Module: BU40024 Dissertation (Economics and International Business, University of Dundee)
Word Count: 6800 (Main body, Chapter 1-5, excluding figures and tables.)
Wayne Scott

Abstract
Shaikh (et al,1999) (2016) proposes a Classical-Marxian theory of inflation. In contrast to Neo-Classical and Keynesian perspectives, Shaikh sees the limit to growth not in full employment, but in corporate profitability. It also states that money is endogenous to capitalism. From this a demand-pull, supply-resistance model is developed in which inflation is driven by new credit relative to GDP, and the rate of growth utilisation. Handfas (2012) has shown the long run validity of the theory in 10 countries including Britain from 1950-2010. This thesis aims to build upon these previous works showing the long-run validity of the model in the British context, including the period following the Great Recession of 2007-2009. To carry this out, ARDL-ECM modelling was used to test the theory for the years 1966-2022. The obtained results show a significant long-run relationship between the growth utilisation rate and inflation, whilst no significant relationship was found for relative new purchasing power. These results challenge the mainstream theories that recent inflation is driven by excessive growth of the money supply, or by a wage-price spiral, and can prove useful for trade-unionists engaged in negotiations for wage rises that meet the cost of living.
Acknowledgements
I would like to extend my gratitude to my dissertation advisor, Carlo Morelli, for the encouragement and advice he has offered throughout the process of writing this thesis. I would also like to thank Oktay Özden for the invaluable advice he has given me on econometric modelling. My appreciation also extends to Tu Senan, from the International Secretariat of the Committee for a Workers’ International, for our ongoing discussions on the causes on inflation in terms of Marxist theory. Finally, I would like to thank Bruce Wallace for allowing me to engage in his course on Marxist political economy in 2012, and the many informal discussions in Wetherspoons over fish and chips, without which, I wouldn’t have applied to study economics.
| Table of contents | |
| 1 Introduction | 6 |
| 2 Literature review | 9 |
| 2.1 Endogenous money | 9 |
| 2.2 Phillips Curve | 10 |
| 2.3 NAIRU | 11 |
| 2.4 Full employment: The limit to growth? | 12 |
| 2.5 Supply resistance | 12 |
| 2.6 Demand pull | 14 |
| 2.7 Inflation and Interest Rates | 15 |
| 3 Methodology | 16 |
| 3.1.1 Model 1 | 18 |
| 3.1.2 The datasets | 18 |
| 3.1.3 OLS regression | 19 |
| 3.1.4 Descriptive statistics | 20 |
| 3.2.1 Model 2 | 21 |
| 3.2.2 The datasets | 21 |
| 3.2.3 OLS regression | 22 |
| 3.1.4 Descriptive statistics | 23 |
| 3.3.1 Model 3 | 24 |
| 3.3.2 The Datasets | 25 |
| 3.3.3 Descriptive Statistics | 25 |
| 3.3.4 Testing the Model | 25 |
| 3.3.5 Stationarity Testing | 26 |
| 3.3.6 Optimal Lag Length | 27 |
| 3.3.7 Long Run and Short Run Analysis | 27 |
| 3.3.8 Inclusion of Dummy Variables | 28 |
| 3.3.9 Testing for Serial correlation | 28 |
| 3.3.10 Testing for heteroscedasticity | 29 |
| 3.3.11 Testing for Normality | 29 |
| 3.3.12 Stability | 29 |
| 4 Results | 30 |
| 4.1.1 Model 1 | 30 |
| 4.1.2 Stationarity | 30 |
| 4.1.3 OLS output | 31 |
| 4.2.1 Model 2 | 32 |
| 4.2.2 Stationarity | 32 |
| 4.2.3 OLS output | 33 |
| 4.3.1 Model 3 | 34 |
| 4.3.2 Stationarity | 34 |
| 4.3.3 Optimal Lag Length | 35 |
| 4.3.4 Short run analysis | 35 |
| 4.3.5 F-Bounds Test | 36 |
| 4.3.6 Long Run analysis | 36 |
| 4.3.7 Heteroscedasticity | 38 |
| 4.3.8 Serial Correlation | 38 |
| 4.3.9 Normality and Stability | 38 |
| 5 Discussion | 40 |
| 5.1 Limitations and Suggestions for Further Study | 42 |
| 5.2 Conclusion | 43 |
| 6. Bibliography | 44 |
| List of Figures | |
| Figure 1 | Estimates for contributions to annual “GDP inflation” 2022, quarter 4 (Choonara, 2023) |
| Figure 2 | The Price-Inflation-Phillips-Curve. (Froyen, 2014, p.215) |
| Figure 3 | The Long-Run Phillips Curve. (Froyen, 2014, p. 217) |
| Figure 4 | Nominal GDP growth (GGDP) and Relative New Purchasing Power (e ), 1966-2022 |
| Figure 5 | Real GDP growth (RGDP) and The Net Incremental Rate of Profit (rr’), 1966-2022. |
| Figure 6 | Implicit GDP deflator (π), Relative New Purchasing Power (e ) and the Growth Utilisation Rate(σ). |
| Figure 7 | Akaike Information Criteria for Model 3 (Top 20 Models) |
| Figure 8 | Actual-Fitted-Residual graph |
| Figure 9 | Jarque-Bera Test |
| Figure 10 | CUSUM Test |
| Figure 11 | CUSUMSQ test |
| Figure 12 | The Net Incremental Rate of Profit (rr’), 1966-2022 |
| Figure 13 | Normalised growth utilisation and inflation rates, USA & United Kingdom (Standardised scaling) (Shaikh, 2016 (USA), Authors calculations (UK)) |
| Figure 14 | Unutilised growth capacity and inflation rates, United Kingdom, 1966-2022 |
| List of Tables | |
| Table 1 | The Datasets and their Sources |
| Table 2 | Descriptive statistics for Model 1 |
| Table 3 | Descriptive statistics for Model 2 |
| Table 4 | Descriptive statistics for Model 3 |
| Table 5 | Dummy Variables in the Model. |
| Table 6 | Stationarity tests for Model 1. Augmented Dickey-Fuller and Phillips-Peron |
| Table 7 | Ordinary Least Squares output for Model 1 |
| Table 8 | Stationarity tests for Model 2. Augmented Dickey-Fuller and Phillips-Peron |
| Table 9 | Ordinary Least Squares output for Model 2 |
| Table 10 | Stationarity tests for Model 3, Augmented Dickey Fuller and Phillips-Peron. |
| Table 11 | Short-Run Error Correction Model |
| Table 12 | F-Bounds Test |
| Table 13 | Cointegrating Equation and Long-Run Coefficients |
| Table 14 | Breusch-Pagan-Godfrey Test |
| Table 15 | Breusch-Godfrey Test |
1. Introduction
Mainstream theories have been unable to adequately explain increasing inflation internationally following the Covid-19 pandemic (Roberts, 2023). Echoing post-Keynesian theory, Andrew Bailey, Governor of the Bank of England argued that workers should show restraint in pay negotiations in order to prevent a wage-price spiral (Burden, 2022). However, data for Britain shows that in 2022, the largest contributing factor to price rises was not wage growth, but unit capital costs as shown in Figure 1. Monetarist theory argues that inflation is a purely monetary phenomenon (De Grauwe and Polan, 2005). This means that inflation is caused by excessive money supply growth without a corresponding rise in production (ibid). However increasing money supply has not been shown to have a significant impact on inflation rates in Britain in the long run (Handfas, 2012).

