Firm Turnover and the Rate of Macro Economic Growth: Simulating the Macroeconomic Effects of Schumpeterian Creative Destruction

During the last few decades increasing attention has been paid in economic and econometric modeling to the role of investment project selection and firm turnover in economic growth. References are sometimes made to Joseph Schumpeter’s notion of Creative Destruction, for instance in Audretsch (1999); Aghion and Howitt (1992); Aghion (1998); Audretsch (1995b); Dasgupta and Stiglitz (1981); Jovanovic (1982); Jovanovic and Lach (1989); Wagner (1999); Winter (1964); Winter (1986). This literature is currently being integrated with so called new growth theory, see for instance and Pakes and Ericson (1998). Caves (1998) is an early summary of the literature.

One reason for this reorientation of research on economic growth may be a renewed interest in Schumpeter (1911) in whichJoseph Schumpeter’s theory of economic development, identifies the introduction and use of new ideas (innovations) – in entering as well as in established firms – as a major source of economic prosperity. Much of this Schumpeterian recognition is however only nominal, in that modellers struggle to fit entrepreneurial entry into neoclassical equilibrium models that we consider incompatible with the existence of reasonably defined entrepreneurs. Schumpeter (1911) himself regarded the entrepreneur a disturber of a Walrasian equilibrium. While the MOSES model, that we simulate in this study, can be seen as a general dynamic game of monopolistic competition kept in constant motion by endogenous entrepreneurial entry competition (Eliasson, 1985), the influential survey article by Franco Modigliani (1958) on new oligopoly theory had had little to say on empetitive entry as a price determining factor, and probably limited the interest in entry among economists for years. When that interest at last arrived, even empirical modellers, unfortunately have considered it mandatory to shoehorn entrepreneurial entry into incompatible equilibrium straitjackets.

Exit, is the companion of entry in Schumpeterian Creative destruction. It plays the necessary role of sorting out entrants that the market test has rejected and, in general, to set resources free for expanding firms. Exits of failed businesses therefore become a natural transactions cost for economic development , and an imp0rtant element in Schumpeterian creative destruction (Table 1). In this process of creative destruction (the term first appeared in Schumpeter, 1942) one could, therefore, argue that a faster turnover of firms should reflect a more intense market search for new business opportunities and a reallocation of resources away from firms that have been unsuccessful in identifying and commercializing new business opportunities, to firms that are successful, or more to the point, been unable to cope with competition. Hence, we should expect a positive correlation between the turnover of firms and growth. Empirical support for this is, for instance, provided by Haltiwanger et al. (2004) and Fogel et al. (2006). However, as the market selection dynamics of the MOSES model will demonstrate below, underlying this proposition is a positive market determined relationship between entrepreneurial entry and exits such that increasing returns to continued search (pushed by entrepreneurial competition) for investment opportunities occurs and successful winners dominate over exiting losers (Eliasson, 2003; ; Eliasson, 1995). While experiments on the MOSES model had already demonstrated that the organization of markets, and notably market flexibility, was instrumental in creating the positive relationship to firm turnover (Eliasson and Taymaz, 2000), this paper conjectures that this positive relationship is nonlinear, and will eventually bend down as an increasing rate of structural change, reflected among other things in fast changes in the population of firms, lowers the reliability of market price signaling and disturbs the market self-coordination functions.

Neoclassical equilibrium economics has difficulties with the concept of systemic (non random) investment mistakes from which agents can learn to improve next period plans. Firms in MOSES form price expectations in the three markets of the m0del (product, labour and financial) and integrate them in their investment, production and recruitment plans (Eliasson, 1976b). Price expectations , however, normally come out more or less wrong; an instance of Stockholm School ex ante-ex post economics. After market confrontations with other firms, most plans thus come out more or less in error. Two types of mistakes are constanly made. Most commonly mistakes take too long to be identified and corrected (Type I mistakes). Most serious, however, are that winners may be lost, often for good (Type II mistakes, see (Eliasson and Eliasson, 1996). Type II mistakes are difficult to observe, but their existence can be determined by running counterfactual experiments on the MOSES model (see further below).

