True cost of living measures for 10 provinces: Using an Engel Curve approach
Auteurs: Herb Emery et Xiaolin Guo
Aperçu
Résumé (français)
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Résumé (anglais)
In Canada, the Consumer Price Index (CPI) is an official measure of cost of living used by government, policymakers, and businesses to index wage and salary adjustments, public pension payments, tax brackets, minimum wages, social assistance transfers, and so forth. If the CPI does not accurately represent the cost of living, taxpayers can end up paying more than intended, and households may receive less in the form of transfers and wages. It is therefore essential that the “true cost of living” is measured accurately. With Survey of Household Spending data from 1997 to 2015, we follow an Engel Curve approach to estimating CPI bias, inferred from consumers’ behavior, which we use to construct “true cost of living” measures for subgroups of the Canadian population in all ten provinces. Overall, we find that the official CPI contains substantial biases that increased in size after the 2008/2009 recession. Although the official CPI suggests no significant shocks to the economy in terms of cost of living, our estimates suggest that households in Canada experienced sharp increases in cost of living and decreases in real income after 2009. For females and households with children, these shocks have resulted in a persistently higher cost of living than those represented by the official CPI.
Détails
Type | Document de travail (en ligne) |
---|---|
Auteur | Herb Emery et Xiaolin Guo |
Année de pulication | 2019 |
Titre | True cost of living measures for 10 provinces: Using an Engel Curve approach |
Série | New Brunswick Institute for Research, Data and Training |
Ville | Fredericton, NB |
Établissement | Department of Economics, University of New Brunswick |
Langue de publication | Anglais |
- Herb Emery
- Document de travail (en ligne)
- True cost of living measures for 10 provinces: Using an Engel Curve approach
- Herb Emery et Xiaolin Guo
- New Brunswick Institute for Research, Data and Training
- 2019