Accounting for the International Great Depression: Efficiency, Distortions and Factor Utilization during the Interwar Period

Alexander Klein; Keisuke Otsu

doi:10.1515/bejm-2020-0215

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Accounting for the International Great Depression: Efficiency, Distortions and Factor Utilization during the Interwar Period

Alexander Klein und Keisuke Otsu

Veröffentlicht/Copyright: 30. August 2021

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Aus der Zeitschrift The B.E. Journal of Macroeconomics Band 22 Heft 2

Abstract

In this paper, we analyze the International Great Depression (IGD) in the U.S. and Western Europe by applying the business cycle accounting method to a dynamic stochastic general equilibrium model with time-varying production efficiency and factor market distortions. We measure the size of labor and capital market distortions with endogenous factor utilization and their relative importance in accounting for output fluctuation during the interwar period. Our main findings are that labor market distortions accounted for two-thirds of the output drops in both the U.S. and Western Europe, endogenous factor utilization amplified the negative effects of labor market distortions, and government spending played an important role in the recovery from the Great Depression in European countries who left the Gold Standard in the early 1930s.

Keywords: international great depression; business cycle accounting; market distortions; factor utilization; total factor productivity

JEL Classifications: E13; E32; N10

Corresponding author: Keisuke Otsu, Faculty of Business and Commerce, Keio University, 2-15-45 Mita, Minato-ku, Tokyo, 108-8345, Japan; and School of Economics, University of Kent, Canterbury, Kent, UK, E-mail: k.otsu@fbc.keio.ac.jp

Acknowledgment

The authors would like to thank the editor, two anonymous referees, participants at the 18th SCE Annual Conference on Computing in Economic and Finance, Money, Macro and Finance Research group Annual Conference and The University of Kent KEMO workshop for helpful comments. We would also like to thank Erik Buyst, Herman de Jong, Albrecht Ritschl, Joan R. Roses, and Paul Sharp for their help with data.

Appendix A: Equivalence Results: Detailed Models of Investment and Labor Wedges

A.1 Expectational Shock Model and Investment Wedges

Following Harrison and Weder (2006), the firm maximizes its profit

π t = y t − w t l t − r t u k , t k t .

where

y t = A t γ u k , t k t θ l t 1 − θ

and A _t represents aggregate externality. The externality is taken as exogenous for individual producers and is defined as

A t = u k , t ̄ k t ̄ θ l t ̄ 1 − θ

where variables with “−” are aggregate variables. The parameter γ > 0 represents the degree of externality.

Now consider the consumer’s problem which is equivalent to that of the benchmark model with constant labor utilization and no wedges. The household maximizes lifetime utility

E 0 ∑ t β t Ψ ln c t + ( 1 − Ψ ) ln 1 − l t

subject to

w t l t + r t u k , t k t + π t + τ t = c t + x t .

The capital law of motion is the same as (5) in the benchmark model.

In equilibrium

θ y t k t = χ δ u k , t χ ,

so that

y t = θ χ δ 1 + γ θ χ − γ θ k t ( χ − 1 ) θ 1 + γ χ − γ θ l t χ ( 1 − θ ) 1 + γ χ − γ θ .

From the labor first order condition

w t = 1 − θ y t l t = 1 − θ θ χ δ 1 + γ θ χ − γ θ k t ( χ − 1 ) θ 1 + γ χ − γ θ l t χ ( 1 − θ ) 1 + γ χ − γ θ − 1 ,

where if χ ( 1 − θ ) 1 + γ χ − γ θ > 1 the labor demand is increasing in wage. This model can contain multiple equilibria due to an upward sloping labor demand curve.

Imagine that there is an exogenous positive non-fundamental expectational shock to the future output, y t + 1 * . The increase in future expected output raises the future expected marginal product of capital and hence increases current investment demand. An increase in future expected income also increases demand for consumption and decreases labor supply. If we assume that the labor demand curve is upward sloping with a slope steeper than the labor supply curve, this shift in the labor supply curve will lead to an increase in current labor input and wages. The increase in current labor input raises the current marginal product of capital which leads to an increase in capital utilization. The increase in current labor and capital utilization enables current output, consumption and investment to increase. Finally, an increase in future output due to the growth in capital stock validates the optimistic expectation.

Comparing the capital Euler equation

1 c t = β ̂ E t 1 c t + 1 χ − 1 χ θ y t + 1 * k t + 1 + 1 ,

to that in the benchmark model, (1) combined with (3),

1 c t = β ̂ E t 1 c t + 1 ω k , t + 1 χ − 1 χ θ y t + 1 k t + 1 + 1 ,

we can see that expectational shocks can be observationally equivalent to investment wedges.

