Disparities in Agricultural Productivity Growth in Andhra Pradesh

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134 The Indian Economic Journal Volume 58(1), April-June 2010

Disparities in Agricultural ProductivityGrowth in Andhra Pradesh

A. Amarender Reddy

In the backdrop of the demand for bifurcation of Andhra Pradesh state based on growingregional disparities, the paper examines the regional disparities in agricultural productivitygrowth in Andhra Pradesh from 1956 to 2007 at district level by using Malmquist productivityindices (MI). Overall, total factor productivity (TFP) growth in agriculture and allied activitiesin Telangana is 1.3 per cent per annum, 1.1 per cent per annum in Coastal, while in

Rayalaseema TFP growth is stagnant. It indicates that, there is a convergence in TFP growthamong districts of developed Coastal and less developed Telangana regions, but districts inRayalaseema region are left out of this growth process, as this region is not able to catch upwith other two regions in agricultural productivity. Irrespective of region most backwarddistricts in agriculture, Srikakulam, Visakhapatnam, Anantapur, Kadapa, Adilabad, Nalgonda,Mahbubnagar and Nizamabad showed stagnation in TFP growth during last 50 years. With theexisting resource endowment and technology, Telangana can increase its output by 28 per centfrom the existing level, while Rayalaseema region can enhance its output by 25 per cent,Coastal region by only 14 per cent as revealed from efficiency estimates. Shadow input sharesindicate that, still gross irrigated area, fertiliser use and availability of labour are limitingfactors to increase production at district level. Inefficiency effects model (Battese and Coelli,1995) reveals that, market infrastructure and credit availability are essential to increaseefficiency. There is significant influence of base year resource endowment both physical and

human for subsequent agricultural growth.

I. Introduction

Andhra Pradesh continues to be a predominantly agricultural state with 60 per cent of

total workforce in agriculture, even though its share in gross state domestic product

(GSDP) decreased to about 22 per cent in 2007. Hence, increasing productivity of

agricultural sector is important to increase incomes of majority of population. The

unweighted average poverty ratios and monthly per capita expenditure (MPCE) for the year

2004-05 calculated from NSSO 61st Round as reported (Chaudhuri and Gupta, 2009)

indicates that the percent of poor is quite low (7.6%) in Coastal region when compared to

both Telangana (12.1%) and Rayalaseema (16.5%) regions. In the same lines, the MPCE

is quite high in Coastal (Rs.631) than Telangana (Rs.552) and Rayalaseema (Rs.524)

regions in rural areas. These differences in the poverty ratios after 50 years of planned

COMMUNICATION FOR DEBATE & RESEARCH / 2

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A. Amarender Reddy, Administrat ive Staff College of India, Hyderabad. E-mai l: [email protected]


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135Disparities in Agricultural Productivity Growth in Andhra Pradesh • A. AMARENDER REDDY

development in united Andhra Pradesh is mostly due to differences in agricultural

productivity and explain to a larger extent the reasons for ongoing agitation for separate

Telangana state. A comprehensive review of regional differences in agricultural productivity

growth in India by Kumar et al. (2008) emphasised that the district-level studies are moreuseful for policy prescription. Keeping the ongoing debate on regional disparities in Andhra

Pradesh intact, the study assess the changes in productivity and efficiency in agricultural

sector at district level with special emphasis on disparities at regional level with major

hypothesis that the productivity growth among districts and regions are not uniform.

Specific questions asked in this paper are: (i) what is the trend in total factor productivity

(TFP) growth among districts, what is the contribution of efficiency change and technical

change in TFP growth? Is there any convergence in TFP growth over the period among

districts and regions?; (ii) what is the trend in the shadow factor shares of inputs at district

and regional level, how they have changed between 1956 and 2007?; (iii) are there any

slacks in inputs at district and regional level, if yes, how much one can reduce input usewithout effecting output? And to what extent output can be increased with the exiting

resources?; and (iv) which factors influence efficiency at district level?

II. Data and Methodology

The Data Envelopment Analysis (DEA) approach is used for measuring productivity

change and efficiency. We have taken the value of crop output (Rs. crore) and value of

livestock and fisheries products (Rs. crore) as two outputs and gross irrigated area (GIA)

in 1000 ha, rainfed area in 1000 ha, labour in thousands (agricultural workers plus

cultivators), livestock population (cattle equivalents; one cattle is equal to one buffalo or

eight sheep or eight goats), fertiliser use (NPK tonnes), mechanisation (tractor equivalent;one tractor is equal to 40 iron ploughs or 80 wooden ploughs) as inputs. We have used

methodology followed in Fare et al. (1994) to estimate malmquist-type measure of

productivity and its decomposition into efficiency change and technical change. The method

assumes output orientation with constant returns to scale (CRS), as the input-oriented and

variable returns to scale (VRS) suffer from some methodological problems while analysing

regional data (Coelli and Rao, 2003).

We have used shadow price information, derived from the shape of the estimated

production surface to measure factor shares as followed by Coelli and Rao (2003) to know

the relative importance of inputs in influencing the productivity at district level, as price

information of inputs is not available for some inputs like irrigation and land. However, theDEA results are susceptible to the effects of data noise, and “unusual” shadow shares, when

degrees of freedom are limited. The paper also estimate slacks in inputs and outputs by using

efficiency measurement systems software. In order to check reliability of efficiency estimates

of DEA method, we also estimated the efficiencies by using Battese and Coelli (1995) frontier

production function approach with same input and output data (aggregated two outputs

namely crop and livestock value to make one dependent variable) with the assumption of



136 The Indian Economic Journal • Volume 58(1), April-June 2010

Cobb-Douglas production function and results are presented. Both methods gave similar

results; hence we can conclude that the DEA results are robust. We have also assessed the

effect of base year values on subsequent growth rate of different inputs and outputs to assess

whether the variables are converging over the period or not? The study used the data atconstant prices of year 2004-05 collected from Andhra Pradesh Statistical Abstracts from 1956

to 2007, every 10, year interval data points are used for DEA approach (to save

computations), while data for every year is used for Battese and Coelli (1995) model.

Districts are grouped into Coastal region (Srikakulam, Visakhapatnam (Visakhapatnam +

Vijayanagaram), East Godavari, West Godavari, Krishna, Guntur (Guntur + Prakasam),

Nellore, Rayalaseema region (Chittoor, Kadapa, Anantapur and Kurnool) and Telangana

region (Mahbubnagar, Hyderabad (Hyderabad + Ranga Reddy), Medak, Nizamabad, Adilabad,

Karimnagar, Warangal, Khammam and Nalgonda) for regional level analysis.

