rafmacalaba/datause-encoder-data huggingface dataset:
District governments do seem to benefit from increased decentralization of construction after a level of about 40 percent, when the unit costs of construction decrease with increasing degrees of fiscal decentralization. This finding is consistent with the case of Korea, where there was an observed reduction in construction costs as a function of increasing degrees of decentralization 26. The gains in lower construction costs are not available for state governments, as unit costs of construction continue to increase with increasing degrees of decentralization (see figure 15). The rate of increase in construction costs at the state level, however, decreases with increasing degrees of decentralization, suggesting that there are indeed some benefits at higher levels of decentralization. We do not see any evidence of a transfer in costs across levels of government from these results.

**Table 14: Impact of Decentralization on Resource Costs for the Case of Germany**

|Variable|State-level Un|it Costs ($/km)|District-level U|nit Costs ($/km)|
|---|---|---|---|---|
||Maintenance|Construction|Maintenance|Construction|
|year|-0.0001||0.0007|-0,904|
||(-0.66)(.3)|(At||364|
|per capita GDP|||-0.09|. .. (.)|
||(2.|92) ($11)|~~(-0.53)|(.7|
|fiscal|0.004|0|3|0.12|
|decentralization'|(1.49)<br>|(..76)|6.6)(3..||
|fiscal|_.. 6.. 7Qq_|A00_-10.00|4-.||
|decentra<br>n|(1.7)|(1.33|(-||
|fiscal<br>_l.l_<br>decentralization|||Z9)<br>i=||
|Schleswigholstein|-0.002|:°10.00°1|°|2)|
||_(-1.50)_|(42)(0.65)(.||4<br>)|
|Niedersachsen|0.|-0.002|0.002|0.8|
||(2.21|)<br>(-1.11)|(1.33)|(36|
|Nordrheinwltoestfral|en<br>-0.002<br>(-1.29)|3|||
|Hessen|40|0<br>~|(.0||
|Rheinlandpfal||.0-9'||O000<br>30,|
|Saarland|0,0.0.1||005|.1|
|Badenwurttemberg|0.00005<br>(0.07)|-0040060.0<br>. . (.2.31|04<br>(..2.1.2||
|R-squared|0.<br>O87|0.95|0.95|0.87|

26 Note **that** Germany (66 percent) and Korea (64 percent) have about the same degree of fiscal decentralization of construction on average as shown in Table 1).

34
**Figure 6.  The change in non‐food deprivations**

<!-- Start of picture text --> Share of Respondents Who Face Deprivations<br>0.85<br>0.75<br>0.65<br>0.55<br>0.45<br>0.35<br>0.25<br>0.15<br>Water Primitive Energy No Municipal Employ Any Face Three or<br>Insufficient Source Waste Collection Food Coping Four<br>Strategy Deprivations at<br>Once<br>Before Blockade After Blockade<br><!-- End of picture text --> Source: WFP Mobile Phone Survey, November 2017.

**Table 3.  Changes in Food Coping Strategies Following the Blockade**

||Reduce<br>Number of<br>Meals<br>Dependent|Restrict<br>Consump<br>tion<br>Variable:|Borrow<br>to Pay for<br>Food|<br>Relied on<br>Less<br>Expensive<br>Food|Limit<br>Portion<br>Size|Water<br>Insufficient|Primitive<br>Energy<br>Source|No<br>Municipal<br>Waste<br>Service|Relied on<br>a Food<br>Coping<br>Strategy<br>for at<br>Least One<br>Day|<br> <br>Experienced<br>Deprivations<br>in at Least 3<br>Dimensions|
|---|---|---|---|---|---|---|---|---|---|---|
||(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|(9)|(10)|
|Post Ind.|<br>0.215**|0.373***|0.160*|0.186*|0.204*|0.061***|0.035**|0.048**|0.039***|0.097***|
||[0.105]|[0.107]|[0.089]|[0.108]|[0.109]|[0.020]|[0.016]|[0.020]|[0.013]|[0.020]|
|Obs.|2,422|2,422|2,422|2,422|2,422|2,422|2,422|2,422|2,422|2,422|

Notes: This table estimates how food coping strategies and household deprivations changed immediately following the imposition of the blockade. All specifications include governorate fixed effects. Robust standard errors are reported in parentheses; * denotes statistical significance at the 10 percent level, ** denotes statistical significance at the 5 percent level, and *** denotes statistical significance at the 1 percent level.

