rafmacalaba/datause-encoder-data huggingface dataset:
# **1. Introduction**

<mark>Logistics combines operations and services related to the movement and storage of goods. Logistics services include freight forwarding; third-party logistics; customs brokerage; road transportation; port, airport and rail operations; and warehousing and refrigeration. Logistics is a critical contribution to economic activity within and across borders. Efficient logistics help reduce trade costs and is essential to trade and regional integration. Low international connectivity, inadequate logistics infrastructure, low-quality logistics services, and heavy trade procedures at and behind the border raise logistics costs. Logistics costs amount to 8% of GDP in the United States but rise to 15%-20% in many middleincome countries and up to 30% in low-income countries, landlocked or island states.</mark><sup>2</sup> <mark>Although logistics is mainly a B2B activity, its efficiency depends on policy interventions. Logistics activities expand in space and time, require specific infrastructure (e.g., ports), involve government controls (e.g., customs clearance), and have a large environmental or spatial footprint (e.g., warehouses, multimodal terminals). Logistics performance, a concept introduced by the World Bank (Arvis et al. 2007), is a cross-cutting concern for the public sector and international organizations. It combines interventions in the following areas: infrastructure and provision of infrastructure services including ports (often in public-private partnership) or land corridors, regulations and market incentives, and border management.</mark><sup>3</sup> <mark>Logistics also require specific attention as a contribution to broader concerns such as spatial planning (e.g., logistics zones), skills and training, urban policies (distribution in urban environments), and especially decarbonization (“green logistics”).</mark><sup>4</sup> <mark>The World Bank introduced the Logistics Performance Index (LPI) in 2007 as a set of country indicators to inform policy makers and practitioners.</mark> What is the World Bank Logistics Performance Index (LPI)?

The World Bank’s Logistics Performance Index is a comprehensive index that has been covering the entire supply chain for between 139 and 160 countries in the 2007 to 2023 editions. It is based on a survey of nearly 1,000 logistics professionals worldwide and is useful for comparing performance across countries and identifying and prioritizing broad reform areas for interventions within countries. The index is based on numerical ratings of 1 (weakest) to 5 (strongest).

The Logistics Performance Index is a weighted average of six components:

1. Efficiency of the clearance process

2. Quality of trade- and transport-related infrastructure 3. Ease of arranging competitively priced international shipments 4. Competence and quality of logistics 5. Ability to track and trace consignments

> 2 Banomyong et al. 2022.

> 3 Arvis et al. 2007; World Bank 2010.

> 4 McKinnon 2015.

1
Table 7. Baseline results: the determinants of female manager and of female entrepreneur

||Panel A: Witho|ut CountryFE<br>|Panel B: Control|for CountryFE<br>|
|---|---|---|---|---|
|Dependent Var.|**Female-Manager**<br>(1)|**Female**<br>**entrepreneur**<br>(2)|**Female-Manager**|**Female**<br>**entrepreneur**|
|**F_c**|0.492***|0.537***|||
||(0.084)|(0.093)|||
|**F_cj**|-0.087|-0.089|-0.023|-0.053|
||(0.073)|(0.074)|(0.057)|(0.059)|
|OwnLargest|0.001|-0.019***|-0.002|-0.019***|
||(0.007)|(0.007)|(0.007)|(0.007)|
|Small3|0.035***|0.041***|0.035***|0.041***|
||(0.005)|(0.004)|(0.005)|(0.004)|
|Large3|-0.004|-0.011**|-0.004|-0.012**|
||(0.006)|(0.005)|(0.006)|(0.005)|
|Age6_10|-0.001|0.001|-0.001|-0.002|
||(0.007)|(0.006)|(0.006)|(0.006)|
|Age10plus|-0.016**|-0.011**|-0.012**|-0.009*|
||(0.007)|(0.006)|(0.006)|(0.005)|
|Corruption|0.000|-0.011|0.036**|0.017|
||(0.013)|(0.013)|(0.015)|(0.012)|
|Overdraft facility|-0.011|-0.008|0.024|0.016|
||(0.014)|(0.012)|(0.018)|(0.014)|
|Trade Credit|-0.078***|-0.041**|-0.044**|-0.004|
||(0.022)|(0.020)|(0.018)|(0.015)|
|Inf. Competition|-0.006|0.007|0.003|0.007|
||(0.013)|(0.011)|(0.010)|(0.009)|
|Outage|-0.021|-0.017|0.019*|0.013|
||(0.014)|(0.012)|(0.011)|(0.009)|
|Web|0.040***|0.020|0.039***|0.014|
||(0.015)|(0.013)|(0.013)|(0.012)|
|Capacity Agglo.|-0.031|-0.047*|0.011|-0.022|
||(0.029)|(0.025)|(0.028)|(0.021)|
|Lngdppc|-0.015*|-0.015*|||
||(0.009)|(0.009)|||
|Education|0.053***|0.039***|||
||(0.013)|(0.012)|||
|Urbanization|0.000|0.000|||
||(0.000)|(0.000)|||
|Country FE|<br>No|<br>No|Yes|Yes|
|Industry, Year FE|Yes|Yes|Yes|Yes|
|Observations|47,993|45,596|50,472|47,702|
|Adjusted R<sup>2</sup>|0.044|0.055|0.074|0.086|

