6. Accuracy and reliability |
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6.1. Accuracy - overall |
6.1.1 How good is the accuracy? |
Medium |
6.1.2 What are the main factors lowering the accuracy? |
Coverage error Measurement error |
6.1.3 If Other, please specify |
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6.1.4 Additional comments |
For cereals and oilseeds produced in Ireland, we are satisfied that both the supply and use of these items are moderately reliable. However, we have concerns about the quality of the data on cereals and oilseeds that are not produced domestically. For these items, we are dependent on external trade data to determine supply volumes. These trade data can contain significant errors in recorded volumes and these errors may be compounded by the use of incorrect CN codes. The items of concern are maize, durum wheat, sunflower, soya and maize |
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6.2. Sampling error |
These questions only apply to surveys. If there is more than one survey, please describe the main survey below and the additional ones in table 6.2 of the annexed Excel file |
6.2.1 Name/Title |
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6.2.2 Methods used to assess the sampling error |
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6.2.3 If Other, please specify |
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6.2.4 Methods used to derive the extrapolation factor |
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6.2.5 If Other, please specify |
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6.2.6 If coefficients of variation are calculated, please describe the calculation methods and formulas |
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6.2.7 Sampling error - indicators |
Please provide the coefficients of variation in table 6.2 of the annexed Excel file |
6.2.8 Additional comments |
Not relevant for 2020 as no survey data was used for estimating December on farm stocks. |
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6.3. Non-sampling error |
See sections below. |
6.3.1. Coverage error |
Census
These questions only apply to censuses. If there is more than one census, please describe the main census below and the additional ones in table 6.3 of the annexed Excel file |
6.3.1.1 Name/Title |
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Over-coverage |
6.3.1.2 Does the sample frame include wrongly classified units that are out of scope? |
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6.3.1.3 What methods are used to detect the out-of scope units? |
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6.3.1.4 Does the sample frame include units that do not exist in practice? |
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6.3.1.5 Over-coverage - rate |
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6.3.1.6 Impact on the data quality |
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Under-coverage |
6.3.1.7 Does the sample frame include all units falling within the scope of this survey? |
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6.3.1.8 If Not, which units are not included? |
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6.3.1.9 How large do you estimate the proportion of those units? (%) |
[0-100] |
6.3.1.10 Impact on the data quality |
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Misclassification |
6.3.1.11 Impact on the data quality |
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Common units |
6.3.1.12 Common units - proportion |
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6.3.1.13 Additional comments |
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Sample survey
These questions only apply to surveys. If there is more than one survey, please describe the main survey below and the additional ones in table 6.3 of the annexed Excel file |
6.3.1.14 Name/Title |
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Over-coverage |
6.3.1.15 Does the sample frame include wrongly classified units that are out of scope? |
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6.3.1.16 What methods are used to detect the out-of scope units? |
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6.3.1.17 Does the sample frame include units that do not exist in practice? |
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6.3.1.18 Over-coverage - rate |
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6.3.1.19 Impact on the data quality |
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Under-coverage |
6.3.1.20 Does the sample frame include all units falling within the scope of this survey? |
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6.3.1.21 If Not, which units are not included? |
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6.3.1.22 How large do you estimate the proportion of those units? (%) |
[0-100] |
6.3.1.23 Impact on the data quality |
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Misclassification |
6.3.1.24 Impact on the data quality |
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Common units |
6.3.1.25 Common units - proportion |
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6.3.1.26 Additional comments |
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Administrative data
These questions only apply to administrative sources. If there is more than one administrative source, please describe the main source below and the additional ones in table 6.3 of the annexed Excel file |
6.3.1.27 Name/Title of the administrative source |
External trade data |
Over-coverage |
6.3.1.28 Does the administrative source include wrongly classified units that are out of scope? |
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6.3.1.29 What methods are used to detect the out-of scope units? |
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6.3.1.30 Does the administrative source include units that do not exist in practice? |
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6.3.1.31 Over-coverage - rate |
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6.3.1.32 Impact on the data quality |
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Under-coverage |
6.3.1.33 Does the administrative source include all units falling within the scope of this survey? |
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6.3.1.34 If Not, which units are not included? |
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6.3.1.35 How large do you estimate the proportion of those units? (%) |
[0-100] |
6.3.1.36 Impact on the data quality |
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Misclassification |
6.3.1.37 Impact on the data quality |
Unknown |
6.3.1.38 Additional comments |
It is currently not possible to assess the impact of incorrect CN codes on our estimates, particularly for those crops that are not produced domestically. |
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6.3.2. Measurement error |
Census
These questions only apply to censuses. If there is more than one census, please describe the main census below and the additional ones in table 6.3 of the annexed Excel file |
6.3.2.1 Name/Title |
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6.3.2.2 Is the questionnaire based on usual concepts for respondents? |
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6.3.2.3 Number of censuses already performed with the current questionnaire? |
