rafmacalaba/datause-encoder-data huggingface dataset:
# I. INTRODUCTION

Juloo, wrope" to a Mandinko, means several things at once. It can refer to a small-scale trader, or to credit or debt. Every Mar.dinko knows the meanings are related. Traders are also lenders, and their loans, while sometimes<sup>useful</sup> like a rope ladder, also tie down a farmer like a rope around the neck.<sup>When</sup> rural people in The Gambia speak of iuloo, in any of these uses, they consciously or unconsciously connote slavery. The Mandinko and other peoples of this small and impoverished West African river nation, an ancient trade route winding thinly through southern Senegal, have had occasion in history to learn quite a bit about ropes and involuntary servitude, and about debt. The linked images and overtones are not empty of emotion.

In recent decades, international interventions in Gambian agriculture have been based mainly on credit. Each year, with mixed motives, new committees convene in Banjul, the capital, to seek new ways of extending loans into the countryside: representatives of multinational and bilateral agencies, governmental bodies, private voluntary organizations--lending for men or women, for groups or individuals, for cash crops or food crops. The composite record of the lending projects has been disappointing for farmers and nearly all others concerned. Particularly unimpressive have been the records of the cooperatives, which now dominate the rural credit picture with their inefficient yet now rather indispensable operations, and the commercial banks, which deal with a'most no
their traditional enforcement strategies and find it difficult to optimally monitor compliance with self-reported income taxes.

In this context, technology may be instrumental in boosting the performance of income tax collection in many ways. On the taxpayer side, technology can be used to simplify tax registration processes, such as the creation of one-stop shops for firms. In addition, taxpayer e-services such as e-filing and e-payment facilities, as well as web tax portals, can significantly ease the burden to comply, increase transparency and predictability of taxes, and reduce scope for corruption, factors which may increase willingness to comply. On the tax administration side, IT solutions such as Electronic Fiscal Devices, can provide crucial data on sales which can then be cross-checked automatically with self-reported income tax declarations. Similarly, the tax administration can obtain and crosscheck data from thirdparty reporting such as VAT data from clients and vendors and rental income withholding with self-reported income. Against these promises, the existing evidence is, once again, rather mixed, and we summarize it below.

# **5.1 Pay As You Earn**

In theory, given the at-source deduction of PAYE tax by the employer, there is less scope for evasion with PAYE compared to self-declared income (Kleven et al., 2011), however, there is very limited empirical evidence from Africa on this. Rather, the existing descriptive evidence suggests that large gaps persist in the quality of PAYE returns data, thus undermining the capacity of revenue authorities to make best use of it and opening loopholes for tax evasion.

One issue is lack of proper tax identification of individuals. Descriptive evidence from both Uganda (Mayega et al., 2021) and Ethiopia (Mascagni and Mengistu, 2019) reveals that tax identification numbers (TINs) for employees are largely missing or incorrect in employers’ PAYE returns. This means that the tax authority is unable to track payments by individuals over time and match individuals’ records with other databases. Reporting aggregated PAYE taxes at the employer level and not linking to individuals also creates an opportunity for 20
Table A16. <u>GVCs and Full-Time Female Non-Production Workers – IV Approach</u>

||(a) All r<br>|egions<br>|(b) MEN<br>|A region<br>|
|---|---|---|---|---|
|Variables|GVC1|GVC4|GVC1|GVC4|
|Ln(Age)|0.0986***|0.111***|0.0659***|0.107***|
||(0.00726)|(0.00851)|(0.0179)|(0.0266)|
|Ln(Gov own.)|0.0708***|0.0713***|0.155***|0.0923**|
||(0.0106)|(0.0123)|(0.0315)|(0.0461)|
|Main city|0.0986***|0.105***|0.117***|0.110***|
||(0.0102)|(0.0117)|(0.0243)|(0.0317)|
|Medium|0.589***|0.590***|0.431***|0.457***|
||(0.0134)|(0.0160)|(0.0319)|(0.0330)|
|Large|1.689***|1.542***|1.475***|1.334***|
||(0.0284)|(0.0627)|(0.0754)|(0.118)|
|GVCs|0.456***|3.151***|0.524***|5.147***|
||(0.0694)|(0.607)|(0.166)|(1.599)|
|Country dummies|Yes|Yes|Yes|Yes|
|Year dummies|Yes|Yes|Yes|Yes|
|Sector dummies|Yes|Yes|Yes|Yes|
|Observations|40,750|40,750|6,797|6,797|

Standard errors in parentheses, *** p<0.01, ** p<0.05, * p<0.1 Note: The intercept is included.

