The World’s Largest Open Access Agricultural & Applied Economics Digital Library

This document is discoverable and free to researchers across the

globe due to the work of AgEcon Search.

Help ensure our sustainability.

Give to AgEcon Search

AgEcon Search
http://ageconsearch.umn.edu
aesearch@umn.edu

Papers downloaded from AgEcon Search may be used for non-commercial purposes and personal study only.
No other use, including posting to another Internet site, is permitted without permission from the copyright
owner (not AgEcon Search), or as allowed under the provisions of Fair Use, U.S. Copyright Act, Title 17 U.S.C.

No endorsement of AgEcon Search or its fundraising activities by the author(s) of the following work or their
employer(s) is intended or implied.
Agricultural Economics Research Review 2018, 31 (1), 113-122
DOI: 10.5958/0974-0279.2018.00011.3

Changing land-use pattern in India: has there been

an expansion of fallow lands?

Ghanshyam Pandeya* and Thiagu Ranganathanb

a
Institute of Economic Growth, University of Delhi, New Delhi-110007, India
b
Indian Institute of Management Nagpur, Nagpur-440010, Maharashtra, India

Abstract This paper examines dynamics of land-use pattern in India with a focus on fallow lands. We
find significant changes in the land-use pattern, and a continuous expansion of fallow lands in spite of
increasing demand for land for agricultural and non-agricultural purposes. The fallow lands are distributed
across the country but have a greater concentration in the states of Bihar, Andhra Pradesh, Rajasthan, and
Karnataka. These changes in the temporal and spatial distribution of fallow lands are due to increasing
variability in the precipitation and irrigation water, and low level of mechanization. If these lands can be
brought under cultivation would enhance agricultural production and food security of the poor and marginal
farmers.

Keywords Land use, Fallow land, Rainfall, Mechanization

JEL classification Q24, O13, Q53, R33

1 Introduction around 21% of the geographical area was occupied by

forests, 8% was utilized for non-agricultural purposes,
Land is the basic resource for agriculture, a primary
5% was barren and unculturable and 7.5% remained
source of livelihood for majority of India’s rural
fallow (GoI, 2015). The average of land holding is just
population. Its allocation to different economic and
1.1 hectares and it has been declining continuously
non-economic activities depends on the population
causing concerns for food and livelihood security of
pressure of both human and livestock, changes in
demand for food, feed and fibres, technological changes millions of smallholder farmers. As the supply of land
and pace of economic development that requires land is fixed, the pathway to increase agricultural production
for non-agricultural purposes and intensifies and improve farmers’ livelihood is to improve
competition for land. However, the rapid population productivity and efficiency of land in a sustainable
growth accompanied by expansion of industrial manner.
activities have been aggravating resource depletion and There have been a few studies in India that have
environmental degradation (Jodha 1989; Harte 2007) examined the issues related to fallow lands. These find
and alter the land use pattern (Palchoudhuri et al. 2015). that irrigation (Giri 1966; Nadkarni & Deshpande 1979;
India has geographical area of 328.7 million hectares, Ramasamy et al. 2005; Bardhan & Tewari 2010), use
of which around 42% is currently used for cultivation of fertilizers (Giri 1966), monsoon rainfall (Nadkarni
of various food and non-food crops. This proportion is & Deshpande 1979; Ramasamy et al. 2005) and size
one of the highest in the world, but due to excessive of operational holdings (Nadkarni & Deshpande 1979;
population pressure the per capita availability of arable Ramasamy et al. 2005; Bardhan & Tewari 2010) are
land is much less than the world average. In 2010-11, some of the factors that determine the extent of fallow
lands. Ramasamy et al. (2005) also identify
*Corresponding author: ghanshyampndy@yahoo.com infrastructure and institutional factors, such as road
114 Pandey G, Ranganathan T