III. Growth Rate of Outputs and Inputs During 1956-2007

Growth in Per Capita Income

Overall, the state recorded compound annual growth rate (CAGR) of 1.76 per cent in

per capita income (PCI) from agricultural and allied sectors, with growth rate in PCI from

livestock (including fisheries) is much higher (3.17%) than PCI from crop sector (1.29%).

Nellore recorded the highest growth rate (4.25%) in agriculture, followed by Warangal

(3.64%), Karimnagar (3.02%), Medak (2.76%) and Krishna (2.71%), while the lower

growth was recorded in Nizamabad (-0.8%), Anantapur (0.31%), Visakhapatnam (0.70%),

and Mahbubnagar (0.88%). This indicates that the districts with resource endowment

showed higher growth. In case of PCI from crop sector, the highest growth was recordedin Warangal (3.33%), followed by Medak (3.28%) and Nellore (3.16%), while Anantapur

and Nizamabad recorded negative growth, some other districts like Mahbubnagar (0.41%),

Chittoor (0.77%), Hyderabad (0.45%) and West Godavari (0.90%) recorded less than 1 per

cent growth per annum. In the case of PCI from livestock sector many districts have

(Nellore, East Godavari, Chittoor and Srikakulam) recorded above 6 per cent growth per

annum, while Warangal, Krishna and West Godavari recorded about 5 per cent, Nalgonda,

Mahbubnagar, Visakhapatnam and Nizamabad districts recorded less than 2 per cent growth

per annum.

Growth in Inputs

CAGRs in credit, fertilisers, private investment in agriculture, literacy rate, farm

mechanisation, urbanisation, market infrastructure and irrigated area are positive and

significantly higher at state level with significant regional differences. Credit growth per

annum in nominal terms is about 10 per cent for Andhra Pradesh; the highest was recorded

in Hyderabad (16%), Kadapa (13%) and Nellore (13%), while less than 8 per cent were

recorded in Srikakulam, Anantapur and Nizamabad. CAGR per annum in fertiliser




consumption is much higher (7.44%) compared to other indicators, more than 8 per cent

is recorded in Warangal, Karimnagar, Khammam, Adilabad, Hyderabad, Kadapa, Nalgonda,

Mahbubnagar and Nizamabad, while less than 7 per cent recorded in Medak, Krishna,

Srikakulam and Anantapur. Growth in per cent of private investment to total investment is3.14 per cent in Andhra Pradesh, the higher growth (more than 5%) is recorded in

Mahbubnagar, Visakhapatnam, Nalgonda, East Godavari, Adilabad, West Godavari and Medak,

while less than 3 per cent was recorded in Srikakulam, Hyderabad, Krishna, Khammam and

Nellore and less than 2 per cent growth was recorded in Chittoor, Kadapa and Anantapur.

Growth rate in literacy rate is increased by 3.05 per cent in Andhra Pradesh, while more than

4 per cent growth was recorded in Karimnagar, Adilabad, Nalgonda, more than 3 per cent

recorded in Nellore, Warangal, Medak, Khammam, Srikakulam, Chittoor, Mahbubnagar,

Visakhapatnam and Nizamabad. Growth in mechanisation is 2.3 per cent in Andhra Pradesh,

with higher growth is recorded in Anantapur (3.46%), Krishna (3.52%), Khammam (3.69%),

Karimnagar (2.97%), Medak (2.39%), West Godavari (2.79%), Chittoor (2.67%) and Kadapa(2.68%). Overall growth in urbanisation is about 1.5 per cent in Andhra Pradesh, of which

Visakhapatnam (3.12%), Karimnagar (2.4%), Hyderabad (2.35%) recorded highest growth,

while Nizamabad, Mahbubnagar, Srikakulam, Kurnool, West Godavari, East Godavari, Krishna

and Warangal recorded less than 1 per cent. Number of market yards increased by just 1.27

per cent per annum in Andhra Pradesh, with higher growth recorded in Kadapa (3.71%),

Hyderabad (3.4%), Kurnool (2.46%), East Godavari (7.76%), Khammam (2.61%), Krishna

(3.78%), Medak (4.07%) and Karimnagar (2.75%), while negative growth recorded in

Nellore, Warangal, Adilabad, Guntur and Nalgonda. Overall growth rate in GIA is much

higher at 1.11 per cent per annum, with higher growth rate in Khammam (3.47%),

Karimnagar (2.81%), Adilabad (2.5%), Warangal (2.49%), Kurnool (1.7%), Nizamabad(1.48%), Nalgonda (1.49%), Mahbubnagar (1.27%), Visakhapatnam (1.26%), Guntur

(1.32%), West Godavari (1.21%) and Medak (1.48%), while the lower growth in GIA is

observed in Hyderabad (0.96%), Anantapur (0.40%), Krishna (0.37%), Nellore (0.05%),

Chittoor (-0.18%) and Srikakulam (-0.22%).

On the other hand, growth rate per annum in labour (cultivators plus agricultural

workers), livestock population in cattle equivalent and cropped area under rainfed are

significantly low. Growth in agricultural labour is 1.02 per cent per annum in Andhra

Pradesh, with the higher growth in Guntur (1.99%), Khammam (1.77%), Mahbubnagar

(1.66%) and Visakhapatnam (1.38%), while lower growth is recorded in Srikakulam (-

1.36%), Nellore (-0.12%), Chittoor (0.66%), Kadapa (0.52%), East Godavari (0.83%),Medak (0.88%), and Nizamabad (0.96%). Overall, the growth rate in cropped area under

rainfed decreased by 0.56 per cent per annum; while the growth rate is significantly lower

in Nellore (-2.83%), Karimnagar (-2.31%), Nalgonda (-1.84%), Mahbubnagar (-1.10%) and

Nizamabad (-1.22%), while there is expansion of area under rainfed only in Visakhapatnam

(1.68%) probably due to expansion of area in Vijayanagaram. Growth rate in livestock

population is just 0.25 per cent per annum, with negative growth recorded in many districts




including Chittoor, Kadapa, Srikakulam, West Godavari, East Godavari, Krishna and Nellore,

only in Guntur, Khammam and Adilabad growth rate is near about 1 per cent per annum.

The annual compound growth rate in PCI from crops is the highest in Telangana (1.7%),

followed by Coastal (1.57%) and Rayalaseema (0.86%), and while growth in PCI fromlivestock is the highest in Coastal (4.44%) followed by Rayalaseema (3.75%) and Telangana

(2.47%). Overall growth rate in PCI from agriculture and allied sectors is the highest in

Coastal (2.17%) followed by Telangana (1.93%) and Rayalaseema (1.29%). Growth in GIA

is the highest in Telangana (1.99%) followed by Coastal (0.72%) and Rayalaseema (0.58%).

