The long-form is important for direct and indirect use.
For most economists, the indirect use through its importance in the design, weighting and benchmarking of every household survey, public or private, is the key issue. The household surveys such as the LFS are critical for analysis of all sorts of short- and medium-term issues.
Direct usage targets location and the attributes of persons and households. For example, it is a key source of data for commuting patterns and housing characteristics.
Businesses use the data to influence the location of facilities such as shopping complexes or major plant investments.
Small agencies use the data to plan local services. For example, the public library branch was closed in a small town called Drumbo near Woodstock. A group of us started the Drumbo Opportunity Centre (www.drumbo-opportunity.ca) to replace the lost services. We used the long-form census data to help plan the services that we would emphasize.
For JCI, key attributes include very detailed occupation, education, and labour force structure for specific industries and regions
In the last year, JCI used that directly in a detailed study for the Retail Council of Canada and HRSDC. Such studies are instrumental in work force planning to develop training and retention strategies.
In April 2009, JCI completed the most recent in a series of studies, for Minister Clement’s ministry, Industry Canada, on knowledge-based activities in detailed industries in Canada that was directly reliant on special tabulations from the long-form data.
The data can also be used to guide the development and evaluation of government activities. For these activities, the local data is particularly important.
In the spring of this year, JCI completed a study on the impact of government program at the local area utilizing census household income measures down to the township level.
Last summer, JCI developed a strategic plan report for the Toronto Central LHIN that used the long-form census data to incorporate some statistics on the socio-economic factors affecting health service demand.
Response rates have been shown to fall if a survey is transitioned from mandatory to voluntary. Achieving good response rates would require a high rate of follow up to the mail survey which is very expensive and very intrusive and difficult to target. This was the issue experienced with the U.S. trial of making the American Community Survey voluntary.
The government has actually planned to increase the number of people they will hand out the survey to, from 20% to 33%. This does not compensate for the drop in the number of respondents because the survey is no longer mandatory. A larger sample cannot compensate for biases in the responses rates from specific groups. The result will simply be more responses from the groups that are likely to react well to the census.
Groups with specific challenges such as those with multiple jobs, language challenges or other issues have been shown least likely to respond to general surveys. Such groups include everyone from new immigrants, to single mothers, the elderly and the isolated. Yet, those are the people who may place differential demands on services and need to be identified. For example, public health in Toronto used the census to help them identify populations at risk during the SARS epidemic.
Comparisons between survey observations are a critical aspect of any analysis program. It will be technically impossible to comfortable with comparisons between the first cycle of the planned NHS and the previous censuses. When we have a few cycles (i.e. 20 years) of NHS, we might be comfortable with its properties but analysis in the intervening period will be very much like working in a fog, a fog of unknown information density.
The coercive element of the census is the price of citizenship. The American Community Survey is also mandatory in the US for reasons of efficient accurate cost-effective data. We do not have compulsory registration, identity cards or other forms of personal tracking in Canada as in many European countries which can substitute for some aspects of a census. Nothing substitutes for the broad analytical data available in the long form. There are not other sources for accurate and complete information.
In terms of privacy, Canadians routinely surrender privacy to their merchants through loyalty cards or even electronic purchases (remember the tjx/winners privacy breach). Statistics Canada, unlike far too many retailers, has never had a privacy breach and goes to extreme lengths to see that none outside of census operations sees the personal records. The individual personal data records are not even available to Mr. Clement's ministry. As a heavy data user, I am extremely aware of the costs and complications of their privacy protection policy. Their policies work to provide secure aggregate analytical data to business and government and should be preserved.
Statistics Canada already makes extensive use of administrative computer files including the various files within the taxation system and other administrative databases. In that area, they probably lead the world in the efficient exploitation of such resources. Private business databases are less useful for statistical purposes because of their necessary proprietary nature, their incompleteness and their general inaccuracy. Naïve suggestions to use records such as credit card data clearly have not worked with those sources. Analyses of such data while useful are NOT a substitute for clean censuses and surveys. The literature on business data mining is rich with discussions of how to surmount these issues for private purposes. However, for public purposes and for good analysis, we require completeness which only the major statistical vehicles can provide. With the census, we are doing more than count people. We are evaluating attributes that are not available in commercial databases.
The response of the Canadian Association for Business Economics is found here.