^{1}

Dante Mendes Aldrighi

This paper examines profit rate (rates of return to capital) convergence in OECD economies in the periods of 1960-2016 and relevant sub-periods. It also performs comparison of profit rates convergence in selected developed and developing economies, using the data for 1973-2003 period. Economy-wide, productive economy and manufacturing rates are estimated and three convergence concepts are considered (beta, sigma, and stochastic convergence). We use a combination of cross-sectional and univariate time series models and density distribution analysis. For each profit rate measure, a strong evidence of beta convergence is provided. In contrast, sigma convergence is indicated only in the case of productive economy profit rate; while in other cases, sigma divergence or the absence of either convergence or divergence are likely. Stochastic convergence is present in a smaller number of economies and is confined to productive economy and manufacturing. The comparison of convergence dynamics in developed versus developing economies confirmed beta convergence in both groups and for their aggregate, but did not establish sigma convergence, given the significant diversity of economies and their different economic trajectories.

Este artigo examina a convergência da taxa de lucro (taxas de retorno do capital) nas economias da OCDE nos períodos de 1960-2016 e subperíodos relevantes. Ele também compara a convergência das taxas de lucro em economias selecionadas desenvolvidas e em desenvolvimento, usando os dados para o período 1973-2003. As taxas de economia produtiva e de manufatura em toda a economia são estimadas e três conceitos de convergência são considerados (beta, sigma e convergência estocástica). Usamos uma combinação de modelos de séries temporais transversais e univariadas e análise de distribuição de densidade. Para cada medida de taxa de lucro, uma forte evidência de convergência beta é fornecida. Em contraste, a convergência sigma é indicada apenas no caso da taxa de lucro da economia produtiva; enquanto em outros casos, a divergência sigma ou a ausência de convergência ou divergência são prováveis. A convergência estocástica está presente em um número menor de economias e está confinada à economia produtiva e manufatura. A comparação da dinâmica de convergência em economias desenvolvidas versus em desenvolvimento confirmou a convergência beta em ambos os grupos e para seu agregado, mas não estabeleceu convergência sigma, dada a significativa diversidade de economias e suas diferentes trajetórias econômicas.

The equalisation and convergence of distributive variables (returns to production factors, factor prices, and factor shares) has been a well-researched topic in economics. Several aspects of the phenomenon have been considered in literature: convergence of profit rates at the industry level in the context of competition among producers (

On the other hand, the empirical analysis of profit rate convergence on international scale has been limited in the literature and this paper is intended to contribute to filling this gap. The paper presents empirical analysis of factor price convergence (FPC) in OECD economies, with a specific focus on profit rates. As part of robustness checks it also compares the profit rate convergence in selected developed and developing economies using alternative profit rate indicator. We distinguish alternative measures of profitability, in particular economy-wide rate of profit, the rate of profit in the productive economy (thereby separating capitalist and non-capitalist sectors of the economy and excluding the latter from the analysis), and the rate of profit in manufacturing. We examine three aspects of convergence: beta-convergence, sigma-convergence, and stochastic convergence. We also use two alternative sources of information to construct rates of profit indicators. We conduct a series of econometric and statistical procedures: regression with cross-sectional data, analysis of dispersion coefficient and kernel density plots, linearity, structural break and unit root tests, and time-series regressions. Regarding terminology, we focus on FPC as opposed to FPE, as

The paper is organised as follows. Section 2 presents a review of theoretical and empirical works in the area. Section 3 discusses the data used in the analysis, the aspects of convergence, and econometric methods. Section 4 contains the results of empirical analysis, and Section 5 provides concluding remarks.

FPE theorem views free trade as a substitute to international movement of production factors and implies that trade between economies (even in the absence of production factor movements that would likewise lead to factor returns equalisation) brings equalisation of wage and profit rates (

In addition, the process may be impeded by the low scale of capital inflows, particularly from the developed to the developing economies, by the persistence of institutional differences, non-capitalist relations, and variation in production techniques that would perpetuate profit rate differentials (

As far as empirical research on international rate convergence is concerned, the following results emerge. The rates of return to capital vary across the economies and are substantially higher in the developing economies (

Overall, as suggested by the literature review, there is only partial evidence of equalisation even in the highly integrated economies of Western Europe and the OECD. This is in line with theoretical analysis by

This paper considers three alternative profit rate measures: profit rate for the total economy, profit rate for the productive economy (including agriculture, mining, manufacturing, utilities, construction, transport, storage and communication, wholesale and retail trade, and hotels and restaurants), and manufacturing profit rate.