Growth rate in fertiliser consumption is also the highest in Telangana (8.38%) followed by

Coastal (7.13%) and Rayalaseema (7.11%). Growth rates in urbanisation, literacy rate and

private investment in agriculture ( per cent of well-irrigated area to total GIA) are also the

highest in Telangana followed by Coastal and Rayalaseema. This indicates, in most of the

development indicators growth in Telangana is the highest, followed by Coastal and the

least in Rayalaseema. This reveals that, there is a convergence of growth in agriculturalsector between Coastal and Telanagana region, but drought prone Rayalaseema is lagging

behind in conformity with Reddy and Kumar (2006).

IV. Disparities in TFP Growth and Efficiency

Table 1 presents the district level TFP growth and its components for Telangana

districts. The highest TFP growth is recorded in Hyderabad, followed by Karimnagar,

Warangal, Khammam, Medak, Adilabad, Nalgonda, Mahbubnagar and Nizamabad. In case

of Hyderabad, the first three decades are with higher TFP growth (24 per cent during 1956-

1966, 69 per cent during 1966-1976, 50 per cent during 1976-1986) and larger share of

TFP growth is contributed by efficiency change, while in last two decades productivitygrowth is stagnant, may be due to shift of resources like land and labour to meet the

demands of urbanisation in Hyderabad. On the other hand in case of Karimnagar,

Mahbubnagar, Nalgonda, Warangal and Khammam TFP growth is higher in last three

decades, while in Adilabad, maximum TFP growth is recorded in last two decades. In most

of the districts, during 1986-1996 efficiency change contributed larger share, while during

1996-2007 technical change contributed larger share in TFP growth. Overall, there is

stagnation in TFP growth in Mahbubnagar and Nalgonda since last 50 years with decrease

in efficiency from 0.90 during 1956-1966 to 0.66 during 1996-2007 in Mahbubnagar and

from 0.77 to 0.70 in Nalgonda during the same period. In Medak, higher TFP growth is

recorded during 1966-1976 and 1986-2007, with overall TFP growth of 16 per cent perdecade coupled with significant increase in efficiency from 0.44 per cent to 0.75 per cent.

While in Warangal, TFP growth is 26 per cent per decade in last 50 years, with consistent

increase, except 1966-1976, for which TFP growth is decelerated, in line with many other

districts during 1976-1996, technical change is contributed a larger share, while during

1996-2007 the share of efficiency change (catching up) is higher in TFP growth. Only

district with deceleration in TFP growth in Telangana is Nizamabad with -3 per cent per




Table 1

Estimates of Efficiency (%) and TFP Growth Rates (%) per Decade and itsDecomposition from 1956 to 2007 in Telangana Districts

District Indicator 1956 1956-1966 1966-1976 1976-1986 1986-1996 1996-2007 1956-2007

Hyderabad Efficiency (B&C) 28 27 31 46 56 61 43

TFP growth 0 24 69 50 0 3 26

Efficiency change 0 10 80 38 0 0 22

Technical change 0 12 -6 8 0 3 3

Karimnagar Efficiency (B&C) 48 46 40 45 58 64 50

TFP growth 0 12 -21 63 68 32 26

Efficiency change 0 19 -8 25 23 30 17

Technical change 0 -6 -14 31 36 1 8

Warangal Efficiency (B&C) 35 36 38 45 57 72 49

TFP growth 0 30 -38 72 46 57 26



Khammam Efficiency (B&C) 61 64 59 58 78 87 69

TFP growth 0 14 -40 66 41 37 17


Technical change 0 -9 1 48 32 8 14

Medak Efficiency (B&C) 44 40 47 59 64 75 56

TFP growth 0 10 21 5 31 15 16

Efficiency change 0 3 42 -10 26 9 13


Adilabad Efficiency (B&C) 50 50 57 67 73 89 67

TFP growth 0 1 4 -5 20 22 8

Efficiency change 0 -2 9 -9 10 0 1


Nalgonda Efficiency (B&C) 77 76 61 64 68 70 68

TFP growth 0 12 -35 43 15 12 6

Efficiency change 0 25 -18 -1 -4 -4 -1


Mahbubnagar Efficiency (B&C) 90 80 64 63 63 66 67

TFP growth 0 -3 -40 58 18 10 4

Efficiency change 0 -4 -25 11 13 4 -1 Technical change 0 1 -19 42 4 6 5

Nizamabad Efficiency (B&C) 93 92 83 82 59 54 72

TFP growth 0 0 0 -9 24 -24 -3

Efficiency change 0 0 0 -17 -18 -30 -14

Technical change 0 0 0 10 51 8 12

Note: Efficiency (B&C) indicates the efficiency estimates from Battese and Coelli (1995) model.




decade, with significant reduction in efficiency from 0.93 per cent to 0.54 per cent during

last 50 years, however even in this district, TFP growth is 24 per cent during 1986-1996,

mostly contributed by technical change (51%) while efficiency change declined by 18 per cent.

Table 2 presents the TFP growth and its components for Rayalaseema districts. InRayalaseema region, TFP growth is decelerated in Anantapur and Kadapa, while it is

slightly higher at 8 per cent and 3 per cent per decade in Chittoor and Kurnool respectively.

In Anantapur both efficiency and technical change decelerated, while in Kadapa, there is

a significant upward movement during 1986-1996. In Kurnool, there was a significant

increase in technical change that helped in slight increase in TFP growth even though

efficiency decelerated, on the other hand in case of Chittoor efficiency change is contributed

to TFP growth.

Table 2

Estimates of Efficiency (%) and TFP Growth Rate (%) per Decade and its Decomposition from 1956 to 2007 in Rayalaseema Districts


Chittoor Efficiency (B&C) 78 87 84 81 89 85 85

TFP growth 0 45 0 0 0 0 8


Technical change 0 -23 0 0 0 0 -5

Kurnool Efficiency (B&C) 95 87 83 80 87 88 85

TFP growth 0 -33 -17 23 55 9 3

Efficiency change 0 -29 -9 3 28 -18 -7


Kadapa Efficiency (B&C) 47 45 44 48 53 61 50

TFP growth 0 -29 -38 5 56 4 -6

Efficiency change 0 -1 -23 -10 13 2 -5

Technical change 0 -28 -20 16 38 1 -1

Anantapur Efficiency (B&C) 96 89 67 66 72 68 72

TFP growth 0 -1 -8 -16 0 4 -5

Efficiency change 0 9 -2 -25 5 -1 -3

Technical change 0 -9 -7 12 -4 5 -1

Table 3 presents TFP growth in Coastal region. In Coastal, the highest TFP growth wasrecorded in Nellore followed by Krishna, Guntur, East Godavari, West Godavari, Srikakulam

and Visakhapatnam. In Nellore, TFP growth was significantly higher with 40 per cent per

decade, of which 24 per cent is contributed by efficiency change and remaining 13 per cent

contributed by technological change. In Krishna, TFP growth is about 18 per cent per

decade of which 11 per cent is contributed by technical change and 6 per cent is

contributed by efficiency change. In Guntur, TFP growth is 13 per cent per decade, all of