To our knowledge little attention has been paid to the feedback effects on production structures, of mistaken price expectations and on firm turnover. One would expect that a constantly ongoing interaction between interdependent price and quantity structures will eventually affect the reliability of prices as information carriers negatively and create a disorderly market behavior that is detrimental to growth (Eliasson et al., 1983; see also Brown et al., 2006). We hypothesize that the positive growth effects of increased firm turnover dominate up to a limit, then to turn negative as the rate of entry and structural change increases, competition intensifies and the rate of firm turnover tilts towards a dominance of mistaken plans due to a disturbed price signaling in markets, and an increased rate of business failure. Destruction begins to dominate over positive creation.

The complexity and the long term nature of the non linear relationships involved make it practically impossible to capture these effects by standard econometric methods and for two reasons. First, time series panel data of sufficient length to reveal the non-linear property are not available. Second, the time span we now consider will include so many interactive influences that the model complexity needed to capture them, and keep them apart, will take us beyond the current capacity of econometric methods. It may also be the case that the negative macro consequences begin to show sufficiently early for agents, including policy makers, to take notice and react to counter these effects. More likely however is that negative consequences take so long to show statistically that their origin cannot be identified, and that corrective measures are both too late and wrong (Eliasson and Taymaz, 1992). To establish the possible theoretical existence of such a long term downside of Schumpeterian Creative Destruction only simulation analysis will do. And MOSES type micro to macro models is the only way of getting some quantitative control of the policy situation. Hence, this analysis becomes a theoretical inquiry into the possible existence of such a negative effect in a controlled experiment. In such a controlled experiment (Eliasson, 1991a; Eliasson et al., 2004), we expect a situation of chaotic behavior to emerge. Under normal circumstances agents make mistakes and respond to mistakes but the markets of the economic system at large will possess sufficient self-regulating capacities to restore order. Above a certain rate of turnover, however, we propose that this market self-regulation will begin to malfunction.

In this paper growth is simulated on the firm based macro model MOSES under different institutional conditions. Growth in this model occurs through the experimental selection of innovations in dynamically competitive markets populated by heterogeneous business actors that make up plans that are rarely correct even in expectation. New firms that enter markets raise competition and force reorganization and rationalization, or exit on incumbent firms. Depending on a number of circumstances this Schumpeterian Creative Destruction (Table 1) in what we call an Experimentally Organized Economy (EOE) may be dominated by positive creation or negative destruction. The internal balance between equilibrating and disturbing forces is determined endogenously in the product, labor and financial markets that are integrated through the internal, profit oriented decisions of individual firms.

The main purpose of this paper is to demonstrate the existence of such a balancing point within this firm based macro model economy based on empirically reasonable assumptions.¹

Testing for the presence of the long-term negative influence we precede in two steps. First, we present the model of the Experimentally Organized Economy in which business mistakes become part of transactions costs. Second, we simulate the model in repeated experiments to establish the existence of a nonlinear long-term relationship between the rate (and balance) of firm turnover and macroeconomic growth that (the proposition) eventually turns negative as the rate of entry is increased, and the rate of structural change occasioned creates market disorder.

