rafmacalaba/datause-encoder-data huggingface dataset:
the generally low savings capacity in Colombia compared to other countries<sup>48</sup> . A simultaneous survey of banked and unbanked people in Mexico City revealed that 45% of the total population held financial savings and 47% of the unbanked were savers. The considerable difference in savings capacity between Bogotá and Mexico City can be attributed to the generally low savings capacity in Colombia. However, the numbers need to be treated with caution due to certain limitations of the Bogotá survey<sup>49</sup> .

19. **Informal savings instruments are used by both banked and unbanked individuals.** Informal savings are used by 13% of the population in Bogotá, compared to 39% of the population in Mexico City. In Bogotá and in Mexico City, banked individuals outnumber the unbanked in their use of informal savings services. As Table 3.2 shows, 19% of banked individuals in Bogotá (7.5% of the total sample) use informal savings, twice as much as the unbanked, with 9% usage of informal savings services (corresponding to 5.4% of the total sample).

20. **The majority of the unbanked saves at home.** Home savings is used three times more frequently by unbanked persons than by the banked population, while other forms of informal savings are as likely to be used by persons with bank accounts as without. There was no notable difference between unbanked and banked regarding the use of “ _tandas_ ” (savings clubs with friends), savings clubs at stores and other organizations and loans to friends and families.

21. **The cost of informal savings is high.** Informal savings systems do not offer interest, so that savings lose value with inflation. In the case of savings clubs and “lay-away plans” at stores, informal savings can be shown to lose a margin in excess of the inflationary loss, since savings are frequently traded in for certain items sold above list price. In addition, informal savings systems do not benefit from any institutional deposit insurance, having to rely on personal trust mechanisms instead.

**Table 3. 2  Banked versus unbanked users of informal savings services**

||**Banked**|**%**|**Unbanked**|**%**|**Total **|**%**|
|---|---|---|---|---|---|---|
|Uses informal savings|318,211|19.0%|237,424|9.1%|555,635|12.9%|
|Does not use informal savings|1,359,091|81.0%|2,379,201|90.9%|3,738,292|87.1%|
|_Total_|1,677,302|_100%_|2,616,625|_100%_|4,293,927|_100%_|

_Source: DANE household study of Bogotá, 2003_ 48 The savings rate in Colombia has been constantly declining since 1990 from 24% of GDP to 14% of GDP in 2003.

49 The DANE did not gather sufficiently robust information on the savings behavior of the interviewed people. A second application of the survey with revised questions is therefore recommended. In contrast, the México City survey included several in-depth questions on savings behavior.

53
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**The majority of policy reports are produced by regional vice presidential units (VPUs).** The Africa region (AFR), East Asia and Pacific region (EAP), and Europe and Central Asia region (ECA) generated more than 52 percent of knowledge products between fiscal years 2008–2012 (Figure 2). For the networks, Finance and Private Sector Development (FPD) and Sustainable Development (SDN) have historically taken up the largest share of policy reports, but in the past few years Poverty Reduction and Economic Management (PREM) has increased its number of policy reports, albeit from a very low level. The Middle East and North Africa (MNA) produced the smallest number of reports among the regions, while the Human Development (HDN) Anchor produced the least among the networks.

**Figure 2: Policy Reports per Year**

<!-- Start of picture text --> Policy Reports per Year Policy Reports per Year<br>368<br>328 337 SDN<br>303 PRM<br>275 HDN<br>FPD<br>SAR<br>MNA<br>LCR<br>ECA<br>EAP<br>AFR<br>WBI<br>2008 2009 2010 2011 2012 2008 2009 2010 2011 2012<br>Source: World Bank Documents & Reports and World Bank SAP database. Source: World Bank Documents & Reports and World Bank SAP database.<br>400 400<br>300 300<br>200 200<br>Number of Policy Reports 100 Number of Policy Reports 100<br>0 0<br><!-- End of picture text -->

# **III. Measuring Transfer of Knowledge**

**Individual knowledge services can be evaluated against their specific objective.** For instance, if knowledge services are meant to improve the design of lending operations, measures can be used to assess whether the quality of operations has improved. If they are intended to improve decisions by customers or stakeholders, measures can be used to assess whether these partners believe their decisions were positively shaped by the knowledge they received. If knowledge services are aimed at generating public goods, it can be assess whether and to what extent those public goods are having the intended outcomes.