Notes: *, **, *** represent statistical significance at the 10, 5, and 1 percent levels. Heteroskedasticitycorrected standard errors clustered at the country-industry level in columns. OLS are used here. We delete FDI firms with 10% or more foreign ownership.

29
# **Chart 4**

<!-- Start of picture text --> Most Subprime Lending For Refinancing<br>100<br>90<br>80<br>70 Refinance<br>60<br>50<br>40<br>30<br>20<br>Purchase<br>10<br>0<br>1998 1999 2000 2001 2002 2003 2004 2005 2006<br>Source: Inside Mortgage Finance, Center for Responsible Lending<br>Percent of Total Subprime Lending<br><!-- End of picture text -->

**Subprime mortgage lending was made possible by liberalization of the financial system, new credit risk management technology, and policy efforts to reduce racial and economic discrimination in lending.** In 1980, Congress passed the Depository Institutions Deregulation and Monetary Control Act (DIDMCA), the first of a series of laws that liberalized the financial system.. DIDMCA did many things, among them ending usury restrictions on mortgage interest rate (Gramlich, 2007). The second ingredient, credit scoring technology, came into being in the 1990s, as banks became aware of the power of historical statistics in predicting credit performance. The third ingredient was an effort to increase the supply of credit to underserved communities, the Community Reinvestment Act (CRA) of 1977.<sup>16</sup> CRA requires banks to provide credit, including mortgages, to all communities in the geographical areas that they serve, including those that are predominately minority and low income.

**In the 1990s, lenders came to realize that lending in low-income neighborhoods was profitable, so long as they could charge an interest rate that was sufficient to compensate for the risk of lower credit scores.** As CRA required banks to lend more in

> 16 For an overview of CRA, see the Federal Reserve Board’s website: http://www.federalreserve.gov/dcca/cra/

13
rate, an indicator of host country FDI restrictions, measures of host country openness to trade, and the log of host country GDP per capita.<sup>30</sup> The specifications in columns (2) and (3) examine how the effects of IPR reform differ for affiliates of parents that do and do not make extensive use of patents in the U.S. Since these specifications require information on the patent activity of parents, only affiliates of firms that can be linked to firms in the NBER patent database are included in the sample. The high patent use dummy is equal to one for affiliates of parents that, over the four years prior to a particular reform, average at least as many U.S. patent applications as the parent of the median affiliate in the reforming country over the same period. The coefficient on the post reform dummy in column (2) is positive but small and insignificant, while the coefficient on the post reform dummy interacted with the high patent use dummy is positive, large, and significant. These results imply that the increases in technology transfer as measured by royalty payments that occur around the time of IPR reform are concentrated among affiliates of parents that use patents extensively. These affiliates experience an increase in royalty payments of about 29%. This is an annual increase in technology flows from parent to affiliate. Cumulated over several years, it implies a substantial increase in the technology intensity of the affiliates of patent-intensive parents.

Similar results are obtained from the specification presented in column (3) that also includes the log of affiliate sales, the log of parent R&D expenditures, and the log of parent system sales. The first of these is meant to control for the expanding demand for technology of an affiliate as it grows, while the latter variables control for the expanding

> 30  Including measures of U.S. dollar real exchange rates vis-à-vis the host country currency did not qualitatively effect the results reported here.

