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Sample Survey Data (sample + survey_data)

Distribution by Scientific Domains
Mathematics and Statistics28%
Business, Economics, Finance and Accounting28%

Selected Abstracts

Poverty decline, agricultural wages, and nonfarm employment in rural India: 1983,2004

AGRICULTURAL ECONOMICS, Issue 2 2009
Peter Lanjouw
Poverty; Agricultural labor; India; Nonfarm employment Abstract We analyze five rounds of National Sample Survey data covering 1983, 1987/1988, 1993/1994, 1999/2000, and 2004/2005 to explore the relationship between rural diversification and poverty. Poverty in rural India has declined at a modest rate during this time period. We provide region-level estimates that illustrate considerable geographic heterogeneity in this progress. Poverty estimates correlate well with region-level NSS data on changes in agricultural wage rates. Agricultural labor remains the preserve of the uneducated and also to a large extent of the scheduled castes and scheduled tribes. We show that while agricultural labor grew as a share of total economic activity over the first four rounds, it had fallen back to the levels observed at the beginning of our survey period by 2004. This all-India trajectory also masks widely varying trends across states. During this period, the rural nonfarm sector has grown modestly, mainly between the last two survey rounds. Regular nonfarm employment remains largely associated with education levels and social status that are rare among the poor. However, casual labor and self-employment in the nonfarm sector reveals greater involvement by disadvantaged groups in 2004 than in the preceding rounds. The implication of this for poverty is not immediately clear,the poor may be pushed into low-return casual nonfarm activities due to lack of opportunities in the agricultural sector rather than being pulled by high returns offered by the nonfarm sector. Econometric estimates reveal that expansion of the nonfarm sector is associated with falling poverty via two routes: a direct impact on poverty that is likely due to a pro-poor marginal incidence of nonfarm employment expansion; and an indirect impact attributable to the positive effect of nonfarm employment growth on agricultural wages. The analysis also confirms the important contribution to rural poverty reduction from agricultural productivity, availability of land, and consumption levels in proximate urban areas. [source]

Eastern European Attitudes to Integration with Western Europe

JCMS: JOURNAL OF COMMON MARKET STUDIES, Issue 2 2004
Anetta Caplanova
This article examines attitudes to membership of the EU and Nato amongst countries in central and eastern Europe. Sample survey data are obtained from the Eurobarometer surveys of transition and EU candidate countries. The empirical results suggest that support for membership increases with socio-economic variables such as in come and education, reflecting self-interest. But attitudinal variables are also important and, in particular, confidence in the free market economy impacts positively on support for membership. Support for EU membership is not a mirror image of that for Nato, with the differences appearing to revolve around self-interest. [source]

Microsimulation of Business Performance

INTERNATIONAL STATISTICAL REVIEW, Issue 3 2000
Philip Kokic
Summary Microsimulation of business performance based on sample survey data is a relatively underdeveloped field, but its application in government economic policy formulation is potentially great since it can be used to measure the distributional effects of change rather than just average change. Techniques which account for the dynamic response of businesses to macro level price expectations have recently been developed (Kokic et al., 1993). These allow individual level business performance to be forecast from sample survey data. In this paper we outline a general methodology for combining these forecasting techniques with Monte Carlo simulation in order to produce a microsimulation of business performance that accurately captures the true distributional characteristics of the underling survey data. Applying this methodology to Australian farm survey data, we show that these methods may be used to forecast the distribution of farm business production and performance within arbitrary subdomains of the surveyed population conditional on a given set of expected commodity price outcomes. The microsimulations reflect both the uncertainty due to climatic variation from one year to the next, which in the Australian context depends largely on geographic location, as well as the uncertainty of commodity prices. [source]

Statistical and methodological issues in the analysis of complex sample survey data: Practical guidance for trauma researchers,

JOURNAL OF TRAUMATIC STRESS, Issue 5 2008
Brady T. West
Standard methods for the analysis of survey data assume that the data arise from a simple random sample of the target population. In practice, analysts of survey data sets collected from nationally representative probability samples often pay little attention to important properties of the survey data. Standard statistical software procedures do not allow analysts to take these properties of survey data into account. A failure to use more specialized procedures designed for survey data analysis can impact both simple descriptive statistics and estimation of parameters in multivariate models. In this article, the author provides trauma researchers with a practical introduction to specialized methods that have been developed for the analysis of complex sample survey data. [source]

Wildlife Population Assessment: Past Developments and Future Directions

BIOMETRICS, Issue 1 2000
S. T. Buckland
Summary. We review the major developments in wildlife population assessment in the past century. Three major areas are considered: mark-recapture, distance sampling, and harvest models. We speculate on how these fields will develop in the next century. Topics for which we expect to see methodological advances include integration of modeling with Geographic Information Systems, automated survey design algorithms, advances in model-based inference from sample survey data, a common inferential framework for wildlife population assessment methods, improved methods for estimating population trends, the embedding of biological process models into inference, substantially improved models for conservation management, advanced spatiotemporal models of ecosystems, and greater emphasis on incorporating model selection uncertainty into inference. We discuss the kind of developments that might be anticipated in these topics. [source]

Impacts of Food and Energy Price Hikes and Proposed Coping Strategies

CHINA AND WORLD ECONOMY, Issue 6 2008
Ling Zhu
F01; Q13; Q41 Abstract Based on sample survey data for the years 2006 and 2007, we find that inflation of food and energy prices in China is moving at a slower pace than in the international market; however, the livelihood of low income groups has been significantly impacted. Urban sample households in low income groups have been shifting from consumption of high value food to lower value substitutes; and all of the rural sample households are reducing their total consumption expenditure in real terms. The Engel's coefficient of the rural household enlarged while their proportion of spending on clothing and energy declined. Farmers' households are moving toward more imbalanced diets, and the nutritional status of the poor is apparently deteriorating. The emergency-response measures that the government should implement include stopping subsidies to biofuel producers, who use foodstuffs as inputs, and providing food aid to the poor. The mid-term strategies should include anti-monopoly tactics, improving the market environment for the right competition, and eliminating price distortion. Midterm and long-term socioeconomic policy reform must be undertaken to adjust the social structure, to correct the mechanism of factor price formation, and to transform the pattern of economic growth. [source]