SAS/ETS 9.22 User''''s Guide 3 ppt

Date Intervals, Formats, and Functions The custom time intervals that are available in Base SAS software can be used in SAS/ETS procedures.. 61 Overview of SAS/ETS Software SAS/ETS softw

12 F Chapter 1: What’s New in SAS/ETS 9.22

 The following tables are now available through theOUTPUTstatement: E1, E2, E3, and E8

 The SIGMALIMoption of theX11statement enables you to specify the upper and lower sigma limits that are used to identify and decrease the weight of extreme irregular values in the internal seasonal adjustment computations

 TheTYPEoption of theX11statement controls which factors are removed from the original series to produce the seasonally adjusted series (table D11) and also the final trend cycle (table D12)

 TheOUTSTAT=option of theX12statement specifies the optional output data set that contains the summary statistics related to each seasonally adjusted series The data set is sorted by the BY-group variables, if any, and by series names

 The PERIODOGRAMoption of the X12statement enables you to specify that the PERI-ODOGRAM rather than the SPECTRUM of the series be plotted in the G tables and plots

 ThePLOTS=option of theX12statement controls the plots that are produced through ODS Graphics

 TheSPECTRUMSERIESoption of theX12statement specifies the table name of the series that is used in the spectrum of the original series (table G0) The table names that can be specified are A1, A19, B1, or E1 The default is B1

 The following tables are now available through theTABLESstatement: E1, E2, and E3

 The following tables are now available through ODS: “Model Description for ARIMA Model Identification”, “Model Description for ARIMA Model Estimation”, “Final Seasonal Filter Selection via Global MSR”, “Seasonal Filters by Period”, and “Final Trend Cycle Statistics” The model description information was previously displayed in notes; an ODS table enables you to export the information to a data set The seasonal filter and trend filter tables are new

 Auxiliary variables have been added to ACF and PACF data sets that are available through ODS OUTPUT The following variables have been added:_NAME_,Transform,Adjust,Regressors, Diff, andSdiff The purpose of the new variables is to help you identify the source of the data when multiple ACFs and PACFs are calculated

The following new feature is experimental:

 The AUXDATA= option of theX12specifies an auxiliary input data set that can contain user-defined variables specified in theINPUTstatement, theUSERVAR=option of the RE-GRESSION statment, or theUSERDEFINEDstatement The AUXDATA= option is useful when user-defined regressors are used for multiple time series data sets or multiple BY groups

A new interactive application, the SAS/ETS Model Editor, enables you to define, fit, and simulate nonlinear statistical models using the MODEL procedure The SAS/ETS Model Editor enables you

Date Intervals, Formats, and Functions F 13

to use the powerful features of PROC MODEL through a convenient and interactive graphical user interface

Date Intervals, Formats, and Functions

The custom time intervals that are available in Base SAS software can be used in SAS/ETS procedures Custom time intervals enable you to specify beginning and ending dates and seasonality for time intervals according to any definition Such intervals can be used to define the following:

 fiscal intervals such as monthly intervals that begin on a day other than the first day of the month (for example, intervals that begin on the 10th day of each month)

 fiscal intervals such as monthly intervals that begin on different days for different months (for example, March of 2000 can begin on March 10, but April of 2000 can begin on April 12)

 business days, such as banking days that exclude holidays

 hourly intervals that omit hours that the business is closed

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Chapter 2

Introduction

Contents

Overview of SAS/ETS Software 16

Uses of SAS/ETS Software 17

Contents of SAS/ETS Software 18

About This Book 20

Chapter Organization 20

Typographical Conventions 21

Where to Turn for More Information 22

Accessing the SAS/ETS Sample Library 22

Online Help System 22

SAS Short Courses 23

SAS Technical Support Services 23

Major Features of SAS/ETS Software 23

Discrete Choice and Qualitative and Limited Dependent Variable Analysis 23 Regression with Autocorrelated and Heteroscedastic Errors 25

Simultaneous Systems Linear Regression 26

Linear Systems Simulation 28

Polynomial Distributed Lag Regression 28

Nonlinear Systems Regression and Simulation 29

ARIMA (Box-Jenkins) and ARIMAX (Box-Tiao) Modeling and Forecasting 31 Vector Time Series Analysis 32

State Space Modeling and Forecasting 34

Spectral Analysis 34

Seasonal Adjustment 35

Structural Time Series Modeling and Forecasting 36

Time Series Cross-Sectional Regression Analysis 37

Automatic Time Series Forecasting 38

Time Series Interpolation and Frequency Conversion 39

Trend and Seasonal Analysis on Transaction Databases 41

Access to Financial and Economic Databases 42

Spreadsheet Calculations and Financial Report Generation 44

Loan Analysis, Comparison, and Amortization 45

Time Series Forecasting System 46

Investment Analysis System 47

ODS Graphics 48

16 F Chapter 2: Introduction

Related SAS Software 48

Base SAS Software 49

SAS Forecast Studio 51

SAS High-Performance Forecasting 52

SAS/GRAPH Software 52

SAS/STAT Software 53

SAS/IML Software 54

SAS/IML Stat Studio 55

SAS/OR Software 55

SAS/QC Software 56

MLE for User-Defined Likelihood Functions 56

JMP Software 57

SAS Enterprise Guide 58

SAS Add-In for Microsoft Office 59

Enterprise Miner—Time Series nodes 59

SAS Risk Products 60

References 61

Overview of SAS/ETS Software

SAS/ETS software, a component of the SAS System, provides SAS procedures for:

