rafmacalaba/datause-encoder-data huggingface dataset:
KENYA’S INFRASTRUCTURE: A CONTINENTAL PERSPECTIVE

# How much more can be done within the existing resource envelope?

About $230 million of additional resources could be recovered each year by improving efficiency (table 12). The three largest potential sources of efficiency gains are reducing distribution losses, improving cost recovery, and raising the capital-budget execution rate (that is, the share of budgeted funds that is actually spent). The two sectors that present the largest potential efficiency dividends are power and WSS.

**Table 12. Potential gains from greater operational efficiency**

||ICT|Irrigation|Power<br>Transport|WSS|Total|
|---|---|---|---|---|---|
|Under-recovery of costs|—|—|8<br>25|35|69|
|Overstaffing|n.a.|—|31<br>—|n.a.|31|
|Distribution losses|—|—|54<br>—|17|71|
|Undercollection|—|—|0<br>0|7|7|
|Undermaintenance|—|n.a.|n.a.<br>0|n.a.|0|
|Low budget execution|0|0|15<br>19|18|52|
|Total|0|0|109<br>44|77|230|

Source: Derived from Foster and Briceño-Garmendia 2009. — = not applicable n.a. = not available Undercharging for water and power services costs Kenya about $70 million each year. In the water sector, it is estimated that the average total cost of producing utility water is $0.99 per cubic meter, while the average effective tariff is only $0.58, which covers only operating and maintenance costs. As a result, the main utilities in the sector cover only 58 percent of their costs, leaving capital investment unfunded. The associated financial burden is approximately 0.2 percent of GDP (figure 15). In the power sector, the burden of underpricing was removed in 2008, when tariffs were raised to $0.20 per kilowatt-hour. Looking ahead to the future, the long-run marginal cost of power in Kenya could fall below that level once planned coal and geothermal plants are in place and power-trading agreements materialize. Those developments should lower prices to end users as well as easing the pressure on national budgets.

Because of inequitable access to power and water services in Kenya, subsidized tariffs are highly regressive. Kenyans with connections to the piped water network have the full capital costs of their service subsidized (implicitly or explicitly) by the state. Given that 69.4 percent of households with access to piped water are in the top quintile of the income distribution, that subsidy policy is very regressive. Although power tariffs are now aligned with costs, when they were subsidized they were similarly regressive, as 87.6 percent of households with access to the power grid are in the richest quintile (figure 16).

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payments data are distinguished as either merchandise or nonmerchandise transactions, not as either goods or services.

1.7 Trade documents filed with customs offices and central bank records of foreign exchange transactions, are the two main sources of national data on merchandise trade. Customs data are generally more precise because they capture all cross-border merchandise movements, including those between head offices and subsidiaries of multinational corporations for which there are no other sources of information. Since the international agreements on harmonizing merchandise trade nomenclature were enacted (the Customs Cooperation Council Nomenclature, the Standard International Trade Code, and more recently the Harmonized System Nomenclature), customs data are internationally comparable for several thousand items.

1.8 Countries must estimate the value of nonmerchandise Current Account transactions using either foreign exchange records or surveys of business establishments. Equivalent customs data cannot be gathered because services and other nonmerchandise transactions are not physically observable. As a result, the figures recorded in balance of payments statements are often underestimated.

# B. **Equivalence Between Excess Transport Costs and Tariffs**

1.9 The distortions arising from transport costs, tariff barriers, and technology lags must be expressed in like terms so that they can be compared and their combined impact on the balance of payments measured. The ad valorem rate of protection typically expressed in nominal terms, is the most appropriate common denominator. But the effective rate of protection would be a better measure unlike the nominal rate of protection, the effective rate of protection for a final good takes into account (using the input-output tables), the rates of protection of the intermediate goods used in production (see Yeats 1980). Transport services are intermediate inputs, and their excess costs contribute to the nominal rate of protection of intermediate products. In industrial countries effective protection rates are roughly twice as large as nominal rates.

