rafmacalaba/datause-encoder-data huggingface dataset:
shares held by the government. 21 percent would be sold to Tanzanians at a later date. Notwithstanding the considerable difficulties in privatizing NMB, the consultants were able to hand over a bank with an established business model and a high level of outreach and profitability.

In the end, 49 percent of shares were sold to a banking consortium led by Rabobank of the Netherlands on September 30, 2005, and the government relinquished control over the day-to-day management of NMB. Management responsibility was transferred to Rabobank and there have been no indications that the government intends to reclaim any direct influence over the management of NMB. The sale price ($29 million) was what earlier evaluations had estimated. Importantly, the bid documents did not contain any branch closure prohibition. This is at least partly due to a study commissioned for the sale itself that found, somewhat contrary to expectations, that the vast majority of NMB’s branches were indeed profitable.

# **<u>IV. DATA AND EMPIRICAL APPROACH</u>**

We use quarterly balance sheet and income statement data for the 42 banks that operated in Tanzania at any point between December 1998 and December 2006 to test whether the privatization of the two successor banks to the original National Bank of Commerce resulted in improved performance. Specifically, we use the following regression to summarize the evolution of NBC, NMB, and the banking sector as a whole in terms of profitability and portfolio quality: Yit = α + β1NBC(PRE)it + β2NBC(POST)it + β3NMB(Contract Management)it + (1) β3NMB(Rabobank)it + β5SIZEit + β5FOREIGNit + β6GOVTit + β7LOAN SHAREit+ β8Gov Securities SHAREit **+ β9** YEARit+ **β10** QUARTERit + εit Y is one of the two bank performance measures mentioned above for bank i in quarter-year t. FOREIGN is a dummy variable equal to one if a bank is foreign-owned, while GOVT equals one if a bank is state-owned.<sup>12</sup> Private domestic ownership is

> 12 Ownership is determined by the majority shareholder. Banks are considered government owned as long as the government holds 50.1% or more of the bank’s shares as it did, for example, with NMB throughout the period (however, the NMB case is treated separately in the regressions via the NMB dummy variables in equation 1). Banks are considered foreign owned if 50.1% or more of shares are held by a foreign entity, such as a foreign bank, as was the case for NBC after its sale to ABSA.

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Policy Research Working Paper 6709

# **Abstract**

With the movement toward universal health coverage gaining momentum, the global health research community has made significant efforts to advance knowledge about the impact of various schemes to expand population coverage. The impacts on efficiency, quality, and gaps in service utilization of reforms to provider payment methods are less well studied and understood. The current paper contributes to this limited knowledge by evaluating the impact of a shift by Vietnam’s social health insurance agency from reimbursing hospitals on a fee-for-service basis to making a capitation payment to the district hospital where the enrollee lives. The analysis uses panel data on hospitals over the period 2005–2011 and multiple cross-section data sets from the Vietnam Household Living Standards Surveys to estimate impacts on efficiency, quality, and equity. The paper finds that capitation increases hospitals’ efficiency, as measured by recurrent expenditure and drug expenditure per case, but has no effect on surgery complication rates or in-hospital deaths. In response to the shift to capitation, hospitals scaled down service provision to the insured and increased provision to the uninsured (who continue to pay out-of-pocket on a fee-for-service basis). The study points to the need to anticipate the intended and unintended effects of any payment reform and the trade-offs among policy objectives.

This paper is a product of the Health, Nutrition and Population Team, Human Development Network; and the Human Development and Public Services Team, Development Research Group. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The authors may be contacted at hnguyen19@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
# **Technology, Taxation, and Corruption: Evidence from the Introduction of Electronic Tax Filing**<sup>_∗_</sup>

Oyebola Okunogbe<sup>a</sup> and Victor Pouliquen<sup>b</sup> Keywords: Technology, taxation, corruption, e-government, electronic tax filing (e-filing) JEL codes: D73, H26, O33

