rafmacalaba/datause-encoder-data huggingface dataset:
# 1. Introduction

In recent years, the growing interest of academics and policymakers in the extent, causes and consequences of governance and misgovemance has been reflected in the proliferation of cross-country indicators of various aspects of governance. In an accompanying paper (Kaufmann, Kraay, Zoido-Lobat6n (1999)) we present a large database compiling several hundred cross-country indicators of various aspects of governance, produced by thirteen clifferent organizations, and covering 178 countries. These indicators report subjective perceptions on a wide range of issues relating to govemance, ranging from the extent to which corruption in the political system affects foreign investment, to the efficiency of public services delivery, to the likelihood that citizens of a country resort to extrajudicial means to settle disputes.

In this paper, we take the view that many of these indicators serve as imperfect proxies for one of a much smaller number of fundamental concepts of governance. Given this view, there are considerable benefits from combining related indicators into a small number of aggregate governance indicators. First, the aggregate indicators span a much larger set of countries than any individual source, permitting comparisons of govemance across a broad set of countries. Second, aggregate indicators can provide more precise measures of governance than individual indicators. Third, it is possible to construct quantitative measures of the precision of both the aggregate govemance indicators and their components, allowing formal testing of hypotheses regarding crosscountry differences in governance We realize these benefits by constructing aggregate governance indicators using an unobserved components model. This model expresses the observed data as a linear function of unobserved governance plus a disturbance term capturing perception errors and/or sampling variation in each indicator. The main advantage of this method is that it allows us to obtain estimates of the variance of this disturbance term for each indicator. These can be interpreted as a measure of how informative each indicator is about the broader concept of governance it measures. We then compute the mean of the conditional distribution of govemance given the observed data for each country as a natural point estimate of the level of governance in that country. Similarly, the variance 1
The lagged regressions with industrial value added provide further credence to the impacts of flood on economic activities (Table 8). Here the WASP(+1) variable stands out as the sole significant explanatory climate variable over all model specifications. It is significant at the 95% level and the regression coefficients are all negative. Damage to capital and infrastructure is likely the cause of the negative impact of excessive rainfall. This result is especially significant given the large body of anecdotal evidence of major flood damages and expected economic effects and yet the nonexistent evidence of these effects in any multi-country econometric analyses. This is due to the lack of a consistent database of flood events and flood hazard exposure that is climate based. Instead, existing flood databases are collected by impacts and thus are biased in reporting flood significance not by their hydrologic magnitude, which is largely exogenous, but rather by their economic or social impact, which is largely endogenous. As a result, the economic effects of flood risk and effects are likely underestimated in the literature. This result is the first that the authors are aware of that demonstrates a statistically significant flood effect on national level economic variables in a multi-country analysis.

**Table 8a: Lagged Industrial Value Added With Country and Year FE’s** Dependent <u>variable: Industrial Value Added</u>

||(Precip)|(Temp)|(P, T)|(W+1)|(T,W+1)|(W-1)|(T,W-1)|(|T,W-1,W+1)|(W-1,W+1)|
|---|---|---|---|---|---|---|---|---|---|---|
|Precip_1|-0.00<br>(0.00)||-0.00<br>(0.00)||||||||
|Temp_1||-0.03|<br>-0.03||-0.07||-0.07|||-0.06|
|||(0.05)|(0.05)||(0.06)||(0.06)|||(0.08)|
|WASP_minus1_|1|||||(0.11)|<br>-0.07<br>(0.11)|-0.06|(0.24)|<br>-0.38<br>-0.36<br>(0.24)|
|WASP_plus1_1||||-0.28<br>(0.13)*|-0.29<br>* (0.13)**||||-0.55<br>(0.27)*|-0.56<br>* (0.27)**|
|Observations|2760|2760|2760|1737|1737|1830|1830||1117|1117|
|Countries|129|129|129|127|127|126|126||105|105|
|R-squared|0.049|0.049|0.050|0.059|0.060|0.046|0.047||0.061|0.062|

Notes: Columns represent model specifications. Standard errors are clustered at the country level. Standard errors in parentheses: * significant at 10%; ** significant at 5%; *** significant at 1%. P = Precipitation; T = Temperature; W+1 = WASP(+1); W-1 = WASP(-1). The WASP_plus1_1, WASP_minus1_1 and Temp_1 variables are lagged by one year.