43
transition toward an open and market oriented economy. They are having to cope with the general decline of state-owned sectors (see Table 3) and, in some cases, the shifting of manufacturing enterprises to suburbs. The two cities also confront a fast increasing urban population without sufficient infrastructure to host such growth.

Economic structures have changed dramatically in Beijing and Shanghai, with the proportion of the service sector in the total economy growing rapidly in the 1990s. However, due to the policy bias in the past, the development of service sectors, especially advanced valueadding business services, still lags behind overall urban growth. In order to compete with cities in the hinterland, Beijing and Shanghai are having to upgrade their industries and seek to become regional hubs in the global economy. Both the administrations of Beijing and Shanghai are aware of the urgent need for innovation capability to sustain urban growth and retain competitive advantages.

**Table 2: The industrial structures of Beijing and Shanghai in selected years, 1978-2001**

|%|1978|1990|1995|2000|2001|
|---|---|---|---|---|---|
|**_Beijing_**<br>||||||
|_Employees_||||||
|Primary sector|28.3|14.5|10.6|11.8|11.3|
|Secondary sector|40.1|44.9|40.7|33.6|34.3|
|Tertiary sector|31.6|40.6|48.6|54.6|54.3|
|_GDP_||||||
|Primary sector|5.2|8.7|5.8|3.6|3.3|
|Secondary sector|71.1|52.4|44|38.1|36.2|
|Tertiary sector|23.7|38.9|50.2|58.3|60.5|
|_Shanghai_||||||
|_Employees_||||||
|Primary sector|34.4|11.1|9.8|10.8|11.6|
|Secondary sector|44.0|59.3|54.5|44.3|41.2|
|Tertiary sector|21.6|29.6|35.7|44.9|47.2|
|_GDP_||||||
|Primary sector|4.0|4.3|2.5|1.8|1.7|
|Secondary sector|77.4|63.8|57.3|47.6|47.6|
|Tertiarysector|18.6|31.9|40.2|50.6|50.7|

_Source_ : Beijing Statistic Yearbook 2002; Shanghai Statistic Yearbook 2002.

**Table 3:The employees in state-owned sectors in Beijing and Shanghai in selected years**

|% ofemployees|1978|1990|1995|2000|2001|
|---|---|---|---|---|---|
|Beijing|54.2|57.1|53.8|45.7|40.4|
|Shanghai|86.2|71.9|59.7|55.7|54.4|

_Source_ : Beijing Statistic Yearbook 2002; Shanghai Statistic Yearbook 2002.

10
school reduces teen pregnancies by 5 percentage points in Malawi.

Since many of the secondary schools are single-sex, one interpretation could be that teens in secondary school simply see members of the opposite sex less frequently than they otherwise would, so lower rates of pregnancy follow. This interpretation is not supported by the data, though: when I categorize secondary schools as single-sex or mixed, I see no significant difference in the pregnancy decline across the two types of schools.<sup>39</sup> In Kenya, dropping out of school is more common among girls than boys, and is most pronounced once girls enter their teens (Kremer, Miguel, and Thornton 2009). This is closely linked to pregnancy: girls in the Kenyan schools are “required to discontinue their studies for at least a year”<sup>40</sup> if they become pregnant. Schooling and childbearing in Kenya are in practice nearly mutually exclusive, as is true in many other contexts (Field and Ambrus 2008). Though I am aware of no _rule_ prohibiting teen mothers from returning to school—though rules of that sort exist in other Sub-Saharan countries (Ferr ́e 2009)—teen mothers still face stigmatization in Kenyan primary and secondary schools (Omondi 2008), so even after giving birth, they are unlikely to continue their schooling. The practical mutual exclusivity of pregnancy and schooling means that high-ability girls at the discontinuity face a tradeoff between attending secondary school and starting a family immediately; this policy may also differ from the policy environment in the US.