density and access to institutional finance as important the entire time period into six sub periods following
determinants of the extent of fallow lands. A few Rada (2016): (i) pre-green revolution period from
household level studies (Ranganathan & Pandey 2017; 1950–1968, (ii) initial green revolution period from
Ranganathan & Pandey 2018) have also identified 1968–1975, (iii) period of wider technology
tenancy, irrigation, mechanization, livestock holdings, discrimination from 1975–1988 (iv) period of
non-farm income opportunities, and distance from agricultural diversification from 1988–1995 (v) post-
nearest town as important factors in farmers’ decision economic reforms period from 1995–2004, and (vi)
to leave the land fallow. the period of agricultural growth recovery from 2004–
2012.
This paper addresses this important question: why there
is an increase in fallow lands despite the fixed supply 2.2 Methods
of land, declining size of land and increasing demand
for land for non-agricultural uses? We examine this 2.2.1 Assessment of shifts in land use
issue by analyzing changes in types of land or inter- Land-use in India is classified into nine broad
sectoral shifts in land- uses and factors responsible for categories. These are represented by the following
land being kept fallow by the farmers. In the following equation.
section, we discuss data and methodological approach
that we employed in this paper. Section 3 discusses R= Fr+ P+M+N+U+W+Fe+Fo+C …(1)
the results. Concluding remarks are made in the final where, R represents the reporting area, Fr the forest area,
section. P the area under permanent pastures, M the area under
miscellaneous tree crops, N the area put to non-
2. Data and methodology agricultural uses, U the barren and unculturable land,
W the culturable waste land, Fe the current fallow land,
2.1 Data Fo the fallow land other than current, and C the net
The analysis of land-use in this paper is based on sown area.
secondary data compiled from various published Differentiating R with respect to time, we get
sources. The data on land uses were taken from
Directorate of Economics and Statistics (DES), ∆R= ∆Fr+ ∆P + ∆M + ∆U + ∆N + ∆W + ∆Fe+ ∆Fo+
Ministry of Agriculture and Farmers Welfare, ∆C …(2)
Government of India. The use of NPK were taken from The terms in Eq. (2) can be rearranged to reflect the
indiastat.com. The data related to sale of tractors and desirable and un-desirable changes in the land use as:
institutional credit outstanding were collected from
publications of the Indian Agricultural Statistics ∆R = ∆E + ∆N + ∆A …(3)
Research Institute and Reserve Bank of India where, ∆E is the net change in ecological sector and
respectively; and the data on rainfall were sourced from equals to ∆Fr+ ∆P + ∆M; ∆N is the net change in non-
the Indian Metrological Department, Government of agricultural use, and ∆A is the net change in agricultural
India. sector and equals to ∆W+ ∆Fe + ∆C.
We analyze changes in land-use pattern in 17 major ∆E can be further be further written as: ∆E1 + ∆E2,
states for the period 1984-85 to 2011-12. These states where, ∆E1 = ∆Fr+ ∆P + ∆M; and ∆E2= ∆U.
are: Andhra Pradesh, Assam, Bihar (including
Jharkhand), Gujarat, Haryana, Himachal Pradesh, ∆E1 is the change in the desirable ecological sector,
Jammu &Kashmir, Karnataka, Kerala, Madhya Pradesh and ∆E2 is the change in the undesirable ecological
(including Chhattisgarh), Maharashtra, Odisha, Punjab, sector.
Rajasthan, Tamil Nadu, Uttar Pradesh (including To examine the intra-sectoral and inter-sectoral shifts
Uttarakhand) and West Bengal. in the land use, we follow Jean-Philippe Puyravaud
Our analysis of land use pattern at all-India level spans (2003) method that provides rate of change in land use.
over six decades starting from 1950-51. To see how
the land-use pattern has evolved over time we divide …(4)
 Changing land-use pattern 115

where, A1 and A2 represent the types of land uses at area to net sown area, X5 is the proportion of non-food
time t1 and t2, respectively. A value of r shows the annual area to net sown area, X6 is institutional agricultural
rate of change in a particular category of land-use. credit outstanding (in billion rupees), and is ε error
term.
2.1.2 Location coefficient
Since we have a panel data-set of states, we also run
Location coefficient (b) identifies spatial distribution fixed effects as well as random effects regressions to
of a land category across, and can be defined as: quantify marginal effects of different factors associated
with fallow lands: The fixed effects model is:
…(5) Yit = β0 + β1X1, it + β2X2, it + β3X3, it+ εit