17
Table A8: Tanzania - Educational attainment of children and their parents by five-year birth cohort

||Average years<br>of schooling|No schooling|Primary|Secondary|Tertiary|
|---|---|---|---|---|---|
|Son||||||
|1941-1945|3.5|36.8|52.8|7.6|2.8|
|1946-1950|4.0|26.9|63.4|7.5|2.2|
|1951-1955|5.2|25.8|54.5|14.6|5.1|
|1956-1960|5.8|19.8|58.5|17.9|3.9|
|1961-1965|6.9|12.0|62.2|22.7|3.0|
|1966-1970|6.6|10.3|68.7|19.4|1.6|
|1971-1975|6.7|8.4|70.9|19.0|1.8|
|1976-1980|6.6|10.2|68.4|19.0|2.4|
|1981-1985|6.9|10.6|63.2|23.8|2.3|
|1986-1990|7.1|10.5|52.8|35.0|1.7|
|Daughter||||||
|1941-1945|1.2|71.4|26.9|1.7|0.0|
|1946-1950|1.5|69.5|29.0|0.0|1.5|
|1951-1955|2.8|53.1|38.1|7.7|1.0|
|1956-1960|3.4|46.3|45.4|7.4|0.9|
|1961-1965|4.8|31.4|55.4|12.5|0.7|
|1966-1970|5.3|23.4|63.8|12.5|0.3|
|1971-1975|5.7|19.7|65.4|15.0|0.0|
|1976-1980|6.1|17.8|64.4|16.1|1.7|
|1981-1985|6.2|17.0|61.5|20.4|1.1|
|1986-1990|6.5|14.3|56.9|28.4|0.4|
|Mother||||||
|1941-1945|0.2|96.2|3.8|0.0|0.0|
|1946-1950|0.2|95.9|4.1|0.0|0.0|
|1951-1955|0.6|88.9|10.6|0.3|0.3|
|1956-1960|0.8|84.9|13.5|1.6|0.0|
|1961-1965|1.1|80.2|19.5|0.4|0.0|
|1966-1970|1.6|73.1|24.4|1.8|0.7|
|1971-1975|2.1|66.6|30.3|2.5|0.5|
|1976-1980|3.2|51.5|43.3|4.2|1.1|
|1981-1985|4.0|42.5|48.0|8.3|1.2|
|1986-1990|4.5|37.2|51.1|10.6|1.1|
|Father||||||
|1941-1945|0.9|85.7|12.9|0.5|1.0|
|1946-1950|0.5|88.1|11.5|0.4|0.0|
|1951-1955|1.3|74.5|24.1|0.9|0.6|
|1956-1960|2.0|68.0|27.9|2.6|1.6|
|1961-1965|2.3|61.1|36.0|2.1|0.8|
|1966-1970|2.7|55.8|38.2|4.7|1.3|
|1971-1975|3.3|48.0|45.5|4.7|1.9|
|1976-1980|4.8|34.9|51.4|9.6|4.1|
|1981-1985|5.2|29.4|55.3|11.6|3.6|
|1986-1990|5.8|25.8|55.5|15.0|3.7|

40
As a result, the Opp-BIA shows the same peculiar progressivity caused by an increasing private contribution among non-vulnerable households and a very low and uniform public transfer.

However, the Opp-BIA shows an even more unequal distribution than traditional BIA. It shows, in fact, that only those most able to pay for public education are likely to attend a public school. Those with a set of circumstances that make them vulnerable are not participating much in the distribution of meager public transfers. By including all children age 6-15 in the distribution of benefits, either attending or not, the Opp-BIA provides a more comprehensive picture than traditional BIA, which only depicts the benefits to those who actually attend school. In doing so, the Opp-BIA analysis presents a bleaker picture of educational spending incidence in Liberia than traditional BIA.

# **[Figures 2a and 2b about here]**

The BIA also provides evidence of the shares of benefits captured by socioeconomic groups. The traditional analysis of shares (Figure 3a) indicates that the pattern of public spending on education in Liberia is clearly not pro-poor. In fact, it follows a very neutral distribution, almost proportional to the share of beneficiaries by quintile (the only exception being a more than proportional concentration of benefits in the third quintile of the distribution of wealth).

