A thesis submitted to Indian Institute of Technology Guwahati in partial fulfillment of the requirements for the degree of. Ira Das for the degree of Doctor of Philosophy in Economics in the Department of Humanities and Social Sciences of the Indian Institute of Technology Guwahati, embodies bona fide record of research work carried out under our joint supervision and guidance.
Acknowledgement
I would also like to express my gratitude to a few eminent scholars for their advice and comments at various stages of my research work. I am grateful to my colleagues in Pragjyotish College, Guwahati for their encouragement and support in pursuing my research work.
Contents
- Urban Bias in the Government Policies in Assam 88
- Nature and Strength of Sectoral Linkages in Assam 112 6.1 Methodology of Measurement of Nature and Strength of
- Effective Linkage Study (Impact Analysis)
- Summary of Findings, Conclusion and
Nature and Strength of Sector Linkages in Assam 112 6.1 Methodology for Measuring Nature and Strength 6.1 Methodology for Measuring Nature and Strength of.
List of Tables
Household income, Batabari Village, 2009 186 Table 7.19 Open-loop effects (crossover effects or net extra-group or . spillover effects) of an exogenous injection on households. Income, for activities, Batabari Village, 2009 187 Table 7.20 Closed-Loop effects (or net contribution of circular effects).
Abstract
Introduction
- Background of the Study
- Statement of the Problem
- Objectives of the Study
- Hypotheses of the Study
- Data Sources
- Methodology
- Layout of the Dissertation
The state's per capita income is one of the lowest in the country. Weak sectoral linkages and biased policies of the government are responsible for rural-urban divide in the state.
Review of Literature
- Rural-Urban Linkage Study
- Study on Rural-Urban Divide
- Reasons behind the Rural-Urban Divide
- Effective Linkage Study (Impact Analysis) to minimise the Divide
- Conclusion
The problem of the rural-urban divide has been studied without establishing the links between sectors in most studies. Therefore, a systematic study of the problem of rural-urban divide and sectoral linkage in the state is required to minimize the divide.
Present Status of Assam Economy
- Geographical Location
- Demographic Pattern
- Occupational Pattern of Population
- State Income
- Agriculture
- Industry
- Infrastructure Facilities
- Transport and Communication
- Power
- Banking Services
- Conclusion
Assam has a monopoly on the production of 'Muga' - the golden thread, in the world, and 99 percent of Muga Silk is produced in the state. However, mobile connections are increasing in both rural and urban areas of the state. The rural-urban difference in providing power facilities in the state is shown in Table 3.9.
Assessment of Rural-Urban Divide in Assam
Rural-Urban Disparity Index
Equal weights have been assigned to each of the indicators for the calculation of the composite index for rural and urban areas. Similarly, the minimum values for the value of the worst performing state of India are in the respective indicators. Before the construction of RUDI, as shown in (i), the rural-urban gap in all selected indicators is examined by measuring the rural-urban gap in the values of the indicators in absolute differences over the years in the respective indicators in the state versus - versus India.
Rural-Urban Divide in Accessing Health Care Facilities in Assam
- Rural-Urban Divide in Health Outputs in Assam
- Rural-Urban Divide in Health Inputs in Assam
- Rural-Urban Disparity Index (RUDI) in Health Indicators
Rural-urban distribution of the selected health output indicators in Assam compared with the all-India average. To quantify the disparity between rural and urban areas of the state, the Rural-Urban Disparity Index has been constructed. This also implies that the rural-urban disparity in the selected health outcome indicators in the state is higher than the national average.
Rural-Urban Divide in Accessing Education Facilities in Assam
RUDI Values for Health Input Indicators
Rural-Urban Disparity Index (RUDI) in Education Indicators
The index is constructed separately for the state and the country as a whole to facilitate comparison. The picture is reversed in the case of RUDI values for educational inputs in the state (see table 4.6b). The difference is not only large in the state, but is also increasing compared to the national average.