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- To improve income distribution;

- To increase food crop production;

- To improve communications and access to and from markets; and,

- To increase foreign exchange reserves by raising the level of coffee production.

2.07 Although the PAR contained no specific goals for reaching women, women figure prominently in the projecc design, particularly in the discussion of extension and credit activities. In developing the extension program, the design team had access to studies showing the prominent role women play in agriculture (Kayberry, 1952; Bryson, 1979). Theme data were supplemented by the results of a small socioeconomic survey conducted in conjunction with the project design. This survey revealed that 71 percent of the women farmers lived in polygamous marriages and when combined with labor data, the designers concluded that "women function as independent farming units" (IFAD, 1980, Annex 1: 13). The survey also founo1 that a majority of young males (ages 17 to 34) were migrating from the rural areas.

2.08 Taking all of the available information together, the PAR concluded that "special attention should be given to the ways and means of providing extension to women farmers who currently play a major role in food crop production" (IFAD, 1980, Annex 3: 4) and "ways should also be found to include women as extension workers to ensure good contacts with women farmers" (IFAD, 1980, Annex 3: 5). Besides recognizing the importance of women as individual farmers, the PAR also took note of the role of informal women's groups, and specifically targeted thess groups as recipients of food crop loans and incorporation into the extension program.

2.09 To accomplish thesa goals, the PAR called for interventions in agricultural extension, adaptive reGearch, agricultural credit, input supply, infrastructure development including construction of storage facilities, rehabilitation of secondary roads, and support to self-help village water projects. The PAR also contained numerical targets in the key sectors, and using these projections as a base, the internal rate of return was estimated to be 11 percent after 30 years, principally from increased food production through the first ten vears and from increased production and marketing of coffee thereafter. (IFAD, 1980: Annex 12, tables 2 and 6).

2.10 The project was to last five years and was estimated to cost US$ 39.7 million, exclusive of US$ 4.0 million of taxes and duties. Financing was to come from four sources: a loan from the International Fund for Agricultural Development (US$ 12.0 million or 30.2 percent), a grant from the European Development Fund (US$ 10.2 million or 25.7 percent), a grant from the German aid organization Kreditanstalt fur Uiederaufbau (US$ 9.7 million or 24.4 percent), and a contribution from the Cameroonian Government (US$ 7.8 million or 19.5 percent).
following the outbreak of the debt crisis. Since the early eighties, the HICs have undergone a prolonged experience of low private investment coupled with the substantial accumulation of external assets by domestic residents. With the single exception of Colombia, where the slowdown was milder, private investment fell sharply in all the heavily-indebted countries for which data were available after 1982. The measure of private capital flight employed in Table 6 is that which is suggested by the emphasis here on the fiscal dimensions of the debt problem. Taken from Dooley and Stone (1991), and based on Dooley (1988), it measures as flight capital only those private capital outflows which do not remit earnings, thus taking as motivation for the flight of capital the desire to evade prospective domestic taxation. By this measure, only Chile, Ecuador, and Uruguay escaped substantial episodes of capital flight during this period.

# V. THE BRADY PLAN AND FISCAL POLICY

These distortionary effects on the domestic economy, and their implications for economic growth in the HICs, provide the motivation for the debt and debt service reduction operations (DDSR) embedded in the Brady Plan. An evaluation of the likely macroeconomic implications of DDSR operations thus requires understanding how these effects come about. Three conceptually distinct mechanisms can be identified through which a large stock of public debt could exert such effects on the domestic economy. All of them, of course, are transmitted through the public sector's budget. In other words, they are all fiscal phenomena.

To clarify these channels of transmission, it is useful to first introduce some notation. Let V, denote the market value of the public sector's external debt. On the simplifying assumption that domestic debt is zero, V, is the present value of the public sector's expected future primary surpluses plus seignorage revenue: 19 The role of domestic debt in what follows depends on whether external debt or domestic debt is treated as senior to the other. If domestic debt were senior, then the present value of expected payments to domestic creditors would have to be subtracted from the right-hand side of equation (7) below. If both types of debt were of equal seniority, then the right-hand side of (7) would be multiplied by the share of external debt in total debt. As it stands, (7) is equivalent to treating external debt as senior. To avoid the straightforward, but tiresome, consideration of each of these cases below, it is simplest to assume that domestic debt is nonexistent.