Following

The first of the profit measures is estimated using AMECO (the European Commission macroeconomics database) for two groups of countries: Group 1 comprising 19 OECD economies in the 1960-2016 period and Group 2 comprising 21 OECD economies in the period of 1980-2016. The profit rate measures for the productive economy and the manufacturing sector (Groups 3 and 4) are estimated using the EUKLEMS database for 11 OECD economies in 1977-2006.

The profit rate for the total economy is estimated as net returns on the net capital stock, with the relevant adjustments for self-employment, as follows:

where

The productive economy and manufacturing profit rates are estimated using capital input data (November 2009 release) as net returns on the net capital stock, as per the following formula:

where

Sigma and beta convergence analyses are performed on profit rates, as defined in Equations (1) and (2). For stochastic convergence analysis, the relative profit rate, a measure of profit rates’ differential, is estimated as the ratio of individual economy profit rate and the weighted average profit rate. The weights are estimated based on consistent real GDP and real sectoral output data from the Maddison Project Database 2018 (for the weighted average profit rate in the total economy), and the UN National Accounts database, “GDP and its Breakdown at Constant 2010 Prices in US Dollars” (for the productive economy and manufacturing rates).

The paper examines three types of convergence - beta convergence, sigma convergence, and stochastic convergence - accentuating the different aspects of the convergence process.

Beta convergence (convergence in levels) examines whether profit rates in a cross-section of economies move over time to some unique level common to all the economies in question. The unconditional beta convergence analysis is performed by running regression with cross-sectional data as follows:

where

Sigma convergence (convergence in variance) concerns the cross-sectional dispersion of profit rates (specifically, increase versus stability or decrease in dispersion). Sigma-convergence analysis is conducted using raw profit rate and weighted average profit rate data.

First, the dispersion coefficient is estimated as follows:

with

where

Secondly, cross-sectional kernel densities of the profit rates are presented for selected years to examine changes in distribution of profit rates over time (the first and the last year of the respective series, as well as the years when the relative profit rate was the highest/ lowest). Following

Stochastic convergence analysis (

where

To conduct stochastic convergence analysis, the sequential procedure is used. Firstly, to determine whether series embed nonlinearity characteristics, the

Secondly, if non-linearity was suggested by the BDS test, the

and

where

Thirdly, for those series found by the BDS test to be linear or those that contain unit roots according to KSS test, the conventional unit root tests are considered (Augmented Dickey Fuller test (ADF), Kwiatkowski-Phillips-Schmidt-Shin (KPSS), and DF-GLS) (Dickey, Fuller, 1981; Kwiatkowski et al, 1992;

and

If

In the event that the Bai-Perron procedure did not identify a break, it was determined that series are non-stationary without breaks. Where at least one break was identified by the procedure, the Lee-Strazicich (LS) Lagrange Multiplier unit root tests with up to 2 breaks were conducted (Lee & Strazicich, 2003, 2004). The ‘crash’ and ‘break’ specifications were tried (Models A and C, in line with Lee-Strazicich definitions): the former for the series that likely contained constants, as suggested by the ADF test, the latter for the series with constant and trend. The maximum number of lags was set to 8, and the breaks at a particular date were identified using the general-to-specific procedure. The test was initially performed with two structural breaks, and if one trend dummy were insignificant, the test with a single break was performed (hence, models AA and CC for the test with two breaks, and models A and C for the tests with a single break). Where none of the breaks are significant, the

where

In the final step, for those series deemed stationary around a linear trend, the linear trend models were estimated using ARMA maximum likelihood, generalised, or conditional least squares. For those cases where breaks were present, the trend model included break(s) identified by the Bai-Perron procedure (given that LS tests are the tests of unit roots with breaks, rather than tests of the presence/number of breaks). If the trend model with break(s) had insignificant trend coefficient, it was re-estimated solely with breaks and no trend.