 econometric analysis

 time series analysis

 time series forecasting

 systems modeling and simulation

 discrete choice analysis

 analysis of qualitative and limited dependent variable models

 seasonal adjustment of time series data

 financial analysis and reporting

 access to economic and financial databases

 time series data management

In addition to SAS procedures, SAS/ETS software also includes seamless access to economic and financial databases and interactive environments for time series forecasting and investment analysis

Uses of SAS/ETS Software F 17

Uses of SAS/ETS Software

SAS/ETS software provides tools for a wide variety of applications in business, government, and academia Major uses of SAS/ETS procedures are economic analysis, forecasting, economic and financial modeling, time series analysis, financial reporting, and manipulation of time series data The common theme relating the many applications of the software is time series data: SAS/ETS software is useful whenever it is necessary to analyze or predict processes that take place over time

or to analyze models that involve simultaneous relationships

Although SAS/ETS software is most closely associated with business, finance and economics, time series data also arise in many other fields SAS/ETS software is useful whenever time dependencies, simultaneous relationships, or dynamic processes complicate data analysis For example, an environ-mental quality study might use SAS/ETS software’s time series analysis tools to analyze pollution emissions data A pharmacokinetic study might use SAS/ETS software’s features for nonlinear systems to model the dynamics of drug metabolism in different tissues

The diversity of problems for which econometrics and time series analysis tools are needed is reflected in the applications reported by SAS users The following listed items are some applications

of SAS/ETS software presented by SAS users at past annual conferences of the SAS Users Group International (SUGI)

 forecasting college enrollment (Calise and Earley 1997)

 fitting a pharmacokinetic model (Morelock et al 1995)

 testing interaction effect in reducing sudden infant death syndrome (Fleming, Gibson, and Fleming 1996)

 forecasting operational indices to measure productivity changes (McCarty 1994)

 spectral decomposition and reconstruction of nuclear plant signals (Hoyer and Gross 1993)

 estimating parameters for the constant-elasticity-of-substitution translog model (Hisnanick 1993)

 applying econometric analysis for mass appraisal of real property (Amal and Weselowski 1993)

 forecasting telephone usage data (Fishetti, Heathcote, and Perry 1993)

 forecasting demand and utilization of inpatient hospital services (Hisnanick 1992)

 using conditional demand estimation to determine electricity demand (Keshani and Taylor 1992)

 estimating tree biomass for measurement of forestry yields (Parresol and Thomas 1991)

 evaluating the theory of input separability in the production function of U.S manufacturing (Hisnanick 1991)

18 F Chapter 2: Introduction

 forecasting dairy milk yields and composition (Benseman 1990)

 predicting the gloss of coated aluminum products subject to weathering (Khan 1990)

 learning curve analysis for predicting manufacturing costs of aircraft (Le Bouton 1989)

 analyzing Dow Jones stock index trends (Early, Sweeney, and Zekavat 1989)

 analyzing the usefulness of the composite index of leading economic indicators for forecasting the economy (Lin and Myers 1988)

Contents of SAS/ETS Software

Procedures

SAS/ETS software includes the following SAS procedures:

ARIMA ARIMA (Box-Jenkins) and ARIMAX (Box-Tiao) modeling and forecasting AUTOREG regression analysis with autocorrelated or heteroscedastic errors and ARCH and

GARCH modeling COMPUTAB spreadsheet calculations and financial report generation

COUNTREG regression modeling for dependent variables that represent counts

DATASOURCE access to financial and economic databases

ENTROPY maximum entropy-based regression

ESM forecasting by using exponential smoothing models with optimized smoothing

weights EXPAND time series interpolation, frequency conversion, and transformation of time series FORECAST automatic forecasting

MODEL nonlinear simultaneous equations regression and nonlinear systems modeling and

simulation

PDLREG polynomial distributed lag regression

QLIM qualitative and limited dependent variable analysis

SIMILARITY similarity analysis of time series data for time series data mining

SIMLIN linear systems simulation

SPECTRA spectral and cross-spectral analysis

STATESPACE state space modeling and automated forecasting of multivariate time series SYSLIN linear simultaneous equations models

Contents of SAS/ETS Software F 19

TIMESERIES analysis of time-stamped transactional data

TSCSREG time series cross-sectional regression analysis

VARMAX vector autoregressive and moving-average modeling and forecasting

Macros

SAS/ETS software includes the following SAS macros:

%AR generates statements to define autoregressive error models for the MODEL

proce-dure

%BOXCOXAR investigates Box-Cox transformations useful for modeling and forecasting a time

series

%DFPVALUE computes probabilities for Dickey-Fuller test statistics

%DFTEST performs Dickey-Fuller tests for unit roots in a time series process

%LOGTEST tests to determine whether a log transformation is appropriate for modeling and

forecasting a time series

%MA generates statements to define moving-average error models for the MODEL

procedure

%PDL generates statements to define polynomial distributed lag models for the MODEL

procedure These macros are part of the SAS AUTOCALL facility and are automatically available for use in your SAS program Refer to SAS Macro Language: Reference for information about the SAS macro facility

Access Interfaces to Economic and Financial Databases

In addition to PROC DATASOURCE, these SAS/ETS access interfaces provide seamless access to financial and economic databases:

SASECRSP LIBNAME engine for accessing time series and event data residing in

CRSPAc-cess database

SASEFAME LIBNAME engine for accessing time or case series data residing in a FAME

database

SASEHAVR LIBNAME engine for accessing time series residing in a HAVER ANALYTICS

Data Link Express (DLX) database

20 F Chapter 2: Introduction

The Time Series Forecasting System

SAS/ETS software includes an interactive forecasting system, described in Part IV This graphical user interface to SAS/ETS forecasting features was developed with SAS/AF software and uses PROC ARIMA and other internal routines to perform time series forecasting TheTime Series Forecasting Systemmakes it easy to forecast time series and provides many features for graphical data exploration and graphical comparisons of forecasting models and forecasts (You must have SAS/GRAPH®installed to use the graphical features of the system.)

The Investment Analysis System

TheInvestment Analysis System, described in Part V, is an interactive environment for analyzing the time-value of money in a variety of investments Various analyses are provided to help analyze the value of investment alternatives: time value, periodic equivalent, internal rate of return, benefit-cost ratio, and break-even analysis

About This Book

This book is a user’s guide to SAS/ETS software Since SAS/ETS software is a part of the SAS System, this book assumes that you are familiar with Base SAS software and have the books SAS Language Reference: Dictionaryand Base SAS Procedures Guide available for reference It also assumes that you are familiar with SAS data sets, the SAS DATA step, and with basic SAS procedures such as PROC PRINT and PROC SORT Chapter 3, “Working with Time Series Data,” in this book summarizes the aspects of Base SAS software that are most relevant to the use of SAS/ETS software

Chapter Organization

Following a briefWhat’s New, this book is divided into five major parts Part I contains general information to aid you in working with SAS/ETS Software Part II explains the SAS procedures of SAS/ETS software Part III describes the available data access interfaces for economic and financial databases Part IV is the reference for the Time Series Forecasting System, an interactive forecasting menu system that uses PROC ARIMA and other routines to perform time series forecasting Finally, Part V is the reference for theInvestment Analysis System

The new features added to SAS/ETS software since the publication of SAS/ETS Software: Changes and Enhancements for Release 8.2are summarized in Chapter 1, “What’s New in SAS/ETS 9.22.” If you have used SAS/ETS software in the past, you may want to skim this chapter to see what’s new Part I contains the following chapters

Chapter 2, the current chapter, provides an overview of SAS/ETS software and summarizes related SAS publications, products, and services

Typographical Conventions F 21

Chapter 3, “Working with Time Series Data,” discusses the use of SAS data management and programming features for time series data

Chapter 4, “Date Intervals, Formats, and Functions,” summarizes the time intervals, date and datetime informats, date and datetime formats, and date and datetime functions available in the SAS System Chapter 5, “SAS Macros and Functions,” documents SAS macros and DATA step financial functions provided with SAS/ETS software The macros use SAS/ETS procedures to perform Dickey-Fuller tests, test for the need for log transformations, or select optimal Box-Cox transformation parameters for time series data

Chapter 6, “Nonlinear Optimization Methods,” documents the NonLinear Optimization subsystem used by some ETS procedures to perform nonlinear optimization tasks

Part II contains chapters that explain the SAS procedures that make up SAS/ETS software These chapters appear in alphabetical order by procedure name

Part III contains chapters that document the ETS access interfaces to economic and financial databases

Each of the chapters that document the SAS/ETS procedures (Part II) and the SAS/ETS access interfaces (Part III) is organized as follows:

1 The “Overview” section gives a brief description of the procedure

2 The “Getting Started” section provides a tutorial introduction on how to use the procedure

3 The “Syntax” section is a reference to the SAS statements and options that control the procedure

4 The “Details” section discusses various technical details

5 The “Examples” section contains examples of the use of the procedure

6 The “References” section contains technical references on methodology

Part IV contains the chapters that document the features of theTime Series Forecasting System Part V contains chapters that document the features of theInvestment Analysis System

Typographical Conventions

This book uses several type styles for presenting information The following list explains the meaning

of the typographical conventions used in this book:

UPPERCASE ROMAN is used for SAS statements, options, and other SAS language elements

when they appear in the text However, you can enter these elements in