rafmacalaba/datause-encoder-data huggingface dataset:
Policy Research Working Paper 8384

# **Abstract**

Most evaluations of public works programs in developing countries study their effects on poverty reduction and other labor market outcomes (job creation, earnings, and participation). However, very few look at other collateral effects, such as the incidence of violence. Between 2009 and 2014, El Salvador implemented the Temporary Income Support Program, which aimed to guarantee a temporary minimum level of income to extremely poor urban families for six months, as well as provide beneficiaries with experience in social and productive activities at the municipal level. Making use of a panel data set at the municipal level for 2007 to 2014, with monthly data on different types of crime rates and social program benefits by municipalities, this paper assesses the effects of the program on crime rates in municipalities in El Salvador. There are several possible channels through which the Temporary Income Support Program can affect crime. Since the program is associated with cash transfers to beneficiaries, a reduction in economically motivated crimes is expected (income effect). But since the program enforces work requirements and community participation, this could generate a negative impact on crime, because the beneficiaries will have less time to commit crime and because of community deterrence effects. Overall, the paper finds a robust and significant negative impact of the Temporary Income Support Program on most types of crimes in the municipalities with the intervention. Moreover, the negative effects of the program on some types of crime rates hold several years after participation. Positive spillover effects for municipalities hold within a radius of 50 kilometers.

This paper is a product of the Social Protection and Labor Global Practice. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The authors may be contacted at pacosta@worldbank.org and emonsalvemontiel@worldbank.org.

_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 views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
<!-- Start of picture text --> V.3 Emerging market credit standards have been V.4 Local and international funding conditions for<br>tightening since 2011Q1. Demand slowed down and is banks in emerging markets deteriorated and only<br>virtually stagnant since 2011Q4 stabilized as recently as 2012Q3<br>Emerging Market Credit Standards and Demand Emerging Market Funding Conditions<br>Diffusion index, below 50 indicates tightening relative to Diffusion index, below 50 indicates tightening relative<br>previous quarter to previous quarter<br>65 80<br>70<br>60<br>60<br>55<br>50<br>50<br>40<br>45<br>30<br>40 20<br>Credit Standards Demand for Loans Local International<br>Source: IIF Lending Survey 2013Q1 Source: IIF Lending Survey 2013Q1<br><!-- End of picture text -->

# **VI. European Bank Lending Activity outside the Euro Area**

**As part of their pre-crisis expansion outside Europe, European banks regularly extended more new loans outside the Euro Area than within** (Exhibit VI.1). Indeed, consolidated foreign claims<sup>33</sup> of European banks to EMDEs experienced extremely high pre-crisis annual growth rates of over 40 percent while they reached over 25 percent to other advanced economies (Exhibit VI.2). Particularly in certain EMDEs, European banks have come to play a critical role in financial markets exposing these countries vulnerable to European shocks.

**As European credit conditions weakened, European banks disproportionately scaled back their external lending flows, especially in 2008 when they turned deeply negative (Exhibit VI.1). Moreover, as the financial crisis spread and the global economy slowed down, growth rates of European claims on EMDEs have recently turned negative again.** As a result of European bank retrenchment, their total foreign claims outside Europe have been falling significantly since their $10 trillion peak in 2008 to $8 trillion, mainly driven by a decline in lending operations to other advanced countries (Exhibit I.4). Overall, European claims on EMDEs have been more resilient relative to developed countries in part because EMDEs were initially not as much affected by financial turmoil in developed financial markets. Moreover, EMDEs are often considered to be growth markets for European banks.

> 33 Consolidated foreign claims include cross-border claims and claims of foreign affiliates in all currencies. Parent claims on foreign affiliates are netted out.