A.2 Predetermined Wage Model and Labor Wedges

Consider a model as Cole and Ohanian (2004) in which labor unions have monopoly power on differentiated labor l _t(j) and has a bargaining power on nominal wage contracts that are set one period ahead of employment. Assume that the total labor l _t is as an aggregation of differentiated labor

l t = ∫ l t ( j ) 1 ζ t d i ζ t ,

where ζ _t represents the labor union’s bargaining power. Following Eggertson (2012) we consider this as a time varying parameter. The firm’s cost minimization leads to the demand for each differentiated labor

l t ( j ) = W t − 1 ( j ) W t − 1 ζ t 1 − ζ t l t ,

where W _t−1(j) is the predetermined nominal wage for labor j and W _t−1 is the aggregate wage index.

Now consider the union’s problem which is to maximize the members’ utility:

E t ∑ β t u c t ( j ) , l t ( j ) .

For simplicity we assume that the labor is the only production factor in the economy so that the budget constraint is

W t − 1 ( j ) l t ( j ) = P t c t ( j ) ,

where P _t is the general price level and c _t is consumption. Optimization leads to the following condition

W t − 1 = ζ t E t − 1 − u l t l t E t − 1 u c t P t l t ,

where we assume a symmetric equilibrium and drop the j notation.

Finally, the firms’ problem leads to the following optimality condition:

W t − 1 P t = m p l t .

Therefore, the labor market equilibrium condition is

(11) m p l t = ζ t P t E t − 1 − u l t l t E t − 1 u c t P t l t .

Comparing (11) to the benchmark labor equilibrium condition (2):

m p l t ω l , t = − u l , t u c , t ,

we can see that an unexpected deflation i.e. P _t < E _t−1[P _t] creates a wedge between the marginal product of labor and the marginal rate of substitution between labor and consumption. Intuitively speaking, deflation raises the real wage that the firm must pay given the predetermined nominal wage, and hence reduces labor demand. An increase in the union’s bargaining power ζ _t also creates a wedges in the labor market. This is because a rise in the monopoly power of labor unions gives an incentive for the union to demand higher contract wages for members and as a result the labor demand will fall. This corresponds to the mechanism proposed by Cole and Ohanian (2004) which explains how the New Deal policies may have prolonged the Great Depression.

Appendix B: Estimation for the Benchmark Model

In our model, investment wedges as well as factor utilization and hence efficiency wedges are all latent variables so that we cannot directly estimate the stochastic process of wedges. Therefore, we rely on structural estimation of the persistence matrix P, variance covariance matrix V. The estimation results are listed in Table A1.^[39] P _ij represents the spill-over of wedges j on wedges i. σ _i represents the standard deviation of the error term of wedges i. ρ _ij represents the correlation coefficient of the error terms of wedges i and j.

Table A1:

Bayesian estimation prior.

Parameter	Distribution.	Mean	S.E.	Support
P _ee	Normal	0.8	0.1	R
P _gg	Normal	0.8	0.1	R
P _kk	Normal	0.8	0.1	R
P _ll	Normal	0.8	0.1	R
P _eg	Normal	0	0.1	R
P _ek	Normal	0	0.1	R
P _el	Normal	0	0.1	R
P _ge	Normal	0	0.1	R
P _gk	Normal	0	0.1	R
P _gl	Normal	0	0.1	R
P _ke	Normal	0	0.1	R
P _kg	Normal	0	0.1	R
P _kl	Normal	0	0.1	R
P _le	Normal	0	0.1	R
P _lg	Normal	0	0.1	R
P _lk	Normal	0	0.1	R
σ _e	Inverse gamma	0.05	2.0	R ⁺
σ _g	Inverse gamma	0.05	2.0	R ⁺
σ _k	Inverse gamma	0.05	2.0	R ⁺
σ _l	Inverse gamma	0.05	2.0	R ⁺
ρ _eg	Beta	0	0.3	[−1, 1]
ρ _ek	Beta	0	0.3	[−1, 1]
ρ _el	Beta	0	0.3	[−1, 1]
ρ _gk	Beta	0	0.3	[−1, 1]
ρ _gl	Beta	0	0.3	[−1, 1]
ρ _kl	Beta	0	0.3	[−1, 1]

Appendix C: Linearization Errors

One concern of our results is that the linearization method might not be appropriate to study large economic fluctuations. When fluctuations of the variables become large, the linear approximation errors will increase. In this section we focus on the labor wedge to understand the magnitude of this issue.

