous reviewers for their valuable comments and suggestions on the manuscript.

NOTES 1. Given the huge influx of migrants from Bihar and Uttar Pradesh to Maharashtra, some political outfits in the state of Maharashtra have been very vocal about the pressure of migration on local economy. Online at: http://www.rediff.com/news/2008/mar/05thackeray.htm (accessed 11 March 2018). 2. Maharashtra Chief Minister stated that unchecked influx into the city has put considerable strain on Mumbai’s infrastructure. “Public amenities such as water, suburban rail network have to bear the burden (of influx).” The opposition expressed concerns over migration and its adverse impact on the fiscal condition © 2018 UNU-WIDER

18


of the state. Available at: https://timesofindia.indiatimes.com/india/Unchecked-influx-straining-Mumbai-De shmukh/articleshow/2850604.cms (laccessed on 11 March 2018). 3. The Finance Commission is a constitutional body that is constituted by the President of India every 5 years under Article 280 of the Indian Constitution. It is entrusted with the responsibility of distributing net proceeds of taxes between Union and State governments, and determining factors governing Grants-in Aid to the States and the magnitude of the same. 4. The Planning Commission was established in the year 1950 when the need for a formal mode of planning was felt. The Commission, an arm of the Union Government of India (thus not deriving its power from the Constitution), had the main function of formulating India’s 5 Year Plans. 5. Dependency Ratio is the ratio of the number of children (0–14 years old) and older persons (65 years or over) to the working-age population (15–64 years old). Source: United Nations (2002). 6. Place of Last Residence criterion was first introduced in the 1971 Census. The Census from 1881 to 1971 reported data on migration using the Place of Birth criterion alone. 7. 1981 census recorded reasons for migration under five broad heads: Employment, Education, Family moved, Education and Others. The Census of 1991 included two additional reasons – Business and Natural Calamities like droughts, floods, etc. The 2001 Census, along with the five reasons in the 1981 Census, had Business and Moved after Birth as the additional reasons. For analysis, we have combined Business, Education and Employment as “Economic” and, Natural Calamity and Moved after birth with “Others”. 8. Male migration within a State due to marriage is however reported to be very low – less than 4 per cent; total intra-State migration due to economic reasons is reported to be less than 10 per cent in the 2001 Census. 9. We have excluded migration “to and from” Union Territories in our study. The figures reported in the entire article pertain to inter-State migration alone. 10. TFR refers to total number of children born or likely to be born to a woman in her lifetime if she were subject to the prevailing rate of age-specific fertility in the population. TFR of about 2.1 children per woman is called Replacement-level fertility. (World Health Organization). 11. DR relates the number of children (0–14 years old) and older persons (65 years or over) to the workingage population (15-64 years old). (United Nations). 12. According to Bl€ochliger and King (2006), fiscal autonomy of sub-central governments is multi-faceted and must be assessed using several indicators, including the share of tax revenue allocated to sub-central governments, the discretion over those taxes, the share of transfers allocated to sub-central governments and the percentage of earmarked transfers. We have also used a few of these indicators to assess fiscal autonomy of the states. 13. Distance calculations are based on the great circle distance between points, and do not account for differences in elevation. 14. Development Expenditure is broadly defined to include all items of expenditure that are designed directly to promote economic development and social welfare. Source: RBI, https://rbi.org.in/scripts/PublicationsView.aspx?id=9492 (accessed on 11 March 2018). 15. It is to be noted that state-reorganization has happened over the years. Sikkim was the 22nd Indian state to be formed in 1975, followed by the formation of three new states namely Arunachal Pradesh, Mizoram and Goa in 1987. Three states namely, Uttarakhand, Jharkhand and Chhattisgarh were formed in the year 2000. Thus, data for these states is available only for the Census year subsequent to their formation year. Also, in-migration data is not available for Jammu and Kashmir for the year 1991, while data for both inmigration and out-migration is not available for Assam for the year 1981. 16. Lewer (2008) notes: “Redding and Venables (2004) and Rose and van Wincoop (2001) show that gravity model estimates are likely to be biased by standard error clustering when some variables in the model apply to only one of the two countries in each observation. Feenstra (2004) shows that adding fixed effects to the model eliminates this bias.” While we have included the two controls in the model which are variables of the origin States alone, we perform the Hausman Test that gives consistent support for Random Effects Model for all three model specifications of our paper. 17. In an earlier version of this article, we used unilateral fiscal variables to determine their impact on outmigration from the States. We got similar results that better fiscal health – evident from a higher share of own revenues and higher development expenditure in their NSDP – can put a check on out-migration.