Entry, and even more so exit of firms caused by mistaken decisions, for long was an avoided issue in economic theorizing. Because of the mathematical difficulties of allowing for autonomous micro behavior in neoclassical equilibrium models´such phenomena were neglected, and even mistakenly regarded as irrelevant. As an empirical phenomenon entry and exit, however, exist, and some economists observed early that economic growth might be affected. Some empirically oriented economists (Acs and Audretsch, 1989; Baldwin and Gorecki, 1987; Baldwin and Gorecki, 1989; Baden-Fuller, 1990; Du Rietz, 1975; Hause and Du Rietz, 1984; Highfield and Smiley, 1987) defied the theoretical problems and launched the needed ad hoc empirical inquiries to learn about the magnitudes involved in firm turnover. Econometric models estimated were also loosely related to mainstream economic theory, and a closer analysis would demonstrate that they normally conflicted with the assumptions of the mainstream equilibrium model. For this reason interest among economists in the growing research on entrepreneurship and new firm formation has not been overwhelming. For a long time conventional wisdom was (e.g., Eriksson, 1984) that “industry growth comes mainly from existing firms”. Since the MOSES model was solidly based on observation in Eliasson (1976a) it was simply impossible to neglect the empirical facts of entry and exit, and an entrepreneurial entry slot was quietly sneaked in, despite advice to the contrary, in Eliasson (1978a). In simulation analyses, Eliasson (1991b) and Eliasson and Taymaz (2000) also demonstrated (1) that entry induced by "above equilibrium profitability" , and (2) exiting firms that had run out of equity, significantly affected long-run growth, but in complex ways of market interactions. The long time needed for significant effects of new entry to appear at the macro level had been demonstrated already by Du Rietz (1975). Johansson (2001), furthermore, showed that new and small firms accounted for all growth in employment in the Swedish IT industry between 1993 and 1998, while the large firms as a group significantly reduced their employment. Entry also “became seen as one of the main mechanisms by which long-run equilibrium” is restored (Audretsch and Mata, 1995). There are however theoretical problems associated with trying to understand the economy wide economics of firm entry, or for that matter entrepreneurship, in terms of neoclassical orthodoxy. Already Schumpeter liked to refer to his entrepreneur as a disturber of Walrasian equilibrium. Kirzner (1973) , on his side, proposed that the entrepreneur should be seen as the restorer of equilibrium states. On that the MOSES modeller has to object that if market transactions costs associated with non stochastic business failure is a normal cost of economic development and an important explanatory factor in economy wide market self- coordination, the walrasian equilibrium central to neoclassical orthdoxy will not be compatible with the existence of reasonably defined entrepreneurs and endogenous exit, and should be kept out of models fearturing Schumpeterian entrepreneurial competition and the entry and competitive exit of firms. This theoretical complication arises when Stockholm School ex ante-ex post considerations are allowed into the market micro to macro machinery (Eliasson, 1983; Eliasson, 1984; Eliasson, 1991a; Eliasson, 1992; Eliasson, 2003).

The stylized facts also are that rates of entry and exit develop parallel, but vary between economies (Caves, 1998; Geroski, 1995; Siegfried and Evans, 1994). Furthermore, there is econometric evidence of rates of entry being dependent on rates of return in the firm and/or in the market entered, but the evidence varies between studies. The reason for the absence of such relationships in some studies might be that entrants are generally overoptimistic and believe their technology to be superior to that of their incumbent competitors in the market and be independent of the situation at large in the market. In reality then, entry depends on expected profitability on the part of the entrant, which is difficult to measure. Highfield and Smiley (1987), however, believe that the lack of empirical support of this neoclassical relationship in other studies (for instance in the much quoted early Orr, 1974) depends on a “ lack of sophistication in modeling entrepreneurs´ expectations about future profit rates”. It is also hard to believe that there should be no relationship between the aggregate profitability situation in a market and the rate of entry in the same market. Stylized facts, in fact, are that entry increases and exit decreases with profitability and growth in the local markets (Siegfried and Evans, 1994).⁵

Another stylized fact is that the average performance of entrants is lower than that of incumbents but that the variation in performance in the entry sample is very much larger (Granstrand, 1986; Caves, 1998). This suggests that newly established firms have a higher exit rate than older incumbents, a property empirically supported by Audretsch and Mahmood (1994); Audretsch and Mahmood (1995) and Caves (1998) survey of empirical literature. This property and the specification of innovation supply and firm entry are also very similar to Jovanovic (1982) model of passive learning of firms, i.e. firms learn of their own capacities by being subjected to the reality of markets. For some, trained in standard micro production analysis, this may seem counter intuitive, since for them old and obsolete plants should exit first. On this Honjo (2000) finds that new firms have greater difficulties surviving than old firms, notably in markets with high entry rates and (therefore) intense competition. Audretsch (1995a) observes that survival rates (over a decade) are lower in highly innovative than non-innovative markets, but entrants that have survived exhibit higher growth rates than other firms. This is also the result of Johansson (2001). Also Baldwin (1995) found that firms that survive exhibit fast growth rates. The higher exit rate of new firms than of incumbents has long been a property of the MOSES model and for exactly the reasons given above (Eliasson, 2000).