where, Nij is area of jth land use category in ith state, Ni The fixed effect of regression model allows us to have
is the sum of area of all land categories in state i, Nj is a separate intercept for each cross-sectional unit i.e.,
the area of jth land category at all-India level, and Ns is state by controlling for the state specific factors.
the sum of all land categories at all-India level. The random effects model can be written as:
A higher value of b implies a higher regional Yit = β0 + β1X1, it + β2X2, it +β3X3, it+ εit +Uit
concentration of a particular category of land-use or
where, Uit is within-state error term.
vice versa.
All other variables are defined as above.
2.3 Determinants of fallow lands
At all India-level, we run a linear regression of the 3 Results and discussion
following form to identify the factors responsible for
3.1 Inter-sectoral changes in land-use
changes in fallow lands:
Table 1 shows inter-sectoral changes in land-use at all-
Y = β0 + β1X1 + β2X2 +β3X3 +β4X4 +β5X5 +β6X6 + ε
India level during 1950–51 to 2011–12. There has been
where, Y is the proportion of current fallow land to net a significant shift in the land-use in favour of non-
sown area. X1 is rainfall (June to September), X2 is agricultural activities throughout the period, but at
nutrient use (NPK in thousand tons), X3 is tractor sales varying rates over time. The shift in land-use to
(number of tractors), X4 is the proportion of net irrigated agriculture was favorable until the period of wider

Table 1. Inter-sectoral changes in land use in India

Categories Pre-green Initial green Wider Diversification Post-reforms Growth Overall

revolution revolution technological period period recovery (1950-
period period discrimination (1988-95) (1995-2004) period 2012)
(1950-68) (1968-75) period (2004-11)
(1975-88)

DE 0.00 -0.045 -0.003 -0.007 0.000 0.001 -0.007

∆E1 0.011 0.007 0.002 0.006 0.004 0.003 0.006
∆E2 -0.011 -0.052 -0.006 -0.013 -0.003 -0.002 -0.013
∆A 0.002 0.003 0.000 -0.001 -0.001 -0.001 0.001
∆N 0.03 0.027 0.011 0.01 0.012 0.011 0.017
Net sectoral 0.036 -0.021 0.008 0.004 0.013 0.013 0.012
changes*
DR 0.004 0.001 0.001 0.001 0.001 0.001 0.002
Source: Authors’ estimates.
Note: *the net sectoral change is equal to algebraic sum of ∆N+ ∆E1 +∆E2 + ∆A
116 Pandey G, Ranganathan T

Table 2. Inter-sectoral changes in land use at state level

State ∆E ∆E1 ∆E2 ∆A ∆N ∆R ∆E ∆E1 ∆E2 ∆A ∆N ∆R

Diversification period (1988-95) Post-reforms period (1995-2004)