© 2018 UNU-WIDER


19

REFERENCES Akerlof, G.A. 1969 “Centre-State Fiscal Relations in India”, Indian Economic Review, 4(2): 99–121. Anderson, J.E. 1979 “A Theoretical Foundation for the Gravity Equation”, The American Economic Review, 69(1): 106– 116. Bagchi, A. 2003a “Rethinking Federalism: Changing Power Relations between the Center and the States”, Publius: The Journal of Federalism, 33(4): 21–42. 2003b Fifty Years of Fiscal Federalism in India: An Appraisal. National Institute of Public Finance and Policy, New Delhi, India. Bagchi, A. and P. Chakraborty 2004 “Towards A Rational System of Centre-State Revenue Transfers”, Economic and Political Weekly, 39(26): 2737–2747. Barro, R.T. and X. Sala-i-Martin 1992 “Regional Growth and Migration: A Japan-United States Comparison”, Journal of the Japanese and International Economies, 6(4): 312–346. Bergstrand, J.H. 1985 “The Gravity Equation in International Trade: Some Microeconomic Foundations and Empirical Evidence”, The Review of Economics and Statistics, 67(3): 474–481. Bhagat, R.B. 2010 “Internal Migration in India: Are the underprivileged migrating more?”, Asia-Pacific Population Journal, 25(1): 27–45. Bhagat, R.B. and S. Mohanty 2009 “Emerging Pattern of Urbanization and the Contribution of Migration in Urban Growth in India”, Asian Population Studies, 5(1): 5–20. Bird, R.M. and M. Smart 2002 “Intergovernmental Fiscal Transfers: International Lessons for Developing Countries”, World Development, 30(6): 899–912. Bl€ochliger, H. and D. King 2006 “Fiscal Autonomy of Sub-Central Governments”, OECD Economic Studies, 2(43): 155–188. Boadway, R.W. 1992 The Constitutional Division of Powers: An Economic Perspective. Canada Communication Group, Ottawa, Canada. Buchanan, J.M. 1950 “Federalism and Fiscal Equity”, The American Economic Review, 40(4): 583–599. Cashin, P. and R. Sahay 1996 “Internal Migration, Center-State Grants, and Economic Growth in the States of India”, Staff Papers, 43(1): 123–171. Chakraborty, P. 2003 “Unequal Fiscal Capacities across Indian States: How Corrective is the Fiscal Transfer Mechanism”, Mimeo. National Institute of Public Finance and Policy, New Delhi, India. 2010 “Deficit Fundamentalism vs Fiscal Federalism: Implications of 13th Finance Commission”s Recommendations”, Economic and Political Weekly, 48(48): 56–63. Das, K.C., and S. Saha 2013 “Inter-State Migration and Regional Disparities in India”. Online at www.iussp.org/sites/default/file s/event_call_for_papers/Inter-state%20migration_IUSSP13.pdf (accessed 15 September 2017). Fei, J.C.H. and G. Ranis 1961 “A Theory of Economic Development”, The American Economic Review, 51: 533–565. Government of India 2014 Report of the Fourteenth Finance Commission. Government of India Press, New Delhi, India.

