rafmacalaba/datause-encoder-data huggingface dataset:
trade flows between PTA members amounted to just under one-third of the world total in 2000-02. However, even this low percentage is misleading because not all trade flows between PTA members can be considered truly preferential. Unilateral and multilateral liberalization have resulted in a growing number of tariff lines with zero or very low MFN duties, in which the margin of preference for PTA members is negligible and the preferences are likely to remain unutilized. In fact, as long as the MFN tariff is at or below the costs of complying with the relevant ROO, exporters have no incentive to take advantage of preferences and therefore trade flows in these products cannot be considered preferential. The literature on ROO compliance costs estimates them to range between 3 and 6 percent of shipment value and, using these figures, we calculate the share of preferential trade in world total at 15 _._ 4 to 11 _._ 4 percent, respectively. This implies that trade in tariff lines where preferences are likely to matter amounts to less than one-half of all trade between PTA partners, and between one-tenth and one-sixth of total world trade. On the regional level, most preferential trade is undertaken by Eastern European and Latin American countries, both within their respective regions and with high income partners. On the other hand, East Asian countries have very low preferential trade shares for South-South and North-South trade alike.

Our paper offers an alternative to the common practice in gravity literature—estimating the effects of PTAs on trade by specifying the dependent variable as total imports or exports. Our results show that total trade is a very poor proxy for preferential trade, implying that the traditional approach for estimating the intra-bloc trade effects of preferential agreements is not correct. In addition, existing gravity studies usually scale-up their estimates of PTA trade effects from point estimates of individual PTAs, which may introduce an upward bias if the PTAs selected are large and more likely to affect trade. We construct an empirical gravity model that addresses both of these concerns by including all known PTAs in the analysis and creating an alternative dependent variable that is limited to preferential trade, conservatively defined as a set of trade flows in tariff lines with a MFN duty rate above 3 percent. Using total imports as the dependent variable, our baseline model shows that PTAs are associated with a 114 percent increase in intra-bloc trade. This effect is significantly smaller than individual agreement estimates from the literature, supporting the hypothesis that scaling up PTA point estimates is a biased approach to calculating the effects of preferential liberalization at the global level.

48
the incidence of poverty in Albania has been shown to be less frequent among pension recipients than it is among NE participants, and that poor heart condition of a household head is likely to be associated with inadequate income generation, health costs and thereby poverty. The set of dwelling characteristics that enter into the report of the NE administrator following the home visit also assume statistically significant coefficients. The presence of a toilet, running water or a telephone as well as the number of dwelling rooms per capita are all negatively associated with the likelihood of program participation. Considering the lack of these amenities and crowding beyond the means of the dwelling are often indicative of poverty, these outcomes are predictable.

Additionally, a unit increase in the walking distance to the bus stop, which is included as an indicator for isolation from social services, reduces the probability of NE participation. Furthermore, we find that the total amount of social assistance funds to the commune exerts a positive effect on program participation.<sup>19</sup> It is reasonable that increases in allocations from the central government are likely to relieve the budgetary concerns of the communes regarding the extension of social assistance services, enabling them to extend coverage to more families in need. Lastly, the indicators for community-level poverty outcomes, such as the presence of cholera, hepatitis or HIV/AIDS in the community in the last 5 years, or living in communities with problems related to access to education, environment and drug abuse, are closely associated with NE participation.

# **5.2 Panel Analysis:**

Following the large literature on the work disincentive effects of income transfer programs, we utilize the APS and static panel data models to explore the impact of household

> 19The data for social assistance fund allocations at the commune level were obtained for the 2002 and 2005 fiscal year from the Albanian Ministry of Labor and Social Affairs.

22
_Figure 6: Share of transfers by decile of the consumption distribution_ <!-- Start of picture text --> 25.00<br>20.00<br>15.00<br>10.00<br>5.00<br>0.00<br>1 2 3 4 5 6 7 8 9 10<br>Consumption decile<br>consumption<br>Transfer as share of<br><!-- End of picture text --> Source: RLMS (2011) Due to the different incidence of public transfers for households located in bottom 40 and top 60 of the income distribution, the “progressive” effect of the oil price shock shown above is reversed as poor families lose more (‐7.13) than the top 60 of the income distribution (‐6.82). (See Figure 7.) 21
<!-- Start of picture text --> 0.38<br>0.375<br>0.37<br>0.365<br>0.36<br>0.355<br>0.35<br>0.345<br>0.34<br>0.335<br>0.33<br>1999 2000 2001 2002 2003 2004 2005 2006 2007<br>Y ear<br><!-- End of picture text -->

**Figure 2. Trend of the fee income share.** The fee income share is the share of non-interest income in total operating income. This figure displays the trend of the fee income share from 1999 to 2007. The fee income share data are yearly averages. The data are from Bankscope.

