I am forwarding his dissertation titled "Analysis of Regional Disparities in Agricultural Development in Assam : An Econometric Approach" submitted for the award of Ph.D. in this institute. Thanks also go to all the professors of the Department of Humanities and Social Sciences of this institute for encouragement, good wishes and useful suggestions.
Abstract
PCA (Principal Component Analysis), one of the regionalization approaches, has been used to examine inter-regional disparities in agricultural development and to identify the lagging regions. In this study, PCA (Principal Component Analysis) was used to construct agricultural development indices.
Contents
An Introduction
Trends in Agricultural Development in Assam
Agricultural Regions in Assam and Analysis of Imbalance
- The Issues
- The Problem
- Scope
- Objectives
- Hypotheses
- Geographical Coverage
- Reference Period
- Methodology
- An Outline of the Work
Archana Sharma, Inter-state differences in the nutritional level of life in India, with special reference to. The frequent occurrence of floods in the state has also made the state's agricultural development an urgent humanitarian issue.
The Region, Regional Development Theories and Methods of Measuring Regional Disparities
- The Concept of Region
- The definition given by Malgavkar and Ghiara clearly emphasize on the factors of homogeneity, nodality and administrative convenience for a planning region. According to
- Inter-Regional Disparity and Development Process
- The more fundamental target is to reduce inter-personal disparities, but one can not reach that target unless inter-regional disparities are reduced 77 The regional imbalances
- Theories Explaining Difference in Regional Growth
- Neo-Classical Models
- Cumulative Causation Models
- The Growth Pole or Development Pole Theory
- Central Place Theories
- Theories of Geographical Diffusion of Innovation
- Growth Foci Model
- Regional Development Potential Theory
- Methods of Measuring Regional Disparities
- Agro-Climatic Zones of Assam
- North Bank Plains
- Lower Brahmaputra Valley
- Central Brahmaputra Valley
- Upper Brahmaputra Valley
- Barak Valley
- Hill Zone
In recent decades, there has been a growing awareness of the existing inter-regional disparity in the level of agricultural development in the country. Shrivastava122 used the composite index to measure regional disparities in agricultural development in Madhya Pradesh.
Model for Regionalisation and Spatio-Temporal Dynamism in the Level of Agricultural Development
The Method of Principal Components—A Tool of Regionalisation
Where "i" refers to the ith variable x. v) finally, the latent root of the first principal component was detected to estimate the variation represented by the first principal component (P1). Here, the sum of squares of the loadings of the first principal component is estimated. The sum of the latent roots of all principal components is equal to the number of x's.
A convenient way to present the latent roots is to express them as a percentage of the total variation in the set of x's. To measure agricultural development differences at the aggregate level, the weighted average component score (WACS) is calculated from the Principal Component Score (PCS) of the retained PCs. The composite index is nothing but the first principal component of the variables where WACS are taken as variables.
Attempts are made to analyze the rate and course of variation within the perspective of tolerable inequality. There are various methods for measuring the degree of regional imbalances and these measurements range from conventional ones such as mean, range, standard deviation, coefficient of variation, index of regional imbalances index of interregional variation etc. In the present study, Use of tools like balance ratio, regional imbalance index, inter-regional imbalance index and regional imbalance coefficient is made to measure the extent of regional disparities in agricultural development in Assam.
These techniques are simple and clear and provide sufficient indications of the extent of regional imbalances. Both the index of inter-regional imbalances and the index of intra-regional imbalances have been used for general observations only as they have no operational use. C denotes the coefficient of disequilibrium R denotes the index of regional disequilibrium. I indicate the index of intra-regional imbalance. Then Nsj is the Jth counter indicator of the standard region.
To remove the inherent limitations of the Cobb-Douglas production function, several alternative production functions have recently been proposed. In light of the aforementioned limitations, this study had to rely on the Cobb-Douglas production function. Because the incorporation of the error component model (or residual model), the Cobb-Douglas production function becomes much easier and simpler.
Another important assumption of the error components model is the homogeneous but distorted relationship between input and output. The exclusion of such variables has some important consequences for the estimates of the function. The model has been drawn up in the light of the dynamic model developed by Balestra and Nerlove130.
Trends in Agricultural Development in Assam
Agricultural Development in India
- Agricultural Production
Particularly gratifying was the growth in the production of food grains, which enabled the country to eliminate frequent famines. The table shows that the increase in the production of food grains was mainly due to the impressive increase in cereals, while the production of pulses almost stagnated. The growth of the agricultural sector can be described by the rise of the index of agricultural production.
It can be seen from the table that agricultural production has shown an increasing trend in case of food grains, no. The average annual rate of increase in the index of agricultural production during the period from 1970-71 to 1999-2000 is 1.92 percent in the case of food grain production. Source: Directorate of Economics & Statistics, Department of Agriculture & Cooperation Table 4.5 Progress for selected agricultural development programmes.