Incidence analysis based on opportunities (Figure 3b) shows, once again, a bleaker scenario, in which the share of benefits is below the population share for three out of four vulnerable groups of children (groups 1, 2 and 4). The opposite occurs for three out of four non-vulnerable groups of children, 5, 6 and 8, whose share of benefits exceeds their share of children age 6-15. The Opp-BIA confirms that the distribution of benefits is less pro-poor when analyzed against 23
**Table 1. Objectives of Standards-Related Policies**

|**Agreements**|**Policy objective**|**Compatibility**<br>**and equivalence**|**Right to**<br>**establish level**<br>**of protection **|
|---|---|---|---|
|WTO|Harmonize|No|No|
|_Customs unions_||||
|Andean Community|Harmonize|No|No|
|ASEAN|Harmonize|No|No|
|Central American Common Market|Harmonize|No|No|
|CARICOM|Harmonize|No|No|
|EU|Make compatible/harmonize|Equivalence|No|
|MERCOSUR|Harmonize|No|No|
|_Free trade agreements_||||
|APEC|Make compatible|Yes|Yes|
|NAFTA|Make compatible|Yes|Yes|
|Group of Three (Mexico, Colombia & Venezuela)|Make compatible|Yes|Yes|
|Free Trade Area of the Americas (FTAA)|Make compatible|Yes|Yes|
|Bolivia-Mexico|Make compatible|Yes|No|
|Chile-Mexico|Make compatible|Compatibility|Yes|
|Costa Rica-Mexico|Make compatible|Yes|Yes|
|México-Nicaragua|<br>Make compatible|Yes|Yes|
|<br>Mexico-Northern Triangle|<br>Make compatible|Yes|Yes|
|Central America-Chile|Make compatible|Yes|No|
|Central America-Dominican Republic|Make compatible|Yes|No|
|CARICOM-Dominican Republic|Make compatible|Yes|No|

Note: The Canada-Chile agreement does not address technical barriers to trade. Source: Based on Kotschwar (2001).

The second type of coordinated approach is the RTA approach, which is the approach followed by RTAs to upgrade standards. It seeks to harmonize member countries’ standards regionally either by upgrading standards in one go and equating them to the international standards or by setting regional standards and gradually upgrading them towards the international standard. This approach is characterized by more formal institutions, a higher degree of enforcement and greater trust. Such trust originates from the more frequent interactions between members and the more comprehensive nature of the agreement, which allows for the possibility of cross-issue retaliation. Due to the elimination of intra-regional tariffs, RTA members cannot use tariffs to prevent the entry of a product satisfying the regional standard, hence increasing the certainty that a country’s upgrading efforts will be translated into greater market access.

The RTA approach is increasingly being used by developing countries as a path to upgrading standards – e.g. Andean Community, Mercosur, and ASEAN. It is for this reason that the rest of the paper focuses on this approach.

# **2.2 DIFFERENT APPROACHES TO THE RECOGNITION OF CONFORMITY ASSESSMENT PROCEDURES**

The success of a regional standards harmonization process in terms of greater regional trade and market access crucially depends on a country’s conformity assessment procedures being recognized by the other member countries: recognition of test data, product certification and competence of accredited conformity assessment bodies.

11
**Figure 5: Welfare mobility by gender, and Education levels for period 2010-12**

<!-- Start of picture text --> Female Male No education Primary Middle School Secondary Tertiary<br>Education Education Education<br>Upward Downward Immobility Upward Downward Immobility Upward Downward Immobility Upward Downward Immobility Upward Downward Immobility Upward Downward Immobility Upward Downward Immobility<br><!-- End of picture text -->

**Note:** Upward movers: proportion of poor or vulnerable population in 1<sup>st</sup> period that move up one or two income categories in 2<sup>nd</sup> period. Downward movers: proportion of vulnerable or middleclass population in 1<sup>st</sup> period that move down one or two income categories in 2<sup>nd</sup> period. Vulnerability line is set at US$13.2 dollar –a-day 2011 PPP. **Source:** Own estimations based on GEIH from 2010 to 2012.

**Figure 6: Welfare mobility by gender, and Education levels for period 2012-14**

<!-- Start of picture text --> Female Male No education Primary Middle School Secondary Tertiary<br>Education Education Education<br>Upward Downward Immobility Upward Downward Immobility Upward Downward Immobility Upward Downward Immobility Upward Downward Immobility Upward Downward Immobility Upward Downward Immobility<br><!-- End of picture text -->

