Dynamic microsimulation

Research articles · Dec 2, 2024

A Micro-Macro Interactive Simulation Model of the Swedish Economy

Gunnar Eliasson

Volume 17(2) Summer 2024

Cite as: G. Eliasson; 2024; A Micro-Macro Interactive Simulation Model of the Swedish Economy; International Journal of Microsimulation; 17(2); 60–128. doi: 10.34196/ijm.00292

Abstract

Work on this micro based macro model of the Swedish Economy began in late 1974 as a joint project between the Federation of Swedish Industries, IBM Sweden and the University of Uppsala. This is an edited version of several instruction manuals I wrote for the coding and later programming of that model. It was published in December 1976 as "A micro - macro Interactive Simulation Model of the Swedish Economy" by the Federation and IBM in two parallel editions. A technical pseudo code to facilitate the final coding of the model in APL, authored jointly by myself, Mats Heiman and Gösta Olavi, was appended to that publication. This republication of the 1976 document, has been slightly trimmed, and lack the Foreword by the President of the Federation, Author’s Remarks, and the Pseudocode. The Pseudocode is however available from the Journal online as (Eliasson et al., 1976). It details the specifications and highlights the modular design of the model and should be helpful for anybody who might want to reproduce a version of the model.

Originally this model, called MOSES, for Model Of the Swedish Economic System, was designed to facilitate understanding and quantifying the role of markets and production firms in economy wide economic development. Of particular interest were the consequences of markets being disturbed by inflation. The modelling approach was bottom up, drawing extensively on empirical research in business economics, not least on my own study on business economic planning practices (Eliasson, 1976a). The model has a general design in that it integrates a standard Keynesian demand driven macro model with a Leontief type input output sector structure. The manufacturing subindustries, furthermore, are populated with boundedly rational (“ignorant”) firms (Simon, 1955; Simon 1959). These firms make up the core market governed supply machinery of the model, and integrate product, labor, and financial market considerations within their business plans. Firms compete in the markets of the model. Their plans and decisions are guided by Stockholm School ex ante price expectations and learning from feed backs of ex post outcome experiences. Schumpeterian entrepreneurs enter markets unexpectedly and compel incumbents to perform. Market competition thus self-coordinates the entire model economy under an upper technology constraint embodied in new investments of firms. The government may intervene in markets, but there are no artificial external equilibrium constraints imposed. I had no ambition to build a micro foundation of existing macro theory, neither has the model been designed to provide forecasts to support policy. The ambition has been to understand what government can do to the economy as one of many monopoly actors with boundedly rational insights.

The ambition was empirical, to begin with to reproduce and understand the long term and cyclical market dynamics of a Sweden like industrial economy. To that end a separate annual Planning Survey to Swedish manufacturing firms, tailored to the needs of the model, was started at the Federation. That survey will eventually provide statistics also to test the model’s capacity to generate distributional characteristics of the Swedish economy.

This article contains 12 figures and 4 tables.

Figures

Figure 1. Business decision system (one firm).
Figure 2. Production system.
Figure 3. Consumption system and prod-markets.
Figure 4. Long-term plan.
Figure 5. INV-decision.
Figure 6. Trend comparison (MACRO – INDUSTRY), annual (change in percent).
Figure 7. (A) Profit and loss statement. (B) Cash flows. (C) Balance sheet.
Figure 8. Shifting of production possibilities curve because of depreciation and new investments in best practice technologies.
Figure 12. (A) Initial position, (B) new transitory initial position after retirement; (C) new preliminary initial position before labour market search.
Figure 9.
Figure 10.
Figure 11.

Tables

Table 1. Model modules
Business system (manufacturing firm model)
Operations planning (short term)
 Production system
 Inventory system
 Expectations
 Profit targeting
 (Cash management)
Investment-Financing (long term)
 Investment plan
 Long term borrowing
Household consumption (macro)
 Buying/consuming
 Saving
Service sector (macro)
Government sector (macro)
 Employment
 Taxes/transfers
 Economic policy
Note: So far only Government employment has been entered into model, and government production is assumed to be proportional to government employment .
Other production sectors (six sectors from input/output table)
Foreign connections
 Prices - exogenous
 Exchange rate exogenous
 Interest rate - exogenous
 Export volume- endogenous for each firm
 Import volume- endogenous (macro)
 Trade assets and debts (endogenous by firm)
Markets
 Labor market
 Product market
 Financial market (a bank)
Exogenous variables
 Foreign prices: one for each of the four sub markets of manufacturing
Foreign Interest rate:
 Technology: The rate of change in labor productivity of new investment vintages.
 The labor force.
Table 2. Step wise master criteria for statistical fit.
A.Certain macro industry trends approximately right (Within 1/2 percent) over a 20 year period (see trend chart Figure 6).
B.Same trends for the four sub industries.
Same criteria for 5-year period.
C.Micro. Compatible with “stylized facts”. No obvious “misbehavior”.
D.Identify (time reaction) parameters that work uniquely (or roughly so) on cyclical behavior around trends.
Table 3. Calibration procedure (trend fitting)
1. Find first reference case. Assess its performance in terms of A in Table 3.
2a). Perform sensitivity analysis with a view to finding new specifications that improve performance in terms of A.
2b). Ditto with a view to investigating the numerical properties of the model within a normal operating range (analysis). Check and correct if properties can be regarded as unrealistic.
2c). For each new reference case, repeat the whole analysis of 2 b) systematically. The purpose is to ensure, each time, that the new reference case is a better specification and not a statistical coincidence and that the properties of the system revealed by the sensitivity analysis above, and judged to be desirable, are presented in the new reference case.
2d). Subject model to strong shocks. Check for “misbehavior”. (For instance, fast explosive or strong contractive economy wide behavior that have been generated by external shocks that may be considered extreme. If so, ponder the possibility that the model may generate empirically reasonable surprises that have not yet been observed.
3. Define new and better references case. Repeat from 2.

Find first reference case. Assess its performance in terms of A in Table 2.

Balance sheet of individual firm consistently generated each quarter
AssetsDebt
K1NW (Residually determined)
K2BW
SUM = A= A