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Książka prezentuje nową ekonomię gospodarstwa domowego przez analizę alokacji czasu z użyciem narządzi statystycznych. Autor przeprowadził badania, których głównym celem było wyjaśnienie sposobów alokacji łącznego zasobu czasu w polskich gospodarstwach domowych w procesie maksymalizowania użyteczności z konsumpcji. Chcąc zidentyfikować czynniki, które determinują alokację czasu, odwołano się do cech społeczno-demograficznych i ekonomicznych osób i gospodarstw domowych, szczególnie zwrócono uwagę na sposoby gospodarowania czasem w zależności od płci.
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"Past research has found that subjective questions about an individuals' economic status do not correspond closely to measures of economic welfare based on household income or consumption. Survey respondents undoubtedly hold diverse ideas about what it means to be "poor" or "rich." Further, this heterogeneity may be correlated with other characteristics, including welfare, leading to frame-of-reference bias. To test for this bias, vignettes were added to a nationally representative survey of Tajikistan, in which survey respondents rank the economic status of the theoretical vignette households, as well as their own. The vignette rankings are used to reveal the respondent's own scale. The findings indicate that respondents hold diverse scales in assessing their welfare, but that there is little bias in either the economic gradient of subjective welfare or most other coefficients on covariates of interest. These results provide a firmer foundation for standard survey methods and regression specifications for subjective welfare data. "--World Bank web site.
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Detailed property histories for five parishes in the central Cheapside area of London, from the 12th to the late 17th century. It includes accounts of the parish churches, and information about the people and buildings associated with the properties.
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Over the past two decades, the causal relationship between climate change and migration has gained increasing prominence on the international political agenda. Despite recent advances in both conceptual frameworks and applied techniques, the empirical evidence does not provide clear-cut conclusions, mainly due to the intrinsic complexity of the phenomena of interest, the irreducible heterogeneity of the transmission mechanisms, some common misconceptions, and, in particular, the paucity of adequate data. This data-oriented review first summarizes the findings of the most recent empirical literature and identifies the main insights as well as the most important mediating channels and contextual factors. Then, it discusses open issues and assesses the main data gaps that currently prevent more robust quantifications. Finally, the paper highlights opportunities for exploring these research questions, exploiting the potential of the existing multi-topic and multi-purpose household survey data sets, such as those produced by the World Bank's Living Standards Measurement Study. The paper focuses on the Living Standards Measurement Study-Integrated Surveys on Agriculture program to discuss potential improvements for integrating standard household surveys with additional modules and data sources.
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This paper contributes to the debate on ways to improve the calculation of inequality measures in developing countries experiencing severe budget constraints. Linear regression-based survey-to-survey imputation techniques are most frequently discussed in the literature. These are effective at estimating predictions of poverty indicators but are much less accurate with inequality indicators. To demonstrate this limited accuracy, the first part of the paper discusses several simulations using Moroccan Household Budget Surveys and Labor Force Surveys. The paper proposes a method for overcoming these limitations based on an algorithm that minimizes the sum of the squared difference between a certain number of direct estimates of an index and its empirical version obtained from the predicted values. Indeed, when comparing the estimated results with those directly estimated from the original sample, the bias is negligible. Furthermore, the inequality indices for the years for which there are only model estimates, rather than direct information on expenditures, seem to be consistent with Moroccan economic trends.
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Over the past decade, national statistical offices in low- and middle-income countries have increasingly transitioned to computer-assisted personal interviewing and computer-assisted telephone interviewing for the implementation of household surveys. The byproducts of these types of data collection are survey paradata, which can unlock objective, module- and question-specific, actionable insights on respondent burden, survey costs, and interviewer effects. This study does precisely that, using paradata generated by the Survey Solutions computer-assisted personal interviewing platform in recent national household surveys implemented by the national statistical offices in Cambodia, Ethiopia, and Tanzania. Across countries, the average household interview, based on a socioeconomic household questionnaire, ranges from 82 to 120 minutes, while the average interview with an adult household member, based on a multi-topic individual questionnaire, takes between 13 to 25 minutes. Using a multilevel model that is estimated for each household and individual questionnaire module, the paper shows that interviewer effects on module duration are significantly larger than the estimates from high-income contexts. Food consumption, household roster, and non-farm enterprises consistently emerge among the top five household questionnaire modules in terms of total variance in duration, with 5 to 50 percent of the variability being attributable to interviewers. Similarly, labor, health, and land ownership appear among the top five individual questionnaire modules in terms of total variance in duration, with 6 to 50 percent of the variability being attributable to interviewers. These findings, particularly by module, point to where additional interviewer training, fieldwork supervision, and data quality monitoring may be needed in future surveys.
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This case study describes Bangladesh's success story using the standardized approach used by the Universal Health Coverage Studies Series (UNICO Studies Series) to provide a balanced account of the key pillars that lay behind the success of pluralism in the health system of Bangladesh. The aim is to recognize the contributions of the different actors (including the Government and the informal sector, which in the past have not been sufficiently recognized) and the strengths and weaknesses of these pillars as the needs and opportunities evolve due to emerging health issues. This lack of knowledge is an impediment to policy formulation and implementation aimed at maintaining the success of Bangladesh in the health sector. The case study suggests that there were four pillars to the successful pluralism that characterized Bangladesh: (a) effective prioritization of public financing on highly cost-effective interventions, (b) effective alignment of government and DP financing based on the mechanism of the SWAp, (c) extensive use of female CHWs and innovative NGOs, and (d) a large informal private sector that functions as a retailer of an unusually large and competitive domestic pharmaceutical industry. It should be acknowledged that determinants such as significant poverty reduction, education of girls, female labor force participation, and water and sanitation interventions outside the health sector also played a significant role in achieving better health outcomes.
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Interviewer design effects occur when data collected by the same interviewer is more similar than data collected by different interviewers. Design effects inflate survey variance and reduce the precision of estimates. Using household survey data collected via computer assisted personal interviewing (CAPI) in Sudan this paper employs a two-level mixed effects regression model to identify interviewer design effects for key variables. The study finds mean interviewer design effect values of 7 with a maximum of 16, implying a significant loss of precision. Recommendations to mitigate interviewer design effects include simplifying questions, sound survey implementation practices, and utilizing multi-way cluster robust standard errors to account for both area and interviewer clustering during data analysis.
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