AP 0.009 0.002 0.007 0.002 -0.003 0.002 -0.018 0.000 -0.018 -0.003 0.019 -0.002
Assam -0.008 -0.001 -0.007 0.001 0.01 0.000 -0.001 -0.003 0.002 0.142 0.005 0.018
Bihar 0.002 0.002 0.000 -0.004 0.016 0.000 -0.087 -0.003 -0.084 0.009 -0.035 0.000
Gujarat -0.002 -0.001 -0.001 0.000 0.004 0.000 0.000 0.000 0.000 0.002 0.001 0.001
Haryana -0.031 -0.021 -0.01 -0.001 0.025 0.000 -0.046 -0.048 0.002 -0.001 0.007 -0.001
HP -0.003 0.009 -0.011 0.000 -0.006 0.005 0.173 0.015 0.158 -0.006 0.086 0.03
J&K 0.004 0.000 0.004 -0.001 -0.005 0.000 -0.029 -0.028 -0.001 0.003 0.001 -0.017
Karnataka -0.002 -0.001 -0.002 -0.001 0.007 0.000 -0.002 -0.001 -0.001 0.000 0.006 0.001
Kerala -0.063 -0.005 -0.057 0.001 0.009 -0.001 -0.041 -0.002 -0.039 -0.004 0.032 -0.001
MP -0.022 0.001 -0.023 0.001 0.008 0.000 -0.017 0.002 -0.019 0.000 -0.026 0.000
Maharashtra -0.002 -0.002 0.000 -0.001 0.013 0.000 0.001 0.000 0.001 -0.002 0.012 0.000
Orissa 0.033 -0.001 0.034 0.000 0.018 0.001 0.039 -0.003 0.042 -0.006 0.015 -0.001
Punjab 0.034 0.017 0.017 -0.001 -0.01 0.000 -0.146 -0.002 -0.144 0.002 0.008 0.001
Rajasthan -0.014 -0.007 -0.006 0.001 0.009 -0.001 -0.010 -0.004 -0.006 -0.001 0.006 -0.002
Tamil Nadu -0.007 0.006 -0.012 0.002 0.005 0.002 0.006 0.003 0.004 0.005 0.011 0.005
UP -0.013 -0.002 -0.011 0.000 0.006 0.000 -0.062 -0.001 -0.061 -0.001 0.004 -0.001
WB -0.126 0.001 -0.126 -0.001 0.009 0.000 -0.050 -0.005 -0.046 -0.002 0.004 -0.001
Growth recovery period (2004-12) Overall (1984-12)
AP -0.005 -0.001 -0.004 0.006 0.009 0.004 -0.004 0.000 -0.005 0.002 0.008 0.001
Assam -0.009 -0.005 -0.004 -0.176 0.014 -0.023 -0.006 -0.003 -0.003 0.001 0.010 0.000
Bihar -0.001 0.001 -0.001 -0.002 0.004 -0.001 -0.03 0.000 -0.03 0.001 -0.004 0.000
Gujarat -0.004 -0.001 -0.003 0.005 0.003 0.002 -0.002 -0.001 -0.001 0.002 0.003 0.001
Haryana -0.001 -0.015 0.013 0.000 0.019 0.002 -0.03 -0.031 0.000 -0.001 0.019 0.000
HP 0.019 0.000 0.019 0.002 -0.033 0.000 0.066 0.009 0.057 -0.002 0.019 0.013
J&K 0.009 -0.001 0.01 -0.002 -0.015 -0.001 -0.006 -0.010 0.004 0.000 -0.006 -0.007
Karnataka -0.001 -0.001 0.000 -0.31 0.008 -0.114 -0.002 -0.001 -0.001 -0.089 0.008 -0.033
Kerala -0.061 0.002 -0.063 -0.004 0.022 0.001 -0.059 -0.002 -0.057 -0.002 0.022 -0.001
MP -0.009 0.000 -0.009 0.000 0.012 0.000 -0.018 0.001 -0.019 0.000 -0.002 0.001
Maharashtra 0.000 0.000 0.000 -0.001 0.005 0.000 -0.001 -0.001 0.000 -0.001 0.011 0.000
Orissa 0.026 -0.003 0.029 -0.021 0.026 -0.006 0.036 -0.002 0.038 -0.008 0.021 -0.002
Punjab 0.094 0.016 0.078 -0.002 0.005 0.001 -0.011 0.011 -0.022 0.000 0.000 0.000
Rajasthan -0.011 -0.006 -0.005 0.004 0.007 0.001 -0.013 -0.006 -0.007 0.001 0.008 -0.001
Tamil Nadu -0.009 -0.004 -0.005 -0.005 0.003 -0.003 -0.003 0.002 -0.005 0.001 0.007 0.002
UP -0.018 0.000 -0.018 -0.002 0.011 -0.001 -0.033 -0.001 -0.032 -0.001 0.007 -0.001
WB -0.068 -0.001 -0.067 -0.004 0.009 -0.001 -0.091 -0.002 -0.090 -0.002 0.008 -0.001

Source: Authors’ estimates.

Note: AP stands for Andhra Pradesh, HP for Himachal Pradesh, J&K for Jammu & Kashmir, MP for Madhya Pradesh, UP
for Uttar Pradesh and WB for West Bengal.

technological dissemination (1975-88) but at the cost The state level analysis of inter-sectoral shifts in the
of undesirable ecological sector. From then onwards, land-use shows a decline in the land for agriculture in
the net change in land for agriculture was negative, favour of non-agricultural and ecological sectors in
showing a shift in the land-use shift towards ecological Haryana, Himachal Pradesh, Karnataka, Kerala,
or non-agricultural sectors or both. It may also be noted Maharashtra, Rajasthan, Orissa, Uttar Pradesh, and
that there was no significant shift in the land-use from West Bengal during the post-reforms period (1995-
non-agriculture to agricultural activities. 2004) (Table 2) primarily owing to increasing
 Changing land-use pattern 117