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6.3.2.4 Preparatory testing of the questionnaire? |
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6.3.2.5 Number of units participating in the tests? |
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6.3.2.6 Explanatory notes/handbook for surveyors/respondents? |
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6.3.2.7 On-line FAQ or Hot-line support for surveyors/respondents? |
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6.3.2.8 Are there pre-filled questions? |
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6.3.2.9 Percentage of pre-filled questions out of total number of questions |
[0-100] |
6.3.2.10 Other actions taken for reducing the measurement error? |
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6.3.2.11 Additional comments |
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Sample survey
These questions only apply to surveys. If there is more than one survey, please describe the main survey below and the additional ones in table 6.3 of the annexed Excel file |
6.3.2.12 Name/Title |
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6.3.2.13 Is the questionnaire based on usual concepts for respondents? |
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6.3.2.14 Number of surveys already performed with the current questionnaire? |
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6.3.2.15 Preparatory testing of the questionnaire? |
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6.3.2.16 Number of units participating in the tests? |
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6.3.2.17 Explanatory notes/handbook for surveyors/respondents? |
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6.3.2.18 On-line FAQ or Hot-line support for surveyors/respondents? |
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6.3.2.19 Are there pre-filled questions? |
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6.3.2.20 Percentage of pre-filled questions out of total number of questions |
[0-100] |
6.3.2.21 Other actions taken for reducing the measurement error? |
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6.3.2.22 Additional comments |
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6.3.3. Non response error |
Census
These questions only apply to censuses. If there is more than one census, please describe the main census below and the additional ones in table 6.3 of the annexed Excel file |
6.3.3.1 Name/Title of the survey |
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6.3.3.2 Unit non-response - rate |
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6.3.3.3 How do you evaluate the recorded unit non-response rate in the overall context? |
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6.3.3.4 Measures taken for minimising the unit non-response |
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6.3.3.5 If Other, please specify |
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6.3.3.6 Item non-response rate |
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6.3.3.7 Item non-response rate - Minimum |
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6.3.3.8 Item non-response rate - Maximum |
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6.3.3.9 Which items had a high item non-response rate? |
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6.3.3.10 Additional comments |
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Sample survey
These questions only apply to surveys. If there is more than one survey, please describe the main survey below and the additional ones in table 6.3 of the annexed Excel file |
6.3.3.11 Name/Title of the survey |
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6.3.3.12 Unit non-response - rate |
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6.3.3.13 How do you evaluate the recorded unit non-response rate in the overall context? |
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6.3.3.14 Measures taken for minimising the unit non-response |
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6.3.3.15 If Other, please specify |
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6.3.3.16 Item non-response rate |
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6.3.3.17 Item non-response rate - Minimum |
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6.3.3.18 Item non-response rate - Maximum |
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6.3.3.19 Which items had a high item non-response rate? |
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6.3.3.20 Additional comments |
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6.3.4. Processing error |
Census
These questions only apply to censuses. If there is more than one census, please describe the main census below and the additional ones in table 6.3 of the annexed Excel file |
6.3.4.1 Name/Title |
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6.3.4.2 Imputation - rate |
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6.3.4.3 Imputation - basis |
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6.3.4.4 If Other, please specify |
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6.3.4.5 Additional comments |
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Sample survey
These questions only apply to surveys. If there is more than one survey, please describe the main survey below and the additional ones in table 6.3 of the annexed Excel file |
6.3.4.6 Name/Title |
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6.3.4.7 Imputation - rate |
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6.3.4.8 Imputation - basis |
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6.3.4.9 If Other, please specify |
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6.3.4.10 How do you evaluate the impact of imputation on Coefficients of Variation? |
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6.3.4.11 Additional comments |
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6.3.5. Model assumption error |
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6.4. Seasonal adjustment |
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6.5. Data revision - policy |
Routine revisions for year N are made in years N+2 and N+3. These revisions occur because the trade data used in compiling the supply balances are not complete until year N+2, with possible revisions also made in year N+3. Non routine revisions are very rare and would only occur in the event of a major error being detected in the underlying data or if there is a revision made to the methodology used to compile the supply balances. |
6.6. Data revision - practice |
6.6.1 Data revision - average size |
Revisions were made to the trade data used to compile the supply balances for 2018 and 2019. Total exports for 2019 were revised down by 1 tonne (-0.0004%). Total imports for 2018 were revised by -4,431 tonnes (-0.15%)while exports were revised by -81 tonnes (-0.5%). |
6.6.2 Were data revisions due to conceptual changes (e.g. new definitions) carried out since the last quality report? |
No |
6.6.3 What was the main reason for the revisions? |
Updated trade data |
6.6.4 How do you evaluate the impact of the revisions? |
Not important |
6.6.5 Additional comments |
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