Originally HHP consisted of two samples: a Budapest subsample and a national sample. The national sample consisted of approximately 2000 hhs and the capital subsample about 600. This two subsamples were treated separately till the 4^th wave. Because of the lowered sample size, it was necessary to unify the subsamples.

After finishing the HHP study a new version of database was created and the two subsamples were merged from the first wave.
 
 

1^st wave, 1992 (Individual and household weight)

• The fact that the Hungarian capital was oversampled in the new, unified sample made necessary a correctional weight for the first wave (SULY92). The original 2050 hhs national sample for the first wave was supposed to be a representative sample of non-institutional Hungarian households and individuals living in these households.
• Households living in Budapest and their member have a weighting value of 0,4. Other (non-Budapest) households got a value of 1. This value is universal in terms that each household member got the same value as his or her household. Since there is no difference between individual and household weights, only one variable was created. This weight is called as SULY92. Every each individual and household participated in the first wave has a weight value of 1 or .40 on this variable.
• Note this results a lower weighted sample size (N=2050), than the unweighted sample size (N=2668). The weighted sample size is equal to the original national sample size.

Cross-sectional weights for adults (EGYKEnnS), for children (GYEKEnnS) and the combined individual weight (KKSULYnn), 2nd-6th wave

• Working out the principle of weights, it was supposed that there are a "natural" panel aging: i.e. individuals die, and born, etc. Beside natural aging there is sample attrition which should be corrected by introducing weights, for certain group of people. By attrition we mean that some household dropped out from the sample, because they refuse to cooperate or move to unknown places, and can not be followed.
• Attrition than was corrected according to the main socio-demographic characteristics of sample dropouts. These characteristics are gender, age, education and settlement type. Correction hereby mean an adjustment to the sample composition of previous wave, rather than a correction to an external source like census or microcensus. Consequently, second wave was adjusted to 1^st wave, 3^rd wave to 2^nd wave, etc.
• However, this solution has some shortcomings. Weights were computed only for those who were aged 16 or more AND completed individual or substitution questionnaire. There are no adult individual weights for children aged under 16, and for those who did not complete individual questionnaire and no substitution questionnaire was administered. It is because educational information are available only from that sources, and because young children simply do not have any educational credential.
• To smooth out that problem a separate weight variable was introduced for children. (GYEKEnnS) It is simply their household weight. The computation of household weights will be discussed below.
• However there are still some individual who has no individual cross-sectional weights. Their number is ranged between 13 and 50 during the panel period. These persons are invisible for statistical procedures, when the data set is weighted.
• The following variables were used during the definition of weights:

• The weights are supposed to correct sampling attrition for the above specified (and broader) categories. If you perform analyses employing variables with narrower categories (like treating separately college degree from university level education), the results might be affected by sampling attrition.
• Based on adults' and children weights a combined (cross-sectional) individual weight (KKSULYnn) was created, so one can weight the total individual sample of HHP. This variable is simply the combination of the two weighting variables i.e., the value EGYKEnnS for adults and GYEKEnnS for children.

• Household weights were computed as the mean individual adult weights. By this we suppose that socio-economic position of households are dependent on their adult members’ resources. This solution is only one of the possible solutions, and it does not necessarily follows that this is the best one. Other option can be to use the individual weight of household head, as was the former praxis in TARKI before the introduction of this new weighting system.
• Again, it may cause some problem that some households do not have weight. It is because of missing individual weights. Specifically it means that in wave 3 and wave 5 two households have no weights.

• Household and individual level longitudinal weights were constructed for those, who participated in more than one waves, and were already member in the starting panel (1^st wave) sample. For example longitudinal weight for the 3^rd wave is available for those who participated in 1^st, 2^nd and 3^rd wave. Similarly, longitudinal weight for the last (6^th) wave refers to that subsample of individuals who were participants in the whole panel period (from the 1^st to the 6^th wave).
• Individual longitudinal weights (EGYLOnnS) for persons aged 16 and older were computed as the product of cross-sectional individual weights.
• Longitudinal household weights (HAZLOnnS) were computed as the mean of longitudinal individual weights of persons living in the same household.
• Longitudinal weights for children (GYELOnnS) were created in the same way as their cross-sectional weights were defined. Children simply got their household longitudinal weight.
• Similar to combined individual cross-sectional weights a combined individual longitudinal weight variable (KLSULYnn) was defined as the combination of EGYLOnnS and GYELOnnS.