rafmacalaba/datause-encoder-data huggingface dataset:
Committee (HFC) having signing power on expenditures. Under the new system the availability of drugs improved, drugs were provided at lower prices than in the private sector, and some instances of the HFC holding health staff accountable for misappropriating DRF funds (PATHS 2008).

# _Separation of duties and staff in warehouses_

One South African distribution agency introduced strict separation of duties and staff in their drug warehouses in order to reduce corruption opportunities. Order fulfillment, checking, and transport were assigned to different staff, and staff working in each area only had access to the information they require to do their particular tasks, work in different parts of the warehouses, and even have different break times to reduce the scope for collusion. This approach has successfully created barriers to corruption (Vian 2006).

# _Harnessing technology and transparency for effective inventory management_

Use of technology and integration of information systems for procurement and inventory management can strengthen internal controls. Inventory reporting and ordering from peripheral health facilities can be facilitated by SMS-based (text messaging) reporting forms, which can improve data accuracy and timeliness. Some countries such as Chile have established IT-supported pharmaceuticals management services that use the same types of technology as the private sector to permit more flexible electronic ordering by health facilities and shorter delivery times (Cohen and Montoya 2001).

# _External accountability through citizen participation_

In Bolivia, citizen participation on health boards was found to lead to significant reductions in overpayment for drugs by procurement units (Gray-Molina, Perez de Rada, and Yáñez 2001). “Local Health Directorates”, which included local government officials and citizen representatives, were established to oversee most health care facilities. Price data collected for various supplies found that hospitals that were supervised by active directorates paid less on average than hospitals that had directorates with less active citizen participation. For instance, hospitals that were supervised by active directorates paid 40 percent less on average for 5 percent dextrose solution (Savedoff 2008). In this case, local supervision combined with citizen vigilance was instrumental to better performance. However, in Pakistan, some districts introduced monitoring by citizen committees after decentralization, which improved availability of medicines. However, the initiative occurred in urban locations with relatively well educated citizens, and was not replicated more widely (World Bank 2004b). These voice initiatives may be less effective than models for community participation which give community representatives real power to make decisions and hold providers accountable for their performance as in the case of Nigeria’s health facility committees for Drug Revolving Funds discussed above.

27
# **1. Introduction**

The modal firm size in most developing countries is one worker, consisting of only the owner of the firm. Among the firms that do hire additional workers, most hire fewer than 10. Hsieh and Olken (2014, p.93) report that in India and Indonesia “the fraction of firms with less than 10 workers is almost visually indistinguishable from 100 percent.” Likewise in Nigeria, survey data indicate that 99.6 percent of firms have fewer than 10 workers.<sup>1</sup> This is in sharp contrast to the United States, where the modal manufacturing firm has 45 workers (Hsieh and Klenow, 2014). Are there constrained entrepreneurs in developing countries with the ability to grow a firm beyond this 10-worker threshold? If so, this raises the questions of whether such individuals can be identified in advance, and of whether public policy can help them overcome these constraints to firm growth?

I investigate these questions through the context of an evaluation of the impact of a national business plan competition in Nigeria. The YouWiN! competition was launched in late 2011 by the President of Nigeria, and in its first year attracted almost 24,000 applications aiming to start a new business or expand an existing one. The top 6,000 applications were selected for a 4-day business plan training course, and then 1,200 winners were chosen to receive awards averaging US$50,000 each. 729 of the 1,200 winners were randomly selected from a group of 1,841 semi-finalists, providing experimental variation from US$36 million in grants that enables causal estimation of the program’s impact, as well as a fair and transparent way of deciding among applications. Three annual follow-up surveys enable tracking the trajectory of impacts.

I find that winning this competition has large positive impacts on both applicants looking to start new firms as well as those aiming to expand existing firms. Three years after applying, new firm applicant winners were 37 percentage points more likely than the control group to be operating a business and 23 percentage points more likely to have a firm with 10 or more workers, while existing firm winners were 20 percentage points more likely to have survived, and 21 percentage points more likely to have a firm with 10 or more workers. Together the 1,200 winners are estimated to have generated 7,000 more jobs than the control group, are innovating more, and are earning higher sales and profits. Examining the channels of impact, I find the main effect appears

> 1 Analysis of non-farm enterprises from the 2012/13 Living Standards Measurement Study, kindly provided by Johanne Buba.

