Using Paradata to Monitor and Improve the Collection Process

in Annual Business Surveys

BySylvie DeBlois, Statistics Canada

Rose-Carline Evra, Statistics CanadaICES-III, Montreal, June 19th, 2007

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OUTLINE

Introduction

Score Function

Paradata

Score Function Recent Update

Future Developments

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Introduction

The Unified Enterprise Survey (UES) is an annual economic survey on financial and characteristic variables, which has been conducted by Statistics Canada since 1998. It combines many surveys.

Average collection period: February to early October

Collection Processing System: Blaise

More than 48,000 questionnaires each year.

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UES Questionnaire

UES includes Services, Trades, Manufactures, Agriculture (aquaculture) and Transportation (couriers and taxi & limousine) surveys.

A questionnaire has about 7 to 10 sections (the number of sections varies depending on the survey):

Introduction (Stats Act - Confidentiality, Respondent info)RevenueExpensesEvents that may have affected business units…Comments

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Introduction

Collection Process:Mail-out of questionnaires Follow-up in case of non-response for some units / Mail-back of questionnairesVerification of received questionnaires / EditsCoding of questionnairesImaging & Data Capture

Sometimes during the collection period, follow-ups are required due to non-response. The score function is used to determine the priority of an enterprise in follow-up.

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Introduction

Collection follow-up tool: Score function (SF)Annual Survey of Manufactures (ASM) score function

Non-ASM score function

Both score functions have their own ways of calculating scores, defining cells and priorities.

This presentation will focus mainly on the Non-ASM score function.

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Score Function

Reduces collection costs yet retains data quality.

Similar to the collection goal of obtaining a high high weighted coverage response rateweighted coverage response rate.

PRIORITY 1: Extensive follow-up for the larger revenue Collection Entities (CE) in cases of non-response.

PRIORITY 0: Minimum follow-up for the smaller CE’s in cases of non-response.

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Useful definitions

A

B

C

DE

Cell

Sampling Unit (part of the enterprise within the cell)

Establishment

NAICS: North American IndustryClassification System (5-digitnumber)

NAICS = YYYYY PROV = AA

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Method: Initial Scores

Within each cell, calculate the score for each UES sampling unit (SU).

Score = the sample weighted revenue of the SU as a percentage of the cell’s total revenue.

Sample weight: UES sampling weightRevenue: Sampling Revenue

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Method: Initial Scores

Cell: For Distributive Trades & Aquaculture: NAICS * Province

For Transportation: NAICS*Prov*Stratum(Take All /Take Some)

For Services: NAICS*Prov*Stratum(TA /TS)* Type of questionnaire (long / characteristic)

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Method: Initial Scores

Within each cellSort SUs by descending score

Cumulate to the survey’s target coverage threshold for the Priority=1s, and the rest are Priority=0s.

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Method: Dynamic Scores

During collection process, twice a week, we:

1. receive updated response codes;

2. recalculate the scores within the cell (i.e. make it dynamic) to update priorities;

3. update priorities on Blaise, the collection tool.

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Method: Dynamic Scores

As collection proceeds:Response (received or completed) questionnaires contribute to the cell thresholdNon-response questionnaires contribute nothing to the threshold Out-of-scope are removed entirely from the cell (reduces the cell’s revenue total)In-Progress questionnaires are still being collected (include appointments)

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During Collection

New total weighted revenue for the CELL (exclude the OOS).

Priority 1’s or 0’s received or completed contribute to reaching the CELL threshold.

In progress

NON-RESPONSE

OOS

Threshold= 65% (308,750k)

In progress

Priority 1

Priority 0

Received or Completed

50,000k

CELL: XXXXXXXX Total: 475,000k

15% reached

50% left to do

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Method: Dynamic Scores

Has the cell reached its threshold?

If yes, stop follow-up.

If no, recalculate scores using In-progress units and the remaining threshold.

Some cells must close due to lack of In-Progress questionnaires

Some In-progress Priority 0s may be promoted to Priority 1s.

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Paradata

Definition: All variables directly related to data collection process

Currently used:Response codeAppointment reason (edit – data collection)Appointment date (recently added)Currently used only by Annual Survey of Manufactures (ASM):

Number of attempts, commodity revenue and shipment revenue

Could possibly be used:Type of contact with the respondentPrevious year’s response codeType of reminder sent / Date / # (mail, remail,…)Others

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Score Function Recent Update

Recently, a study was done on the impact of appointments on the response rate (for reference year 2003).

Following our findings the “appointment date” was added as paradata into the score function.

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Appointments: The Study

During the collection period, an appointment might be scheduled with the respondent.

“Does the fact of having a appointment affect the response rate?”

Note: When an appointment is made and it’s a priority 1 questionnaire, it remains in the SF with a priority 1 with the “still in progress status”. Therefore, no priority 0 will be put as priority 1.

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Response Rates: app versus no app

The response rate is significantly lower for the questionnaires with an appointment.

RY2003 (Non-ASM surveys)

Response Rates : app versus no app APP NO APP TOTAL

Response 4070 6644 10714 (38%) % 42% 51% 47%

Non-response 5162 4202 9364 (55%) % 53% 32% 41%

Out-of-Scope 534 2233 2767 (19%) % 5% 17% 12%

TOTAL 9766 13069 22835

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Response Rates: Scheduling of the appointment

The response rate is significantly lower for questionnaires when the appointment is made toward the end of the collection period.

Response Rates according to the Time of the Appointment

None Early Middle Late Respondents 51% 46% 37% 29% NonRespodents 33% 47% 58% 70%

Out-of-Scope 16% 7% 5% 1%

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Other Facts

The longer a questionnaire stays in appointment, the greater is the probability of that questionnaire being a non-response at the end of the collection period.

23.8% of the questionnaires with appointments were classified as non-respondent, because at the end of the collection period their cases were still open.

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Appointment: Conclusion

When possible, we should avoid making an appointment. Especially, at the end of the collection period.

In cases of appointments, follow-up should occur soon after the appointment is made. An appointment is still a good way of improving the response rates.

The treatment of the appointments in the score function should be modified. Extra “In progress” units will be promoted to priority 1 in order to compensate for possible non-response.

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Facts / Findings

A unit may not have an appointment date or may have one that is constantly changing.

Many appointment dates are within a few weeks.

It was decided to only consider units that have a late appointment date, and there are not many.

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Facts / Findings

An appointment can mean many things.

Many unexpected factors caused the changes to be less efficient than initially expected.

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Human Errors

The interviewer:Enters the wrong value for a variable (for example, appointment reason)

Does not update a key variable (for example, appointment date)

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System Problems

System FailuresAs a result, some variables are affected, like the number of attempts.

Files not properly loadedMissing values or variables

Some follow-up events occur outside of the system

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Theoretical / Practical

Appointment date is also used to set the “remail” (remail of questionnaire) and fax date.

Also, some appointment dates are default dates (differ from survey to survey).

Appointment is also used as a reminder to the interviewer to call a respondent unavailable at the moment of the initial call.

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Future Developments

Establish what is really an appointment; do more studies on the appointments.

Study more paradata to “quantify” the importance of each unit, give priority and improve the score function.

Introduction of a cost function to help assign the priority and the type of follow-up.

Combine the ASM score function and the Non-ASM score function.

Thank You / Merci!!!Questions ???

Pour plus d’information veuillez contacter / For more information, please contact:

Rose.Evra@statcan.ca ou / or

Sylvie.DeBlois@statcan.ca