Printer Friendly

Impact of land acquisition on farmers lifecycle and lifestyle.

Introduction

The only issue which decides for change of profession and place of survival overnight, Land Acquisition affects the livelihood of individual as well family members. Thus it accelerates to social change and social stratification by relocation due to landlessness and joblessness. This issue has been affecting the land owners worldwide. According to a study conducted by Negi and Ganguly (2011) which suggests that around 50 million people have been displaced in India due to various kinds of development projects in over 50 years, these; dams, mines, industrial development, and others account for over 21 million development-induced IDP as shown in figure-1.

Punjab is popularly perceived as an agricultural-rural state in the light of the strides it made in agricultural development, eventually shaping itself into the green revolution (Grewal, 2005). Now Punjab faces number of protests, agitations against grabbing of their agricultural land. Land of agricultural farmers and labourers has been grabbed by Government of Punjab. This case of acquisition is counted under public purpose by the Indian Railways. This keeps on adding to the problems of displaced people and people whose profession has been shifted/changed due to land grabbing for Dedicated Freight Corridor Project across the State. Since Independence, it is one of the most affected States in case of resettlement and rehabilitation. Thus to meet these problems, the programme of rehabilitation has been an integral part of Five Year Plans. With the passage of time they have been accommodated to rural and urban avocations. Government of India has been providing rehabilitation to displaced persons since 1947. Over the decades nation has been burdened with the cost and cases of rural rehabilitation and urban settlements. According to 1951 Census, about 7.5 million persons had moved into India in search of permanent home, 4.9 million from West Pakistan and about 2.6 million from East Pakistan.

No doubt different types of amenities and facilities which are in our possession today have come after sacrifice of land owners of their time. According to the central agriculture department, the total availability of arable land in the country was 185.09 million hectares in 1980-81. But in 2005-06 it has come down to 182.27 million hectares. Thus, during this period the cultivable land area has decreased by 2.52 million hectares (i.e. 20 lakh 20 hectares).

In recent times we again witness a similar problem relating to land acquisition but for a different reason altogether. Now, a number of developmental projects are affecting settled and rehabilitated population of Punjab. It's a project of Indian Railways named 'Dedicated Freight Corridor Project'. A train crossing over the entrance of the village was never in the thoughts of the villages that on some day it will alarm their lifecycle and lifestyles. This part comes in the Eastern Corridor, from Ludhiana (Punjab) to Dankuni (near Kolkata), total 1839 km. Land has been acquired under Railway Amendment Act (RAA), 2008. Whatsoever is the project, some have lost part or major portion of their agricultural land, and some have lost their residence too. But there are families whose complete land acquisition has ended up their profession and even displaced from their native place.

The objectives of this paper is:

* to study the impact of land acquisition on the life styles of the project affected persons (PAPs);

* to know the category of land owners affected in this project;

* to find how the land owners have utilized the amount of compensation, and;

* to evaluate the knowledge of the PAPs (Project Affected Persons) about the Land Acquisition procedures, its benefits and effects.

Methodology

The present study is based on the collective views of the people from villages located on either side of the railway tracks. These are Ghaghar Sarai, Madanpur, Khairpur Shekhan, Hashampur, Kheri Gandian, and Kharajpur of Tahsil Rajpura in District Patiala of Punjab. Among these villages coverage of residential area has been reported only in Kheri Gandian during the survey. In this case, they had been demolishing the house structure in due time after notice issued by the State Government. Its impact over ones psychological state is not less than T-Sunami or avalanche. Every planning of life gets torn to shreds. The study is based mainly on the primary data collected through field survey. In total 50 households were selected from these villages. Questionnaire was designed to know the land holding size, type of land acquired, change in profession, primary and secondary occupation, annual income, use of compensation, acquaintance about the acts and policies related to land acquisition, and impact on their social and economic life.

The data was collected through purposive survey technique using structured questionnaire. Later informal and formal discussions were also held in the villages and with individuals. The data has been analyzed using suitable techniques like frequency, percentage and correlation.

