Purpose
With this paper, the authors aim to investigate the drivers behind three of the most important aspects of the Chinese real estate market, housing prices, housing rent and new construction. At the same time, the authors perform a comprehensive empirical test of the popular 4-quadrant model by Wheaton and DiPasquale.
Design/methodology/approach
In this paper, the authors utilize panel cointegration estimation methods and data from 35 Chinese metropolitan areas.
Findings
The results indicate that the 4-quadrant model is well suited to explain the determinants of housing prices. However, the same is not true regarding housing rent and new construction suggesting a more complex theoretical framework may be required for a well-rounded explanation of real estate markets.
Originality/value
It is the first time that panel data are used to estimate rent and new construction for China. Also, it is the first time a comprehensive test of the Wheaton and DiPasquale 4-quadrant model is performed using data from China.
This paper investigates the effects of Chinese financial and fiscal policies designed to counter the worldwide Great Recession of 2008. We examine how policies designed to increase bank credit and health (i.e., asset liquidity, capital adequacy ratio, profitability, and bad loan ratio) influenced firm-level output, employment and investment. We also explore the impact of China's expansionary fiscal policy with regard to these firm-level variables. We find that the policy effects varied based on firm-level characteristics such as size, liability ratio, profitability, ownership and the industry in which the firm operates. With respect to the dynamic effects, our results suggest that Chinese financial and fiscal policies were generally effective in the short run, but their positive impacts ceased within two years.
This paper applies the threshold quantile autoregressive model to study stock return autocorrelations and predictability in the Chinese stock market from 2005 to 2014. The results show that the Shanghai A-share stock index has significant negative autocorrelations in the lower regime and has significant positive autocorrelations in the higher regime. It attributes that Chinese investors overreact and underreact in two different states. These results are similar when we employ individual stocks. Besides, we investigate stock return autocorrelations by different stock characteristics, including liquidity, volatility, market to book ratio and investor sentiment. The results show autocorrelations are significantly large in the middle and higher regimes of market to book ratio and volatility. Psychological biases can result into return autocorrelations by using investor sentiment proxy since autocorrelations are significantly larger in the middle and higher regime of investor sentiment. The empirical results show that predictability exists in the Chinese stock market.
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