urbanization and industrialization. On the other hand, the least instability, followed by land for non-
there was an increasing trend in the land for agriculture agricultural uses, and net sown area.
in Gujarat, Andhra Pradesh and Assam but at the cost
of ecological sector (mainly undesirable). In Bihar, 3.2 Spatial distribution of fallow lands
Jammu & Kashmir and Madhya Pradesh there was a Locational coefficients estimated to know the pattern
shift in the land-use towards agriculture at the cost of of concentration of fallow lands are presented in table
non-agricultural sector. 3. There is a sharp increase in the concentration of
To cross-check results obtained from the aggregated fallow lands in Tamil Nadu, Rajasthan, Assam, Bihar,
categories of land-use, we estimate growth rates for Uttar Pradesh and Andhra Pradesh. The more disturbing
individual land categories, and results are presented in feature is their very high concentration in Bihar, Andhra
the appendix table A1 and A2. At all India level, the Pradesh, Tamil Nadu, Rajasthan, and Karnataka. This
highest growth is recoded for the non-agricultural uses probably is due to increase in the instability of surface
(1.28%), followed by area under forests (0.58%), irrigation, and erratic rainfall. On the other hand, there
current fallows (0.51%) and net sown area (0.17%). was a decline in the concentration of current fallows
On the other hand, barren and unculturable land in Gujarat, Haryana, Punjab, and Tamil Nadu.
witnessed a negative growth of 1.54% per annum, and
was followed by land under miscellaneous tree, 3.3 Determinants of fallow lands
culturable waste, other uncultivated land excluding Often, farmers leave some part of their land
fallow lands, and fallow land other than current fallows. uncultivated for a season to improve physical and
The current fallows in India have shown a positive chemical properties of soil, or because its remoteness
growth trend while the area under fallows other than (Bamwerinde et al. 2006; Gellerich et al. 2007; Bakker
current fallows have shown a declining trend over time. and Van Doorn 2009). They also leave land fallow
The area under current fallows recorded a compound because of several other reasons including lack of
growth rate of 0.51% per annum, while the area under
resources, poor irrigation facilities, extreme weather
other fallows declined at the rate of -0.23 % per annum.
conditions and soil erosion. We assess the role of a
Appendix table A2 provides compound annual growth few factors associated with current fallow lands. Table
rates in different categories of land-uses for states. 4 presents results of the linear regression, and of the
There is a positive trend in the land used for non- Newey method. The Newey estimator is used to
agricultural purposes across the states because of rising overcome the problems of autocorrelation and
demand for it for housing, industrial activities and heteroscedasticity, that are often present in the time
infrastructure creation. Barren and unculturable land series.
increased only in Himachal Pradesh and Orissa; and
declined in all other states with Punjab experiencing There is an inverse relationship between the monsoon
the highest rate of decline. rainfall and proportion of current fallow lands to the
net sown area. A one-unit increase in rainfall leads to
Assam experienced the highest rate of increase in 0.097% decline in the proportion of current fallow
current fallow lands, and was followed by Odisha, lands. Fertilizer use (NPK) also shows a negative
Kerala, Maharashtra and Himachal Pradesh. But there relationship with proportion of current fallow lands but
was a significant decline in it in Punjab, Haryana and it is not statistically significant. However, we find
Tamil Nadu. significant decline in the proportion of current fallow
The instability indices1 for different land-uses are lands with improvements in mechanization i.e., tractor.
shown in appendix table A3. The fallow lands The irrigation turns out to be significant and positive
(including current fallows and other than current showing increase in fallow lands with an increase in
fallows) and barren, and unculturable lands are more the irrigated area. An increase in the proportion of non-
unstable than other land categories. Forest lands show food area also leads to a decline in fallow lands.

1
Cuddy-Della Valle Instability Index (per cent) = . where, CV is the coefficient of variation in percent, and R2 is the
adjusted coefficient of determination from a time trend regression.
118 Pandey G, Ranganathan T

Table 3. Locational coefficients of fallow land in states

States Wider technological Diversification Post-reforms Growth Overall

discrimination period period recovery period (1984-12)
period (1984-88) (1988-95) (1995-2004) (2004-12)
FL CF FL CF FL CF FL CF FL CF