> 39In the cross section, the reductions in teen pregnancy associated with going to the two types of schools are also similar and statistically indistinguishable: 9 percentage points for girls at mixed schools, and 10 percentage points for those who attend all-girls’ schools.

> 40Excerpted from Ferr ́e (2009), p. 5.

27
4

# 1. **Microstates and per capita income levels**

In this paper, we consider a large cross section of 157 countries for which at least 10 years of annual data on per capita GDP adjusted for differences in purchasing power parity is available. Of these, 33 are microstates defined as having an average population over the period 1960-1995 of less than one million. These countries are listed in Table 1, and range in size from tiny St. Kitts and Nevis with population of 42,000 to Mauritius with 912,000. The income range is similarly wide, from very poor African countries such as Guineau-Bissau and Comoros with real PPP-adjusted per capita GDPs around $600 to wealthy oil-exporting countries such as Qatar with per capita GDP of over $18,000.

If microstates suffer from the disadvantages of smallness, they should be poorer on average than larger states. What do we actually find? Not controlling for any other characteristic, microstates have the same range of per capita incomes as the rest of the samnple (Figure 1). However, if we control for the location by continent of all countries, whether they are oil producers, and whether they belong to the OECD, then microstates are actually significantly _richer_ than other states (Regression 1). Microstates are 50 percent (=-exp(.4025)-1) richer than other states, controlling for location. We note that this result does not reflect the obvious outliers in the sample, since the oil exporting countries Qatar and Bahrain are picked up by the OIL dummy, and Luxembourg and Iceland are picked up by the OECD member dummy. Even if we exclude two other particularly wealthy microstates (Bermuda and Bahamas), we still find that microstates are nearly 40 percent richer than other states. Figure 2 shows the income residual by quintile of population, and we see the very strong income effect in the microstate bottom quintile of population. We also note that the favourable performance of small states carries over to other quality of life indicators. For example, if we in tum use under-five infant mortality and life expectancy at birth as the dependent variable in the above regression, we find that infant mortality is significantly lower in small states by 22 per thousand, while life expectancy is about four years higher. We are not sure why microstates are so much richer than their regional neighbours and have so much better human development indicators, but we see this as a decisive refutation of the macro arguments that microstates suffer from a development disadvantage.

Are microstates richer than others, controlling for location, because they save more or because they have a higher productivity level? We use the Mankiw-Romer-Weil (1992)
Table 7. Average annual (1995-98) and potential exports under growth scenario

|_Trading_||_Exports_|_(USD million)_||
|---|---|---|---|---|
|_partners_|||||
||_Actual_|_Potential_|_Potential/Ac_<br>_tual ratio_|_Potential_<br>_minuis_<br>_Actual_|
|Armenia's|||||
|exports to:|||||
|Azerbaijan|--|6,660|--|6,660|
|Georgia|7,478|43,989|5.9|36,511|
|Turkey|4,692|65,706|14.0|61,014|
|<br>EU|63,223|389,802|6.2|326,579|
|Russia|72,457|106,988|_1.5_|34,531|
|USA|5,916|178,417|30.2|172,501|
|Iran|38,233|75,805|2.0|37,572|
|Other CIS|37,304|<br>61,485|1.6|24,181|
|Subtotal|229,303|928,853|4.1|699,550(|
|Azerbaijan's|||||
|exports to:|||||
|Armenia|--|4,577|--|4,577|
|Georgia|86,813|20,197|0.2|-66,616|
|Turkey|60,654|45,937|0.8|-14,717|
|<br>EU|<br>92,900|<br>454,389|4.9|361,489|
|Russia|124,475|193,765|1.6|69,290|
|USA|<br>4,808|<br>209,877|43.7|205,069|
|Iran|161,604|75,174|_0.5_|-86,430|
|Other CIS|85,038|79,158|0.9|-5,880|
|Subtotal|616,292|1,083,075|1.8|466,783|
|Georgia's|||||
|exports to:|||||
|Armenia|18,869|30,474|1.6|11,605|
|Azerbaijan|20,148|20,357|1.0|209|
|<br>Turkey|<br>29,927|<br>95,341|3.2|65,414|
|<br>EU|20,255|585,376|28.9|565,121|
|Russia|<br>56,892|<br>224,191|3.9|167,299|
|USA|4,322|259,552|60.1|255,230|
|Iran|2,328|75,829|32.6|73,501|
|Other CIS|21,100|93,877|4.4|72,777|
|Subtotal|173,841|1,384,997|8.0|1,211,156|

