rafmacalaba/datause-encoder-data huggingface dataset:
project so, for instance, if the SFD had not financed a project to pave the local road, then the road would have remained unpaved. This is an extreme assumption, and is not entirely plausible, because other organizations – NGOs, ministries, local self-help groups – might well have stepped in if the SFD were not present. Thus the comparison between D and F may be expected to provide an upper bound to the effect of the SFD.

- (iii) **C vs. E.** In this case the comparison measures the incremental impact of SFD interventions, given that there are already other interventions.  If there are synergies between SFD projects and other interventions – for instance, an SFD sewerage project might work best if some other entity is already at work providing piped water – then this comparison should pick up this effect.

<!-- Start of picture text --> Is there an SFD intervention?<br>Yes: A No: B<br>With other “SFD only”: With other No<br>interventions D interventions: interventions<br>(“mixed”): C E at all: F<br><!-- End of picture text -->

**Figure 2.  Creating a Counterfactual for SFD interventions**

In the results reported below, we measure the impact using all three comparisons. But before doing this, some discussion of the data is warranted.

# **Data Considerations**

Most SFD programs operate at the level of a village (or sub-village), and this is the level at which the analysis is conducted. Although the basic unit of observation is the village, many of the variables – per capita income and expenditure levels, for instance – are based on household-level data. The main source of such data is the 2004/2005 edition of the national Household Income, Expenditure and Consumption _Impact Evaluation: Egyptian Social Fund for Development_ _Version of June 29, 2009_ _Page 12 of 36_
# WPS3134

## **Institutional Reform and the Judiciary**

### **Which Way Forward?**

#### **Roumeen Islam**<sup>**1**</sup>

#### **World Bank**

This paper presents some general lessons in institution building that has relevance for reform of the judiciary. The paper emphasizes the value of simplicity in design commensurate with country capacity, the importance of innovation/experimentation, and of economic openness in effective institution building. It underscores how the incentives of individuals depend on both the details of institutional design within the judiciary itself but also some critical institutions external to the judiciary. Finally the paper argues for the need to ground reform initiatives on a solid empirical and comparative approach. It illustrates some of these issues by drawing on a recent project conducted by the World Bank and others.

World Bank Policy Research Working Paper 3134, September 2003 _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 view of the World Bank, its Executive Directors, or the countries they represent. Policy Research Working Papers are available online at http://econ.worldbank.org._

> 1 This paper is based on work done for the World Development Report 2002, Building Institutions for Markets., World Bank.I am grateful to Rafael La Porta for reviewing parts of this manuscript and offering helpful suggestions and to Rick Messick for comments on an earlier draft. Juan Botero kindly provided helpful suggestions. I thank Theodora Galabova for excellent research assistance.

1
yields the average wage which is then adjusted for inflation by deflating the wage by the consumer price indices taken from the IMF International Finance Statistics Yearbook. With the exception of France for which the wage index presented in the IMF IFS Yearbook was used, wage growth in Issue Brief Table 2.4 was taken from Davis (1993) The compound rate of wage growth is computed by applying the yearly rates to an index over the period and then solving for the average annual growth rate which would have produced this result.

# F. Real rates of Return to Capital and Education

These rates of return were presented in Issue Brief 2 and were intended to illustrate possible alternatives to an investment in a pay-as-you-go pension system. Real rates of return to equities presented in Issue Brief Table 2.4 were calculated using annual indices provided by the Intemational Finance Corporation (IFC). The annual index changes are based on total returns in US dollars. These nominal returns were calculated and adjusted for inflation using the U.S. consumer price index from the IMF IFS Statistical Yearbook. Annex Table 9 below, shows these annual real rates of returns along with simple and compounded average returns over the period.

56
- 18 -

over, proper valuation of these enterprises, assignment of clear administrative responsibility for implementing the program, resolution of policy and administrative conflicts, and assembly of the speaialized technical expertise necessary to prepare for and negotiate the divestiture case by case are key components of such preparatory work. Lack of systematic artention to them and the consequent underestimation of the efforts required have caused avoidable delays and errors to the detriment of the privatization programs of some LDC governments.

# III. Emerging Issues

An important conclusion of this review is that the extent of privatization that has occurred in many LDCs, for which data are available is modest in relation to their planned programs of divestiture.30 The scale and pace of privatization in the more developed countries, in relative terms, has been more impressive. In part, this reflects the ideological shift that has occurred in the governments and the society at large in several of the western countries.31 Thus in the U.K. and the U.S., strong political leaders with a commitment to the private sector have

- 30/ The basic sources of data used are the papers by Hemming & Mansoor and Berg and Shirley (cited above).