AP 1.66 2.42 1.63 1.97 1.67 2.11 1.64 2.05 1.65 2.10
Assam 0.33 0.23 0.31 0.22 3.84 4.80 1.58 1.93 1.81 2.18
Bihar 1.87 2.32 1.78 2.24 1.65 2.25 1.86 2.66 1.77 2.38
Gujarat 0.08 1.58 0.07 1.00 0.03 0.85 0.02 0.52 0.04 0.90
Haryana 0.01 1.16 0.00 0.96 0.01 0.84 0.05 0.66 0.02 0.86
HP 0.14 0.29 0.18 0.29 0.13 0.27 0.12 0.27 0.14 0.28
J&K 0.05 0.39 0.05 0.46 0.07 0.49 0.15 0.44 0.08 0.45
Karnataka 0.72 1.21 0.67 1.23 0.67 1.62 0.73 1.50 0.69 1.43
Kerala 0.22 0.23 0.22 0.24 0.25 0.35 0.35 0.40 0.27 0.32
MP 0.62 0.39 0.57 0.39 0.53 0.40 0.55 0.40 0.56 0.40
Maharashtra 1.03 0.55 1.13 0.70 1.22 0.77 1.11 0.91 1.14 0.76
Orissa 0.68 0.44 0.46 0.21 0.72 0.47 0.77 0.88 0.66 0.52
Punjab 0.01 0.23 0.07 0.27 0.03 0.17 0.01 0.13 0.03 0.19
Rajasthan 2.15 1.75 1.79 1.17 2.02 1.52 1.74 1.08 1.90 1.34
Tamil Nadu 1.93 2.28 2.49 1.68 2.94 1.77 3.42 1.48 2.82 1.74
UP 0.88 0.78 0.90 0.78 0.74 0.76 0.59 0.90 0.76 0.81
WB 0.29 1.01 0.15 0.71 0.10 0.63 0.07 0.85 0.13 0.77
Source: Authors’ estimates.
Note: FL stands for fallow land other than current fallow land, and CL stands for current fallow land.

Table 4. Linear regression estimated of determinants of fallow lands at all-India level

Liner Difference Newey

Rainfall -0.097*** -10.155*** -0.097***

(3.38) (3.94) (3.85)
NPK -0.000 -0.000 -0.000
(0.32) (0.19) (0.32)
Tractors -0.949 0.000 -0.949**
(1.21) (0.18) (2.20)
Proportion of net area irrigated 0.520** 0.974** 0.520**
(2.11) (2.33) (2.60)
Proportion of non-food area in total area -0.427* -0.941** -0.427*
(1.71) (2.75) (1.90)
Credit outstanding 0.155 -0.779 0.155
(0.22) (0.37) (0.26)
Constant 17.016 -0.081 17.016***
(3.95) (0.17) (5.76)
Number of observations 32 31 32
R-squared 0.560 0.602
Adjusted R-squared 0.454 0.502
t- statistics in parentheses. ***, ** and * denote significance at 1%, 5% and 10% levels, respectively.
 Changing land-use pattern 119