Figure 1. Estimates for contributions to annual “GDP inflation” 2022, quarter 4 (Choonara, 2023)
Shaikh (et al, 1999) (2016. ch.15) develops a Classical-Marxian1 demand-pull/supply-resistance theory of inflation which stands in opposition to the mainstream theories. The demand side variable in this theory is the growth of new purchasing power relative to GDP (e). It is argued that new credit is made available because companies demand it in order to expand production. Therefore, nominal GDP growth is a function of relative new purchasing power. A portion of this newly available credit will not be absorbed fully by supply contributing positively to inflationary pressures. Whilst this is consistent with the monetarist accounts, it starts from an alternative theoretical foundation of endogenous money. The role of new credit in the this theory tends to have a more significant impact on inflation in the presence of hyperinflation, or when inflation reaches a “critical level”.
Whilst for both the Post-Keynesian and monetarist schools, full employment is the limit to growth (ibid), the Classical-Marxian theory argues that the limit to growth is the corporate incremental net rate of profit (rr’), and that real output growth responds positively to profitability. This theoretical growth limit is reached when entirety of the corporate net operating surplus is reinvested back into production (when I/P=100%). As the real rate of growth begins to reach its limit, this produces a bottleneck situation in which supply becomes tighter and prices begin to rise. This represents the process of supply resistance in the Classical-Marxian model. Shaikh (et al,1999) originally termed this supply-side variable the “throughput limit”, and later the “Growth Utilisation Rate”, represented byσ (2016, Ch.15).
Therefore, in the Classical-Marxian model inflation is a function of the growth utilisation rate, the net rate of profit and relative new purchasing power. The model can be summarised as follows (Shaikh, 2016, pp.698-703);
Nominal output growth as a function of RNPP
Gy= F(e )
+
Real output growth as a function of RNPP, profitability, and growth utilisation
Gyr= F(e, rr’, σ)
+, +, –
Inflation is the difference between nominal and real GDP growth
π= Gy-Gyr
Inflation as a function of RNPP, profitability and Growth utilisation.
π= F(e, rr’, σ)
+, -, +
σ can alternatively be expressed as 1-σ to represent unutilised growth capacity, similar to the role of unemployment in the Phillips Curve
π= F(e, rr’, 1-σ)
+, -, –
Simplified form
π= F(e, σ)
+, +/-
Shaikh’s theory has shown empirical validity in a number of countries. Handfas (2012) utilises econometric analysis showing a statistically significant long run relationship in 10 countries, including Britain, and six other OECD countries. Özden and Bolkol (2023) found similar results for 23 European Countries between 2001-2020. However, the impact of relative new purchasing power was not found to be significant.
This dissertation utilises the Autoregressive Distributive Lag – Error Correction Model (ARDL-ECM) to test for the presence of a long run relationship between inflation and the hypothesis set out in the Classical-Marxian model. The obtained results show that the model is a good fit with actual inflation rates.
2.Literature Review
This literature review addresses debates about the nature of money. This is followed by an outline of key theories of both the Monetarist and post-Keynesian schools regarding inflation, before outlining the Classical-Marxian theory and its supporting literature. At each stage, the theories are applied to real developments in the British economy over the selected period.
2.1. Endogenous money
In the Ricardo-Hume quantity theory, the national price level derives from the level of money in a national economy (Humphrey, 1974). This premise laid the theoretical basis for Friedman’s notion that inflation is always a monetary phenomenon (De Grauwe and Polan, 2005). The quantity theory was rejected by Marx (1990), as well as others such as Tooke and Newmarch (1928). In opposition to Ricardo, it is argued that price level determines the quantity of money (Somerville, 1933, pp.334-335). Therefore, we can see the differences in the approach expressed as thus:
QTM: MV=PY (1)
Marx: PY=MV (2)
Where MV=Money supply*Velocity of circulation, and PY=Price Level*Output (Roberts, 2020). Whilst Marxists accept the basic relationship expressed in equation 1, the causal direction is inverted. The values of commodities are not determined by the quantity of money in circulation but by the labour content required to produce them. This forms the basis for prices of production (ibid). Therefore, changes in the money supply won’t succeed in determining inflation rates (ibid). Shaikh (2016, p.191) points out that new credit, which is technically limitless based on fiat currency, is made available following the demand for it from capitalists to meet the needs of expanding production. Money, therefore, is endogenous in the classical and Marxian frameworks, an assumption also shared by the post-Keynesian school (ibid) (Nayan et al., 2013)
2.2. Phillips curve
One way to analyse the relationship between inflation and unemployment during the post-war era was the Phillips curve. Whilst the original Phillips curve suggested an inverse relationship between wage-price growth and unemployment (Phillips, 1958), this was later adapted to a model to explain general inflation. Since reducing unemployment increased the bargaining power of workers, these increased wages would find their way into prices (Samuelson and Solow, 1960). This idea seemed to hold true in the years following the WW2. However, the 1970s marked a turning point when economies experienced a phenomenon known as “stagflation,” characterised by simultaneous increases in both inflation and unemployment alongside a decline in output, exposing the limitations of the Phillips curve model (Shaikh, p.703). This notion is also closely tied to the wage-price spiral theory (Blanchard, 1986). Research from the IMF suggests that there is little evidence to support that rising wages are a leading cause of inflation, and notes that in many advanced countries such as Britain, real wage growth has been stagnant (Alvarez et al., 2022).
Marx opposed the argument of modern Keynesians that increased wages lead to price inflation – the argument implicit in the Phillips Curve (Roberts, 2023). Arguing against those who warned workers not to fight for pay rises as these would be cancelled out by price rises, Marx (1996) took the view that since the value and hence the price of a commodity is regulated by the labour content required to produce them, increased wages do not mean increased prices, but declining rates of profit. Whilst the increased demand for consumer goods may increase prices in that sector, the declining profit rate will lead to reduced demand for luxury goods by the rich, and thus falling prices in that regard. The increasing demand for necessities leads to workers and fixed capital transferring from the luxury goods sector for supply to catch up with the increased demand, meaning prices returning to their original level (ibid). Marx argues that prices tend to rise, and wages slowly catch up as workers struggle for higher pay(ibid), the IMF study into the wage-price spiral confirms that this is the scenario that has played out in countries like Britain (Alvarez et al., 2022).