> _∗_ We thank Emil Abdykalykov, Penelope Fidas, Alisher Isaev, Rustam Karimov, Vazha Nadareishvili, Dmitry Pyatachenko, Inomjon Sadulloev, World Bank Group (WBG) Tajikistan country office, and partners from the Tax Committee of Tajikistan for their invaluable cooperation. We are also grateful for input from Alejandra M. Alcantara, Anne Brockmeyer, Ana Goicoechea, Marc Gurgand, Asim Khwaja, Liam Wren Lewis, Christopher D. Miller, Jennifer Murtazashvili, Dina Pomeranz and several seminar participants. The study protocol received approval from Harvard Institutional Review Board. The study was registered on the AEA RCT registry website (ID: AEARCTR-0000914). The research for this paper received funding from the Impact Program managed by the WBG Trade and Competitiveness Global Practice and the Impact Evaluation to Development Impact Trust Fund (i2i) managed under the WBG Development Impact Evaluation Unit. The findings, interpretations, and conclusions expressed in this paper, including any errors, are entirely ours and do not necessarily represent the views of the Tax Committee of Tajikistan, the World Bank Group, its Executive Directors or the countries they represent.

> aWorld Bank Development Research Group

> bParis School of Economics
**Figure 14. Moderate poverty headcount rates considering both pre‐ and post‐fiscal income aggregates, separately for households with different compositions in terms of economic agency, presence of child and presence of elderly**

<!-- Start of picture text --> Change in poverty (p.p.)<br>Poverty headcount rate<br>70% 10.0<br>60% 5.0<br>50% 0.0<br>40% -5.0<br>30% -10.0<br>20% -15.0<br>10% -20.0<br>0% -25.0<br>Pre-fiscal poverty rate Post-fiscal poverty rate Change in poverty<br><!-- End of picture text --> Source: authors’ estimations based on PNAD-C 2019. Notes: M stands for single male breadwinner, F for single female breadwinner, CO/M for couple with a man as the main breadwinner, CO/F for couple with a woman as the main breadwinner, and OT for households in which there are either no members with strictly positive habitual labor income or both heads earn the same income amount. Similarly, C stands for “at least one child”, NC for “no child”, E for “at least one elderly member”, and NE for “no elderly”. Family composition is determined by whether there is at least one household member that declared to be the spouse of the household head. Economic agency is determined considering the highest-earning individual in terms of habitual labor income as the household main breadwinner. The household is considered to have a child if there is at least one member aged 15 or less who is neither the household head nor the spouse, and to have an elderly member if there is at least one member aged 60 or more. Pre-fiscal poverty indicates the poverty headcount rate considering market income plus pensions, while post-fiscal poverty indicates the poverty headcount rate considering consumable income. The bars in green follow the same logic of the other bars, although they are colored differently to emphasize the existence of different groups in terms of the presence of elderly (i.e., those in green have elderly while those in blue do not).

32
INFRASTRUCTURE AND GROWTH IN AFRICA

# **Figure 3. Electric power infrastructure, 1991–2005**

<!-- Start of picture text --> a. Electricity-generating capacity<br>(in megawatts per 1,000 workers)<br>2.0<br>1991–5 2001–5<br>1.0<br>0.0<br>-1.0<br>-2.0<br>-3.0<br>-4.0<br>-5.0<br>Western EAP7 Africa North Africa West Africa East Africa Southern Central Africa<br>Europe Africa<br>b. Quality of the provision of electricity services<br>(based on electric power transmission and distribution losses)<br>1.00<br>1991–5 2001–5<br>0.95<br>0.90<br>0.85<br>0.80<br>0.75<br>0.70<br>Western Europe EAP7 Africa North Africa West Africa East Africa Southern Africa Central Africa<br>Median (logs)<br>Median<br><!-- End of picture text --> 29
Table 5: Distribution of Land Classes by Province

|Class|Punjab|Sindh|NWFP|Balo.|Pakistan||
|---|---|---|---|---|---|---|
|Arable Land (percent of|each class b|y province)|||M ha|Percent<br>of<br>arableland|
|. Very good|67|21|4|9|5.2|26|
|II. Good|53|33|8|6|7.0|35|
|III. Moderate|50|31|14|4|4.8|24|
|IV. Marginal|48|7|19|23|3.0|_15_|
|Forest and Rangeland (pe|rcent of eac|h class by pro|virce)||M ha<br>.|Percent<br>of<br>forest/ raznge<br>f<br>|
|V+VI. Moderate/Good|<br>18|1|62|6|1.4|4|
|VI. Poor|30|6|17|43|15.4|38|
|VII. Unproductive|18|12|13|46|23.2|58|

Note: 1. NWFP figures also include Tribal Areas 2. Pakistan figures include Northerm Areas.

