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Regional Sources of Growth Acceleration in India

Gujarat, West Bengal, Karnataka, Maharashtra, Kerala and Tamil Nadu were the major contributors to the growth acceleration in India after 1991-92. Although regional disparity may increase temporarily, the causality test provides support to the hypothesis about spread effects. The regional growth targets assigned by the Eleventh Plan in India seem to rely on the spread effects of economic growth acceleration in the better-off states to achieve its 9% growth target and reduce regional disparity in the long run. To strengthen the spread effects, the domestic economy should be further integrated and interlinked with free flow of goods, services and factors of production.


Regional Sources of Growth Acceleration in India

Ravindra H Dholakia

Gujarat, West Bengal, Karnataka, Maharashtra, Kerala and Tamil Nadu were the major contributors to the growth acceleration in India after 1991-92. Although regional disparity may increase temporarily, the causality test provides support to the hypothesis about spread effects. The regional growth targets assigned by the Eleventh Plan in India seem to rely on the spread effects of economic growth acceleration in the better-off states to achieve its 9% growth target and reduce regional disparity in the long run. To strengthen the spread effects, the domestic economy should be further integrated and interlinked with free flow of goods, services and factors of production.

An earlier version of the paper was presented as a keynote address to the International Regional Science Symposium and 40th Annual Regional Science Conference held in January 2009 at Nirma University, Ahmedabad. Thanks are due to Shreekant Iyengar, Brajesh Kumar and Apurva Adhvaryu for providing assistance in data collection and computations.

Ravindra H Dholakia ( is with the Indian Institute of Management, Ahmedabad.

Economic & Political Weekly

november 21, 2009 vol xliv no 47

1 Growth Acceleration in India

esearch on identifying distinct phases in the growth history of India has almost conclusively established as of now that there have been four different phases of economic growth since the beginning of the 20th century. There have been debates and differences in the findings and opinions on the exact break dates in the long-term growth path in the national economy (Ganesh 1992; DeLong 2001; Wallack 2003; Panagariya 2004; Sinha and Tejani 2004; Hatekar and Dongre 2005; Nayyar 2006 and Balakrishnan and Parameswaran 2007). Most of the researchers approached this problem by first identifying significant changes in economic policies around a year and tested their hypotheses of the growth shift from the preidentified year empirically with observed data. The exceptions to such an approach to identify the break dates for growth of the Indian economy were the studies by Ganesh (1992) and Balakrishnan and Parameswaran (2007). Both these studies derived the exact break dates endogenously from the data set itself rather than pre-identifying and testing for statistical significance. While Ganesh (1992) used the Quandt test (1960) to identify one break point at a time, Balakrishnan and Parameswaran (2007) used Bai and Perron (1998, 2003) method to identify multiple break points simultaneously. Both the studies identified only one break point in the growth history of post-independence period in India although the exact dates differed marginally. Since the latter study (Balakrishnan and Parameswaran 2007) used longer time series and the latest methodology, the authors claimed that their findings were more reliable. However, in response to a comment (Dholakia R H 2007), when they revised their estimates using the same methodology but using the most recent data on the gross domestic product (GDP) with base year 1999-2000, they found two instead of one break points in the post-independence growth history of India (Balakrishnan and Parameswaran 2007a).1

Thus, as per the established findings as of now, there are four distinct phases of economic growth through which the Indian economy progressed since the beginning of the 20th century. These phases and the corresponding approximate growth rates observed are given in Table 1 (p 68).

It can be seen from the table that during the first 50 years of the 20th century, when India was under the British rule, the economy was almost stagnant. Maximum acceleration of 2.4 percentage points in the growth rate of aggregate GDP was achieved during the first 30 years of independence. The acceleration in the growth rate of per capita income (PCI) was however limited to only 1.2 percentage points per annum, because the population growth accelerated. Maximum acceleration of 2 percentage

Table 1: Continuous Compounded Annualised Growth Rates (CAGR) of Real GDP by Phases in India

Time Period CAGR Acceleration in CAGR of CAGR of Acceleration in (in %) Percentage Points Population (in %) PCI (in %) Percentage Points

1900-01 to 1950-51 1.0 – 1.0 0 –

1950-51 to 1980-81 3.4 2.4 2.2 1.2 1.2

1980-81 to 1991-92 5.3 1.9 2.1 3.2 2.0

1991-92 to 2003-04 5.9 0.6 1.8 4.1 0.9

Source: Basic data on GDP from Sivasubramonian (2004) and CSO (2007).

points was achieved in the growth of PCI during the next decade (the 1980s), when the GDP growth accelerated further and population growth decelerated. During the first 13 years of the wideranging economic reforms, when the GDP growth further accelerated with the population growth further decelerating, the rate of acceleration in growth of PCI sharply fell to only 0.9 percentage point. The growth acceleration in aggregate GDP although positive has sharply declined during the three phases of growth in the second half of the 20th century in India.

The sources of growth and acceleration during these phases of the growth history have been studied using four different approaches. The first one of these is the neoclassical growth approach of functional distribution of labour, land, capital and technical progress (Dholakia B H 1974 and 2001; and Sivasubramonian 2004). These studies found technical progress to be the major source of growth as well as of acceleration in growth during the second half of the 20th century. The second approach was to consider institutional ownership between the public and the private sector (Dholakia B H 1980 and 2001). The findings were interesting. During the first 30 years of independence, it was the technical progress particularly in the public sector undertakings that contributed substantially to the growth of GDP and hence to the growth acceleration of 2.4 percentage points. However, in the subsequent period, it was the private sector particularly the private corporate sector that was mainly responsible for the growth acceleration. The third approach was of considering the sectoral classification of GDP (Dholakia B H 1974, 2001; Sivasubramonian 2004; Ganesh 1992; and Balakrishnan and Parameswaran 2007). Although the findings of these studies vary, it is established that the non-agricultural sector, particularly the tertiary sectors drove the economy both during the 1980s and the 1990s, contributing substantially to the growth acceleration.