Table 5. Results of the panel regression for fallow land non-agricultural sector. In Odisha and Himachal
Pradesh there is a decline in the land for agriculture at
Fixed Random
the cost of either ecological or non-agriculture or both
effect effect
sectors.
Proportion of net area irrigated -0.371*** -0.286*** The fallows have expanded in the country. There is a
(3.59) (3.83) concentration of fallow lands in Tamil Nadu.,
Proportion of non-food area in 0.087 0.013 Rajasthan, Uttar Pradesh, Bihar and Andhra Pradesh.
total area (0.64) (0.13)
The regression analysis identifies erratic rainfall and
Rainfall -0.554* -0.595**
poor mechanization as important factors for increase
(1.78) (2.22)
in fallow land area.
Constant 29.539*** 29.325***
(5.03) (5.00)
References
Number of observations 420 420
R-squared 0.043 Bamwerinde, W., Bashaasha, B., Ssembajjwe, W. & Place,
Adjusted R-squared 0.003 F. (2006). The puzzle of idle land in the densely
populatedkigezi highlands of south-western Uganda.
t- statistics in parentheses. ***, ** and * denote significance International Journal for Environment and
at 1%, 5% and 10% levels, respectively. Development, 3, (1): 1-13.
Bakker, M.M., & van Doorn, A.M. (2009). Farmer-specific
relationships between land use change and landscape
The regression results of the panel fixed effects and factors: introducing agents in empirical land use
random effects models are presented in table 5. The modelling. Land Use Policy, 26: 809-817.
proportion of current fallow lands is negatively and
Bardhan, B., & Tewari, S.K. (2010). An investigation of
significantly associated with the net irrigated area and
land use dynamics in India and land under-utilization.
rainfall. The effect of rainfall seems to have a greater Indian Journal of Agricultural Economics, 65(4): 658-
influence. These results indicate that in regions with 676.
low and erratic rainfall farmers tend to leave more of
Gellrich, M., Baur, P., Koch, B., & Zimmermann, N.K.
their land uncultivated.
(2007). Agricultural land abandonment and natural
In an earlier study conducted by the authors using forest re-growth in the Swiss mountains: A Spatially
household level data from India Human Development Explicit Economic Analysis. Agriculture. Ecosystems
Survey (IHDS) for 2011-12 finds that with access to and Environment, 118: 93-108.
irrigation and ownership of machines (tractors and Giri, R. (1966). Changes in land-use pattern in India. Indian
power-tillers) farmers leave less of their land fallow Journal of Agricultural Economics, 21(3): 23–32.
(Ranganathan & Pandey 2018). A well-functioning GoI (2015). Directorate of Economics and Statistics.
lease market is also observed to reduce the proportion Ministry of Agriculture and Farmers Welfare,
of land to be left fallow. On the other hand, the decision Government of India.
to leave the land fallow is also determined by the herd Harte, J. (2007). Human population as a dynamic factor in
size; larger the herd size, greater is the probability of environmental degradation. Population Environment,
leaving a larger proportion of land fallow. 28: 223–236
Jodha, N. (1989). Depletion of common property resources
4 Conclusions in India: micro-level evidence. Population and
Our findings show a marginal increase in the land for Development Review, 15:261-283.
cultivation at the cost of undesirable ecological sector. Nadkarni, M.V., & Deshpande, R. (1979). Under-utilization
There has been a continuous expansion in land for non- of land – climatic or institutional factors? Indian Journal
agricultural uses mostly diverted from the ecological of Agricultural Economics, 34 (2): 75-83.
sector. The inter-state sectoral changes in the land-use Palchoudhuri, Y., Roy, P.S., & Srivastava, V.K. (2015). A
pattern in Haryana, Karnataka, Kerala, Maharashtra, new socio-economic index for modeling land use and
Uttar Pradesh, West Bengal and Himachal Pradesh land cover change. Journal of Land and Rural Studies,
showed a decline in agriculture sector at the cost of 3(1): 1-28.
120 Pandey G, Ranganathan T

Puyravadu, J.P. (2003). Standardizing the calculation of Ranganathan, T., & Pandey, G. (2018). Who leaves farmland
annual rate of defostration. Forest Ecology and fallow and why? An empirical investigation using
Management, 177(1-3): 593-596. nationally representative survey data from India. The
European Journal of Development Research, https://
Rada, N. (2016). India’s post-green-revolution agricultural
doi.org/10.1057/s41287-018-0139-2
performance: what is driving growth? Agricultural
Economics, 47(3): 341–350. Ranganathan, T., & Pandey, G. (2017). Tenancy and
fallow land. World Development Perspectives, 7: 28-
Ramasamy, C., Balasubramanian, R., & Sivakumar, S.D.
31.
(2005). Land use patterns with special reference to
fallow lands – an empirical investigation in Tamil Nadu. Received: 18 March 2018; Accepted: 24 May 2018
Indian Journal of Agricultural Economics, 60(4): 629-
643.
 Changing land-use pattern 121

Appendix Table A1. Compound annual growth rate of land use for different purposes in India

FR ANA BUL NAS OUL LMIS CWL FL CF

Pre-green revolution period 1.99 1.83*** -0.64** 0.86 3.60 -5.79*** -2.39 -3.39 -0.02
(1950-68)
Initial green revolution period 0.47* 2.17** -4.94*** 0.13 -0.65* -0.68 1.15 -0.81 2.22
(1968-75)
Wider technological discrimination -0.04 1.01 -0.40* -0.18 -0.53*** -0.19* -1.18 0.81* 2.44**
period (1975-88)
Diversification period (1988-95 ) 0.37*** 1.02 -1.26* 0.08 -0.78*** 0.41* -1.09 -0.60** -0.40
Post-reforms period (1995-2004) 0.19*** 1.08** -0.58*** -0.37 -0.65** -0.94 -0.69*** 1.48 2.31
Growth recovery period (2004-11) 0.00 1.05** -0.21 0.02 -0.27** -1.22* -0.92* -0.26 0.24
Overall (1950-2012) 0.58 1.28 -1.54 0.17 -0.24* -1.20 -0.91 -0.23* 0.51
Source: Authors’ estimates.
Note: FR stands for forest, ANA stands for area under non-agricultural uses, BUL stands for barren and un-cultural land,
NAS stands for net area sown, OUL stands for other uncultivated land excluding fallow land, LMIS stands for land under
misc. tree crops and groves not included in net area sown, CWL stands for cultural waste land, FL stands for fallow land
other than current, CL stands for current fallow land.
***, ** and * denote significance at 1%, 5% and 10% levels, respectively.