Figure 2. The Price-Inflation-Phillips-Curve. (Froyen, 2014, p.215)
2.3. NAIRU
The non-accelerating inflationary rate of unemployment (NAIRU) hypothesis (Espinosa-Vega and Russell, 1997) argues that trade-offs between inflation and unemployment are temporary. As workers begin to demand higher pay, firms will engage in cost cutting measures meaning unemployment will return to its natural rate. Keynesian stimulus therefore will result in inflationary surges (ibid). In the long run therefore, the Phillips curve adheres to a vertical trajectory. The NAIRU theory contends that the natural rate of unemployment is shaped by the state and constraints on competition, meaning that much of the unemployment in the 1970s was voluntary, as people opted to live on welfare instead (Shaikh, 2016, p.661)For Shaikh (2016, p.592) and Marx (1990, pp.781-793), there is also a persistent rate of unemployment that exists, however, this is an involuntary reserve army of labour to be pushed from and pulled into production according to the whims of capital. This analysis also extends to the under-employed (Magdoff, 2004).
Proponents of NAIRU have had to deal with developments in the latter half of the 2010s where unemployment was low in Britain, but this was not translating into wage or price inflation. This was attributed to a decreasing NAIRU because of underemployment (Bell and Blanchflower, 2018). Interest rates come to play a key role in controlling inflation in the NAIRU framework. If interest rates rise, this could increase unemployment and thus decrease inflation (Ball and Mankiw, 2002). This reflects the strategic approach taken by the Bank of England to increase interest rates in 2022 to “wring out” inflation (Pill, 2023).

