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Record W2029557783 · doi:10.1177/002070200606100203

China's Economic Transformation

2006· article· en· W2029557783 on OpenAlexaboutno aff
Wendy Dobson

Bibliographic record

VenueInternational Journal Canada s Journal of Global Policy Analysis · 2006
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobalization, Economics, and Policies
Canadian institutionsnot available
Fundersnot available
KeywordsChinaTransformation (genetics)Political scienceEconomic transformationEconomic reformEconomic systemEconomicsLaw

Abstract

fetched live from OpenAlex

Year after year China's economic transformation is the top cover story. Frequently the commentary is polarized between breathless optimism and suspicious skepticism, which usually means the truth lies somewhere in between. This will be true of many views and statements in this article because of diversity in a huge country and because of rapid change. Indeed, where all can agree is that China's re-emergence as a world economic power after a hiatus of several hundred years is a dramatic accomplishment. Some of the Asian tigers have done better on export-led growth, but no economy of this size has reformed and opened so quickly.Consider some of the numbers:* Growth: For 25 years China has been the world's fastest growing economy; 9-10 percent annual growth means that the economy doubles in size every seven or eight years.* Size: Using a purchasing power parity measure, China is already the world's second largest economy after the United States. Measured by current exchange rates, its economy is the world's sixth largest after the United States, Germany, Japan, the United Kingdom and France, and will soon be the fourth largest.* Integration through foreign direct investment (FDI): In the past five years China has emerged as a global manufacturer and trader because of FDI inflows. In the past four years it has received the largest absolute inflows (although round-tripping through Hong Kong is a contributing factor).* Integration through trade: In 2005, the size of its total trade (imports plus exports) surpassed Japan's to make it the world's third largest trader.These numbers need to be put in perspective in at least three ways. First, even when China becomes the world's largest economy, its average citizen will still be relatively poor. It has been said that China will grow old before it becomes rich. Second, many of the superlatives apply to three city clusters, in the Pearl River Delta, around Shanghai, and around Beijing, where huge building programs and infrastructure projects have propelled more than 140 million people to first-world status. Third, we cannot talk about the future without understanding thousands of years of history. Going back just to the 1949 revolution, private property was abolished and today attitudes remain ambivalent towards property rights despite their importance as a key building block of a modern market economy. Even so, the past 30 years provide a remarkable record of successful economic policies. China's managers are doing many of the right things to create a transparent market economy, but major political constraints remain because of the communist party's determination to maintain its grip on political power and on the commanding heights of the economy.My purpose in this article is to assess China's transformation using a long-term economic growth framework and to explore the implications for the rest of us. I will do this by reviewing the main drivers of growth: inputs of capital, labour, land, and new technologies, as well as the role of key institutions, and then discuss some of the main implications for the world economy and for Canada in particular.PROSPECTS FOR SUSTAINED LONG-TERM GROWTHMainstream economists agree that sustained growth is determined by inputs and technology, but also by institutions. In particular, government's role should be to provide the necessary frameworks for an efficient market economy. It should improve the economy's ability to reallocate resources from failure to opportunity. It should contribute a strong human resource base, encourage flexible labour markets, and provide social safety nets. And it should provide an incentive framework, including a strong and resilient financial system, which supports and rewards innovation. I keep these benchmarks in mind in the following discussion.The role of capital and financial markets in long-term growthChina has the world's highest saving rate, at 43 percent of GDP, and an investment-to-GDP ratio of more than 45 percent. …

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)0.001
metaresearch head score (Gemma)0.001
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: Empirical · Consensus signal: none
Teacher disagreement score0.052
Threshold uncertainty score0.104

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0040.002
Scholarly communication0.0050.002
Open science0.0000.003
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0150.002

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 head0.006
GPT teacher head0.225
Teacher spread0.219 · 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
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

Citations80
Published2006
Admission routes1
Has abstractyes

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