12
national trade flows limits the identification to the comparison between PTA member countries and country-pairs without PTAs in a way that is not completely consistent with the theoretical basis of the gravity equation (Larch et al., 2017).

To address these concerns, we extend our baseline specification in equation (3) in several directions. First, we use yearly data and include lags and leads of the depth variables to estimate the dynamic effects of PTAs. Figure 3 presents the results on the dynamic effects of deep agreements. Results are based on specifications (1) to (4) in Table 3, modified to include two leads and four lags of the depth variables to accommodate heterogeneous effects over time and to test for anticipatory effects of agreements. The inclusion of the leads thus also provides for an informal test for the “strict exogeneity” of trade agreements (see Bergstrand et al., 2015).<sup>28</sup> The results suggest that both current and future levels of PTA depth are statistically uncorrelated with current levels of trade flows. It takes at least two years for a deep agreement to increase trade flows and the effects are twice as large as the ones we find in specifications without lags and leads (Table 3). As shown in Figure 3, these results are robust to the use of different measures of depth.

Figure 3: Dynamic effects of Depth

> 28 As an alternative way to address the problem of reverse causality, we check whether previous trade flows predict depth. In results available upon request, we find no significant relationship between past trade flows and depth in both OLS and PPML regressions.

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|||CH8|CH9|CH9_1||CH10|CH11|CH12|
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# e) A Systematic Shortcut Procedure for Matching

Chapter V presents a systematic short-cut procedure, the ABM method, for matching products in complex multiproduct industries. This method confines matching to products which account for more than 1 per cent of the gross value of output of an industry. Smaller items were only included in case they matched with a similar product in the other country where it is important, or in case they were required to complete a match with an important product. The advantage of our short-cut method over the alternative maximalist procedure, is that it improves the quality of the results by eliminating "outlier" PPPs, and that it offers considerable savings in research time.

# f) The Unit Value Approach is not Inferior to Specification Pricing

It is sometimes suggested that unit values such as we derived from census information are inherently inferior to specification pricing as practiced by ICP. In fact we do not believe this to be true and have explained why in chapter VI.

Specification pricing as practiced by ICP involves meticulous characterisation of the items chosen as representative, whereas our "prices" are unit values derived by confrontation of census information on values and quantities of product. In practice the "products" may be a mix of items and qualities and be very far from the ideal of specification pricing. But there are compensatory advantages in the industry of origin approach:

- 1) the unit values are average transaction values for the whole year for all producing locations of the countries compared, whereas ICP prices are quotes, shelf, list or monitored prices for one point in the year in a limited number of locations.

- 2) with the census one can judge the representativity of the "unit values" which are selected from a much wider range of information than ICP had at its disposal. For instance, our 17 industry sample yielded 1,434 Mexican unit values from which 192 were chosen to match with the USA, and 543 Brazilian unit values of which 171 were matched with the USA. ICP, by contrast, had to live with what it got from national statistical offices (at least for consumption goods). For Mexico it received only 284 of the much larger number of consumer prices it requested, as compared with 359 for Brazil and 571 for the USA (Kravis, Heston and Summers, 1982, p. 45).

The unit value specification was particularly poor in the case of motor vehicles, largely because of census confidentiality rules. The census information was therefore supplemented in this case by information on output and consumer price structures furnished by trade associations. This adjustment produced a reasonable though not an optimal adjustment for quality. In any case we would stress that our method of handling the problem does not lead to results which are inferior to those of ICP for this particular industry. The ICP multilateral comparison of motor vehicles was based largely on Japanese and European models which were unrepresentative of the situation in Brazil, Mexico and the USA.
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# HOW ECONOMIC ADJUSTMENT AFFECTS WOMEN

126. In many countries today women and men may operate in the same broad spheres of economic activity, but often play different roles and face different opportunities and constraints. Failure to identify the implications of these differences at the operatioral level may jeopardize objectives at the economy, sector, or project level and may compromise progress toward other development goals.

127. The macroeconomic framework is as important to women as it is to men. Macroeconomic policies appear to have less specific impact on women than the provision of education, health, credit, or extension services do -- gender-based constraints show up more at the sector level. But sector and macro policies are not unrelated. Moreover, macro policies do affect women -- and women's generally weaker capacity at present to respond to macro policies may affect the impact of these policies. Some of the likely effects of macro policies are discussed here (based largely on Collier 1987 and 1989, Joekes and others 1988, and Joekes 1988).

