MATRICULAS DE COMERCIO

calculate 𝑻𝑻𝑻𝑻𝑻𝑻 in selected developing economies

This section outlines the results of the calculation of 𝑇𝑇𝑇𝑇𝑇𝑇 for 17 selected developing economies, using public data from the World Bank Development Indicators. 𝑇𝑇𝑇𝑇𝑇𝑇 was calculated using Cobb-Douglas Production function with a Solow residual. The descriptive statistics reported in Table 6.1 shows that there is a strongly balanced panel of 442 observations for each of GDP, capital stock and labour stock for the 17 selected developing economies. Table 6.2 displays the contribution (in logs) of each capital, labour and 𝑇𝑇𝑇𝑇𝑇𝑇 to national output for the selected 17 economies.

Table 6.1: Descriptive statistics of variables used to calculate TFP

Variable Obs Mean

Std.

Dev. Min Max Real GDP 442 0.04 0.05 -0.21 0.34 Capital Stock (𝐴𝐴) 442 0.03 0.05 -0.04 0.80 Labour Stock (𝐿𝐿) 442 0.01 0.01 -0.02 0.06

Notes: Data for GDP constant at 2010 US$ from World Bank (2017). Data for labour stock from World Bank (2017). Capital stock author’s calculation using data on gross fixed capital formation (constant 2010 US$) from (World Bank, 2017) and capital depreciation rates from Feenstra et al. (2015).

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Table 6.2 shows that there is an extremely weak correlation amongst GDP, capital and labour, though there is a strong correlation between GDP and 𝑇𝑇𝑇𝑇𝑇𝑇 (column 1). Diagnostic tests of variance inflation factor (VIF) also indicate that there is moderate multicollinearity amongst the variables used to decompose national output (mean VIF 1.00). The correlation of 𝑇𝑇𝑇𝑇𝑇𝑇 growth, aggregate capital and labour stock growth is zero. This would suggest that it is possible to uniquely estimate the fraction of output growth that is due to aggregate capital or labour stock growth and 𝑇𝑇𝑇𝑇𝑇𝑇 growth absent any other assumptions about the correlation of output growth due to aggregate factor input growth and 𝑇𝑇𝑇𝑇𝑇𝑇 growth. This will lend support to the argument that much of the significance of the variance of 𝑇𝑇𝑇𝑇𝑇𝑇 growth across these selected developing economies is associated with negative 𝑇𝑇𝑇𝑇𝑇𝑇 growth. Amongst these 17 selected developing economies the average 𝑇𝑇𝑇𝑇𝑇𝑇 expected growth is 0 percent per year. This means that if one of the 17 economies are chosen at random with equal probability, the expected growth rate of 𝑇𝑇𝑇𝑇𝑇𝑇 is 0 percent per year. This is hardly suggestive of technological change.

Table 6.2: Results of Pearson correlation analysis of the relationship between GDP (log), capital stock (log), labour stock (log) and 𝑇𝑇𝑇𝑇𝑇𝑇 (log)

(In logs) GDP Capital

Stock Labour Stock Capital Stock 0.09 (0.06) 1 Labour Stock 0.01 (0.88) -0.12** (0.01) 1 TFP 0.87** (0.00) -0.01 (0.78) -0.01 (0.80)

Notes: 442 observations for each variable. The correlation of all data in logs. **Correlation is significant at the 0.01 level. p value in brackets.

Table 6.2 shows that there is a statistically significant negative (at the one percent level) relationship between capital stock and labour stock (r(440) = -0.12,

p=0.01) . The null hypothesis is not rejected at the 0.01 level. Not surprisingly,

there is evidence that 𝑇𝑇𝑇𝑇𝑇𝑇 is highly statistically positively significant at the one percent level (r(440) = 0.87, p=0.01). Holding all other variables constant, a unit

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increase in 𝑇𝑇𝑇𝑇𝑇𝑇 is expected to be associated with approximately an 80 percent increase in national output amongst these 17 selected developing economies.

Table 6.3: Results of least square regression of GDP, capital stock, labour stock and TFP for the period 1990 to 2015

(In logs) GDP Capital Stock 0.05* (2.25) Labour stock 0.15 (0.96) TFP 1.00*** (37.60) Constant 0.040*** (18.11) Obs 442 R 0.87 R2 _0.76

Notes: Least square regression to examine whether there is a relationship between GDP and the proximate determinants of economic growth (capital stock, labour stock and 𝑇𝑇𝑇𝑇𝑇𝑇. All data used in the least square regression was in logs. Dependent variable GDP, independent variables are capital stock, labour stock and 𝑇𝑇𝑇𝑇𝑇𝑇. t statistics in parentheses. *p<0.05, **p<0.01, ***p<0.001

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Figure 6.1: Scatter plot of predicted line of the association between GDP and productivity for the period 1990 to 2015

Table 6.3 displays the least squares regression results of the estimation of the relationship amongst GDP, capital stock, labour stock and 𝑇𝑇𝑇𝑇𝑇𝑇. The data set used to calculate 𝑇𝑇𝑇𝑇𝑇𝑇 yields interesting results for the productivity of capital stock and labour stock in the 17 selected developing economies for the period 1990 to 2015. Not unexpectedly, there is evidence of a strong positive statistical relationship between GDP and 𝑇𝑇𝑇𝑇𝑇𝑇 (in logs) (Figure 6.1: Scatter with predicted line of

relationship between GDP and productivity). However, unexpectedly, these selected developing economies exhibit high levels of extensive growth, particularly

characterised by consistently increasing levels of capital stocks (Table 6.4: Average percentage change (log) of sources of growth of 17 selected developing economies 1990 to 2015). Appendix (B) graphically portrays the decomposition of the sources of economic growth in the 17 selected developing economies.