Since the labor first order condition (2) is a static equation in which only the labor wedge is unknown, we can directly calculate non-linear labor wedges using data of observable variables. We take a log of the computed non-linear labor wedge and normalize at 1929 = 0 to compare them with the labor wedges computed from the linearized model. The standard deviations of each series for each country are listed in Table A2. It turns out that the magnitude of errors from linear approximation in computing labor wedges are not significant.

Table A2:

Standard deviations in labor wedges.

	Non-linear FOC	Model	Difference
Denmark	1.71%	1.72%	0.01%
Finland	7.48%	7.44%	−0.04%
France	10.80%	10.83%	0.03%
Germany	9.41%	9.67%	0.27%
Italy	9.19%	9.36%	0.17%
Netherlands	15.32%	15.47%	0.15%
Norway	10.49%	10.53%	0.03%
Spain	7.78%	7.77%	0.00%
Sweden	22.27%	22.27%	0.00%
UK	5.51%	5.55%	0.04%
US	6.18%	6.14%	−0.05%

Appendix D: Individual Simulation Results of European Countries

In Table A3 we present the individual simulation results for the European countries. We mainly focus on France, Germany, Italy and the UK because they are significantly larger than other European economies; the GDP shares in 1929 relative to the aggregate European economy in our sample are 18.6, 25.1, 12.0 and 24.1% respectively, which adds up to 79.8%.

Table A3:

Contribution of each wedge on output.

	Belgium			Denmark
	1929–32	1932–38	Cont	1929–32	1932–38	Cont
Efficiency	−0.124	−0.072	0.902	0.081	−0.072	0.348
Government	−0.009	0.013	−0.019	0.080	−0.058	−0.580
Investment	−0.007	0.017	0.006	−0.002	0.067	−0.504
Labor	−0.004	−0.014	0.112	−0.199	0.056	1.736
Data	−0.144	−0.055	1.000	−0.040	−0.008	1.000
	Finland			France
	1929–32	1932–38	Cont	1929–32	1932–38	Cont
Efficiency	−0.072	0.092	0.340	−0.180	0.275	0.209
Government	0.050	−0.025	−0.153	−0.015	0.031	−0.002
Investment	0.052	−0.036	−0.115	0.081	−0.155	0.176
Labor	−0.168	0.162	0.928	−0.117	−0.144	0.617
Data	−0.138	0.193	1.000	−0.230	0.007	1.000
	Germany			Italy
	1929–32	1932–38	Cont	1929–32	1932–38	Cont
Efficiency	0.054	−0.015	−0.083	−0.023	0.075	0.515
Government	−0.069	0.185	0.465	0.032	0.089	−0.463
Investment	−0.009	0.078	0.166	0.075	0.031	−0.865
Labor	−0.217	0.039	0.452	−0.199	−0.212	1.813
Data	−0.241	0.288	1.000	−0.115	−0.016	1.000
	Netherlands			Norway
	1929–32	1932–38	Cont	1929–32	1932–38	Cont
Efficiency	−0.085	−0.114	0.675	0.059	0.028	0.490
Government	0.034	−0.035	0.081	0.007	−0.001	−0.013
Investment	−0.027	0.170	−0.707	0.051	0.013	−0.309
Labor	−0.098	−0.089	0.952	−0.169	0.016	0.831
Data	−0.177	−0.068	1.000	−0.052	0.055	1.000
	Spain			Sweden
	1929–32	1932–38	Cont	1929–32	1932–38	Cont
Efficiency	−0.060	−0.907	1.677	0.012	0.034	0.100
Government	0.180	0.517	−1.383	−0.032	0.015	0.041
Investment	−0.350	0.295	−0.166	−0.009	0.036	0.235
Labor	0.097	−0.396	0.872	−0.048	0.051	0.623
Data	−0.134	−0.491	1.000	−0.078	0.137	1.000

Table A3:

(continued)

	UK
	1929–32	1932–38	Cont
Efficiency	−0.087	−0.040	0.054
Government	−0.018	0.023	0.209
Investment	−0.001	0.050	0.263
Labor	−0.006	0.071	0.475
Data	−0.113	0.104	1.000

France experienced one of the largest and persistent depressions in Europe. In France labor wedges contribute the most to the overall output fluctuation. Both labor and efficiency wedges individually account for the initial drop of output equally as large as in the data while investment wedges counteract this effect during the 1929–1932 period. Investment and labor wedges further depress the economy while efficiency wedges are counteracting this effect during the recovery period. A notable shock to the labor market is the 40 h work week policy introduced in 1936 which caused a decline in labor supply.

