sectoral balances

Consistent modelling and inconsistent terminology

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Simon Wren-Lewis has a couple of recent posts up on heterodox macro, and stock-flow consistent modelling in particular. His posts are constructive and engaging. I want to respond to some of the points raised.

Simon discusses the modelling approach originating with Wynne Godley, Francis Cripps and others at the Cambridge Economic Policy Group in the 1970s. More recently this approach is associated with the work of Marc Lavoie who co-wrote the key textbook on the topic with Godley.

The term ‘stock-flow consistent’ was coined by Claudio Dos Santos in his PhD thesis, ‘Three essays in stock flow consistent modelling’ and has been a source of misunderstanding ever since. Simon writes, ‘it is inferred that mainstream models fail to impose stock flow consistency.’ As I tried to emphasise  in the blog which Simon links to, this is not the intention: ‘any correctly specified closed mathematical macro model should be internally consistent and therefore stock-flow consistent. This is certainly true of DSGE models.’ (There is an important caveat here:  this consistency won’t be maintained after log-linearisation – a standard step in DSGE solution – and the further a linearised model gets from the steady state, the worse this inconsistency will become.)[1]

Marc Lavoie has emphasised that he regrets adopting the name, precisely because of the implication that consistency is not maintained in other modelling traditions. Instead, the term refers to a subset of models characterised by a number of specific features. These include the following: aggregate behavioural macro relationships informed by both empirical evidence and post-Keynesian theory; detailed, institutionally-specific modelling of the monetary and financial sector; and explicit feedback effects from financial balance sheets to economic behaviour and the stability of the macro system both in the short run and the long run.

A distinctive feature of these models is their rejection of the loanable funds theory of banking and money – a position endorsed in a recent Bank of England Quarterly Bulletin and Working Paper. Partially as a result of this view of the importance of money and money-values in the decision-making process, these models are usually specified in nominal magnitudes. As a result, they map more directly onto the national accounts than real-sector models which require complex transformations of data series using price deflators.

Since the behavioural features of these models are informed by a well-developed theoretical tradition, Simon’s assertion that SFC modelling is ‘accounting, not economics’ is inaccurate. Accounting is one important element in a broader methodological approach. Imposing detailed financial accounting alongside behavioural assumptions about how financial stocks and flows evolve imposes constraints across the entire system. Rather like trying to squeeze the air out of one part of a balloon, only to find another part inflating, chasing assets and liabilities around a closed system of linked balance sheets can be an informative exercise – because where leverage eventually turns up is not always clear at the outset. Likewise, SFC models may include detailed modelling of inventories, pricing and profits, or of changes in net worth due to asset price revaluation and price inflation. For such processes, even the accounting is non-trivial. Taking accounting seriously allows modellers to incorporate institutional complexity – something of increasing importance in today’s world.

The inclusion of detailed financial modelling allows the models to capture Godley’s view that agents aim to achieve certain stock-flow norms. These may include household debt-to-income ratios, inventories-to-sales ratios for firms and leverage ratios for banks. Many of the functional forms used implicitly capture these stock-flow ratios. This is the case for the simple consumption function used in the BoE paper discussed by Simon, as shown here. Of course, other functional specifications are possible, as in this model, for example, which includes a direct interest rate effect on consumption.

Simon notes that adding basic financial accounting to standard models is trivial but ‘in most mainstream models these balances are of no consequence’. This is an important point, and should set alarm bells ringing. Simon identifies one reason for the neutrality of finance in standard models: ‘the simplicity of the dominant mainstream model of intertemporal consumption’.

There are deeper reasons why the financial sector has little role in standard macro. In the majority of standard DSGE macro models, the system automatically tends towards some long-run supply side-determined full-employment equilibrium – in other words the models incorporate Milton Friedman’s long-run vertical Phillips Curve. Further, in most DSGE models, income distribution has no long-run effect on macroeconomic outcomes.

Post-Keynesian economics, which provides much of the underlying theoretical structure of SFC models, takes issue with these assumptions. Instead, it is argued, Keynes was correct in his assertion that demand deficiency can lead economies to become stuck in equilibria characterised by under-employment or stagnation.

