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SAS/ETS 9.22 User's Guide 139

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SAS/Ets 9.22 User's Guide 139. Provides detailed reference material for using SAS/ETS software and guides you through the analysis and forecasting of features such as univariate and multivariate time series, cross-sectional time series, seasonal adjustments, multiequational nonlinear models, discrete choice models, limited dependent variable models, portfolio analysis, and generation of financial reports, with introductory and advanced examples for each procedure. You can also find complete information about two easy-to-use point-and-click applications: the Time Series Forecasting System, for automatic and interactive time series modeling and forecasting, and the Investment Analysis System, for time-value of money analysis of a variety of investments | 1372 F Chapter 19 The PANEL Procedure Example PANEL Procedure Example 19.1 Analyzing Demand for Liquid Assets In this example the demand equations for liquid assets are estimated. The demand function for the demand deposits is estimated under three error structures while demand equations for time deposits and savings and loan S L association shares are calculated using the Parks method. The data for seven states CA DC FL IL NY TX and WA are selected out of 49 states. See Feige 1964 for data description. All variables were transformed via natural logarithm. The data set A is shown below. data a length state 2 input state year d t s y rd rt rs label d Per Capita Demand Deposits t Per Capita Time Deposits s Per Capita S L Association Shares y Permanent Per Capita Personal Income rd Service Charge on Demand Deposits rt Interest on Time Deposits rs Interest on S L Association Shares datalines CA 1949 6.2785 6.1924 4.4998 7.2056 -1.0700 0.1080 1.0664 CA 1950 6.4019 6.2106 4.6821 7.2889 -1.0106 0.1501 1.0767 CA 1951 6.5058 6.2729 4.8598 7.3827 -1.0024 0.4008 1.1291 CA 1952 6.4785 6.2729 5.0039 7.4000 -0.9970 0.4492 1.1227 CA 1953 6.4118 6.2538 5.1761 7.4200 -0.8916 0.4662 1.2110 . more lines . As shown in the following statements the SORT procedure is used to sort the data into the required time series cross-sectional format then PROC PANEL analyzes the data. proc sort data a by state year run proc panel data a model d y rd rt rs fuller parks dasilva m 7 model t y rd rt rs parks model s y rd rt rs parks id state year run The income elasticities for liquid assets are greater than 1 except for the demand deposit income elasticity 0.692757 estimated by the Da Silva method. In Output 19.1.1 Output 19.1.2 and Output 19.1.3 the coefficient estimates -0.29094 -0.43591 and -0.27736 of demand deposits Example 19.1 Analyzing Demand for Liquid Assets F 1373 RD imply that demand deposits increase significantly as the service charge is reduced. The price elasticities 0.227152 and .