**All policy reports are required to have a development objective.** Task team leaders (TTL) need to specify a clearly defined development objective, as well as intermediate outcomes of the report and risks to achieving the desired results when creating a budget code for an ESW or TA in the system.  They can choose among one or more of five predefined development objective categories for an ESW or TA: i) informs bank lending); ii) informs government policy; iii) builds capacity; iv) informs the development community and v) stimulates public debate.  Figure 3 below shows the distribution of development objectives among our policy report dataset.  The development objective of about 55 percent of policy reports is to inform government policy and of 49 percent to inform public debate. Correlation among the different development objectives is weak.  The three pair-wise correlations between building client

7
|_hh_electricity_access_|Does the<br>household<br>have access to<br>electricity?||Houses which have a generator/ solar<br>panels but aren’t connected to a grid<br>are also recorded as having access to<br>electricity|
|---|---|---|---|
|_hh_dependency_ratio_|Household<br>dependency<br>ratio||Individuals that are younger than 15<br>or older than 65 are classified as<br>“dependents”|
|_hh_formal_education_|Does anyone<br>in the<br>household<br>posses any<br>formal<br>education?|||
|_nonfarm_enterprise_|Someone in<br>household<br>owns a non-<br>farm<br>enterprise|||
|_totcons_LCU_|Consumption<br>aggregate per<br>capita, in<br>LCU||MWI: absent in w3, w4<br>MLI: absent in w2|
|_totcons_USD_|Consumption<br>aggregate per<br>capita, in<br>USD|Consumption aggregates<br>(_totcons_LCU)_are converted<br>to current USD and deflated<br>to 2020 dollar values, using<br>exchange rates and a deflator<br>extracted from World Bank<br>databases (Azevedo et al.,<br>2011)|TZA: consumption aggregates for the<br>refresh sample, wave 5, include rent<br>and durables, which is not the case<br>elsewhere.|
|_cons_quint_|Household<br>consumption<br>quintile||Quintile of_totcons._This amounts to a<br>within wave quintile|
|_hh_asset_index_|Household<br>asset index|Index based on a PCA of all<br>assets owned by the<br>household||
|_HDDS_|Household<br>dietary<br>diversity<br>index|Index derived from a<br>household consumption<br>module. See the manuscript<br>for more information|MLI: absent in w2|

37
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To control for project selection into IE, we include both institutional and idiosyncratic factors, assuming the confounders are observed or time-invariant. These factors range from time, sector and country effects, project and project leader fixed effects, and project leader changes. If project leaders of potentially high-disbursing projects are more likely to select into IE, then projects with IE may disburse faster partially due to the project leader decision to adopt an IE. If, on the other hand, project leaders select into IE because their projects need additional help and support, then projects with IE will disburse at a slower pace. Our data provide some support for the latter case.

We find that impact evaluations have a large and significant effect on the rate of disbursement of operations, reducing the gap between planned and actual disbursements and increasing disbursements relative to average disbursements in the typical project in the same sector. By averting common delays in the early stages of the project cycle, impact evaluations might make less relevant the need for teams to push disbursements out in the later stage of project implementation.

We conclude that projects with IE are more likely to implement their activities as planned and, in so doing, may be more likely to achieve their objectives.<sup>8</sup> Furthermore, our results support the idea that project financing and IE research are complementary outputs of the World Bank. This might have implications for the use of IE as an operational tool to improve delivery of projects, and for weighing the costs of IE research against the benefits on the Bank’s project portfolio. For development organizations like the World Bank, an optimal balance between project financing and IE research may help them reach their efficient frontier. More generally, we hope our results may contribute to shifting the discussion away from just questioning the effectiveness of aid to a discussion on constructive ways to make aid more effective.

Finally, we consider the potential channels through which World Bank impact evaluations can affect project implementation. We speculate that these channels include:<sup>9</sup> (a) better planning and evidencebase in project design, (b) greater implementation capacity due to training and support by research team and field staff, (c) better data for policy decisions, and (d) observer effects and motivation. These channels are not necessarily specific to IE research and learning more about them could inform development policy more widely. Finally, we discuss the limitations of our analysis and outline an initial agenda for future research.

The remainder of our paper is organized as follows. Section 2 summarizes the literature. Section 3 describes the institutional background and the data. Section 4 explains the analytical strategy. Section 5 summarizes the results. Section 6 concludes.

# 2. LITERATURE REVIEW

> 8 Here, we are assuming that assumptions (i) and (ii) above are met; that is, (i) the problem/goal is correctly identified and (ii) an appropriate course of action and financing agreed to. 9 See also the discussion in Legovini (2010).

4
# **Assessing the Direct Economic Effects of Reallocating Irrigation Water to Alternative Uses: Concepts and an Application***

Susanne M. Scheierling The World Bank

**_Keywords_** : water reallocation, irrigation water transfers, economic feasibility, foregone direct benefits, estimation techniques, agroeconomic model, farmer compensation.