In our model, export volumes are represented by total exports. This has certain disadvantage since, according to the theoretical justifications of the gravity model, the 22
Lin, B. and Z. Jiang (2011). Estimates of Energy Subsidies in China and Impact of Energy Subsidies Reform. Energy Economics, Vol.33, pp.273-283.

McKibbin, Warwick J., Adele C. Morris, Peter J. Wilcoxen and Cai, Yiyong (2015). Carbon Taxes and U.S. Fiscal Reform. National Tax Journal, Vol. 68 (1), pp. 139-55.

McKitrick, R. (2017). Global Energy Subsidies: An Analytical Taxonomy. Energy Policy 101: 379-85.

Rao, N.D. (2012). Kerosene Subsidies in India: When Energy Policy Fails as Social Policy, Energy for Sustainable Development 16 (1): 35-43.

Sadeque, Zubair and Miklos Bankuti. 2017. A bottom-up financial model of power generation in Bangladesh. Background Paper. The World Bank.

Sen, A. 2015. Gas Pricing Reform in India: Implications for the Indian Gas Landscape. Oxford Energy Institute. Working Paper #96. <u>https://www.oxfordenergy.org/wpcms/</u> Solaymani, S. and F. Kari (2014). Impacts of energy subsidy reform on the Malaysian economy and transportation sector. Energy Policy, 70, 115–125. doi:10.1016/j.enpol.2014.03.035.

Taheripour, Farzad, Wallace E. Tyner, and Dominique van der Mensbrugghe. 2014. Computable General Equilibrium Analysis of Energy Sector Reforms in Bangladesh: A World Bank Consulting Project, Report 2: Reduction in electricity subsidy in a static framework.

Timilsina, G. R. (2018). Where Is the Carbon Tax after Thirty Years of Research? Policy Research Working Paper, WPS 8493. World Bank, Washington, DC.

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Timilsina, Govinda R. and Ram M. Shrestha (2007). Alternative Tax Instruments for CO2 Emission Reduction and Effects of Revenue Recycling Schemes. Energy Studies Review, Vol. 15 (1), pp. 19-48.

32
The net enrollment rate in primary school in Ecuador is high—90 percent. Net enrollment rates in secondary school are substantially lower—45 percent. Overall enrollment rates changed very little between 1990 and 2001: Calculations based on the 1990 and 2001 Population Censuses suggest that the net primary enrollment rate increased from 88.9 to 90.1, and the net secondary enrollment rate increased from 43.1 to 44.7 (Vos and Ponce 2005). In part because of this stagnation in enrollment rates, the Ecuadorean government has given high priority to identifying policies that increase the coverage of the education system, especially at the secondary level.

There is no gender disparity in educational attainment in Ecuador—enrollment rates are marginally higher for girls than for boys. Mean years of schooling of the adult population ages 15 and older is 6.5 years. On average, education outcomes in Ecuador are comparable to those of other countries with similar income levels. However, as is the case in many other countries, educational outcomes vary a great deal by household socioeconomic status. For example, heads of households above the poverty line have approximately four more years of schooling than those below the poverty line in urban areas, and three more years in rural areas (World Bank 2004).