Now, if the economic system is always in the process of returning to the flexible-price full-employment equilibrium, then financial stocks will be, at most, of transitory significance. They may serve to amplify macroeconomic fluctuations, as in the Bernanke-Gertler-Gilchrist models, but they will have no long-run effects. This is the reason that DSGE models which do attempt to incorporate financial leverage also require additional ‘ad-hoc’ adjustments to the deeper model assumptions – for example this model by Kumhof and Ranciere imposes an assumption of non-negative subsistence consumption for households. As a result, when income falls, households are unable to reduce consumption but instead run up debt. For similar reasons, if one tries to abandon the loanable funds theory in DSGE models – one of the key reasons for the insistence on accounting in SFC models – this likewise raises non-trivial issues, as shown in this paper by Benes and Kumhof  (to my knowledge the only attempt so far to produce such a model).

Non-PK-SFC models, such as the UK’s OBR model, can therefore incorporate modelling of sectoral balances and leverage ratios – but these stocks have little effect on the real outcomes of the model.

On the contrary, if long-run disequlibrium is considered a plausible outcome, financial stocks may persist and feedbacks from these stocks to the real economy will have non-trivial effects. In such a situation, attempts by individuals or sectors to achieve some stock-flow ratio can alter the long-run behaviour of the system. If a balance-sheet recession persists, it will have persistent effects on the real economy – such hysteresis effects are increasingly acknowledged in the profession.

This relates to an earlier point made in Simon’s post: ‘the fact that leverage was allowed to increase substantially before the crisis was not something that most macroeconomists were even aware of … it just wasn’t their field’. I’m surprised this is presented as evidence for the defence of mainstream macro.

The central point made by economists like Minsky and Godley was that financial dynamics should be part of our field. The fact that by 2007 it wasn’t, illustrates how badly mainstream macroeconomics went wrong. Between Real Business Cycle models, Rational Expectations, the Efficient Markets Hypothesis and CAPM, economists convinced themselves – and, more importantly, policy-makers – that the financial system was none of their business. The fact that economists forgot to look at leverage ratios wasn’t an absent-minded oversight. As Oliver Blanchard argues:

 ‘… mainstream macroeconomics had taken the financial system for granted. The typical macro treatment of finance was a set of arbitrage equations, under the assumption that we did not need to look at who was doing what on Wall Street. That turned out to be badly wrong.’

This is partially acknowledged by Simon when he argues that the ‘microfoundations revolution’ lies behind economists’ myopia on the financial system. Where I, of course, agree with Simon is that ‘had the microfoundations revolution been more tolerant of other methodologies … macroeconomics may well have done more to integrate the financial sector into their models before the crisis’. Putting aside the point that, for the most part, the microfoundations revolution didn’t actually lead to microfounded models, ‘integrating the financial sector’ into models is exactly what people like Godley, Lavoie and others were doing.

Simon also makes an important point in highlighting the lack of acknowledgement of antecedents by PK-SFC authors and, as a result, a lack of continuity between PK-SFC models and the earlier structural econometric models (SEMs) which were eventually killed off by the shift to microfounded models. There is a rich seam of work here – heterodox economists should both acknowledge this and draw on it in their own work. In many respects, I see the PK-SFC approach as a continuation of the SEM tradition – I was therefore pleased to read this paper in which Simon argues for a return to the use of SEMs alongside DSGE and VAR techniques.

To my mind, this is what is attempted in the Bank of England paper criticised by Simon – the authors develop a non-DSGE, econometrically estimated, structural model of the UK economy in which the financial system is taken seriously. Simon is right, however, that the theoretical justifications for the behavioural specifications and the connections to previous literature could have been spelled out more clearly.

The new Bank of England model is one of a relatively small group of empirically-oriented SFC models. Others include the Levy Institute model of the US, originally developed by Wynne Godley and now maintained by Gennaro Zezza, the UNCTAD Global Policy model, developed in collaboration with Godley’s old colleague Francis Cripps, and the Gudgin and Coutts model of the UK economy (the last of these is not yet fully stock-flow consistent but shares much of its theoretical structure with the other models).

One important area for improvement in these models lies with their econometric specification. The models tend to have large numbers of parameters, making them difficult to estimate other than through individual OLS regressions of behavioural relationships. PK-SFC authors can certainly learn from the older SEM tradition in this area.

