第1讲时间序列数据研讨.pptx

Time Series Aanlysis 时间序列分析赵文哲经济学院 Lecture one Introduction of Time Series 1 1. What is time series ? Time series is a sequence of values a specific variable has taken on over some period of time. The nature of time series: ? The observations have a natural ordering in time. ?A ssume some regularity of the observation frequency . ?T he past can affect the future, but not vice versa. ?T ime series is a sequence of random variables indexed by time, it is also called a stochastic process . 2 2. Why use time series analysis ? Many economic problems can be analyzed using time series data. For example, ? many macroeconometric analyses are based on time series data. Forecasting the future economic conditions is one important objective of many analyses. ? understanding the relations between a set of possibly related variables ? uncovering the ongoings within an economic system or a specific market. 3 2. Why use time series analysis (continued) ? JAN TINBERGEN (1939) constructed the first econometric model for the United States and thus started the scientific research programme of empirical econometrics . ? The prevailing assumption was that, according to the classical linear regression model , the residuals of the estimated equations are stochastically independent from each other. 4 2. Why use time series analysis ( continued) ? DONALD COCHRANE and GUY H. ORCUTT (1949) ? They showed that if residuals of an estimated regression equation are positively autocorrelated , the variances of the regression parameters are underestimated and, therefore, the values of the F and t statistics are overestimated. ? This problem could be solved , at least for the frequent case of first order autocorrelation, by transforming the data adequately. 5 2. Why use time series analysis ( continued) ? JAMES DURBIN and GEOFFREY S. WATSON (1950/51) developed a test procedure which made it possible to identify first order autoc