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Part I - General Approach to the Diagnostic

Published online by Cambridge University Press:  14 December 2023

António S. Cruz
Affiliation:
University of Copenhagen
Ines A. Ferreira
Affiliation:
University of Copenhagen
Johnny Flentø
Affiliation:
University of Copenhagen
Finn Tarp
Affiliation:
University of Copenhagen

Summary

Information

Figure 0

Figure 2.1 Mozambique in Southern Africa

Source: Authors’ construction based on Natural Earth Data (available at: www.naturalearthdata.com/about/terms-of-use/).
Figure 1

Figure 2.2 Road infrastructure and rivers

Source: Authors’ construction using © OpenStreetMap contributors (available at: www.openstreetmap.org/, www.opendatacommons.org/) for roads and the Regional Centre for Mapping of Resources for Development (RCMRD) (available at: https://opendata.rcmrd.org/) for waterways.
Figure 2

Figure 2.3 Administrative map of Mozambique

Source: Authors’ construction based on Natural Earth Data (available at www.naturalearthdata.com/about/terms-of-use/).
Figure 3

Figure 2.4 Real GDP growth per capita, smoothed (1991–2019)Note: Series are smoothed using a Kernel-weighted local polynomial smoothing algorithm; growth is based on GDP in constant 2011 international prices; countries are as follows: Mozambique = MOZ, Ethiopia = ETH, Ghana = GHA, Tanzania = TZA.

Source: Authors’ estimates based on data from WDI (World Bank 2020).
Figure 4

Figure 2.5 Sectoral trends in employment (1997–2015)

Source: Authors’ estimates based on household survey data series 1996/97, 2002/03, 2008/09, and 2014/15 (see MEF/DEEF 2016); private services include finance; public services include health, education, and public administration.
Figure 5

Figure 2.6 Sectoral contributions to levels of real value added (1991–2019)Note: Figure refers to the percentage contribution to production value-added in constant 2014 prices; public services include health, education, and public administration.

Source: Authors’ estimates based on unpublished data from National Institute for Statistics.
Figure 6

Figure 2.7 Labour productivity differences by sector (1997–2015)Note: X-axis is the natural logarithm of the ratio of labour productivity of the indicated sector to aggregate labour productivity; thus, values below 0 show lower than average productivity; private services include finance.

Source: Authors’ estimates based on household survey data series 1996/97, 2002/03, 2008/09, and 2014/15 (see MEF/DEEF 2016).
Figure 7

Figure 2.8 Sectoral contributions to real value-added growth, smoothed (1991–2019)Note: Manufacturing includes construction and utilities; growth refers to production value-added in constant 2014 prices; non-linear five period filter used.

Source: Authors’ estimates based on unpublished data from National Institute for Statistics.
Figure 8

Table 2.1 Expenditure components and sources of funds, 1999–2019 (as % shares of GDP)

Source: Authors’ estimates compiled from National Statistics Institute, Central Bank of Mozambique, and Ministry of Economy and Finance (internal).
Figure 9

Figure 2.9 ODA as percentage of GNI, 1990–2018

Source: Net ODA received (% of GNI) from World Bank (2020) data.
Figure 10

Figure 2.10 Major exports in US$ millions (2000–2019)Notes: Primary materials include energy exports; agricultural goods include fisheries.

Source: Authors’ estimates based on unpublished data from Central Bank of Mozambique.
Figure 11

Figure 2.11 Export complexity score (1991–2017)Notes: Lower scores mean less complex exports.

Source: Smoothed estimates from The Growth Lab at Harvard University (2020) data.
Figure 12

Table 2.2 Macroeconomic and fiscal indicators (2002–2019)

Source: Ministry of Economy and Finance database, unpublished.
Figure 13

Table 2.3 Metrics of poverty and inequality in Mozambique, 1996/1997–2014/2015

Source: Authors’ calculations from household survey microdata (see MEF/DEEF 2016).
Figure 14

Table 2.4 Household-level indicators of access/ownership of key assets

Source: Authors’ calculations from household survey microdata (see MEF/DEEF 2016).
Figure 15

Table 2.5 Comparison of social sector spending and outcomes

Source: Government Spending Watch (2020); UNICEF (2020).
Figure 16

Figure 3.1 Worldwide Governance Indicators, 2005 and 2018Note: Centre is at –2.5; lines further away from the centre correspond to better outcomes. The scores range from –2.5 to 2.5, with higher values representing better outcomes. Key: Voice and account, voice and accountability; Pol. violence, political violence; Gov. effect., government effectiveness; Reg. qual., regulatory quality; Rule law, rule of law; Control corr., control of corruption.