I find another point of agreement in Simon’s statement that ‘heterodox economists need to stop being heterodox’. I wouldn’t state this so strongly – I think heterodox economists need to become less heterodox. They should identify and more explicitly acknowledge those areas in which there is common ground with mainstream economics.  In those areas where disagreement persists, they should try to explain more clearly why this is the case. Hopefully this will lead to more fruitful engagement in the future, rather than the negativity which has characterised some recent exchanges.

[1] Simon goes on to argue that stock-flow consistency is not ‘unique to Godley. When I was a young economist at the Treasury in the 1970s, their UK model was ‘stock-flow consistent’, and forecasts routinely looked at sector balances.’  During the 1970s, there was sustained debate between the Treasury and Godley’s Cambridge team, who were, aside from Milton Friedman’s monetarism, the most prominent critics of the Keynesian conventional wisdom of the time – there is an excellent history here. I don’t know the details but I wonder if the awareness of sectoral balances at the Treasury was partly due to Godley’s influence?

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Happy Christmas from the Office of Budget Responsibility

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The sectoral balances approach to economic forecasting has come under scrutiny recently. It is certainly the case that when used carelessly, projections based on accounting identities have the potential to be either meaningless or misleading. This will be the case if accounting identities are mistakenly taken to imply causal relationships, if projections are presented without a clear statement of the assumptions about what drives the system or if changes taking place in ‘invisible’ variables such as the rate of growth of GDP are not identified (balances are usually presented as percentages of GDP).

Used with care, however (or luck, depending on your perspective), the approach is not without its merits – as I have argued previously. If nothing else, the impossibility of escaping from the fact that in a closed system lending must equal borrowing imposes logical restrictions on the projections that can be made about the future paths of borrowing in a ‘closed’ macroeconomic system.

Which brings us to the Chancellor’s Autumn Statement and the OBR’s rather helpful projections. As Duncan Weldon notes, the OBR are likely to receive a rather warmly written card from the Chancellor’s office this Christmas. While true that the OBR have, in the past, been less than helpful to the Chancellor, one can’t help but wonder about the justification for announcing the OBR projections at the same time as the Chancellors’ statements. Why are the OBR projections not made known to the public at the same time that they are made available to the Chancellor?

But back to sectoral balances. The model used by the OBR produces projections which comply with sectoral balance accounting identities. Four are used: those of the public sector, the household sector, the corporate sector and the rest of the world. The most closely watched is of course the public sector balance. The headline result of the OBR forecasts is that the public sector will run a surplus by 2019. What has so far received less attention (at least since Frances Coppola examined the projections from the March 2015 OBR forecasts) is the implication of this for the other three balances. The most recent OBR projections are shown below.

Fig-1-November-2015

Since the government is projected to run a small surplus from mid-2019, the other three sectors must collectively run a deficit of equal size. The OBR projects that the current account deficit will fall from its current level of around five per cent of GDP to around two per cent of GDP. The UK private sector must be in deficit. Interesting details lie in both the distribution of this deficit between the household and corporate sectors, and in the changes in figures since the last OBR reports in March and July.

In order to show how the numbers have changed since the previous forecasts, I have collected the data series from all three releases into individual charts.

The OBR series from these three releases for the public sector financial balance are shown below. Other than postponing the date at which the government achieves a surplus (and some revisions to the historical data) there is little difference between the three releases.

Fig-2-Public

Changes to the projections for the current account deficit are more significant. The latest projections include improvements in the projected deficit of between 0.5% and 1% of GDP, compared with the July predictions. With the current account deficit at record levels in excess of 5% of GDP, I think it is fair to say the projections look optimistic. I note that in each of the three OBR series, the deficit starts to close in the first projected quarter. Put another way, the inflection point has been postponed three times out of three.

Fig-3-ROW

Things start to get interesting when we turn to the corporate sector. Here the projections have changed rather more significantly. Whereas the previous two data series showed the corporate sector reversing its decade-long surplus in 2014 and finally returning to where many think the corporate sector should be – borrowing to invest – the new series contains significant revisions to the historical data. As it turns out, the corporate sector has remained in surplus, lending one per cent of GDP in Q2 2015. The corporate sector is not now projected to return to deficit until Q3 2018.