Figure 3. The Long Run Phillips Curve. (Froyen, 2014, p. 217)
2.4. Full Employment: The limit to growth?
In the neoclassical approach, expansion of the money supply can only lead to rising prices as growth is restrained at the level of full employment (Ball and Mankiw, 2002). The Post-Keynesian school also argues that full employment is the limit to growth (Shaikh, 2016, p.660). Shaikh (2016, p.695) rejects this, as when faced with labour shortages, migrant labour can be used to expand production and services further. This basic fact is illustrated in the National Health Service, Britain’s largest employer, which could not function without skilled and unskilled immigrant workers (Baker, 2022). The migration of workers from former colonies to Britain in the post-war era played an instrumental role in fuelling the boom years, in the face of labour shortages brought by the death and destruction of the war (Thompson, 2014).
2.5 Supply resistance
Shaikh (2016, p.468) therefore, argues that the limit to growth is not full employment of labour, but the net incremental rate of profit (Corporate Rate of profit – interest rate). This theoretical growth limit is reached when all surplus is reinvested back into production. The ratio of investment/profit is the growth utilisation rate (Shaikh, p.896). This is similar to the capacity utilisation rate utilised by Dumenil and Levy (1999) in their theory of inflation. This premise is derived from Marx’s schema of expanded reproduction, as well as Ricardo’s corn-corn model (Shaikh, 1973). Net profitability itself has shown a close correlation with real GDP growth in the USA in Shaikh’s work, whilst growth utilisation tracks inflation rates closely (Figure 13). The Marxian labour theory of value is central to the thesis. In the Marxian framework, the operating surplus of corporations derives from the exploitation of labour-power (Marx, 1990, 283-306). The capitalist-class can only invest back into production the surplus wealth produced by the working-class. Therefore, growth is limited by the amount of surplus-value in the economy. This notion of the available surplus value creating a limit to growth is summarised by Trotsky (1972);
“…only the values that have been created by human labour are at the disposal of society… where labour has created no new value, there even Rockefeller can get nothing.”
This approach has demonstrated its usefulness in explaining the phenomenon of stagflation in the 1970s. Shaikh demonstrates that in the USA, the profit rate fell faster than the growth utilisation rate, resulting in supply tightness and thus inflation (Shaikh, 2016, p.703). This led to a scenario where you had rising prices at the same time as rising unemployment, a phenomenon that couldn’t be explained by the post-Keynesian Phillips curve, or the neoclassical school which also saw inflation as a full-employment phenomenon (ibid). Handfas (2012) applies the Classical model to ten countries, including Britain. The results for Britain show a similar situation in the 1970s as that of the USA, of increased growth tightness combined with falling profit rates, fuelling both inflation and unemployment.
The overall trend in fixed capital investment in Britain changed considerably during the 1990s, which was largely tied to the neoliberal restructuring of the economy, particularly in the oil industry (Woolfson, Foster and Beck, 2013, pp.526-543). Facing falling profitability and rising prices, British oil producers competitively outsourced services such as IT, restoring profits. It was necessary to lower the value of fixed capital investment in this period as a direct attack on labour would not have been tolerated given the recent Piper Alpha disaster and the strikes for safety which followed (ibid). This period was also marked by intense de-industrialisation (Tomlinson, 2021). Fixed capital investment has generally remained quite low since this period, with a shift towards services in Britain rather than manufacturing (ibid). Services generally are resistant to improvements in labour productivity compared to manufacturing (Leys, 1995).
Whilst the Classical Marxian theory asserts that a falling profit rate increases inflationary pressures, an increase in corporate profits has been highlighted by trade unions such as Unite (2022) since the pandemic, to aid the argument that pay must increase to tackle the cost-of-living crisis. However, the price-level is path-dependent based on fiat currency (Shaikh, 2016, p.695), meaning that inflation is influenced by profitability in previous years also. As the Unite (2022) study shows, profitability was lower prior to the pandemic than it is currently which could have a lagged effect on inflation. This increase in profits gives credence to the argument that the current situation is one of profit-fuelled inflation, commonly called greedflation, and often a profit-price spiral (Choonara, 2023) (Roberts, 2023). However, it’s worth considering if it is high profits driving up inflation in the first instance, or inflation driving up profits. Marx (2010, p.16-18) explained in a letter to Engels that a period of inflation effectively lowers the price of labour whilst increasing the amount of surplus-value accrued by employers. This increases the rate of exploitation of workers, and thus profitability, unless wages rise at the same rate as prices (ibid).
2.6. Demand-pull
Handfas (2012) introduced a major change to Shaikh’s (et al,1999) original theory, which presented inflation as a supply-side phenomenon regulated by the growth tightness in an economy. Handfas recognised the role played by demand-side factors, the growth of new credit relative to GDP. In other words, excess demand. This appears similar to the monetarist argument that inflation is a monetary phenomenon. However, Shaikh (2016, p.719) argues that the growth of new credit tends to fuel inflation in scenarios where the inflation rate has risen above 20%. In situations in which we have lower inflation, the growth utilisation rate will play a larger role in determining inflation.
Whilst Marx wrote at a time when money was backed by gold and other precious metals which had a limit to its supply, the switch to fiat currency in the 20th century means that in theory, the money supply is limitless (Shaikh, 2016, p.191). Therefore, episodes of hyperinflation can be accounted for in the classical which has demonstrated a strong relationship between RNPP growth and inflation for countries such as Argentina, which experienced rates of inflation of up to 3000% (Shaikh, 2016, pp.719-721). This cannot be accounted for by reference to increased production, therefore, including excess demand into the model represented a step forward for the theory. This approach has been used by Barredo-Zuriarrain (2022) to argue that the hyperinflation rates in Venezuela can be explained by excessive government credit to subsidise the oil industry.
Özden and Bolkol (2023) applied the theory to 23 European countries, including Britain, and found a statistically significant relationship between inflation and the classical model. However, the regressions for each country are not shown, making it harder to draw conclusions about Britain. The classical model was shown to hold across the countries examined. However, the effects of changes in RNPP were not shown to play a significant role in determining inflation rates at the European level. This result can be expected given the low rate of inflation that has prevailed across Europe since the 1990s (Abdih, Lin and Paret, 2018).
3.7 Inflation and Interest Rates
The logic of the Classical-Marxian model outlined thus far would suggest that the 2022 increase in interest rates by the Bank of England (Pill, 2023) would be counter-productive to fighting inflation, as this lowers the net incremental rate of profit increasing supply tightness. However, if the growth utilisation rate, as a result of increased borrowing costs, falls at a faster pace than profitability, this can alleviate inflationary pressures. This can also reflect a longer-term goal of purging the system of unprofitable capitals. The rise of unprofitable “zombie-firms” in Britain, which exist only to service their debt, has long been noted in the literature (Adam Smith institute, 2013). The increase in interest rates has already led to insolvencies in England and Wales, reaching the highest level since the 2009 crisis (Financial Times, 2024). Marx highlighted that this process of companies going bust leads to their capital stock being acquired below its value by more profitable rivals (Marx, 1991, pp.339-349). Thus, raising the general rate of profit. The Classical-Marxian theory suggests that this would increase growth potential, stabilising inflation rates for a period. However, this can come at a costly price of triggering a recession and a sharp drop in demand (Choonara, 2023).
3.Methodology
To examine the validity of the Classical-Marxian model in the British context, it is necessary to test several assumptions underlying the theory before testing for the long run and short run coefficients of the main hypothesis.
As outlined in this section, a combination of regression models are used. Models 1-2 represent the assumptions of the theory, using the Ordinary Least Squares regression method to test for statistically significant positive relationships as hypothesised.
Given that the main (restricted) hypothesis of the Classical-Marxian model includes 3 variables in total, it is possible that we will see a range of orders of integration across the variables. Therefore, the ARDL-ECM model is utilised to account for possible mixed order of integration in Model 3. A summary of all datasets used to derive the variables, and their sources can be found in Table 1. Eviews 10 was used to carry out all regression models.
Table 1. The Datasets and their Sources