2
corn, soybeans, switch grass, corn stover, wheat straw, wood residues, animal manure, and yellow grease. Their study does not incorporate impacts of the changes in the U.S. agricultural sector on international agricultural markets and the resulting adjustments on world prices and land allocation. The more recent work by Chen et al. (2010) endogenizes both yields and gasoline prices using a multi-market equilibrium model of US agriculture, biofuel and gasoline markets. Chen et al. look at the impact of meeting the 36 billion gallons renewable fuel standard (RFS) and associated subsidies with conventional and second-generation biofuels. They compare the welfare and GHG impacts of the RFS to a carbon tax of $30/mt.

Following the extreme price hikes of spring 2008, Collins (2008), Mitchell (2008), and Timmer (2008) provide ad-hoc insightful background analysis of key factors affecting food prices including the role of the emergence of biofuels and the resulting increase in agricultural feedstock demand. These papers do not formally address the global multi-crop land allocation problem.

Rosegrant (2008) uses the IMPACT model to analyze several scenarios departing from the recent (2007) biofuel demand.<sup>1</sup> The IMPACT model is a partial equilibrium (PE) global agricultural model incorporating major agricultural activities for 115 countries. The model incorporates land area and yield responses to prices, an improvement over the FAPRI-based biofuel models. Recent extensions of the IMPACT model account for demand for biofuel and feedstock. Rosegrant suggests that biofuel demand contributed about 30 percent of the price increases during the period covering the early 2000s until 2007. The latter figure refers to the effect on the weighted average grain prices, with the largest effect on corn prices (39 percent) but lesser effects on rice and wheat prices (21 and 22 percent, respectively). Roberts and Schlenker (2010) use a calorie-equivalent approach to aggregate wheat, corn, rice, and soybean production. They estimate aggregate supply and demand for calories and quantify the impact of a biofuel shock equivalent to the current U.S. biofuel mandate on the price of calories from these four crops. They find that the calorie price increases by about 20 percent when accounting for calories saved through dried distillers grains with solubles (DDGS), and 30 percent when abstracting from these by-product calories savings.<sup>2</sup>

> 1 Note there are other references to the same IFPRI analysis which are not cited here.

> 2 For an in-depth review of literature on food supply effects of biofuels, please see Timilsina and Shrestha (2010).

6
- 31 -

# Financing High Growth: The Saving-Investment Challenge.

36. The previous section focused on the consistency of fiscal policy given growth, inflation and sustainable current deficit targets. The relationship between fiscal deficit and growth was not examined directly. How does fiscal policy affect growth? One key link is through the implications of fiscal policy for saving and investmenL Maintaining high growth will require an adequate investment effort. Empirical evidence from Pakistan suggests that the rate of capital accumulation is a major determinant of economic growth. What constitutes an adequate investment effort? Over the past 20 years, Pakistan's average fixed investment rate has been around 17% of GDP. which, given the rate of growth of the economy, yielded a net capital output ratio of 2.75 and a gross capitl-output ratio of 3.14. So, assuming unchanged efficiency, a 6% growth trget will require a gross fixed investment effort of about 19% of GDP p.a., which is higher than the past average rate. However, this ignores an important factor: the need to build up the economic and social infrastructare which appears to have been neglected in the past. Evidence from fast-growing economies show that their investment efforts have been in the range of 24-30% of GDP p.a. Therefore, it is reasonable to expect that Palistan would need to accelerate its investment effort to the 21-22% of GDP range in order to sustain the growth rate of 6% p.a. This corresponds to a gross ICOR of about 3.5.

37. The financig of this investment effort, however, will present a major challenge. Table 18 shows the trend in investment fiance broken down by its components-foreign and national saving. The patter shows a fairly strong dependence on foreign saving-about a quarter of the investment effort is financed through foreign saving. We saw in the previous section that the level of sustainable current account deficits (foreign saving) is around 3% of GDP--much lower than the 5% of the past. At the same time, it was noted above that the fixed investment rate will need to be raised from 17% of GDP to around 21-22%. Adding the two yields a total required increase in national saving effort of 6-7% of GDP. This is an indication of the magnitude of internal adjustment necessary to ensure the consistency of growth with macroeconomic stability.

