rafmacalaba/datause-encoder-data huggingface dataset:
(Table 4b). Hence choosing to delay their own reforms or reforming less than developed countries, and thereby holding back South-South trade growth, could reduce substantially the potential gains to developing countries.

**_Agriculture is where cuts are needed most._** To realize that potential gain from opening up goods markets, it is in agriculture that by far the greatest cuts in bound tariffs and subsidies are required. This is because of the very high rates of assistance in that sector relative to other sectors. Food and agricultural policies are responsible for more than three-fifths of the global gain foregone because of merchandise trade distortions (column 1 of Table 4a) – despite the fact that agriculture and food processing account for less than 10 percent of world trade and less than 4 percent of global GDP. From the point of view of welfare of developing countries, agriculture is at least as important as it is for the world as a whole: their gains from global agricultural liberalization represent almost two-thirds of their total potential gains, which compares with just one-quarter from textiles and clothing and one-ninth from other merchandise liberalization (Table 4b).

**_Subsidy disciplines are important, but increased market access in agriculture is crucial._** Extremely high applied tariffs on agricultural relative to non-farm products are the major reason for food and agricultural policies contributing 62 percent of the welfare cost of current merchandise trade distortions. Subsidies to farm production and exports are only minor additional contributors: 4 and 1 percentage points respectively, compared with 56 points due to agricultural tariffs.<sup>6</sup> This is even truer for developing countries than for developed ones (compare columns 1 and 2 of Table 5). Disciplining those domestic subsidies and phasing out export subsidies is nonetheless very important, so as to prevent re-instrumentation of assistance from tariffs to domestic subsidies and to bring agriculture into line with non-farm trade in terms of not using export subsidies.

**_In developing countries the poor would gain most from multilateral trade reform._** Full global merchandise trade liberalization would raise real factor returns for the poorest households most. This is implied in Table 6, where for developing countries the

> 6 This result is very similar to that reported from a partial equilibrium study by Hoekman, Ng and Olarreaga (2004). In our initial empirical analysis we also included crude estimates of implicit forms of farm export subsidization such as via food aid, export credits or state trading enterprises, but even that was not enough to raise that export subsidy share above 1 percent.

9
|Tanga|Coastal|5.05|0.385|
|---|---|---|---|
|Shinyanga|Central|5.70|0.364|
|Singida|Central|6.27|0.432|
|Manyara|Central|6.87|0.531|
|Tabora|Central|8.37|0.754|

Source: Author‟s calculations using HBS 2007 data.

An important route out of poverty for maize growers is the option of applying the available factors of production to an activity other than producing maize<sup>21</sup> . With her land, labor, capital and knowledge, a maize grower may choose to grow an alternative high value crop such as sunflowers or other horticultural produce. The decision to do so would entail a shift for the household from producing their staple food to purchasing it. However, in the absence of a secure mechanism for purchasing food within the village, the risk of facing food insecurity may exceed the premium that could be attained from switching to higher value crops. The farmer is effectively locked in a cycle of food production for subsistence that prevents their entry into more profitable markets.

# **6.0 Concluding remarks**

In the post reform period, farm-gate buying has emerged as the most prevalent mechanism for marketing maize in many regions of Tanzania. In this paper, we estimate the transaction costs associated with farm-gate buying, specifically search and information costs, using a measure of household remoteness (distance to market) as a proxy. We showed that the dispersion of maize producers and the farm-gate buying system make transaction costs such as search and village to town transport particularly widen the price gap, causing a downwards pressure on producer prices. We also showed that since non local buyers with limited information about the local market enter and search for maize more actively when maize is abundant, buyer search costs incurred are likely to be higher in the harvest season than in the lean season.

> 21 Maize is an annual crop. Unlike perennial crops such as cashew, coffee or banana, the decision to plant maize must be newly made each year.