Generally speaking, the short-term effects of entry on aggregate output appear not to be large, and slow in coming (for a survey see Eliasson, 1991b). The important long- term effects of new entry are indirect and systemic and are even slower in coming. To quantify them you need a full scale dynamic, micro based model of the entire economy.

Firm turnover involves innovative entry, learning and imitation, enforced reorganization and competitive exit, together making up the Schumpeterian Creative destruction process of Table 1. This process, which is endogenous and the explicit driver of the micro macro simulation model MOSES, may or may not generate macroeconomic growth, depending on economic circumstances endogenous in the model.

4.1. Economic Growth through Competitive Selection

One could say that the four mechanisms of Schumpeterian Creative Destruction in Table 1 updates a set of performance characteristics represented each period through the rankings of as many Salter curves (see Figure 1). Under positive circumstances (incentives, competition, competence) the Salter curves are shifted outwards. Economic growth occurs. This positive outcome is, however, not guaranteed. Circumstances might be negative and destruction dominate, changing the shape of the Salter curves. Stagnation might follow instead.

Figure 2

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Firms are guided in their investment decisions by the expected return to capital over and above the market interest rate. The key selection problem of economic growth however is that winning innovations are identified and not lost, and succesfully carried on to industrial scale production and distribution. Market selection is a complex and resource using process, lost winners representing a large social cost in terms of lost output. Competence bloc theory presents the critical actors involved in technology selection, commercialization of innovations and scale up. Otimal market selection performance occurrs when the long term macroeconomic incidence of two kinds of economic mistakes are minimized; keeping losing projects on the books for too long (Type I mistakes) and losing winners (Type II mistakes), type II mistakes being the by far most important. While close to impossible to observe directly, the existence of type II mistakes can however be demonstrated through simulation experiments on the MOSES model, as can also the entire optimization process by designing and testing different market organizations (Eliasson and Eliasson, 1996; Eliasson, 2001; Eliasson, 2003).

Short-term production decisions and recruiting are guided by a criterion called Maintain or Improve Profits (MIP). Firms constantly climb expected profit hills that change from period to period because of innovation and the ongoing climbing traffic, and keep modifying their supply plans and recalculating their expected profits as market prices change endogenously and as they learn from experience (Eliasson, 1976a; Eliasson, 1977; Eliasson, 1991a ). The more expectational mistakes the firms make the more cautious they become. However, the more disturbed market pricing, the larger the incidence of business mistakes, and the more likely that winners will be lost (Type II mistakes), the cummulated consequences of which may be very large and only emerge with a long lag. Type II mistakes that we expect occur in MOSES simulations, will bias long term growth in the entry experiments negatively.

Each experiment has been rerun by gradually increasing the entry parameters exogenously. Figure 2, Figure 3, Figure 4, Figure 5 show the average value of GNP in the experiments, and the trend line shows the regression “curve” estimated by regressing the GNP level on a quadratic function of the entry parameter.

Figure 3

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Figure 4

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Figure 5

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Figure 6A shows the entry rate. The entry rate is defined as the proportion of net entrants at the end of the simulation (year 75). As may be expected, the entry rate increases almost monotonically by the value of the entry parameter to reach some 80 percent. Figure 6B shows the effects of the entry parameter on the exit rate that is defined as the ratio between the number of exits and the number of firms at the beginning of the simulation (there were 225 firms at year 0). As expected, the entry rate also increases the exit rate because of the increased competition in the markets.⁷

Figure 6

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The parameters in the entry function are moved such that the entry rate is steadily increased. The exit rate is completely endogenized, but faster and slower exit can be specified in terms of the criteria model firm management applies to close down a firm.

The endogenized balance between entry and exit is shown in Figure 6. The exit rate in Figure 6C decreases compared to Figure 6B because the firm population increases faster than the number of exits. To demonstrate the change over from the approximately linear to the non-linear macroeconomic response to firm turnover we present four sets of figures showing the GNP levels after 15, 35, 55 and 75 years respectively (Figures 2–5). For 75 years also manufacturing output is shown (Figure 5B).

