This paper examines the Cagan effect in China by using a panel smooth transition approach on the firm-level data. Our results reveal that the demand for money by firms relatively decreases for the high inflation period, because the firm anticipates further price increase that it seeks a substitute for money, supporting the presence of the Cagan effect in firms in China. A policy implication of our finding is that efficiently managing Inflation Expectation is necessary in China in stimulating the economy through expansion of the money supply.
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In 2009, the obvious behavior of the public’s purchase of real estate against future price increase makes the Chinese government explicitly express that inflation expectation should be efficiently managed for the first time. A number of studies have explored the relationship between inflation and inflation expectation in China. However, little research has explored above relationship in the perspective of the Cagan money demand. Recently [
[
where,
where
Following [
where, the transition function
where, c denotes a location parameter,
Given the properties of the transition function, we have
The firm-level data for the period of 1999 to 2007 are drawn from the annual surveys of Chinese manufacturing by the China National Bureau of Statistics. These annual surveys cover all state-owned enterprises, and those non-state-owned enterpricses with annual sales over 5 million RMB. This database has been widely used by previous studies, as it contains detailed firm-level information for manufacturing enterprises in China. Particularly, we are interested in the variables related to measuring firm financial holdings, average wage, total sales, and cost of capital.
To begin with, we first test for linearity in Equation (3). According to the p-values for the LM tests [
The estimation results show that the coefficients on total sales and the nominal interest rate are both statistically significant and have expected signs for both the low and high inflation periods. The coefficient on wages is statistically significant and positive for the low inflation period, but not significant for the high inflation period, which is consistent with Cagan’s hypothesis.
Variable | Description |
---|---|
mit | Natural log-difference of Mit, where Mit is computed as liquid asset subtracting the sum of inventory and accounts receivable for firm i at the end of year t, as shown in [ |
yit | Natural log-difference of total sales for firm i at the end of year t. |
wit | Natural log-difference of Wit, where Wit is measured as the total payroll (given by “total wages payable”), divided by the number of employees for firm i at the end of year t. |
rit | Natural log-difference of Rit where Rit is computed as the total financial expenditures divided by the total debt (given by “total liabilities”) for firm i at the end of year t, as shown in [ |
Parameter | Estimate | Parameter | Estimate |
---|---|---|---|
0.292*** | 0.096*** | ||
?0.098*** | ?0.007 | ||
0.037*** | ?0.031* | ||
0.387*** | ?0.105*** | ||
0.005 |
Note: ***, **, * indicate statistical significance of the difference at the 1%, 5% and 10% levels, respectively.
There are a relatively limited number of studies addressing Cagan’s hypothesis on money demand in China. This paper attempts to fill this gap by adopting a panel smooth transition approach on the firm-level data. Our results support the presence of the Cagan effect in China. In addition, it is found that the higher the inflation rate is, the stronger the Cagan effect is. The policy implications are obvious. Firstly, central banks should be more concerned with inflation expectation than they have been in the past, for inflation may have a significantly greater acceleration in the high inflation period. Secondly, once inflation expectation zooms up, central banks need to pursue aggressive and nontraditional monetary policy to reestablish suitable price anticipations by the public.
We would like to thank the foundation from the National Natural Science Foundation of China (71201174 and 71002056) and Guangdong Natural Science Foundation (S2013010015019; 2014A030313577) for financial support of this research.