Munich Personal RePEc Archive

Chinese Divisia monetary index and GDP nowcasting

Barnett, William A. and Tang, Biyan (2015): Chinese Divisia monetary index and GDP nowcasting.


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Since China’s enactment of the Reform and Opening-Up policy in 1978, China has become one of the world’s fastest growing economies, with an annual GDP growth rate exceeding 10% between 1978 and 2008. But in 2015, Chinese GDP grew at 7%, the lowest rate in five years. Many corporations complain that the borrowing cost of capital is too high. This paper constructs Chinese Divisia monetary aggregates M1 and M2, and, for the first time, constructs the broader Chinese monetary aggregates, M3 and M4. Those broader aggregates have never before been constructed for China, either as simple-sum or Divisia. The results shed light on the current Chinese monetary situation and the increased borrowing cost of money.

GDP data are published only quarterly and with a substantial lag, while many monetary and financial decisions are made at a higher frequency. GDP nowcasting can evaluate the current month’s GDP growth rate, given the available economic data up to the point at which the nowcasting is conducted. Therefore, nowcasting GDP has become an increasingly important task for central banks. This paper nowcasts Chinese monthly GDP growth rate using a dynamic factor model, incorporating as indicators the Divisia monetary aggregate indexes, Divisia M1 and M2 along with additional information from a large panel of other relevant time series data. The results show that Divisia monetary aggregates contain more indicator information than the simple sum aggregates, and thereby help the factor model produce the best available nowcasting results.

In addition, our results demonstrate that China’s economy experienced a regime switch or structure break in 2012, which a Chow test confirmed the regime switch. Before and after the regime switch, the factor models performed differently. We conclude that different nowcasting models should be used during the two regimes.

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