Discussion

Table-1 shows the information about (A) village wise households, (B) household size categorization, and (C) male-female population of the villages enumerated. It represents the number of households taken during direct interaction to canvass the questionnaire designed for the purpose to meet the objective. Out of the 50 households, 17 small households have been with the population up to 4 members, 28 medium households with population from 5 to 8 members, and 5 large households were having population for more than 9 members. This covered both the nuclear and joint families. Among the population of all age groups 159 males and 117 females population have been reported.

Table-2 gives information about the age and marital status of the population in these villages. As seen 26.8 percent of the population is up to the age of 18 years and 9.4 percent of the population has been reported under old age group. Virtually the onus lies over the remaining categories. The very purpose of this table is to present the dependency over the young and middle aged group. Diagram (Figure-3) showing age group of the households has been placed below.

Table-3 reveals that the percentage of literate population is 69.2 percent near to literacy rate (71.4 percent) (2) of rural Punjab. This also makes the human being to handle the situation in a best possible to plan either by way of change in profession or by relocating themselves. The level of literacy among the villagers made the survey easier and comfortable.

Information collected was initially not expected in such a small survey. 12 percent of the households, whose land has now been acquired, had already seen the face of displacement and resettlement in their earlier life. However this project has not affected these families at a big scale. Only one case of migrated household has been seen who is hailed from other district of Punjab purchased land in village Khairpur Sheikhan years back. Even after his land was acquired, household has remained in the same (semi-medium) category. Remaining 86.0 percent households have been living there over the decades. (Table-4).

Since land is the only commodity in the lifespan of an individual which makes men richer in various aspects. As discussed in table 4, 86.0 percent of the population is residing there over the decades and 14.0 percent of the population has moved later on. Respondents have their own views about the land depending upon their financial status, future liabilities and commitments. Most of the responses have resulted recommendation to the protection of land for the future of their families (56.0 percent). (Table-5).

In Table-6 we look from the point of view either the land is fertile or not. Respondents said their complete land is fertile and can be used for agricultural purposes; however, people have been using it for residential or commercial purposes also. Land thus acquired has been utilized by the land owners for the use as required. Before land acquisition, 74.0 percent households land was purely serving the agricultural purpose, 16.0 percent for the residential purpose and 10.0 percent for the both. Between 84.0 percent of the household's in terms of percentage points 50.0 had been managing cultivation either by themselves or their family members, and remaining percentage points 34.0 of households were either getting the cultivation done through contract or by labour.

* In this category total land in possession of farmers has been acquired. ** Increase noticed with decrease in Semi-medium category. *** Increase in Semi-medium and decrease in Medium category after land acquisition noticed simultaneously.

Table-7 provides the information about the change in farmer's category after the land acquisition. Crux of this table is to know the households who are now landless. This is the situation next to table 4 and 5 when population after land acquisition got displaced and looks forward for resettlement and rehabilitation schemes, and finally relocating. There are 5 households in the category of marginal farmers, who are now landless (16.7 percent). Increase in small category farmer is the result of decrease in semi-medium category. Category of semi-medium farmers thus also remains maintained with the decrease in medium category.

It can be seen from the Table-8 that compensation has been awarded in full to all the land owners as per the 'Entitlement Matrix' for Dedicated Freight Corridor Project Based on RAA 2008 and NRRP 2007. 10.0 percent of the households have opposed the compensation amount and only 60.0 percent out of the households who did not agree to the award of compensation have appealed in the court for enhancement of the compensation amount.

Table-9 depicts that as life takes u-turn especially for the families whose complete land or in-partial, complete house structure or in-partial has been acquired; the onus lies with the head of the household for the utilization of the compensation amount. Truly the same does not happen in all the families due to various reasons such as joint family or joint registry of the land acquired. Therefore the compensation amount is largely distributed.

Percentage shown above will not add up to 100 percent as amount of compensation have been utilized for more than one purpose as shown in last column (Options > 1) indicating that amount has been utilized for clearance of outstanding loan by two households, besides purchase of land. However, majority of households have purchase land, cleared outstanding loans, and invested on education of their children. Households who have bought luxury items have kept the in safe side for their children's marriage.