Table 18. Paldstan - Saving-Investment Balance, 1972-92 (% of GDP)

|____________________<br>||Average<br> 1972-80|Average<br>1980-85|1986|1987|19B8|1989|1990|1991|1992|
|---|---|---|---|---|---|---|---|---|---|
|Invesbflent||||||||||
|- Gross Fixed Ilnvesunent|16.7|16.8|17.0|17.5|16.5|17.3|17.3|17.1|17.2|
|- Change m stocks|4.3|1.8|1.8|1.6|15|1.6|1.6|1.6|1.4|
|- Gross Invesuient|_16A_|18.6|18.8|19.1|18.0|18.9|18.9|18.7|18.6|
|Financed by:||||||||||
|- Foreign Saving|5.5|4.0|3.9|2.2|4.4|4.8|4.2|4.8|3.0|
|- National Saving|10.9|14.6|14.9|16.6|13.6|14.1|14.2|13.9|13.4|

Source: World Tables 1993 and Minislly of Finance
trade (12 percent)—all sectors with low labor productivity, LFS (2018). While a large share of women are salaried workers (73 percent), most do not have a formal job (only 24 percent declare to be enrolled in social security). The average uneducated, employed woman is 41 years old, lives in a household of 4 people where one out of two times the head is a man, has one child, and is slightly more likely to be married than single (40 percent against 34 percent). A larger share of women working in personal services, compared to the average uneducated employed woman, are divorced or widowed, which could signal that these women select into a low-return activity out of necessity.

_Employed women with secondary education._ They are scattered among service sectors— chiefly employed in health and education services (25 percent); wholesale and retail sale (13 percent); government administration (10 percent); finance, insurance, and real estate (10 percent); and the textile industry (10 percent). The share of salaried work is higher among this group (87 percent), as is the share of formal employees (60 percent). It is also noteworthy that the public sector employs a significant portion of this group—25 percent against only 5 percent for the uneducated employed women—and that the remaining 75 percent are employed in the private sector. These women are 36 years old, on average, live in a household with four members, where 70 percent have a male head, and 50 percent are single.

_Employed women with superior education._ They work mostly in three sub-sectors: health and education services (43 percent); finance, insurance, and real estate (17 percent); and public administration (12 percent). They also display the largest share of formal employment (80 percent), as expected. Most of them are salaried (90 percent), and they are almost equally divided between the private (54 percent) and the public sectors (45 percent). Educated women are slightly younger than uneducated women, being on average 37 years old. Almost 17
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_<mark>New legislation to support orderly sovereign debt restructurings.</mark>_ <mark>Legal steps in jurisdictions that govern international bonds (importantly but not exclusively New York and London) or where payments are processed can contribute to more orderly restructuring by promoting a more level playing field between sovereign debtors and creditors. For instance, national legislation can cap the amounts that may be reclaimed from defaulted government bonds bought at a deep discount. In 2010, the United Kingdom enacted such a law for countries taking part in the Heavily Indebted Poor Countries (HIPC) debt relief initiative, while Belgium in 2015 passed the socalled Anti–Vulture Funds Law, which prevents litigious creditors from disrupting payments made via Euroclear. It would also energize legislation to facilitate a majority restructuring, which would allow a sovereign and a qualified majority of creditors to reach an agreement binding on</mark> all creditors subject to the restructurings.

_<mark>More transparency on debt data and debt contracts.</mark>_ <mark>It is of utmost importance that the World Bank, the IMF, and the G20 continue to insist on strengthening the transparency of debt statistics. A new and significant complication in assessing the external indebtedness of many developing economies involves China, which has become the largest bilateral creditor in recent years, and its lending is often shrouded in nondisclosure clauses.</mark><sup>30</sup> <mark>More granular data on private sector creditor exposure may facilitate, in case of debt distress, more expedient creditor-debtor negotiations and allow both creditors and governments to identify which bonds are at risk of holdout or litigation tactics. An encompassing transparency initiative would include, for instance, full disclosure on sovereign bond ownership as well as credit default swaps that shift lender composition overnight. The accounts for the country itself must become more comprehensive, with improved data on domestic debt and debt owed by state-owned enterprises. Accounting for</mark> pension burdens is also increasingly important.

