The Study Of Macroeconomic Forecasting Based On Business Study

In current word, the social economic of every country is admist the winds of change, and there are many uncertain factors. The economic development of China is in an important period of strategic opportunities as while as facing new challenges. In this situation, only the effective forecast of China’s economic cyclical fluctuation and mastering the direction of economic fluctuation can we actively formulate corresponding policies according to the formation reasons of the fluctuation and the fluctuation characteristics in order to Slow down the economic cycle fluctuation and reduce the economic losses to sustain the economy of our country develop stably and high-speedly. Business survey, as the products of a certain degree of economic development to emerge as the times require, is an important and effective method and approach to predict he change trend of economic development. With the establishment and development of socialist market economy of our country, in order to meet the needs of macroeconomic policy and the government enterprise, in the early90’s, the National Bureau of statistics, the state information center, the people’s Bank of China and other departments have began to study foreign business survey experience, proceed to the5000households around the industrial production enterprises to carry out business survey work, and included the business survey officially in the national statistical system in the late90’s.Business cycle is an important tool for monitoring fluctuations in the economic sycle, and forecast the macroeconomic boom. Indices of business survey not only can objectively describe the functioning of the national economy, but also can predict the future development trend of macroeconomy. Indices of business survey is divided into the leading index, consistency index, lagging index and early warning index.while the composed leading index is composed by a group of leading index which lead the coincident index to predict future economic trends. This has important significance to the choice of the macroeconomic policy and enterprise, personal investment planning. At present, there have been many articles using macroeconomic indicators to analysis and study the trend of fluctuation of macroeconomy and economic prediction. While, there are very few people combining the indice of business survey based on the data of business survey and macroeconomic index to analyse and predict the economic trend.This study is mainly to combine the leading business survey indicators and macroeconomic indicators. Through the methods of seasonal adjustment, the time difference correlation analysis and peak-trough corresponding, this paper picks out leading indicators of business survey from the5000households’s15difussion indicators of business survey released by People s Bank of China quarterly statistics:the overall operation of the enterprises, the energy and raw material supply, product sales, cash flow, investment in business equipment etc, and9macroeconomic indicators released by China Economic Information Network:the purchasing managers index (PMI), economists expectation, economist confidence, entrepreneurs confidence, investment in real estate development etc. This paper synthesize leading composite index by NBER method, then combine the leading composite indicators and other leading composite indicators received from macroeconomic to predict the fluctuation of macroeconomic cycle by Probit model. This paper mainly investigate the combination can improve the prediction accuracy f economic fluctuations or not, and to what extant can improve the prediction accuracy.The purpose of this paper is trying to find a new method to forecast economic fluctuation, and looking for suitable new indicators to improve the prediction precision of turning point and the main macroeconomic indicators.This paper, based on Probit model, let the0-1two element sequence of the consistent synthetic index of Bureau of statistics as explained variable, let7leading macroeconomic indicators and leading composite indicator CIBS that picked and composed from a group of business survey index as explanatory variables to establish the discrete choice model, through this to forecast and analysis the turning point’s probability of our economic cycle fluctuation, and investigate the prediction properties of leading composite index of business survey in the model. The main structure of this paper is as follows:The first part is the introduction that chiefly present the writing background, writing significance, the methods and the innovations. The second part introduces the screening and test of the business survey leading index. The third part briefly introduces some basic forms of Probit model and it’s estimation methods. The fourth part is empirical analysis, this part is through debugging the Probit model to analyze the prediction performance of business survey leading composite index CIBS to economic cycle fluctuation. The fifth part is the final conclusion, and pointed out the innovation and deficiency of this paper.The main conclusions of this study are:As China’s economy is in rapid development period, the classical cycle and growth cycle models are subject to certain limitations in use, so the growth rate cycle analysis in China is still the main way of economic analysis; Macroeconomic growth forecast can make use of the indictors:steel production, cement production, vehicle production, fertilizer production, stock tuading volume, reverse CPI, investment in fixed assets this year to predict the economy; The composite index CIBS1of three leading indicators of business survey:the situation of energy supply, the supply situation of raw materials and the master of the situation of bank loans three, shows good turning point prediction performance of economic fluctuation in the past ten years in China’s economic development, this index can be used as a reference index of China’s macroeconomic regulation in the future, and also look forward to the leading composite index can be tested and modified further in future practice; the leading composite index CIBS2of economist confidence, economists expectation, the purchasing managers index (PMI), the real estate financing index show better in the model’s in-sample forecast, but seems to contribute little to the out-sample forecast.