Table 3

TFP Estimates of Efficiency (%) and TFP Growth Rates (%) per Decadeand its Decomposition from 1956 to 2007 in Coastal Districts


Nellore Efficiency (B&C) 52 41 41 62 86 89 61

TFP growth 0 -10 15 139 58 39 40



Krishna Efficiency (B&C) 75 74 74 79 92 92 82

TFP growth 0 15 -6 27 40 17 18



Guntur Efficiency (B&C) 90 80 89 94 88 88 90

TFP growth 0 23 3 27 2 13 13 Efficiency change 0 19 -4 14 -19 -4 0


East Godavari Efficiency (B&C) 91 86 81 80 92 92 86

TFP growth 0 16 1 0 6 0 4


Technical change 0 -14 -1 0 6 0 -2

West Godavari Efficiency (B&C) 95 92 86 81 87 82 85

TFP growth 0 0 0 0 13 0 2



Srikakulam Efficiency (B&C) 61 60 60 66 80 91 71

TFP growth 0 -3 -3 -34 34 26 1

Efficiency change 0 47 1 -39 -6 16 0


Visakhapatnam Efficiency (B&C) 90 86 84 85 93 92 88

TFP growth 0 0 0 0 0 0 0



which contributed by technical change. In East Godavari, there is almost stagnant TFP

growth, with deceleration in technological change. Srikakulam, Visakhapatnam and West

Godavari showed stagnation in TFP growth, even though in Srikakulam it improved during

last two decades. Among top 10 districts in terms of TFP growth six districts are from

Telangana, three from Coastal and one from Rayalaseema. Among the top four districts

namely Nellore, Hyderabad, Karimnagar and Warangal, the contribution of efficiency change

is higher than technological change, which indicates they are catching up with other frontier

districts. Among top 10 districts in efficiency six are from Coastal (Guntur, East Godavari,

West Godavari, Krishna, Visakhapatnam and Srikakulam), three are from Rayalaseema




(Anantapur, Chittoor and Kurnool) and only two are from Telangana (Nizamabad and

Khammam). While technological change contribution is higher in Krishna, Kurnool,

Khammam and Nizamabad.

Table 4 presents the region-wise trends in TFP growth. Overall TFP growth in Telanganais about 13 per cent per decade, while the same are 11 per cent per decade in Coastal,

while TFP growth in Rayalaseema is stagnant. In Telangana and Coastal until 1976 there

is stagnation in TFP growth, then after there is a good growth, while in Rayalaseema except

1986-1996, there is stagnation in growth. In both Coastal and Telangana, most of the

growth came from technological change, which indicates technological progress ushered by

Green Revolution in major crops like paddy. In Coastal, efficiency is highest throughout the

period, while in Telangana efficiency is the lowest, it indicates that with the existing

resource endowment and technology Telangana can increase its output by more than 28 per

cent from the existing level, while Coastal region can enhance it by only 14 per cent and

Rayalaseema by 25 per cent in 2007.

Table 4

Region-wise Estimates of Efficiency (%) and TFP Growth Rate (%) per Decade

and its Decomposition from 1956 to 2007

Region Indicator 1956 1956-1966 1966-1976 1976-1986 1986-1996 1996-2007 1956-2007

Telangana Efficiency (B&C) 54 53 51 58 64 70 59

Efficiency (DEA) -48 -40 -42 -37 -33 -28 -38

TFP growth 0 10 -15 34 28 16 13



Coastal Efficiency (B&C) -22 -27 -30 -23 -11 -10 -20

Efficiency (DEA) -32 -21 -19 -15 -17 -14 -20

TFP growth 0 5 1 14 20 13 11



Rayalaseema Efficiency (B&C) -24 -26 -33 -32 -27 -25 -28

Efficiency (DEA) -23 -15 -23 -29 -22 -25 -23

TFP growth 100 91 83 102 125 104 100

Efficiency change 0 10 -9 -9 11 -4 -1

Technical change 0 -17 -9 12 12 9 1Total Efficiency (B&C) -35 -37 -40 -34 -26 -23 -32

Efficiency (DEA) 62 71 69 72 74 77 71

TFP growth 0 4 -10 20 24 12 10



Note: Efficiency (B&C) indicates the efficiency estimates from Battese and Coelli (1995) model and Efficiency (DEA) from Data Envel-

opment Analysis model.




V. Changes in Factor Shares Differ Over Time and Space

Factor shares are virtual inputs and outputs, where the actual quantity is multiplied by

shadow price. Shadow price represents the scarcity value imposed by DEA on each input,

in the case of output; shadow share represents relative importance of each output inmaximising aggregate output value. These shadow shares also reflect either general factor

endowments or scarcity value (marginal productivity multiplied by input quantity) of inputs

at district level. Table 5 presents our estimated shadow shares obtained from the DEA. The

last two series in Table 5 represent the shadow shares for crops and livestock (both sum

to unity) over the study period. The change in shares appear to be quite reasonable as crops

accounted for 65 per cent of the total output in 1956 and its share reduced to 59 per cent

in 2007. The first six series in the table represent the shadow input shares. Shadow share

of irrigated land is much higher, even though it decreased from 59 per cent to 43 per cent,

which indicates that the scarcity of irrigated land in Andhra Pradesh and its importance in

increasing production. The shares of fertilisers increased from 11 per cent to 27 per cent,which indicates the increasing use of fertiliser in Andhra Pradesh over the period. The share

of cropped area under rainfed, aggregated over all the districts, seems to be quite stable

around 13 to 14 per cent. The labour share shows a steady increase from 1 per cent in

1956 to 9 per cent in 2007 and the share of livestock increased from 1 per cent to 5 per

cent, which indicates that slowly scarcity value of labour and livestock increased over the

study period in the labour and livestock abundant agrarian economy. While the share of

tractor (equivalent of farm equipment) decreased from 15 per cent to 3 per cent, however,

we have to note that this variable included tractor equivalent of tractors, wooden and iron

plough, hence it also reflect outdated farm machinery.