The German depression was as large as that in France whereas, unlike in France output fully recovered by 1938. In Germany government and labor wedges contribute roughly half each to the overall output fluctuation. Labor wedges account for most of the initial drop of output during 1929–1932 while government wedges account for most of the recovery during the 1932–1938 period. The large role played by government wedges on the recovery can be attributed to the increased government spending on rearmament (Ritschl 2002; Temin 1991).

The output drop in Italy between 1929 and 1932 was about half of that in France and Germany where output remained at its trough level throughout the 1930s as in the case of France. In Italy labor wedges are by far the most important wedge in accounting for the overall fluctuation in output. Labor wedges account for more than all of the initial drop in output. The slow recovery is mainly due to the further deterioration in labor wedges while government wedges were counteracting these forces. The deterioration in labor wedges are consistent with the Fascist labor market policies including the 40 h work week restrictions introduced in 1934. The increase in government wedges is consistent with the increase in military expenditure due to the Italo-Ethiopian war during 1935–36.

The depression in the UK during the 1930s was half the size of those in France and Germany and relatively short-lived. In fact, the Great Depression in the UK began in the early 1920s and the 1930s was a continuation of this depression period.^[40] In the UK labor wedges contribute most to the overall output fluctuation. Efficiency wedges alone can fully account for the initial output drop. Unlike other countries, labor wedges did not contribute much to the drop in output during the 1929 to 1932 period partially because the work week was already reduced significantly due to union bargaining in the early 1920s (Broadberry 1986, 1990; Cole and Ohanian 2002). Moreover, the improvement in labor wedges accounts for most of the recovery in output during the 1932–1938 period. Also, as in Germany and Italy, government wedges contributed to the recovery implying the expansionary effect of rearmament as stated in Thomas (1983). Crafts and Mills (2013) argues that the news of massive future defense spending after 1935 provided a boost to real GDP in the UK by stimulating private expenditure. This is consistent with the positive effect of investment wedges on output during the recovery period.

Appendix E: Data Appendix

E.1 Belgium

GDP, Private Consumption, Gross Fixed Capital Formation: Buyst, E. (1997) “New GNP Estimates for the Belgium Economy during the Interwar Period” Review of Income and Wealth, 43 (3), Table 3.

Employment: (Industrial employment without transportation sector): Goosens, M. D. (1988), De Belgische Arbeidsmarkt Tijdens het Interbellum, Tijdschrift voor Economie en Management, 33 (2), Table 1.

Hours: Clark, C., (1951), The Conditions of Economic Progress, London, Macmillan & Co. Ltd

Population, Wholesale Prices, Money Wages, Money Supply: Mitchell, B.R. (2013), International Historical Statistics: Europe, 1750–2010, 5th edition, Palgrave Macmillan: Basingstoke, Table A5, H1, B4, G1-G3.

Nominal Interest Rate: Historical Financial Statistics, International Policy Rates.

E.2 Denmark

GDP: Hansen, S. V. (1974), Okonomisk vaekst I Danmark, Bind II: 1914–1970, Akademisk Forlag, Kobenhavn, Table 1, 4.

Private Consumption, Gross Fixed Capital Formation: Niels Kaergard (1991), Okonomist Vaekst, Jurist-og Okonomforbundets Forlag, Table 2, 3.

Employment: Pedersen, P. J., (1974) Arbejdsstyrke og beskætigelse 1911–70, Socialt Tidsskrift, Vol. 53 (2), pp. 31–56.

Hours: Clark, C., (1951), The Conditions of Economic Progress, London, Macmillan & Co. Ltd

Nominal Interest Rate: Historical Financial Statistics, International Policy Rates.

E.3 Finland

GDP, Private Consumption, Gross Fixed Capital Formation, Employment, Population: Hjerppe, R. (1996): Finland’s Historical National Accounts 1860–1994: Calculation Methods and Statistical Tables, Jyvaskyla: Suomen Historian Julkaisuja, via The Nordic Historical National Accounts Database:

h ttp:/ /old.nhh.no/forskning/nnb/?selected = brows/xls

Hours: Clark, C., (1951), The Conditions of Economic Progress, London, Macmillan & Co. Ltd

Wholesale Prices, Money Supply: Mitchell, B.R. (2013), International Historical Statistics: Europe, 1750–2010, 5th edition, Palgrave Macmillan: Basingstoke, Table H1, B4, G1-G3.