As shown in Table 9 it reveals that 12 households have utilized the compensation amount for the purchase of land in the neighbouring districts depending upon their necessity and affordability. Change in farmer category can be seen as decreased in Marginal Farmers with the increase ** in Small farmer, Medium, and Semi-medium category in Table-10.

* There is fall of percentage in the category of Marginal Farmers as compared to table 7 (from 16.7 to 12.0 percent) after utilization of compensation for land. ** However, rise in percent has come up in the categories of small, semi-medium and medium.

As discussed, land has been purchased away from the home town by most of the farmers, looking forward the return on investment in future and hike of land prices depending on their financial commitments. Four households who could not afford to purchase land at some other place are now landless. Change as increase in other category of farmers is timely investment. Investment of 12 households is quite visible from the above table as increase by 8 (in 'Net change' column) in Small, Semi-medium, and Medium category. Rest, the difference of four households is noticeable in 'After Acquisition and 'After Utilization of Compensation' total (See Table-11). Graph (Figure-4) below shows the changes in farmer category during all the three stages i.e. before acquisition, after acquisition and later in utilizing of compensation for land purchase.

While the literacy level of the villagers is high, the knowledge level about the Land Acquisition process, land pooling scheme, and rehabilitation process less than expectation has been reported. Either the organization and responsible authorities of the area are not making them aware about the facts before the acquisition or the willingness to sale land for the sake of money is higher. However, as per respondents awareness about Land Acquisition Act is higher (66.0 percent) as compared to schemes and policies (30.0 percent). It is understood that most of the villagers are not aware about issuance of notifications rather they came to know from the markings and sign boards placed by the railway authorities as Table 12 shows.

Table-13 indicates that there is lesser percentage (6.0 percent) of population who said that economic status is better after acquisition, possibility of two categories reflects here one who was under debt or has constructed their own house. Worst (54.0 percent) has been responded after land acquisition much as it was assumed. People got displaced are now landless, houseless and some are now in search of job to fulfill their family needs. Though compensation has been awarded as per the market rate but the loss of immovable asset has affected their heart and mind that their economic status has diminished.

The following Table-14 shows the relationship level:

Details of Bivariate Correlation have been obtained by choosing the variables 'Economic Status before Acquisition' and 'Economic Status after Acquisition'. In defined cell of the correlation matrix, in each cell Pearson's correlation coefficient, p-value for two tailed test of significance, and the sample size is obtained. The correlation coefficient between economic status before and after acquisition is 0.332 and the p-value for two-tailed test of significance is less than 0.05. Concluding that there is a strong positive correlation between 'Economic Status before Acquisition' and 'Economic Status after Acquisition' and this correlation is significant at the significance level of 0.05.

As per Table-15, lesser change is seen in change of primary occupation as per the information provided by the respondents. Also, total frequency of primary occupation (from codes 2 to 6) is higher (23.2 percent) than cultivation (i.e. 12.7 percent). As discussed in Table-13, smaller changes in cultivation and agricultural labour frequency has necessitated the families to look for a job/business prospect considering that their economic status has decreased. Noticeable decreased in frequency of prime occupation of cultivation has decreased (from 12.7 to 12.3 percent) and simultaneous increase in frequency of agricultural labour from (4.7 to 5.1 percent) after land acquisition. It also affected the frequency of 'No work' in before and after the land acquisition.

Table-16 shows the effect of joblessness as well landlessness in the cultivation and agricultural labour. Income in some cases has ceased due to demolition of house structures. Percentage of 'No work' has gone down with the increase in search of job/business prospects. This mainly has come up with the fall in secondary occupation where more than one source was also available for income purpose. Change in 'No work' frequency does not indicate to loss of job rather it indicates cases where earning has reduced after the acquisition of land. It can be observed from the following table below (Table-17) depicting details after correlating data for annual income before and after land acquisition.

Details of Bivariate Correlation have been obtained by choosing the variables 'Annual Income Primary Source Before Acquisition' and 'Annual Income Primary Source After Acquisition'. The two-tailed test was used because there was no prediction about the direction of relation between the variables have been tested. In defined cell of the correlation matrix, in each cell Pearson's correlation coefficient, p-value for two tailed test of significance, and the sample size is obtained. The correlation coefficient between annual income before and after acquisition is 0.970 and the p-value for two-tailed test of significance is less than 0.0005. Concluding that there is a strong positive correlation between 'Annual Income Primary Source Before Acquisition' and 'Annual Income Primary Source After Acquisition' and that this correlation is significant at the significance level of 0.01.

