The golden age of the world economy and Portuguese economic growth: applied study, 1950-2018

Figures & data

Table 1. Real GDP per capita growth rates (%) in different regions of the world economy, 1820–2018

	1820–1870	1870–1913	1913–1950	1950–1973	1973–2018
Western Europe	0.72	1.09	0.87	4.06	1.76
Eastern Europe	1.32	0.75	1.72	3.58	1.82
Western Offshoots	1.24	1.77	1.09	2.36	1.69
Latin America	0.65	1.35	1.25	2.69	1.62
Asia (East)	−0.19	-	-	5.20	3.42
Asia (South and South-East)	−0.18	0.79	−0.29	1.85	3.49
Middle East	0.36	-	-	3.66	2.74
Sub-Saharan Africa	0.00	-	-	2.01	1.17
World	0.62	1.31	0.67	2.94	1.90

Source: Own calculations, using data from the Maddison Project (2020).

Note: The growth rates were calculated from amounts expressed in 2011 USD.

Table 2. Real GDP per capita growth rates (%) in different countries of the world economy, 1820–2018

	1820–1870	1870–1913	1913–1950	1950–1973	1973–2018
Australia	3.75	1.06	0.99	2.43	1.99
Austria	0.85	1.45	0.18	4.94	1.97
Belgium	1.20	1.05	0.70	3.54	1.61
China	0.14	0.10	−0.56	2.81	4.91
Denmark	0.91	1.57	1.56	3.08	1.64
Finland	0.65	1.44	1.91	4.25	1.77
Former USSR	-	-	1.90	3.35	1.58
France	1.01	1.45	1.08	4.01	1.42
Germany	1.25	1.61	0.17	5.02	1.98
India	−0.19	0.54	−0.23	1.40	3.64
Italy	0.12	0.84	0.87	4.95	1.58
Japan	0.36	1.01	0.63	8.06	1.69
Mexico	0.08	1.52	1.53	3.41	1.74
Netherlands	0.77	0.88	1.07	3.45	1.85
Norway	0.91	1.66	1.84	3.25	3.49
Portugal	−0.14	0.58	1.39	5.45	1.97
Spain	0.25	1.24	0.33	5.41	2.24
Sweden	0.83	1.78	2.33	3.06	1.68
Switzerland	-	2.39	0.94	3.59	1.93
South Africa	0.16	0.89	2.16	2.19	1.35
United Kingdom	1.14	0.80	0.81	2.42	1.54
United States	1.18	1.75	1.12	2.45	1.64
World	0.62	1.31	0.67	2.94	1.90

Source: Own calculations, using data from the Maddison Project (2020).

Note: The growth rates were calculated from amounts expressed in 2011 USD.

Figure 1. Expenditure in the metropolis under the scope of the development plans, 1953–1971 (percentage of GDP).

Source: Ferraz (2020a, p. 50).

Table 3. Portuguese GDP growth rates and its components (%), 1913–2018

	1913–1950	1950–1973	1973–2018
GDP	2.79	5.71	3.72
Private consumption	2.68	4.73	3.71
Public consumption	3.45	6.97	5.38
Gross Fixed Capital Formation	5.94	8.90	1.74
Exports	3.01	5.71	6.84
Imports	3.70	9.06	5.68

Sources: Own calculations, using data from Batista et al. (1997), Pinheiro (coord. 2001), Valério (2008), AMECO (2021), and INE (2021).

Note: The growth rates were calculated from amounts expressed at 1914 prices.

Figure 2. Sectoral production of the Portuguese economy, 1947–1977 (1947 = 100).

Source: Own calculations, using data from Neves (1994) and Valério (2008).Note 1: The values were calculated from amounts expressed at 1914 prices.Note 2: The primary sector includes activities such as agriculture and fisheries. The secondary sector includes the activities of industry, electricity and construction. The tertiary sector includes service activities.

Figure 3. Degree of Openness of the Portuguese Economy (as a percentage of GDP), 1885–2018.

Sources: Own calculations, using data from Fontoura and Valério (2001), Valério (2008), AMECO (2021), and INE (2021).

Figure 4. Portuguese GDP per capita as a percentage of the G7ʹs average GDP per capita, 1885–2018.

Sources: Own calculations, using data from the Maddison Project (2020).Note 1: G7 = Canada, France, Germany, Italy, Japan, United Kingdom and United StatesNote 2: The values were calculated from amounts expressed in 2011 USD.