3.1.1 Model 1.
The first assumption of the Classical-Marxian model is that nominal output growth is a function of relative new purchasing power.
Gy=f(e)
This is due to the fact that the availability of new credit tends to fuel investment as it is issued following demands from private companies to meet the expanding need of production as outlined in the discussion on endogenous money in the literature review. Shaikh takes nominal GDP growth as a measure of nominal output growth. The variables are calculated as follows;
The dependent variables: Nominal GDP growth (GGDP)

The independent variables: Relative new purchasing power (e).

(Shaikh, 2016, pp.895-896)
3.1.2 The Datasets
Datasets for GDP and the current account were taken from the Office for National Statistics website. To proxy total credit, the Net Domestic Credit series from the World Bank was used. This was used as it was the only long run credit series available. Whilst M2 money supply data may have been an acceptable alternative, this data is not readily available before 1986Q4, which would therefore, limit the scope of analysis if used. Since the Net Domestic Credit series only includes annual data, this also restricts us to using annual data across all datasets. Current account data was taken from the ONS website.
3.1.3 Ordinary Least Squares
Shaikh (2016, pp.705) demonstrated a positive and statistically significant relationship between GGDP and e for the United States between 1950-2010 using the Ordinary Least Squares method (OLS), with two lags on the independent variable, which is done for this test. Research which has applied the Classical-Marxian model to European countries found that e does not have a significant impact on inflation levels (Özden and Bolkol, 2023), therefore, it is possible that the results may show that this hypothesis does not hold for Britain.
The general form for the OLS regression is expressed as;

By substituting in our dependent and independent with two lagged independent variables, this becomes;

The Augmented Dickey-Fuller(ADF) and Phillips-Peron(PP) method were applied to test for stationarity at different levels prior to running the regression model, in order to avoid a spurious result. The variables must show the same order of integration against the constant and/or trend, otherwise alternatives must be explored
3.1.4 Descriptive Statistics
Table 2. Descriptive statistics for Model 1


Figure 4. Nominal GDP growth (GGDP) and Relative New Purchasing Power (e ), 1966-2022
3.2.1 Model 2
In the Classical-Marxian model, the growth of real output is a function of relative new purchasing power, the net incremental rate of profit and the growth utilisation rate;
Gyr= F(e, rr’, σ)
+, +, –
Shaikh shows that a strong positive relationship exists between real GDP growth(as measure of real output), and the net rate of profit alone for the USA. Therefore, a restricted formula is tested in which real GDP growth is taken as a measure of real output growth;
RGDP=f(rr’)
This is because investment follows profitability positively. As profitability increases, investment, and thus real GDP will grow. The variables can be represented as follows:

(Shaikh, 2016, pp.895-896)
3.2.2 The Datasets
The datasets for real GDP growth available from the World Bank were used. Whilst Shaikh uses net operating surplus to calculate rr’, the only readily available datasets for Britain shows gross operating surplus of corporations, available from the Office for National Statistics website. This data is used as as a proxy for net operating surplus. This has also been done in other applications of the Classical-Marxian model, including Özden and Bolkol (2023), who demonstrate that GOS and NOS correlate closely, meaning that changing the variable doesn’t significantly impact the model. The only long-run series representing corporate gross fixed capital formation is only available from 1997 onwards as previous data was removed due to accounting errors. Therefore, it is necessary to use a constructed dataset combining the most recent dataset with an archived one ending in 2016, prior to the amendment. Datasets for interest rates were taken from the Bank of England website. For the years 1966-2022, an annual interest rate was calculated based on 12-month averages.
3.2.3 OLS Regression
Shaikh does not use regression modelling to test this hypothesis for the USA, instead showing results visually using a boxplot. However, there is no reason that we cannot apply the same OLS regression method applied in Model 1 to this hypothesis. Since the OLS regression model is represented;

