| Inflation is an important reference variable for the government to formulates economic policies,and it’s also a key factor affecting business decision-making,personal investments and consumption decisions.Therefore,a timely and accurate prediction of future inflation is of paramount importance to governments,businesses and individuals.However,the implementation of accurate inflation prediction still faces many challenges due to the extremely complex nature of the formation mechanism and dynamic characteristics of inflation.The inflation forecasting method still needs further optimization.In recent years,the study of the usefulness of accounting information has expanded from micro level to macro level,providing an opportunity to use the micro-level information to predict macroeconomic indicators.The existing research finds that aggregated accounting has predictive ability for future inflation.Analysts whom are important information intermediaries use macro,industry and enterpriselevel information to generate analysis reports.Compared with macro statistics,analyst recommendations are timely.On the one hand,analysts generate recommendations based on the company’s operating conditions,analyst recommendations can convey information on corporate earnings.On the other hand,analyst recommendations can cause capital market volatility.So whether to use analyst recommendations data to predict future inflation is a question worth studying.Studies have shown that the change in the summary analyst recommendations have a significant correlation with the market-level stock returns,indicating that the analyst recommendations have macro information value.In this context,this paper further explores whether the aggregate analyst recommendations have macroprediction value,and discusses the predictability role of aggregated analyst recommendation changes on inflation indicators(CPI,PPI,RPI).And explore the differences in predictive effects under different macroeconomic conditions.In addition,the paper examines the reason why aggregate analyst recommendations can predict inflation,and whether existing CPI forecast data makes full use of aggregated analyst recommendations.The structure of the full text is as follows: the introduction of the research background and research significance of the article,then summarizing the macroeconomic related literatures of inflation prediction and aggregate micro information prediction,then proposing the research topic and theoretical analysis and hypothesis deduction.Drawing on the existing literatures to establish a model to empirically test.Finally,we draw the conclusions of this paper and put forward the research prospects.The main conclusions of this paper are as follows: First,the aggregate analyst recommendations have predictive effect on future inflation(representative indicators are CPI,PPI,RPI);indicating that the analyst recommendations contain information on future price.We can use analyst recommendation data to forecast future inflation.Second,during the macroeconomic volatility period,aggregate analyst recommendations have stronger predictive effect on inflation,indicating that the aggregate analyst recommendations is more reflective of future inflation in the future when economic volatility is more severe.Third,aggregate analyst recommendations can reflect future aggregate earnings because analysts use valuation models to form their recommendations,and aggregate analyst recommendations as a proxy for investor sentiment which affect the stock market,both of which are the reason why aggregate analyst recommendations can predict the future inflation.Fourth,the change in aggregated analyst recommendations is significantly correlated with existing CPI forecasts,indicating that existing inflation forecasters have used information from analyst recommendations.However,there is also a significant correlation between aggregate analyst recommendation changes and CPI forecasting errors,indicating that existing CPI forecast data does not fully utilize the macro information contained in the analyst recommendations,and we can use aggregate analyst recommendations data to improve existing inflation forecasting data.The possible research contributions of this paper are as follows: Firstly,the research on usefulness of micro information to predict macro information is currently focused on accounting earnings.This paper expands the research on macroeconomic forecasting of micro information.Secondly,this paper further emphasizes the role of analysts as Information intermediary by studying the relationship between aggregate analyst recommendations and aggregate earnings and stock market excess returns.Thirdly,with the rapid development of the capital market,China’s securities analysts have also experienced the transformation from "stock critics" to "industry experts".The paper proves that the analyst group can also play an important role in macroeconomic forecasting.Finally,the predecessors’ research on whether the capital market is a "barometer" of China’s macro-economy is controversial.This paper uses information of analysts to prove that analysts can reflect future earnings information into the stock market in a timely manner.The capital market has the function of reflecting the real economy in advance and we explain the principles. |
