MétaCan
Menu
← Back to cohort
Record W2788476120 · doi:10.55016/ojs/sppp.v11i1.43286

Alberta’s Changing Industrial Structure: Implications for Output and Income Volatility

2018· article· en· W2788476120 on OpenAlexaffabout
Bev Dahlby, Mukesh Khanal

Bibliographic record

VenueThe School of Public Policy Publications · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsVolatility (finance)EconomicsEconometrics

Abstract

fetched live from OpenAlex

The counterpart to the economic cycle is the policy cycle. Whenever there is a downturn in the Alberta economy because of slumping oil and gas prices, politicians of all persuasions, from Peter Lougheed to Rachel Notley, have called for policies to diversify the economy, on the assumption that expanding other sectors of the economy will insulate Alberta’s economy against volatile oil and gas prices. However, just because a sector is not directly part of the oil and gas extraction sector, does not necessarily make it counter-cyclical. In fact, the sectors that have been promoted in the name of diversification are often linked to the oil and gas extraction sector and follow the same boom-bust cycle.In other words, the government’s attempts to subsidize certain sectors in the name of “diversification” do not insulate the provincial economy from fluctuations in oil and gas prices and may even exacerbate the economic cycle. Missing in the discussion is an appreciation of how changes in the structure of the Alberta economy have affected output and income volatility. In the last 20 years, sectoral output shares have become more diversified in Alberta, and this has contributed to a 21 per cent reduction in aggregate output volatility over that period. Successive governments have tried promoting manufacturing as a way to diversify the economy, but manufacturing is the third most volatile sector, and its volatility is linked closely with the boom-bust cycles of the oil and gas extraction sector. So, increasing manufacturing, including petrochemical manufacturing, will actually make output volatility worse, not better. In fact, a one standard deviation increase in average per capita output in the oil and gas extraction sector is associated with in a 9.45-per cent increase in average per capita output in the chemical manufacturing subsector, suggesting the same boom-and-bust relationship between the two sectors. It is not the only sector like that: 16 other sectors in Alberta are linked to the same boom-bust cycle as the oil and gas sector. The more important diversification issue in the province is not output volatility, but the volatility of labour income. In the last 20 years, labour income has become increasingly concentrated in Alberta’s two most volatile sectors, oil and gas extraction and construction. As a result, volatility of aggregate labour income in Alberta increased by 40 per cent during that period. Rather than trying to change Alberta’s industrial mix by subsidizing industries that may only contribute to more volatility of economic output, a more sensible government approach would be to adopt policies that address the problem of labourincome volatility. That would include finding ways to expand unemployment insurance for Alberta workers, as the current federal government policy actually provides fewer supports to unemployed Albertans than it does to residents of other regions. Average weekly earnings of Albertans were 20 per cent higher than national average weekly earnings over the 2012 to 2016 period. However, maximum annual insurable earnings under EI are determined based on national average weekly earnings. Higherwage earners should have the opportunity to enrol in a voluntary supplemental EI program, and if the federal government does not want to provide it, the provincial government could. Additionally, the government can promote self-insurance among workers by expanding tax-sheltered savings products, like tax-free savings accounts, so workers can accumulate back-up funds when labour incomes are high, to help sustain them during downturns. Finally, the provincial government needs to abandon its procyclical spending patterns. That means spending less money when oil revenues are high, to avoid exacerbating labour and material shortages, and maintaining spending, rather than forced cutbacks, during downturns in the economy. That, of course, would require a great deal more political discipline than the easier and more fashionable attempts to subsidize output diversification.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.057
Threshold uncertainty score0.156

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0020.001
Scholarly communication0.0040.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.081
GPT teacher head0.346
Teacher spread0.265 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2018
Admission routes2
Has abstractyes

Explore more

Same venueThe School of Public Policy Publications→Same topicCanadian Policy and Governance→French-language works237,207→