The fourth approach of considering regional aspects of growth has been relatively ignored with only one attempt being made (Dholakia R H 1994). The study considered 20 state economies and three broad sectors in each of them to identify the break dates endogenously in the growth path during the period 1960-61 to 1989-90 using the Quandt test (1960). Thus, the study had identified regional sources of growth acceleration between phases 2 and 3 of Table 1. The sectoral dimension in the study provides a very different perspective on the sources of growth acceleration from the one based only on the nationwide aggregative sectoral approach (Dholakia R H 2007). The findings of the study are summarised for ready reference in Table 2.

It is seen from Table 2 that only seven state economies experienced growth acceleration before the national break date. These states were Bihar in 1967-68, Andhra Pradesh (AP) in 1968-69, Maharashtra and Tripura in 1972-73, Gujarat in 1973-74, Uttar Pradesh (UP) in 1974-75 and Madhya Pradesh (MP) in 1979-80.2 In the rest of the states the acceleration in the growth rate was either not experienced at all or experienced much later than the nation as a whole. Among the seven states experiencing growth acceleration earlier than the whole national economy, in terms of sequencing, the growth acceleration of the tertiary sector did not precede the growth acceleration of the whole state economy in any state.3 On the contrary, in all the seven states the tertiary sector experienced acceleration only after (AP, Bihar, Maharashtra, Tripura and UP) or at best simultaneously (Gujarat and MP) with the whole economy.

This finding is not surprising because prior to 1980-81, India was hardly integrated with the rest of the world and only the domestic demand would drive the economic activities. It is only

Table 2: Estimates of Break Dates for State Economies in India

States Primary Sector Secondary Sector Tertiary Sector Whole Economy
Andhra Pradesh - - 1972-73(+) 1968-69(+)
Arunachal Pradesh 1979-80(+) - - -
Assam - 1979-80 (+) 1979-80 (+) 1979-80(+)
Bihar - 1980-81 (+) 1972-73(+) 1967-68(+)
Gujarat 1982-83 (-) 1975-76(+) 1973-74(+) 1973-74(+)
Haryana - 1981-82(+) - -
Himachal Pradesh - - 1984-85(+) 1985-86(+)
Jammu and Kashmir 1985-86(-) - 1973-74(-) 1985-86(-)
Karnataka - - 1975-76(+) 1985-86(+)
Kerala 1972-73(-) 1972-73(-) 1972-73(-)
Madhya Pradesh - 1978-79(+) 1979-80(+) 1979-80(+)
Maharashtra - - 1984-85(+) 1972-73(+)
Manipur 1977-78(-) 1969-70(+) 1979-80(+) 1977-78(-)
Orissa 1965-66(-) - 1970-71(-) 1967-68(-)
Punjab 1984-85(+) 1979-80(-) -
Rajasthan 1982-83(+) 1974-75(+) -
Tamil Nadu - 1979-80(-) 1983-84(+) -
Tripura - - 1975-76(+) 1972-73(+)
Uttar Pradesh 1973-74(+) 1974-75(+) 1976-77(+) 1974-75(+)
West Bengal 1982-83(+) - 1972-73(+) 1982-83(+)
All India 1979-80(+) 1981-82(+) 1982-83(+) 1981-82(+)
  • (1) (+) indicates acceleration and (-) indicates deceleration.
  • (2) No adjustments have been made for weather or public administration. Source: Summarised from different tables in Dholakia (1994).
  • the production of goods (primary and secondary sectors) that can generate the demand for services and, therefore, the growth acceleration in the goods sector must precede the one in services. Even with severe limitations of data, consideration of regional aspects can significantly help us understand and interpret the growth story.

    After 1980-81, the Indian economy started getting more and more integrated domestically and internationally. Rapidly growing export demand for the Indian goods and particularly services became the driving force for the economic activities in India. The analysis of determining endogenously the trend break dates by sector in different states for identifying regional sources of acceleration between phases 3 and 4 of Table 1 above would, therefore, hardly be relevant in terms of establishing primacy of sectoral activities to understand the growth story of the country. H owever, finding out the contribution of different states in the observed acceleration in economic growth in the nation could be rewarding for pursuing economic reforms further in the lagging

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    states. It can help to identify the major contributor states so r esponsible for the observed acceleration in economic growth in that their policies can be emulated by other states to the ex-the country. The third section considers all better-off states and tent possible. Competitive politics among states, if properly worse-off states as two regions to find out whether the two regulated by the centre, can result in further growth regions are economically integrated in the sense that growth in a cceleration in the nation. one causes the growth in the other and if so, how best to plan for

    The second section of the present paper estimates the contri-the growth acceleration in the nation. The fourth section exambution of each state in the observed growth acceleration in the ines the plausibility and feasibility of the sectoral growth targets nation between the periods 1980-81 to 1991-92 and 1991-92 to set for each state by the Planning Commission for the Eleventh 2003-04. It identifies the states and the sectors within states Five-Year Plan by examining the growth history of all the states

    Table 3: Estimates of Annualised Growth Rates of GSDP at Constant (1993-94) Prices by Table 3: (Continued) Primary, Secondary and Tertiary Sectors in States of India States Sectors 1980-81 to 1991-92 1991-92 to 2003-04 Difference in States Sectors 1980-81 to 1991-92 1991-92 to 2003-04 Difference in Growth T-Values Growth T-Values Growth Rates

    Growth T-Values Growth T-Values Growth Rates (b) (in %) (b) (in %) 7=(5)-(3)

    (b) (in %) (b) (in %) 7=(5)-(3) 1 2 3 4 5 6 7 1 2 3 4 5 6 7

    Maharashtra P 3.15 3.23 2.76 3.92 -0.39Andhra Pradesh P 2.44 3.48 3.45 7.39 +1.01