Details of Bivariate Correlation have been obtained by choosing the variables 'Resident Status before Acquisition' and 'Economic Status after Acquisition'. In defined cell of the correlation matrix, in each cell Pearson's correlation coefficient, p-value for two tailed test of significance, and the sample size is obtained. The correlation coefficient between resident status before acquisition and economic status after acquisition is 0.393 and the p-value for two-tailed test of significance is less than 0.05. Concluding that there is a strong positive correlation between 'Resident Status before Acquisition' and 'Economic Status after Acquisition' and this correlation is significant at the level of 0.01.

# Resident Status before Acquisition refers that living place is Native place (i.e. belongs to ancestral property), Migrated or Rehabilitated.

Down fall in Primary Source of Income

Graph (Figure-5) depicts that cases of 11 households holding agricultural land and their primary source of income was agriculture. After acquisition of land their primary source of income has been affected. In first two cases whose complete part of the land has been acquired their income has touched the minimum level i.e. zero. Annual income has been shown in millions for clarity in representation, thus indicating for the first household income in INR has decreased from [??]1.20 lacs to [??]0.00 and so on.

The next graph (Figure-6) depicts the case of 4 households holding agricultural land and income from agriculture was their secondary source of income. After acquisition of land their secondary source of income has been affected. Annual income is shown in millions.

Conclusion and Suggestions

The various factors relating to land acquisitions in Punjab on the lives of people have been analyzed, and based on the responses of the project affected persons, this paper concludes following. It has led to a number of changes in the category of the farmers, utilization of compensation amount by the land owners, and changes in the categories and income of primary and secondary occupation. It is evident from the discussions quoted above, that each table that land acquisition was for the public purpose in the interest of the nation. At the same time it is revealed that it was an agricultural land of the private parties acquired by the government for the public purpose. It is a universal truth that everything raises with the time, let it be demand, supply of any of the product. Demand and supply for several products is met after production, distribution and consumption. However, the place of survival rather say productive source also (i.e. land) does not increases with the time. Acquisition either at a small or a large scale has always affected in some percentage from large to the marginal farmers.

Notes

(1) CPI views on Land Acquisition Bill (LARR Bill 2011), a CPI publication 12/2011

(2) Primary Census Abstract-India, Census of India 2011

(3) Land Acquisition Act here refers to 'Land Acquisition Act, 1894 (1 of 1894)' published by Govt. of India, Ministry of Law and Justice. (4) LARR Act, 2013 here refers to Right to Fair Compensation and Transparency in Land Acquisition, Rehabilitation and Resettlement Act, 2013 (30 of 2013) published by Govt. of India, Ministry of Law and Justice. (5) Land Pooling Policy here refers to Notification No. 6/23/13-6Hg1/ 1440 dated 19th June, 2013 by Govt. of Punjab, Department of Housing and Urban Development. (6) Rehabilitation Act here refers to Displaced Persons (Compensation and rehabilitation) Act, 1954 [Act 44 of 1954].

References

Bal, Gurpreet (1995): 'Development and Change in Punjab' Published by National Book Organization, New Delhi.

Census of India, (2011)): 'Primary Census Abstract, India' Published by ORGI, New Delhi. Chakravorty, Sanjay (2013): 'The Price of Land-Acquisition Conflict Consequence', Oxford University Press, New Delhi.

Department of Housing and Urban Development, (2013):"Land Pooling Policy" Notification issued vide No. 6/23/13-6Hg1/ 1440 dated 19th June, 2013 by Government of Punjab.