Table 6 shows the district-specific average output and input shadow shares for 1986-2007

underlying the TFP indices reported here. These shares are averaged over the last three

decades of the study period 1986 to 2007. These figures indicate that, in the total output of

agriculture and allied sector, share of crop output is 53 per cent, while share of livestock

(including fisheries) products is 46 per cent. The shadow share of GIA is highest with 45

per cent, followed by labour (26%), rainfed land (13%), livestock population (10%) and farm

implements and fertiliser (3 per cent each), which shows the importance of irrigation, labour,

rainfed area and livestock population in agrarian economy in Andhra Pradesh. Share of

irrigated land is much higher in the districts with scarce irrigation facilities (with higher

marginal productivity) in Adilabad (0.94), Anantapur (0.89), Chittoor (0.66), Kurnool (0.69),

Mahbubnagar (0.57), Hyderabad (0.57) and Kadapa (0.56). The shadow shares of labour are

quite high in districts with labour intensive agriculture with paddy as main crop without

much mechanisation like Nellore, (0.70), Nalgonda (0.62), Khammam (0.64), Srikakulam

(0.71), Warangal (0.57), Medak (0.46), Kadapa (0.38), Nizamabad (0.30) and Mahbubnagar

(0.38). In districts where land is a limiting factor due to urbanisation, its shadow share is

quite high. For example, in the Hyderabad, Krishna and Guntur the land share is 0.37, 0.44




Table 5

Factor Shares (Ratios) Estimated from DEA in 2007

District Labour Livestock Rainfed GIA Fertiliser Mechanisation Crop Livestock Population Area Value Value

Hyderabad 0 0 0 0.86 0 0.14 0 1(0) (0) (.09) (.91) (0) (0) (.51) (.49)

Karimnagar 0 0 0.45 0 0.55 0 1 0(0.19) (0) (0) (.81) (0) (0) (0.54) (.46)

Warangal 0 0 0.43 0.57 0 0 1 0(0) (0) (.05) (0.95) (0) (0) (.77) (.23)

Khammam 0 0 0.33 0.67 0 0 1 0(0) (0) (0) (0.91) (0.09) (0) (0.58) (0.42)

Medak 0.17 0 0 0.42 0.38 0.04 0 1(0) (0) (0) (1) (0) (0) (.25) (.75)

Adilabad 0 0 0 0.88 0 0.12 1 0(0) (0) (0) (0.85) (0.15) (0) (0.56) (0.44)

Nalgonda 0.22 0 0 0.2 0.58 0 0.22 0.78(0) (0) (0) (.92) (.08) (0) (.48) (.52)

Mahbubnagar 0.14 0 0 0.52 0.25 0.08 0.35 0.65(0) (0) (0) (.9) (0.1) (0) (.6) (.4)

Nizamabad 0 0 0.4 0.6 0 0 1 0(0) (0) (.37) (0) (.63) (0) (.94) (0.06)

Chittoor 0 0 0.12 0.64 0.24 0 0.42 0.58(0) (0) (0.01) (0.99) (0) (0) (1) (0)

Kurnool 0 0.31 0 0.69 0 0 0.69 0.31(0) (0) (0) (1) (0) (0) (.8) (.2)

Kadapa 0.05 0.05 0 0 0.9 0 1 0

(0) (0) (0) (0) (1) (0) (0.41) (0.59)

Anantapur 0 0.12 0 0.03 0.84 0 1 0(0) (0) (0) (0.89) (0) (0.11) (1) (0)

Nellore 0.48 0 0 0.52 0 0 0 1(0) (0) (0) (0) (0.07) (0.93) (0.61) (.39)

Krishna 0.3 0.03 0 0.67 0 0 0.37 0.63(0) (0) (0) (0) (0) (1) (0.63) (0.37)

Guntur 0 0.21 0 0.79 0 0 0.61 0.39(0) (0.12) (0) (.88) (0) (0) (.57) (.43)

East Godavari 0 0.29 0 0 0.71 0.01 1 0(0) (0.1) (0) (0) (0) (0.9) (1) (0)

West Godavari 0 0 1 0 0 0 0.36 0.64

(0) (0) (1) (0) (0) (0) (.84) (.16)Srikakulam 0.44 0 0 0.56 0 0 0.56 0.44

(0) (0) (0.67) (.33) (0) (0) (1) (0)

Visakhapatnam 0 0 0 0 0.86 0.14 0.14 0.86(0) (0) (0.5) (0.4) (.09) (0) (0) (1)

State 0.09 0.05 0.14 0.43 0.27 0.03 0.59 0.41(0.01) (.01) (.13) (.59) (.11) (.15) (.65) (.35)

Note: Figures in Parenthesis are for year 1956.




and 0.49 per cent respectively. In districts where land is a limiting factor due to urbanisation,

its shadow share is quite high. For example, in the Hyderabad share of land is 0.37. The

shadow share of land is also higher in West Godavari (0.67) and East Godavari (0.26),

Karimnagar (0.52), Chittoor (0.26) and Nizamabad (0.26) indicating higher land productivityin these districts. Shares of other factors, including livestock and fertiliser are also plausible

and appear to support the general scarcities of these resources in different districts. However,

in some districts the shadow share estimates are unusually high or low due to the

dimensionality problem in DEA or the district factor endowment may be significantly differ

from sample average, because of district-specific factors, such as land scarcity, labour

abundance, etc. For many districts, the errors in estimation of shadow prices may be a

combination of these two factors, to varying degrees.

Table 6

Average Factor Shares (Ratios) for Last Three Decades (1986-2007) Estimated from DEA

District Labour Live- Rainfed GIA Fertiliser Mechanisation Crop Livestock stock Area Value Value

Hyderabad 0.05 0.00 0.37 0.57 0.00 0.00 0.00 1.00

Nellore 0.70 0.00 0.00 0.30 0.00 0.00 0.00 1.00

West Godavari 0.00 0.33 0.67 0.00 0.00 0.00 0.00 1.00

Nalgonda 0.62 0.00 0.00 0.32 0.06 0.00 0.19 0.81

Mahbubnagar 0.38 0.00 0.00 0.57 0.05 0.00 0.20 0.80

Krishna 0.16 0.44 0.00 0.40 0.00 0.00 0.32 0.68

Medak 0.46 0.00 0.00 0.42 0.12 0.00 0.37 0.63

Khammam 0.64 0.00 0.00 0.36 0.00 0.00 0.47 0.53

Guntur 0.00 0.49 0.00 0.51 0.00 0.00 0.53 0.47East Godavari 0.00 0.64 0.26 0.10 0.00 0.00 0.58 0.42

Srikakulam 0.71 0.00 0.00 0.29 0.00 0.00 0.60 0.40

Visakhapatnam 0.00 0.00 0.12 0.51 0.09 0.28 0.62 0.38

Karimnagar 0.06 0.00 0.52 0.23 0.19 0.00 0.65 0.35

Warangal 0.57 0.00 0.16 0.26 0.00 0.00 0.76 0.24

Chittoor 0.05 0.01 0.26 0.66 0.02 0.00 0.77 0.23

Nizamabad 0.30 0.00 0.26 0.44 0.00 0.00 0.85 0.15

Adilabad 0.00 0.00 0.01 0.94 0.00 0.05 0.87 0.13

Anantapur 0.01 0.09 0.00 0.89 0.01 0.00 0.92 0.08

Kadapa 0.38 0.00 0.00 0.56 0.00 0.06 0.94 0.06

Kurnool 0.12 0.07 0.00 0.74 0.00 0.07 0.98 0.02

State 0.261 0.104 0.132 0.453 0.028 0.023 0.531 0.469

Table 7 presents actual input use and outputs for the year 1956, within parenthesis we

presented slack in variables (in%) in that year. The table also presents for inefficient districts,

the benchmarks considered while measuring slacks and for efficient districts, number of times

acted as benchmark while estimating slacks for inefficient districts. In the year 1956,

Nizamabad, Kurnool, West Godavari and Visakhapatnam are efficient districts, with

Nizamabad acted 14 times as benchmark for other districts, while Visakhapatnam 12 times,

Kurnool 11 times and West Godavari 4 times. Overall slack in crop output is zero, while




livestock output is 12.5 per cent. This indicates that with the existing resources, livestock

output could have been increased by 12.5 per cent in the base year 1956 in Andhra Pradesh.