22
**Table 13. Cross section, Roads, regional dummies interactions.**

||(1)|(2)|(3)|(4)|
|---|---|---|---|---|
||OLS|OLS|2SLS|2SLS|
||pcGDPgrowth|pcGDPgrowth|pcGDPgrowth|pcGDPgrowth|
|Constant|-3.045|-1.686|-2.085|2.604|
||(1.043)***|(1.011)|(2.169)|(7.157)|
|GDPpc71|-0.000|-0.000|-0.000|-0.001|
||(0.000)|(0.000)|(0.000)|(0.001)|
|prim_expen_70|-0.043|-0.062|-0.062|-0.087|
||(0.036)|(0.034)*|(0.058)|(0.084)|
|second_expen_70|0.002|0.002|0.002|0.001|
||(0.002)|(0.001)|(0.003)|(0.004)|
|Invt_GDP7195|0.236|0.209|0.187|0.097|
||(0.048)***|(0.043)***|(0.109)*|(0.196)|
|pavroads7195|-0.101|4.250|0.353|-8.633|
||(0.350)|(1.621)**|(0.480)|(10.902)|
|EA*pavroads7195|1.746||2.914||
||(0.891)*||(4.421)||
|LI*pavroads7195||-6.112||0.000|
|||(1.736)***||(0.000)|
|MI*pavroads7195||-4.037||9.525|
|||(1.461)***||(11.397)|
|Observations|51|51|41|41|
|R-squared|0.59|0.65|||
|Wu-Hausman F test, p-<br>value|||0.29|0.32|

Robust standard errors in parentheses. * significant at 10%; ** significant at 5%; *** significant at 1%. Regional dummies: EA (East Asia), LI (low income countries), MI (middle income countries). Instruments: see Table 3 and 4.

33
sexual activity, and risky sexual behavior. The evidence presented here suggests that as girls and young women returned to (or stayed in) school, they significantly delayed the onset (and, for those already sexually active, reduced the frequency) of their sexual activity. The program also delayed marriage – which is the main alternative for schooling for young women in Malawi – and reduced the likelihood of becoming pregnant. As the treatment/control differences in schooling become starker during the second year of the program, the treatment impacts on marriage, fertility, and risky sexual behavior are likely to become stronger.

One should not assume that the changes in self-reported sexual behavior will result in a decline in HIV incidence among this cohort of program beneficiaries. Future rounds of household survey and Biomarker data collection will shed light on these questions. For now, however, schooling CCTs for young women in the context of poor Sub-Saharan countries with high HIV rates seem like “win-win” programs, as they may not only increase schooling for young women, but also significantly reduce their risk of HIV infection. Furthermore, increases in age at first marriage and pregnancy, as well as improved educational attainment may lead to improved outcomes for the next generation, as there are a host of negative externalities for children that are associated with early marriage, such as higher child mortality or lower educational attainment (Morrison and Sabarwal, 2008). The evidence presented in this paper provides impetus for the expansion of CCT programs (which already cover much of Latin America) to Sub-Saharan Africa.

21
- 18 -

# Table 6: Changes In Productive Assets

|% Who Own|Gong<br>(N-|zhullng<br>200)|T<br>(N-2|al<br>00)|Jur<br>(N-|ong<br>199)|Xlajla<br>(N-20|ng<br>0)|
|---|---|---|---|---|---|---|---|---|
||1983|1987|1983|1987|1983|1987|1984|1988|
|Tractor|1|9.5|0|0|3.5|8.0|4.0|5.5|
|Truck/boat|0|0.5|4.5|<br>26.0|0|0|0|0|
|Pump engine|1|2|0|1.5|<br>6|11.5|0.5|<br>1.5|
|Thresher|0|3|0|0.5|<br>2.5|<br>12|92.0|97.0|
|Buffalo/oxen|5|19|0|3.0|53|77|94.5|92.5|
|Pigs|81|66|86.5|66.5|85|84.5|97.5|98.5|
|Other anknals|15|30|.5|0|1.5|0|0.5|0.5|
|Average value<br>per household<br>(yuan) a/|570|1476|250|577|403|914|1060<br>2|195|

a/ The values are not deflated. The price Index for agricultural equipment rose by 15 percent between 1983/4 and 1987/8.
**Table 1.  Regressions with Country and Year Fixed Effects**