Agricultural Development In Assam
- Climate
- Agricultural Production
- Index of Agricultural Production
- Yield Rate
- Agricultural Holding
- Fertilizer
- Irrigation
- Area Under High Yielding Variety (HYV)
- Agricultural Credit
- Crop Insurance
- Special Production Programme
Although the growth rate is impressive, it is lower than the all-India average (2.6 percent per annum). Agricultural production in Assam is increasing due to increased use of compound fertilizers (eg NPK) and HYV seeds, irrigation system and mechanization. Among the important crops in the country, the area under rice dominated, accounting for almost 65 percent of the total sown area in 1998-1999. On the other hand, large farms (20 hectares and more) accounted for only 0.09 percent of the total number of operating farms with 11.37 percent of the total managed area in the country.
The creation of gross irrigation potential in the state till 1998-99 was 4.83 lakh hectares under the government scheme. The following table shows the target and achievement of additional potential created under various irrigation schemes in the state. Centrally sponsored scheme on Integrated Post Management (IPM) for judicious use of pesticides in crops implemented since 1994-95 in the state.
Agricultural Regions in Assam and Analysis of Imbalance
Agricultural Regions in Assam
The composite index of agricultural development given in the following equation is the first principal component of the 9 variables. It is observed that the degree of intra-regional imbalances is higher at the district level than in the agricultural region. The maximum amount of imbalance is found in the case of gross irrigated area in relation to agricultural region.
The range of variation in the coefficient of imbalances of different indicators in Assam disaggregated at the district level (Table 5.10) is found to be lower than that at the regional level, in terms of agricultural region, but it is higher than that of natural region. In the case of district level, there is also the highest degree of imbalances in respect of gross irrigated area compared to all other relative indicators. It is found that the degree of imbalances is lower in terms of literacy rate in agricultural region than at district level.
Co-efficient of Imbalance in Natural Regions of Assam
The interregional imbalance was measured by taking the values of various indicators at the regional level. Regional Index of Regional Imbalance A. Intra-regional disparities in different regions can be seen from Table 5.16. From table 5.17, it can be seen that intra-regional imbalances are higher in backward districts and highly developed districts followed by developed and developing districts.
It can be observed that the extent of intra-regional imbalance has an inverse relationship with agricultural development of regions. The index of intra-regional imbalance was found to be 27.50 in the “Backward” region versus 14.27 inches. disaggregated at district level.
Factors Responsible for Disparities
Chapter 6
Regionalisation of the State and Results of Spatio-Temporal Dynamism in the Level of Agricultural Development
- Regionalisation –Concept and Approaches
- Regionalisation-Methodology
- Identification of the Level of Agricultural Development of the Agro-Climatic Zones
- Spatial Disparity in the level of Agricultural Development in Assam
- Spatial-Dynamism in the Level of Agricultural Development
- Temporal Dynamism in the level of Agricultural Development
According to Table 6.2, the levels of development in the agricultural sector of the agro-climatic zones of Assam can be identified by arranging the agro-climatic zones in the following order:. It can be seen that the ranking of the agro-climatic zones is almost identical with spatial (regional) effects and regionalization indices. This section will discuss the estimates of the temporal effects on agricultural production based on the error component model applied to the six agro-climatic zones of the state.
The model is based on the assumption that the effects of the temporal factors are independent of the efficiency level of a region (region effect) and the level of inputs used (input effect). For this purpose, the agro-climatic zones can be classified into three groups based on the coefficient of variation of their temporal effects. From Table 6.5 it can be seen that the temporal effect is very variable and does not follow a specific trend for any of the six agro-climatic zones.
Identification of Agro-Climatic Zones of Assam
Indentification of Agricultural Regions of Assam on the basis of Principal Component Analysis
Identification of Agro-climatic zones of Assam on the basis of Spatio-Temporal Dynamism
Summary of Findings and Strategy for Balanced Regional Development of Agriculture in Assam
Summary of Findings
Agricultural production in Assam is one of the lowest in the country, accounting for only 5.6 percent of India's production. There are several problems in irrigation development in the hill area due to its hilly nature and scarcity of flat land. Lack of required irrigation facilities in Assam reduces the use of fertilizers and HYV seeds, which affects agricultural production in the state.
Among the spatiotemporal factors, some are susceptible to human influences in the long term. Apart from the problem of spatial imbalances, there is another area of concern, which is the temporal variation in the level of agricultural production. The steadiness and survival of the growth in agricultural production over the years in the state is often questionable.
A Strategy for Balanced Agricultural Development
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Sharma, Archana (1992) Interstate differences in the nutritional standard of living in India with special reference to Assam, Indian journal of regional science, Vol. 1969). A Factor Analysis of Fertilizer Use by Farmers, Indian Journal of Agricultural Economics, Vol. 1983) Regional Disparities in Agricultural Development in Madhya Pradesh, Indian Journal of Regional Science, Vol. Measuring the levels of development – a taxonomic approach, Indian Journal of Regional Science, Vol. 1990) Regional Disparities in Agricultural Development, Deep & Deep Publications, New Delhi.