Fig-4-Corporate

Since the net financial balance for any sector is the difference between ex post saving – profits in the case of the corporate sector – and investment, these revisions imply either falling corporate investment, rising profits, or both.

The data series for corporate investment are shown below. The historical data have been revised down significantly. Investment in Q2 2015 is 1% of GDP lower than previously recorded. (This is hard to square with Osborne’s statement that ‘business investment has grown more than twice as fast as consumption’.) The reduction compared to previous forecasts widens in the projection out to 2020. Nonetheless, it is hard to escape the conclusion that the projections are extremely optimistic. By 2020, business investment is expected to reach twelve per cent of GDP, higher than any year back to 1980.

Fig-5.Investment

What of business profits? These are shown in the table below, taken from the OBR report. It seems that corporate profit grew at 10% year-on-year in 2014-15, despite GDP growth of around 2.5%. While projected growth rates decline, corporate profit is expected to grow at over 4% annually in every year of the projection out to 2021 (in a context of steady 2.5% GDP growth). There is not much sign of Goodhart–Nangle in these projections.

Fig-6-Profits

So, to recap: by 2020 we have government running a surplus just under 1% of GDP, a current account deficit of 2% of GDP and a corporate sector deficit around 1% of GDP. Those with a facility for mental arithmetic will have already arrived at the punchline – the household sector will be running a deficit of around 2% of GDP. In fact, given data revisions, the household sector appears to be already running a deficit close to 2% of GDP – a deficit which is projected to remain until 2021 (see figure below).

Fig-7-HHAs a comparison, note that in the period preceding the 2008 crisis, the household sector ran a deficit of not much over 1% of GDP, and for a shorter period than currently projected.

The OBR has this to say on its projections:

Recent data revisions have increased the size of the household deficit in 2014 and we expect little change in the household net position over the forecast period, with gradual increases in household saving offset by ongoing growth of household investment. Available historical data suggest that this persistent and relatively large household deficit would be unprecedented. This may be consistent with the unprecedented scale of the ongoing fiscal consolidation and market expectations for monetary policy to remain extremely accommodative over the next five years, but it also illustrates how the adjustment to fiscal consolidation assumed in our central forecast is subject to considerable uncertainty.  (p. 81)

Perhaps there is something to the sectoral balances approach approach after all. One can only wonder what Godley would make of all this.

Jo Michell

Models, maths and macro: A defence of Godley

To put it bluntly, the discipline of economics has yet to get over its childish passion for mathematics and for purely theoretical and often highly ideological speculation, at the expense of historical research and collaboration with the other social sciences.

The quote is, of course, from Piketty’s Capital in the 21st Century. Judging by Noah Smith’s recent blog entry, there is still progress to be made.

Smith observes that the performance of DSGE models is dependably poor in predicting future macroeconomic outcomes—precisely the task for which they are widely deployed. Critics of DSGE are however dismissed because—in a nutshell—there’s nothing better out there.

This argument is deficient in two respects. First, there is a self-evident flaw in a belief that, despite overwhelming and damning evidence that a particular tool is faulty—and dangerously so—that tool should not be abandoned because there is no obvious replacement.

The second deficiency relates to the claim that there is no alternative way to approach macroeconomics:

When I ask angry “heterodox” people “what better alternative models are there?”, they usually either mention some models but fail to provide links and then quickly change the subject, or they link me to reports that are basically just chartblogging.

Although Smith is too polite to accuse me directly, this refers to a Twitter exchange
from a few days earlier. This was triggered when I took offence at a previous post
of his in which he argues that the triumph of New Keynesian sticky-price models over their Real Business Cycle predecessors was proof that “if you just keep pounding away with theory and evidence, even the toughest orthodoxy in a mean, confrontational field like macroeconomics will eventually have to give you some respect”.

When I put it to him that, rather then supporting his point, the failure of the New Keynesian model to be displaced—despite sustained and substantiated criticism—rather undermined it, he responded—predictably—by asking what should replace it.

