Download Using SAS software in developing the regional economy and finance analysis and forecasting system

1998
INTRODUCTION..................................................................................................................................3
MATHEMATICAL MODEL OF THE REGION’S ECONOMY....................................................3
SUBSYSTEMS .......................................................................................................................................5
"CLIENT-SERVER" ARCHITECTURE ..........................................................................................5
USERS.....................................................................................................................................................6
DATA PROCESSING ...........................................................................................................................6
STATISTICAL FACILITIES...............................................................................................................7
REPORTS...............................................................................................................................................7
USING THE AERO SYSTEM FOR PREDICTION .........................................................................8
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Introduction
Server Ltd., in cooperation with some organisations of Russian Academy of
Science, created a unique Regional economics and finance analysis and
forecasting system (AERO) for a large industrial region of Russia — the
Sverdlovsk region.
AERO is implemented within the SAS System and utilize broadest
resources in carrying out statistical investigations, realization data import,
creating business graphs etc. The system gives users thoroughly developed
user-friendly interface to the main features of the SAS system. The objectoriented interface of the system is based on SAS/AF and is implemented
using the SCL programming language.
This system helps experts of the Russian Central Bank Main administration
office for the Sverdlovsk region to analyze and forecast development in the
following spheres of the region’s economy:
v Overall economic situation in the region (10 branches);
v Situation in the banking system of the region (including assets and
liabilities structure);
v Situation in the financial system;
v Structure and trends in the circulation of money;
v Securities and currency market;
v Situation in the social sphere.
In its calculations, the system tracks over 500 parameters. The data used
by this system comes from the heterogeneous (Informix, FoxPro) databases
of the Russian Central Bank and the State Statistics Committee (city
Ekaterinburg).
From a mathematical point of view, the model of the region’s economy is a
system of interconnected variables which, in an aggregated form, describes
the situation in different spheres of the region’s economy and simulates their
interrelations based on pre-set rules.
The system is designed to generate short- (1-2 months) and long-term (3-6
months) forecasts of the region’s economic development, helping analysts
find the causes for the existing situation and simulate «what if’-scenarios.
The average calculation time to analyze or forecast this region’s economic
trends is between 1 and 30 minutes depending on how complicated the
studied situation is.
AERO is the first system of this kind used in a Central Bank of Russia
division.
Mathematical model of the region’s economy
The model belongs to the class of macro-economic models. It contains
descriptions of production processes, circulation, distribution and consumption
of public product in material and financial aspects within the region with the
regard for import and export.
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To create our system we used data on the current status and trends in the
economy of Russia in general. Many of the conclusions made regarding a
region’s economic state and trends are based on the data provided by federal
economic and statistical institutions.
The system analyzes the macro-economic characteristics covering the
main processes underway in a macro-economy, such as:
• Production data split by branch and by form of ownership of respective
businesses; employment situation by branch,
• Prices and their development,
• Nominal income and spendings of private persons,
• Real income of citizens,
• Import and export of goods in the region,
• Income and spending for the regional budget,
• Financial situation in industry;
• Overall situation in the banking business;
• Bank loans,
• Money circulation in the region and between neighbor regions.
The quality of analysis is determined not by just stating the appropriate
figures, but by discovering their interrelations and the influence the
governmental and regional authorities have on them by changing:
• Taxation policy,
• Expenditures of federal and regional authorities,
• Activity on the free market,
• Regulations regarding obligatory bank reserves,
• etc.
Analytical problems that can be solved using the system:
• evaluation of after-effects of macro-economic policy on regional and
federal levels,
• exploration of economically dangerous variant of macro-economic policy,
• exploration of correlation between macro-economic indexes, which
characterize condition of real economic sectors, monetary system and
social sphere in different variants of macro-econimic policy,
• exploration of influence of outer conditions into state and trends of
development of region economy.
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In the SAS System the model is implemented as a stored SAS Datastep. It
uses a table of input variables and, as a result, returns a table of output
variables.
Subsystems
The system involved consists of following functional blocks:
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Administration implements an execution of following functions:
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editing, adding and deleting users;
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giving a user an access to another user’s data;
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viewing a journal of users actions;
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making backup copies of the data base.
Modelling allows to fulfil following actions:
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implementing modelling calculations, enabled answers the
“Why?” and “What if?” questions;
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examination the reachable set of the model, enabled answer the
“How to?” question;
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carrying out an identification of the model (tuning the inner
parameters of the model in accordance with statistical data).