22
# **Investing Mineral Wealth in Development Assets: Ghana, Liberia and Sierra Leone**

Daniel Boakye, Sébastien Dessus, Yusuf Foday and Felix Oppong<sup></sup> World Bank, April 2012 Poverty Reduction and Economic Management, Africa JEL classification: L71, L72, Q30 Keywords: Ghana, Liberia, minerals, Sierra Leone, sustainable development, wealth accounting Sector board: Economic Policy

>  Authors are thankful to Kathy Bain, Mamadou Barry, Milan Brahmbhatt, Ishac Diwan, Glenn-Marie Lange, Miria Pigato, Paulo de Sa and Kristina Svenson for their useful comments.
in essence, providing teachers and principals with more information on _how_ to help students stay in school. The second treatment arm adds to the first arm the list of sixth-grade students at high risk of dropping out (component 2), providing school actors more accurate information on _who_ needs the most help. The third treatment arm adds to the first two arms small behavioral nudges (component 3) to try and keep dropout prevention top-of-mind for principals and teachers. A fourth, control arm included schools that received no intervention. This multi-arm design, summarized in Diagram 1, allows us to disentangle the impact of each component on dropout.

**Diagram 1** : four-experimental groups

<!-- Start of picture text --> TREATMENT 1<br>Guide/training<br>1000 schools<br><!-- End of picture text --> <!-- Start of picture text --> TREATMENT 2<br>Guide/training<br>+ List<br>1000 schools<br><!-- End of picture text --> <!-- Start of picture text --> TREATMENT 3<br>Guide/training<br>+ List<br>+ Reminders<br>1000 schools<br><!-- End of picture text --> <!-- Start of picture text --> CONTROL<br>No intervention<br>1000 schools<br><!-- End of picture text -->

# Data

Our main data source is the administrative school data set compiled by SIRE. This data set includes unique student identifiers that has enabled longitudinal tracking of student academic records since 2011. The academic records include basic demographic information and detailed grades earned by subject and year, as well as information on enrollment status, including whether the student dropped out and whether they passed the grade. This data was the main input for estimating the dropout prediction model, as well as the data source for the main outcome of interest (student level dropout).

We also collected data on the quality of implementation of the program and several intermediate (self-reported) outcomes through a series of paper-based and online questionnaires integrated into the SIRE platform. All schools participating in the experiment were requested to complete an baseline questionnaire online, two follow-up online surveys, and a final, paper-based follow-up survey. In addition, the 3,000 treatment schools were also requested to complete an online 14
more than 35 years old, 35 percent of the cost in Table A1.3 was annualized over 35 years. The final results are shown in Table A1.4.

## **Table A1.3: Hydropower parameter assumptions**

|**Category**|**Size (MW)**|**Capex (US$/kW)**|**Refurbishment costs (% of capital costs)**|
|---|---|---|---|
|Small|0–50|4,000|35|
|Medium|50–400|2,000|35|
|Large|>400|1,500|35|

_Source_ : World Bank hydropower specialists.

## **Table A1.4: Country-specific hydropower parameter estimates**

|**Country**|**Weighted average capex (US$/kW)**|**Country**|**Weighted average capex (US$/kW)**|
|---|---|---|---|
|Angola|3,143|Mozambique|3,500|
|Burkina Faso|4,000|Namibia|2,000|
|Burundi|4,000|Nigeria|1,500|
|Congo, Dem. Rep.|2,643|Rwanda|4,000|
|Côte d’Ivoire|3,000|Sierra Leone|4,000|
|Ethiopia|2,727|Sudan|3,071|
|Ghana|1,750|Swaziland|3,333|
|Guinea|3,667|Tanzania|2,571|
|Kenya|3,231|Togo|2,000|
|Lesotho|2,667|Uganda|2,800|
|Malawi|2,889|Zambia|2,083|
|Mali|3,333|Zimbabwe|1,500|

_Source_ : World Bank staff calculations.