# **V. Final Reflections**

Extremely accommodative global liquidity conditions mitigate some of the risks discussed. Unlike the 1980s and 1930s, real ex-post interest rates are close to historic lows. Furthermore, in the major advanced economies, central banks’ tolerance for higher interest rates may decline

> 30 See Gelpern, Horn, Morris, Parks, and Trebesch (2021), who are the first to analyze the features of China’s overseas lending contracts.

30
# **References**

- Berger, Mark (1989) “Demographic Cycles, Cohort Size, and Earnings,” _Demography_ 26(2):31121.

- Berger, Mark C. (1985) “The Effect of Cohort Size on Earnings Growth: A Reexamination of the Evidence,” _Journal of Political Economy_ , 93(3): 561-73

- Birdsall, Nancy, Allen Kelley, and Steven Sinding (2001) _Population Matters: Demographic Change, Economic Growth, and Poverty in the Developing World_ . Oxford University Press: New York.

- Bloom, David, David Canning, and Pia Malaney (2000) “Population Dynamics and Economic Growth in Asia,” _Population and Development Review_ , Supplement 2000; 26(0): 257-90

- Bloom, David, and David Canning (2001) “Cumulative Causality, Economic Growth, and the Demographic Transition,” in Nancy Birdsall, Allen Kelley, and Steven Sinding, Editors, _Population Matters: Demographic Change, Economic Growth, and Poverty in the Developing World_ . Oxford University Press: New York, 165-97.

- Bloom, David, and Jeffrey Williamson (1998) “Demographic Transitions and Economic Miracles in Emerging Asia,” _World Bank Economic Review_ 12(3): 419-55.

- Coale, Ansley and Edgar Hoover (1958) _Population Growth and Economic Development in LowIncome Countries_ , Princeton, N.J.: Princeton University Press.

- Deaton, Angus, and Christina Paxson (1997) “The Effects of Economic and Population Growth on National Saving and Inequality.” _Demography_ 34(1): 97–114.

- Freeman, Richard B. (1979) “The Effect of Demographic Factors on Age Earnings Profiles,” _Journal of Human Resources_ 14: 289-318.

- Johnson, D. Gale (2000) “Population, Food, and Knowledge,” _American Economic Review_ 90(1): 1-14.

- Korenman, Sanders, and David Neumark (2000) “Cohort Crowding and Youth Labor Markets: A Cross-National Analysis, in David Blanchflower and Richard Freeman, eds. _Youth Employment and Joblessness in Advanced Countries_ .  University of Chicago Press, Chicago: 57-105

- Lam, David (1997) “Demographic Variables and Income Inequality,” in Mark R. Rosenzweig and Oded Stark, editors, _Handbook of Population and Family Economics_ , Volume 1B, North-Holland - Elsevier Science, pp. 1015-1059.

- Lam, David (2005) “How the World Survived the Population Bomb: An Economic Perspective,” in Sisay Asefa, Editor, _The Economics of Sustainable Development_ , W.E. Upjohn Institute for Employment Research, Kalamazoo, MI: pp. 99-132.

- Lam, David, and Leticía Marteleto (2005) “Small Families and Large Cohorts: The Impact of the Demographic Transition on Schooling in Brazil,” in _Changing Transitions to Adulthood in Developing Countries_ , National Academy of Sciences, forthcoming.

25
> - 17 -

industrialization increase the demand, employment opportunity and potential earnings for healthy and educated workers. Economic growth is largely determined by the overall economic policies pursued by the government. Labor market policies also matter: low salaries for teachers, restrictions on labor mobility, and hiring and firing reduce the earning opportunities and incentives to invest in education, causing underutilization of educational facilities and misallocation of labor. At a sectoral policy level, pricing policies for public health and education services can have deleterious effects on social projects and the sectors.'°