**Note:** Upward movers: proportion of poor or vulnerable population in 1<sup>st</sup> period that move up one or two income categories in 2<sup>nd</sup> period. Downward movers: proportion of vulnerable or middleclass population in 1<sup>st</sup> period that move down one or two income categories in 2<sup>nd</sup> period. Vulnerability line is set at US$13.2 dollar –a-day 2011 PPP.
**TABLE 4.1: Household Discouragement of Using a Public Service** Number of public services that each household reported to be discouraged to use (out of a list of 13 public services)

|**Number of Agencies**<br>**where the Household is**<br>**Discouraged**|**Number of**<br>**Households**|**%**|
|---|---|---|
|0|640|37.7%|
|1|628|37.0%|
|2|247|14.6%|
|3|95|5.6%|
|4|42|2.5%|
|5|23|1.4%|
|6|6|0.4%|
|7|6|0.4%|
|8|2|0.1%|
|9|5|0.3%|
|10|2|0.1%|
|11|0|0.0%|
|12|0|0.0%|
|13|0|0.0%|
|**Total households**|**1696**|**100.0%**|

**TABLE 4.2: Number and Percentage of Households Discouraged by Public Agency**

|**Public Agency**|**N**|**%**|
|---|---|---|
|Secretaria Municipal de Transito|53|3.13|
|Direccion Nacional de Immigraciones|76|4.48|
|Notarias Publicas|81|4.78|
|ReNIEC|94|5.54|
|Registros Publicos|112|6.60|
|Policia Nacional de Peru|138|8.14|
|Escuelas o universidades estatales|150|8.84|
|Hospitales públicos y Centros de Salud|154|9.08|
|Banco de la Nacion|159|9.38|
|Area de rentas de su municipalidad|160|9.43|
|Empresa de Agua y desague|193|11.38|
|EsSalut|202|11.91|
|SUNAT|277|16.33|
|**Households discouraged in at least one institution**|**1056**|**62.26**|
|**Households discouraged in at least two institutions**|**428**|**25.24**|

N = Number of households that needed each service and decided not to seek it % = Proportion of households that needed each service and decided not to seek it Total number of households is 1696 EsSalut: Seguredad Social en Salud SUNAT: Superintendencia Nacional de Administración Tributaria ReNIEC: Registro Nacional de Identificación y Estado Civil 27
Table 4: STRUCTURAL CHANGES IN SELECTED DEVELOPING COUNTRY GROUPS C04MMODITY EXPORTS, 1965-1987 (Cont d)

||Tota<br>Value of exp|l<br>E<br>orts (USSmn)|xporter'<br>Prim|s share of all de<br>ary stage|veloped count<br>Processe|ry imports (X)<br>d commodities|<br>Share of pr<br>totat commod|imary stage in<br>ity exports (X)|
|---|---|---|---|---|---|---|---|---|
|Commodity Group/Regional Exporterd|<br>1965|1987|1965|1965-87 chg|1965|1965-87 chg|1965|<br>1965-87 chg|
|PETROLEUM|||||||||
|ALADI|84|8,403|0.5|<br>6.3|1.3|0.7|48|41|
|Andean Group|1,702|8,486|13.2|<br>-8.4|18.8|-12.1|62|-1|
|CARICOM|200|1,063|0.1|<br>0.4|5.6|-4.6|4|47|
|Other America|469|642|0.1|<br>-0.1|13.5|-12.2|2|0|
|Sub-Saharan Africa|238|12,100|2.9|<br>7.9|0.2|0.4|97|1|
|North Africa|1,480|14,676|17.9|<br>-8.2|1.3|6.9|97|-25|
|West Asia|4,939|45,973|56.7|<br>-21.3|11.1|3.8|92|-8|
|ASEAN|278|8,559|2.2|<br>3.0|2.9|3.0|65|1|
|Other Asia and China|8|3,330|--|1.8|0.2|2.6|23|36|
|Developing Oceania|--|--|--|--|--|--|0|2|

a The composition of the developing country groups is as follows: ALADI - Argentina, Brazil, Chile, Mexico, Paraguay, Uruguay.

Andean Group - Bolivia, Colombia, Ecuador, Peru, Venezuela. CARICOM - Bahamas. Barbados, Belize, Guyana, Jamaica, Trinidad and Tobago. Other America - Antigua, Dominica, Grenada, Saint Lucia, Saint Vincent, Bermu.da, Cuba, Dominica, Falktand Islands, French Guiana, Greenland, Guadaloupe, Haiti, Martinique, Antigua, Panama, Surinam.

Sub-Saharan Africa - All countries in Africa except Rep. of South Africa and those listed in North Africa (below). North Africa - Algeria, Egypt, Libya, Morocco, Sudan, Tunisia.

ASEAN - Brunei, Indonesia, Malaysia, Philippines, Singapore, Thailand.