**_JEL codes_** : C61, O13, Q12, Q25.

__________________________

* The paper is based on Economic and Sector Work (ESW) carried out in the Water Anchor of the World Bank‘s Transport, Water and ICT Department.  An earlier version of the paper, entitled ―Measuring Foregone Direct Benefits of Irrigation Water Transfers: The Effect of Model Specification‖ by Susanne M. Scheierling and Robert A. Young was presented at the 2010 Annual Meeting of the Agricultural and Applied Economics Association (AAEA) in Denver, CO.  Helpful comments on the concept note and drafts of the paper were provided by the following colleagues at the World Bank: Julia Bucknall, Liping Jiang, Marie-Laure Lajaunie, Xiaokai Li, Halla Qaddumi, Joop Stoutjesdijk, and Caroline van den Berg. Robert A. Young (Colorado State University) also provided detailed comments.  Romila Sudhir helped with the literature review, and Silke Heuser assisted with the review of water-related projects.  The views expressed in the paper are those of the author and do not necessarily reflect the views and policies of the World Bank.  Please send correspondence to: sscheierling@worldbank.org.
|**Sub-domain:**<br>|**Goods**(production/consumption, including basic<br>|needs)<br>|
|---|---|---|
|**Presence of rules (institutions)**|**Enactment of rules (institutions)**|**Existing data**<br>**sources/indices**|
|_Formal_<br>•Number of international instruments<br>and conventions on ESC rights,<br>including land rights, standard of<br>living, freedom from hunger and<br>social security ratified (1)<br>•Pro-redistribution legislation for<br>access to and control over productive<br>assets (including land) (2)<br>•Regulatory framework in place for<br>market based allocation of basic<br>needs and goods<br>•Pro-transparent and simple regulation<br>exists for small businesses (2)<br>•Legislation exists ensuring fair<br>trading conditions/relationships<br>between buyers and sellers (2)|_Formal_<br>•Number of formal social policy commitments to<br>basic needs provision backed by budget execution<br>(2)<br>•Percentage of threatened evictions prevented through<br>formal legal processes and protection (2)<br>•Percentage of productive assets owned by poorest 20<br>percent of households<br>•Percentage of productive assets owned by richest 20<br>percent of households<br>•Number of cases of fair-trading violations filed<br>through the justice system per year (2)<br>•Number of mechanisms for ensuring transparency<br>and accountability among product producers and<br>distributors<br>•Number of complaints regarding transparency and<br>accountability by product producers and distributors<br>per year<br>_Informal (cultural)_<br>•Percentage of women able to inherit property<br>•Percentage of men able to inherit property<br>•Percentage of “lower” castes or classes owning<br>property<br>•Percentage of women within household owning<br>property and productive assets<br>•Percentage of men within household owning<br>property and productive assets<br>•Percentage of households with joint ownership of<br>property and productive assets|(1) Office of the UN High<br>Commissioner for Human<br>Rights<br>(2) World Bank Country Policy<br>and Institutional<br>Assessment<br>Where no data source is<br>identified, data must be<br>collected using the national<br>survey or in-depth research<br>techniques.|

71
Table 4: Impact of President and House Majority on Federal Highways, RD Estimates

||Presi|dential Elec|tions|Legis|lative Elect|ions|
|---|---|---|---|---|---|---|
||_p_= 2|_p_= 3|_p_= 4|_p_= 2|_p_= 3|_p_= 4|
||(1)|(2)|(3)|(4)|(5)|(6)|
|Winner|-0.222|-0.478|-1.019|-0.188|-0.166|-0.286|
||(0.574)|(0.742)|(0.885)|(0.404)|(0.404)|(0.446)|
|Observations|6,808|6,808|6,808|9,220|9,220|9,220|
|R-squared|0.395|0.396|0.396|0.346|0.346|0.346|
|Fixed Effects|Yes|Yes|Yes|Yes|Yes|Yes|

_Notes:_ The table shows the regression discontinuity estimates of the winner of presidential (columns 1-3) and legislative (columns 4-6) elections on multi-lane road (federal highway) outcomes. The estimation method is a spline polynomial approximation with second, third, and fourth polynomial, respectively. Robust standard errors clustered at the municipality level are reported in parentheses. All specifications include state, time,

** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1.

# **VI. What Explains Highway Politics in Mexico?**

## **A. Testing for Potential Motives**

To help understand the president’s inclination to provide particularistic benefits in highway construction, we employ the above-mentioned RD framework to test two theories. The first hypothesis reflects a bargaining mechanism between the executive and the legislature that influences the strategic distribution of federal outlays. In such an environment, the president also resorts to distributive politics to compromise the election prospects of opposition candidates (Berry et al., 2010), and influence the composition of the legislature (McCarty, 2000). A key prediction of this theory is that presidential pork is large when the size of the president’s party in the legislature is small (McCarty, 2000). The second hypothesis is consistent with _machine politics_ which consist in targeting constituents with public expenditure reflecting common ideological interests and policy priorities (Cox and McCubbins, 1986; Alesina, 1988; Dixit and Londregan, 1996; Besley and Coate, 1997). For example, evidence from the U.S. suggests that federal pro20
10 With respect to prices, the results are much more clear-cut where the private sector is responsible for distribution (and this is only in 9 provinces and in Buenos Aires). A sharp reduction in prices which in most cases flows directly to final consumers (except for transferred contracts) is the most obvious outcome of the reforms. Taking a typical residential consumer, wholesale prices represent 50% of their total bill. In the case of the privatization of the federal distribution companies (Edenor, Edesur, and Edelap) 50% of their load is bought through eightyear fix-price contracts sign prior to privatization. The impact in the reduction of wholesale prices is then approximately 25%. This means that a fall of 56% in wholesale prices (from an average of 32 U$/MWh in 1993 to 20 u$/MWh in 1996) implied a reduction of around 16% in residential tariffs. For large industrial user the impact is even larger as wholesale prices account for up to 95% of their total electricity bill. For these users the reduction in electricity costs is in the region of 25%.

||Table 2: Spot Prices||
|---|---|---|
||**V.ge**||
|1992|-1<br>4115<br>7**80M5**<br>|**4- 20.47**|
|**-9**-|32A.1<br>-<br>**_5&75_**|**_,_2- S5I**|
|**_1995_**<br>|<br>206<br>.80.13-<br>|14.58|
|**19,96**|r<br>20.157<br>68.83|<br>1285,|

As seen in Table 2, the fall in average prices is in great part explained by the fall in the minimum price. This reflects the entry and availability improvements achieved by the new rules in the system. Maximum observed prices are still high as in most cases they represent transmission constraints, which result in out of merit dispatch. Between, 1992 and 1997 the minimum observed hourly price in the interconnected system fell from over 20 u$/MWh in the moment of restructuring (1992) to near 13 u$/MWh in 1997.

An additional point worth mentioning is the trend in the prices paid for the concessions. In Buenos Aires (in bold in the Table), at least, there is an observable trend to improved sale prices for the electricity distribution companies as time goes by as seen in Table 3. (The results are less transparent for the provincial distribution companies since the levels and types of risks faced by investors are much more diverse than around Buenos Aires). But the evolution observed around BAs over time can suggest that as the regulatory framework is better established, investors are willing to reduce the risk premium demanded and as a result better prices are paid for the concessions.

This may also suggest that a sequential approach to privatization in which a gradual sale of the firms in the sector is done can improve the outcome. As confidence in the new arrangements increases as a result of time investors reduce the risk premium demanded to invest in the sector resulting in larger prices paid for the companies (lower discount rate).
16 the first differences of the stock values in local currency<sup>as well as in German</sup> mark at average-of-period exchange rates exaggerate the historical transaction values.

In the following regression analysis first differences of<sup>the original</sup> stock data were used as a proxy for net outflows. As<sup>the high inflation</sup> countries of Latin America have a particularly high weight<sup>in German FDI, the</sup> respective end-of-period exchange rates were included in the regression equation in order to capture valuation effects.6 The data set covers 41 countries and eleven years (1977 to 1987). The only index for the degree of openness<sup>available</sup> covering all the 41 countries is the FS-index. The resulting regression<sup>equation</sup> is: 7 + O.08*LGDM + O.04*LEXAN + 1.92*FS, Rsquared - 0.11, NOB: 451 - (3.2) (1.9) (0.8) Chisquared 77.9 (critical value: 33.9) Although changes in FDI stock are measured at an aggregate<sup>level the</sup> numbers often reflect the behavior of only a few investors.<sup>Thus heteroscedas-</sup> ticity is a potential problem, not only with respect to<sup>the different countries,</sup> 6Cross rates derived from market rates vis-a-vis the US-Dollar as published by the IMF were used. When valuation effects due<sup>to exchange rate changes are</sup> properly taken into account, the regression results obtained<sup>from other adjusted</sup> for the "end-of-period effect" deviate very little<sup>from those using first</sup> differences of the original stock data.

> 7 - LX:- log(X), DLX:- log(X) log(X(-l)), XDMST: German FDI stock in German mark, EXDM: local currency per German mark, GDM: GNP of<sup>the host country in</sup> German mark, EXAN: German exports to the host country<sup>relative to the host</sup> country's GNP, FS: FS-index; adjusted t-values in brackets; Chisquared:<sup>White-</sup> test on homoscedasticity.- Data sources: see Annex I