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Molnár, Gy. 2005): Az adatállomány és a rotációs panel (The Data Content and the Rotating Panel). In: Kapitány Zs Molnár, Gy Virág, I. MTA KTI, Budapest, pp. 141– 147.
|Observations in the LFS (persons)|
|15–64 years, not in full-time education||18,353||7,755||23,870|
Source: Version of the LFS of the HCSO maintained by the CERS Databank.
For the unemployment data see https://nfsz.munka.hu/tart/munkaeropiac. The GDP figures (http://www.ksh.hu/stadat_files/gdp/hu/gdp0086.html) are seasonally adjusted and measured at constant prices. Statistics for 2021 Q2 are not available yet.
If in a micro-economy two out of four people work, one of them 40 hours a week and the other 20 hours, the employment rate is 50% but FTE equals only to 1.5/4 = 37.5%.
Since the LFS only becomes representative when the entire quarterly sample is queried, the timing of interviews could affect the results when comparing January–February, March and April–June. If, for example, the inhabitants of small villages were always included in the third month of a quarter (which is not the case), their absence in the first and presence in the second period would distort comparison over time and would paint a bleaker picture of employment than it is. In view of this (moderate) risk, we also report comparisons based on quarterly data.
The fraction of workers qualified as employed without working at least one hour amounted to 3.4% during January-February compared to 7.4% in April-June.
When comparing entire quarters, FTE, adjusted for calendar effect, fell by 5.5 percentage points or 7.7%. Nevertheless, the data is distorted because the labour market situation had already deteriorated in March due to the lockdown, and therefore, the first quarter cannot entirely be regarded as a “pre-pandemic period”.
Authors' calculations based on the version of the LFS of the HCSO maintained by the CERS Databank.
There are 674 and 656 observations in the two periods considered of individuals identifying themselves as Roma primarily or secondarily.
There are limitations to using LFS for reconstructing developments between two waves. Workers in employment during waves t and t + 1, may have been unemployed between the two interviews and if they became unemployed or changed jobs more than once, it is impossible to determine the length of unemployment. If only once, then it is possible to estimate based on the starting date of their employment ongoing in quarter t + 1. However, the number of status changes is not known.
In spite of the closure of schools, the proportion was far from one hundred% probably because non-formal educators (music teachers, driving instructors etc.), educational service providers and the entire staff of schools and training centres including cleaners and maintenance staff also belong to the sector. 63.4% of teachers worked from home.
For example, enterprises can report quarterly turnover, which equals the total of three-months turnover.
We do not include data from 2010 so that the estimates presented below are not distorted by the financial crisis. Data from September 2020 are not yet available.
We can calculate value added only for firms with more than 50 employees that is why we do not show the corresponding estimates. Still, the results are similar on this subsample as well.
Attrition was 9.7% in 2008 and 8.8% in 2009.
The only exception is 2020, where only data from 2018 is provided, since balance sheet and Wage Survey data from 2019 is not yet available.
The merging procedure relied on the codes of Koren – Pető (2020). If a firm is not included in the Wage Survey, we use the industry level average instead.
The standard deviation of the physical presence variable is 0.2 in the database.
If the dropout firms were simply excluded, it would implicitly suggest that attrition is unrelated to changes in turnover. This assumption is probably not true for last year's crisis.