Money Wages: Singer-Kerel, J. (1961), Le cout de la vie a Paris de 1840 a 1954, Colin.

Nominal Interest Rate: Historical Financial Statistics, International Policy Rates.

E.4 France

GDP, Private Consumption, Gross Fixed Capital Formation, Employment: The CEPII web site:

h ttp://www.cepii.fr/francgraph/bdd/villa/mode.htm

Hours: Clark, C., (1951), The Conditions of Economic Progress, London, Macmillan & Co. Ltd

Population, Wholesale Prices, Money Supply: Mitchell, B.R. (2013), International Historical Statistics: Europe, 1750–2010, 5th edition, Palgrave Macmillan: Basingstoke, Table A5, H1, B4, G1-G3.

Money Wages: Singer-Kerel, J. (1961) Le cout de la vie a Paris de 1840 a 1954, Colin, pages 536–537.

Nominal Interest Rate: Historical Financial Statistics, International Policy Rates.

E.5 Germany

GDP, Private Consumption, Gross Fixed Capital Formation: Ritschl, A. (2002), Deutschlands Krise und Konjunktur. Binnenkonjunktur, Auslandsverschuldung und Reparationsproblem zwischen Dawes-Plan und Transfersperre 1924–1934, Berlin: Akademie-Verlag.

Employment: Hoffmann, W.G. (1965): Das Wachstum der deutschen Wirtschaft seit der Mitte des 19. Jahrhunderts, Berlin: Springer Verlag, Table 20.

Hours: Clark, C., (1951), The Conditions of Economic Progress, London, Macmillan & Co. Ltd

Population: Hoffmann, W.G. (1965): Das Wachstum der deutschen Wirtschaft seit der Mitte des 19. Jahrhunderts, Berlin: Springer Verlag, Table 1.

Wholesale Prices, Money Wages, Money Supply: Mitchell, B.R. (2013), International Historical Statistics: Europe, 1750–2000, 5th edition, Palgrave Macmillan: Basingstoke, Table H1, B4, G1-G3.

Nominal Interest Rate: Historical Financial Statistics, International Policy Rates.

E.5 Italy

GDP, Private Consumption, Gross Fixed Capital Formation, Population: Baffigi, A. (2011), Italian National Accounts, 1861–2011, Banca d’Italia Economic History Working Papers 18.

Employment: Constructed from labor force and unemployment data. Clark, C., (1951), The Conditions of Economic Progress, London, Macmillan & Co. Ltd (for labor force, interpolated). Mitchell, B.R. (2013), International Historical Statistics: Europe, 1750–2010, Palgrave Macmillan: Basingstoke (for unemployment).

Hours: Constructed from Zamangi, V. (1994), Una Riconstruzione dell’Andamento Mensile dei Salari Industriali e dell’Ocupacione 1919–39, in Ricerche per la storia della Banca d’Italia, Vol. 5, Bari: Laterza, pp. 348–378 and Rossi, N., A. Sorgato and G. Toniolo (1993), I Conti Economici Italiani: una Riconstruzione Statistica, 1880–1990, Rivista di Storia Economica, Vol. X, pp. 1–47.

Wholesale Prices, Money Wages, Money Supply: Mitchell, B.R. (2013), International Historical Statistics: Europe, 1750–2010, 5th edition, Palgrave Macmillan: Basingstoke, Table H1, B4, G1-G3.

Nominal Interest Rate: Historical Financial Statistics, International Policy Rates.

E.6 The Netherlands

GDP: Smits, J.P., Woltjer, P.J. and Ma, D. (2009), A Dataset on Comparative Historical National Accounts, ca. 1870–1950: A Time-Series Perspective, Groningen Growth and Development Centre Research Memorandum GD-107, Groningen: University of Groningen.

Private Consumption: Centraal Bureau voor de Statistiek (2001): Tweehonderd jaar statistiek in tijdreeksen, 1800–1999, Voorburg/Heerlen, 2001, Table 9.

Gross Fixed Capital Formation: Groote, P., R. M. Albers and H.J. de Jong (1996), A Standardised Time Series of the Stock of Fixed Capital in the Netherlands, Groningen Growth and Development Centre Research Memorandum GD-25, pp.20.

Employment: Van Ark, B. and H. J. de Jong, (1996): “Accounting for Economic Growth in the Netherlands since 1913.” Groningen Growth and Development Centre Research Memorandum GD-107, Table A.1.