In case of inputs, highest slack is observed in rainfed area (35%), followed by fertiliser

(24.9%), livestock population (22.8%), labour (14.7%), mechanisation (14.2%) and least incase of GIA (6.1%). This indicates that, without affecting the output, one could have reduced

the use of rainfed area by 35 per cent, fertiliser by 25 per cent, livestock population by 23

per cent, labour use by 15 per cent, farm machinery by 14 per cent and GIA by 6 per cent

in the base year. In case of rainfed area slacks are highest in Kadapa (74%) followed by

Nalgonda (64%), Anantapur (63%), Guntur (59%), Nellore (56%) and Adilabad (52%). In

case of fertiliser slacks are highest in Guntur (58%), Anantapur (58%) and Chittoor (62%),

which indicates overuse of fertilisers in Guntur, Anantapur and Chittoor in as early as 1956.

Slack in livestock population is higher in Kadapa (60%), Adilabad (57%), Khammam (44%),

Nalgonda (38%), Chittoor (38%) and Nellore (35%).

Table 8 presents slack variables in the model for the year 2007. In the year 2007,Hyderabad, Adilabad, Chittoor, West Godavari, East Godavari and Visakhapatnam are

efficient districts, with East Godavari acted 12 times as benchmark for other districts, West

Godavari and Adilabad acted 8 times each, while Hyderabad 6 times, Visakhapatnam 5

times and Chittoor 3 times. Overall, slack in crop output is 1.4 per cent, while livestock

output is 10.2 per cent. This indicates that with the existing resources livestock output

could have been increased by 10.2 per cent and crop output could have been increased by

1.4 per cent in the year 2007. In case of inputs, highest slack is observed in livestock

population (23%), followed by farm machinery (23%), rainfed area (21%), labour (7.2%),

fertiliser (5.3%) and least in case of GIA (1.7%). Which indicates that without affecting

the output, one could have reduced the use of livestock population by 23 per cent, farmmachinery by 23 per cent, rainfed area by 21 per cent, labour by 7.2 per cent, fertiliser by

5.3 per cent and GIA by 1.7 per cent. In case of livestock population slacks are highest in

Karimnagar (61%), Warangal (60%), Nellore (58%), Srikakulam (55%), Nizamabad (50%)

and Nalgonda (51%). In case of farm machinery slack is highest in Khammam (57%),

Karimnagar (50%), Anantapur (48%), Nellore (48%), Kadapa (43%), Nalgonda (40%) and

Warangal (36%). In case of rainfed area the highest slack is in Anantapur (55%) followed

by Krishna (41%), Kurnool (40%), Nellore (35%) and Srikakulam (33%). The highest slack

in labour is reported in Guntur (24%) followed by Khammam (19%), Karimnagar (16.5%)

and Anantapur (14%). The highest slack in fertiliser use is recorded in Kurnool (24%)

followed by Nizamabad (16%), Guntur (11.5%) and Srikakulam (11.3%). Table 9 presents region-wise factor shares and slack variables. Factor shares are much

higher for GIA and fertiliser in both Telangana and Rayalaseema, while in Coastal in

addition to irrigation and fertilisers, mechanisation and cropped area under rainfed are also

having higher factor shares in 1956. While in 2007, factor shares of irrigated area reduced

except Coastal, shares for fertiliser and cropped area under rainfed increased, while in

Rayalaseema factor shares for fertiliser and livestock increased at the cost of irrigated area.




Table 7

Value of Inputs and Output (Slack in Variables as % of Actual in Parenthesis) in 1956

S. District Bench Labour Livestock Rainfed GIA Fertiliser Mecha- Crop Livestock No. mark (1000) (1000) Area (1000 ha) (1000 t) nisation Value Valuedistricts/* (1000 ha) (tractors) (Rs. (Rs.

crore) crore)

1 Hyderabad 20, 11, 9 335 441 306 49 3 1133 75 53(16.9) (24.7) (0.0) (0.0) (15.1) (10.7) (0.0) (0.0)

2 Karimnagar 20, 11, 9 543 751 407 132 5 2267 178 96(0.0) (22.2) (27.5) (0.0) (37.5) (10.3) (0.0) (0.0)

3 Warangal 20, 11, 9 526 716 360 123 3 2469 170 38(10.7) (26.0) (0.0) (0.0) (19.1) (26.1) (0.0) (0.0)

4 Khammam 20, 11, 9 323 485 297 54 2 1247 187 88(25.9) (44.3) (37.0) (0.0) (0.0) (28.1) (0.0) (0.0)

5 Medak 20, 11 544 577 375 98 4 2020 141 177

(18.2) (19.2) (49.0) (0.0) (26.5) (20.3) (0.0) (0.0)

6 Adilabad 20, 11, 9 359 511 487 29 2 1619 134 69(51.2) (57.3) (51.7) (0.0) (0.0) (60.5) (0.0) (0.0)

7 Nalgonda 20, 11, 9 570 862 666 121 3 3065 248 174(10.8) (37.6) (64.0) (0.0) (0.0) (38.6) (0.0) (0.0)

8 Mahbubnagar 20, 11, 9 497 799 918 103 3 2554 326 145(1.4) (28.6) (49.0) (0.0) (0.0) (28.5) (0.0) (0.0)

9 Nizamabad (14) 395 420 176 127 1 1593 819 110

10 Chittoor 11, 9 727 952 263 177 5 2765 603 50(23.3) (37.6) (0.0) (0.0) (61.9) (18.9) (0.0) (118.2)

11 Kurnool (11) 572 801 1179 63 6 2084 474 104

12 Kadapa 20, 9 472 569 346 119 1 1322 303 53

(54.7) (60.3) (73.5) (43.8) (0.0) (35.5) (0.0) (0.0)13 Anantapur 11, 9 608 730 991 126 6 1800 754 60