58
||**Table 2: Alternative e**|**fficiency meas**|**ures**|||
|---|---|---|---|---|---|
||**(1)**|**(2)**|**(3)**|**(4)**|**(5)**|
|Dependent variable: Pure technical<br>efficiency|**Super**<br>**efficiency**|**Super**<br>**efficiency**<br>**(outliers**<br>**dropped)**|**BCC**<br>**efficiency**|**Bias**<br>**corrected**<br>**efficiency**|**FDH**<br>**efficiency**|
|Volatility in Occupancy*Number of|<br>-0.270***|-0.164**|-0.175***|-0.079**|-0.102**|
|<br>workers (logs)|<br>(0.085)|(0.063)|(0.057)|(0.029)|(0.038)|
|Volatility in Occupancy|0.783***|0.495**|0.539***|0.211**|0.310***|
||(0.231)|(0.190)|(0.165)|(0.082)|(0.107)|
|Number of workers (logs)|0.209**|0.110|0.078|0.009|0.115***|
||(0.096)|(0.083)|(0.078)|(0.040)|(0.039)|
|Central region Y:1 N:0|0.025|0.044|0.103|0.067*|0.098|
||(0.096)|(0.089)|(0.077)|(0.036)|(0.062)|
|Eastern region Y:1 N:0|<br>0.262***|<br>0.278***|<br>0.216***|<br>0.057|<br>0.082|
||(0.090)|(0.065)|(0.071)|(0.047)|(0.068)|
|Northern region Y:1 N:0|-0.096|0.063|0.023|-0.014|0.180*|
||(0.192)|(0.136)|(0.103)|(0.047)|(0.094)|
|Sabah & Sarawak Y:1 N:0|0.072|0.152*|0.143*|0.070*|0.139*|
||(0.114)|(0.080)|(0.070)|(0.034)|(0.074)|
|Age of firm (logs)|0.023|0.081*|0.072|0.023|0.034|
||(0.039)|(0.045)|(0.043)|(0.022)|(0.037)|
|Part of a chain Y:1 N:0|0.013|-0.148*|-0.056|-0.010|-0.116|
||(0.171)|(0.082)|(0.071)|(0.043)|(0.078)|
|Women's ownership (proportion)|-0.062|-0.106|0.010|0.029|0.250**|
||(0.264)|(0.202)|(0.206)|(0.122)|(0.104)|
|Finance major obstacle Y:1 N:0|-0.049|-0.023|0.046|0.024|0.031|
||(0.102)|(0.104)|(0.115)|(0.055)|(0.056)|
|Occupancy rate|0.141|0.102|0.144|0.029|0.226|
||(0.335)|(0.216)|(0.172)|(0.090)|(0.144)|
|Number of power outages|-0.002|-0.021|-0.015|-0.004|0.006|
||(0.033)|(0.024)|(0.022)|(0.011)|(0.008)|
|Largest owner is manager Y:1 N:0|-0.045|0.017|-0.055|0.002|-0.008|
||(0.074)|(0.068)|(0.053)|(0.032)|(0.053)|
|Website Y:1 N:0|<br>-0.083|<br>-0.055|<br>-0.069|<br>-0.024|<br>-0.054|
||(0.112)|(0.104)|(0.107)|(0.050)|(0.057)|
|Low competition Y:1 N:0|<br>0.010|<br>0.008|<br>0.007|<br>-0.014|<br>-0.121**|
||(0.118)|(0.069)|(0.059)|(0.024)|(0.049)|
|Intermediate competition Y:1 N:0|<br>0.074|<br>0.021|<br>0.048|<br>0.026|<br>0.027|
||(0.099)|(0.105)|(0.101)|(0.056)|(0.099)|
|Two-star hotel Y:1 N:0|<br>-0.104|<br>-0.108|<br>-0.078|<br>-0.013|<br>-0.012|
||(0.071)|(0.072)|(0.063)|(0.026)|(0.054)|
|Three-star hotel Y:1 N:0|<br>0.027|<br>0.024|<br>0.051|<br>0.040|<br>-0.104*|

39
- 35 -

from Appendix 1 equation (1.7b), V[X] = a {Vtyp] + u Vty]} = 30,000 {(82 x 81.62) + (3502 x .82) + (81.62 x .82) + (302 x 8 2)} S[X] = 30,000 x 713.7 = 21.4 x 106 cv[X] = .406.