Hours: Clark, C., (1951), The Conditions of Economic Progress, London, Macmillan & Co. Ltd

Nominal Interest Rate: Historical Financial Statistics, International Policy Rates.

E.6 Norway

GDP, Private Consumption, Gross Fixed Capital Formation, Population: Grytten, O. H. (2004), “The Gross Domestic Product for Norway, 1830–2003.”’, in: Eitrheim, Ø., Klovland, J. T.,Qvigstad, Jan F. eds. Historical Monetary Statistics for Norway, Oslo: Norges Bank.

Employment: Clark, C. (1951): The Conditions of Economic Progress, London, Macmillan & Co. Ltd, page 103.

Hours: Clark, C., (1951), The Conditions of Economic Progress, London, Macmillan & Co. Ltd

Wholesale Prices, Money Wages, Money Supply: Mitchell, B.R. (2013), International Historical Statistics: Europe, 1750–2010, 5th edition, Palgrave Macmillan: Basingstoke, Table H1, B4, G1-G3.

Nominal Interest Rate: Historical Financial Statistics, International Policy Rates.

E.7 Spain

GDP, Private Consumption, Gross Fixed Capital Formation: Prados de la Escosura, L. (2003), El progreso económico de España, 1850–2000, Madrid: Fundación BBVA, Appendix F, H.

Employment, Hours: Prados de la Escosura, L.: mimeo

Population, Wholesale Prices, Money Supply: Mitchell, B.R. (2013), International Historical Statistics: Europe, 1750–2000, 5th edition, Palgrave Macmillan: Basingstoke, Table A5, H1, B4, G1-G3.

Money Wages: Maluquer de Motes, J., 1989, Precios, Salarios y Beneficios. La Distribucion Funcional de la Renta, in A. Carreras eds. Estadisticas Historicas de Espana, S. XIX-XX, Fundacion Banco Exterior: Madrid, Table 12.14.

Nominal Interest Rate: Historical Financial Statistics, International Policy Rates.

E.8 Sweden

GDP, Private Consumption, Gross Fixed Capital Formation, Employment, Population: Krantz, O. and L. Schön (2007): Swedish Historical National Accounts, 1800–2000, Lund University Macroeconomic and Demographic Database:

h ttp://www.ehl.lu.se/database/LU - MADD/

Hours: Clark, C., (1951), The Conditions of Economic Progress, London, Macmillan & Co. Ltd

Wholesale Prices, Money Wages, Money Supply: Mitchell, B.R. (2013), International Historical Statistics: Europe, 1750–2010, 5th edition, Palgrave Macmillan: Basingstoke, Table H1, B4, G1-G3.

Nominal Interest Rate: Historical Financial Statistics, International Policy Rates.

E.9 UK

GDP, Private Consumption, Gross Fixed Capital Formation, Employment, Population: Feinstein, C. H. (1972): National Income, Expenditure and Output of the United Kingdom, 1855–1965, Cambridge: Cambridge University Press, Table 5, 55, 59.

Hours: Clark, C., (1951), The Conditions of Economic Progress, London, Macmillan & Co. Ltd

Wholesale Prices, Money Wages, Money Supply: Mitchell, B.R. (2013), International Historical Statistics: Europe, 1750–2010, 5th edition, Palgrave Macmillan: Basingstoke, Table H1, B4, G1-G3.

Nominal Interest Rate: Historical Financial Statistics, International Policy Rates.

E.10 US

GDP, Private Consumption, Gross Fixed Capital Formation, Employment: Kendrick, J. W. (1961): Productivity Trends in the United States, Princeton University Press, Table A-IIa, A-VI.

Population, Hours, Money Wages: Carter, S., S. Gartner, M. Haines, A. Olmstead, R. Sutch and G. Wright (2006): Historical Statistics of the United States. Cambridge: Cambridge University Press, Table Aa6-8, Ba4592-4596, Ba4396.

Wholesale Prices, Money Supply: Mitchell, B.R. (2013), International Historical Statistics: Americas, 1750–2010, 5th edition, Palgrave Macmillan: Basingstoke, Table H1, G1-G3.

Nominal Interest Rate: Historical Financial Statistics, International Policy Rates.

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Received: 2020-10-04

Revised: 2021-05-14

Accepted: 2021-08-14

Published Online: 2021-08-30

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https://doi.org/10.1515/bejm-2020-0215

Schlagwörter für diesen Artikel

international great depression; business cycle accounting; market distortions; factor utilization; total factor productivity