Overall, evidence of

This section presents the empirical results. The sub-sections that follow examine consecutively the beta-, sigma- and stochastic convergence.

There was a solid evidence of beta convergence in all four groups, though in most cases correction for outliers and cyclical variation was needed. In a basic specification (unconditional form of convergence with no dummy variables), the convergence coefficient was positive and insignificant, and the regression residuals were not normally distributed (given that the average annual rate of change in profit rates in Portugal was substantially lower, and in Australia, Ireland, and Luxembourg somewhat higher than in the rest of the group). A significant and negative coefficient was obtained when the dummy variable was set for the four economies. Excluding Portugal and setting dummy variables for the recession years of 1980-82 and 2009, or restricting the sample to 1982-2016, gave a negative (albeit insignificant) convergence coefficient. In Group 2 (including 21 economies over the period of 1980-2016), similar evidence of beta convergence arose (with dummy variables for Ireland and Luxembourg). Regarding Groups 3 and 4 (productive economy and manufacturing profit rates in 1977-2006, based on KLEMS data), all specifications indicated beta convergence. (Due to the presence of heteroscedasticity, the use of Huber-White standard errors was required in two estimations.)

The beta convergence regression results are presented in

Models
Constant
Beta
R
^{2}
_{adj} JB
Het.
Group 1
Specification 1
-0.489
0.119
0.021
96.475
0.231
(-0.309)
(0.606)
(0.000)
Specification 2
3.097
-0.156
0.964
1.378
0.503
(7.379)
(-3.917)
(0.502)
Specification 3
2.196
-0.121
0.125
1.377
HW
(2.965)
(-1.238)
(0.502)
Specification 4
4.421
-0.153
0.487
0.749
HW
(5.457)
(-1.501)
(0.688)
Group 2
Specification 5
5.932
-0.337
0.686
0.996
0.761
(8.926)
(-4.234)
(0.608)
Group 3
Specification 6
8.663
-0.699
0.441
0.014
HW
(3.399)
(-2.745)
(0.993)
Group 4
Specification 7
9.908
-0.514
0.292
0.187
0.172
(3.539)
(-2.262)
(0.911)

Note. Specification 1 (19 economies, economy-wide profit rate, AMECO data, 1960-2016 period); Specification 2 (dummy variables for Portugal, Australia, Ireland and Luxembourg); Specification 3 (dummy variables for 1980-82 and 2009, exclusion of Portugal); Specification 4 (all economies, 1982-2016 period); Specification 5 (21 economies, economy-wide profit rate, AMECO data, 1980-2016 period); Specification 6 (11 economies, productive economy profit rate, KLEMS data, 1977-2006 period); Specification 7 (11 economies, manufacturing profit rate, KLEMS data, 1977-2006 period). HW is Huber-White robust standard errors. JB is Jarque-Bera test for normality; Het. is White test of heteroscedasticity. T-statistics and Jarque-Bera probabilities are indicated in parentheses.

The dispersion of economy-wide profit rates, while fluctuating within the 0.2-0.4 band during the period of 1960-2016, trended downwards in the 1960s, increased in the early-1970s, fell in the second half of the 1970s, exhibited stability in 1980-1998, and then substantially increased in the late 1990s and into the post-GFC period. This regularity confirms the observation made by

Group 2 additionally included Japan. This did not alter the

The dispersion in manufacturing profit rates tended to co-move with the productive economy rate dispersion until the early 1990s, with divergence between the coefficients then becoming more pronounced. Figures in the Appendix confirm this regularity: starting from the early 2000s, a group of economies with substantially higher and growing profit rates than the rest of the sample (Australia, Austria, Finland, the Netherlands, and the US), as well as Italy as a clear outlier (with low and declining rates), can be identified. In the OECD context, the diverging manufacturing performance (albeit not precisely in terms of profitability) has been documented by both micro-level (

We further apply density distribution analysis to examine the dynamics of dispersion (

The results of the formal econometric tests of the dispersion coefficients are in line with the distribution analysis (

