Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics for Economist Ch. 17 Unemployment Rate Analysis 1.Analysis on Economically Active Population 2.Designing Unemployment Rate Analysis in Sampling Method 4.Weighting on Samples 5.Standard Error 6.Bias

Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics STATISTICS 2/16 INDEX 1 Analysis on Economically Active Population 2 Designing Unemployment Rate Analysis in Sampling Method 4 Weighting on Samples 5 Standard Error 6 Bias

Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics STATISTICS 3/16 Analysis on Economically Active Population 1. Analysis on Economically Active Population U/E Rate Population above Age 15 Non-Economically Active Population Economically Active Population Employed Unemployed Labor force participation rate - Ratio of Economically Active Population to Population above age 15 Unemployment Rate -Ratio of Unemployed Population to Economically Active Population Korea National Statistics Office Measuring Unemployment Rate using the Data from Census on Economically Active Population Korea National Statistics Office Measuring Unemployment Rate using the Data from Census on Economically Active Population

Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics STATISTICS 4/16 INDEX 1 Analysis on Economically Active Population 2 Designing Unemployment Rate Analysis in Sampling Method 4 Weighting on Samples 5 Standard Error 6 Bias

Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics STATISTICS 5/16 Designing Unemployment Rate Analysis in Designing Unemployment Rate Analysis in 1997 Sampling Framework  10% Sampling Cluster -Sampling Data Based on National Census (Sampling Cluster must contain at least 10% of All Administrative districts) -The Households included in Sampling Cluster represent All of Ordinary Households in The Country. A Population in use Sampling Framework of E.A.P. Survey We use 10% Sampling Cluster-drawn out form all administrative districts- as Sampling Framework in E.A.P Survey (E.A.P = Economically Active Population)

Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics STATISTICS 6/16 Sample Size  Decide Sample Size Sample size of E.A.P Survey -Designated number of sample in each cluster at survey in 1997  Small Large  Budget Wasting Unreliable In the level of satisfying Target Precision, Each Local office decide sample size considering workforce and budget Designing Unemployment Rate Analysis in Designing Unemployment Rate Analysis in 1997

Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics STATISTICS 7/16 INDEX 1 Analysis on Economically Active Population 2 Designing Unemployment Rate Analysis in Sampling Method 4 Weighting on Samples 5 Standard Error 6 Bias

Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics STATISTICS 8/16 3. Sampling Method Multi-Stage Cluster Sampling Drawing out Survey Area Dividing Survey Area Drawing out Sampling Cluster Deciding Sampling Framework After Dividing whole Country in accordance with administrative district,We Confirm the Sampling Framework consisting of 10% sampling cluster of 22,029, and then make groups according to the guidelines Drawing out Random Quota Samples as desire Diving Survey Area in The Household number Basis (Adjacent 8 Households) Cluster sampling 3 surveying areas-24 Households- from each Sampling Cluster. After Drawing out 1 Survey area in Random, Survey Northern and Clockwise also

Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics STATISTICS 9/16 INDEX 1 Analysis on Economically Active Population 2 Designing Unemployment Rate Analysis in Sampling Method 4 Weighting on Samples 5 Standard Error 6 Bias

Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics STATISTICS 10/16 4. Weighting on Samples Weighting  Why Weighting does matter?  How do we give the weight on Samples? Adjust the revealed unbalance in the sampling process trough weighting - Because There ’ s no 1 on 1 relation between Samples in District and Households in District, A household in certain administrative district would have different probability to be included in the Sample - Other Factors like Gender and Age would have effect on the probability that Someone to be included the Sample A Weighting process should make Each Sub-sample would represent the Component Ratio of the Population in Adjusted Sample Each Individual included in sample should have different weight according to residence, gender, age… etc.

Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics STATISTICS 11/16 INDEX 1 Analysis on Economically Active Population 2 Designing Unemployment Rate Analysis in Sampling Method 4 Weighting on Samples 5 Standard Error 6 Bias

Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics STATISTICS 12/16 4. Standard Error In E.A.P survey, Applying Multi-Stage Cluster Sampling method Cluster Sample If One survey area are included, The probability adjacent areas are chosen would get larger Random Sample The event one survey area get chosen and the event adjacent area get chosen are statistical independent Information S.E. As The Cluster sample has less information compared to The Random sample, The Formula used in calculating Standard Error of Random Sample does not hold.

Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics STATISTICS 13/16 4. Standard Error Half-Sample Method  How to know whether One Estimate Has real confidence or not? Doing identical survey independently again, then Comparing the results- this method would indicate the confidence of first survey, But there is a Budget concentration.  How to get same effect without doing repetition? Instead of repetition, We use half-sample. Dividing given sample to two part, then get the estimates from the each other (Half-Sample Method)  Ex.-Estimating the number of Unemployed in Korea Dividing Sample households in one survey area in half Estimate from the each half sample -1.04mil.,1.08mil One Estimate=1.06mil(average) Difference to each estimate: 20,000 (Standard Deviation) Unemployment in Korea = 1.06mil  20,000

Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics STATISTICS 14/16 4. Standard Error Random Sample and Cluster Sample  Why We do not use a Random Sample in real survey? 1.Incomplete information of residence. 2.Money.  Because We must do face to face interview, Using Cluster sample makes us spend less money. (Money does matter in real world even in statistics.)  Calculating Standard Error in Cluster Sample If you want to calculate the S.E., You must know sampling method first (There needs more information related to sample). In Cluster sample, Characteristic of sample makes difference in S.E. The Half-Sample Method in cluster sample makes easier this complicated problem.

Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics STATISTICS 15/16 INDEX 1 Analysis on Economically Active Population 2 Designing Unemployment Rate Analysis in Sampling Method 4 Weighting on Samples 5 Standard Error 6 Bias

Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics STATISTICS 16/16 6. Bias Bias Sampling Bias As Sample survey does not cover whole Population, There occurs Bias if a Chosen Sample not represent the Population. In the Census-Surveying whole Population, the Omitted part is so small to consider- there’s no bias. One Household in sample represent 430 households in population, so non-response of one household has great impact on survey result. In survey, A Omitted household is recorded to have identical contents that is from a adjacent household, This is irrational. Non-response Bias Used Criteria like Having a Job, ability to work, Searching for job…etc. are arbitrary. There is difficulty to distinguish Employed/Unemployed. Obscure in Classification A Bias is a worse problem than a Standard Error. In Biased Sample, We can not notice the existence of a bias after examining the data.