# **C. The C.l.F./F.O.B. Approach and its Limitations**

1.10 An ad valorem measurement of the cost of international transport and insurance can be obtained by comparing the c.i.f. and f.o.b. values of trade. The volume of exports and their f.o.b. value are listed in the exporting country's statistics. The same product is entered in the partner's import statistics in volume and in c.i.f. value. The difference between the c.i.f. and f.o.b. values as a fraction of the f.o.b. value, gives an indication of the ad valorem freight and insurance costs (Table 1.1). The bi-directional approach makes it possible to estimate, by country and product, comparable indicators of transport costs, referred to as freight factors.
_Table 6: Delivery Aspect of the DTS Programs_

|Implementation Aspects|Description|Average<br>Among DTS<br>Trainees|
|---|---|---|
|DTS implementation scheme (%)|Block release (scheme=1)|91.0|
||Day release (scheme=2)|9.0|
||Adequate guidance from supervisors|23.0|
|How work processes were learned|Learned from peers|5.0|
|during OJT (%)|Learned by doing it yourself|6.0|
||All above|48.0|
||Higher level (NC2–NC5)|71.0|
|Certification upon graduation (%)|Lower level (NC1 or COC)|6.0|
||No certificate|27.0|
|Atl lth f iTVI tii|Total number of weeks spent in school/TVIs|26.7|
|cua eng or n- ranng<br>and in-lant trainin|Total number of weeks spent in company/plant|40.7|
|p g|Weekly total number of hours spent for OJT|45.2|

Source: _DTS Tracking Survey Data, 2015, World Bank._ Note: _a. Block release refers to a schedule where students/trainees complete 40 percent of their training full-time in a TVI, then complete the remaining 60 percent of their training full-time in a plant. (TESDA Circular No. 31 s.2012)_ _b. Day release refers to a schedule where trainees spend two days per week in a school and the remaining work days in a plant. (TESDA Circular No. 31 s.2012)_ 31
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**Table 7:** **_Production and Average Yield_** _of_ **_Cotton in the World_**

|Country|Production<br>(million ton)|Area<br>(thousand ha)|Yield<br>(kg / ha)|
|---|---|---|---|
|Israel|27|16|1,697|
|Australia|329|260|1,266|
|Turkey|580|559|1,039|
|China|3,739|4,985|750|
|USA|3,515|5,173|679|
|Egypt|411|371|538|
|Pakistan|1,312|2,804|468|
|**India**|**2,095**|**7,315**|**286**|
|**World Total**|**16,673**|**30,527**|**546**|

Source: ICAC (1994) Many economists (for example, G(ulati and Sharma, 1994) argue that liberalizing cotton exports will help Indian farmers improve agriculture raanagement, which will, in turn, solve part of these problems. Some argue that if cotton yields do not improve, India may even face a shortage of cotton in the future. India has by far the largest acreage of cotton cultivation in the world and is the only country to produce a full range of varieties of nearly all staple: lengths. It is unfortunate that India is not maximizing their comparative advantage of cotton production.

# _Inefficient Public_ **_Procurement_** _of_ **_Cotton_**

WAhile cotton yields have been stagnant, the loss of cotton by public cotton traders, particularly state traders, has further reduced the level of available cotton for domestic spinning mills in India. Often, public traders fix their purchasing price when the market is at its peak, sell it in the lean period, and end up with losses. Also, in seasons when the quality of cotton is poorer, they cannot find suitable buyers and build up large unsold stocks, which are eventually wasted. For example, Bhala (1995) pointed out that a significant amount of cotton was lost by the MAFED, which has monopolized cotton trading in Maharashtra for over two decades.

The incompetence of the public traders is even more apparent in the export market than in the domestic market. Finding the right quality and variety on time, keeping buyer connections, establishing a reputation are all essential factors to successful trading. Many public traders are not professionally trained, and cannot find suitable overseas buyers. Therefore, although most of the cotton export quota is allocated to public traders, private traders often act as middlemen on behalf of the public exporters. While the public 18
# **References:**

- Aghion, Philippe, and Peter W. Howitt. 2008. _The Economics of Growth_ . Cambridge (MA): MIT press.

- Almond, Douglas, and Janet Currie. 2011. Human capital development before age five. In Orley Ashenfelter and David Card (eds): _Handbook of Labor Economics, Volume 4_ : 13151486, Amsterdam: Elsevier.

- Akbar, Prottoy A., Victor Couture, Gilles Duranton, Ejaz Ghani, and Adam Storeygard. 2017. Accessibility and Mobility in Urban India. World Bank Working Paper, forthcoming.