Source: Authors’ compilation based on Worldwide Governance Indicators (World Bank 2020).
Figure 17

Figure 3.2 Judicial independence, 2007–2019Note: The scores range from 1 to 7, with 1 being ‘not independent at all’ and 7 ‘entirely independenť.

Source: Authors’ compilation based on the Executive Opinion Survey (World Economic Forum 2020).
Figure 18

Figure 3.3 Political participation and sub-components, 2006 and 2020Note: Centre is at 1; lines further away from the centre correspond to better outcomes. The scale ranges from 10 (best) to 1 (worst). Key: Pol. participation, overall political participation score; Elections, free and fair elections; Eff. power, effective power to govern; Ass. rights, association/assembly rights; Free. expression, freedom of expression.

Source: Authors’ compilation based on the transformation index of the Bertelsmann Stiftung (BTI 2020).
Figure 19

Figure 3.4 Stateness and sub-components, 2006 and 2018Note: Centre is at 1; lines further away from the centre correspond to better outcomes. The scale ranges from 10 (best) to 1 (worst). Key: Stateness, overall score; Mon. use force, monopoly on the use of force; No rel. dogmas, no interference of religious dogmas; Basic admin., basic administration.

Source: Authors’ compilation based on the transformation index of the Bertelsmann Stiftung (BTI 2020).
Figure 20

Figure 3.5 Political corruption index, 2005–2019Note: The scale ranges between 0 and 1; the index runs from less corrupt to more corrupt.

Source: Authors’ compilation based on Varieties of Democracy data (Coppedge et al. 2020; Pemstein et al. 2020).
Figure 21

Figure 3.6 Trust in police, Rounds 6 and 7 of the Afrobarometer

Source: Authors’ compilation based on Afrobarometer Rounds 6 and 7 (Afrobarometer 2020).
Figure 22

Figure 3.7 International cooperation, 2006 and 2020Note: Centre is at 1; lines further away from the centre correspond to better outcomes. The scale ranges from 10 (best) to 1 (worst). Key: Int. coop., overall score; Use sup., effective use of support, which represents the extent to which the political leadership uses the support of international partners to implement a long-term strategy of development; Credibility, represents the extent to which the government acts as a credible and reliable partner in its relations with the international community; Reg. coop., regional cooperation, which represents the extent to which the political leadership is willing and able to cooperate with neighbouring countries.

Source: Authors’ compilation based on the transformation index of the Bertelsmann Stiftung (BTI 2020).
Figure 23

Table 3.1 Overview of the sample

Source: Authors’ calculations based on quantitative survey.
Figure 24

Table 3.2 Composition of the sample

Source: Authors’ calculations based on quantitative survey.
Figure 25

Table 3.3 Geographical origin of the respondents

Source: Authors’ calculations based on quantitative survey.
Figure 26

Figure 3.8 Choice of main constraints. (a) All ranking positions, number of occurrences. (b) Ranking = 1, number of occurrences

Source: Authors’ calculations based on quantitative survey.
Figure 27

Table 3.4 Overview of ranking distribution

Source: Authors’ calculations based on quantitative survey.
Figure 28

Figure 3.9 Choice of main constraints by gender (a) All ranking positions, number of occurrences (b) Ranking = 1, number of occurrences

Source: Authors’ calculations based on quantitative survey.
Figure 29

Figure 3.10 Choice of main constraints from respondents affiliated with the business sector (a) All ranking positions, number of occurrences (b) Ranking = 1, number of occurrences

Source: Authors’ calculations based on quantitative survey.
Figure 30

Figure 3.11 Choice of main constraints from respondents affiliated with academia (a) All ranking positions, number of occurrences (b) Ranking = 1, number of occurrences

Source: Authors’ calculations based on quantitative survey.
Figure 31

Figure 3.12 Choice of main constraints from respondents affiliated with the public administration (a) All ranking positions, number of occurrences (b) Ranking = 1, number of occurrences

Source: Authors’ calculations based on quantitative survey.
Figure 32

Figure 3.13 Distribution of statements by institutional area

Source: Authors’ calculations based on quantitative survey.
Figure 33

Figure 3.14 Distribution of average scores across statements, according to the Likert scores

Source: Authors’ calculations based on quantitative survey.
Figure 34

Figure 3.15 Frequency of statements under the institutional areas by average scores

Source: Authors’ calculations based on quantitative survey.
Figure 35

Table 3.5 Top issues with significant differences between men and women

Source: Authors’ calculations based on quantitative survey.

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