Other Asia and China - Bangladesh, India, Rep. of Korea, Laos, Sri Lanka, Afghanistan, Burma, Democratic Kampuchea, Hong Kong Macau, Maldives, Nepal, Pakistan, China.

West Asia - All Asian developing countries not in ASEAN or other Asia and China. Developing Oceania - American Samoa, Fiji, French Polynesia, Guam, Kiribati, New Caledonia, Papua New Guinea, Samoa, Sotomon Islands, Tonga, Vanatu.
<!-- Start of picture text --> Figure 23. PIMI and Investment<br>PANEL A PANEL B<br>PIMI vs. Public Investment (I/Y) PIMI vs. Private Investment (I/Y)<br>DJI NAM<br>COG<br>ZMB<br>LAO BWA<br>STP ETH MRT<br>BLZ YEMLAOGMBTGOBDISENGABTCDSLESDNSWZTTOGINNGABRB KGZEGYUGAKENAZEBENKHMPAKMOZALBMNEMNGMRTSLVNAMMWIPHLZMBCIVGHATURLSOMKDUKRMDGSRBBGDBLRBFAMLIJORRWAMDABWAKAZARMBOL PER THATUNCOLBRA ZAF BLZ COG YEMSTPGMBTGOBDISENGABTCDSLESDNSWZTTONGABRB DJIKGZEGYUGAKENAZEBENKHMPAKMOZALBMNEETHMNGSLVPHLMWIGHACIVTURLSOMKDUKRMDGSRBBGDBLRBFAMLIJORRWAMDAKAZARMBOL PER THATUNCOLBRA ZAF<br>GIN<br>0 1 2 3 4<br>0 1 2 3 4 PIMI<br>PIMI<br>90% CI Linear Fit SSA Non-SSA<br>90% CI Linear Fit SSA Non-SSA<br>NOTE: PIMI corresponds to average of 2007-2010 and Private Investment (I/Y) to 2014.<br>NOTE: PIMI corresponds to average of 2007-2010 and Public Investment (I/Y) to 2014. Regression line = 0.09 + 0.02x + ε, R-square (%): 4.62<br>Regression line = 0.10 - 0.02x + ε, R-square (%): 6.06<br>.4 .4<br>.3<br>.3<br>.2<br>.2<br>.1<br>Public Investment Private Investment .1<br>0<br>-.1 0<br><!-- End of picture text --> Finally, Figure 24 displays the relationship between PIMI and what we call the efficiency of public investment.<sup>29</sup> There is a positive and significant relationship between public investment management and the efficiency of public investment.<sup>30</sup> Interestingly, Figures 23 and 24 show that countries with better PIMs tend to have lower but more efficient levels of public investment, and they tend to crowd-in private investment. Relative to the international norm, some countries are clearly underperforming —which is the case of Sao Tome and Principe, Senegal, Mozambique, Malawi, among others.

**Figure 24. PIMI and Efficiency of Public Investment**

<!-- Start of picture text --> PIMI vs. Efficiency<br>BLZ COG YEMLAOGMBBDITGOSENGABTCDSLESDNNGA EGYUGAKENAZEKHMMOZALBMNEETHMNGMRTSLVNAMPHLMWIZMBGHATURLSOUKRMKDSRBBGDBLRBFAMLIRWAMDABWAKAZARMBOL PER THATUNCOLBRA ZAF<br>DJI<br>STP<br>0 1 2 3 4<br>PIMI<br>90% CI Linear Fit SSA Non-SSA<br>NOTE: PIMI corresponds to average of 2007-2010 and Efficiency to average of 2010-2013<br>Efficiency variable: growth per capita/rate of investment.<br>Regression line = -0.74 + 0.28x + ε, R-square (%): 5.18<br>2<br>0<br>-2<br>Investment Efficiency -4<br>-6<br><!-- End of picture text -->

> 29 This is a very broad measure computed as the ratio of growth per capita to investment-GDP ratio —as suggested by King and Levine (1993).

> 30 World Bank (2017) also shows that countries with sound PIMIs tend to have strong institutions —that is, greater regulatory quality, improved rule of law and better control of corruption. However, there is a great deal of heterogeneity. Some countries in the region exhibit not only high PIMIs but also high levels of country governance —e.g. South Africa, Rwanda and Botswana. Others show the opposite —e.g. Sudan and Republic of Congo are among the countries with low PIMIs and low levels of governance.

_Infrastructure in Sub-Saharan Africa - 39_