# **Conclusions**

This paper demonstrates that there is little correlation between the localized effect of violence and access to food, and that food access is significantly correlated with the blockage of ports during the conflict. These results have important implications for the regional targeting of food assistance, where it could be important to de‐emphasize indicators of violence in the determination of food assistance.

It is important to reiterate that these results do not suggest that violence has no impact on households. Rather these results provide information on how better to target households for assistance once the 18
<!-- Start of picture text --> Gam Debt Service Coverage Ratio Gam Debt-to-Equity Ratio ==@—=Net Profit Margin<br>9 20%<br>8 10%<br>/ 0%<br>10%<br>g° =<br>2’ 5 o<br>& -20% &<br>& A r=<br>2 -30% ©<br>& 3 a<br>iz 2 -40% ad@<br>|<br>-1 -70%<br>ongdG nm rtuHnewor wadcktierewttnnmnmwtunw hr wOworaooweidnomatw<br>amraioaraoaa»araanaaaaorancdcedcsdcesdc¢$dccdcecdeoeosdcded Bei dt ad ada<br>amraorarnrona>ara»a»aaaa»anmtdbddb=drstd$ ©oeoeodcodsd coe eo co coc & &<br>a cA A A Tt Tt ti Tt TD TAT NN NNN NNN NN NN NN ON OS<br><!-- End of picture text -->

<!-- Start of picture text --> — — —@—=<br>il<br><!-- End of picture text -->
- Lagakos, D., Moll, B., Porzio, T., Qian, N., and Schoellman, T. (2012). Experience Matters: Human Capital and Development Accounting. NBER Working Papers 18602.

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- Levinsohn, J. A., McLaren, Z., Shisana, O., and Zuma, K. (2011). HIV Status and Labor Market Participation in South Africa. Working Paper 16901, National Bureau of Economic Research.

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44
|||PRE Working P*pr Serbs||Contact|
|---|---|---|---|---|
||i|A<br>uthor<br>tor<br>panar|||
|WPS402|The GATT as International<br>Disciplin<br>Over Trade Restrictions: A Public<br>Choice Approach|e J. Michael Finger|March 1990|N. Artis<br>38010|
|WPS403|Innovative<br>Agricultural<br>Extension<br>for Women: A Case Study of<br>Cameroon|S. Tjip Walker|||
|WPS404|Chile's Labor Markets in an Era of<br>Adjustment|Luis A. R;viiros|April 1990|R. Luz<br>34303|
|WPS405|Investments<br>in Solid Waste<br>Management:<br>Opportunities<br>for<br>Environmental<br>Improvement|Carl Bartone<br>Janis Bemrtein<br>Frederick Wright|April 1990|S. Cumine<br>33735|
|WPS406|Township,<br>Village, and Private<br>Industry in China's Economic<br>Reform|William Byrd<br>Alan Gelb|April 1990|K. Chan<br>38966|
|WPS407|Public Enterprise<br>Reform:<br>A Challenge<br>for the World Bank|Ahmed Galal|April 1990|G. Orraca-Tetteh<br>37646|
|WPS408|Methodological<br>Issues in Evaluating<br>Debt-Reducing<br>Deals|Stijn Claessens<br>Ishac Diwan|||
|WPS409|Financial Policy and Corporate<br>Investment<br>in Imperfect Capital<br>Markets: The Case of Korea|Mansoor<br>Dailami|April 1990|M. Raggambi<br>37657|
|WPS41<br>0|The Cost of Capital and Investmen<br>in Developing<br>Countries|t Alan Auerbach|April 1990|A Bhalla<br>37699|
|WPS411|Institutional<br>Dimensions<br>of Poverty<br>Reduction|Lawrence<br>F. Salmen|May 1990|E. Madrona<br>37496|
|WPS412|Exchange<br>Rate Policy in Developin<br>Countries|g W. Max Corden|May 1990|M. Corden<br>39175|
|WPS413|Supporting Safe Motherhood:<br>A Review of Financial<br>Trends<br>Full Report|L. M. Howard|May 1990|S. Ainsworth<br>31091|
|WPS414|Supporting Safe Motherhood:<br>A Review of Financial Trends<br>Summary|L. M. Howard|May 1990|S. Ainsworth<br>31091|
|WPS415|How Good (or Bad) are Country<br>Projections?|Norman Hicks<br>Michel Vaugeois|April 1990|M. Berg<br>31058|
**Policy Research**

# **Country Operallons**

WPS 1028 This paper-a product of the Latin America and the Caribbean Technical Department-is part of a larger effort to document poverty conditions in the region. Copies of the paper are available free from the World Bank, 1818 H Street NW, Washington, DC 20433. Please contact Liliana Longo, room 14-187, extension 39244 (November 1992, 26 pages).