Ho: No statistically significant relationship between RGDP and rr’
H1: A statistically significant relationship between RGDP and rr’
The ADF and PP tests were again applied prior to running the regression model.
3.2.4 Descriptive Statistics
Table 3. Descriptive statistics for Model 2


Figure 5. Real GDP growth (RGDP) and The Net Incremental Rate of Profit (rr’), 1966-2022.
3.3.1 Model 3.The main hypothesis of the Classical-Marxian model is that inflation is determined by the demand pull of new purchasing power, and the supply resistance determined by net profitability and the growth utilisation rate;
π=f(e ,rr’,)
+, – , +
As Shaikh demonstrates, rr’ and correlate closely, meaning that the model can be further simplified to
π=f(e, )
+, +/-
The variables can be derived as follows:

(Shaikh, 2016, pp.895-896)
3.3.2 The Datasets
Datasets for e have already been derived to test the assumptions. Office for National Statistics datasets were used for both GFCF and GOS. As in the previous models, a constructed series was used for GFCF, and the Gross Operating Surplus of corporations series was used to proxy GOS. The implicit GDP deflator series is taken from the Office for National Statistics website. Other measures such as the Retail Prices Index or the Consumer Prices Index, which are more common measures in matters such as wage negotiation, may also be suitable datasets for inflation (Unite 2022). Unlike RPI, the GDP deflator doesn’t take into account inflation on imported goods (Office for National Statistics, 2023), including import price rises stemming from the Ukraine War and the pandemic (Caporale et al., 2022)
3.3.2 Descriptive Statistics

3.3.4 Testing the Model
To test the model, the ARDL-ECM cointegration approach first developed by Pesaran et al. (2001) is utilised. ARDL models are suitable for analysing the Classical-Marxian model as it can handle variables that are of mixed order of integration as long as they are stationary at I(0) or I(1). Since the ECM utilises first differences, variables will become stationary and thus cointegrated in the model (Asteriou and Hall, 2007, 310-311). The ARDL-ECM model is also suitable for the Classical-Marxian model, which is based on path-dependent prices (Shaikh, 2016, p.695), as it includes lagged values of both the dependent and independent variables (Asteriou and Hall, 2007, 310-311). This is the approach used by Handfas (2012) which showed significant long run relationships across 10 countries.
Since the dataset begins shortly before the inflationary spiral of the 1970s, a visual inspection of the inflation series shows a distinctive downward trend, as does the dataset for . This would indicate non-stationarity. The dataset for e appears to be trendless and hence stationary. This suggests a mixed order of integration making the ARDL-ECM the ideal approach

3.3.5 Stationarity Testing.
A number of tests are applied to test for stationarity. The Augmented-Dickey Fuller (ADF) test is a widely used test in econometric measuring. However, the ADF is not the strongest test for stationarity as noted by Handfas (2012). Therefore, the Phillips-Peron (PP) test is also applied, as it was in Models 1&2. If as anticipated the variables show a mixed order of integration of I(0) and I(1), then we can proceed to derive the ARDL-ECM model, as the variables become cointegrated in the ECM. If any variables reveal stationarity at I(2), we cannot proceed with the ARDL model.
3.3.6 Optimal Lag Length
To determine the optimal number of lags for both our dependent and independent variables, the Akaike Information Criterion is applied;


HO: No long-run relationship between variables
H1: A Long run relationship exists between variables
From this, we can then derive the ARDL model.

This can be further modified by including the ECM term to allow us to see how the model moves from the short-run to the long run. If the cointegrating error correction model yields a negative and significant result, this is evidence of movement from the short run to the long-run equilibrium.

3.3.8 Inclusion of Dummy Variables.
To account for the impact of policy shocks, a number of annual dummy variables are included. This was the approach adopted by Handfas (2012). Included are the same years as Handfas, with dummies added to the years 2020-2021 to account for the impact of the pandemic and the shocks to both supply and demand during this period.
Table 5. Dummy Variables in the Model.

3.3.9 Testing for Serial correlationIt is necessary to test for the presence of serial correlation in the model. To do this the The Breusch-Godfrey Test is applied. A p-value below the 5% significance level suggests the presence of serial correlation, meaning that the null hypothesis of no serial correlation cannot be rejected,
H0: No serial correlation at up to 2 lags
H1: Serial correlation at up to 2 lags
(Breusch, 1978) (Godfrey, 1978)
3.3.10 Testing for heteroscedasticityThe regression returns a Durbin-Watson value. A value close to 2, which is the ideal value, indicates little evidence of heteroscedasticity, and evidence for a constant variance of the residuals. The Breusch-Pagan-Godfrey Test is also applied to further test for heteroscedasticity in the results. A p-value below the 5% significance level suggests the presence of heteroscedasticity in the model, meaning that the null hypothesis of homoscedasticity cannot be rejected;
H0: Homoscedasticity
H1: Heteroscedasticity (Breusch and Pagan, 1980)
3.3.11 Testing for Normality
To determine if the residuals of the model output are normally distributed the Jarque-Bera (1980) test is applied. Residuals are normally distributed when they follow the classic bell-curve shape. A p-value below 5% indicates that the residuals do not follow normal distribution, meaning the null hypothesis of normal distribution cannot be rejected.
H0: The residuals are normally distributed.
H1: The residuals are not normally distributed.
3.3.12 Stability
To test for the presence of structural breaks, the CUSUM and CUSUMSQ tests developed by Brown et al. (1975) are applied. This tests both the long-run and short-run coefficients. If the coefficients stay within the 5% significance level, we can conclude that the residuals in the model are stable and do not deviate substantially from the mean.
4. Results
4.1.1 Model 14.1.2 Stationarity.The ADF and PP tests returned similar results. GGDP was shown to be not significant at the 5% level in both tests when only the constant term is included, whilst at levels, e shows significance at the 1% level. The GGDP series becomes significant at the 5% level in both tests when the constant and trend terms are included. Therefore, there is no need to take the first differences of the series
Table 6. Stationarity tests for Model 1. Augmented Dickey-Fuller and Phillips-Peron