    S 6.15 17.70 3.99 5.97 -2.16 S 7.42 16.75 6.03 20.55 -1.39 T 6.56 29.33 7.42 38.68 +0.86

    T 7.23 21.89 6.92 39.45 -.31 GSDP 5.65 16.41 5.54 16.39 -0.11 GSDP 5.27 11.16 5.62 31.01 +0.35 Manipur P 2.13 7.83 2.86 8.44 +0.73

    Arunachal Pradesh P 8.05 12.39 (-)0.13* – -8.18 S (-)2.33* -6.25 6.16 +8.58

    T 6.07 40.05 6.44 20.87 +0.37

    S 7.69 9.84 4.42 3.72 -3.27

    GSDP 2.48 2.34 5.28 12.35 +2.80

    T 9.15 18.91 7.94 22.84 -1.21 Meghalaya P 3.33 4.46 5.49 9.61 +2.16

    GSDP 8.29 29.47 3.95 11.78 -4.34 S 3.55 6.75 8.34 23.96 +4.79

    Assam P 4.41 1.99 0.79 5.43 -3.62 T 7.11 24.31 5.96 36.30 -1.15

    S 3.58 8.86 2.31 7.21 -1.27 GSDP 5.15 12.11 6.14 20.91 +0.99

    T 4.90 18.56 4.76 16.47 -0.14

    Orissa P 2.00* -2.16 4.41 +0.16

    GSDP 3.38 13.91 2.68 19.21 -0.70

    S 7.17 10.81 2.50 5.43 -4.67 Bihar + Jharkhand P 2.72 4.08 2.99 5.10 +0.27

    T 6.10 19.87 6.52 55.09 +0.42 S 6.00 11.31 5.02 5.48 -0.98

    GSDP 3.80 6.93 3.96 15.77 +0.16 T 5.42 26.64 5.65 19.57 +0.23

    Punjab P 4.74 19.52 2.17 11.92 -2.57 GSDP 4.12 11.84 4.38 12.02 +0.26

    S 6.30 26.48 5.58 17.11 -0.72 Goa P 0.84 1.87 1.55 3.99 +0.71

    T 3.84 30.82 6.60 30.87 +2.76 S 2.89 1.83 11.04 12.16 +8.15

    GSDP 4.75 35.02 4.47 32.18 -0.28 T 6.35 17.96 7.60 14.45 +1.25Rajasthan P 5.54 3.57 2.50 2.33 -3.04 GSDP 3.96 6.48 7.79 25.70 +3.83 S 7.36 18.13 6.93 10.37 -0.43 Gujarat P 1.10* – 2.97* – +1.87 T 7.58 18.40 7.44 33.48 0.14 S 6.71 12.24 8.13 12.02 +1.42 GSDP 6.59 10.27 5.65 11.61 -0.94 Tamil Nadu P 3.87 5.88 0.33* --3.54

    T 5.98 24.97 7.89 50.61 +1.91

    S 4.25 10.25 4.79 8.78 +0.54 T 6.30 24.53 7.95 34.13 +1.65

    GSDP 4.16 6.64 6.61 12.45 +2.45

    Haryana P 4.30 6.43 1.97 8.23 -2.33 GSDP 4.95 18.65 5.43 16.73 +0.48

    S 6.77 16.88 6.07 32.71 -0.70

    Uttar Pradesh +

    T 7.33 30.13 8.59 23.16 +1.26

    Uttarakhand P 2.57 10.91 2.30 9.88 -0.27 GSDP 5.82 17.09 5.51 30.43 -0.31

    S 6.74 22.30 4.30 10.43 -2.44 Himachal Pradesh P 2.35 3.17 1.88 8.51 -0.47

    T 5.66 26.30 4.45 34.83 -1.21 S 6.21 7.84 9.18 16.10 +2.97

    GSDP 4.51 22.61 3.61 19.72 -0.90 T 6.39 20.53 7.20 20.72 +0.81 West Bengal P 5.05 10.32 3.84 14.79 -1.21 GSDP 4.73 10.09 6.35 62.12 +1.62 S 3.91 16.78 5.74 36.24 +1.83

    Karnataka P 2.41 6.18 2.45 3.79 +0.04 T 4.71 47.26 8.91 46.94 +4.20 S 6.27 18.13 7.55 21.05 +1.28 GSDP 4.62 26.56 6.69 88.17 +2.07 Total of 20 states P 2.75 7.71 2.35 8.88 -0.40

    T 6.83 54.09 9.42 55.41 +2.59

    S 5.80 25.47 5.56 15.79 -0.24

    GSDP 4.91 21.57 6.89 35.09 +1.98

    T 5.98 49.97 7.15 95.43 +1.17

    Kerala P 0.51* – (-)0.44* – -0.95 GSDP 4.69 22.23 5.30 38.35 +0.61

    S 3.06 5.70 6.02 8.75 +2.96 Nation P 3.28 11.24 2.72 11.47 -0.56

    T 4.18 19.15 7.81 36.37 +3.63S 6.42 30.76 6.18 25.21 -0.24

    GSDP 2.70 5.89 5.38 22.50 +2.68 T 6.58 70.45 7.77 81.04 +1.19

    Madhya Pradesh + GSDP 5.29 32.95 5.91 65.32 +0.62

    Chhattisgarh P 1.00 2.05 1.84 2.61 +0.84

    (1) *Represents CAGR based on three-year average at the end points since the growth rate S 5.03 6.46 6.11 13.75 +1.08 parameter in the semi-log regression is not significant even at 10% level. The rest of the growth

    rates reported here are statistically significant at least at 10% level, with most of them being T 5.76 37.61 5.51 28.03 -0.25significant at 1% level.

    (2) P = Primary Sector, S = Secondary Sector, T = Tertiary Sector

    GSDP 3.40 8.42 4.33 12.71 +1.03

    Source : Basic data on GSDP from CSO web site.