3. Source: Mian and Mirza (1993).

The first four classes are arable; the last four are forest or rangeland. Crucially, the land capability surveys have found that negligible additional land is available for arable agriculture. The limits of land expansion appear to have been reached.

There are several constaints on land productivity in Pakistan. These include soil erosion, problems related to irrigation, and inappropriate use of land.

# Soil Erosion

Water erosion is most severe on hillsides, and along river banks. Some of the erosion is the result of long-term natual processes, but it has been accelerated by various abuses, notably the depletion of natural vegetation and excessive tiflage. Over 11 million hectares are estimated to be affected by water erosion. Similar practices have also made wind erosion a serious problem, affecting about 5 million hectares. Flood damage from soil erosion is getting increasingly serious. Natural vegetation, which forms the best water absorber, has been stripped.

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# V. **Simulations of the Pakistan General Equilibrium Model**

# **Benchmark Simulation**

After having calibrated our model to historical Pakistan macro data, we carry out an out of sample simulation based upon 2012. That is, we assume that all fiscal policy parameters (tax rates, real public core spending, and deficit financing rules) remain constant for the 8 years of the simulation. We assume that the country runs a managed exchange rate, and arbitrarily assume that the exchange rate is devalued by 6 percent per year. At the same time, we assume that the world inflation rate is 4 percent annually and world growth is 2 percent per year. We chose the exchange rate devaluation rate so as to approximate the gap between world and Pakistan inflation over recent years. The world inflation and growth projections were taken from the World Economic Outlook (WEO) of the International Monetary Fund. The model is then run forward for 8 periods and generates a set of macro-economic variables. In addition, year by year real incomes are calculated for each of the 18 household categories. The results for this simulation are given in Appendix Table 1.

As our simulations generate a large of endogenous outcomes for different economic parameters, there is a question of how best to compare different policy simulations. We have, in general, chosen to make comparisons in terms of 8 period averages of key variables. In some instances, we will also use averages rates of change in particular variables to make comparisons. Such averages and overall rates of change are, of course, broad measures. The interested reader can use the Appendix tables to compare individual years.

We see in Appendix Table 1 that annual real growth averages 3.2 percent. The average inflation rate is 9.9 percent over the same 8 year forward looking time horizon. Thus, the 16
significantly more likely to export. It is only within this select group,<sup>1</sup> of most likely highly productive firms, that productivity has no predictive power.

A second important insight is that the globalization pattern tends to be somewhat different for manufacturing firms than for agriculture or mining firms. In particular, there is a much longer tail of smaller exporters and these firms focus, not surprisingly on trade with neighboring countries. More remarkable is that also the type of products traded by small exporters tend to differ from product categories that dominate the export bundle of larger exporters. As a result, the revealed comparative advantage of Rwandan manufacturing firms is somewhat different between small and larger firms.

We obtain many more detailed insights along the way, but it is hard to summarize them succinctly. The key contribution of this report is to offer a first glimpse of the GVC engagement of firms that represent an exhaustive sample of formal firms in a developing country. This cross-industry overview provides a useful complement to the literature that contains many case studies looking at individual industries or segments within an industry in particular countries.<sup>2</sup> The remainder of this paper is organized as follows. In Section 2 we present a brief overview of the economy of Rwanda, followed by a discussion of the administrative data in Section 3. The presentation of the results, in Section 4, is organized around eight insights which are discussed in separate sub-sections. In the concluding Section 5, we summarize those insights.