Test
Group 1
Group 2
Group 3
Group 4
Total economy
Total economy
Productive economy
Manufacturing
BDS
d=2
0.743
0.546
0.726
0.759
d=3
0.506
0.149
0.706
0.795
d=4
0.158
0.835
0.824
0.616
d=5
0.082
0.810
0.557
0.451
d=6
0.069
0.657
0.978
0.716
ADF
Stat.
-3.119
-3.868
-1.890
-2.933
Model
Constant [1]
Constant+trend [0]
Constant [0]
Constant [0]
KPSS
Stat.
0.177
0.067
0.431
0.159
Model
Constant [5]
Constant+trend [2]
Constant [4]
Constant [1]
DF-GLS
Stat.
-1.841
-3.979
-1.483
-2.981
Model
Constant [0]
Constant+trend [0]
Constant [0]
Constant [0]
Bai-Perron
Stat.*
45.563 [2]
Stat.**
54.145 [2]
Break
1990, 1994
LS
Stat.
-5.457 [6]
Model
A
Break
2003
Trend/break
Coefficient
0.009
-0.241
t-stat
(4.919)
(-4.505)
Model
ARMA-CLS
ARMA-CLS
Summary
Stationarity
Trend stationarity
Stationarity with break
Stationarity
Stability
Divergence
Convergence
Stability

Note. Augmentation lags are shown in square brackets. * and ** represent UDMax and WDMax statistics (that indicate the number of selected breaks); the breaks are based on the UDMax statistic. The critical values for UDMax and WDMax are 8.88 and 9.91 respectively. The critical values for ADF test are -4.13, -3.49, -3.17 at 1%, 5% and 10% level for the model with constant and trend, and -3.55, -2.91 and -2.59 at 1%, 5% and 10% level for the model with constant. The KPSS test critical values are 0.22, 0.15 and 0.12 at 1%, 5% and 10% level for the model with constant and trend and 0.74, 0.46 and 0.35 at 1%, 5% and 10% level for the model with constant. The DF-GLS test critical values are -3.77, -3.19 and -2.89 at 1%, 5% and 10% level for the model with constant and trend and -2.63, -1.95 and -1.61 at 1%, 5% and 10% level for the model with constant. AA indicates ‘crash’ specification for the Lee-Strazicich test. The critical values for the Lee-Strazicich AA model are -4.54, -3.84 and -3.50 at 1%, 5% and 10% level of significance; for model A are -4.24, -3.57 and -3.21 at 1%, 5% and 10% level of significance.

Stochastic convergence analysis was performed for the relative profit rates in the respective economies in the four groups. The results of the tests are shown in

In Group 1 (economy-wide profit rates, 1960-2016, 19 economies), according to the BDS test, the relative profit rates in Austria, Germany, Greece, Portugal, and Spain exhibited non-linearity characteristics (

In Group 2 (economy-wide profit rates, 1980-2016, 21 economies), according to the BDS test, the relative profit rate in Greece was likely to have been non-linear (

In Group 3 (productive economy profit rates, 1977-2006, 11 economies), non-linearity in the relative rates was detected in Austria, while non-linear stationarity was likely to have been present in only the de-trended data (

In Group 4 (manufacturing profit rates, 1977-2006, 11 economies), relative rates were non-linear in Japan, but according to KSS test, linear non-stationarity was detected for both demeaned series and de-trended and demeaned series (

In summary, in Group 1, relative profit rates exhibited deterministic behaviour (linear or non-linear stationarity with or without trends and breaks) in 11 of 19 cases. However, stochastic convergence to the weighted average rate level was experienced in 31.6% of cases (five of 19). In Austria, Finland, and Germany, the relative rate was stationary at a level other than 1. In France, Luxembourg, and Spain, the relative profit rate trended towards a level other than 1. In Group 2, the stationarity of various forms was observed in 11 cases out of 21. Stochastic convergence to the weighted average rate level was detected in Greece and the UK (nonlinear stationarity and trend stationarity without breaks, respectively), thus in 9.5% of cases. In other economies, relative rates trended away from 1 (Australia, Luxembourg, the Netherlands, and Spain) or fluctuated around a non-unitary mean (Denmark, Norway, Portugal, Sweden, and the US). In Group 3, deterministic patterns were identified in eight cases of 11. Stochastic convergence to the unitary level was observed in 36.4% of cases (Australia, Denmark, Finland, and the Netherlands). Among Group 4 economies as well, the deterministic behaviour was evident in eight cases, and stochastic convergence to the weighted average rate level in Australia, Austria, Finland, and the Netherlands (36.4% of cases). These findings are largely in line with sigma convergence analysis results, as most instances of convergence were observed in the productive economy and manufacturing, and for total economy, during 1960-2016, rather than 1980-2016.