(24.9) (29.0) (63.3) (0.0) (58.1) (0.0) (0.0) (85.8)

14 Nellore 20, 9, 18 639 1058 426 312 6 2292 249 71(1.1) (35.4) (56.0) (17.0) (0.0) (0.0) (0.0) (0.0)

15 Krishna 20, 18 573 712 131 337 11 1615 547 124(17.8) (26.0) (17.7) (26.6) (40.1) (0.0) (0.0) (0.0)

16 Guntur 20, 11, 9 896 852 789 213 10 3173 740 375(9.0) (0.0) (58.9) (0.0) (57.8) (2.9) (0.0) (0.0)

17 East Godavari 9, 18 711 757 251 289 6 2640 994 64(2.2) (0.0) (0.0) (0.4) (12.8) (0.0) (0.0) (179.9)

18 West Godavari (4) 600 679 134 338 9 2045 1075 190

19 Srikakulam 9, 18 1013 819 260 226 6 2879 865 46(37.7) (17.4) (0.0) (0.0) (42.2) (13.6) (0.0) (242.0)

20 Visakhapatnam (12) 740 751 206 170 4 2673 445 618

State 11643 14242 8968 3206 96 43255 9325 2705(14.7) (22.8) (35.0) (6.1) (24.9) (14.2) (0.0) (12.5)

Note: *for efficient districts number of times acted as benchmark are reported in parenthesis.




Table 8

Value of Inputs and Output (Slack in Variables as % of Actual in Parenthesis) in 2007

S. District Bench- Labour Livestock Rainfed GIA Fertiliser Mecha- Crop Livestock No. mark (1000) Population Area (1000 ha) (1000 t) nisation Value Valuedistricts/* (1000) (1000 ha) (tractors) (Rs. (Rs.

crore) crore)

1 Hyderabad (6) 589 530 196 76 100 3124 513 974

2 Karimnagar 17, 18 985 980 154 513 137 9124 2066 723(16.5) (61.3) (0.0) (18.3) (0.0) (49.8) (0.0) (109.3)

3 Warangal 17, 18 951 962 197 394 123 6613 2298 578(13.4) (60.2) (0.0) (0.0) (1.9) (35.6) (0.0) (140.0)

4 Khammam 6, 17 815 922 265 244 86 7126 2102 675(18.8) (46.3) (0.0) (0.0) (2.4) (57.0) (0.0) (20.7)

5 Medak 1, 20, 853 763 321 200 60 5675 1285 96710, 18 (0.0) (21.0) (26.4) (0.0) (0.0) (0.0) (15.4) (0.0)

6 Adilabad (8) 613 868 445 89 64 2354 2071 339

7 Nalgonda 20, 10, 968 1102 265 388 122 9417 1456 86617, 18 (0.0) (51.3) (15.8) (0.0) (0.0) (40.4) (0.0) (0.0)

8 Mahbubnagar 1, 20, 6, 1146 1249 542 257 88 6145 1413 79410, 17 (0.0) (29.8) (28.4) (0.0) (0.0) (0.0) (0.0) (0.0)

9 Nizamabad 17, 18 646 548 129 286 107 3745 1099 397(9.5) (50.6) (0.0) (0.0) (16.3) (17.2) (0.0) (98.6)

10 Chittoor (3) 1018 741 261 187 63 10640 1897 1111

11 Kurnool 1, 6, 17 1069 895 767 253 148 5349 2218 751(14.4) (0.0) (40.2) (0.0) (23.8) (24.3) (0.0) (0.0)

12 Kadapa 20, 6, 17 615 571 306 166 57 4479 1068 324(0.0) (0.0) (6.1) (6.9) (0.0) (43.0) (0.0) (29.0)

13 Anantapur 20, 6, 17 1063 945 1024 164 66 6809 1675 526(14.3) (0.0) (54.9) (0.0) (0.0) (48.4) (0.0) (8.3)

14 Nellore 1, 18 601 772 115 296 132 7170 983 1201(0.0) (58.1) (35.4) (0.0) (7.0) (47.8) (38.9) (0.0)

15 Krishna 1, 6, 17, 18 1002 592 298 440 209 7415 2572 2276(0.0) (0.0) (41.0) (0.0) (8.4) (19.8) (0.0) (0.0)

16 Guntur 1, 6, 17 2549 1408 778 662 301 10872 5056 2373(23.6) (0.0) (9.5) (0.0) (11.5) (13.6) (0.0) (0.0)

17 East Godavari (12) 1087 508 287 503 148 5405 4465 2003

18 West Godavari (8) 1082 489 79 628 230 6990 3581 3182

19 Srikakulam 6, 17, 18 500 786 257 203 81 3446 1236 573(0.0) (54.8) (33.2) (0.0) (11.3) (27.6) (0.0) (0.0)

20 Visakhapatnam (5) 1511 1118 503 310 70 5837 2405 1497

State 19663 16749 7189 6259 2392 127735 41461 22130(7.2) (23.0) (20.8) 9(1.7) (5.3) (22.9) (1.4) (10.2)

Note: *for efficient districts number of times acted as benchmark are reported in parenthesis.




Output shares of crops are much higher in 1956 with 0.80 per cent in Rayalaseema, 0.66

per cent in Coastal and 0.58 per cent in Telangana, while the share is reduced in Coastal

to 0.43 per cent in 2007, while in Rayalaseema a slight decreased to 0.78 has been

reported, while in Telangana slight increase to 0.62 has been reported.

Table 9

Region-wise Factor Shares (Ratios) and Slack in Variables as % of Actual Input and Outputs Estimated from DEA in 1956 and 2007

Region/year Labour Livestock Rainfed GIA Fertiliser Mecha- Crop Livestock Population Area nisation Value Value

Factor share

1956

Telangana 0.021 0.000 0.057 0.806 0.117 0.000 0.581 0.419Coastal 0.000 0.031 0.310 0.230 0.023 0.404 0.664 0.336

Rayalaseema 0.000 0.000 0.003 0.720 0.250 0.028 0.803 0.198

2007

Telangana 0.059 0.000 0.179 0.524 0.196 0.042 0.619 0.381

Coastal 0.174 0.076 0.143 0.363 0.224 0.021 0.434 0.566

Rayalaseema 0.013 0.120 0.030 0.340 0.495 0.000 0.778 0.223

Slack as % of actual

1956

Telangana 13.4 29.4 38.4 0.0 15.4 25.9 0.0 0.0

Coastal 11.4 12.5 33.1 7.6 25.0 2.8 0.0 15.3

Rayalaseema 24.3 29.9 31.7 10.7 38.9 12.4 0.0 41.6

2007

Telangana 6.7 37.6 11.2 3.8 2.5 28.9 1.4 33.7

Coastal 7.2 15.5 13.9 0.0 6.1 15.5 1.9 0.0

Rayalaseema 8.2 0.0 37.7 1.4 10.5 23.9 0.0 5.1

VI. Factors Influencing Technology and Efficiency

In addition to the DEA, to estimate robustness of efficiency estimates, we have used

frontier production function Battese and Coelli (1995) model. It also shed light on which

inputs have major contribution in district frontier production function (best practice

technology) and also to know the factors which influence the efficiency of districts asexplained in methodology section.