|Dependent Variables:|GDP_perca|p_gwth|Ag ValAdd|Growth<br>|Ind_ValA|dd P|overty_hea|dcount|
|---|---|---|---|---|---|---|---|---|
||(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|
|WASP_plus1|-1.82<br>(1.08)*||0.61<br>(1.17)||-0.15<br>(0.27)||-2.83<br>(25.90)||
|WASP_minus1|-2.69||-0.85||-0.20||3.28||
||(0.98)***||(1.04)||(0.24)||(18.44)||
|Temp|0.08<br>(0.32)||0.13<br>(0.33)||0.04<br>(0.08)||-1.71<br>(2.70)||
|WASP_plus1 (lag)||-2.86<br>(1.11)**||0.54<br>(1.18)||-0.56<br>(0.27)**||104.19<br>(105.41)|
|WASP_minus1 (lag)||-1.78<br>(1.01)*||0.87<br>(1.04)||-0.36<br>(0.24)||68.67<br>(47.07)|
|Temp (lag)||-0.06<br>(0.10)||-0.29<br>(0.17)*||-0.06<br>(0.08)||15.58<br>(10.53)|
|Observations|1686|1677|1418|1416|1098|1117|59|57|
|Countries|133|137|120|125|105|105|42|40|
|R-squared|0.05|0.07|0.18|0.16|0.05|0.06|0.94|0.88|

Notes: Standard errors are clustered at the country level. Standard errors in parentheses * significant at 10%; ** significant at 5%; *** significant at 1%. The WASP_plus1_1, WASP_minus1_1 and Temp_1 variables are lagged by one year.

The results from the specification with fixed country and year effects are presented in Table 2. These are the most robust model specifications and therefore the most meaningful results. The model with temperature and precipitation as the two independent variables showed temperature to be significant at the 95% level and precipitation at the 90% level. Interestingly, the sign of the regression coefficients were positive in both cases. The sign implies that a warmer year coincides with higher economic growth for the countries of the world, and similarly for (more) precipitation. However, when the WASP variables were included, temperature was no longer significant. Instead, the WASP(-1) variable was significant at the 99% confidence level and the WASP(+1) variable was significant at the 90% level. In both cases, the regression coefficients were negative, indicating that a greater area of a country in drought (WASP(-1)) coincided with less (or negative) economic growth,. The coefficients indicate that a 1 % increase in the fraction of a country’s area undergoing drought causes a 2.7 reduction in GDP growth for a given year. More area with anomalously high rainfall or flooding (WASP(+1)) also coincided with reduced economic 13
- 15 -

**Figure** 8: **Contractual savings portfolio distribution** (OECD countries)

<!-- Start of picture text --> 100% -<br>7 E fl U<br>20<br>80° i .4 263 24 27 30 3<br>70%<br>60%<br>3e8 3 29 2 2 5 22 19<br>50%' X3 3: g<br>40%<br>30%<br>20%31 m 38<br>10%<br>-44 3 -3 4 P 4 7;743 4<br>1982 1984 1986 1988 1990 1992 1994 1996<br>l Cash-anddepo.91 U Bills and bd8 03Loans 0 Sha-es *01her<br><!-- End of picture text -->

**Source:** 1998 OECD Institutional Investors Statistical Yearbook and WB institutional investors database.

**Figure 9: Contractual savings portfolio distribution (non-OECD countries)**

<!-- Start of picture text --> 100% 2 1 2-i2 14<br>90% 4 _,,,, __29 4<br>80% - 4~~~~~~~~~ l ~~~28<br>70% 3<br>50%<br>49% -<br>40%-C5<br>30%<br>20%<br>10%<br>0%3 3:_<br>1982 1984 1986 1988 1990 1992 1994 1996<br>l CCash and depoas 38 *ilsan050n0998 OLoans 0S6ares 301951<br><!-- End of picture text -->

**Source:** 1998 OECD Institutional Investors Statistical Yearbook and WB institutional investors database.

In general, not only is the portfolio distribution of contractual savings more skewed towards assets such as stocks and bonds, it is also more skewed towards longterm assets. For instance, Figure 10 shows how the share of short term loans in non-life insurance companies' portfolios increased from about 25 percent to almost 40 percent between 1982 and 1996, while for contractual savings it remained well below 10 percent.
# **V. Misalignment and its sources**

In this section we estimate the equilibrium real exchange rate for the Argentine peso. The sample covers the period 1960-2001 and the data are annual. We first describe the construction of the series and then present the results.