# Transmission and distribution costs

T&D costs were estimated based on reported km of T&D lines, excluding LV distribution lines below 1 kV for which no reliable information is available. T&D line data used in the reference year calculations are listed in annex 4. For the purpose of these study, two costs were used: one for lines above 33 kV, and the other for lines between 1 kV and 32 kV. While the cost of building and maintaining T&D infrastructure varies significantly across countries, structure type, voltage, and terrain (desert, flatland, forest, mountains, urban versus rural), it was not possible within the scope of this study to perform a detailed T&D cost analysis in each country. Assumptions, provided by industry specialists, are summarized in Table A1.5.

## **Table A1.5: Assumptions on T&D cost estimates**

|**Component**|**Assumed value (US$/km)**|**Economic life (years)**|
|---|---|---|
|Lines 110kV or above|165,000|50|
|Lines below 110kV down to 66kV|65,000|40|
|Lines below 66 kV down to 1 kV|10,000|30|

_Source_ : World Bank T&D specialists.

For LV distribution lines below 1 kV, costs assumed in setting tariffs in Peru for the five-year period 2013–2017 were used. The regulatory procedure assumed replacement costs of LV networks in six different settings—high-density urban, medium-density urban, low-density urban, peri-urban, 74
- World Bank. 2005b. Technical Annex for a Proposed IDA Grant in the Amount of SDR 20.1 million (US$30 million equivalent) and a Proposed IDA Credit in the Amount of SDR 30.2 million (US$45 million equivalent) to the Democratic Socialist Republic of Sri Lanka for a Tsunami Emergency Recovery Program – Phase II. Washington D.C.

# **Maldives**

Government of Maldives. 2005. The Maldives: One Year after the Tsunami. Male, Maldives.

- Government of Maldives, Ministry of Finance and Treasury. 2005. Tsunami Relief and Reconstruction Fund: Operation Manual. Maldives

- World Bank. 2005c. Technical Annex for a Proposed IDA Grant in the Amount of SDR 3.7 million (US$5.6 million Equivalent) and a Proposed IDA Credit in the Amount of SDR 5.6 million (US$8.4 million Equivalent) to the Republic of Maldives for a Post-Tsunami Recovery and Reconstruction Project. Washington D.C.

- The official website of National Disaster Management Center (NDMC). 2005. (http://www.tsunamimaldives.mv)

# **Pakistan**

- Asian Development Bank and World Bank. 2005. Pakistan 2005 Earthquake: Preliminary Damage and Needs Assessment. Islamabad, Pakistan.

- World Bank. 2005d. Technical Annex for a Proposed Credit in the Amount of SDR 281.8 Million (US$400 Million Equivalent) to the Islamic Republic of Pakistan for an Earthquake Emergency Recovery Credit. Washington D.C.

- United Nations. 2005. Pakistan 2005 Earthquake: Early Recovery Framework. Islamabad, Pakistan.

- World Bank and Asian Development Bank. 2005. Pakistan 2005 Earthquake: Preliminary Damage and Needs Assessment. Islamabad, Pakistan.

# **Grenada**

- Organization of Eastern Caribbean States. 2004. Grenada: Macro Socio-Economic Assessment Caused by Hurricane Ivan. <u>www.oecs.org</u>

- World Bank. 2004a. Grenada Hurricane Ivan: Preliminary Assessment of Damages. Washington D.C.

- World Bank. 2005e. Grenada: A Nation Rebuilding: An Assessment of Reconstruction and Economic Recovery One Year after Hurricane Ivan. Washington D.C.

# **Honduras**

- World Bank. 2004b. Learning Lessons from Disaster Recovery: The Case of Honduras. Washington D.C.

33
(in both countries one-quarter of the resident population are foreign born). The _de facto_ free mobility for third-country nationals once within the borders of the Schengen area (Koikkalainen, 2011) is likely to be affected by similar economic forces but may be harder to study since those border crossings require no documents, unlike for trans-Tasman travel.

