The first level, simple charts and indicators, and general questionnaire results will be displayed in this way, with vivid images.

The second level, descriptive statistics, analyzes the characteristics of data distribution.

The third level, econometric analysis, establishes the model. Econometric analysis can be divided into several levels. The first level is simple regression, including binary and multivariate regression, and the handling of basic econometric problems (* * * linear, heteroscedasticity and autocorrelation).

The second level is more professional, including model specification error checking and model correction, model selection and processing of special data types (time series, dummy variables, panel data, etc.). ), simultaneous equations, VEC model, VAR model, conditional heteroscedasticity model, etc. The third level includes ordered dependent variable, panel VAR, neural network, quantile model and seasonal adjustment model. Model, establish a research paradigm, and then study according to this model.

Topic selection and estimation

Question 1: tentatively set a topic (including research object, research question, theory or method to be adopted, etc. ). You can use subtitles. Subtitles generally point to research methods or perspectives.

Question 2: Give the research objectives and questions, and give the preliminary answers (there must be a preset preliminary conclusion before the research. The so-called "empirical analysis" can be regarded as a test of the preliminary conclusions put forward.

Question 3: Make a literature review (requirements: ① The content of literature review must be closely related to your research, that is, sort out and summarize the relevant literature according to your own research questions or contents (pay attention to the relevance); (2) Literature review should be the basis of your research and can be used as a theoretical knowledge platform or background for your research; (3) Literature review must lead to the problem you are studying, that is, comment on the existing literature according to your marginal contribution or research characteristics (pay attention to pertinence).

Question 4: Prove the problem you are studying and its importance (list the arguments of "importance" first, then give the corresponding arguments).

Question 5: Try to use measurement software (such as Eviews, SPSS, STATA or R) to import data, and make a preliminary descriptive analysis and prediction of the data.