© 2018 UNU-WIDER

20


Harris, J.R. and M.P. Todaro 1970 “Migration, Unemployment and Development: A Two-Sector Analysis”, The American Economic Review, 60(1): 126–142. Joe, W., P. Samaiyar, and U.S. Mishra 2009 “Migration and Urban Poverty in India: Some Preliminary Observations”. Working Paper 414. Trivandrum, India: Centre for Development Studies. Keshri, K., and R.B. Bhagat 2011 “Temporary and Seasonal Migration in India”, Genus, 66(3): 25–45. Kone, Z.L., M. Y Liu, A. Mattoo, et al. 2017 Internal Borders and Migration in India. The World Bank. Online at documents.worldbank.org (accessed 21 November 2018) Kundu, A. 2009 Urbanisation and migration: An analysis of trends, patterns and policies in Asia. United Nations Development Programme Human Development Reports, Research Paper 2009/16, June 2009, P. 23. Kumar, S. and S. Managi 2009 “Compensation for Environmental Services and Intergovernmental Fiscal Transfers: The Case of India”, Ecological Economics, 68(12): 3052–3059. Kurian, N.J. 2000 “Widening Regional Disparities in India: Some Indicators”, Economic and Political Weekly, 35(7): 538–550. Lewer, J.J. and H. Van den Berg 2008 “A Gravity Model of Immigration”, Economics Letters, 99(1): 164–167. Lewis, W.A. 1954 “Economic development with unlimited supplies of labour”, The Manchester School, 22(2): 139– 191. Mahapatro, S.R. 2012 “The Changing Pattern of Internal Migration in India”. European Population Conference. McMillan, A. 2000 “Delimitation, Democracy, and End of Constitutional Freeze”, Economic and Political Weekly, 35 (15): 1271–1276. 2001 “Constitution 91st Amendment Bill: A Constitutional Fraud?”, Economic and Political Weekly, 36 (14/15): 1171–1174. Mukherji, S. 2001 Low Quality Migration in India: The Phenomena of Distressed Migration and Acute Urban Decay, Paper presented at the 24th IUSSP Conference, Salvador, Brazil. Online at http://archive.iussp.org/ Brazil2001/s80/S80_04_Mukherji.pdf (accessed 21 November 2017) Oates, W.E. 1999 “An Essay on Fiscal Federalism”, Journal of Economic Literature, 37(3): 1120–1149. Padamanabha, P. 1988 Census of India-1981 Series-1-India (Migration Tables). Controller of Publications, Government of India, Delhi, India. Pham, B.N. and P.S. Hill 2008 “The Role of Temporary Migration in Rural Household Economic Strategy in a Transitional Period for the Economy of Vietnam”, Asian Population Studies, 4(1): 57–75. Ramos Lobo, R., and J. Suri~ nach Caralt 2013 A Gravity Model of Migration between ENC and EU. AQR–Working Papers, 2013, AQR13/09. Rangarajan, C. and D.K. Srivastava 2011 Federalism and Fiscal Transfers in India. Oxford University Press, India. Rao, M.G. and R.J. Chelliah 1996 Fiscal Federalism in India. Indian Council of Social Science Research, New Delhi, India. Rao, M.G., and N. Singh 2003 The Political Economy of Center-State Fiscal Transfers in India, Working Paper 107. Stanford University, Stanford, CA.