The short answer is that there is no single model that will adequately tell you all you need to know about a macroeconomic system. A longer answer requires a discussion of methodology and the way that we, as economists, think about the economy. To diehard supporters of the ailing DSGE tradition, “a model” means a collection of dynamic simultaneous equations constructed on the basis of a narrow set of assumptions around what individual “agents” do—essentially some kind of optimisation problem. Heterodox economists argue for a much broader approach to understanding the economic system in which mathematical models are just one tool to aid us in thinking about economic processes.

What all this means is that it is very difficult to have a discussion with people for whom the only way to view the economy is through the lens of mathematical models—and a particularly narrowly defined class of mathematical models—because those individuals can only engage with an argument by demanding to be shown a sheet of equations.

In repsonse to such a demand, I conceded ground by noting that the sectoral balances approach, most closely associated with the work of Wynne Godley, was one example of mathematical formalism in heterodox economics. I highlighted Godley’s famous 1999 paper
in which, on the basis of simulations from a formal macro model, he produces a remarkably prescient prediction of the 2008 financial crisis:

…Moreover, if, per impossibile, the growth in net lending and the growth in money supply growth were to continue for another eight years, the implied indebtedness of the private sector would then be so extremely large that a sensational day of reckoning could then be at hand.

This prediction was based on simulations of the private sector debt-to-income ratio in a system of equations constructed around the well-known identity that the financial balances of the private, public and foreign sector must sum to zero. Godley’s assertion was that, at some point, the growth of private sector debt relative to income must come to an end, triggering a deflationary deleveraging cycle—and so it turned out.

Despite these predictions being generated on the basis of a fully-specified mathematical model, they are dismissed by Smith as “chartblogging” (see the quote above). If “chartblogging” refers to constructing an argument by highlighting trends in graphical representations of macroeconomic data, this seems an entirely admissible approach to macroeconomic analysis. Academics and policy-makers in the 2000s could certainly have done worse than to examine a chart of the household debt-to-income ratio. This would undoubtedly have proved more instructive than adding another mathematical trill to one of the polynomials of their beloved DSGE models—models, it must be emphasised, once again, in which money, banks and debt are, at best, an afterthought.

But the “chartblogging” slur is not even half-way accurate. The macroeconomic model used by Godley grew out of research at the Cambridge Economic Policy Group in the 1970s when Godley and his colleagues Francis Cripps and Nicholas Kaldor were advisors to the Treasury. It is essentially an old-style macroeconometric model combined with financial and monetary stock-flow accounting. The stock-flow modelling methodology has subsequently developed in a number of directions and detailed expositions are to be found in a wide range of publications including the well-known textbook by Lavoie and Godley—a book which surely contains enough equations to satisfy even Smith. Other well-known macroeconometric models include the model used by the UK Office of Budget Responsibility, the Fair model in the US, and MOSES in Scandinavia, alongside similar models in Norway and Denmark. Closer in spirit to DSGE are the NIESR model and the IMF quarterly forecasting model. On the other hand, there is the CVAR method of Johansen and Juselius and similar approaches of Pesaran et al. These are only a selection of examples—and there is an equally wide range of more theoretically oriented work.

This demonstrates the total ignorance of the mainstream of the range and vibrancy of theoretical and empirical research and debate taking place outside the realm of microfounded general equilibrium modelling. The increasing defensiveness exhibited by neoclassical economists when faced with criticism suggests, moreover, an uncomfortable awareness that all is not well with the orthodoxy. Instead of acknowleding the existence of a formal literature outside the myopia of mainstream academia, the reaction is to try and shut down discussion with inaccurate blanket dismissals.

I conclude by noting that Smith isn’t Godley’s highest-profile detractor. A few years after he died—Godley, that is—Krugman wrote an unsympathetic review of his approach to economics, deriding him—oddly for someone as wedded to the IS-LM system as Krugman—for his “hydraulic Keynesianism”. In Krugman’s view, Godley’s method has been superseded by superior microfounded optimising-agent models:

So why did hydraulic macro get driven out? Partly because economists like to think of agents as maximizers—it’s at the core of what we’re supposed to know—so that other things equal, an analysis in terms of rational behavior always trumps rules of thumb. But there were also some notable predictive failures of hydraulic macro, failures that it seemed could have been avoided by thinking more in maximizing terms.

Predictive failures? Of all the accusations that could be levelled against Godley, that one takes some chutzpah.

Jo Michell