31/ Commander and Killick, 2.Rcit.
|**Table 5: Government Expenditure on**<br>**Education in 2000 for SADC countries**<br>As % of GDP|
|---|
|Angola<br>2.61|
|Botswana<br>2.15|
|Lesotho<br>10.11|
|Malawi<br>4.14|
|Mozambique<br>2.36|
|South Africa<br>5.58|
|Swaziland<br>6.2|
|Tanzania<br>2.17|
|**Zambia**<br>**1.99**|
|Zimbabwe<br>4.70<br>Source: WDI, World Bank,. Figure for Botswana is for 2001 and for<br>Mozambique and Tanzania for 1999.|

Zambia’s expenditure on education as a % of GDP is the lowest amongst the countries shown. For Sub-Saharan Africa, the corresponding figure stood at 3.4 while for the least developed countries at 2.9. In addition to the low spending on education, there are some concerns that resources may not be suitably distributed across various disciplines. The following <u>graph illustrates the point.</u> <!-- Start of picture text --> Students in Zambia by Discipline (1998/99)<br><!-- End of picture text --> <!-- Start of picture text --> Agriculture<br>Engineering, 2%<br>manufacturing and Health and welfare<br>construction 3% Education<br>22% 32%<br>Science<br>8%<br>Humanities and arts<br>1%<br>Social sciences, business<br>and law<br>32%<br><!-- End of picture text --> 18
informal firms, both inter- and intra-county outdegree increase for the median county as well as on average. However, for 83% of counties, the increase in intra-county outdegrees exceeds the increase in inter-county links.<sup>25</sup> If informal firms source an even higher share of their inputs locally, the predicted shift towards intra-county trade represents a lower bound. We will discuss this in Section 6.1.

Table 5: The importance of Kenya’s primary cities in a revised network

|**Nairobi**|**Momb**|**asa**<br>in %|**Other counties**|
|---|---|---|---|
|Population<br>9|3||88|
|GDP<br>25|5||70|
|GDP w/o agriculture<br>33|7||60|
|**Number of outlin**|**ks**|||
|_Model ft_||||
|Administrative data<br>69|11||20|
|Model predicted network<br>70|11||19|
|_Revised network: informal frms ≈small frms_||||
|Default scenario<br>65|10||25|
|_p_(_θ_) using employ. share only<br>66|10||23|
|_Revised network: alternative linking patterns for _|_informal _|_frms_||
|0% sales, 50% input to/from formal<br>59|9||32|
|0% sales, 75% input to/from formal<br>63|10||28|
|25% sales, 50% input to/from formal<br>59|9||32|

The above table documents the share of overall firm-to-firm links which have a supplier based in Nairobi, Mombasa or the remaining 45 counties. We present the spatial dispersion of outlinks in the data, the predicted (formal sector) network as well as our default scenario for the revised network and four alternative scenarios to assess sensitivity.

If counties are selling less to Nairobi and Mombasa, where do their inter-county trade links shift? We find that the number of bilateral trade links is now more sensitive to social ties between counties. In Table C2, we regress the number of links between two counties on both travel distance and social connectedness (Bailey et al., 2021), and compare the results for the baseline and the revised network.<sup>26</sup> The findings indicate that, in the revised network, inter-county trade links are more strongly associated with the strength of social ties between counties.

The increased importance of within-county trade and trade between socially connected counties gives rise to a network with a more pronounced group structure. We quantify the extent to which the network is partitioned by measuring the network’s modularity (Newman, 2006). The modularity of a network is higher when groups of nodes have more links among each other

> 25While inter-county trade rises for the median county, 18 out of 47 counties actually have fewer links with other counties in the revised network.

> 26Social connectedness is measured using friendship network data provided by a popular social media platform, see Bailey et al. (2021).

27
clouds could have traveled past the closest districts by the time an image was taken. Regardless, the results are uniform in that all affected districts are neighbors. Overall, the model seems to give a fair picture of when and where the eruptions were at their most intense, although the ground level intensity can be hard to specify.