After reviewing the literature on repetition (students repeating grades in school) in developing countries, Patrinos and Psacharopoulos examine factors related to repetition in Bolivia and Guatemala. They develop a model to estimate the incidence and determinants of repetition. They use multivariate logistic regression analysis to estimate the determinants of repetition, using the results in simulations to determine probabilities of who is more likely to repeat.

Their empirical analysis shows that certain populations are more likely to repeat a grade: children from less wealthy households and children of indigenous origins. This suggests that any targeting activities could be directed to the poor and could have an indigenous component, such as bilingual education.

**The Policy Research Working PaperoSeries disse oinates th frdings of work mnder way in theBark An objectiveof the series is to get these rindings out quickly, even if presentations are less than fuilly polished. The findings, interprctations,** and **conclusions in these papers do not necessarily represent of ficial Bank policy.**

**Froduced by the Policy Research Dissemination Center**
**Figure 15: Indicators related to social capital and collective action in the Dominican Republic**

||Rank (out<br>of 24)|DR (0-100<br>scale)|Regional<br>Average|
|---|---|---|---|
|Interpersonal Trust|15|57.7|59.6|
|**Civilparticipation**||||
|Religious Groups|4|60.5|43.1|
|Parents' Associations|6|27.1|22|
|Committees for CommunityImprovement|1|25|14.1|
|Professional Associations|8|8.3|7.5|
|Women's Associations|4|13.3|8.7|
|**Political activism**||||
|Protest Participation|19|5.4|8.0|
|Electoral Participation|12|76.1|73.4|
|Interest inpolitics|5|44.5|37.8|
|Percentage Attemptingto Persuade Others|10|33.5|31.5|
|Percentage Who Worked For Candidates|1|19.9|11|
|**Localgovernment**||||
|Attended a Municipal Meeting|1|27.3|11.2|
|Demand-Makingon Municipal Government|8|15.1|12|
|Satisfaction with Local Government Services<br>Source: Americas Barometer 2010,Seligson and Smith,2010|20|48.8|51.8|

Source: Americas Barometer 2010, Seligson and Smith, 2010 Red: indicator for the DR below regional average; green, above regional average As we have seen, the case of the Dominican Republic is paradoxical. On the one hand, Dominican population registers a relatively high level of associative participation and approval for democracy compared to other countries in Latin America and the Caribbean (Espinal and Morgan, 2008). On the other hand, however, just 15% of the Dominicans think that the government acts on behalf of the whole population and general welfare<sup>14</sup> , the lowest value in the region. Moreover, citizens have a high perception of corruption (see Seligson and Smith 2010:72) and they consider that the quality of public services is poor. Only 28% of the population believes that public policies improve living conditions. Confidence in different institutional bodies of the DR is, at best, intermediate if we compare to the regional average, with the army and the central government recording the lowest levels of trust. Therefore, it seems that civic engagement is not translated into effective coalition building for reforms and improvement in the DR welfare state, which in turn provokes low levels of institutional trust.

> 14 Latinobarómetro, 2010

[24]
The following Tables A10 and A11 relate to estimation results from the synthetic panel methodology and show the upper and lower bound on poverty transitions between two different time periods. Results show that for the first panel, the majority of bounds capture the true value, with the exception of three transitions for models 1 and 3 (in gray). For the second panel, all estimated bounds are able to “sandwich” the true panel value across all specified models. These results, along with other validation exercises for other countries, provide strong support in that the analysis carried out in this paper captures, to some extent, the true mobility patterns observed in the country.

**Table A10.** Panel 1 to 4 (331 observations, only sample 1), years 1999 to 2002

|||**mo**|**del 1**|**m**|**odel 2**|**m**|**odel 3**|**m**|**odel 4**|
|---|---|---|---|---|---|---|---|---|---|
|**True**<br>**transiti**<br>**ons**<br>**(sample**<br>**0)**|**Transition**|**Lower**<br>**bound**|**Upper**<br>**bound**|**Lower**<br>**bound**|**Upper**<br>**bound**|**Lower**<br>**bound**|**Upper**<br>**bound**|**Lower**<br>**bound**|**Upper**<br>**bound**|
|**45,8 **|Poor topoor|59,9|41,6|55,9|41,4|78,9|65,2|58,8|44,6|
|**36,1 **|Poor to non<br>poor|21,3|29,6|25,3|39,8|2,3|16,0|22,4|36,6|
|**6,0 **|Non poor to<br>poor|0,0|8,6|0,0|8,1|6,0|13,6|0,8|8,1|
|**12,1 **|Non poor to<br>nonpoor|18,8|10,2|18,8|10,7|12,8|5,2|18,1|10,7|
||R-squared|0,11||0,22||0,25||0,27||