Up to 15 years the levels of GNP increase proportionally with the rates of entry and exit (Figure 2). Decreasing returns to further entry begin to show as a small down bending of the trend curve after 35 years, which becomes pronounced after 55 years and very striking at 75 years both for GNP and manufacturing output. The downward bending at year 75 also comes at a lower turnover rate than at years 35 and 55.

For our purposes it is sufficient to establish the existence of this non-linear negative effect under the dynamic market assumptions of the simulation. The negative effects however take a long time coming, but the final surge may become very strong. This is also what we had conjectured onn the basis of prervious experience from the MOSES model on the cumulative incidence of Type II expectational mistakes, or on the market disorder created by speeding up market transactions excessively

It is not meaningful at this stage to draw any further quantitative conclusions. For obvious reasons the number of firms populating the model is only a tiny fraction of the number of firms of the real Swedish economy. The scales of the entry, exit and entry parameters in Figure 6 do not say anything about the rate at which firms are turned over per period or year. We can observe from Figures 6A, B that there is a parallel increase in the entry and exit rates, also as expected. The long-term growth to the 75-year horizon peaks at an entry parameter between 100 and 150. At that turnover level some 60 percent of the end population of firms is new. Many new entrants have exited during the 75-year period.⁸

On the exit side (Figure 6B) long-term (75 years) output peaks when exits number some 43-44 percent of the initial (year 0) population of 225 firms. While both the number of entrants and exits increases, the number of entrants is much larger than the number of exits. On the entry side, the “optimal” number in the model simulation amounts to some 1.1 percent of the stock of firms per year, which is slightly above the average of just below 1 percent in the 1970s and 1980s in Swedish manufacturing (Andersson et al., 1993).⁹ We have no corresponding exit data and apparently the exit rate simulated is much lower (Figure 6C). We can only say that if the scale would be calibrated to the level of the real economy the proportion of firms replaced through Schumpeterian creative destruction each period would be very large as you go to the right in Figure 6. There is, however, the possibility, indicated earlier, that the strong negative bend on the growth curve at very high rates of entry after 50 years depends on a too low exit rate (unbalanced turnover) and would go away if we speed up the rate of exits by making management more profit conscious. Hence, the extreme bending down in Figure 5A and B is unlikely to occur in reality because such high entry rates rarely occur for such long periods. But the effect is there to show. To capture it in a time series analysis on entry, exit and growth rates, generated by the model over a 75 year period, a very different model than the standard linear regression model would, however, be needed.

Literature increasingly reports strong econometric support for a positive linear relationship between entry and growth and also on a positive influence on production growth of a balanced entry and exit process. Firm turnover, however, involves a reallocation of resources and structural change. Above some limit the rate of structural change will begin to affect the reliability of price signaling in markets negatively, and raise the incidence of mistaken business decisions.Winners may get lost (Type II mistakes). To test for a long- run, non-linear negative influence of a very fast and (perhaps) unbalanced firm turnover process very long time series data that are not available are needed. Simulation has been the only way of establishing the possible theoretical existence of this phenomenon. It may even be so that the firm turnover rate needed to generate disturbances in the price system has to be so extreme that it “cannot occur” under normal circumstances in reality. If so, the negative relationship will not be observable. The micro-to-macro model of the Swedish economy has been found to embody the expected non-linear characteristics and for the reasons hypothesized. The output growth curve began to bend down after about half a century at entry rates that were far above recorded entry rates during the past 20 years. In that sense the model economy can be characterized as robust in response to price disturbances.

Long-term sustained, fast and stable growth in macro economic output is a desired ambition of industrial policy. We can say that the simulation experiments reported on directly perform the transformation of Table 1 into macro change, firms being guided in their investment and production decisions by price expectations and a profitability criterion called Maintain or Improve Profits (MIP. See (Eliasson, 1976b) as they compete for income in product markets and for resources in capital and labour markets. Growth occurs if winning projects/firms are opting for investment and growth and losers are contracting or shutting down. This ideal market dynamic may not always be the outcome, however. Long – term investment decisions in MOSES firms are guided by the expected return to capital over the market interest rate. The MIP criterion accepts that firms are temporarily inferior performers by that rate of return criterion, but force them to constantly improve their performance. Hence, if firms cannot meet their own short-term profit standards they may decide to contract operations rather than invest and expand. In this particular set of experiments unreliable price signaling in markets may lead both to mistaken production and investment decisions and tilt an increasing number of firms onto a lower than possible growth path. Similarly, unbalanced growth, with too few exits may raise factor prices and tilt expansive firms onto lower growth paths.¹⁰