> Step 6 Substitute these values for R, p, cy, and CX (and, say, A = 2) in equation (16),

P = 2(.406) ((.406)(.0066)/2 + (.4)(.09)} = 2(.406) (.00134 + .036)

**=** .030.

Step 7 So, the risk adjustment here is somewhat trivial and the appraiser, in retrospect, was not really assisted (or hindered) in the appraisal task through this consideration.

Other perspectives on the size of the adjustment can be gained by reference to the period returns. The absolute value of the year 5 adjustment is 52.8 x 106 x .03 = 1.58 x 106, and the certainty equivalent return is thus 51.22 x 106. Using this certainty equivalent in place of the expected return in years 5 through 20 yields a 'risk corrected' ERR of 1.99 percent which is about 100 x (2.25 - 1.99)/2.25 = 11.6 percent less than the expected ERR of 2.25 percent.

This minor adjustment magnitude is probably representative of the great majority of public projects, especially those reviewed by the World Bank. Naturally, the results can be made more 'interesting' (i.e., the economic consequences of risk can be made to seem more important) by enlarging some of the terms, especially CX but also R.
19 presented above for Panama are based on a three-year eligibility period, which is the practice currently adopted in Chile.

In the case of connections, the larger value of the subsidy payment make such schemes considerably more cost-effective. Thus, with a subsidy of USS$750 per eligible household, the administrative costs would only absorb 7% of the total expenditure.

Finally, it is important to note that the administrative burden of a water subsidy could be dramatically reduced if the scheme could be integrated with other subsidy measures operating within the same country. If eligibility criteria between subsidy schemes can be harmonized, the costs of conducting socio-economic assessments can be shared across a number of schemes. The relevance of this issue to the Panama case will be developed further in Section 6 below.

# **Incentive Effects**

A final concern in determining the value of a subsidy payment is the avoidance of the perverse incentives that can potentially be created by subsidy systems.

First, a subsidy which covers 100% of the costs of the service will eliminate incentives for the efficient use of water, and is likely to create a non-payment habit that may be difficult to break at a later date. Therefore, full-scale subsidies should be avoided in favor of schemes that cover only a proportion of the total costs. To strengthen payment incentives, the subsidy can be made contingent on the household contributing its own share of the bill. For example, in Chile, water subsidies are capped at 85% of the value of the bill and are only disbursed upon proof that the household has paid its share.

It is interesting to note that the principle of subsidizing less than the full value of the bill received widespread support from the Panamanian public when they were questioned in the survey conducted as part of the subsidy study. Table 5.2 reports answers to the question of whether subsidy beneficiaries should be required to make some financial contribution of their own towards the cost of water supply. Over 90% of those interviewed were in favor of this principle, including those who currently benefit from a subsidy payment that covers the entirety of their bill.

**Table 5.2: Responses to the Question: ',Should Those Who Receive Subsidies Themselves Be Required to Contribute a Proportion of the Total Bill?' (%)**

||**Yes**|**No**|**Don't know**|**Total**|
|---|---|---|---|---|
|Formnal residential users:|||||
|-with continuous service|93.4|5.2|1.4|100.0|
|-with intermittent service|92.3|6.9|0.7|100.0|
|Current subsidy beneficiaries|91.5|7.4|1.1|100.0|
|Informal or clandestine connections|94.3|5.1|0.6|100.0|
|Total|93.3|5.6|1.1|100.0|
<!-- Start of picture text --> 100000<br>,<br>#<br>80000 7<br>t<br>/<br>/<br>]<br>— 60000 i<br>Qo<br>2I<br>=]<br>> I<br>= 40000 I<br>I<br>I<br>4<br>7<br>20000 /<br>)<br>1980 1990 2000 2010 2020<br>Year<br>== Sporadic —— Systematic<br>----- Total<br><!-- End of picture text -->
supervisory power (borrower) in column 4, indicating that international banks avoid foreign subsidiary usage in case of greater official supervisory power in borrower countries. The foreign subsidiary and borrower country subsidiary shares vary positively with Monitoring (borrower) in regressions 4 and 5, as better financial market monitoring institutions in borrower countries appear to make borrower country subsidiary usage more attractive. In addition, the foreign subsidiary share is positively and significantly related to Creditor rights (borrower), and negatively and significantly to Time to enforce contracts (borrower). Overall, regression 4 provides evidence that foreign subsidiary usage is positively related to the quality of institutions in borrower countries as related to financial market monitoring, creditor rights, and the time to enforce contracts, while foreign subsidiary usage is negatively related to borrower country supervisory, power consistent with regulatory arbitrage.

