A factor analysis of modernisation in village india

A FACTOR ANALYSIS OF MODERNISATION IN VILLAGE INDIA

INTRODUCTION

Now there does not exist a field of study which analyses the economic and social processes that are transforming village communities in the developing world, and relates village to national development.

Not Yet policies to increase agricultural productivity attitudes, skills,

cultural achievements at the village level are important in the developing

countries.

There are three basic obstacles which must be surmounted in studying micro-development :

1• the communities undergoing socio-economic change

are many, and widely different

2

• quantified information on village economic struc ture and performance is scarce and often of dubious accuracy.

3

• there are no theories generating models of sequential change and development at the village level which are theoretically persuasive and amenable to policy implementation

**This paper attempt to overcome some of these difficulties in analysing village development in India.

The data for the research taken from village surveys by representative villages in each of the fifteen states between 1960 and 1962.

The purpose was to obtain comparable information on the structure and performance of village com munities.

The published results contain statistics on income, landholdings, educational, transport facilities, etc., as well as verbal descriptions of village history, caste composition and styles of life.

DATA

The number of villages included from each state is proportional to the rural population of that state.

We also chose our sample so as to reflect the full range of variation in village development contained in the original studies.

Statistical techniques such as discriminant analysis were used to identify outliers which needed further checking

Extensive cross-checking of sources was used in the data preparation (this process took about nine months)

Ranked the 108 villages with regard to each of seventeen

variables

Grouped the villages into 3,4 or 5 ranked categories

depending upon the fineness of the survey data

In those cases, numerical scores were assigned to the ranked groups according to

the scale

Experiments with alternative scales (logarithmic and

squared) indicated that the results were insensitive to the

scale chosen.

DEFINITION OF VARIABLES

Variable DefinitionPopulation Villages were ranked according to the number of house holds, which ranges from 932

to 8, with a mean of 158 households.

Number of Castes

This indicator ranks villages into five categories according to the number of named caste groups resident in the village

Extent of Commercialisation

This indicator groups villages into one of three sets (high, medium and low) depending upon the proportion of yearly village produce which is sold to markets.

Quality of Agricultural Technology

This composite index ranks villages according to the proportion of arable land which is irrigated and the propor tion of farm households which use chemical fertiliser or pesticides.

Location and Access to Transport

This indicator also is a composite of several data series : quantity and quality of village access to transport facilities

Awareness of Social Legislation

One of the very few indicators of social attitudes we could contrive from the survey information was the extent of awareness in the village of legislation on social issues

Variable DefinitionEducation (1) the percentage of children aged 5 to 14 who attended school

(2) the percentage of female children aged 5 to 14 in school(3) the num ber of literate males over 14 expressed as a percentage of all males over

14 (4) the educational facilities avail able in and near the village.

Family Household Type

This variable ranks villages according to the proportion of simple households, (i.e., containing one married couple with their unmarried children) in the village

Female Child Marriage

This variable ranks villages by the number of married females who are less than 14 years old

Percentage of Low-caste Households

The number of people belonging to low castes expressed as a percentage of the total village population

Co-operative Membership

The number of village households which were members of multi-purpose co-operative societies

Income This variable combines two aspects of village income: the average monthly income per household and a measure of extent of inequality in income distribution. households in the village with average monthly incomes below 50 Rupees.

Variable DefinitionLand Per Capita This indicator classifies villages according to the quantity of arable land per capita

(the total amount of land used for farming divided by the village population).

Community Development Activity

Villages were divided into four groups according to the number and size of development projects under taken by the community.

Employment in Agriculture

For each village, the number of people aged 15 to 59 who were engaged in agriculture was expressed as a percentage of all people in that age group.

Percentage of Households Owning Land

Villages were classified according to the percentage of households owning some farmland

Percentage of Tenant Farmers

This variable classifies villages accord ing to the percentage of households who lease land from owners or who work land they do not own, on a share-cropping arrangement.

THE STATISTICAL TECHNIQUE

• Factor analysis requires no pre-existing theory of functional relation ships, can handle masses of diverse data relating to a large number of social and economic characteristics and communities.

• Factor analysis therefore helps to circumvent many of the difficulties inherent in the study of micro-development.