We have demonstrated in this paper that faster growth for some time may mean significantly less growth later, at a stage when it may be impossible to restore the long-term outcome. Sustainability involves an “optimization” over a very long time span. An interesting question is if the policy maker should have a role in that optimization decision. The first problem to resolve, then, is to figure out the reasons for the long-run negative effect of fast turnover on growth. Wouldn’t the economy have developed endogenous market correction mechanisms that eliminate such long-run effects? The negative effects (and first) take a long time in coming. They cannot be discovered ahead of time by analytical methods so there is no opportunity for policy makers to act ahead with precise targeting of counter measures. Second, even if they had known what was coming, policy makers might not understand what to do and easily enact mistaken policies (Eliasson and Taymaz, 1992). Third, part of the difficulties of understanding the social and econmic costs of disturbed markets has to do with the incidence of lost winners (Type II mistakes) that may even permanently hold back economic development (see Ballot and Taymaz, 1998 on the incidence of technlogical lock-ins in the MOSES economy). Fourth, however, the low entry rates per year should be seen in relation to the total firm population. The model firm population features much less heterogeneity than the real firm population. Hence, the model economy is not as robust as the real economy and the downward bending of the curve should occur at a lower entry rate than in reality. Accounting for that one might perhaps say that the large entry rates to the right in Figure 6A, involving a very large increase in the firm population, are not sustainable for an entire economy for such a long period, only locally and then the realistic range of entry over a long period would be just above or just below the optimum, but not so far off. Then negative effects may go undiscovered for decades. In conclusion one might at least take note of the fact that this observation from model experiments is in line with Swedish experience over the last 80 years: a steady lowering of new firm formation per year from a peak around 3 percent in the 1920s to a low around 0.5 percent in the 1990s (Andersson et al., 1993). As a consequence industrial structures increasingly became dominated by a group of incumbent large firms, several of which ran into trouble during the oil crises years of the 1970:s. To prevent a large scale destruction of obsolete firms and a negative immediate employment effect the exit process of the real economy was slowed by an extreme subsidizing program. This subsidy program and alternative disbursements of public money under the same budget constraint has been reenacted on the (real) firms in the model, mostly the shipyards. Sweden at that time was the second largest shipbuilding nation of the world supplying almost 10 percent of output. Today none of these shipyards exists, The creative destruction had been artificially slowed by industrial policy interference, which was socially very costly in terms of lost output, all being estimated in an economy wide cost benefit study on MOSES Carlsson (1983). Since all receipients of industrial subsidies were represented in the data base of MOSES subsidies could be allocated on the now dead firms exactly by amount and time received. Those firms in fact only survived in the model simulation (as well as in reality) only as long as the subsidies were doled out. If the money was taken away, and redistributed equally on all firms through a lowering of the payroll tax, the crisis firms all exited and the economy soon recovered to grow on the earlier faster trajectory, albeit at a lower level. So government had been adding worse to bad by subsidizing the worst performers that were also paying the highest wages (steel and shipyards; Carlsson, 1983) in Sweedish manufacturing. The negative impact on the real Swedish economy of the extreme subsidy program began to be fully observable and understood only as late as the early 1990s. and the MOSES simulations were instrumental in making that collossal policy mistake statistically visible.

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Author details

1. Gunnar Eliasson

   The Ratio Institute (and The Royal Institute of Technology), Stockholm, Sweden

   For correspondence

   g.eliasson@outlook.com

2. Dan Johansson

   The Ratio Institute (and The Royal Institute of Technology), Stockholm, Sweden

3. Erol Taymaz

   Department of Economics, Ankara, Turkey

   For correspondence

   etaymaz@metu.edu.tr