# **_V.1 Data_**

Empirical estimation of our model requires data on three variables: the real effective exchange rate _q_ , the stock of net foreign assets as a percentage of GNP _f_ , and relative sectoral productivity _n_ . Following the majority of the literature, we use a CPI-based index of the real effective exchange rate (henceforth REER), whose weights are based on Argentina’s bilateral trade flows averaged over the period 1998-2000. We construct weights for 40 trading partners which combined account for 90 percent of Argentina’s trade. Figure 4 reports the weights corresponding to a higher level of aggregation distinguishing only five trading partners: Europe, United States, Asia, Mercosur and the rest of the World (ROW). Mercosur is Argentina’s main trading partner, accounting for almost 40 percent of her total trade. Within Mercosur, Brazil is the leading trading partner, with about 30 percent of Argentina’s trade. Next comes Europe, with 25 percent (of which 23 percent corresponds to the Euro area). The U.S. follows with 17 percent, and finally the rest of the world accounts for about 5 percent of Argentina’s trade.

The stock of net foreign assets _F_ can be computed by accumulating past current account balances: Of course, to implement this procedure we still need an initial value _F_ 0. We take it from Broner et al. (1998), who estimate _F_ 1965 at US$-3,853 million; _f_ is then computed as the ratio of _F_ to the U.S. dollar-denominated GNP.

Finally, data on sectoral productivity or even for overall productivity are not available for Argentina and many of the partner countries for the sample period. However, we take advantage of the already robust evidence of a long-run relation between sectoral productivity and sectoral prices (see, among others, Canzoneri et al. (1999), Alberola and Tyrväinen (1999)) to use an index of relative sectoral prices as a proxy for sectoral productivities. More precisely, we use the comparative index of the relative price of nontradable versus tradable goods devised by Kakkar and Ogaki (1999) for estimation purposes: we proxy _n_ with the (log) ratio of Argentina’s consumer price index (CPI) to the wholesale price index (WPI), relative to the corresponding ratio for Argentina’s trading partners. The trade weights used in the computation are those used to construct the real effective exchange rate.

# **_V.2 Econometric Results_**

Table I reports the results of Johansen cointegration tests for Argentina using a VAR of order 3. Inspection of the table indicates that on the basis of the maximal eigenvalue test 13
varies, I only include those that are precise to the village or subregion location and exclude those that are only recorded at the regional level.

LRA attacks are recorded using a binary variable for whether or not a particular community was attacked by rebels in 2004. Insecurity is a binary variable for whether “any section of the community found it difficult to cultivate their land in 2004 because of insecurity.”<sup>14</sup> Variables for the distance from each community nearest to rebel attacks in each year are created from the NUS and the ACLED data sets. Specifically, these measure the distance (in arc degrees) from community _i_ to the nearest attacked community (excluding community _i_ ). For the NUS data, these are created for the rebel attacks in 2004, 1999, and 1992. The ACLED data contain information on LRA attacks for each year from 1997 to 2003.

On average, communities were relatively close to attacks by the LRA as the average distance varied between 0.20 and 0.90 decimal degrees (approximately 22 and 100 kilometers, respectively). For the closest communities, this was as low as approximately 3.6 kilometers. Moreover, close to one third of the sample communities were attacked in 2004. A similar number of communities reported being insecure.

Consumption is measured as the natural log of per capita annual total household consumption.<sup>15,16</sup> Livestock holding are aggregated into tropical livestock units<sup>17</sup> (TLU). Household members are defined as all household members who have lived in the house 6 months

> 14. The full text of the questions as well as full descriptive statistics of the variables are provided the appendix (tables S.1–S.3).