Country
BDS
KSS (1)
KSS (2)
ADF
KPSS
DF-GLS
Bai-Perron
LS
Trend
Summary
p-value
t-stat
t-stat
t-stat
LM-stat
t-stat
UDMax
Breaks
LM-stat
Model
Breaks
Australia
0.870
5
0
CT
4
0
0.012
TS
Austria
2
0
0
NLS
Belgium
0.639
5
-2.326
0
CT
5
-2.371
0
49.627
1975, 1995
-4.385
6
C
1973
URB
Canada
0.924
2
-2.068
0
C
0.447
5
-0.989
0
128.734
1973, 2009
-2.540
4
SP
UR
Denmark
0.945
3
0
CT
5
0
0.005
TS
Finland
2
-2.059
0
-2.871
1
1
C
5
0
ST
France
0.254
5
-2.042
1
CT
5
-2.170
1
59.809
1975, 2009
8
CC
1978, 2000
-0.005
TSB
Germany
5
0
0
NLS
Greece
4
-2.987
0
CT
5
-2.167
0
101.556
1969, 1978
-5.181
7
CC
1976, 1991
URB
Ireland
0.957
6
-2.192
0
CT
5
-1.983
0
41.789
1974, 1995
-2.688
4
SP
UR
Italy
0.133
4
-1.934
0
C
5
0
48.152
1987, 2009
-2.063
0
A
1985
URB
Luxembourg
0.569
4
0
CT
4
0
39.371
1975, 2008
0
C
1976
0.006
TSB
Netherlands
0.753
3
-3.131
0
CT
0.235
5
-1.715
0
34.245
1971, 1997
-4.635
2
CC
1974, 1996
URB
Norway
1.000
6
-1.906
0
CT
0.517
5
-1.873
0
52.302
2000, 2009
-4.912
1
CC
1985, 2006
URB
Portugal
2
0
-3.034
0
-1.662
2
C
5
2
38.043
1972, 1980
8
AA
1976, 1983
SB
Spain
5
-1.010
0
0
0
CT
0.139
5
-1.931
0
56.856
1993, 2005
5
CC
1979, 1986
-0.005
TSB
Sweden
0.321
3
-2.982
0
CT
4
-2.839
0
107.902
1977, 1990
1
C
1989
-0.005
TSB
UK
0.425
2
1
C
5
1
17.339
1979, 1999
6
AA
1976, 1986
SB
USA
0.642
2
-2.962
0
CT
4
-2.401
0
70.767
1975, 2009
-3.973
3
C
1985
URB

Country
Ng-Perron
Phillips-Perron
MZa
MZt
MSB
MPT
Adj t-stat
Australia
0
Denmark
4
Finland
2
UK
-2.545
3