Table 4. Results of the estimations (OLS method with Robust Standard Errors)

Explanatory variables	Coefficients k Estimation (2)
Const	1.73 (0.91)
$GDPp{c}_{t-1}$	−0.07 (0.10)
$INVESTMEN{T}_t$	0.17 (0.05) ***
$INVESTMEN{T}_{t-1}$	0.07 (0.04) **
$TRAD{E}_t$	0.08 (0.06) **
$TRAD{E}_{t-1}$	0.01 (0.04) *
$HIGHE{R}_t$	0.01 (0.02)
$HIGHE{R}_{t-1}$	−0.02 (0.01)
$LIF{E}_t$	0.49 (0.24) **
$LIF{E}_{t-1}$	0.37 (0.37)
$LABOU{R}_t$	0.45 (0.37)
$LABOU{R}_{t-1}$	0.54 (0.25) **
t	0.00 (0.02)
Adjusted R-squared	0.58
P-Value (F)	0.00
P-Value of LM test for autocorrelation	0.89
P-Value of Durbin-Watson test for autocorrelation	0.33
P-Value of White test for heteroskedasticity	0.66
Variation Inflation Factors (VIF)	Values ≤ 3.0
P-Value of CUSUM test for Parameter Stability	0.33
CUSUMSQ test for Parameter Stability	All values fall within the critical bands of the 5% confidence intervals.

Note 1: “*”, “**” and “***” represent the statistical significance of the regressor at the 10%, 5% and 1% levels, respectively. Figures in parentheses are standard errors.

Note 2: The tests were performed using Gretl (2021).

Note 3: The appropriate ARDL lag order was chosen using the Akaike Information Criterion (AIC), Hannan-Quinn Information Criterion (HQC) and Schwarz-Bayesian Criterion (SIC/BIC).

Note 4: For the results of the stationary tests, see Table A1, A2 and A3 in the Appendix, which enables us to conclude that the variables are stationary.

Table

Test with constant and without trend
Variable	Lags	Test statistic	Conclusion
$GDPp{c}_t$	3	−4.80 ***	I (0)
$INVESTMEN{T}_t$	0	−6.14 ***
$TRAD{E}_t$	0	−7.41 ***
$HIGHE{R}_t$	1	−4.93 ***
$LIF{E}_t$	0	−13.39 ***
$LABOU{R}_t$	1	−5.23 ***

Note 1: ADF (Dickey & Fuller, 1979) tests were performed using Gretl (2021).

Note 2: In the ADF tests, *, ** and *** denote the rejection of the null hypothesis ($h_0$) of a unit root at the 10%, 5% and 1% levels. The maximum number of lags was chosen using the rule provided by Schwert (1989). The actual lag was obtained by testing down in order to optimise the Schwarz/Bayesian information criterion (SIC/BIC).

Table

Test with constant and without trend
Variable	Lags	Test statistic	Conclusion
$GDPp{c}_t$	0	−4.21 ***	I (0)
$INVESTMEN{T}_t$	1	−4.48 ***
$TRAD{E}_t$	0	−4.80 ***
$HIGHE{R}_t$	3	−2.60 **
$LIF{E}_t$	1	−2.30 **
$LABOU{R}_t$	0	−4.90 ***

Note 1: ADF-GLS (Elliot et al., 1996) tests were performed using Gretl (2021).

Note 2: In the ADF-GLS tests, *, ** and *** denote the rejection of the null hypothesis ($h_0$) of a unit root at the 10%, 5% and 1% levels. The maximum number of lags was chosen using the rule provided by Schwert (1989). The actual lag was obtained by testing down in order to optimise the Schwarz/Bayesian information criterion (SIC/BIC).

Table

Test with constant and without trend
Variable	Lags	Test statistic	Conclusion
$GDPp{c}_t$	3	0.38 *	I (0)
$INVESTMEN{T}_t$	3	0.58 **
$TRAD{E}_t$	3	0.23
$HIGHE{R}_t$	3	0.13
$LIF{E}_t$	3	0.54 **
$LABOU{R}_t$	3	0.07

Note 1: KPSS tests (Kwiatkowski et al., 1992) were performed using Gretl (2021).

Note 2: In the KPSS test, *, ** and *** denote the rejection of the null hypothesis ($h_0$) of stationarity at the 10%, 5% and 1% levels. The optimal lag was obtained using the Newey-West automatic bandwidth selection.

Table

“Innovational Outlier Tests”
Test with constant and without trend
Variable	Break date	Lags	Test Statistic	Conclusion
$GDPp{c}_t$	1975	0	−6.40 ***	I (0)
$INVESTMEN{T}_t$	1975	0	−7.06 ***
$TRAD{E}_t$	1974	0	−9.22 ***
$HIGHE{R}_t$	2003	0	−12.40 ***
$LIF{E}_t$	1956	0	−16.64 ***
$LABOU{R}_t$	1975	0	−6.42 ***

Note 1: Unit root tests with a breakpoint (Eviews, 2021, following Perron, 1989) were performed using Eviews (2021).

Note 2: In the unit root tests with a breakpoint, *, ** and *** denote the rejection of the null hypothesis ($h_0$) of a unit root with a possible break at the 10%, 5% and 1% levels. The maximum number of lags was chosen using the rule provided by Schwert (1989). The actual lag was obtained by testing down in order to optimise the Schwarz/Bayesian information criterion (SIC/BIC).

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