Rural-Urban Divide in Employment Generation in Assam
- Rural-Urban Divide in Percentage Distribution of Working Persons in Different Sectors
- Rural-Urban Divide in Unemployment and Underemployment Rates in Assam
- Rural-Urban Disparity Index (RUDI) in Employment Generation in Assam
The rural-urban disparity in education levels is still prevalent both for the state and the country. The rural-urban divide is prominent in the manufacturing sector, which shows less rural industrialization for the state than the national average. The tertiary sector shows that a large disparity still exists between rural and urban areas both at state and national levels.
Urban Bias in the Government Policies of Assam
Urban Bias in Health Sector
For comparison, per capita health expenditures for rural and urban areas were estimated from available data. During this period, per capita government expenditure on health care services for both rural and urban areas increased significantly. Per Capita Expenditure on Health Care Services for Rural and Urban Areas of the State.
Urban Bias in Education Sector
Per capita expenditure on rural and urban students is calculated by dividing the total expenditure on rural and urban students by the total enrollment of rural and urban students for the respective years. The figure for the year 2005-2006 is used to calculate the per capita expenditure for the year 2006-2007 as the enrollment figure for the year 2006-2007 is not available. The grants are intended for secondary schools in Kamrup district, Assam. Since no data are available on the distribution of rural-urban student enrollment data in Kamrup District for the period 2006-2007, rural and urban per capita expenditure is calculated by dividing total subsidies by the enrollment of students in secondary school as given in the 7th All India Educational Survey.
Per capita Expenditure on Students on New School Building
Urban Bias in Employment Generation
- Per Capita Total Government Expenditures in Rural Areas and Urban Areas
- Wages of Agricultural and Industrial Workers
- Investment in Agriculture and Industry
- Safety Net Programmes of the Government across Rural and Urban Areas
Therefore, government expenditure on basic services for rural and urban areas is compared by examining the urban bias in generating employment in the state. The distribution of fair price shops in rural and urban areas in the state is presented in Table 5.8. This is consistent with the reliance on PDS in the country in rural and urban areas.
Manifestations of Urban Bias
- Differences in Infrastructure in Rural and Urban Areas
- Slow Growth of Agriculture
Accordingly, the provision of infrastructure facilities in rural and urban areas in the state is compared to examine whether urban bias in the provision of infrastructure facilities in rural and urban areas has contributed to the rural-urban divide in Assam. The table shows that there is a wide difference between the infrastructure facilities available in rural areas and urban areas in the state as the CII is only 59.07 in rural areas compared to 719.61 in urban areas (the difference is 660.54). Therefore, it can be concluded that there is policy bias on the part of the government in providing infrastructure facilities to rural and urban areas in the state.
Conclusion
Agricultural workers include cultivators and agricultural workers and non-agricultural workers include household industry workers and other workers (ie non-agricultural workers=Total workers – cultivators – agricultural workers) as stated in the Census Report. The table shows that during the years 1980-81 to 2008-09, the value added per worker in the agricultural sector has decreased with an annual cumulative of (-0.40) percent while the same has increased with an annual cumulative of 0.51 per percent for non-agricultural workers. And, the CAGR is (-0.40) percent for agricultural workers and 0.51 percent for non-agricultural workers during the same period.
Nature and Strength of Sectoral Linkages in Assam
Measurement of Nature and Strength of Sectoral Linkage in Assam
- Linkage Analysis without Import Leakages
- Linkage Analysis with Import Leakages
- Rank Correlation between the Linkage Indices for the State
The tables show that only 5 percent of sectors have both high backward and forward linkage values, while 15 percent of sectors have high backward linkages but low forward linkages. Similarly, the sector with low backward and high forward linkages is zero, and sectors with low backward and forward linkages account for 50 percent of all sectors. In addition, the dispersion of backward and forward linkages was found to increase with import leakage, meaning that sectors affected fewer sectors in the country than overall (same as observed by Ramadhyani, 1984 in another study).
