用稀疏PLS回归分析中国经济活动的替代指标

Jan J. J. Groen, Michael Nattinger
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引用次数: 4

摘要

与其他中国经济数据相比,中国官方公布的GDP增长率在过去10年一直非常平稳。为了更好地识别中国的商业周期,我们从大量中国高频数据中构建了一个稀疏偏最小二乘(PLS)因子,针对与中国经济重要方面高度相关的变量。我们得出的替代增长指标清楚地识别了中国的商业周期波动,它在中国的样本外测试以及应用于其他经济体时都表现良好。利用这一指标,我们将偏离增长趋势的情况分解为全球增长、信贷供应和货币政策的组成部分,这种分解表明,与中国2015-16年的放缓相反,中国2018-19年的放缓主要是由于国内信贷状况恶化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Alternative Indicators for Chinese Economic Activity Using Sparse PLS Regression
Official Chinese GDP growth rates have been remarkably smooth over the past decade, in contrast with alternative Chinese economic data. To better identify Chinese business cycles, we construct a sparse partial least squares (PLS) factor from a wide array of Chinese higher-frequency data, targeted toward variables that are highly correlated with important aspects of the Chinese economy. Our resulting alternative growth indicator clearly identifies Chinese business cycle fluctuations and it performs well both in out-of-sample testing for China as well as when applied to other economies. Using this indicator, we decompose deviations from growth trends into global growth, credit supply, and monetary policy components, and this decomposition suggests that, in contrast to China’s 2015-16 slowdown, the country’s 2018-19 slowdown was mainly due to deteriorating domestic credit conditions.
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