The second factor of potential interest is that in 2007 New Zealand opened a much larger seasonal work option for up to 9,000 migrants per year in horticulture, with preference for Pacific Islanders. About 1,500 Tongans come to New Zealand each year under this scheme (Gibson and McKenzie, 2014a), more than six times the number coming via PAC settlement migration. There is no formal interaction between these two migration pathways (seasonal workers are told they have no option to settle), and they select from different parts of the skills distribution in Tonga with the PAC applicant pool positively selected (McKenzie et al, 2010) and the seasonal workers negatively selected by a focus on people not in formal employment (Gibson and McKenzie, 2014b). Moreover, the seasonal workers go to regional New Zealand while Auckland is the first destination for most PAC migrants. Yet our surveys and follow-up qualitative interviews uncovered at least two linkages; since many Tongans come to regional areas on a rolling basis throughout the year for seasonal work, it creates a derived demand for permanent resident Tongans, such as for church pastors, and some of the PAC migrants responded to these opportunities and left Auckland for the regions. Second, information about opportunities in regional centers appears to flow from seasonal workers to settlement migrants, indirectly through family and other contacts in Tonga; this stickiness of information corroborates the findings of McKenzie et al (2013) that migrants may not be well informed about opportunities in destination countries. Other countries also are expanding seasonal and temporary migration, so these indirect linkages may be of interest.

# **References**

24
Our solution is to adopt a difference-in-differences approach. The magnitude of each of the six distinct effects that we describe in our conceptual framework is expected to increase with a sector’s financial vulnerability. This means that we can identify with more certainty the causal impacts of financial development on FDI by focusing on the differential effects of financial development across sectors with different financial vulnerabilities, in a model including an extensive set of time-varying country and industry fixed effects. In some regressions, we also control for the volume of sector-specific activity in source and destination countries to distinguish between the direct and indirect effects of SFD and DFD on FDI. This approach was originally suggested by Rajan and Zingales (1998).<sup>9</sup> Its application to uncover the causal and various effects of SFD and DFD on bilateral FDI is novel.

A second contribution lies in the FDI data that we employ to implement our empirical approach. It is common to use balance of payments (BOP) data to study FDI. These data have major drawbacks, including their inability to reflect the use of external sources of funds in destination countries by multinational enterprises (MNEs)<sup>10</sup> or their poor coverage, especially at the sector-level, of bilateral FDI transactions. Some studies resort to data from one source country to get better proxies (e.g. volume of sales of U.S. foreign affiliates) of MNEs’ activities. However, doubts can be raised about the external validity of their findings while relying on FDI data from one source country complicates the simultaneous investigation of the effects of SFD and DFD on FDI. Finally, using BOP FDI data or indicators of the general activities of MNEs in destination countries does not allow the direct estimation and comparison of the effects of financial development at the extensive and intensive margins of FDI.

We circumvent these issues by using a unique, and under-exploited,<sup>11</sup> database on sector-specific bilateral real greenfield manufacturing FDI covering the entire world during the period 2003-2010. The _fDi Markets_ database records, at the firm-level, the capital investment associated with each greenfield FDI project, without making a distinction between internal and external financing. It also includes the source and destination

> 9See, among others, Beck (2002), Kroszner et al. (2007), Manova et al. (2011), Chor and Manova (2012) or Manova (2013) for an application of this approach in the fields of economic growth or international trade. 10BOP FDI data only capture the proportion of the funding of existing and new foreign affiliates coming from related parties outside the host country, such as an equity investment or a loan by the parent company.

> 11Using “ _fDi Markets_ database” as our search string, we obtained 55 results only in Google Scholar.

3
order to repay the loan even if unprofitable.

Treated firms appear to have higher profits on average than control firms in the last year; but this is not statistically significant, and we lack power to detect moderate positive impacts on profits due to COVID-19 curtailing our sample size. In contrast, treatment-group firms report significantly _lower_ sales and profits in the last 30 days prior to the endline survey, compared to control group firms. The endline survey was conducted in October 2021, which was just after national elections, and a peak in COVID-19 and subsequent restrictions. It may therefore be that surviving firms in the treatment group were particularly exposed to the challenging macroeconomic climate around the time of the survey, although we do not observe a different distribution of treatment versus control-group firms across sectors.