Appendix Table A2. State-wise compound annual growth rate of land use for different purposes in India 1984–2012)

States FR ANA BUL NAS OUL LMIS CWL FL CF

AP 0.18*** 0.95 0.39** 0.003 1.89 0.53** -1.19 0.37* -0.37

Assam -0.27 1.18 -0.37 0.13 -0.67 -1.01 -1.49 3.60 6.18*
Bihar -0.12*** 0.88 -0.07 -0.52 -0.39* 1.14 -0.17 0.36* 0.14**
Gujarat -0.15** 0.26 -0.14 0.50*** 0.02 -0.50 0.03 -5.82 -4.10***
Haryana -6.97 2.72 -0.97* 0.004 0.07 8.36 0.65 5.93** -1.95**
HP 0.74 3.54 7.54 -0.36 1.31 2.12*** 0.23 0.38 1.26
J&K -1.61 0.18* 0.18* 0.09** -0.03 -0.47 -0.16* 4.65* -0.72*
Karnataka 0.01* 0.82 -0.10 -0.15* -0.93 -0.63 -0.47 0.64** 1.25**
Kerala 0.001 2.49 -5.63 -0.28*** -21.03* -9.82* -1.42* 2.70 2.73
MP 0.31 0.79 -1.28 -0.08** -1.19 -8.17 -0.46*** -0.07 0.13
Maharashtra 0.07* 1.14 0.16 -0.19 -0.34* 0.74* -0.52 0.66** 2.07
Orissa 0.15* 2.50 3.76 -0.93 -1.74 -4.46 -0.45 1.75* 5.19
Punjab 0.13 0.46 -4.99*** -0.01 -0.79 0.46 -8.03*** -7.39 -3.70**
Rajasthan 0.87 0.82 -0.80 0.53* -0.35 -1.85** -1.30 -0.13 -1.20
Tamil Nadu 0.01 0.85 0.40*** -0.67 -0.94 1.84 0.81*** 2.74 -1.37**
UP -0.004 1 -1.71 0.04* -0.93 1.21 -1.65 -1.66 0.60**
WB 0.28*** 0.68 -10 -0.11* -1.37** 0.19 -6.94 5.43 0.18
Source: Authors’ estimates.
Note: FR stands for forest, ANA stands for area under non-agricultural uses, BUL stands for barren and un-cultural land,
NAS stands for net area sown, OUL stands for other uncultivated land excluding fallow land, LMIS stands for land under
misc. tree crops and groves not included in net area sown, CWL stands for cultural waste land, FL stands for fallow land
other than current, CL stands for current fallow land.
***, ** and * denote significance at 1%, 5% and 10% levels, respectively.
122 Pandey G, Ranganathan T

Appendix Table A3. Instability of land use pattern in India during the different periods

Periods FR ANA BUL NAS OUL LMIS CWL FL CF

Pre-green revolution period 0.045 0.066 0.041 0.015 0.102 0.358 0.022 0.051 0.078
(1950-68)
Initial green revolution period 0.011 0.026 0.019 0.015 0.012 0.073 0.036 0.048 0.163
(1968-75)
Wider technological discrimination 0.005 0.006 0.022 0.016 0.009 0.013 0.013 0.038 0.113
period (1975-88)
Diversification period (1988-95 ) 0.002 0.011 0.005 0.003 0.008 0.029 0.008 0.023 0.036
Post-reforms period (1995-2004) 0.002 0.005 0.023 0.022 0.007 0.031 0.006 0.043 0.172
Growth recovery period (2004-11) 0.000 0.009 0.012 0.008 0.001 0.014 0.011 0.026 0.053
Overall (1950-2012) 0.061 0.049 0.100 0.030 0.126 0.355 0.056 0.145 0.120
Source: Authors’ estimates.
Note: FR stands for forest, ANA stands for area under non-agricultural uses, BUL stands for barren and un-cultural land,
NAS stands for net area sown, OUL stands for other uncultivated land excluding fallow land, LMIS stands for land under
misc. tree crops and groves not included in net area sown, CWL stands for cultural waste land, FL stands for fallow land
other than current, CL stands for current fallow land.