Analysis allows to fulfil differents methods of statistical investigation:
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cluster analisys;
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factor analisys;
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regression analisys;
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ARIMAX - analisys.
Data Management enables:
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implementing functional modifications of time series with the aid
of user-friendly interface;
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viewing, renaming and deleting the time series.
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direct access to the SAS Language;
Data Import produces:
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data import from DBF-files and Informix data base;
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manual input of the data.
Reports produces:
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simple graph plots;
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graph with two vertical axes;
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bar charts;
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pie charts;
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block charts.
"Client-Server" architecture
The system is realised in «client-server» architecure, with the use of
SAS/CONNECT and SAS/SHARE packages, that enables to use existance
technical facilities with the maximum effectivity. Users of the system work with
a personal computer in the Windows 3.11/ Windows 95 environment. Data
bases, data and application servers is running in UNIX operational system.
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Connection between client and server is implemented via TCP/IP protocol. On
the both platforms the SAS environment is running.
Hardware and platform independence of the SAS environment makes easy
to change the system architecture from local to «client-server» (switching is
done by changing the value of one macro-variable).
Tasks demanding high productivity or relating with proccessing of large
amounts of data (model calculations, for example) are running on the server.
Procedures which don’t demand large outlays are running on the client.
These are data import from local data bases, graphics presentation, work with
text editors or spreadsheets etc.
Users
Users of the system are divided into three categories:
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Administrator performs:
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users actions control;
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outer data configuration;
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data base support;
Analyst fulfils:
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modelling calculations;
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reachable set explorations;
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statistical investigations;
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primary data processing;
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reports creating;
Operator perfoms:
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outer data import;
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manual data input.
Data processing
Heterogeneity of statistical data toward store formats and units of measure
offer leads to large difficulties in their use. Thus wide capability of the SAS
Systems for import of mixed data provide an great assistance. Another
particular problem is reliability of receiving data. Implemented method of data
processing enables obtaining reliable, unified data suitable for further
investigations.
Data processing consists of the following:
• Outer data configuration (describe from and how to get the data,
Administration subsystem).
• Outer data import (Import subsystem).
• Reduction to a common unit of measure (Data Management subsystem).
• Data verification and Data refinement (Data Management subsystem).
• Reduction to a common time intervals (Data Management subsystem).
• Exploration (Modelling and Analysis subsystems).
• Making reports (Reports subsystems).
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Statistical facilities
In the system involved a traditional statistical instrument of data analysis is
also presented. We use SAS/STAT and SAS/ETS packages.
Following kinds of statistical analysis has been selected:
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cluster analysis, which allows to choose from a great number of time
series the most intersected;
factor analysis, which fulfils a retrieval of hypothetic external factors,
influenced on a definite group of time series;
regression analysis, which can be used in order to prove a hypothesis
of dependences between time series;
ARIMAX-analysis, which is ordered to create a mathematical model
both for one time series and for several time series.
Every kind of analysis is described by a set of parameters, such as
variables in hand, evaluation method etc. This set of parameters, named as
template, can be stored in the data base and restored for further analysis.
Results of analysis can be viewed as a tables of coefficients, graphs etc.
Reports
According to the most used kinds of reports in the Russian Central Bank
Main administration office for the Sverdlovsk region from the variety of reports
of the SAS/GRAPH package has been selected the following:
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simple graphs:
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graphs with two vertical axes;
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additive graphs;
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additive normalized graphs;
factor graphs;
bar charts:
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additive charts;
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additive normalized charts;
pie charts;
block charts.
Besides, for every kinds of the graphs one can:
• assign intervals on every axes;
• perfom pre-aggregation of time series;
• set draw type (different color, line type or marker) and define desired
colors, line types or markers;
• change frequency of tick marks on either axes;
• show grid;
• show reference lines;
• put into graph values of time series in particular points;
• assigne titles, axes labels, legends etc.;
• store parameters of the graph for further utilization in Analysis or
Modelling subsystems;
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• store made graphs for further viewing;
• send graphs into printer or into WMF-, BMP- files.
Using the AERO system for prediction
During the period of experimental exploitation of the system, one-month
predictions of definite factors had been perfomed, and in a month they was
compared with statistical values. This experiment showed that about 70% of
predicted values had a good correlation with statistical data.
Nowdays the system is used in Russian Central Bank Main administration
office for the Sverdlovsk region.
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