Date/Time
Date(s) - 25/01/2023
2:00 pm - 3:30 pm
Category(ies) No Categories
IASS Webinar 25: Unemployment Estimates for the Brazilian Labour Force Survey Using State-Space Models
25 January 2023 at 2pm – 3:30pm (CET)
All are invited to the webinar, organised by the International Association for Survey Statisticians.
Please register for the IASS Webinar at:
https://us06web.zoom.us/webinar/register/WN_3qVk_0coTXyi3akDZjcuHQ
After registering, you will receive a confirmation email containing information about joining the webinar. There will be time for questions. The webinar will be recorded and made available on the IASS and ISI web site. See below for the abstract and biography of the speakers.
Webinar Abstract
The Brazilian Labour Force Survey (BLFS) is a quarterly rotating panel survey with 80% sample overlap between two successive quarters. We will present time series models developed to produce model-based single month estimates at national level as well as small area (state-level) estimates, which are both at a higher frequency than those currently being published. In addition, multivariate time series models that integrate survey data and Google Trends series for nowcasting are considered. High dimensionality problems are solved using a dynamic state space model. In this case, we also discuss the choice of search terms and approaches for targeting predictors in the dimensionality reduction process. The models account for the autocorrelation due to sample overlap and the increased volatility in the labour force series in 2020. This is joint work with Luna Hidalgo (IBGE) e and Jan van den Brakel (Statistics Netherlands and Maastricht University).
Biography
Caio Gonçalves is a Researcher at João Pinheiro Foundation, Regional Statistical Office of the state of Minas Gerais in Brazil. PhD Candidate in Population, Territory and Official Statistics at the National School of Statistical Sciences (ENCE) from the Brazilian Institute of Geography and Statistics (IBGE). His developing thesis is about producing labour force model-based figures with higher frequency and small domains using time series analysis for repeated surveys. He also works as a Consultant at IBGE developing models to estimate the population at census enumeration areas using satellite images, administrative records and survey data. His main interest areas are model-based approaches for producing official/public statistics, big data, time series analysis and small area estimation.
Denise Silva is retired and voluntary Principal Researcher of the National School of Statistical Sciences (ENCE) from the Brazilian Institute of Geography and Statistics (IBGE) and Senior Associate Researcher at the Society for the Development of Scientific Research (SCIENCE). She completed her PhD in Statistics at the University of Southampton and has been working as a survey methodologist for more than 35 years as well as a lecturer at graduate and undergraduate levels. Denise was president (2019-2021) of the International Association of Survey Statisticians (IASS), is an elected member of the International Statistical Institute (ISI) and is an editor of the Statistical Journal of the IAOS. Her main areas of interest are survey methods, official/public statistics, small area estimation and time series analysis.