The first column of Table 6.4 shows each economies’ output growth. Unsurprisingly none of the economies have achieved more than one percentage change in economic growth over the 25-year period. Apart from Zimbabwe, Jamaica

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and Malawi, the remaining 15 economies experienced nearly identical rates of economic growth over the full period. The remaining columns of Table 6.4 decompose percentage changes (in logs) in economic growth into contributions from capital stock, labour stock and productivity. The increase in economic growth in the 17 selected developing economies is primarily determined by changes in capital stock (column 2). 𝑇𝑇𝑇𝑇𝑇𝑇 levels are expectedly low for all 17 selected

developing economies. Nigeria, Kenya and Egypt exhibited comparatively higher percentage changes in GDP constant from 1989 to 1990 and higher percentage changes in productivity from 1989 to 1990 (Figure 6.2: Productivity and real GDP in 1990).

In 1990 each unit change of TFP is associated with a 100-percent increase in real GDP in the selected developing economies (Figure 6.2: Productivity and real GDP in 1990). By 2000 a unit change in 𝑇𝑇𝑇𝑇𝑇𝑇 on average associated with a positive increase of 76 percent in real GDP in the selected developing economies (Figure 6.3: Productivity and real GDP in 2000). By 2015, a unit change in 𝑇𝑇𝑇𝑇𝑇𝑇 on average is associated with a 95 percent percentage increase in real GDP in the selected developing economies (Figure 6.4: Productivity and real GDP in 2015).

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Table 6.4: Average percentage change (log) of sources of growth of 17 selected developing economies 1990 to 2015

Notes: Results of Cobb-Douglas production function with 𝑇𝑇𝑇𝑇𝑇𝑇 as Solow residual equation:

𝑌𝑌

𝑡𝑡

= 𝐴𝐴

𝑡𝑡

𝐴𝐴

𝑡𝑡𝛼𝛼

𝐿𝐿

𝑡𝑡1−𝛼𝛼. Data for GDP constant at 2010 US$ from World Bank (2017). Capital

stock author’s calculation using perpetual inventory method with data on gross fixed capital formation (constant 2010 US$) from World Bank (2017) and capital depreciation rates from Feenstra et al. (2015). Data for labour stock from World Bank (2017). TFP author’s calculations using data on GDP, capital stock and labour stock from World Bank (2017).

GDP Constant

Contribution to National Output Country Capital Stock Labour Stock Total Factor Productivity BGD 0.05 0.04 0.01 0 BWA 0.05 0.04 0.01 0 EGY 0.04 0.02 0.01 0 GHA 0.06 0.02 0.01 0 IND 0.07 0.03 0.01 0 JAM 0.01 0.01 0.01 0 KEN 0.04 0.03 0.01 0 LKA 0.05 0.02 0 0 MUS 0.05 0.02 0.01 0 MWI 0.01 0.01 0.01 0 MYS 0.06 0.04 0.02 0 NGA 0.06 0.03 0.01 0 PAK 0.04 0.01 0.02 0 SLE 0.03 0.10 0.01 0 TZA 0.05 0.02 0.01 0 ZMB 0.05 0 0.02 0 ZWE 0.01 0.01 0.01 0

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Figure 6.2: Productivity and real GDP in 1990 for the sample of 17 selected developing economies

Notes: Data for Output per Worker from World Bank (2017). TFP author’s calculations from data retrieved from World Bank (2017)

Figure 6.3: Productivity and real GDP in 2000 for the sample of 17 selected developing economies

Notes: Data for GDP per capitafrom World Bank (2017). TFP author’s calculations from data retrieved from World Bank (2017)

BGD BWA EGY GHA IND JAM KEN LKA MUS MWI MYS NGA PAK SLE TZA ZMB ZWE -.2 -.1 0 .1 .2 .3 GDP (Constant US$ 2010) -.4 -.2 0 .2 .4

Total Factor Productivity

GDP Constant Linear prediction

Coefficient: 0.76 p-value: 0.03 R2_{: 0.27} Coefficient: 1.06 p-value: 0.00 R2_{: 0.90}

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Figure 6.4: Productivity and real GDP in 2015 for the sample of 17 selected developing economies

Notes: Data for GDP per capita from World Bank (2017). TFP author’s calculations from data retrieved from World Bank (2017)

6.3

Summary of the results of calculating the aggregate

In document DIARIO OFI CIAL DIRECTOR: Luis Ernesto Flores López (página 61-68)