Effect of agricultural policy on succession decisions of farm households

Policymakers, economists, and researchers have recently been interested in assessing the impact of farm program payments on the growth and survival of farm businesses. Planning for succession is an integral part of managing a farm business. This study uses farm-level data to investigate the impact of government farm policy and farm growth on both succession decisions and the likelihood of intra-family transfers of the farm business. Results indicate that succession decisions are significantly influenced by government farm policy, farm wealth, age, and educational attainment of current farm operators. Results show that off-farm work by operators and spouses and regional location are positively correlated with non-family farm succession decisions. On the other hand, farm ownership, educational attainment, and marital status of the operator increase the likelihood of family-based succession decisions. However, in the presence of retirement income from other sources such as pension, parents are less likely to have a family successor.

Human Personality Behavior Based on Family Structure Using a Thematic Apperception Test

This study focuses on analyzing the relationship between the ways an individual projects a story from a picture shown to him or her with the past and the family background of the individual. We have taken the sample of 30 students heterogeneous with respect to gender and age. Each respondent was shown three pictures and wrote one story per picture; the stories were then analyzed on the basis of a thematic apperception test (TAT). A human personality has many aspects and dimensions. We will be trying to throw some light on the impact that the family structure and the bringing up of an individual has on the development of his or her personality.     

Improved estimator of population total in PPS sampling

In this paper, we have considered an estimation of the population total Y of the study variable y, making use of information on an auxiliary variable x. A class of estimators for the population total Y using transformation on both the variables study as well as auxiliary has been suggested based on the probability proportional to size with replacement (PPSWR). In addition to many the usual PPS estimator, Reddy and Rao's (1977) estimator and Srivenkataramana and Tracy's (1979, 1984, 1986) estimators are shown to be members of the proposed class of estimators. The variance of the proposed class of estimators has been obtained. In particular, the properties of 75 estimators based on different known population parameters of the study as well as auxiliary variables have been derived from the proposed class of estimators. In support of the present study, numerical illustrations are given.     

A new approach: Interrelated two-way clustering of gene expression data

The paper presents a new approach to interrelated two-way clustering of gene expression data. Clustering of genes has been effected using entropy and a correlation measure, whereas the samples have been clustered using the fuzzy C-means. The efficiency of this approach has been tested on two well known data sets: the colon cancer data set and the leukemia data set. Using this approach, we were able to identify the important co-regulated genes and group the samples efficiently at the same time.     

A New Approach to the Estimation of Inter-Variable Correlation

The use of different measures of similarity between observed vectors for the purposes of classifying or clustering them has been expanding dramatically in recent years. One result of this expansion has been the use of many new similarity measures, designed for the purpose of satisfying various criteria. A noteworthy application involves estimating the relationships between genes using microarray experimental data. We consider the class of ‘correlation-type’ similarity measures. The use of these new measures of similarity suggest that the whole problem needs to be formulated in statistical terms to clarify their relative benefits. Pursuant to this need, we define, for each given observed vector, a baseline representing the ‘true’ value common to each of the component observations. These ‘true’ values are taken to be parameters. We define the ‘true correlation’ between each two observed vectors as the average (over the distribution of the observations for given baseline parameters) of Pearson's correlation with sample means replaced by the corresponding baseline parameters. Estimators of this true correlation are assessed using their mean squared error (MSE). Proper Bayes estimators of this true correlation, being based on the predictive posterior distribution of the data, are both difficult to calculate/analyze and highly non robust. By constrast, empirical Bayes estimators are: (i) close to their Bayesian counterparts; (ii) easy to analyze; and (iii) strongly robust. For these reasons, we employ empirical Bayes estimators of correlation in place of their Bayesian counterparts. We show how to construct two different kinds of simultaneous Bayes correlation estimators: the first assumes no apriori correlation between baseline parameters; the second assumes a common unknown correlation between them. Estimators of the latter type frequently have significantly smaller MSE than those of the former type which, in turn, frequently have significantly smaller MSE than their Pearson estimator counterparts. For purposes of illustrating our results, we examine the problem of inferring the relationships between gene expression level vectors, in the context of observing microarray experimental data.     

Book Reviews: E.A. Wrigley (ed.), Poverty,Progress and Population., Cambridge: Cambridge University Press, 2004, XIV+ 463 pp.

Book Review

Book Reviews: E.A. Wrigley (ed.), Poverty, Progress and Population., Cambridge: Cambridge University Press, 2004, XIV+ 463 pp.     

Book Reviews: Tim Dyson,Robert Cassen,and Leela Visaria (eds.), Twenty-First Century India: Population,Economy, Human Development,and the Environment. New York: Oxford University Press Inc., 2004, XXii + 414 pp.

Book Review

Book Reviews: Tim Dyson, Robert Cassen, and Leela Visaria (eds.), Twenty-First Century India: Population, Economy, Human Development, and the Environment. New York: Oxford University Press Inc., 2004, XXii + 414 pp.