- Akbar, Prottoy A. and Gilles Duranton. 2017. Measuring the Cost of Congestion in a Highly Congested City: Bogota. Mimeographed, University of Pennsylvania.

- Angel, Shlomo, Jason Parent, Daniel L. Civco, and Alejandro M. Blei. 2012. _Atlas of Urban Expansion_ . Cambridge, MA: Lincoln Institute of Land Policy.

- Arnott, Richard. 2004. Does the Henry George Theorem Provide a Practical Guide to Optimal City Size? _American Journal of Economics and Sociology_ 63(5), 1057-1090.

- Arnott, Richard, André De Palma, and Robin Lindsey. 1993. A Structural Model of Peak-Period Congestion: A Traffic Bottleneck with Elastic Demand. _American Economic Review_ 83(1): 161-179.

- Ashraf, Nava, Edward Glaeser, Abraham Holland, and Bryce Millet Steinberg. 2015. Water, Health, and Wealth. Work in progress, Harvard University.

- Azariadis, Costas, and Allan Drazen. 1990. Threshold externalities in economic development. _Quarterly Journal of Economics_ 105(2): 501-526.

- Baldwin, Richard, Rikard Forslid, Philippe Martin, and Frédéric Robert-Nicoud. 2005. Economic geography and public policy. Princeton (NJ): Princeton University Press.

- Berg, Claudia, Uwe Deichmann, Yishen Lieu, and Harris Selod. 2017.  Transport Policies and Development. _Journal of Development Studies_ 53(4): 465-480.

- Blanchard, Olivier J. and Lawrence F. Katz. 1992. Regional evolutions. _Brookings Papers on Economic Activity_ : 23, 1–76.

- Bleakley, Hoyt and Jeffrey Lin. 2012. Portage and path dependence. _Quarterly Journal of Economics_ 127(2): 587–644.

- Bloom, Nicholas, Benn Eifert, Aprajit Mahajan, David McKenzie, and John Roberts. 2013. Does management matter? Evidence from India. _Quarterly Journal of Economics_ 128(1): 1–51.

- Buckley, Robert, Achilles Kallergis, and Laura Wainer. 2015. _The Housing Challenge: Avoiding the Ozymandias Syndrome_ . New York: Rockefeller Foundation and New School.

- Card, David, Jochen Kluve, and Andrea Weber. 2010. Active labour market policy evaluations: A meta‐analysis. _Economic Journal_ 120(548), F452-F477.

- Carrillo, Paul E., Arun S. Malik and Yiseon Yoo. 2016.  Driving Restrictions that Work? Quito's Pico y Placa Program. _Canadian Journal of Economics_ , 49(4), 1536-1568.

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# Long-Term Impacts of Alternative Approaches to Increase Schooling:

**JEL codes:** C93 Field Experiments; I21 Analysis of Education; I22 Educational Finance; I25 Education and Economic Development; I28 Government Policy; O12 Microeconomic Analyses of Economic Development. **Keywords:** Cambodia; education; long-term effects; merit-based targeting; poverty-based targeting; randomization; scholarships. _∗_ We are grateful for financial support from the World Bank’s Strategic Research Program Trust Fund. We thank Simeth Beng, Tsuyoshi Fukao, and staff of the Ministry of Education of the Royal Government of Cambodia for input and assistance at various stages of this project. Alice Danon provided outstanding research assistance. For helpful comments, we thank Maria Bertling, Theresa Betancourt, Monnica Chan, Olivia Chi, Mark Chin, Jishnu Das, David Deming, Alejandro Ganimian, Sibylla Leon Guerrero, Rema Hanna, Andrew Ho, Whitney Kozakowski, Guilherme Lichand, Sophie Litschwartz, Dana McCoy, Jonathan Mijs, Karthik Muralidharan, Charles Nelson, Gautam Rao, Margaret Sheridan, Abhijeet Singh, and Martin West. The usual disclaimers apply. The findings, interpretations, and conclusions expressed in this paper are those of the authors and do not necessarily represent the views of the World Bank, its Executive Directors, or the governments they represent. Harvard University IRB Protocol Title “From Schooling to Young Adulthood”, Number IRB16-1518.