Bank regulation potentially is endogenous to absolute and relative loan volumes. Borrowing countries experiencing large syndicated loan provision by local subsidiaries of international banks, could, for instance, increase the quality of regulation to discourage such credit provision. To mitigate potential endogeneity, we next re-estimate regressions 4-6 of Table 4 using instrumental variables (IVs), taking Capital regulation (borrower), Overall activity restrictions (borrower), Official supervisory power (borrower), and Monitoring (borrower) to be potentially endogenous. Following Houston et al. (2012, p. 1879), we employ instrumental variables that have been advanced in the literature as possible determinants of regulation. First, we use the time-varying means of the regulatory variables (excluding the pertinent country) to reflect possible ‘regulatory contagion’ (see DemirgucKunt and Detragiache, 2002).<sup>20</sup> Second, we use a dummy variable indicating that the central bank supervises banks for prudential purposes (from the World Bank regulation

> 20 <mark>Specifically, in case of a borrower-country regulatory variable, we instrument it by the mean of this variable for all borrower countries excluding the pertinent borrower country. In the regressions with bilateral data, in analogous fashion we construct the instruments for lender-country regulatory variables.</mark>

18
<!-- Start of picture text --> 05<br>0 freed ANT ots \<br>GP REL DR EL<br><!-- End of picture text --> <!-- Start of picture text --> 0.2 SI<br>K \<br>03<br>—_—s PO EL DR EL<br><!-- End of picture text --> <!-- Start of picture text --> 05 0.2 SI<br>K \<br>0 freed ANT ots \ 03<br>GP REL DR EL —_—s PO EL DR EL<br>0.35 0.05<br>03 0.045<br>0.04<br>0.25<br>0.035<br>0.2<br>0.03<br>0.15 0.025<br>O41 0.02<br>0.05 0.015<br>0.01<br>° a<br>-0.05<br>0<br>-0.1 LA<br>mG meEP DR mEL mTOT mG mEP DR EL mTOT<br><!-- End of picture text --> <!-- Start of picture text --> 0.05<br>0.045<br>0.04<br>0.035<br>0.03<br>0.025<br>0.02<br>0.015<br>0.01<br>0<br>LA<br>mG mEP DR EL mTOT<br><!-- End of picture text --> <!-- Start of picture text --> 0.35<br>03<br>0.25<br>0.2<br>0.15<br>O41<br>0.05<br>° a<br>-0.05<br>-0.1<br>mG meEP DR mEL mTOT<br><!-- End of picture text -->
# **Section 7: Liquidity and Diversification Requirements**

Section 7 of the 2011–12 survey includes nine main questions covering regulations on liquidity and diversification requirements, approximately half of which are comparable to the previous round of the survey.

Overall, 86 percent of the countries have rules or supervisory guidelines regarding contingency funding plans, including stress testing of banks’ liquidity management (Table A7). About three quarters of the jurisdictions that participated in the recent survey reported having regulatory rules or supervisory guidelines regarding diversification of funding sources of banks' liquidity management, requirements for the management of foreign currencies and regulatory minimum ratio on liquid assets. On the other hand, 55 percent of the countries have maturity mismatch/gap limit requirements.

There have been some notable changes between the current and previous rounds of the survey. For example, in 2010, 56 percent of countries reported having regulatory rules or supervisory guidelines regarding asset diversification, which was 10 percentage points higher than in 2005.<sup>13</sup> Furthermore, 28 percent of EMDEs in 2010, up from 11 percent in 2005, reported that they prohibited making loans to foreign borrowers. On this front, the share of the advanced economies dropped from a mere three percent in 2005 to zero percent 2010. Moreover, 99 percent of jurisdictions in 2010, a slight uptick from 97 percent in 2005, report having limits on their lending to a single borrower or group of inter-related borrowers. This slight increase was mainly driven by advanced economies. Finally, changes were also experienced in reserve requirements. While the share of countries with Central Bank reserve and/or deposit requirements declined slightly from 90 percent in 2005 to 86 percent in 2010, the percentage of countries requiring their banks to hold reserves in foreign currencies or other foreign-denominated instruments increased by 10 percentage points from 25 percent in 2005 to 35 percent in 2010.<sup>14</sup> While both of these changes were mainly driven by advanced economies, a notably higher percentage of EMDEs had such requirements in place in 2005 and 2010. These findings highlight the fact that ensuring financial stability through stricter reserve requirements has been more prevalent among EMDEs relative to advanced economies.