2004

21

Asymmetric Federalism in India, Working Paper 2004/08. UC Santa Cruz International Economics, Santa Cruz, CA. 2006 “The Political Economy of India”s Fiscal Federal System and Its Reform”, Publius: The Journal of Federalism, 37(1): 26–44. Registrar General and Census Commissioner 2001 Census of India-2001 Series-1-India (Migration Tables). [CD-ROM]. Sekhar, A.C. 1982 Census of India-1971 Series-1-India (Migration Tables). Controller of Publications, Government of India, U.T. Chandigarh, India. Shaw, R.P. 1986 “Fiscal versus Traditional Market Variables in Canadian Migration”. Journal of Political Economy, 94(3, Part 1): 648–666. Singh, N. 2007 Fiscal Federalism and Decentralization in India. MPRA Paper 1447. Munich Personal RePEc Archive Sinha, A. 2004 “The Changing Political Economy of Federalism in India: A Historical Institutionalist Approach”, India Review, 3(1): 25–63. Sivaramakrishnan, K.C. 2000 “North-South Divide and Delimitation Blues”, Economic and Political Weekly, 35(35/36): 3093– 3097. Skeldon, R. 2002 “Migration and poverty”, Asia-Pacific Population Journal, 17(4): 67–82. Srivastava, R. 1998 “Migration and the Labour Market in India”, Indian Journal of Labour Economics, 41(4): 583– 616. 2011 “Internal Migration in India: An Overview of its Features, Trends and Policy Challenges”, Workshop Compendium Volume II: Workshop Papers, National Workshop on Internal Migration and Human Development in India. UNESCO, New Delhi, India: 1–47. Srivastava, R., and S.K. Sasikumar 2003 An Overview of Migration in India, Its Impacts and Key Issues. Paper presented at the Regional Conference on Migration, Development and Pro-Poor Policy Choices in Asia, Dhaka, Bangladesh. Online at www.eldis.org/vfile/upload/1/document/0903/Dhaka_CP_2.pdf (accessed 22 November 2017). Tillin, L. 2006 “United in diversity? Asymmetry in Indian Federalism”,Publius: The Journal of Federalism, 37(1): 45–67. Todaro, M.P. 1969 “A Model of Labor Migration and Urban Unemployment in Less Developed Countries”, The American Economic Review, 59(1): 138–148. Todaro, M. 1980 “Internal Migration in Developing Countries: A Survey”, in S.H. Preston and R.A. Easterlin (Eds.), Population and Economic Change in Developing Countries. University of Chicago Press, Chicago, IL. UNDP (United Nations Development Programme) 2009 Human Development Report 2009 Overcoming Barriers: Human mobility and development. Palgrave Macmillan, New York, NY. Vijayanunni, M. 1998 Census of India-1991 Series-1-India (Migration Tables). Controller of Publications. Government of India, Delhi, India. Weingast, B.R. 2009 “Second Generation Fiscal Federalism: The Implications of Fiscal Incentives”, Journal of Urban Economics, 65(3): 279–293. Yadava, S.S. and K.N. Yadava 1995 “Migration Urbanization and Economic Development in India”, Journal of Population, 1(2): 157– 173.

© 2018 UNU-WIDER

22


APPENDIX FIGURE A1 (A) NET IN-MIGRATION – 1971; (B) NET IN-MIGRATION – 1981; (C) NET IN-MIGRATION – 1991; (D) NET IN-MIGRATION – 2001 (A): NET IN-MIGRATION -1971

(B): NET IN-MIGRATION -1981

1971

1981

Maharashtra

MAHARASHTRA

West Bengal

WEST BENGAL

Madhya Pradesh

MADHYA PRADESH HARYANA

Assam Haryana

KARNATAKA

Karnataka

ORISSA

Nagaland

GUJARAT

Meghalaya

MEGHALAYA

Manipur

NAGALAND

Orissa

SIKKIM

Jammu & Kashmir

TRIPURA

Tripura

JAMMU & KASHMIR

Himachal Pradesh

MANIPUR

Gujarat

HIMACHAL PRADESH

Tamil Nadu

PUNJAB

Andhra Pradesh

RAJASTHAN ANDHRA PRADESH

Punjab Rajasthan

TAMIL NADU

Kerala

KERALA

Bihar

BIHAR

Uttar Pradesh -1800000

-800000

UTTAR PRADESH 200000

1200000

2200000

(C): NET IN-MIGRATION -1991

-3000000

-1000000

(D): NET IN-MIGRATION - 2001

2001

1991 Maharashtra Haryana Gujarat West Bengal Jharkhand Punjab Madhya Pradesh Uttaranchal Goa Arunachal Pradesh Karnataka Meghalaya Sikkim Chhatisgargh Himachal Pradesh Mizoram Tripura Jammu & Kashmir Manipur Nagaland Assam Orissa Andhra Pradesh Kerala Tamil Nadu Rajasthan Bihar Uttar Pradesh

Maharashtra Madhya Pradesh West Bengal Gujarat Haryana Assam Karnataka Arunachal Pradesh Goa Nagaland Punjab Meghalaya Mizoram Manipur Orissa Sikkim Tripura Himachal Pradesh Andhra Pradesh Rajasthan Tamil Nadu Kerala Bihar Uttar Pradesh -3000000

-1000000

1000000

1000000

3000000

-5000000

Source: Computed from Census of India (various years) © 2018 UNU-WIDER

-2000000

1000000

4000000

3000000