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    for the last 25 years. The fifth and the final section concludes the discussion providing some policy recommendations.

    2 Contribution of States in Growth Acceleration

    The basic premise for doing such an exercise is that a nation is an aggregation of its regions. Thus, if we add the incomes of all states (regions), we should get the national income. This premise does not strictly hold in India given the problems in measurement and the data availability issues for some states and union territories. However, such problems are not considered serious in terms of magnitudes and are, therefore, ignored in India.

    In order to derive the contribution of states in the national growth acceleration between two given time periods, it is necessary to estimate the growth rates of the states in the two time periods. This can be done for each sector and for the economy as a whole. The relevant concept of income is the gross state domestic product (GSDP) originating within the geo

    s tructure of regional growth in the country. The impact on the regional composition is captured by the relative shares of GSDP by the three broad sectors as presented in Table 4.

    Tables 3 and 4 together provide the base for estimating a state’s contribution to the growth acceleration (or deceleration) observed in the national average from the period 1980-81 to 1991-92 and 1991-92 to 2003-04.4 These estimated contributions of each state in the national growth acceleration (or deceleration) in the primary, secondary and tertiary sectors along with the whole economy are presented in Table 5 (p 71).

    The table clearly brings out the major regional sources of acceleration in the national economy during phases 3 and 4 of its growth story. Phase 3 (1980-81 to 1991-92) was a period of decontrol and deregulation, whereas phase 4 (1991-92 to 2003-04) was a period of liberalisation and globalisation. Gujarat emerged as a clear winner during this phase with highest contribution to the

    graphical boundary of the state and is measured at Table 4: Average Relative Shares of All States in GSDP by Broad Sectors (in %)
    constant (1993-94) prices. The estimates of annu- Primary Secondary Tertiary 1980-81 to 1991-93 GSDP Primary Secondary Tertiary 1991-92 to 2003-05 GSDP
    alised growth rates based on continuous com- Andhra Pradesh 8.45 6.16 8.34 7.87 8.62 7.02 8.59 8.16
    pounding are derived by fitting the following re- Arunachal Pradesh 0.12 0.08 0.07 0.09 0.14 0.10 0.10 0.11
    gression for each time period: Assam 3.25 1.53 2.14 2.42 2.76 1.09 1.82 1.91
    ln Y = a + b*t + u Bihar + Jharkhand 9.20 4.92 5.68 6.86 7.65 3.95 4.68 5.37
    Where ‘ln’ stands for natural logarithm, ‘Y’ for Goa 0.22 0.37 0.41 0.33 0.20 0.47 0.44 0.38
    GSDP in the sector, ‘t’ for years, ‘u’ for random error Gujarat 6.25 8.32 6.80 6.98 6.02 10.66 6.98 7.69
    term, ‘a’ for the intercept parameter, and ‘b’ for the Haryana 3.63 3.45 2.45 3.15 3.85 3.29 2.65 3.19
    growth rate parameter. Table 3 (p 69) presents the estimates of the growth rate parameter ‘b’ for the economy and three sectors in 20 states considered in this study for the two time periods, 1980-81 to HPKarnataka KeralaMadhya Pradesh + Chhattisgarh Maharashtra 0.71 5.85 3.45 9.12 8.07 0.63 5.68 2.87 6.70 19.00 0.70 5.34 4.90 6.63 15.98 0.69 5.62 3.84 7.63 13.65 0.64 6.15 3.09 8.47 9.13 0.88 6.27 2.87 6.79 18.78 0.67 6.19 4.57 5.92 18.31 0.72 6.21 3.68 6.92 15.66
    1991-92, and 1991-92 to 2003-04. Manipur 0.20 0.36 0.21 0.24 0.19 0.15 0.20 0.18
    Table 3 reveals tremendous variation in the Meghalaya 0.23 0.11 0.28 0.22 0.25 0.12 0.28 0.22
    growth experience of the state economies in India Orissa 4.03 2.18 2.31 2.95 3.31 1.82 2.25 2.45
    over the 24 years considered in the present study. Punjab 5.35 3.42 3.71 4.26 5.70 3.48 3.25 4.05
    It indicates significant structural changes in the Rajasthan 5.09 4.11 4.42 4.60 5.88 5.01 4.72 5.15
    state economies and in the regional profile of the Tamil Nadu 5.15 11.66 8.19 7.85 5.48 10.39 8.95 8.30
    country. During the third phase (the 1980s) of the Uttar Pradesh + Uttarakhand 14.95 10.95 12.81 13.19 14.41 10.12 10.70 11.63
    growth story of the nation, the high growth states were Arunachal Pradesh, Haryana, Maharashtra West Bengal Total of 20 states Source: Same as Table 3. 6.68 100 7.49 100 8.62 100 7.57 100 8.08 100 6.74 100 8.74 100 8.01 100

    and Rajasthan, the rest being low growth states. All these four high growth states of the 1980s turned into low growth states during the fourth phase of the growth story of the nation (1991-92 to 2003-04). However, Goa, Gujarat, Himachal Pradesh, Karnataka, Meghalaya and West Bengal became high growth states from the low growth states during the same period. Similar stories can be found by considering the sectoral growth rates. It is clearly seen from the table that smaller states like Arunachal Pradesh, Manipur, Meghalaya, Himachal Pradesh and Goa (which are generally excluded from several regional studies in India!) are the ones experiencing very wide fluctuations in their sectoral growth rates. In short, the Indian growth story in its third and the fourth phases has considerable twists and turns for its regions. Since the major difference between the third and fourth phases of growth in India is in terms of increased globalisation and greater liberalisation, these policy changes have significant differential impacts on composition and national growth acceleration. Almost one-third of the national growth acceleration during this period was accounted for by Gujarat alone. West Bengal and Karnataka were respectively the second and the third largest contributors to the national growth acceleration. Kerala, Maharashtra and Tamil Nadu also contributed substantially to the growth acceleration. However, out of these high performing six states, only Gujarat and Karnataka performed consistently in all the three sectors. West Bengal and Kerala performed in the secondary and tertiary sectors, while Maharashtra and Tamil Nadu performed only in the tertiary sector. The smaller states doing well in all the three sectors and positively contributing to national growth acceleration were Goa and Manipur.