> _†_ Associate Professor of Education and Economics, Harvard University, Graduate School of Education. E-mail: `felipe_barrera-osorio@gse.harvard.edu` .

> _‡_ PhD Candidate, Harvard University, Graduate School of Education. E-mail: `adebarros@g. harvard.edu` .

> §Lead Economist, World Bank. E-mail: `dfilmer@worldbank.org` .

Evidence from a Experimental Scholarship Program in Cambodia<sup>_∗_</sup> Felipe Barrera-Osorio<sup>_†_</sup> Andreas de Barros<sup>_‡_</sup> Deon Filmer<sup>§</sup> **JEL codes:** C93 Field Experiments; I21 Analysis of Education; I22 Educational I25 Education and Economic Development; I28 Government Policy; Analyses of Economic Development. **Keywords:** Cambodia; education; long-term effects; merit-based targeting; randomization; scholarships. We are grateful for financial support from the World Bank’s Strategic Research Program We thank Simeth Beng, Tsuyoshi Fukao, and staff of the Ministry of Education of Government of Cambodia for input and assistance at various stages of this project. provided outstanding research assistance. For helpful comments, we thank Maria Monnica Chan, Olivia Chi, Mark Chin, Jishnu Das, David Deming, Sibylla Leon Guerrero, Rema Hanna, Andrew Ho, Whitney Kozakowski, Sophie Litschwartz, Dana McCoy, Jonathan Mijs, Karthik Muralidharan, Charles Nelson, Rao, Margaret Sheridan, Abhijeet Singh, and Martin West. The usual disclaimers The findings, interpretations, and conclusions expressed in this paper are those of the authors and do necessarily represent the views of the World Bank, its Executive Directors, or the governments represent. Harvard University IRB Protocol Title “From Schooling to Young Adulthood”, IRB16-1518.
**-7-**

to compile nontariff barrier inventories. 6/ In this study we utilize summary statistics drawn from the GATT, UNCTAD, ICC and Commerce Department inventories by Walter (1969) (1972) to study longer-term trends in the level and pattern of nontariff measure use. Walter established a useful classification scheme for NTBs, based on the normal "intent" of these measures 'see Table 1), and published NTB two-digit SITC frequency and coverage indices for years around 1966 in 18 OECD countries. Since the methodology and data sources used in preparing the 1966 data were very similar to that employed in the UNCTAD Data Base the two sources can be linked to empirically assess changes in the frequency and coverage or nontariff measures. 7/

- 6/ The data on nontariff barrier use in the 1960s was drawr. from detailed surveys of NTBs made by a number of international and U-S. government organizations. The results of these surveys have been published in International Chamber of Commerce (1969), U.S. Office of the Special Representative for Trade Negotiations (1968), U.S. Bureau of International Comerce (1968), UNCTAD (1969) (1970) and a special GATT inventory of nontariff barriers compiled from submissions by each member country regarding the nontariff barriers facing its exporters. Given the extent of the surveys, and the amount of detail published on their findings, the information on nontariff barrier use in the 1960s appears to be as comprehensive as that compiled by UNCTAD for the 1980s. UNCTAD published detailed information on entries in its 1960s inventory. See UNCTAD (1973) (1974) for an example which illustrates how comprehensive the earlier statistics were.

- 7/ Several differences should be noted in the two data sources. First, Walter was unable to compile data on NTBs facing Finland and Ireland's agricultural imports, while New Zealand's import licensing requirements for industrial goods were not included in his inventory. These measures are included in the UNCTAD Data Base. Second, Walter excluded "voluntary" export restraint arrangements from his records while VERs are included in the Data Base. It shoutld be noted, however, that VERs did not appear to be used widely in the 1960s so this should not have an important influence on the comparisons. Finally, trade restrictions for Greece were not tabulated in the 1966 inventories but are included in the UNCTAD Data Base for 1986. Both inventories have been compiled from official government or national sources. See Walter (1972, pp. 339-340) and UNCTAD (1983) for a listing. An additional problem arises with the Japanese data. In 1984, the Japanese data in the UNCTAD Data Base were substantially revised to include material published only in Japanese. This resulted in a doubling of the number of recorded NTBs. If Walter was unable to include Japanese language material, the 1966 numbers would be understated.
results offer a nuanced perspective on the impact on export dynamics: domestic banks appear to promote the expansion of export especially by reducing the exit rate of exporters, rather than promoting the entry of new businesses into export activities. That is, their boost to the size of the export sector comes hand in hand with a reduction in the dynamism of the export sector. This is not necessarily a symptom of inefficient behavior, as banks might perform a buffering role for exporters vis-`a-vis unforeseen contingencies. However, more worryingly, we find that in none of the circumstances in which the buffering role of banks would be more valuable, their chilling effect on exporters’ exit is more pronounced. By contrast, this effect is stronger in countries characterized by lower independence of bank managers from external pressures and poorer bank supervisory quality. These results are mostly attributable to domestic banks in middle- and low-income countries, while the presence of foreign banks is conducive to a significantly higher dynamism of the export sector.