The psychometric-appraised, uncollateralized loans show similarly high repayment rates to regular collateralized loans offered by the MFI prior to the onset of COVID-19. However, psychometric loans disbursed in early 2020 performed worse than psychometric loans disbursed prior to 2020, since they were almost immediately hit by the COVID-19 pandemic.

To our knowledge, our study is the first RCT to evaluate the impact of psychometric credit appraisal for entrepreneurs on not only access to credit and repayment, but also firm — outcomes. Convincing financial institutions to adopt an innovative technology and to experiment with uncollateralized lending, especially in a financial sector where extensive — physical collateralization of loans is the norm is challenging. An additional challenge is convincing financial institutions to randomize the roll-out of a new product at the individual borrower level, implying that they cannot grant loans to half of the borrowers whom they deem creditworthy (and hence would expect to be profitable clients) via the screening process.

Psychometric credit scoring technology has been tested to address the information asymmetries faced by financial institutions particularly in developing countries, and shown to enhance screening of MSMEs that do or do not have other forms of credit history (Arr ́aiz et al., 2017; Alibhai et al., 2018). These studies do not seek to provide evidence of causal impacts of psychometric-appraised lending on downstream firm outcomes. A recent related 4
Pap 44 government from directly or indirecly expropriating the sector's specific assets. For the most part, though, the creation of TOJ was not performed in that way. Instead, a single monopoly company was created, to which a strong monopoly was granted. and ownership was concentrated in a foreign principal." At the time of the creaton of TOJ, it seems that the intention was for GOJ to retain an important share in TOJ. But C&W saw the advantages of expanding its ownership share, and eventually took over 79% of TOJ stock. See Table 4. Yet some moderate safeguards were built Into the privatizabon. since 13% of the govemment' **s** tockna was sold In a way that facilitated acquisition by workers and domestic households. For example, 2% of the outstanding stock (21.1 million shares) was reserved for employees, while 51,000 residential customers of JTC were granted priority for up to 1750 shares each.9 79. A comparison of the price of TOJ stock in relation to the company's revenues offers an indication of whether the 1987 license arrangements were viewed by investors as credible. Figure 23 shows that until April 1991 TOJ shares were being traded at less than 20 US cents. Assuming that the company achieves every year the lower bound alowed by its license (17.5%), we can compute the rate of discoun **t** hat would generate a price equal to approximately US$.20. Comparing that rate of discount with the actual real rate of interest in Jamaica gives us a measure of how much confidence 0 Apat trorn C&W. the lrgea sharholders e the employees of TOJ (owning 2% of outstanding stock) and seven insdiituonal investor, none with a larger stake than 2%. The lrgest individual shareholder is Joseph Mayor Matalonm the son of TOrs Chairman of TOJs Board, and also a member of TOJ Bowd. who owns .5% of the stock See TOJ 1991 Annual Report After legal cost and excluding dividends receied during a period of two and a half yeas, the GOJ received USS 1SSM. which after discounting (at 12%). represents USS130M. which is our valuation of GOJ-s shares in JTC and JAMINTEL as of March 87. _This._ the GOJ seems to hava received a fair value for its es.

' By the time the prvitizAtion was completed. the govemrnment had sold all of its stock, aside from a few nominal shars enabl it to keep a represenuisve on the Board.

' The empbyee shae scherm implied some restridions on resale. Employees purchasing shares through the 'employe share scheme' could resae frly only those shars that were 'prority shures. Discounted shares could be transferred within two ye, o-ly to 'eligible' employees. while tree share were not transfeable during the frst two years. Unsold 'employee share schem' shares -wo to be retained in a p-d to be sold to 'ligible employees' after the dose of the application list See TOJ prospectus. Almost all shares resentd lor thle mployees were sold, either in the first on the second round. TOJs 1991 Annuai Report 1ist 20.341.946 shares being held by employees thus. appWroimately 750.000 sham that were originally reserned for the empblyw remained to be sold to employeos by March 1991.