# **2. Overview of the Rwanda economy**

## **2.1 General**

Rwanda is a small, landlocked country in East Africa, neighboring the Democratic Republic of Congo (to the west), Tanzania (east), Kenya (north), and Tanzania (south). It is a densely populated country with 12.2 million inhabitants in 2017. Its economy has performed quite well over the last 10 years, driven to a large extent by important public investment programs. Its GDP expanded from 3.83 billion (in current USD) in 2017 to 9.14 billion ten years later.<sup>3</sup> This amounts to an annual growth rate of 9.1% per year, which is among the better performances in sub-Saharan Africa. The strong economy is also reflected in a declining poverty rate. In 2005, 67% of the population was living on at most $1.90 (in 2011 PPP) per day, but this had declined to 56% by 2013, the last year for which there is comparable data. Still, with a GNI per capita of 1,990 (in PPP, current international $), which is approximately

> 1 Only one ninth of the firms that register with the business income tax registration, for which we observe sales, also register as employer, and only in that case do we also observe employment.

> 2 A broad overview of the literature studying GVCs using case studies can be obtained from the list of publications of the Global Value Chain Initiative: https://globalvaluechains.org/

> 3 These statistics are taken from the World Bank World Development Indicators online database that can be accessed at http://databank.worldbank.org/data/source/world-development-indicators/.

3
66 the composition of electricity demand in the industry at the time of these price increases. Table 5.2 gives the composition of electricity demand for broad consumer groups.

_Table 5.2: Zimbabwe: Elecirical Energy used by Broad Consumer Groups (millions of kWh)_

|__________________________|1981|1982|1983|1984|
|---|---|---|---|---|
|Industy totu|5417|5562|5215|5328|
|Commercial<br>agricultu|re541.3|673.1|650.0|592.1|
|Mining|1360.3|1331.1|1271.9|1272.3|
|Manufacturing*|3516.1|3558.0|3293.9|3463.6|
|Domesticconsumers"|<br>990.8|987.9|926.6|925.9|
|Others|728.9|764.9|827.8|958.6|
|**Total**|**7137.4**|**7316.9**|**6970.2**|**7212.5**|

E13lactriciycnsumption in the nu iwgectrsws doinated by clectzicity intensive industry whefe the four major consumes, Sabd Chmicus (MUimzrs), Rodeu Ltd. mnd Rhomet (Farchomc) and Zisco (stol) togclhor in 1981 accounted for over 83 percnt of the consumption in this swctor. 3 Domestic electricity consumption was limited to urban consumers as the degrce of rual clectrification was clativcly low.

As table _5.2_ shows, over two-thirds of the electricity in the industrial sector was consumed by manufacturing, followed by mining, which accounted for a quarter and the rest was consumed by commercial agriculture and forestry. Within the manufacturing sector, electricity consumption was dominated by electricity-intensive industries, mainly metals (ferochrome and steel) and fertilizers. Electricity intensive industries such as fertilizers and metals are quite inflexible with respect to interfuel substion and the share of el ectricity in the unit cost of production is high. Also, the metal industries are price takers in the highly competitive international metal market Table 5.3 gives the index of industrial production for a selected group of industries in Zimbabwe at the time of an electricity price increase.
where the dependent variable ���� represents both _A_ and _S_ for brevity. ���� denotes a number of education outcomes such as reading and math literacy and years of schooling, for an individual _i_ born in province _j_ in year _t_ . Reading literacy is represented by a dummy variable which equals 1 if an individual can read without any difficulty, and 0 otherwise. Math literacy is similarly represented by a dummy variable with the value of 1 for an individual who can do a calculation without difficulty, and 0 otherwise. Since students usually had to take an examination to complete a degree at the end of each school level (before 2000) (see, for example, Pham (1995)), achieving a school degree could be an important landmark for an individual’s education.<sup>13</sup> As such, we also include in the outcome variable ���� dummy variables that indicate whether the individual accomplished a primary school degree or a lower secondary school degree (which requires finishing five and nine years of schooling respectively).