    On the other hand, UP (including Uttarakhand) was the major laggard contributing negatively to growth acceleration in all the three sectors, as also Bihar and Assam. Actually, the national

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    Table 5: States’ Contribution to Growth Acceleration by Sectors
    States Primary Secondary Tertiary GSDP
    R1*G1 - R0*G0 (in % points)
    Andhra Pradesh 0.0914 - 0.0340 - 0.0090 0.0443
    Arunachal Pradesh - 0.0098 - 0.0017 0.0013 - 0.0031
    Assam - 0.1214 - 0.0297 - 0.0180 - 0.0306
    Bihar + Jharkhand - 0.0217 - 0.0968 - 0.0431 - 0.0474
    Goa 0.0012 0.0414 0.0075 0.0164
    Gujarat 0.1102 0.3085 0.1441 0.2178
    Haryana - 0.0805 - 0.0343 0.0480 - 0.0077
    Himachal Pradesh - 0.0046 0.0415 0.0040 0.0132
    Karnataka 0.0096 0.1175 0.2179 0.1518
    Kerala -0.0312 0.0851 0.1517 0.0944
    Madhya Pradesh + Chhattisgarh 0.0646 0.0779 - 0.0560 0.0402
    Maharashtra - 0.0024 - 0.4195 0.3103 0.0963
    Manipur 0.0011 0.0175 0.0001 0.0036
    Meghalaya 0.0059 0.0062 -0.0035 0.0025
    Orissa - 0.0092 - 0.1109 0.0059 - 0.0150
    Punjab - 0.1298 - 0.0216 0.0718 - 0.0215
    Rajasthan - 0.1352 0.0453 0.0164 - 0.0123
    Tamil Nadu - 0.1813 0.0020 0.1951 0.0625
    Uttar Pradesh + Uttarakhand - 0.0526 - 0.3029 - 0.2490 - 0.1749
    West Bengal - 0.0272 0.0943 0.3731 0.1862
    Total of 20 states - 0.5230 - 0.2142 1.1684 0.6168
    National GDP - 0.56 - 0.24 1.19 0.62

    Source: Tables 3 and 4.

    growth in the primary sector and the secondary sector registered a deceleration over the two phases largely because most of the states experienced deceleration in these two sectors. During the fourth phase, the growth acceleration in the nation is mainly contributed by the better-off states. The worse-off states except West Bengal have not contributed substantially to the growth acceleration in the nation during the phase of liberalisation and globalisation.

    In agriculture, only Gujarat, AP and MP (including Chhattisgarh) had substantial positive contribution. On the other hand, Tamil Nadu, Rajasthan, Punjab, Haryana and UP experienced a substantial deceleration. Thus, the agriculture in the nation suffered because the traditional agricultural areas of the nation performed poorly, while the shift to more commercialised agricultu re in states like Gujarat, AP and MP was not sufficient to compensate.

    In the secondary sector, Maharashtra, UP, Orissa and Bihar had substantial negative contribution to the growth acceleration, and a substantial positive contribution came from Gujarat, Karnataka, West Bengal and Kerala. Thus, the industries also got differentially impacted during liberalisation as expected. The traditional industries with considerable participation of public sector and enjoying a large degree of protection experienced relative decline and modern industries with larger private sector participation grew fast in the liberalised and globalised era. The state governments’ policies and state level reforms also played an important role in the growth performance of states particularly in attracting industrial investments.

    In tertiary sector, most of the states performed well and contributed positively to the acceleration of growth in the nation. The major laggards in this sector were UP and MP. Surprisingly, it is West Bengal and Maharashtra which have contributed substantially to the growth acceleration in this sector, even more

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    than the traditionally hailed leaders in services like Karnataka, Tamil Nadu and Kerala.

    3 Causality for Growth among Regions

    Consideration of regional dimension in India generally stems from the concerns about disparity and inequality among states and regions in the levels of development. However, another equally important angle would be of efficiency. When growth or development in an economy is considered in terms of geography, regional disparity or inequality, particularly in income originating, is inevitable, because growth impulses are invariably location-specific (Myrdal 1957 and Hirschman 1959). The question of interest would then be whether it leads to further polarisation and concentration of economic activities by attracting the resources from the periphery or whether it leads to spread of economic activities and trickle down of economic opportunities to the periphery. While one can theorise and argue about the likely dominance of one over the other of these effects, it is better to examine the empirical evidence in this regard.

    The popular empirical evidence often cited for the regional polarisation implying continuance or increasing inequality and disparity in development levels of states over time is to consider the weighted or unweighted coefficient of variation of per capita GSDP originating within the geographical boundaries of the states. Another (and perhaps more sophisticated) measure is the Gini coefficient of inequality.

    Table 6 presents the Gini coefficient of inequality in the country among states since 1980-81. The table shows that regional inequality has risen over time in India. The traditional conclusion would, therefore, be that Indian regional data supports the polarisation hypothesis against the spread effect of regional

    Table 6: Trends in Interstate Inequality, 1980-81 to 2006-07

    Year Gini Coefficient Year Gini Coefficient Year Gini Coefficient
    1 2 1 2 1 2
    1980-81 0.115 1989-90 0.133 1998-99 0.159
    1981-82 0.121 1990-91 0.166 1999-00 0.164
    1982-83 0.113 1991-92 0.134 2000-01 0.164
    1983-84 0.113 1992-93 0.148 2001-02 0.207
    1984-85 0.112 1993-94 0.151 2002-03 0.204
    1985-86 0.114 1994-95 0.158 2003-04 0.209
    1986-87 0.111 1995-96 0.174 2004-05 0.205
    1987-88 0.122 1996-97 0.164 2005-06 0.208
    1988-89 0.119 1997-98 0.160 2006-07 0.206

    Gini Coefficients here are calculated on the basis of 14 major states in India. Source: Centre for Monitoring Indian Economy for the basic data.

    growth. However, such crude tests based on inequality measures should not be used to verify hypotheses that essentially describe processes and causal effects. There is a need to test these hypotheses directly by considering two regions, a better-off r egion (B) consisting of all better-off states and a worse-off region

    (W) consisting of the rest of the states in the country; and then carrying out the Granger causality test for the level of the income and the rate of change in the income in the two regions.