> 15. The variable is calculated by summing the following consumption sections: food consumption (purchased, consumption of home production, and free), non-durable goods and frequently purchased services (including rent), semi-durable and durable goods and services, and nonconsumption expenditure (such as remittances and taxes). 16. Total household consumption includes all the typical consumption categories, including the consumption of home produce and food aid. The recall periods vary across the components of consumption from the past week for food to the past year for semidurables and durable goods and services as well as for nonconsumption expenditure (such as taxes and remittances). The aggregate consumption annualizes components and assumes that behavior over the recall period is representative for the entire year.

> 17. Tropical livestock units are aggregated as follows: cattle=0.70, sheep and goats=0.10, pigs=0.20, poultry=0.01.

10
sample was to conduct a census of traders in the selected markets. In Benin, this task proved extremely difficult given the very large number of retailers in the major markets and the mobility of traders between market days. Thus, the process followed in Benin to conduct a census of traders was to obtain lists of traders from ONASA (Office National d'Appui a la Securite Alimentaire), and the regional bureaus of Ministry of Commerce. In addition to these lists, the survey team undertook a count of traders present on the market day, and used these three sources of information to construct a census from which a sample was randomly draw, resulting in a total sample of 663 food crop and cash crop traders.

In Malawi, a reconnaissance survey of traders was conducted in July-August 1999 in order to count and identify traders according to their status (independent, buying agent, or selling agent), their level (retail or wholesale), and the types of products they traded. The information on the name, type, and location of traders from the reconnaissance survey were entered into a spreadsheet and the sample was drawn randomly from the census data using a computer algorithm. Thus, for the three types of products, a total sample of 738 traders was interviewed in Malawi. Thus, for both countries, the total sample of independent traders is 1371.

# _2.3 Survey Instrument_

Initially, a questionnaire was designed for independent agricultural traders in both countries. During the course of field visits, the questionnaire was tailored to the specific market conditions of each country, while at the same time maintaining the same structure and format across the two countries. The coverage of the survey instrument is not only very broad, but also innovative in the type of infornation gathered. Thus, the trader questionnaire covered the following main areas: (a) defining the trading enterprise; (b) trader characteristics; (c) factors of productions and operating costs; (d) trading activities and marketing costs; (e) relationships and coordination costs. One innovation in the survey instrument is that, in addition to annually constructing volumes of sales, purchases, and storage, the questionnaire also addresses specific arbitrage behavior on the last completed wholesale transaction. Moreover, in contrast to typical market surveys which focus on trading activities and business assets, data were collected on search behavior and 6
The policy implications of these results are of significant interest. On the one hand, our analysis suggests that it is indeed appropriate for the WTO _Agreement on TBTs_ to champion the use of international standards whenever possible. If Members follow this path, they can help limit the negative effects of standardization and harmonization on outsiders—and in particular, on developing countries. However, our evidence—combined with existing results due to Swann et al. (1996) and Moenius (2004, 2006)—suggests that it is not just mandatory technical regulations that can have significant trade impacts, but voluntary product standards as well. As previously noted, the WTO’s treatment of these two groups of norms is asymmetric: technical regulations are subject to relatively stringent requirements that are directly enforceable through WTO dispute settlement proceedings, whereas the position for product standards is considerably more blurred. There may well be a case to be made in the future for redressing this imbalance.

In regard to future research work in this area, we view three areas of particular interest. First, it will be important to test the applicability of our findings to other sectors, in particular those that are of export interest to developing countries. Second—and flowing from the previous point— there is likely to be a high payoff from investing in improved data in this area. Research on nontariff measures generally, and product standards in particular, suffers from a chronic lack of detailed, reliable, and comprehensive data. Clearly a major effort is required to remedy this situation, in particular if attention is to be paid both to mandatory technical regulations and voluntary product standards.

Finally, the World Bank EU standards database discloses significant cross-sectoral differences in the number and type (harmonized or not) of standards. Future work could usefully investigate the determinants of that variation. Just as political economy has proved a useful tool for analyzing

- 24 -