Table 15: 10 Most Impacted Provinces

|Province|Year|Intensity|
|---|---|---|
|Jawa Tengah|2010|34.641|
|Yogyakarta|2010|18.607|
|Sulawesi Utara|2004|16.224|
|Jawa Barat|2010|10.271|
|Sulawesi Utara|2007|6.387|
|Sulawesi Utara|2008|4.861|
|Nusa Tenggara Timur|2014|2.356|
|Aceh|2014|2.134|
|Sulawesi Utara|2005|0.684|
|Jawa Timur|2010|0.660|
|Note: Multiplied by 1,000|||

Table 16: Aggregated Volcano Intensity Data by Province and Year

|Province|2004|2005|2007|2008|2010|2014|
|---|---|---|---|---|---|---|
|Aceh||||||2.134|
|Banten|||||0.163||
|Jawa Barat|||||10.271||
|Jawa Tengah|||||34.641||
|Jawa Timur|||||0.660|0.432|
|Nusa Tenggara Timur||||||2.356|
|Papua||0.061|||||
|Sulawesi Utara|16.224|0.684|6.387|4.861|||
|Sumatera Utara||||||0.487|
|Yogyakarta|||||18.607||

25
33

**Table 5:** MPC from unearned income larger for non-basic consumption goods (non-staples, alcohol and tobacco, transportation and communication, clothing) and gifts; MPC from earned income at least as large as MPC from unearned income for basic consumption (staple food) and investment goods (education).

|**Marg.Propensity to Cons.**|**Kili**|**manjaro**|**Ru**|**vuma**||**Gansu**|**Inne**|**r Mongolia**|
|---|---|---|---|---|---|---|---|---|
||**OLS**|**hh FE**|**OLS**|**hh FE**|**OLS**|**hh FE**|**OLS**|**hh FE**|
|Food|||||||||
|_Staple food_|||||||||
|**Earned income**|0.004**|0.006**|0.026**|0.006|0.008**|0.003|0.007***|0.005**|
||(1.967)|(2.071)|(3.115)|(0.499)|(2.094)|(1.041)|(4.511)|(2.734)|
|**Unearned income**|-0.001|0.035|-0.052|0.070|0.014*|0.016**|0.011|0.011|
||(-0.058)|(1.222)|(-0.559)|(0.630)|(1.950)|(2.161)|(1.466)|(1.607)|
|_Non-staple food_|||||||||
|**Earned income**|0.023***|0.013**|0.054***|0.025**|0.042***|0.001|0.039***|0.021***|
||(4.646)|(2.253)|(5.849)|(2.483)|(4.193)|(0.153)|(11.800)|(5.989)|
|**Unearned income**|0.187***|0.083**|0.060|0.120|0.065***|0.045**|0.103***|0.094***|
||(5.803)|(2.274)|(0.651)|(0.949)|(4.968)|(2.830)|(4.306)|(4.050)|
|_Alcohol and tobacco_|||||||||
|**Earned income**|0.001|0.001|0.002|0.000|0.011**|0.004*|0.009***|0.006***|
||(1.269)|(0.927)|(1.623)|(-0.188)|(3.004)|(1.962)|(7.965)|(4.696)|
|**Unearned income**|<br>0.017*|<br>0.002|<br>0.018|<br>0.055**|<br>0.023**|<br>0.017***|<br>0.053***|<br>0.053***|
||(1.853)|(0.217)|(0.901)|(2.382)|(2.955)|(3.365)|(4.141)|(4.825)|
|Non-food|||||||||
|_Housing and appliances_|||||||||
|**Earned income**|0.018|0.013|0.020***|0.016**|0.071**|0.077**|0.054***|0.044**|
||(1.237)|(0.665)|(3.828)|(2.618)|(2.886)|(2.509)|(4.968)|(3.254)|
|**Unearned income**|0.057|0.065|0.232**|0.146|0.191***|0.186***|0.043|0.048*|
||(1.017)|(0.991)|(2.435)|(1.192)|(3.498)|(3.555)|(1.374)|(1.793)|
|_Transportation and_<br>_communication_|||||||||
|**Earned income**|0.005***|0.003*|0.018***|0.009**|0.026**|0.019**|0.037***|0.028***|
||(3.764)|(1.838)|(4.652)|(2.126)|(2.832)|(2.367)|(7.141)|(4.315)|
|**Unearned income**|0.044***|0.037**|0.203***|0.187**|0.052**|0.038|0.047**|0.038*|
||(3.597)|(2.547)|(3.658)|(2.858)|(2.328)|(1.572)|(2.568)|(1.869)|
|_Clothing_|||||||||
|**Earned income**|0.003***|0.002*|0.019***|0.012***|0.010***|0.007**|0.016***|0.006**|
||(3.995)|(1.866)|(7.526)|(4.912)|(4.040)|(2.682)|(6.674)|(2.225)|
|**Unearned income**|0.055***|0.049***|0.177***|0.170***|0.010**|0.012**|0.020**|0.025**|
||(6.648)|(4.868)|(6.098)|(4.952)|(2.762)|(2.150)|(2.020)|(2.643)|
-9-

"it seems that the financial incentive to the French mayors is too low to elicit strong enough reaction." In the Netherlands, the responsibility for clean-up rests with the regional authorities.