Jaswinder Singh (2013): "Preliminary Information related Land Measurement', Singla Law Agency, Chandigarh

Entitlement Matrix for "Dedicated Freight Corridor Project Based on RAA 2008 and NRRP 2007" (Revised 13.06.2011) http://dfccil.org/dfccil_app/d0cs/atttcxl1.pdf, accessed on 15 Feb, 2014

First Five Year Plan, "Rehabilitation of Displaced persons, Chapter 38' http://planningcommission.nic.in/plans/planrel/fiveyr/1st/1planch38.html accessed on 3 Feb, 2014.

Gaur Ajai S. and Gaur Sanjaya S. (2014): "Statistical Methods for Practice and Research", Sage Publications, New Delhi.

Grewal, Reeta (2005): "Five Thousand Years of Urbanization in Punjab", Manohar Publisher and Distributors, New Delhi.

Mahadevia, Darshini (2008): "Inside the Transforming Urban Asia--Processes, Policies and Public Actions", Concept Publishing Company, New Delhi.

Mahalingam, Ashwin and Vyas, Aditi (2011): "Comparative Evaluation of Land Acquisition and Compensation Processes across the World", Economic and Political Weekly, Vol. XLVI No. 32.

Malik, Yudhvir Singh (2012): "Land Acquisition-A National Issue: Lessons from Haryana" Published in The Administrator Journal of LSBNAA, Special Issue December 2012, Vol. 53 No. 2.

Mathur, Hari Mohan (2012): "Resettling Displaced People-Policy and Practice in India", Routledge Taylor and Francis Group, New Delhi.

Ministry of Law and Justice (1894): "Land Acquisition Act, 1894 (1 of 1894)", Government of India, New Delhi.

Ministry of Law and Justice (2013): "Right to Fair Compensation and Transparency in Land Acquisition, Rehabilitation and Resettlement Act, 2013 (30 of 2013)", Government of India, New Delhi.

Siddiqui, Kamal (1997): "Land Management in South Asia-A Comparative Study", Manohar Publisher and Distributors, New Delhi.

Rehabilitation Act 1954, "Displaced Persons (Compensation and Rehabilitation) Act, 1954 [Act 44 of 1954]' http://punjabrevenue.nic.in/dpcract.htm Accessed on 15 May, 2014.

Sharma R. N. and Shashi R Singh (2009): "Displacement in Singrauli Region: Entitlements and Rehabilitation", Economic and Political Weekly, Vol. XLIV No. 51.

Singh, R.Y. (2012): "Geography of Settlements," Rawat Publications, Jaipur.

Somayaji, Sakarama and Talwar Smirithi (2011): "Development-induced Displacement, Rehabilitation and Resettlement in India" Published by Routledge, Abingdon, Oxon.
Table 1: Detail of Village wise households, Household size
and Population

Code   Category                      Frequency   Percentage

A      Village wise households

1      Ghaghar Sarai                 7           14.0
2      Hashampur                     6           12.0
3      Khairpur sheikhan             2           4.0
4      Kharajpur                     2           4.0
5      Kheri Gandian                 21          42.0
6      Madanpur                      12          24.0

B      Household Size

1      Small (up to 4 members)       17          34.0
2      Medium (5 to 8 members)       28          56.0
3      Large (9 and above members)   5           10.0

C      Population

1      Male                          159         57.6
2      Female                        117         42.4

Source: Field Survey, February 2014.

Table 2: Population Profile

Code   Category                          Frequency   Percentage

A      Age

1      Children (0-7 years)              32          11.6
2      Teenager(8-18 years)              42          15.2
3      Adolescence (19-25 years)         42          15.2
4      Young (25-40 years)               65          23.6
5      Middle aged (40-60 years)         69          25.0
6      Old (senior citizens60+ years)    26          9.4

B      Marital status

1      Never Married                     105         38.0
2      Married                           157         56.9
3      Widow                             6           2.2
4      Widower                           8

Source: Field Survey, February 2014.

Table 3: Literacy Status of Population

Code   Category                         Frequency   Percentage

A      Education

1      Primary (or passed below 8th)    47          17.0
2      Middle                           25          9.1
3      Matric                           69          25.0
4      10+2                             34          12.3
5      Graduate                         11          4.0
6      Post Graduate                    2           0.7
7      Professional                     3           1.1
8      Illiterate                       85          30.8

Source: Field Survey, February 2014.