Examination of Reasons behind Rural-Urban Divide in Assam
Rural-Urban Differences in Infrastructure (I): Unilateral urban policies are reflected in the availability of infrastructure for different areas (Braun, 2007). While the raw data on the rural-urban divide (D) are collected from the SKK Reports, the data on the Relative Backwardness of Agriculture (S) are collected from central and state government publications (on the contribution of the agricultural and non-agricultural sectors to NKZHP and for the number of workers in agriculture and non-agriculture). In the model, the rural-urban divide (D) is regressed on the relative backwardness of agriculture (S) and weak sectoral linkages (W).
Conclusion
Livestock Milk and milk products, such as ghee, butter and other milk. Wood-based industries Plywood and their products, sawing and planing wood, wood and cane products, wood furniture, etc., production of structures such as pillars, doors, windows, etc., other wood,. Miscellaneous coal tar Coke, bitumen, etc., coal tar, miscellaneous petroleum products including candle manufacture.
Effective Linkage Study (Impact Analysis): A Social Accounting Matrix Analysis
Methodology of Constructing Social Accounting Matrix (SAM)
- Structure of SAM
- Village SAM Multiplier Model
- Decomposition of the Multiplier Effects
The framework is used to measure the system-wide impact of changes in exogenous accounts. In designing village models, the simplest assumption is that the responses of village factors to changes in income are strictly proportional to the total level of activity in each account (ie, column sums in the SAM). Dividing each element in SAM by the total of the corresponding column yields a matrix of average proportions, S.
Construction of SAM for the Village Batabari in Assam
- Study Village, Industry and the Data
- Construction of the Village SAM for Batabari
- Aggregate SAM for Batabari
- Selected Socio-Economic Characteristics of the Village
- Educational Qualification of the Villagers
- Contribution of the Sectors to the Village GDP
The rest of the village (ROV) implies to everywhere outside the village except the industry, because ROV (industry) is taken as another institution. The contribution of the various sectors in the village to the village's GDP is shown in table 7.7. Village GDP is calculated following the procedure carried out by Parikh and Thorbecke (1996), Subramanian (2006) and Taylor and Adelman (2006).
Contribution of Sectors to the Village GDP (%)
Contribution of Factors to Total Value Added
The contribution of the factors to the total income of the village is presented in table 7.8 and figure 7.2. From the table and figures, it appears that the contribution of family work is relatively higher (42.8 percent) in the total value of the addition of factors than other factors.
Composition of Household Income and Per Capita Income across Households
The pattern of per capita income (excluding imputed family labor income) for different households is shown in Figure 7.4. While the average per capita income of all household groups is calculated at Rs, the per capita income of all other household groups is above average except small farmers with a large number of 59.6 percent of the population. The income received by the government per household per day through various schemes (i.e. in terms of social sector expenditure) is estimated on the basis of village SAM and found to be Rs.
Distribution of Factor Income Shares across Household Groups (in %)
- Import Penetration Ratio (IPR) and Export Intensity (EI) of Trade in Batabari
- Sources of Income for the Households and their Distribution
- Government Subsidy to the Industry and its Return to the Locality Benefits of setting up of Nilon’s industry in Dalgaon can be examined from
- Examination of Scope of Setting up of More Food-Processing Industry in the Locality
- Analysis of the Impact of the Industry on the Village through SAM Multiplier Model
- Results of Output, Income and Employment Multipliers
Earning factor income (payments for government and private jobs) + transfer income from remaining villages. The subsidy is given for the benefit of the people [The reason for government incentives is to change society's bias against investment and increase the rate of return on investments that may have relatively low private returns but provide external benefits to society as a whole (Laird and Rinehart, 1967; Keipi, 1997; Singh, 2009)]. The volume of daily transaction of industry-related goods (mainly carrot, chilli, potato/pumpkin, cauliflower/Ol Govi/papaya, tomato/mango) in the market is 427 tonnes.