Note. As per

Country
BDS
KSS (1)
KSS (2)
ADF
KPSS
DF-GLS
Bai-Perron
LS
Trend
Summary
p-value
t-stat
t-stat
t-stat
LM-stat
t-stat
UDMax
Breaks
LM-stat
Model
Breaks
Australia
0.836
2
-2.391
2
CT
3
-2.457
1
39.433
1995, 2006
5
CC
1992, 2006
0.010
TSB
Austria
2
-2.469
0
-2.347
0
-2.603
1
CT
4
-2.766
1
28.494
1992, 2012
-3.594
4
C
2004
URB
Belgium
0.833
5
-2.331
0
CT
4
-2.244
0
49.461
1995, 2009
-3.785
7
C
2000
URB
Canada
0.994
2
-0.802
0
C
4
-0.580
0
104.535
2000, 2009
-2.381
8
A
2009
URB
Denmark
0.870
5
0
C
3
-2.782
0
ST
Finland
2
-1.541
0
-1.568
0
-1.830
1
C
4
-1.853
1
49.017
1997, 2009
-2.310
6
AA
1994, 2014
URB
France
0.870
2
-1.981
5
CT
0.184
5
-0.856
0
44.960
1987, 2009
-4.224
3
C
2000
URB
Germany
2
0
-2.985
0
-2.419
0
C
4
-1.705
0
27.439
1993, 2006
-2.474
1
A
2009
URB
Greece
2
0
0
NLS
Iceland
0.983
2
-2.696
2
CT
0
-2.581
2
44.121
1987, 2002
-3.790
7
C
2003
URB
Ireland
0.611
3
-1.355
0
C
0.501
4
-0.636
0
40.537
1996, 2004
-3.209
8
A
2015
URB
Italy
0.221
4
-0.769
0
C
5
-0.779
0
51.391
1987, 2009
-2.466
8
A
1999
URB
Japan
0.904
2
-1.472
0
C
4
-1.489
0
53.955
1985, 1992
-2.327
3
SP
UR
Luxembourg
0.879
3
0
CT
2
-3.441
0
75.025
1988, 2006
1
CC
1990, 2005
0.008
TSB
Netherlands
0.704
2
-2.740
1
CT
4
-2.826
1
81.717
1997, 2009
7
CC
1990, 2007
0.013
TSB
Norway
0.763
2
-1.445
0
C
4
-1.462
0
21.056
1986, 2000
8
A
1997
SB
Portugal
0.969
3
-1.574
0
C
4
-1.266
0
37.136
1986, 1996
8
AA
1998, 2004
SB
Spain
2
-0.802
0
-1.332
0
-2.053
0
CT
4
-1.906
0
38.676
1993, 2005
7
CC
1995, 2008
-0.012
TSB
Sweden
0.912
4
-1.717
0
C
0.601
5
-0.964
0
84.497
1989, 2000
5
A
2005
SB
UK
0.768
2
1
CT
1
-3.979
1
-0.008
TS
USA
0.273
6
-2.806
1
CT
4
-2.776
1
56.170
1992, 2009
6
CC
1995, 2007
0.003
TSB

Country
Ng-Perron
Phillips-Perron
MZa
MZt
MSB
MPT
Adj. t-stat
Denmark
5
Luxembourg
-13.728
-2.565
0.187
6.947
3
UK

Note as per

Country
BDS
KSS (1)
KSS (2)
ADF
KPSS
DF-GLS
Bai-Perron
LS
Trend
Summary
p-value
t-stat
t-stat
t-stat
LM-stat
t-stat
UDMax
Breaks
LM-stat
Model
Breaks
Australia
0.917
5
-3.216
2
CT
2
-2.832
1
67.067
1993, 2001
2
CC
1995, 2001
0.041
TSB
Austria
2
-1.070
0
-2.269
0
-1.489
1
C
4
-1.608
1
82.850
1984, 2000
8
AA
1989, 1995
SB
Denmark
0.794
6
-3.051
0
CT
0
0
29.930
1994, 2000
8
CC
1991, 2001
0.028
TSB
Finland
0.917
5
-1.428
1
C
4
-1.252
1
79.263
1995, 1999
8
AA
1990, 1998
SB
Germany
0.790
4
-1.767
0
C
4
-1.414
0
41.136
1981, 1992
-3.385
4
SP
UR
Italy
0.353
2
-1.988
0
C
2
0
11.726
1995, 2003
-3.449
4
SP
UR
Japan
0.320
2
-2.826
1
CT
4
-1.572
1
27.562
1981, 1994
-2.518
4
SP
UR
Netherlands
0.986
6
-1.764
1
C
4
1
87.303
1987, 2000
8
AA
1999
SB
Spain
0.895
5
-1.745
1
CT
3
-1.944
1
106.061
1986, 1992
7
CC
1995, 1999
-0.016
TSB
UK
0.765
5
5
C
4
5
59.886
1982, 1986
5
AA
1991, 2001
SB
USA
0.776
6
-2.746
0
CT
3
-2.194
0
42.333
1981, 1993
6
CC
1989, 1991
0.011
TSB