We will focus our attention on the treatment coefficient � . Our hypothesis is that the ME program helps increase education attainment for individuals who resided in DRV-controlled areas during their school ages than their peers in French-controlled areas. As earlier discussed, we offer two measures for the treatment variable (interaction term) ��� ∗�� . Our first, and preferred, measure assigns ��� as a dummy variable that equals 1 if individual � was born between 1940 and 1945 (treatment group) and equals 0 if individual i was were born either before the war in 1924-1935 (first control group) or after the war in 1950-1961 (second control group). Individuals in the treatment group would be of prime school age (i.e., between 6 and 14 years old) during the

> 13 In addition, our calculation using the 1997-98 VLSS shows that the average years of schooling for a Vietnamese adult (age 15 and above) hovered around 6.4. This number, however, has increased in recent years (Dang and Glewwe, in press). We focus mostly on the quantity of education and long-term life outcomes such as household living standards in this paper, since like most household consumption surveys, the V(H)LSSs do not offer test data on the quality of education. But note that estimation results in Dang and Glewwe (in press) point to stronger-than-average performance on international standardized test scores for Vietnamese students compared with other countries at a similar income level.

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10 potential duration of benefts - who have exhausted their entitlement - receive some kind of govemmental support; but the level of that support Is usually lower. Thus potential duration does affect the total amount of earnigs replaced during many spells of unemployment. Potential duration varies from as low as 26 weeks or less In most states In the U.S., to 30 weeks in Japan to a year or more in many European countries. In those countries, such as Spain, where the rate of flow out of unemployment Is very low, Ul laws generally specify a longer potntial duration.

Table 2. Gross Replacement Rates, 1989, for a Single Worker Country Rate Australla 24 Belgium 50 Canada 59 Denmark 64 Finland 57 France 59 Germany 58 Japan 28 Netherlands 70 Norway 62 New Zealand 27 Spain 62 Sweden 90 United Kingdom 16 United States 25 Source: OECD, EmDlovment Outlook, 1991, p. 233.

Within the general choice of potential duration, is that duration variable or fixed, and what determines how potential duration varies? In most U.S. states potential duration Is variable, and Is determined by considerations of work history similar to those that determine the WBA.

Is there a second-tier Ul program that becomes effective after regular benefts are exhausted? For example, Austria and Ireland offer unemployment assistance at lower leveis of support to very long-term unemployed workers. These programs are not, strictly speaking, Ul programs, but
# _Denmark_

Denmark is one of the countries with a strong government initiative for electronic invoice. It has made electronic invoice compulsory in B2G since February 2005 so that all public-sector institutions in the country accept only e-invoices from business suppliers. Small vendors without the capacity to issue e-invoice can send paper invoices to the “read-in bureau,” which transforms paper invoices into electronic invoices and transfers them to public institutions without charging a service fee. Business suppliers can also use private invoice portals that provide invoicing service or use their own accounting or invoicing system to transmit invoices directly to the public institutions (Agency for Modernisation Ministry of Finance). Approximately 15 million transactions are now invoiced electronically, giving the government and the public sector savings of € 100 million in three years (Gartner, 2009). According to the Eurostat, 39 percent of enterprises with at least 10 employees in Denmark sent or received e-invoices in 2010.<sup>22</sup>

# _France_

Three methods of ensuring the authenticity and integrity of e-invoices are allowed. The first is any technical solutions establishing a reliable audit trail between the invoice issued or received and the underlying goods or services, and the second a procedure defined as an advanced electronic signature. The third is a form of a structured message in a standard agreed between the parties (Schmandt & EngelFlechsig, 2013). According to the Eurostat, 36 percent of enterprises with at least 10 employees in France sent or received e-invoices in 2010.<sup>23</sup>

# _Germany_

All transmission methods including an e-mail, a PDF file, a text file, a computerized facsimile, and a facsimile server have been allowed as a valid e-invoice format subject to the authenticity of the origin and the integrity of the invoice contents since new rules on e-invoice took effect on July 1, 2011, in compliance with the EU VAT Directive (KPMG, Germany: VAT essentials). A reliable audit trail ensuring a link between an invoice and the underlying performance may also be established through a manual matching between the invoice and business documents presenting activities such as an order, a payment, or a delivery of goods and services (Schmandt & EngelFlechsig, 2013). According to the Eurostat, 36 percent of enterprises with at least 10 employees in Germany sent or received e-invoices in 2010.<sup>24</sup>

# _United Kingdom_

> 22 Ibid. 23 Ibid. 24 Ibid.

13