# V. Data and Measurement Issues

The data set utilized in our analysis comprises of project evaluation data for 259 Bank-financed social projects prepared by Operation Evaluation Department (OED), and aggregate data reflecting economy-wide policies compiled by WDR 1991. The project data cover 84 countries for the period of 1974-1990, with 34 countries from Africa, 12 from Asia, 17 from EMENA, and 21 from LAC). For each project, information is available on the rating given by OED regarding project performance (satisfactory or unsatisfactory rating) at the time of project evaluation-usually about 12-18 months after the physical completion of project implementation. In addition, the data set includes the amount of the loan, estimated cost and actual cost, and dates of completion. Further, for projects evaluated in 1989 and 1990, the likelihood of longer term project sustainability is also available, although the number of observations is small (N=56). Economy-wide policy indicators include, currency over-evaluation (measured by black market premium, a variable reflecting the deviation between official and black market exchange rates);

> **10** In our communications with Bank experts one telling remar}c: 'when user charges in health are 'too low', for example, not only is financial sustainability of the sector weakened, but a disproportionate share of project benefits may be captured by those not in the target group; unnecessary consumption may take place because there is little or no price deterrent; and an ethos of cost-consciousness and cost-contaimment is unlikely to emerge among managers in health institutions." (R. Hecht)
**Table 4. Impacts on sectoral outputs (% change from the base case)**

||Pub|lic investm|ent|Equal ca|sh transfer|to HH|Progressi|ve cash tra<br>HH|nsfer to|Corpora|te income|tax cuts|
|---|---|---|---|---|---|---|---|---|---|---|---|---|
||Subsidy|CTAX|Both|Subsidy|CTAX|Both|Subsidy|CTAX|Both|Subsidy|CTAX|Both|
|Agriculture|-0.83|-0.72|-1.50|1.09|1.38|2.51|1.16|1.43|2.50|0.07|0.13|0.10|
|Oil|-9.50|-8.47|-16.06|-8.40|-7.24|-13.96|-8.36|-7.23|-14.02|-9.22|-8.07|-15.54|
|Natural Gas|1.15|-8.20|-7.25|2.65|-6.77|-4.48|2.66|-6.76|-4.44|1.22|-7.69|-6.70|
|Other mining|2.57|2.73|4.62|-0.30|-0.37|-1.20|-0.33|-0.37|-1.10|1.91|1.99|3.42|
|Food, beverage, tobacco|-1.07|-1.00|-2.00|1.03|1.29|2.37|1.09|1.33|2.37|0.60|0.66|1.18|
|Textile|-0.54|-0.57|-1.07|1.39|1.55|3.00|1.45|1.57|2.90|5.66|5.62|11.24|
|Petroleum products|-9.44|-8.35|-15.90|-8.33|-7.12|-13.80|-8.30|-7.11|-13.85|-9.21|-7.99|-15.45|
|Chemicals|-0.26|-0.74|-1.06|0.26|-0.13|0.10|0.30|-0.14|-0.03|0.86|0.25|0.83|
|Non-metals|5.82|6.70|11.27|-0.29|0.03|-1.34|-0.40|0.02|-0.99|3.63|4.46|7.40|
|Metals|5.12|6.11|10.02|-1.17|-0.61|-2.66|-1.17|-0.62|-2.64|3.85|4.59|7.52|
|Machinery|6.71|7.82|13.15|-0.49|0.10|-1.50|-0.52|0.09|-1.41|8.66|9.63|17.43|
|Other manufacturing|2.21|2.37|4.10|0.77|0.85|1.23|0.80|0.87|1.23|2.33|2.34|4.18|
|Electricity|-3.50|-4.62|-7.65|-2.08|-3.10|-4.85|-2.06|-3.09|-4.87|-5.22|-4.26|-9.00|
|Construction|10.84|12.48|21.20|-0.08|0.57|-1.38|-0.26|0.55|-0.77|4.71|6.19|9.71|
|Trade|-0.55|-0.45|-1.08|-0.87|-0.90|-1.86|-1.01|-0.95|-1.70|0.37|0.67|1.24|
|Transport|-2.24|-2.15|-4.13|-0.61|-0.36|-0.76|-0.53|-0.31|-0.77|-1.42|-1.39|-2.73|
|Commercial services|-0.01|0.07|-0.02|0.70|0.83|1.46|0.68|0.81|1.44|0.59|0.68|1.16|
|Public services|-0.45|-0.46|-0.76|0.45|0.61|1.23|0.51|0.59|0.92|0.15|-0.04|-0.02|
|Other services|-0.63|-0.56|-1.11|0.66|0.88|1.63|0.69|0.87|1.47|1.68|1.70|3.28|