Table 4: Category of Residence Status of the Households

Code   Category             Frequency   Percentage

1      Ancestral Property      43          86.0
2      Migrated                 1          2.0
3      Rehabilitated            6          12.0

Source: Field Survey, February 2014.

Table 5: Respondent Perception about Land Ownership

Code    Category                   Frequency   Percentage

1       Ancestral Property                6         12.0
2       As Security for Children         28         56.0
3       Kept as Asset for sale           10         20.0
4       Agricultural purpose              6         12.0

Source: Field Survey, February 2014.

Table 6: Category of Land Acquired

Code   Category           Usage of land      Frequency   Percentage

A      Land Status

1      Agricultural       Agricultural       37          74.0
2      Non-agricultural   Residential        8           16.0
3      Agricultural       Agricultural and   5           10.0
         and Non-           residential
         agricultural       purpose
B      Cultivation by

1      Self/ Family                          25          50.0
2      Contract                              17          34.0

Source: Field Survey, February 2014.

Table 7: Change in Category of Farmers

Code   Category of           Before        After
         Land Owner          Acquisition   Acquisition

1      Marginal Farmer               30             25
         (< 2.5 acre)
2      Small Farmer                   6              7
         (2.5 to 5 acre)
3      Semi-medium                    5              5
         (5 to 10 acre)
4      Medium                         1            --
         (10 to 25 acre)
5      Large                         --            --
         (25 acre & above)
       Total                         42             37

Code   Category of           Increase   Decrease
         Land Owner

1      Marginal Farmer            --        5 *
         (< 2.5 acre)
2      Small Farmer             1 **         --
         (2.5 to 5 acre)
3      Semi-medium                --         --
         (5 to 10 acre)
4      Medium                     --      1 ***
         (10 to 25 acre)
5      Large                      --         --
         (25 acre & above)
       Total                        1         6

Source: Field Survey, February 2014.

Table 8: Award of Compensation

Code   Category                     Frequency   Percentage

A      Recipient of Compensation

1      Full                         50          100.0
2      Partial                      --          --

B      Compensation Acceptability

1      Yes                          45          90.0
2      No                           5           10.0
C      Appealed in Court
1      Yes                          3           60.0
2      No                           2           40.0

Source: Field Survey, February 2014.

Table 9: Utilization of compensation

Code   Category                Frequency   Percent-   Options > 1
                                             age *
A      Compensation
         utilized for
1      Purchase of Land        12          24.0       7 (2)
2      Construction of house   4           8.0        4 (1), 6 (1)
3      Repair of House         7           14.0       4 (1), 5 (1),
                                                        & 8 (1)
4      Kept for                6           12.0       8 (1)
         children marriage
5      Luxurious bought        7           14.0       4 (1), 8 (1)
6      FDs/Savings             10          20.0       7 (1), 8 (2)
         for children
7      O/S Loan cleared        12          24.0       5 (1), 6 (1)
8      Invested on             7           14.0
         children education
9      If > 1 option           15          30.0

Source: Field Survey, February 2014. Multiple
responses reported regarding utilization of
compensation amount.

Table 10: Change in Farmer Category after Award of Compensation

Code   Category of           After         After
       Land Owner            Acquisition   Utilization of
                                           Compensation

1      Marginal Farmer       25            22
         (< 2.5 acre)
2      Small Farmer          7             9
         (2.5 to 5 acre)
3      Semi-medium           5             9
         (5 to 10 acre)
4      Medium                --            1
         (10 to 25 acre)
5      Large                 --            --
         (25 acre & above)
       Total                 37            41

Code   Category of           Increase   Decrease
       Land Owner

1      Marginal Farmer       --         3
         (< 2.5 acre)
2      Small Farmer          2          --
         (2.5 to 5 acre)
3      Semi-medium           4          --
         (5 to 10 acre)
4      Medium                1          --
         (10 to 25 acre)
5      Large                 --         --
         (25 acre & above)
       Total                 7          3

Source: Field Survey, February 2014.

* There is fall of percentage in the category of Marginal Farmers as
compared to table 7 (from 16.7 to 12.0 percent) after utilization
of compensation for land. However, rise in percent has come up in
the categories of small, semi-medium and medium.