Table 10 presents the results of Battese and Coelli (1995) frontier production function

model results. Both dependent and independent variables are in logged form; hence it

assumes cobb-douglas production function and the coefficients represent elasticities of

respective independent variables. The dependent variable is “logged value of agricultural

production”, while independent variables are rainfed area (1000 ha), gross irrigated area




(1000 ha), labour (cultivators plus agricultural labourer in thousands), livestock (cattle

equivalents in thousands), fertiliser consumption (tonnes) and mechanisation (tractor

equivalent). Only GIA and labour variables are having positive elasticities, while all other

variables are having negative elasticities (which are in line with the findings of significantslacks, except GIA and labour). Time variable is having significant positive coefficient,

indicating there is a positive technological progress. Among explanatory variables in

inefficiency effects, number of market yards, agricultural credit, and Rayalaseema regional

dummy are positively associated with efficiency (negatively associated with inefficiency); all

other variables are having negative association with efficiency. As in line with efficiency

estimates, Telangana region is having positive and significant association with inefficiency

(hence negative association with efficiency).

Table 10

Battese and Coelli (1995) Model Results for Period 1956-2007

Dependent variable: value of agricultural production (Rs. crore) Coefficient t-ratio Mean

Constant 4.115* 16.0 1551.6

Log (agricultural labour (1000)) 1.442* 32.6 782.6

Log (livestock population (cattle equivalent 1000 nos.)) -0.949* -19.3 787.6

Log (rainfed area (1000 ha)) -0.164* -7.4 409.8

Log (gross irrigated area (1000 ha)) 0.143* 4.0 229.4

Log (fertiliser (tonnes)) -0.062* -3.3 47.6

Log (mechanisation (tractor equivalent)) -0.016 -0.5 3967.6

Time (year) 0.023* 18.2 26.5

Returns to scale 0.417Inefficiency effects

Constant 0.964 1.7

Log (market yards (number of market yards) -0.052* -2.0 65.7

Log (credit (Rs. crore) -0.222* -11.8 1750.8

Urbanisation (%) 0.002* 3.4 24.1

Literacy (%) 0.004 1.7 33.1

Private investment to total investment (%) 0.011* 8.9 30.9

Log (annual rainfall (mm) 0.050 0.6 922.8

Telangana region dummy 0.124* 2.0 0.5

Rayalaseema region dummy -0.274* -3.6 0.2

Sigma-Squared 0.088 13.5

Gamma 0.838 23.1

Log likelihood function = 46.2

LR test of the one-sided error = 408.4

Number of cross-sections = 20

Number of time periods = 52

Total number of observations = 1040

Note: * Indicates significant at 5% level of significance




VII. Base Year Effect on Subsequent Agricultural Growth

Table 11 presents the results of growth in per capita income (PCI) from agriculture and

allied activities as dependent variable and value of various other variables in base year

(1956) as explanatory variables. Labour and per capita income from agriculture in initialyear is having negative and significant influence on growth in per capita income, while

urbanisation in initial year is having negative but insignificant association. The fertiliser

consumption, irrigated land, and literacy rate in the base year are having positive influence

on growth in PCI from agriculture and allied activities at district level. Hence one can

conclude that, resource endowment (both physical and human) in initial years is having

positive influence on subsequent growth in per capita income.

Table 11

Effect of Base Year Resource Endowment on Subsequent Growth

of PCI from Agriculture During 1956-2007

Dependent variable: per cent growth (1956-2007)in per capita income from agriculture

Constant 9.236 (0.9)

Base year PCI from agriculture -1.386* (-4.0)

Base year agricultural labour (1000) -1.654* (-2.1)

Base year GIA (1000 ha) 0.455 (1.3)

Base year fertiliser (1000 tonnes) use 0.868* (2.7)

Base year Literacy (%) 0.189 (0.6)

Base year Urbanisation (%) -0.608 (-1.4)

Annual rainfall (mm) 1.84 (1.7)

R2 0.74

Note: Figures in parenthesis are t-values; all values of base year variables are in logged form except, variables measured in per cent.

* Indicates significant at 5% level of significance

VIII. Conclusion

The paper examines productivity growth since formation of united Andhra Pradesh in

1956 at district level by using Malmquist productivity indices. Overall, TFP growth in

agriculture and allied activities in Telangana is about 1.3 per cent per annum, the same are

1.1 per cent per annum in Coastal, while TFP growth in Rayalaseema is stagnant. It

indicates that, there is a convergence in TFP growth among districts of developed Coastal

and less developed Telangana regions, but districts in Rayalaseema region are left out of

this growth process, as Rayalaseema region is not able to catch up with other two regions

in agricultural productivity. Another important finding is that irrespective of region most

backward districts in agriculture, that is Srikakulam, Visakhapatnam, Anantapur, Kadapa,

Adilabad, Nalgonda, Mahbubnagar and Nizamabad showed stagnation in TFP growth during




last 50 years. With the existing resource endowment and technology, Telangana can increase

its output by more than 28 per cent from the existing level, while Rayalaseema region can

enhance its output by 25 per cent, Coastal region by only 14 per cent as revealed from

efficiency estimates. Shadow input shares indicate that, still gross irrigated area, fertiliseruse and availability of labour are three important inputs, which limits the district

production frontier. Inefficiency effects model (Battese and Coelli, 1995) reveals that,

market infrastructure and credit availability are two important variables in increasing

efficiency. Study results also emphasis importance of resource endowment (physical and

human) in base year for subsequent growth.

References

Battese, G.E. and T.J. Coelli (1995). “A Model for Technical Inefficiency Effects in a Stochastic Frontier Production

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Appendix

Table A1

Region-wise Value of Explanatory Variables for Technical Inefficiency in the Model (B&C 1995) in 1956 and 2007

Region Year Markets Credit Urbanisation Literacy Private Rain(nos.) (Rs. crore) (%) (%) Investment(%) (mm)

Telangana 2007 619 48447 25.2 46.0 71.7 1084.61956 369 505 14.3 6.3 9.4 804.5

Coastal 2007 728 48701 34.5 53.9 22.6 1293.0

1956 420 1042 16.4 10.7 2.3 814.5

Rayalaseema 2007 379 13408 24.9 51.1 68.6 716.6

1956 125 277 14.2 9.8 28.9 682.0

Disparities in Agricultural Productivity Growth in Andhra Pradesh

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