128. Women's capacity to adjust to changes in economic circumstances varies, as does men's. Better educated women or women equipped to respond (because they have access to credit, resources, and so on) may do very well. But many, arguably most, women are not well educated or well equipped, and many are at a disadvantage compared to men. The question is, how to open up opportunities to women so that they can respond more effectively. Constraints on women's economic responsiveness and flexibility have been identified. They include family and household responsibilities and limited cultural expectations (which especially affect the poor and uneducated); poorer access to information/technology, resources, and credit; and outright discrimination in the labor markets. These constraints not only impede women's entry into more remunerative sectors, but also block their exit from less remunerative sectors (Bevan and others 1988; Collier 1987). Thus women may be concentrated in "women's ghettoes" of economic disadvantage. The failure to equip women to operate as flexible and responsive economic agents can thus help perpetuate entire sectors of low-productivity economic activity.

129. Women's greater inflexibility can also hamper economic adjustment programs. The core requirement for economic adjustment is the reallocation of labor and resources into more remunerative and sustainable activities, in response to market incentives. In short, markets have to function. Adjustment may well cause dislocation and pain during adjustment, but the objective is to achieve adjustment rapidly, protect the vulnerable as much as possible, and equip them to participate as soon as possible in the more productive lines of work. To the - extent that women cannot easily adjust to changing economic circumstances, they - and their dependent children -- are likely to suffer more and suffer longer. Redressing the inequities in women's education and opening up other economic opportunity to women thus has nontrivial implications for the scope, depth, and speed of adjustment programs.
**Figure 1:** Mapping of Ebola Cases and Sample

<!-- Start of picture text --> 10 ° N 10 ° N<br>9.5 ° N 9.5 ° N<br>9 ° N 9 ° N<br>8.5 ° N 8.5 ° N<br>8 ° N 8 ° N<br>7.5 ° N<br>7.5 ° N<br>7 ° N<br>7 ° N<br>13 ° W 12.5 ° W 12 ° W 11.5 ° W 11 ° W 10.5 ° W<br>13 ° W 12.5 ° W 12 ° W 11.5 ° W 11 ° W 10.5 ° W<br>Log(VHF Entries + 1)<br>2 4 6 8 Sections in Ebola Sample (160) Sections only in RCT Sample<br>(a) Heat Map of VHF Cases by Section (b) Sections Used in Ebola Analysis<br><!-- End of picture text --> Figure 1(a): the number of entries (logged) by section in the Viral Hemorrhagic Fever (VHF) database maintained by the CDC during the Ebola crisis. Figure 1(b): map of all sections that contain clinics that were part of the original randomized experiment. Sections in light gray are excluded, because they contain more than one clinic from the original RCT.

# **3.3 Randomization**

## **3.3.1 Matching and Blocking**

We grouped the 254 clinics in our sample into matched triplets. Clinics in a triplet fall within the same district and exhibit similar levels of utilization and performance at baseline.<sup>18</sup> Within each triplet, we then randomize clinics into control, community monitoring (CM), or non-financial awards (NFA). This results in 84 clinics assigned to control, 85 to CM, and 85 to NFA. Figure 2 illustrates this allocation of treatment and the timing of randomization relative to data collection. We include matched-triplet fixed effects in our reduced-form specifications to account for the blocked randomization.

> 18 We exactly match clinics by district and type (MCHP or CHP) and then select matches based on the Mahalanobis distance between eight indicators specified by the Ministry of Health: completion of first-year vaccinations, institutional deliveries, completion of fourth antenatal care visit, charging of fees for maternal and under-5 services, nurse absenteeism, staff attitude, maternal mortality, and under-5 mortality.

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# **Bank Activity and Funding Strategies: The Impact on Risk and Returns**

Asli Demirgüç-Kunt<sup>1</sup> World Bank Harry Huizinga<sup>*</sup> Tilburg University and CEPR

**Key words** : non-interest income share, wholesale funding, diversification, universal banking, bank fragility, financial crisis

**JEL classifications** : G01, G21, G28

> 1 We thank Wolf Wagner and participants of a seminar at the Nake Day 2008 for comments and Haiyan Yin for excellent research assistance. This paper’s findings, interpretations, and conclusions are entirely those of the authors and do not necessarily represent the views of the World Bank, its Executive Directors, or the countries they represent.