Table 11: Broad Picture from Land Acquisition to Land Purchase

Category of         Before        After
land owner          acquisition   acquisition

Marginal Farmer     30            25
  (< 2.5 acre)
Small farmer        6             7
  (2.5 to 5 acre)
Semi-medium         5             5
  (5 to 10 acre)
Medium              1             --
  (10 to 25 acre)
Large (25 acre      --            --
  and above)
Total               42            37

Category of         After            Net
land owner          utilization of   change
                    compensation

Marginal Farmer     22               -8
  (< 2.5 acre)
Small farmer        9                +3
  (2.5 to 5 acre)
Semi-medium         9                +4
  (5 to 10 acre)
Medium              1                -1/+1
  (10 to 25 acre)
Large (25 acre      --               --
  and above)
Total               41               3

Source: Field Survey, February 2014.

Table 12: Awareness about Land acquisition
Acts, Policies and schemes

Code   Category             Frequency   Percentage

A      Land Acquisition
         Act, 1894 (3)
1      Yes                        33         66.0
2      No                         17         34.0

B      LARR Act, 2013 (4)
1      Yes                        23         46.0
2      No                         27         54.0

C      Land Acquisition
         Process
1      Yes                        27         54.0
2      No                         23         46.0

D      Land Pooling
         Policy (5)
1      Yes                        15         30.0
2      No                         35         70.0

E      Rehabilitation Act
         and Policies (6)
1      Yes                        27         46.0
2      No                         23         54.0

Source: Field Survey, February 2014.

Table 13: Economic Status of the Households

Code   Category             Frequency   Percentage

A      Before Acquisition
1      Better               30          60.0
2      Worst                10          20.0
3      No change            10          20.0

B      After Acquisition
1      Better               3           6.0
2      Worst                27          54.0
3      No change            20          40.0

Source: Field Survey, February 2014.

Table 14: Relationship between Household's Economic Status Before and
After Acquisition

Correlations                               Economic      Economic
                                           status        status
                                           before        after
                                           acquisition   acquisition

Economic status      Pearson correlation   1             .332 *
before acquisition   Sig. (2-tailed)                     .018
Economic status      Pearson correlation   .332 *        1
after acquisition    Sig. (2-tailed)       .018

* Correlation is significant at the 0.05 level (2-tailed).

Table 15: Change in Primary Occupation after Land Acquisition

Primary Occupation    Before                   After

                      Frequency   Percentage   Frequency   Parentage

Cultivation                 35         12.7          34        12.3
Agricultural Labour         13          4.7          14         5.1
Govt./Pvt. Job              30         10.9          30        10.9
Others                      14          5.1          14         5.1
If 1 and 4                   5          1.8           5         1.8
If 2 and 4                   2          0.7           2         0.7
Student                     60         21.7          60        21.7
No work                    117         42.4         115        41.7
In search of job/           --           --           2         0.7
  business
  prospects

Source: Field Survey, February 2014.

Table 16: Change in Secondary Occupation after Land Acquisition

Secondary           Before                   After
Occupation
                    Frequency   Percentage   Frequency   Percentage

Cultivation                5          1.8           1          0.4
Agricultural               3          1.1           4          1.4
  Labour
Dairying                   3          1.1           3          1.1
Pension                    6          2.2           6          2.2
Rent from                  6          2.2           4          1.4
  (Land/House)
Others                    25          9.1          25          9.1
If > 1 option              3          1.1           4          1.4
No work                  225         81.5         222         80.4
In search of job/         --           --           7          2.5
  business
  prospects

Source: Field Survey, February 2014.

Table 17: Relation between Annual Income Primary Source before and after
land Acquisition

Correlations                               Primary income

                                           Before        After
                                           Acquisition   Acquisition

Annual Income Primary       Pearson        1             .970 *
Source Before               correlation
Acquisition                 Sign.                        .000
                              (2-tailed)
Annual Income Primary       Pearson        .970 *        1
Source After Acquisition    correlation
                            Sign.          .000
                              (2-tailed)

* Correlation is significant at the 0.01 level (2-tailed)

Note: Value less than 0.0005 are shown as 0.000 in SPSS outputs.