• The object of its use in this instance is to " explain " most of the varia tion between the villages of 17 economic and social variables in terms of far fewer " Factors,".

• If this can be done, the 17 variables can then be classified into a small number of clusters each of which is associated with just one of the Factors.

• The particular technique which was chosen for obtaining the Factors in terms of the variables has the following further properties : The Factors are completely uncorrelated with each other.

• The Factors are derived so as to maximise the percentage of the total variance (of the 17 variables) attributable to each successive Factor, given the inclusion of the preceding Factors.

• The number of Factors is determined by the rule that so soon as the next Factor to be extracted would " explain " less than 5% of the overall variance, that extraction should terminate without that Factor being extracted.

• Factor analysis does not allow us to attribute cause and effect. It does, however, permit us to delineate the underlying regularities in a complex mass of data by extracting from a larger set of variables the mutual interdepen dence among the subsets of characteristics comprising each Factor.

• The results of the Factor analysis are summarised in Table 1. Each entry in the table (or matrix) shows the importance of the influence of the Factors (or columns) on the variables (rows). More specifically, each entry or " Factor loading," is the net correlation between a Factor (set) and a single observed variable.

• The Factor loadings may be interpreted more familiarly in terms of the squares of the entries in the Factor matrix. the square of each entry in the matrix represents the proportion of the total unit variance of each variable which is explained by each Factor.

• The right-hand column of the table gives the sum of the squared Factor loadings, or the " communality " of each variable. The communality indicates the proportion of the total unit variance explained by all the com mon Factors taken together and is therefore analogous to R2 in regression analysis.

THE RESULTS OF THE ANALYSISTh

e Fi

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The

Seco

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The

Third

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The

Four

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The

Fift

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The economic characteristics which have their highest loadings

Factor 1 are the population of the village, the extent of commercialize tion of pro ductive output, the quality of agricultural technology, and the nearness of villages to towns and transport facilities.

Factor 2 characterises the extent of modern family practices.

Villages with high scores on this Factor have a large proportion of nuclear (as com pared to extended) family households and a small proportion of girls under the age of 14 who are married.

proportion of all village households which are low-caste, and the proportion of households which belong to co-operatives.

Villages that score high on this Factor have a high proportion of low-caste households, and a large percentage of households who are members of co-operatives. .

Income, land per capita.

Villages that score high on this Factor have low incomes, small plots of land and undertake more than the average number of community development projects. This Factor therefore indicates the extent of village poverty.

Factor 5, describes the extent to which the land tenure arrangements.

Villages that have a high proportion of households owning land, have many people engaged full-time in agriculture as well as a relatively large amount of land per capita.

SPECIFIC VARIABLES

IncomeA profile of high-income villages would include the following charac teristics in order of importance:

• a relatively high amount of land per capita (in Factor 4), • a high degree of commercialisation (Factors 1 and 5),• better than average performance in adopting improved

agricultural technology (Factor 1), • a relatively large number of castes (Factor 1), • more awareness of national social legislation (Factors 4 and 1)• a higher than average level of educational achievement (Factor 1)

Agricultural Technology

The quality of agricultural technology bears no systematic relationship to the agricultural characteristics included in Factor 4 but relates instead to commercialisation, size of village and nearness to transport facilities and towns (Factor 1, 55% of variance). These associations indicate that, by 1961, differences in land tenure had had considerably less impact on tech nical innovations in Indian agriculture than had commercialisation and the creation of farm-to-market roads.

Extent of Commercialisation

The extent of commercialisation has considerable weight in three of the five Factors, which confirms findings elsewhere that growth in market ac tivities is a particularly powerful solvent of traditional society.' Increased commercialisation means greater dependence on market sales, a corres ponding reduction in production for self-use, and a resulting increase in the proportion of cash receipts to real income.

Transport and Location

Better transport facilities allow goods and people to become outwardly mobile. Opportunities are created for new occupational choices, new earnings from market sale, and for imports of producer and consumer goods into the hinterland. The economic integration of villages into the national economy leads to the diversification and enlargement of commercial and cultural transactions between the village and the outside world.