**Table A11.** Panel 3 to 6 (300 observations, only sample 1), years 2001 to 2004

|||**mo**|**del 1**|**m**|**odel 2**|**m**|**odel 3**|**m**|**odel 4**|
|---|---|---|---|---|---|---|---|---|---|
|**True**<br>**transiti**<br>**ons**<br>**(sample**<br>**0)**|**Transition**|**Lower**<br>**bound**|**Upper**<br>**bound**|**Lower**<br>**bound**|**Upper**<br>**bound**|**Lower**<br>**bound**|**Upper**<br>**bound**|**Lower**<br>**bound**|**Upper**<br>**bound**|
|**45,8 **|Poor topoor|55,1|35,4|53,7|38,0|62,0|44,2|59,2|39,0|
|**28,5 **|Poor<br>to<br>non<br>poor|21,8|41,5|23,2|38,9|14,9|32,7|17,7|38,0|
|**3,6 **|Non<br>poor<br>to<br>poor|0,5|9,0|0,5|7,6|0,6|10,0|0,9|9,2|
|**22,1 **|Non<br>poor<br>to<br>nonpoor|22,5|14,0|22,6|15,5|22,4|13,1|22,2|13,9|
||R-squared|0,19||0,28||0,27||0,25||

44
_How Fan HE Oshna ladwauy Groww? 39_

# TABLE 14: TRuAL **CALcuLATiON** OF zNzRGY **CONSUWnON ANUD PRoDucTIVIY FOR COLLECTIVE** INDUSTRY (INCLUDING NON-INDEPENDENT UNITS AND "OTMERN OwNERsH FORUS) 1980 AND 1985 (continuaton)

# 2. Using Pubbshed GVIO Figures

|Branch|Energy<br>10000<br>1980|Cons.<br>t<br>atd coal<br>1985|OVIO<br>1980|Yi P80<br>1985|Ton**st**<br>10000y<br>1980|**d**coal per<br>uffGVIO<br>1985|%Rise<br>GVIO/E<br>1980/85|
|---|---|---|---|---|---|---|---|
|1|1325|1477|22.51|62.90|_58.85_|23.48|150.62|
|2|_-5S56_|-6616|1.65|4.44|-3372.19|-1490.09|126.31|
|3|13|392|18.69|35.66|0.70|10.99|-93.67|
|4|-224|-260|1.23|3.18|-182.11|-81.76|122.74|
|5|2129|2311|103.39|238.08|20.59|9.71|112.14|
|6|1663|1925|313.5'|723.80|5.30|2.66|99.42|
|7|1441|2519|79.93|163.08|18.03|15.45|16.72|
|8|134|131|26.18|48.48|5.12|2.70|89.39|
|9|391|509|3S.60|108.00|10.93|4.71|133.03|
|10|719|963|96.50|354.55|7.45|2.72|174.33|
|11|41|48|100.83|_154.S0_|0.41|0.31|30.88|
|12|46|56|28.26|45.32|1.63|1.24|31.71|
|13|300|434|51.44|21.99|5.83|19.74|-70.45|
|14|-14|66|9.84|111.53|-1.42|0.59|-340.43|
|15|12S4|1738|71.41|99.74|17.56|17.43|0.78|
|Sum|3662|5693|961.01|2175.25|3.81|2.62|45.60|
9 one-quarter over that period (figure 2). But not all the re-instrumentation is towards less production- and trade-distorting measures. Of particular note is the growth in non-tariff import barriers ostensibly for food safety or environmental reasons. Two cases that have already been subject to WTO dispute settlement are the EU’s restrictions on imports of beef from cattle that have been fed growth hormones, and of food and feed products containing genetically modified organisms (GMOs). In both cases the EU was found by the WTO’s panel and appellate body to be not in conformity with its obligations, yet neither case has been settled to the satisfaction of the complainants.