The paper can yield relevant policy insights. The first regards the structure of the financial system: complementing domestic banking development with the development of capital markets and with the openness of the banking system to foreign financial institutions can have first-order effects on the dynamism of firms’ international activities. The second implication regards the importance of complementing banking development with an improvement of the incentives of bank managers that mitigates their inclination to protect incumbent exporters. These two types of financial reforms could reinforce each other, as they both would tend to reduce distortions in the allocation of financial resources in the export sector.

# **References**

Abiad, A., G. Dell’Ariccia, and G. B. Li (2011). Creditless recoveries. IMF Working Papers 11/58, International Monetary Fund.

Abiad, A., P. Mishra, and P. Topalova (2014). How does trade evolve in the aftermath of financial crises? IMF Economic Review 62(2), 213–247.

Abiad, A., E. Detragiache, and T. Tressel (2008). A new database of financial reforms. IMF Working Papers 08/266, International Monetary Fund.

Ahn, J.B. (2011). A theory of domestic and international trade finance. IMF Working Paper 11/262.

Allen, F. and D. Gale (2001). Comparing Financial Systems. MIT Press.

Amiti, M. and D. Weinstein (2011). Exports and financial shocks. Quarterly Journal of Economics 126(4), 1841–1877.

Araujo, L., G. Mion, and E. Ornelas (2016). Institutions and export dynamics. Journal of International Economics 98, 2-20.

22
- In the case of market capitalization, the link with economic development was not initially significant, thus even low income countries could have large capital markets. However, this is no longer the case.

**Figure 4: Changes in Income Elasticities over Time for Several Financial System Components***

<!-- Start of picture text --> 0.7<br>0.5<br>Private credit<br>Deposits<br>0.3<br>Market cap.<br>Turnover<br>0.1 NIM<br>-0.1<br>-0.3<br>1980 1985 1990 1995 2000 2005<br><!-- End of picture text -->

*** Based on coefficients of pooled OLS regressions for the period 1980-2006 with the logarithm of X as a dependent variable. The independent variables include the logarithms of GDP per capita, population size and density, the value of fuel exports to GDP, the poverty gap, and a dummy that indicates whether the country is an offshore financial center or not (see http://www.imf.org/external/np/ofca/ofca.asp). To allow for time-varying coefficients of these indicators, two interactions are added for each of these indicators:**

**one interaction with a time indicator (where 1980 is t=0) and another with the square of the time indicator. The time indicator and its square are also both included as independent variables on their own.**

# **IV. LOOKING AHEAD**

Important gaps in the currently available cross-country information on financial sector development will need to be filled:

- While information on _banks_ is far more thorough than for other sectors (thanks in large part to the Fund’s IFS), it is nonetheless far from complete, even for very basic bank size indicators. In particular, as regards _access and reach_ , efforts are also needed to collect more systematically data on accounts originating from the variety of non-bank institutions that cater more directly to the lower income groups (coops, savings and loans, postal banks, microfinance institutions, etc.).<sup>40</sup> Further efforts are also needed to perfect the links between survey data on the percentage of households with access to a financial account and institutional data on the number of accounts.<sup>41</sup> Filling up this gap is particularly important in view

> 40 Christen et al. (2004) and Peachey and Roe (2006) have already made important contributions in this direction.

> 41 Honohan (2006) provides a key first step in this direction.

33