This paper focuses on the _Bono de Desarrollo Humano_ (BDH) program, which grew out of an earlier program known as the _Bono Solidario_ . The _Bono Solidario_ was created in 1999, in the midst of an economic crisis. The purpose of the program was to make cash transfers to poor households, but eligibility criteria were not clearly defined. As a result, many of the households that received transfers were non-poor, and many poor were not covered by the program.

Since 2003, the BDH program has taken steps to re-target transfers towards the poor. To this effect, the government developed a composite welfare index on the basis of information on household composition, education levels, dwelling characteristics, and access to services, aggregated by principal components. This index is known as the Selben. The Selben covers around 90 percent of households in rural areas in Ecuador, and about the same fraction of households in selected urban areas that were judged to have a high incidence of poverty. Households surveyed by the Selben are ranked by their Selben score. In theory, 40 percent of households, those with the lowest Selben score, are eligible for $15 monthly transfers by the BDH. However, until recently the government did not have the budget to make transfers to all 4
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# **5 Implications of Investment Procyclicality for IFC Operations**

## **5.1 Potential Drivers of Procyclicality**

Both demand- and supply-side factors could explain the observed procyclicality of IFC investment. The key demand-side factor is the typical impact of the business cycle on capital inflows and demand for credit described in the literature review: during downturns, worsening macroeconomic indicators lead to higher risk premiums and fewer profitable opportunities, reducing demand for investment across the economy. Meanwhile, at the firm level, unfavorable market conditions may prompt IFC clients with approved loans to delay disbursement until an improving macroeconomic environment bolsters their ability to service debt.

While investment demand is driven by the business cycle, supply-side factors are directly influenced by IFC policy. For most investment projects, the key additionality of IFC financing is its relatively long tenor. By investing in illiquid assets, IFC can provide a stable source of funding and unlock risk premia that are unavailable to their short-term counterparts.<sup>15</sup> However, short-term risk aversion may discourage countercyclical investments even if they promise to yield long-term firm- and market-level gains. For example, a lack of clarity on risk appetite during downturns could lead to prioritization of short-term portfolio management at the expense of longer-term risk premia. IEG’s 2012 report noted this in stating, “the Corporation did not achieve an increased volume of investments as a reflection of a strategic choice to protect its portfolio as well as an overestimation of the prospective deterioration in portfolio quality.” Staff performance incentive

> 15 See Papaioannou et al. (2013).

12
low skilled group, the value-added paramneters are positive and significant in the wage share estimation and insignificant in the employment share specification for all workers. With reference to gender, the value-added parameter is positive for the semi-skilled male workers and negative for the semi-skilled female workers, this suggests that growing firms tend to increase male rather than female production workers.

It is interesting to note that the unemployment control is positive for the semi-skilled group and negative or neutral for the highly skilled and low-skilled groups. This suggests that employers increase the relative share of production workers as overall unemployment rises.

We find that capital and highly skilled workers are complements while capital and semiskilled workers are substitutes. This result is consistent with Tan (2000). Also, capital and semiskilled male production workers are substitutes while capital and semi-skilled female production workers are complements.

Finally, technology is biased toward the use of highly skilled workers. This implies that technology is skill-using for highly skilled workers but skill-replacing for semi-skilled and unskilled workers. Furthermore, technical change is skill-using for male and female highly skilled workers and skill-replacing for the semi-skilled male production workers. Tan (2000) finds that, in Malaysia, technical change is skill-using only for male highly skilled workers.

# 4. Time **of benefit from technology**

Probit models of technology adoption are informative but ill-suited to dynamic processes (L6pez-Acevedo 2001). To analyze the temporal relationship of labor demand and TA, we use event analysis. As Tan (2000) suggests, comparing the period of TA to skill-mix changes in previous and consecutive time periods facilitates effective event analysis. The variable r represents the time period relative to TA; the period of adoption is _r_ = 0 , the period preceding adoption is r= -1, and the period following adoption is r= 1. Since companies adopt technology at different times, the period in which r = 0 differs between firms, Also, we define that T = 0 in all periods for a firm that never adopts technology. Since we only have point data for 1992, 1995, and 1999, rranges from -2 to 2. Using information on rfrom all firms that adopt technology, we 10