As for trade between high-income and developing countries, the EU claims leadership in providing non-reciprocal preferential access to its markets for its former colonies in Africa, the Caribbean and the Pacific (ACP) under the Cotonou Agreement. Earlier this decade it also began providing duty-free and quota-free access to its markets for ‘everything but arms’ to UN-designated Least Developed Countries (LDCs), although it also excluded services and it continues to delay the opening of three sensitive food markets (bananas, rice and sugar). These measures _may_ help the better-off ACP and LDC farmers with a marketable surplus although, in the case of ACP supplies subject still to quotas, most of the benefits accrue to the holders of EU import quotas (who are more likely to be from a European than an ACP country). But these preferential agreements necessarily are at the expense of very many more equally poor exporters in other (nonACP, non-LDC) developing countries including China, Indonesia, India, Pakistan and Vietnam. Whether they are a net help to preference-receiving and other developing countries is an empirical question that can only be answered with an empirical model that incorporates all those trade preferences in its protection database.
interpolation, thus both increasing the mean and changing inequality. We call this adjustment “top heavy adjustment with Pareto tail.” We justify the adjustment of the survey mean to national accounts consumption on the grounds of missing top incomes. This is however open to criticism. It might be argued that some elements of national accounts consumption should (1) be excluded altogether, or (2) spread more widely along the distribution than the top 10%. For example, some of the discrepancy between national accounts consumption and household surveys is related to differences in definition, such as the inclusion of expenditures by non-profit institutions serving households (NPISH) or imputed consumption of collectively provided goods.<sup>24</sup> We ought to subtract these components from the national accounts consumption but sufficiently detailed data are not available separately for a large number of countries. Other sources of the discrepancy, such as imputed rents of owneroccupiers in the national accounts, could be included (if they are not estimated by household surveys), but should be spread further along the distribution than just the top 10%.<sup>25</sup> For these reasons our estimates should be seen as an approximate first step, in the absence of a more careful analysis using unit-record data.

> 24 According to Deaton (2005), NPISH consumption accounted for 3.9% of total consumption in the UK in 2001, up from 2.1% in 1970. In addition, he argues that this share might be even higher in poor countries, although there exist no data.

> 25 Deaton (2001) argues that in India approximately half of the gap between national accounts consumption and household surveys is due to imputed rents.

15
# **2.2 Data**

We obtained data on 1,883 SMEs that applied for a working capital loan with our partner bank, from two sources: administrative data from our partner bank and Equifax Peru. The administrative data include the EFL score and the date when the SME applied for the loan, as well as the applicant’s age, gender, business sales, and whether or not our partner bank approved them for a loan. The applicants in our sample were on average 39 years old and 50 percent of them were female. Average annual business revenues were about US$12,000 (see Column 1 in Table 1). In addition, for each loan applicant, the data include the national ID number (DNI) and, if their business is registered under the business name instead of the individual’s name, it also includes the business’s tax payer number (RUC).<sup>2</sup> Our second data source is Equifax Peru, the largest credit bureau in the country. For the DNIs and RUCs in the EFL data, we purchased five years of monthly information on borrowing from regulated financial institutions, covering the period from May 2011 to April 2016.<sup>3</sup> Equifax collects this information from the Peruvian Bank Supervisor’s (SBS) credit registry ( _Central de Riesgos_ ). SBS collects data directly from all regulated financial institutions monthly, covering the universe of commercial banks, as well as all regulated NBFIs. For each ID number in any given month, we obtained the total amount borrowed (current and delinquent) from each SBS supervised financial institution in Peru, for the three loan types most relevant in our sample: microloans, loans to small firms, loans to medium firms. If a borrower has more than one loan of the same type with the same institution, Equifax reports only the sum of these loans, with no information on how many loans constitute this total amount.

Our primary outcome of interest is whether loan applicants took out a new loan in the six months following their application to our partner bank. We measure loan take-up

> 2 We originally had 1,909 SMEs in the data. All provided their DNI and 1,327 also provided an RUC. However, for 20 SMEs, the DNIs and RUCs are inconsistent with each other, suggesting typos. We drop these observations from the sample to avoid using wrong information from our second data source. We also drop 6 observations where two DNIs reported the same RUC, that is, three SMEs where two co-owners seem to each have applied for a loan. In these cases, it is not possible to cleanly assign an EFL score to the SME as the unit of observation. Thus, we end up with a sample of 1,883 SMEs. The fraction of the sample dropped is not significantly different below and above the EFL threshold. 3 By law, Equifax is not allowed to provide data that are older than five years.

7