Estimation in capture–recapture models when covariates are subject to measurement errors and missing data

For capture–recapture models when covariates are subject to measurement errors and missing data, a set of estimating equations is constructed to estimate population size and relevant parameters. These estimating equations can be solved by an algorithm similar to the EM algorithm. The proposed method is also applicable to the situation when covariates with no measurement errors have missing data. Simulation studies are used to assess the performance of the proposed estimator. The estimator is also applied to a capture–recapture experiment on the bird species Prinia flaviventris in Hong Kong. The Canadian Journal of Statistics 37: 645–658; 2009 © 2009 Statistical Society of Canada     

Can We Compare Life Satisfaction Between Nationalities? Evaluating Actual and Imagined Situations

Do differences in reported life satisfaction between societies reflect real differences or do they reflect cultural differences in the way people rate their experiences? Study 1 showed that imagining better or worse life situations affected student respondents’ ratings of their own life satisfaction, as predicted by range–frequency theory. Study 2 investigated how German and Polish students rated their actual life satisfaction and how satisfied they would be under three imagined scenarios. Study 3 similarly compared Danish and Hungarian students. Both studies found significant differences in the rating of the hypothetical situations, and moderate correlations between ratings of satisfaction in the hypothetical situations and reality, but in neither study were national differences in actual satisfaction predicted by differences in hypothetical satisfaction. Overall, the results suggest that national differences in rated life satisfaction are real rather than reflecting differences in how satisfaction is rated.     

Estimates of Spatial Prices in India and Their Sensitivity to Alternative Estimation Methods and Choice of Commodities

This paper provides Indian evidence on sub-national PPPs that point to considerable spatial price heterogeneity within the country, based on Indian National Sample Survey (NSS) data. The prices of various commodities have been generated from the household specific unit values obtained from the information on expenditures and quantities from the NSS unit records. This paper shows that the CPD model, proposed in the cross country context, can be adapted to the household context to estimate spatial prices in the intra country context. The proposed CPD based model is shown to be formally equivalent to certain well known fixed weight price indices under certain parametric configurations. The empirical contribution includes a systematic comparison between the spatial price indices from alternative models, namely the CPD and utility based models, and the result that the utility based methods point to a much greater extent of spatial price heterogeneity than is suggested by the CPD type models. The results also record the sensitivity of the spatial price indices to the choice of commodities in the utility based approach. The pairwise comparison of estimates suggests that commodity selection may be more important than model selection in its impact on the spatial price estimates, though the latter is important as well. The study provides estimates of rural–urban differentials in spatial price indices that suggest some interesting differences between the constituent states. The results make a strong case for further research on the topic of sub-national PPPs in the context of large heterogeneous countries.     

M-quantile models with application to poverty mapping

Over the last decade there has been growing demand for estimates of population characteristics at small area level. Unfortunately, cost constraints in the design of sample surveys lead to small sample sizes within these areas and as a result direct estimation, using only the survey data, is inappropriate since it yields estimates with unacceptable levels of precision. Small area models are designed to tackle the small sample size problem. The most popular class of models for small area estimation is random effects models that include random area effects to account for between area variations. However, such models also depend on strong distributional assumptions, require a formal specification of the random part of the model and do not easily allow for outlier robust inference. An alternative approach to small area estimation that is based on the use of M-quantile models was recently proposed by Chambers and Tzavidis (Biometrika 93(2):255–268, 2006) and Tzavidis and Chambers (Robust prediction of small area means and distributions. Working paper, 2007). Unlike traditional random effects models, M-quantile models do not depend on strong distributional assumption and automatically provide outlier robust inference. In this paper we illustrate for the first time how M-quantile models can be practically employed for deriving small area estimates of poverty and inequality. The methodology we propose improves the traditional poverty mapping methods in the following ways: (a) it enables the estimation of the distribution function of the study variable within the small area of interest both under an M-quantile and a random effects model, (b) it provides analytical, instead of empirical, estimation of the mean squared error of the M-quantile small area mean estimates and (c) it employs a robust to outliers estimation method. The methodology is applied to data from the 2002 Living Standards Measurement Survey (LSMS) in Albania for estimating (a) district level estimates of the incidence of poverty in Albania, (b) district level inequality measures and (c) the distribution function of household per-capita consumption expenditure in each district. Small area estimates of poverty and inequality show that the poorest Albanian districts are in the mountainous regions (north and north east) with the wealthiest districts, which are also linked with high levels of inequality, in the coastal (south west) and southern part of country. We discuss the practical advantages of our methodology and note the consistency of our results with results from previous studies. We further demonstrate the usefulness of the M-quantile estimation framework through design-based simulations based on two realistic survey data sets containing small area information and show that the M-quantile approach may be preferable when the aim is to estimate the small area distribution function.     

India’s Social Development in a Decade of Reforms: 1990–91/1999–2000

The economic reforms initiated in India in 1991 have brought about visible upliftment of economic conditions of the country. This paper examines if the economic process is associated with an enhancement of India’s social development in equal measure in the reform decade of nineties. Ray (1989) considered thirteen social indicators of India and constructed the country’s social development index (SDI) as a certain weighted average of the selected indicators, for the years between 1950–51 and 1975–76. The present work broadly follows Ray (1989) in tracking the social development in the decade of economic reforms from 1990–91 to 1999–2000. The movement of SDI in nineties has been compared with the movements of India’s per capita income and plan expenditure on the social sector. The results show that though there has been growth in the social sector, it is not by far quite encouraging and perhaps more needs to be done in the social sector. The views expressed in the article are those of the author and not of the institution he serves.     

国家、民族、社区——美国国家公园建设的经验及教训

美国国家公园建设过程中,以国家为主导,注重国家意识,定位服务功能,体现其教育理念,并在此过程中将管理和利用模式由开始的保护转变为现在的保护与利用并行,为全世界提供了一个成功的模板。但在其100年的发展过程中,环境的破坏,原住民权利的漠视,游客管理的混乱,是其曾遇到或正在面临的问题。建议我国在进行国家公园建设时,应扬长避短,突出国家名义,强调社区参与和游客管理先行,并注重国家公园的公益性和教育功能。