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Record W2746766022

Enduring Virtues: Saving and Investing as National Priorities in 2017

2017· article· en· W2746766022 on OpenAlexaboutno aff
William B. P. Robson

Bibliographic record

VenueC.D. Howe Institute Commentary · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsInvestment (military)Depreciation (economics)National wealthDebtConsumption (sociology)Capital (architecture)CommodityMeasures of national income and outputEconomicsBusinessFinanceQuarter (Canadian coin)National savingsService (business)Economic growthMarket economyNational accountsEconomyCapital formationHuman capitalFinancial capitalPolitics
DOInot available

Abstract

fetched live from OpenAlex

Canada’s 150th anniversary is an apt time to reflect on past progress and how to build on it. A key lesson from our own history and global experience is that faster-growing economies have higher saving and investment. Forgoing consumption today adds to wealth: resources for the housing, capital, infrastructure and investments abroad that boost living standards tomorrow. But Canadians’ recent national saving – as households, as owners of businesses, and through our governments – has been feeble. Over the year to the third quarter of 2016, we consumed 98 percent of national disposable income. Our national saving rate was 2 percent, way below an average above 7 percent since the mid-1990s. The problem was not so much our individual behaviour: households saved almost $1, 700 per person. But losses by businesses – and, more important, governments running deficits – reduced national saving to barely $900 per Canadian. Such weak saving meant that, to finance net investment that totaled $3, 200 per Canadian, we had to borrow more than $2, 300 per Canadian abroad. Not necessarily bad – but about $2, 800 of that investment was in housing. Capital spending by businesses and governments – projects likelier to improve our capacity to export and service foreign debt – barely exceeded depreciation. Sagging national saving has its counterpart in a virtual flat-lining of national net worth. While some of this weakness is cyclical, we would be rash to count on surging world demand and higher commodity prices to pull us ahead. Our saving as households may look respectable, but with so much of our wealth in housing, and a subdued outlook for returns on financial assets, more would be better. Business profits will rebound, but to get corporate saving back to historical levels, we need greater efficiency. Policy can help private-sector saving: governments should be relying more on consumption taxes and treat household saving more generously, and reduce taxes that raise business’ costs and lower returns to investment. The top priority for governments, however, is fixing their own budgets. Much of what governments call “investment” is transfer payments and consumption. Federal capital spending does not even match depreciation: Ottawa’s net investment is negative. And notwithstanding the rhetoric, deficits have nothing to do with investment. Capital spending creates assets, not liabilities. When governments run deficits, consuming more than tax revenue net of transfers and interest payments can cover, their deficits erode national net worth – as they are doing now. We need less focus on near-term GDP and boosting consumption. Higher saving and investment, as households, through businesses and Canadian governments, is our surest path to a more prosperous future.

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)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.202
Threshold uncertainty score0.407

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0130.006
Scholarly communication0.0150.006
Open science0.0020.006
Research integrity0.0040.008
Insufficient payload (model declined to judge)0.0370.010

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 head0.071
GPT teacher head0.357
Teacher spread0.285 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations2
Published2017
Admission routes1
Has abstractyes

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