4.1.3 OLS Regression Output
Table 7. Ordinary Least Squares output for Model 1.

Overall, the model seems to perform poorly. The coefficient for the independent variable e is not statistically significant at any level of lag (as indicated by the high p-values). The R2 value is reasonably high at 57%, however the Durban-Watson statistic is 1.00, far from the ideal value of 2, indicating the presence of heteroscedasticity in the model.
4.2.1 Model 24.2.2 StationarityAs in Model 1, the ADF and PP tests are applied to ensure the same order of integration of I(0) or I(1). As can be observed, both tests show stationarity at levels across all criteria. The trend term is restricted, including only the constant term in the regression model.
Table 8. Stationarity tests for Model 2, Augmented Dickey-Fuller and Phillips-Peron

4.2.3 OLS Regression Model
Table 9. Ordinary Least Squares output for Model 2.

The output suggests that there is a statistically significant relationship between the net incremental rate of profit and the real output growth rate, with a positive coefficient indicating that an increase in the net incremental rate of profit is associated with an increase in real output growth. The coefficient value is 0.979 suggesting the relationship is remarkably strong. The R2 value is 0.244, indicating that other factors also influence real GDP growth, as would be expected from testing a restricted formula.
4.3.1 Model 3
4.2.2 Stationarity
Table 10. Stationarity tests for Model 3, Augmented Dickey-Fuller and Phillips-Peron.

Both tests returned similar results. As anticipated, e is stationary at I(0) whilst π and σ show stationarity at I(1). Since we have a mixed order of integration, we can proceed to run the ARDL-ECM model as variables of mixed integration will become cointegrated in the ECM.
4.3.3 Optimal Lag Length

The results of the AIC test shows that the optimal number of lags for the models. The result is 1,0,3,0,0,0, with 1 lag applied to π, 3 lags applied toσ and no lags applied to e or any of the dummy datasets.
4.3.4 Short -Run analysis

Table 11 displays the short-term results from the error correction model. D(σ) with a p-value of 0.811, and D(σ-1) with a p-value of 0.537 are not statistically significant at the 5% level. D(σ(-2)) is statistically significant at the 1% level with a p-value of 0.003 and has a negative coefficient of -0.191. In the restricted formula tested,σ can have a positive or negative impact. Likewise, the cointegrating ECM term coefficient is negative at -0.35 and statistically significant at the 1% level, returning a p-value of 0.000 suggesting that the model shows convergence from the short run to the long run equilibrium, however the speed of adjustment is relatively slow. The observed-R2 results is 71.72% suggesting that the model is a relatively good fit.
4.3.5 F-Bounds Test
Table 12. F-Bounds Test

The obtained results from the F-bounds test show an f-statistic of 7.882. This value exceeds all the upper bounds across all significance levels and sample sizes. Therefore, we can conclude that there exists a long run relationship between the variables.
4.3.6 Long-Run Analysis
Table 13. Cointegrating Equation and Long-Run Coefficients

The long run results obtained from the ARDL model show that σ(-1) is positive, yet not significant at the 5% level. The coefficient for e is close to 0, with a p-value of 0.888, and is therefore not statistically significant at the 5% level, suggesting a weak relationship between inflation and relative new purchasing power in the UK. The Dummy series is statistically significant and negative, but more importantly, our Dummy*σ series is statistically significant and positive, showing a long-run relationship between π and σ when the impact of policy shocks are accounted for. The series Dummy*e continued to show insignificance when shocks are accounted for. Therefore, we cannot conclude that e has a statically significant effect on inflation in the long run, with σ being able to account for most of the changes in the model.

4.3.7 Heteroscedasticity

The results of the Breusch-Pagan-Godfrey Test show a P value of 0.3270, meaning our results are not significant at the 5% level. Therefore, the null hypothesis of homoskedasticity cannot be rejected. The lack of heteroscedasticity was also indicated by the Durbin-Watson statistic in our ARDL-ECM results as it was close to the ideal value of 2 at 2.013
4.3.8 Serial Correlation
The results of the Breusch-Godfrey LM Test returned a P value of 0.1945, meaning our results are not significant at the 5% level, suggesting little evidence of serial correlation up to 2 lags. Therefore, we cannot reject the null hypothesis of no serial correlation in the model.

4.3.9 Normality and Stability
The Jarque-Bera test analyses the normality of distribution of the residuals. The returned p-value is 0.839, exceeding the 5% significance level. Therefore, we fail to reject the null hypothesis of normal distribution of the residuals. Our CUSUM and CUSUMSQ output also show that our residuals stay with the 5% bounds demonstrating stability in the model.