Country
Ng-Perron
Phillips-Perron
MZa
MZt
MSB
MPT
Adj. t-stat
UK
-1.800
1

Note as per

Country
BDS
KSS (1)
KSS (2)
ADF
KPSS
DF-GLS
Bai-Perron
LS
Trend
Summary
p-value
t-stat
t-stat
t-stat
LM-stat
t-stat
UDMax
Breaks
LM-stat
Model
Breaks
Australia
0.920
3
1
CT
0.462
23
1
40.290
1987, 1993
5
CC
1993, 2001
0.026
TSB
Austria
0.984
3
-2.192
1
CT
4
-2.138
1
84.729
1995, 2000
7
C
1989
0.026
TSB
Denmark
0.936
6
-2.406
0
C
3
0
10.194
1987, 1994
2
A
1993
SB
Finland
0.769
2
-1.403
0
C
4
-1.069
0
47.310
1994, 1998
8
AA
1988, 1994
SB
Germany
0.840
2
-1.634
0
C
4
-1.222
0
63.295
1992, 2001
8
AA
1993, 1998
SB
Italy
0.703
3
-3.082
1
CT
1
1
43.717
1990, 2003
6
CC
1988, 1998
-0.039
TSB
Japan
2
-1.369
1
-1.128
1
1
CT
3
-1.705
2
70.470
1981, 1994
-4.702
4
CC
1987, 1998
URB
Netherlands
0.878
5
-2.838
0
CT
3
-2.454
0
111.384
1994, 2000
6
CC
1992, 2004
0.037
TSB
Spain
0.872
5
-3.018
1
CT
3
-2.540
1
91.666
1992, 2003
-3.673
6
C
1990
URB
UK
0.841
6
-1.768
0
C
4
0
30.754
1993, 1999
-2.687
3
AA
1992, 2000
URB
USA
0.996
2
6
CT
4
-1.670
3
86.187
1989, 1993
7
CC
1989, 2000
0.030
TSB

Note as per

It may be argued that factor price convergence is phenomenon that is not limited to developed countries alone, but that concerns nations with different levels of economic development. We note that other sources of data are available for the construction of profit rate indicators. Comparison of profit rate levels and dynamics may also be instructive.

To address these issues, we make use of “Extended Penn World Tables: Economic Growth Data assembled from the Penn World Tables and other sources” database constructed A. Marquetti and estimate economy-wide profit rate for a total of 39 developed and developing economies over the 1973-2003 period. The economies included in the sample are: Australia, Austria, Belgium, Canada, Denmark, Finland, France, Greece, Ireland, Italy, Japan, Luxembourg, Netherlands, New Zealand, Norway, Portugal, Spain, Sweden, Switzerland, the UK and the US in the developed economies group, and Bolivia, Chile, Colombia, Costa Rica, Hong Kong, Israel, Jordan, Kenya, South Korea, Mauritius, Mexico, Panama, Peru, South Africa, Sri Lanka, Thailand, Trinidad and Tobago and Venezuela in the developing economies group. The database has a number of gaps in the series and shorter time series for a number of economies, hence the selection of the countries was dictated by data availability.

The profit rate is calculated conventionally as ratio of net operating surplus to capital stock as:

where

The visual examination of the average profit rates for the world in total and for the developed and developing economies indicates three regularities (

The beta convergence was present in both country groups and for the aggregate of the groups (

Models
Constant
Beta
R
^{2}
_{adj}JB
Het
Aggregate
2.329
-7.959
0.178
0.626
HW
(2.646)
(-2.315)
(0.731)
Developed
2.286
-10.017
0.088
1.907
0.123
(1.805)
(-1.711)
(0.385)
Developing
3.590
-10.358
0.315
0.725
0.487
(3.194)
(-2.972)
(0.696)

Note. As per

With regard to sigma convergence, the profit rate dispersion coefficient tended to be stable during the period or had moderate upward trend (