    The hypothesis of the spread and trickling down effects would hold if the income and growth of the better-off region Granger-causes the income and growth of the worse-off region with positive coefficients. The same direction of causality with negative coefficient would support the polarisation and concentration hypothesis. However, if the causality is found from the worse-off region to the better-off region, or if there is bidirectional causality, then the empirical evidence may be consider ed inconclusive about these hypotheses.

    The exercise carried out here considers data on GSDP at constant (1999-2000) prices from all states for the period 1980-81 to 2006-07 after making necessary adjustments for base year changes. Among the better-off states (B), AP, Goa, Gujarat, Haryana, Karnataka, Kerala, Maharashtra, Punjab and Tamil Nadu are included. The rest are included among worse-off states (W). The GSDP of these two categories, B and W are derived by adding the GSDP of states belonging to the respective groups.

    The Granger-Causality test is performed by vector auto regression (VAR) modelling where the selection of lags is done through Akaike Information Criterion (AIC) because the Wald test is s ensitive to the lag selection. Table 7 presents the results of the Granger-Causality test.

    The table clearly shows that both the VAR model and the Wald test for Granger-Causality confirm only unidirectional causality of level as well as rate of change in GSDP from B-group of states to W-group of states. Moreover, the coefficients in both the cases are positive indicating that an increase in the level (and the rate of

    Table 7: Granger-Causality – Results of VAR Model and Wald Test

    Dependent Variable Independent Parameter Standard P-Value Wald Test
    Variable Estimate Error
    1 2 3 4 5 6
    I On GSDP levels with lag = 2 based on minimum AIC
    1 GSDP-B Constant -63493 45120 0.1747 Chi-Square = 2.07
    GSDP-B(t-1) 1.378 0.284 0.0001 with 2 degrees of
    GSDP-W(t-1) 0.067 0.379 0.8621 freedom and
    GSDP-B(t-2) -0.692 0.311 0.0378 significant only
    GSDP-W(t-2) 0.470 0.382 0.2321 at 35.47% level
    2 GSDP-W Constant 33967 34702 0.3394 Chi-square = 8.02
    GSDP-B(t-1) 0.618 0.218 0.0103 with DF=2 and
    GSDP-W(t-1) 0.185 0.291 0.5318 significant @
    GSDP-B(t-2) -0.380 0.239 0.1283 1.81% level
    GSDP-W(t-2) 0.519 0.294 0.0926
    II On Δ GSDP with lag=1 based on minimum AIC
    1 Δ GSDP-B Constant 9687 6903 0.1745 Chi-Square=0.16 with
    Δ GSDP-B(t-1) 0.928 0.242 0.0009 DF=1 and significant
    Δ GSDP-W(t-1) -0.147 0.365 0.6920 @ 68.81% level
    2 Δ GSDP-W Constant 13507 5158 0.0157 Chi-Square = 20.29
    Δ GSDP-B(t-1) 0.815 0.181 0.0002 with DF=1 and signi
    Δ GSDP-W(t-1) -0.631 0.273 0.0305 ficant @ 0.01% level

    Both the tests are consistent in their conclusions.

    change) of GSDP of the better-off states would lead to (or cause) an increase in the level (and the rate of change) of GSDP of the worse-off states in India. Thus, the Indian regional data over the last 27 years clearly supports the hypothesis of spread and trickle-down effect rather than the backwash or polarisation effect. This is an important finding for the Planning Commission and the Finance Commissions whose main concerns so far have been regional disparities and inequalities while allocating and devol ving resources among states.

    Economic growth in better-off states does spur growth in the worse-off states not only through temporary migration of labour and capital but also through the forward and backward linkages of economic activities. The more integrated the national economy geographically, the higher are the benefits of the spread and the trickle-down effect of the leading regions to the lagging regions. Since increased globalisation has reduced the constraints on effective demand and thereby on the extent of specialisation in the regional economies, it has paved the way for increased spread and trickle-down effects through greater regional integration in the domestic economy. The backwash and polarisation effects become relevant more in an overall static framework where the size of the cake for sharing among regions remains more or less constant. Increased globalisation, on the contrary, has enabled a rapid expansion of the production possibility frontier not only through reduced barriers to trade enabling greater flow of goods and services across borders, but also through increased factor mobility across nations. Rapid liberalisation of domestic economic policies to ensure fuller economic integration of all state economies could be the most effective alternative to achieve further efficiency and acceleration in the growth rate. Concerns about regional equity and disparities in such a domestically wellintegrated economy, operating in an increasingly globalised environment need not distract the efforts particularly in the light of the empirical findings of the present section.

    4 Plausibility of Regional Growth Targets

    In recognition of the regional aspects of growth and competitive politics, the Planning Commission has started decomposing its national growth target for the five-year plan for each state and bigger union territories since the Tenth Plan. It further provides the growth targets for each region by the three broad sectors agriculture, industry and services, broadly corresponding to the standard classification of primary, secondary and tertiary sectors. The Eleventh Plan (2007-08 to 2011-12) has provided the regional growth targets ranging from 5.4% pa to 13.5% pa if union territories are included, and 5.9% to 12.1% per annum if only states are considered. This is indeed a substantial variation in comparison to the national growth target of 9% pa. However, the Planning Commission (2007) has not provided any reasons, justifications or indications of expected changes in economic policies in the res pective states for achieving those targets.

