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In the five decades since Kuznets (1955) published his hypothesis on income inequality, a large and significant portion of the work on income distribution and inequality has involved using cross-sectional data for developmental comparisons at the intra- and international levels. Using cross-sectional data, these studies have tracked inequality trends that were deemed the consequence of growth and technical progress due to fiscal manipulations, such as levying taxes and granting subsidies to satisfy some welfare target. While this prior work provided valuable insight at the macroeconomic level on the interrelationship of development, economic growth, and income inequality, only over the last few decades has the research emphasis shifted from an understanding of the implications of income inequality at the aggregate level to that at the individual level. Using cross-sectional data it is possible to track income groups over time, but not the composition nor the characteristics of these groups, which are likely to change over time and affect their position in the income distribution. On the other hand, with the availability of longitudinal, micro-level data it has become possible to investigate in more detail underlying facets of income distribution, such as income mobility, and the lack of it, among households. Using three panels of the Survey of Income and Program Participation (SIPP) (1993, 1996, and 2001) and building upon the methodological suggestions of Jarvis and Jenkins (1998) and Jenkins (2000), this paper looks at a household's economic and demographic characteristics relative to their position in the income distribution. For example, results indicate that between 1996-1999, 13 million households experienced changes in their annual income that resulted in their moving up or down two or more quintiles in the income distribution. On the other hand, 39 percent of households (38.5 million) remained in the same quintile between 1996-1999 with the majority of these households experiencing intra-quintile movements. Of notable interest is that of those households remaining in the fourth and top quintiles between 1996-1999; 70 percent and 65 percent, respectively, experienced positive intra-quintile gains in income ranging, on average, from $3,550 to $10,812 annually.JEL classification: C81, D31, O15

Are those in poverty likely to remain there or can they move out of this situation
without help from other sources? Our understanding of those in or near poverty is
primarily based upon the analysis of either annual income or the income distribution
from cross-sectional survey data. It has been argued in the literature that this type of
data can be misleading when faced with questions pertaining to transitions in and out
of poverty. Studies of the persistence of poverty should focus on individuals and their
families, in conjunction with labor market situations, in order to provide an insight
into why the situation continues.

Using the Survey of Income and Program Participation (SIPP) 1996 panel, it was
possible to investigate low-income dynamics and to model family incomes for the
years 1996-1999. This article provides a descriptive analysis that evaluates the lowincome
dynamics of families and their exit and re-entry rates into low income. It
also investigates family income and poverty experiences based upon a componentsof-
variance model that identifies permanent and transitory factors and provides insight
into low-income dynamics.

Prior empirical research on the earnings penalty of being a tied-migrant has focused primarily on the working wives of servicemen. Over the last couple of decades the increased number of women in the armed forces makes it feasible to study the earnings of another group of tied-migrants, the husbands of servicewomen. Using data from the 2000 U.S. Census, Sample Edited Detail File (SEDF), we show that there is a consistently lower age-earnings pattern for military husbands as well as wives. These annual earnings patterns capture the essence of, but do not provide an explanation for, the observed annual earnings differences. These differences are evaluated using multivariate analysis accounting for sample selectivity. Moreover, decomposition analysis strongly suggests that demand-side factors account for a greater portion of the differences in annual earnings than has been previously acknowledged and, therefore, that retention might respond favorably to job matching assistance and/or employer hiring incentives offered military spouses.

Identifying the earnings penalty associated with being a tied mover has focused on the working wives of servicemen. However, the number of women serving in the armed forces now makes it feasible to study the earnings losses of a group of tied-mover males, the husbands of servicewomen. Using data from the 2000 U.S. Census, the authors identified a sample of such men and compare their earnings to civilian husbands of working civilian wives to extend and generalize on tied-mover earnings effects. Multivariate analysis accounting for selection bias and controlling for migration, demographic, household, and labor market characteristics shows that military husbands earn about 70 percent of civilian husbands, whereas military wives earned about 50 percent of civilian wives. Since different estimation procedures provide comparable outcomes regardless of gender, these results reveal a detrimental earnings effect for military husbands similar to earlier estimates for military wives.

The translog functional form imposes no a priori restrictions on the substitution possibilities between the factor inputs, by relaxing the assumption of strong separability, and the CES–translog cost function specification allows for testing homothetic technology with Hicks‐neutral technical change. In this paper an n‐factor CES–translog production function is presented which develops the parameters to directly assess scale effects from those due to technology in the production structure. In addition, by applying Shephard's lemma it was possible to derive the input demand functions, as well as the partial elasticities of substitution and the cross‐partial price elasticities of demand for a generalized CES–translog production structure.

Factors that most likely influence a veteran to have health insurance & to use a Veterans Affairs (VA) medical facility (joint-choice case) were assessed by analyzing data from the third Survey of Veterans (N = 9,442 respondents, 1987) under a bivariate probit specification. Findings indicate that a veteran's decision to use a VA facility is largely dependent on whether the individual has some type of health insurance coverage. A simple simulation highlights the impact of veterans' disability status, relative to their household income, in terms of their probabilities of having health insurance & using a VA facility. Changes in how health care is provided to vulnerable populations could increase the demand for VA care, given that veterans with low incomes & disabilities have a greater propensity to use VA. These findings could provide a baseline for the potential increased usage of VA care. 3 Tables, 25 References. Adapted from the source document.