Is the Real Estate Industry Squeezing out the Manufacturing Industry?-The China Experience
Bibliographic record
Abstract
IntroductionAccording to post on CNN Money on 11/11/2014, investors worldwide are now able to buy shares of Chinese companies listed on the Shanghai stock exchange. Even though the purchase process is bit complicated, Donald Amstad of Aberdeen Asset management calls this, a very, very important day for and for the world financial system. As investment in Chinese companies becomes more and more available to investors across the globe, it becomes even more important to have information about the Chinese economy and Chinese companies. In this paper, investigate the impact of the hot Chinese real estate industry on the manufacturing industry in China.China overtook the U.S. as the world's largest manufacturing nation in 2010. The United Nations reported in 2011 that has the largest manufacturing industry in the world by an increasing margin. Despite the encouraging news, there are many outcries in about how the overheating real estate industry has halted the manufacturing industry. Alini (2013) claims this happened in France during the period 2000 - 2007 and may have been the cause of the loss of 328,000 jobs in the manufacturing industry in Canada from 2002-2008.Industry leaders in expressed their concerns in the China Enterprise Competitiveness Annual Meeting in 2012. A comment by Simcere Pharmaceutical Group founder and Chairman Ren Jinsheng said that, we can pick up business innovation only if the real estate economy cools down, which represented the manufacturing industry leaders' thought. The consensus is that the real estate economy has sucked innovative resources from the manufacturing industry. So, is China's manufacturing industry booming or is it suffering?According to the World Bank, China's manufacturing value added as percent of GDP was above 32% from 2004-2009. It dropped to 29.62% in 2010. It was last measured at 30.57 in 2011. China's global account surplus surged after 2004. It rose from 2.8% of GDP in 2003 to 10.8% in 2007. Many economists and countries argue that the RMB needs to appreciate to rebalance China's trade. Since 2003, the Chinese government has been trying to narrow external surpluses through measures such as allowing modest appreciation of the currency. The RMB has slowly appreciated against the US dollar from 8.2770 in 2003 to around 6.23 in May, 2014. In 2013, China's surplus dropped to 2% of GDP. On the surface, it seems that currency appreciation did help to balance the trade surplus. However, empirical evidence on the effects of an RMB appreciation on China's exports has been mixed for the largest category of exports, processed exports (Thorbecke & Smith, 2010; Cheung et al., 2010; Thorbecke, 2011). While acknowledge that exchange policy might have contributed to China's decreasing trade surplus, suspect that the difficulty of the manufacturing industry to compete with the real estate industry for capital also has contributed to the decreasing trade surplus.Based on manufacturing value added as percent of GDP and China's global account surplus, China's manufacturing industry might not be as strong as United Nations has described. This research is the first to investigate the effect of the rising real estate industry on China's manufacturing industry. We look at the effect both in terms of stock returns and the financial health of both industries. First, investigate the monthly stock returns for the two industries. We then look at various financial ratios and the growth rate of the two industries. If the real estate industry has negatively affected the manufacturing industry, should detect evidence that returns and total activity in the manufacturing sector have declined.Literature ReviewPrevious research has focused on land supply and how it affects development. The current land supply model causes inter-regional tension and constrains development (Wang, Potter & Li 2014; Wang 2014). …
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".