5. Discussion
The results derived are consistent with the Classical-Marxian theory of inflation. The only assumption that was not shown to hold is a positive relationship between nominal GDP growth and relative new purchasing power. The results showed an insignificant, weak, negative relationship. There are several reasons why this may be the case. Nominal GDP growth has been largely stagnant since the 1990s. Britain has experienced an explosion in the service sector (Tomlinson, 2021). The service sector is associated with lower output growth, and less room for improvements in labour productivity compared with that of manufacturing (Leys, 1995). In the period of de-industrialisation, the growth of credit in this period likely flowed into services and speculation, weakening the link between new credit and nominal output (ibid).
A significant and strong positive relationship was observed for the assumption that RGDP=f (rr’). Whilst the Classical-Marxian theory argues that falling rr’ lowers the maximum rate of growth, increasing inflationary pressures, we see a sharp increase in rr’ from the start of the pandemic until 2022 (Figure 12), consistent with the literature pointing to a rise in corporate profits in Britain since 2020. This suggests that increasing profit margins are indeed contributing disproportionately to price rises (Unite, 2022), whilst wage-growth stagnates (Alvarez et al., 2022). Therefore, the demands for real pay rises being put forward by trade-unions such as Unite (2022), who rightly point out the hypocrisy of the Bank of England arguing for workers to accept wage cuts, unemployment and increased interest rates (Pill, 2023), whilst no similar call is made for profit restraint.

The results from the ARDL-ECM model were similar to previous efforts to apply the Classical-Marxian theory to Britain. RNPP was not found to have a significant impact on inflation in Britain in the long run or short run. This is consistent with findings by Özden and Bolkol (2023) which found no significant relationship between RNPP and inflation at the European level. This is to be expected from the theory, which argues that in cases where inflation rates are below 20%, prices will respond more to supply-side dynamics – increasing accumulation and declining profitability (Shaikh, 2016, p.719). Across Europe, we have seen historically low rates of inflation since the 1990s (Abdih, Lin and Paret, 2018), meaning that credit growth has not had a significant impact on inflationary pressures.
A significant and positive long-run relationship was found between inflation and growth utilisation when the impact of policy shocks was accounted for, whilst relative new purchasing power was not found to be significant in the long run. This is consistent with the literature for the UK which suggests a remarkably strong relationship between the two variables. Handfas (2012) showed a stronger relationship with an R2 value of 91% compared to 71% in the obtained results. This is perhaps due to his use of explicative dependent variables: eσ and eσ2. Shaikh also shows that we can observe the strong relationship between growth utilisation and inflation by use of standardised scaling. We can observe that growth utilisation experienced some recovery during the late 1990s following the fall in growth utilisation in the early part of the decade, but has largely stagnated since the early 2000s, never returning to its previous peaks, whilst inflation has also stayed at a relatively low level for decades, consistent with the Classical-Marxian theory (Shaikh et al, 1999).

5.1 Limitations and Suggestions for Further Studies
This study has broadly followed the approach as set out by Shaikh (2016, ch.15) and Handfas (2012), utilising the implicit GDP deflator as the measure of inflation. Further studies could benefit from instead using broader measures of inflation, including CPI, CPIH, and RPI. For example, RPI is the preferred measure of trade unionists in wage negotiations. Unite the Union (2022) insists on arguing that pay rises should be based on RPI and not CPI, as the exclusion of housing costs effectively acts as a tax on workers. This is why employers prefer the CPI measure, as it allows for the further restriction of wages (ibid).
The GDP deflator also doesn’t measure inflation on imported goods (Office for National Statistics, 2023). The global supply chain shortages brought about by the pandemic and later the Ukraine war have increased import costs, playing an instrumental role in the inflationary situation in Britain (Caporale et al., 2022), part of the reason the difference between the GDP deflator and RPI has been so vast since 2020. Stronger results may also be obtained by using alternative variables, such as the explicative variables used in Handfas’ study, or logged values, as was done by Özden and Bolkol (2023).
5.2.Conclusion
The Classical-Marxian model offers an alternative to both the neoclassical approach – which blames the state, and the post-Keynesian approach – which blames labour. Inflation in this framework is a function of growth utilisation, with the upper limit to growth being the net rate of profit, with excess demand playing a secondary role (and in Britain, an insignificant one at that). Therefore, inflation is a product of the capitalist mode of production itself and is not determined exogenously by state printing of money, or by trade union power pushing up wages in the face of full employment. As has been demonstrated, the current inflationary period is one characterised by rocketing profits, not wages, therefore, strike action by trade unions for real pay rises are justified.
As has been demonstrated, the Classical-Marxian theory can adequately explain the dynamics of inflation in Britain in the selected time period with a significant long run relationship between inflation and growth utilisation. The datasets also allow for the construction of an alternative Phillips curve in which unutilised growth capacity (1-σ) can play the role of the unemployment rate, producing a better long run relation than the post-Keynesian Phillips curve (Figure 14). Therefore, the theory can arm trade-unionists with counterarguments needed to challenge the theories of mainstream economics and their disciples in the Bank of England who demand that labour pays the price for the inflation crisis.

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1 The theory was described as the Classical-Marxian theory in Shaikh’s 1999 paper which focused on supply resistance. By 2016, Shaikh and others (Handfas, 2012) had incorporated demand pull factors into the model, describing the model as simply Classical. The theory itself is strongly influenced by Marx’s labour theory of value. We can also expect supply resistance to play a more significant role in the determination of inflation rates in Britain (See section 2.6). Therefore, it is justified to use the original Classical-Marxian terminology.




















