> 13 If we limit our analysis to only those countries that have responded to both surveys – the matched sample-, the increase is larger from 43 percent in 2005 to 57 percent in 2010.

> 14 Limiting our analysis only to those countries that have responded to both surveys, the increase is somewhat smaller from 29 percent in 2005 to 36 percent in 2010.

35
Agency (JICA), the German Development Bank (KfW) and the United Kingdom’s Department for International Development (DFID) - similarly summarize their self-evaluations in a single ‘outcome’ rating. Precisely due to their widespread availability and ease of harmonization, the use of such project outcome ratings is prevalent in the aid effectiveness literature.

However, there are several grounds for doubting whether these outcome ratings capture either donor contribution or the likelihood of sustained improvements in development outcomes. First, they are an aggregation of several subratings and therefore mask variance in the contribution of individual components or interventions. Second, by assessing primarily whether a project has achieved its stated objectives, they may encourage project designers to limit their ambition to what can be easily, and sometimes already has been, achieved.<sup>7</sup> Third, they can reorient time horizons to short-term outputs, which are easier to measure within the project life-cycle, over longer-term efforts to resolve core problems (Andrews 2021).

# **3. Methods**

# _3.1. Research Questions_

We seek to advance the existing literature by considering four questions. First, can any general statements be made about the impact of development aid on sector outcomes? Second, does consideration of aggregate project outcome ratings within each sector mediate the terms of that relationship? In other words, do outcome ratings provide information on the relationship between aid and outcomes? Third, can the application of novel econometric and machine learning techniques better detect associations between project characteristics and development outcomes? And finally, what can such methods illuminate about the characteristics of development projects associated with positive sector outcomes?

# _3.2. Data_

Data on sector outcomes and country characteristics are obtained from the World Development Indicators (WDI, World Bank 2021), covering 1990 _−_ 2015. For official development assistance (ODA) flows, we used the AidData Core

> 7This may explain the inability of previous researchers to explain more than 30 percent of the variance in outcome ratings. If every project defined objectives to achieve the highest rating, the correlation between ratings and project/country characteristics would be zero. IEG does assess the ‘Bank’s contribution’, defined as ‘the extent to which the services provided by the World Bank ensured quality at entry of the project and supported effective implementation through appropriate supervision.’ Its evaluation of project efficacy, or the extent to which outcomes were achieved, is also required to examine ‘whether the achieved outcomes can plausibly be attributed to the government program or project.’ But the first focuses largely on compliance with fiduciary and reporting requirements; while the second does not evaluate whether the objectives would have been achieved in the absence of the Bank’s involvement.

5
20 biased in favor of labor-intensive techniques of production. Some evidence of this is presented in Krueger (1975) in her study of the Indian automobile industry. The manufacturers she interviewed did not believe that there were any significant economies of scale to be exploited.

The crucial question with respect to the relevance of the new trade modelling to developing countries is not whether the markets are merely oligopolistic but whether the oligopolistic characteristics derive from economies of scale. After all, it is the economies of scale that enable an oligopolistic firm to reduce average costs sufficiently, as the scale of output increases, and thereby capture a larger share of the global profits. The evidence from the developing world on this count is clearly in the negative.

# 2. Economk Sirz

The small size of developing country markets makes strategic trade policy irrelevant on several grounds. First, the small size of domestic markets precludes the exploitation of scale economies in the domestic market making Krugman's import-protection-as-export-promotion argument irrelevant.

Second, as Krugman (1989) has argued, small size reduces the ability of developing country governments to play strategic games. This will be so because small countries are not typically the repositories of the global industries the capture of whose rents through strategic games is the focus of the new trade theory. And even if such global industries were based in a small country, the small size itself will severely detract from the ability of the country to act as a credible first-mover.

Third, because of their small size, developing countries stand to attract and, therefore, to lose more from foreign retaliation. Whatever might be said of the argument that their small size will actually induce the larger countries to be more concessionary as the cost to them will be small, and that they will