A more formal analysis (

Test
Aggregate
Developed
Developing
BDS
d=2
0.060
0.577
0.044
d=3
0.017
0.251
0.017
d=4
0.004
0.373
0.035
d=5
0.001
0.081
0.069
d=6
0.001
0.039
0.099
KSS
Stat.
-3.785
N/A
-2.131
ADF
Stat.
-3.671
-2.017
-1.952
Model
Constant
Constant
Constant
Stat.
-3.542
-2.347
-1.849
Model
Constant+trend
Constant+trend
Constant+trend
KPSS
Stat.
0.204
0.446
0.407
Model
Constant
Constant
Constant
Stat.
0.103
0.135
0.156
Model
Constant+trend
Constant+trend
Constant+trend
DF-GLS
Stat.
-2.836
-1.630
-1.727
Model
Constant
Constant
Constant
Stat.
-3.378
-2.392
-2.023
Model
Constant+trend
Constant+trend
Constant+trend
Bai-Perron
Stat.
20.004
66.769
Stat.
20.004
79.346
Break
1998
1983, 2000
LS
Stat.
-3.756
-4.060
-5.113
Model
AA
AA
AA
Break
1987, 1990
1984, 1988
1987, 1997
Stat.
-6.394
-8.287
-6.086
Model
C
CC
CC
Break
1986
1987, 1999
1985, 1992
Trend/break
Coefficient
0.000
0.001
0.001
t-stat
0.067
0.650
0.957
Model
ARMA-CLS
ARMA-CLS
ARMA-CLS
Summary
Stationarity
Stationarity with break
Stationarity with break
Stability
Stability
Stability

Note. As pr

Overall, we conclude that consideration of a more inclusive group of countries does not alter the results compared to the study when limited number of more homogeneous countries (OECD or EU) is examined. The beta-convergence took place in developed and developing countries alike. Sigma-convergence analysis pointed to stability of the dispersion across the countries in a given group (i.e., neither convergence nor divergence) or moderate increase in dispersion (i.e., divergence). This result is consistent with the study of OECD profit rates: it is expected that inclusion of a greater number of diverse economies with different economic trajectories and experiences would not result in sigma convergence as was the case in same of the OECD groups.

This paper examined the issue of convergence in profit rates in OECD economies in recent decades. Three profit rates indicators (economy-wide, productive economy, and manufacturing rates) and three convergence concepts (beta, sigma, and stochastic convergence) were considered. It was shown that the profit rates in a cross-section of the economies converged to a single steady-state level, and a negative relationship between the initial level of the profit rates and their change rates was demonstrated (i.e., beta convergence was present). The dispersion of profit rates was stable in the case of economy-wide profit rates in 1960-2016 and manufacturing profit rates in 1977-2006 (the absence of sigma convergence or divergence). Some increase in manufacturing profit rates dispersion was indicated in the later part of the period (late 1990s and the 2000s), indicating a nascent sigma divergence tendency. Productive economy profit rates exhibited clear sigma convergence (decline in dispersion), while economy-wide rates in 1980-2016 showed clear sigma divergence (increased dispersion). On an individual country basis, stochastic convergence (conceptualised as mean reversion of the relative profit rates towards the unitary level, or trend stationarity with a negative trend coefficient) was indicated in a smaller number of cases, being most common in the case of productive economy and manufacturing profit rates. The robustness check performed on a larger set of developed and developing economies and aggregate profit rates confirmed the findings with regard to presence of beta convergence, but did not identify reduction of profit rates’ dispersion (sigma convergence), given the diversity and heterogeneity of economies in the set. The study is in line with previous research efforts in the field. The identified different levels of profit rates across the developed and developing economies confirms the previous findings by

^{th}Conference paper, 23-26 August, Vienna.

^{st}century”. In Panitch, L., Albo, G., Chibber, V. (Eds). The Crisis This Time: Socialist Register 2011. London: The Merlin Press.

E25, C22, O40, F15

In the case of capital, the developed economies with abundant capital and low returns experience capital outflow to developing economies, characterised by capital scarcity and high capital returns, thereby leading to profit rate equalisation across economies (

Another notable study conducted by

The first group (1960-2016) based on AMECO includes Australia, Austria, Belgium, Canada, Denmark, Finland, France, Germany, Greece, Ireland, Italy, Luxembourg, Netherlands, Norway, Portugal, Spain, Sweden, the UK, the USA. The second group (1980-2016) based on AMECO additionally includes Iceland and Japan. The two groups (1977-2006) based on KLEMS database include Australia, Austria, Denmark, Finland, Germany, Japan, Italy, Netherlands, Spain, the UK, and the USA.

The increase of labour share in the mid-1970s is documented by

The database is available at https://sites.google.com/a/newschool.edu/duncan-foley-homepage/home/EPWT