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In order to reveal the relationship between FDI and economic growth in ShaanXi, statistical data of ShaanXi's GDP and FDI from 1994~2009 were used to study the relationship between FDI and economic growth in ShaanXi based on OLS model. The results showed that FDI played a certain role but not the main character in promoting economic growth. Under certain policy the expansion of foreign direct investment...
This paper aim at developing the grey econometric model with lags information. Considering the breakpoint of the traditional econometrics model, the study gives the primary steps and constraint condition of grey econometric model with lags information. Furthermore this paper makes empirical analysis using data from a segment market, and tests the average relative error of the model. The result reveals...
The recent studies on financial distress are mostly confined to static econometric or statistical methods based on cross-sectional financial data ,and it is ignored that the variation of companies' financial status is a dynamic process. In order to show the change of companies in financial position, this study constructed the financial distress prediction model based on panel logit. On the selection...
Prepayment risk of the residential mortgage has gradually become important to commercial banks. It affects banks' income, disturbs cash flow management, triggers reinvesting risk and blocks the process of securitization. This paper states four main methods of constructing empirical models, focuses on analyzing their applicability in China and finally comes to a conclusion that an econometric model...
By collecting the data on China's tax revenue and GDP since 1978, using the methods of time series and econometrics to measure and analyze the tax elasticity as well as setting up an error correction model, the authors find out that during 1978-1994 China's long-term tax elasticity is 0.4, less than its short-term elasticity of 1.84; since 1995, China's tax elasticity has changed dramatically with...
In this paper, we use different scales to examine the volatility of return, volume and trading amount by intra-daily high frequency data. Besides the conventional measures of the volatility that make use of the unobserved variance or standard deviation of its return, another two different types of return - absolute return, high-low return are introduced. Two models are considered. One is an ARMA model...
In this paper we discuss the volatility of daily returns of GBP/CNY exchange rates, find there exists a leptokurtic feature (higher peak and fat tail) that results from some occasional jumps. So, we introduce the jump-diffusion stochastic volatility model to describe the time series of daily returns, and give the parameter estimations by MLE (maximum likelihood estimation) method. Through the empirical...
According to the principle of economy, the stock market will decline, if required reserve ratio (RRR) is set higher. As main macro-economic control, the RRR is one of tools which are often used. However, although the People's Bank of China adjust the RRR so frequently in the recently, the stock market didn't run as expectation. This paper is concerned with the phenomenon and analyzes the reason for...
Although there is considerable literature on optimal monetary policy for industrial countries, little research has been undertaken to investigate suitable monetary policy analysis framework for emerging countries that confront a different mix of shocks and have a fear of floating. This paper uses a New Keynesian model to simulate the quarterly data of 1996-2005 in China. Drawing on our econometric...
Based on the China economy data 1996-2005, two issues are addressed in this paper. First, we examine the ability of the DSGE model to describe stylized facts about China economy. The model succeeds to replicate the variability observed in 1996-2005. Second, we compare two methods of motivating money in DSGE Model. Drawing on our econometric analysis, we argue that the cash-in-advance model, closed...
Traditional models for panel data were widely used to analyze real estate price impact factors. But traditional models for panel data may cause spatial dependence problems. So spatial and geographical factors should be taken into account. Global spatial autocorrelation Moran's I indices are calculated and local spatial autocorrelation LISAs are figured. Then spatial regression models, including spatial...
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