Table 18: Relationship between Resident Status before Acquisition and
Economic Status after Acquisition

Correlations                               Resident      Resident
                                           status        status
                                           before        After
                                           acquisition   Acquisition

Resident status      Pearson correlation   1             .393 *
Before Acquisition   Sign. (2-tailed)                    .005
Economic Status      Pearson correlation   .393 *        1
after acquisition    Sign. (2-tailed)      .005

* Correlation is significant at the 0.01 level (2-tailed).

# Resident Status before Acquisition refers that living place is Native
place (i.e. belongs to ancestral property), Migrated or Rehabilitated.

Table 19: Acquisition of Agricultural Land

Household   Primary income

            Before LA     After LA


1           Rs.1,20,000   Rs.0
2           Rs.1,00,000   Rs.0
3           Rs.1,44,000   Rs.72,000
4           Rs.8,80,000   Rs.8,40,000
5           Rs.5,00,000   Rs.4,50,000
6           Rs.4,25,000   Rs.3,75,000
7           Rs.4,50,000   Rs.4,00,000
8           Rs.2,50,000   Rs.2,25,000
9           Rs.4,00,000   Rs.3,80,000
10          Rs.2,00,000   Rs.1,75,000
11          Rs.4,20,000   Rs.3,60,000

Source: Field Survey, February 2014.

Down fall in Secondary Source of Income

Household
Secondary    Before LA     After LA
income

1            Rs.1,65,000   Rs.65,000
2            Rs.1,50,000   Rs.1,20,000
3            Rs.1,50,000   Rs.25,000
4            Rs.1,00,000   Rs.0

Source; Field Survey, February 2014.

Figure 1: People Displaced by Development Projects

Category 1   4.3
Category 2   2.5
Category 3   3.5
Category 4   4.5

Note: Table made from bar graph.

Figure 2: Size of the households

Household Size

Small     34.0%
Medium    56.0%
Large     10.0%

Note: Table made from pie chart.

Figure 3: Age Group Categories of Household Members

Age Group: Household Members

Middle aged (40-60 years)         25.0%
Old (Senior Citizens 60+ years)    9.4%
Children (0-7 Years)              11.6%
Teenager (8-18 years)             15.2%
Adolescence (19-25 years)         15.2%
Young (25-40 years)               23.6%

Note: Table made from pie chart.

Figure 4
Change in Farmers Category
Before LA, After La, and After Compensation Utilisation

                     Marginal   Small    Semi-    Medium   Large
                      Farmer    Farmer   medium

Before Acquisition      30        6        5        1        0
After Acquisition       25        7        5        0        0
After Utilization       22        9        9        1        0
  of Compensation

Note: Table made from line graph.

Figure 5
Acquisition of Agricultural
Land: Source of Primary Income

Before Land   After Land
Acquisition   Acquisition

0.12             0
0.144            0.1
0.88             0.072
0.5              0.84
0.425            0.45
0.45             0.375
0.25             0.4
0.4              0.225
0.2              0.175
0.42             0.36

Note: Table made from line graph.

Figure 6
Acquisition of Agricultural Land: Source of Secondary Income

Before        After
Acquisition   Acquisition

0.165         0.065
0.15          0.12
0.15          0.025
0.1           0
COPYRIGHT 2014 Centre for Indian Development Studies
No portion of this article can be reproduced without the express written permission from the copyright holder.
Copyright 2014 Gale, Cengage Learning. All rights reserved.

Article Details
Printer friendly Cite/link Email Feedback
Author:Shorey, Brij Mohan Krishan; Farooquee, Nehal A.
Publication:Political Economy Journal of India
Article Type:Report
Geographic Code:9INDI
Date:Jul 1, 2014
Words:5492
Previous Article:Community participation in Sarva Sikhya Abhiyan: a micro analysis.
Next Article:Performance of South Asian economies in meeting the MDGs and role of the world bank.
Topics:

Terms of use | Privacy policy | Copyright © 2019 Farlex, Inc. | Feedback | For webmasters