Employment in Agriculture

The low statistical correlation between agricultural employment and Factor 1 is noteworthy. Apparently the better located, highly commer cialised, more technologically advanced villages do not differ significantly from their opposites with regard to the proportion of people engaged in agriculture. This lack of significant correlation between agricultural and other aspects of modernisation is probably due to the relative infrequency of livelihood alternatives outside of agriculture. Although it is common for village households to supplement their agricultural income with subordinate occupations, these are usually not sufficiently remunerative to allow villagers to move out of agriculture completely.

Land Per CapitaLand per capita has its greatest secondary loading in Factor 5 (16% of variance), indicating a relationship between the amount of land available, the extent of employment in agriculture and the prevailing system of land tenure.

Awareness of National Social LegislationThe extent of awareness of national social legislation is the only attitudinal characteristic we were able to include in our analysis. It is probably a proxy for other changes in attitudes which we were unable to capture with our data sources.

EducationOur variable indicating educational facilities and their effectiveness (as measured by adult literacy and percentage of school age children in school) associates most closely with economic and attitudinal modernisation as summarised in Factor 1. An examination of the simple correlations of education with the variables in Factor 1 suggests, however, that this associa tion arises primarily because large villages also tend to be better endowed with educational facilities.

Family Household Type

The literature on kinship stresses that the extended household (three generations with or without collateral relatives living together) is an economic unit of peasants working co-operatively for subsistence and that the extended household tends to give way to the nuclear family household once cash earn ings grow and alternative modes of employment emerge. Our analysis supports these views (see Factor 2). Where there are many nuclear house holds and infrequent child marriages, there is less land ownership and greater awareness of national social legislation.

Proportion of Low-caste Households

The absence of systematic relationships between density of low-caste households and Factors other than 3 implies that villages with a relatively large proportion of low-caste households are neither better nor worse off than other villages with regard to income and other positive attributes of welfare and modernisation. The probable reason for this is the greater geographic and occupational mobility of low-caste households.

Membership in Co-operatives

The frequency of membership in co-operatives is associated only with Factor 3, indicating that, as of 1961, co-operatives had not yet contributed significantly to economic development and to social modernisation. There are several possible explanations. The co-operative movement might have been too recent for its effects to be evident by 1961.

Community Development Activities

The negative association between community development activity and income in Factor 4, which reflects the compensatory character of the pro gramme, also suggests that, as of 1961, community development efforts had not been successful in raising village incomes sufficiently to overcome these differences.

• The differences between economically advanced and backward villages were largely the result of an historical adjustment to superior growing conditions and access to urban markets, rather than the result of recently initiated development programmes.

• Our factor analysis points up the importance of various economic forces to village modernisation. Factor 1, which explains most of the inter-village variance, includes the extent of commercialisation, the quality of agricultural technology and nearness to transport and cities.

• The im portance of economic forces is shown also in the relationships (in Factors 4 and 1) between higher income and commercialisation and improvements in agricultural technology.

• These economic associations suggest that rural development policy in India can profitably be concerned with conventional economic programmes—the creation of farm to market roads, agricultural extension services, profitable technologies, and the fostering of commercial crops.

CONCLUSION

CONCLUSION• Giving up traditional social practices in village India seems to

lag behind economic improvement and behind changes in social attitudes. Our indicator of modern family practices (movement to nuclear households and decline in female child marriage) appeared in the second Factor, and ac counted for only half as much variation among villages as the indicators of economic and cultural modernisation in Factor 1. Economic incentives worked to keep the extended family together.

• The influence of caste in our study appears in the awareness of social legislation prohibiting untouchability, in the number of castes per village and in the percentage of village population composed of low castes. The factor analysis suggests that the weaker the caste system the higher the level of income and development, and that the income and modernisation status of the untouchables are equivalent to those of other rural Indians : the simple correlation between percentage of low caste persons in a village and village income is 0.09!

• The evidence on what might be accomplished through land reform is mixed. Types of land tenure do not appear to influence agricultural incomes or agricultural technology. There is, however, a significant association between larger farms and higher than average incomes per head.

PRESENTED BY :

Irna Azzadina 29011002Yessie Fransiska 29011013Masca Indra 29011019Renni Rengganis 29011025Adityawarman 29011026Enny Nuur’Aini 29011032