    Before setting those targets, the Planning Commission (2007) has considered statewise sectoral growth performance in the Tenth Five-Year Plan during the three years from 2001-02 to 2004-05. However, those results and the targets have hardly any relationship. The regional growth target setting seems to be an ad hoc arithmetic exercise. It is important to check the plausibility and feasibility of those targets by considering the best performance of states during the past two decades. The best performance is identified as the highest growth rate clocked during any five consecutive years in the state over the period 1980-81 to 2003-04. Such maximum achieved growth rates by sectors for each state are presented in Table 8 along with the Eleventh Plan targets set by the Planning Commission (2007).

    Several interesting points emerge from Table 8 (p 73). First of all, considering the best performance of states during the last two decades, only AP, Arunachal Pradesh, Goa, Gujarat and Rajasthan have grown at a rate higher than 9% pa for five

    november 21, 2009 vol xliv no 47


    c onsecutive years. The rest of the states have never experienced In the industrial and service sectors, however, the targets often such a high growth rate for five consecutive years so far. On the are more ambitious than the best performance in the past other hand, the Eleventh Plan has assigned a target of growth would suggest. rate higher than 9% pa to Haryana, Himachal Pradesh, Karna-It is interesting to note that the national growth target is set at taka, Kerala, Maharashtra, and West Bengal besides AP, Goa and 9% pa for the Eleventh Plan implying a considerable acceleration Gujarat. Moreover, out of all these nine states, only Gujarat is as-in the growth rate during the plan period, and that the nine states signed a target that it has achieved in the past. The remaining identified earlier are considered the major regional sources for eight states have been assigned the growth target that they have such an acceleration. All these states except Himachal Pradesh not achieved so far. and West Bengal belong to the category of the better-off states. It

    In order to derive the upper limit of plausible growth perform-appears that the Planning Commission has implicitly accepted ance in states, the maximum growth rates clocked during any the arguments in favour of efficiency over equity. However, the evidence on the direction of causality pro-

    Table 8: Maximum Growth Rates* for Five Consecutive Years during 1980-2004 in States and Growth Targets of Eleventh Plan in India (in %)

    vided in the present study implies that the

    States Maximum Growth for 5 Consecutive Years Eleventh Plan Targets
    Primary Secondary Tertiary GSDP Average@ Agriculture Industry Service Total
    1 2 3 4 5 6 7 8 9 10
    Andhra Pradesh 6.49 11.01 9.83 9.07 9.42 4.0 12.0 10.4 9.5
    Arunachal Pradesh 12.67 16.95 12.88 10.48 13.82 2.8 8.0 7.2 6.4
    Assam 4.89 5.62 7.55 5.13 6.26 2.0 8.0 8.0 6.5

    Bihar+ 7.58 10.10 8.58 7.46 8.50 7.0 8.0 8.0 7.6 Jharkhand 6.3 12.0 8.0 9.8

    Planning Commission has not given up the concerns on regional equity, but has reposed its faith on the spread and trickle-down effects to address regional disparities over time. This, however, implies some important policy changes both at the central and the state levels.

    Goa 4.19 17.30 12.07 10.41 14.54 7.7 15.7 9.0 12.1

    Gujarat 18.37 15.61 9.14 12.39 13.62 5.5 14.0 10.5 11.2 5 Summary and Policy Implications Haryana 9.08 9.45 10.85 8.17 9.98 5.3 14.0 12.0 11.0

    The present study finds that Gujarat, West

    Himachal Pradesh 7.53 14.36 10.65 8.74 11.33 3.0 14.5 7.5 9.5

    Bengal, Karnataka, Maharashtra, Kerala and

    Karnataka 6.79 11.39 10.76 8.77 10.14 5.4 12.5 12.0 11.2

    Tamil Nadu are the major contributors to the

    Kerala 6.20 10.70 10.14 6.68 10.37 0.3 9.0 11.0 9.5 Madhya Pradesh+ 5.19 10.36 7.36 6.59 7.43 4.14 8.0 7.0 6.7

    observed growth acceleration of 0.62 percent-Chhattisgarh 1.17 12.0 8.0 8.6 age points in India after 1991-92. All of them Maharashtra 10.89 8.71 10.03 8.98 9.76 4.4 8.0 10.2 9.1 except West Bengal are better-off states hav-Manipur 4.81 17.23 9.53 8.13 10.27 1.2 8.0 7.0 5.9

    ing higher per capita GSDP than the national

    Meghalaya 7.89 10.43 8.81 8.35 9.58 4.7 8.0 7.9 7.3

    average. This would lead to increase in the re-

    Orissa 6.05 10.95 8.30 5.10 7.92 3.0 12.0 9.6 8.8

    gional disparity or inequality index for the

    Punjab 6.41 8.02 8.50 5.98 7.81 2.4 8.0 7.4 5.9

    time being. However, the causality test pro-

    Rajasthan 15.12 10.86 10.21 10.63 12.76 3.5 8.0 8.9 7.4

    vides support to the hypothesis about the

    Tamil Nadu 7.42 8.38 10.16 7.54 9.25 4.7 8.0 9.4 8.5

    Uttar Pradesh+ 3.93 8.41 7.17 6.01 6.37 3.0 8.0 7.1 6.1 spread and trickle-down effects working Uttarakhand 3.0 12.0 11.0 9.9 among Indian regions. These effects will be West Bengal 8.15 7.48 10.42 7.17 9.26 4.0 11.0 11.0 9.7

    stronger and felt faster if the domestic eco

    * These growth rates are CAGR in GSDP by sectors at constant 1993-94 prices. @ This represents weighted average growth rate based on maximum sectoral growth rates with the weightage of sectoral nomy is very well integrated and interlinked GSDP in the year 2003-04.