(ii) locally polluting firms are owned by non-local residents; (iii) the central governm.ent is more responsive to international conceris. The case of Brazil is an obvious example. Alternatively, the international pressure may be indirect, as in Eastern Europe and the Mediterranean, where; "...most countries in the reg:on aspire to one or another form of assr,ciation the [European) Community, and hence wish to demonstrate their status as good Europeans by adopting environmental policies consistent with those of the Community.";90r (iv) other budgetary responsibilities are ignored. For instance when health care is funded locally, if pollution control policies are formulated nationally. they must account for the full impact of ill health on the local budget.

Divergent objectives within a single tier of government will mean that some form of caordination is necessary to alleviate external effects such as

- (i) transboundary pollution. Horizontal coordination may be preferable to central control, as has been recognized in Indonesia, where

"[in orderi to make maximum use of existing personnel and other resources and to avoid establishing new agencies of uncertair capability, it would seem advisable to consider seriously the establishment of a pollution control or water management board, which would bring together the talents of all existing agencies.... Such coordinating bodies have proved to be more effective in other countries than the creation of independent new agencies.";`0 and 'Weiss (1991).

'°Asia Development Bank (1990).
The overall rate of return to schooling in Vietnam at about 9 to 10 percent, is at the global average. It is higher than in most countries in the region, demonstrating that further private investment in education is a sound priority (Table 1). The returns to primary schooling have decreased over time, which is not surprising given the level of achievement and universal access in Vietnam. The returns to primary schooling are lower than the regional average. The returns to secondary are low, but not much lower than the regional average. The returns to tertiary education are high, significantly higher that the regional average, and on par with China, the Philippines and Thailand. In fact, the returns to tertiary education in Vietnam are among the highest in the world.

<u>Table 1: Returns to Schooling (selected countries)</u>

|Economy|<br>Year|<br>Returns|<br>Primary|<br>Secondary|Tertiary|
|---|---|---|---|---|---|
|Australia|2010|13|14|20|4|
|Brazil|2012|11|8|6|17|
|Cambodia|2012|5|13|3|12|
|China|2002|17||9|21|
|Indonesia|2010|10|13|10|12|
|Japan|2007|14|||9|
|Korea, Rep.|2010|13|||13|
|Lao PDR|2008|5|11|5|6|
|Mongolia|2011|9|14|4|10|
|Philippines|2014|8|10|6|22|
|Russian Federation|2009|3|||7|
|Singapore|1998|13|7|10|11|
|Thailand|2011|9|3|5|17|
|United States|2010|13||5|15|
|Vietnam|2010-<br>2014|9-10|6.0|2-5|18-21|

Source: Montenegro and Patrinos 2014 Since the early 1990s, the returns to higher education have increased significantly (Figure 2). In 1992, the returns to primary were 10.8 percent, secondary was 3.8 percent and tertiary 3.0 percent (Moock, Patrinos and Venkataraman 20032003). By 2008, the returns to tertiary had soared to 17 to 20 percent (Doan 2013; Montenegro and Patrinos 2014). In 2010, the returns to primary were 6.1, secondary 2.0, and tertiary was 17.8 percent (McGuinness, Kelly, Thu and Thu 2015). Thereafter, there seems to be a decline in the relatively high returns to university (Doan, Tuyen and Quan 2018), but it remains much higher than other levels. Similar findings are presented in Demombynes and Testaverde (2018).

5
22 Spady. R.B., and A. Friedlasuder (1978), 'Hedonic Cost Functions for the Regulated Trucking Industry," Bell Journal of Economics, (Spring, 1978), pp. 159-79.

Taplin, J.H.E. (1982) "Inferring Ordinary Elasticities from Choice or HodeSplit Elasticities," Journal of Transport Economics and Policy, 16, 55--63.

Waters II, W.G. (1984) "A Bibliography of Articles Relevant to Transportation Appearing in Major Economics Journals: 1960--1981," Vancouver$ Centre for Transportation Studies, U.B.C.

Waters U1, W.G. (1989) 'A Bibliography of Articles Relevant to Transportation Appearing in Major Economics Journals: Update 1982--1987,' Vancouvers Centre for Transportation Studies, U.B.C.

Winston, C. (1985) 'Conceptual Developments in the Economics of Transportations An Interpretive Survey," Journal of Economic Literature, 23, 57--94.
10 Caribbean the second highest appears broadly reasonable, although the omission of nontariff barriers and exchange rate distortions probably leads to an underestimation of protection in Sub-Saharan Africa.

