Journal of the Royal Statistical Society. Series A (Statistics in Society)
Applications and Case Studies Improving the Quality of Economic Data: Lessons from the HRS and AHEAD [статья]
Опубликовано на портале: 26-04-2003F. Thomas Juster, James P. Smith Journal of the Royal Statistical Society. Series A (Statistics in Society). 1997. Vol. Vol. 92. No. 440. P. pp. 1268-1278.
Missing data are an increasingly important problem in economic surveys, especially when trying to measure household wealth. However, some relatively simple new survey methods such as follow-up brackets appear to appreciably improve the quality of household economic data. Brackets represent partial responses to asset questions and apparently significantly reduce item nonresponse. Brackets also provide a remedy to deal with nonignorable nonresponse bias, a critical problem with economic survey data.
Producing Monthly Estimates of Unemployment of Employment Accounting to the International Labour Definition [статья]
Опубликовано на портале: 22-09-2003David Steel Journal of the Royal Statistical Society. Series A (Statistics in Society). 1997. Vol. Vol. 160. No. 1. . P. pp. 5-46..
Monthly unemployment statistics are available in Britain from a monthly count of the number of people claiming unemployment-related benefits. There has been considerable debate on the appropriateness of this measure. Unemployment and employment statistics are available quarterly from the Labour Force Survey (LFS), using International Labour Office (ILO) definitions. In this paper various options for producing monthly unemployment estimates according to the ILO definition are examined. Methods considered are a monthly LFS, calculating rolling averages from the quarterly LFS, and methods which combine LFS and claimant count data. It is proposed that a monthly LFS of 60 000 households be introduced which can produce monthly estimates of total unemployment and more detailed estimates quarterly. Such a survey would also fill an important gap by providing monthly employment statistics which are needed to provide a complete picture of the labour market.
Опубликовано на портале: 19-07-2004Juha M. Alho Journal of the Royal Statistical Society. Series A (Statistics in Society). 1997. Vol. 160. No. 1. P. 71-85.
Current official population forecasts differ little from those that Whelpton made 50 years ago either in the cohort-component methodology used or in the arguments used to motivate the assumptions. However, Whelpton produced some of the most erroneous forecasts of this century. This suggests that current forecasters should ensure that they give users an assessment of the uncertainty of their forecasts. We show how simple statistical methods can be combined with expert judgment to arrive at an overall predictive distribution for the future population. We apply the methods to a world population forecast that was made in 1994. Accepting that point forecast, we find that the probability is only about 2% that the world population in the year 2030 will be less than the low scenario of 8317 million. The probability that the world population will exceed the high scenario of 10736 million is about 13%. Similarly, the probability is only about 51% that the high-low interval of a recent United Nations (UN) forecast will contain the true population in the year 2025. Even if we consider the UN high-low intervals as conditional on the possible future policies of its member states, they appear to have a relatively small probability of encompassing the future population.