    with free flow of goods, services and factors

    Source: Planning Commission (2007) for cols 7 to 10; and author’s calculations for cols 2 to 6.

    of production. The regional growth targets five consecutive years in the three sectors can be considered with assigned by the Eleventh Plan in India, although highly ambitious the weightage given by the sectoral shares in GSDP in the termi-for most of the states, seem to rely on the spread and trickle-down nal year 2003-04. Such a growth rate for each state is presented effects of economic growth acceleration taking place in the in column 6 of Table 8. This is certainly the most optimistic better-off states to address the problems of regional disparity and growth rate for a state when all best conditions experienced in inequality. The Planning Commission has identified almost all the past in each of its sectors are realised simultaneously during better-off states to deliver the required growth acceleration in the same five-year period. Compared to this most optimistic the national growth rate. It is a welcome change in the approach growth rate, the target set by the Planning Commission (2007) is of the Planning Commission not to sacrifice efficiency for immehigher in eight states out of the 20 states considered in Table 8. diate equity concerns, but to take a long-term view where the two This raises serious doubts about the feasibility of the regional are complementary objectives, as the findings of the present growth targets set by the Planning Commission (2007) particu-study indicate. larly because it has not given any justification or any indication In order to achieve such a complementarity between the on the direction of efforts and changes in economic policies re-growth and equity objectives in the long run, it is necessary to quired in the respective states. In this context, it is surprising to implement several policy changes at an early date. It is important find that the targets set for the agricultural sector is consistently for the national policymakers to provide economically and geoless than the best performance already achieved during any five graphically well-integrated national markets for all goods and consecutive years in the case of every state without exception. services. This can be done by removing or at least reducing

    Economic & Political Weekly

    november 21, 2009 vol xliv no 47

    significantly all barriers to the physical movement of goods and services across states. If there are any artificial controls or r egulations on such movements, they need to be immediately r emoved. It will open up the regional markets and production sector to inter-regional competition by reducing all artificial protections under whatever garbs or excuses. Thus, there is a need to equalise all rates of commodity taxation across states. The move to introduce a uniform goods and service tax across states is a welcome step in this context. The direct fiscal incentives given to industries and businesses in any existing locations similarly need to be abolished. The incentives can be in terms of provision of better infrastructural facilities and not tax holidays.

    Simultaneously, the national policymakers need to worry about integrating all state economies effectively for free movement of the factors of production. Free mobility has two dimensions – legal and economic. Most of the factors (though not all) are legally allowed to move across states in India, but there are significant costs attached to such movements because of linguistic, social and imperfect informational reasons. Aggressive pursuit of schooling drive, provision of relevant information, spreading electronic networks and communication channels to cover all the geography and compelling states to provide satisfactory healthcare and to use common language on public


    1 It is too early to detect another expected break point in the year 2003-04 as was argued by the finance minister in his budget speech of 29 February 2008. But a consistent and considerably high growth performance during 2003-04 onwards is likely to lead to another trend break and further acceleration in economic growth in India when sufficient data points are available in future. During 2003-04 to 2008-09, the average real growth rate clocked is 8.5% pa, however, the state income data are not available beyond 2006-07 as of now.

    2 Punjab and Haryana got separated from the old Punjab state in 1966 and their data series, therefore, started only from 1965-66 onwards. As a result, it was not possible to identify the trend-break year for them if it occurred around late or mid1960s, which is most likely to be the case since it is well known that Indian agriculture turned around in the mid-1960s largely on account of developments of irrigation and high yielding varieties of seeds in Punjab and Haryana.

    3 Even if we include Punjab and Haryana among the states experiencing acceleration earlier than the nation, the argument in the text remains valid, because agriculture was the sector in these states to turn around first.

    4 The difference in the national average growth rates during the two periods is represented as (GN1–GN0) = ΣRi1*Gi1 – Σ Ri0 * Gi0 where Ri is the relative share of region i and Gi is the growth rate in region i. Subscripts 0 and 1 represent the two time periods, 1980-81 to 1991-92 and 1991-92 to 2003-04 respectively. Then, (GN1 – GN0) = Σ[Ri1 (Gi1 – Gi0) + Gi (Ri1 – Ri0)], where the bracketed


    term represents contribution of the ith region.


    Bai, J and P Perron (1998): “Estimating and Testing Linear Models with Multiple Structural Changes”, Econometrica, Vol 66, pp 817-58.

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    places would go a long way to reduce barriers to mobility of factors of production. Moreover, wherever restrictions on transfer of ownership rights on property including land exist, they need to be relaxed for the better flow of factors of production across states.

    Finally, the state governments should consider seriously the challenge of achieving the growth targets assigned to them by the Planning Commission. An economy restricting private initiative and relying exclusively on the public sector usually does not grow rapidly. This has been the case in several states. There is a need to liberalise laws to allow private initiative particularly in those fields where private participation has not been encouraged hitherto like primary education, primary healthcare, sanitation, power supply, surface irrigation, forestry, mining, etc. The success stories of public-private partnerships implemented in d ifferent states need to be replicated soon. Similarly, the state bureaucracies need to be friendly to business and industry so as to expedite approval processes. This may require significant a dministrative reforms at the state level. Most importantly, the states need to consider seriously liberalising the land and labour m arkets by appropriately changing laws and policies. In this r egard, the experience of the forward-looking performing states

    would come in handy.

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    Panagariya, A (2004): “Growth and Reforms during 1980s and 1990s”, Economic & Political Weekly, Vol 39, No 25, pp 2581-94, June.

    Planning Commission (2007): The Eleventh Five-Year Plan (New Delhi: Government of India).

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    Wallack, J (2003): “Structural Breaks in Indian Macroeconomic Data”, Economic & Political Weekly, Vol 38, No 41, pp 4312-15, October.

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