The regional groupings used in the analysis were based on the aggregates used in the World Bank's _Global Economic Prospects._ The developing country regions were: East Asia; South Asia; Latin America and the Caribbean; Sub-Saharan Africa; Middle East and North Africa; Other Europe; and Eastern Europe and the former Soviet Union. The developed country regions were: the European Community; the United States of America; Canada; Japan; Other Industrial; and Other High Income. A notable feature of the regional classification is the inclusion of Singapore, Taiwan and Hong Kong in the developed (Other High Income) group. Full details of the country cassification are given in _Global Economic Prospects_ (World Bank 1992, Appendix 1). Intra-regional trade was explicitly included in the model since, given the structure of the regions, this trade is typically subject to trade restrictions.

# 3. Experiments and **Results**

The experiments undertaken for this paper involve export expansion in the developing countries caused by trade liberalization or by investment or improvements in technology, which are frequently linked with trade liberalization. Protection policies are the primary policies affecting export levels, but the staic welfare gains from trade liberalization are
Financial Regulation and Government Revenue In this section, we discuss three issues that are useful in our accounting exercise:

-

- 1. compliance banks responded by purchasing NBE bills as prescribed by the regulation (Table 1);

-

- 2. safety overall safe asset purchase increased one-to-one with the NBE bill purchase (Table 2 and Figure 1);

3. profitability – banks’ profit growth slowed down, but did not turn negative (Table 3 and Figure 2).

# **Compliance**

In this subsection, we show that banks started to purchase this bond in proportion to lending (0.27 : 1) as prescribed by the regulation. For this task, we use the monthly bank balance-sheet information and present a simple fixed effect regression, highlighting that the policy had an actual effect on the behavior of private banks. For this reason, we use the volume of NBE bills purchased by bank _i_ in month _m_ and year _y_ , and regress it over a dummy variable taking unit value after April 2011, _Policymy_ , interacted with the monthly bank-specific volume of lending, _Lendingimy_ , and bank, month, and year fixed effects. The null hypothesis of this test is _b_ = 0 _._ 27, given the 27% rule. In the presentation of the main results, we exploit a variety of variations by including and excluding certain sets of fixed effects. Under no circumstances can we reject that banks start purchasing the government bonds as prescribed by the regulation.

In Table 1, we report the results of regression (1) for the whole variation in column (1). We exploit only within-bank variation by including only bank fixed effects in column (2), and then by removing year-specific shocks in column (3) and month-specific shocks in column (4). Finally, we replace the last two with non-parametric effects for every month of every year in column (5). Though the point estimates move slightly across these estimations, the null hypothesis _b_ = 0 _._ 27 can never be 7
# **Introduction**

Are cryptocurrencies, particularly as epitomized by Bitcoin, genuinely a potential competitor for fiat money or gold, or are they mainly a speculative bubble akin to 17<sup>th</sup> century Dutch tulips? A critical question is the extent to which there is an underlying transactions demand, now or in the future, to justify their high if wildly fluctuating prices. The results of this paper provide perhaps the strongest quantitative evidence to date demonstrating that, the use of Bitcoin for both domestic and international payments has been significant worldwide.

The vast bulk of media focus has been on cryptocurrencies as an evolving asset class. And although there has been some previous quantitative research providing some insight into the use of Bitcoin in facilitating illegal activities, this work typically concentrates on the analysis of the users, not the type of use, classifying users into legal and illegal agents, rather than distinguishing between investment purchases and transactions use. Furthermore, these analyses have only been applied to on-chain transactions,<sup>1</sup> that is, those that are immutably registered on the blockchain. On-chain transactions, however, constitute only a small share of the universe of all Bitcoin trades, most of which are “off-chain” utilizing some form of exchange, some heavily regulated, some not so much.<sup>2</sup> This paper thus develops a new methodology for examining off-chain transaction data that allows one to probabilistically tag individual trades as “crypto vehicle transactions,” that are clearly distinguished from the use of Bitcoin as an investment vehicle. We do not know whether results such as ours can potentially explain prices for crypto currencies, but they certainly show that the popular media focus on Bitcoin as speculative asset ignores its very active use in payments and capital flows.

> 1  See Chung, 2019; Foley et al, 2019; Framewala et al, 2020; Ron and Shamir, 2013; Yang et al 2019; Zhao and Guan, 2015.

> 2  Though arriving at a precise estimate is difficult, as not all exchanges provide data on trade volume, while other exchanges might have incentives to provide inaccurate data, the off-chain transaction volume involving Bitcoin appears to have been at least 10 times the volume recorded on the Bitcoin blockchain (Sources: CryptoCompare.com API, Blockchain.com API)

1