rafmacalaba/datause-encoder-data huggingface dataset:
**Figure 5: Household Spending on Energy Products (share of total household expenditure)**

<!-- Start of picture text --> .02<br>Gasoline<br>Diesel<br>Electricity<br>LPG<br>.015<br>Kerosene<br>The<br>expenditu<br>re shares<br>.01<br>.005<br>0<br>.01 .198 .386 .574 .762 .95<br>Household Percentiles<br><!-- End of picture text --> Source: Libyan Household Consumption Survey 2007/8; Libyan authorities; and Bank staff calculations.

Households derive substantial benefits from energy subsidies. We estimated the total value of direct energy subsidies received by households at 2.5 billion LYD (Table 20)— 6.7 times higher than total household expenditure on these products. About 1 billion LYD of this total derive from gasoline and 1.1 billion LYD from electricity. This underscores the significant share of subsidy incorporated in energy prices in Libya: on average, the government should increase energy prices by 670% to reach market levels and eliminate subsidies.

**Table 20: Energy Subsidies (Million LYD)**

||**Gasoline**|**Diesel**|**Electricity**|**LPG**|**Kerosene**|**Total**|
|---|---|---|---|---|---|---|
|Quintile_1|177.4|4.6|203.5|53.6|3.0|442.0|
|Quintile_2|214.8|4.7|231.3|55.4|5.2|511.4|
|Quintile_3|221.8|3.6|232.7|54.1|5.7|517.8|
|Quintile_4|222.4|3.8|225.1|52.5|6.7|510.4|
|Quintile_5|206.3|4.5|243.6|49.5|6.9|510.8|
|Total|1,042.6|21.2|1,136.2|265.2|27.4|2,492.5|

Source: Libyan Household Consumption Survey 2007/8; Libyan authorities; and Bank staff calculations.

23
Policy ReseaRch WoRking PaPeR 4929

# **Abstract**

The authors examine a unique public spending program that is proliferating across developing countries, the constituency development fund, to investigate when legislators exert more effort on behalf of their constituents. Using data from India, they find that legislator effort is significantly lower in constituencies where voters are more attached to political parties. They are also lower in constituencies that are reserved for members of socially disadvantaged groups (lower castes), specifically in those reserved constituencies that are candidate strongholds. This result is robust to controls for alternate explanations and implies that legislators pass on pork when voters are more attached to political parties or influenced by identity issues. These findings have implications for the evaluation of constituency development funds. They also provide a new answer to a central issue in political economy, the conditions under which legislators seek to “bring home the pork” to constituents, that attaches great importance to the role of political parties.

This paper—a product of the Growth and the Macroeconomics Team, Development Research Group—is part of a larger effort in the department to explore governance improvements to accelerate development. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The authors may be contacted at pkeefer@worldbank.org or skhemani@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
quantifying externalities of DDT on human health based on area and population exposed to DDT, and the risks posed by the use of DDT. In order to gain a better understanding of the costs and benefits of DDT use to combat malaria, a separate countrywide analysis of all countries with high incidence of malaria has been carried out. The analysis includes not only countries where DDT is currently being used, but also countries where the introduction of DDT may help in lowering the incidence of malaria. The externalities are quantified in economic terms, wherever feasible, with estimates of direct treatment costs and indirect costs imposed by morbidity and mortality as captured by Disability Adjusted Life Years (DALY) to arrive at an overall estimate of the impacts. It is expected that the estimates presented in this paper would strengthen the understanding of net health benefits of reintroducing DDT in malaria control programs throughout the globe. The remainder of the paper is organized as follows: Section 2 summarizes the health effects of DDT and the risks posed by DDT-as cited in the literature. Section 3 provides estimates of population exposure to DDT. Direct and indirect estimates of health externalities of DDT are presented in Section 4. Direct and indirect costs of malaria are presented in Section 5, while Section 6 concludes the paper.

# **2.** **_Health Effects and Risks Posed by DDT_**

DDT, a white tasteless and almost odorless crystalline solid, is an organochlorine contact insecticide that kills by acting as a nerve poison. DDT is categorized by the WHO as Class II "moderately hazardous". “Acute effects in humans who are exposed to low to moderate levels may include nausea, diarrhea, increased liver enzyme activity, irritation of the eyes, nose and/or throat. At higher doses, tremors and convulsions are also possible” (Pesticide Action Network-UK, 2011).

Health externalities from DDT exposure that are reported in various studies include: a poisoning hazard to children following acute ingestion, temporary damage to nervous system, possible carcinogenic effects (can cause liver, pancreas, testicular cancer, breast cancer, leukemia and lymphoma), development effects, adverse effects on the hormonal system and reproductive 4
|**TableII**|**RegisteredUnempl**|**oyedReceiving **<br>**SocialAssistan**|**UnemploymentI **<br>**ce**(SA)|**nsurance**(UI)**an**|**d/or**|
|---|---|---|---|---|---|
||**Registered**<br>**unemployed**|**ReceivingUI**<br>**(Total)**|**ReceivingUl**<br>(%)|**ReceivingSA**<br>**(Total)**|**ReceivingSA**<br>(%)|
|**1991**|301,951|247,728|82.00|NA||
|**1992**|260,274|87,322|33.55|NA||
|**1993**|368,095|122,853|33.37|101,607|27.60|
|**1994**|371,481|85,032|22.89|168,416|45.33|
|**1995**|333,291|89,995|27.00|147,101|44.13|
|**1996**|329,749|93,517|28.36|135,440|41.07|
|**1997**|347,753|92,914|26.72|155,345|44.67|
|**1998**|428,209|119,931|28.01|193,706|45.24|
|**1999**|535,211|144,690|27.03|272,813|50.97|

**Source:** _Social Policy._ Ministry of Labor, Social Affairs and Family.

**Table III Expenditure on Social Assistance and Labor Market Policies (in miions SK)**

||Social|Assistance|**Labor Marke**|**tPolicies**|**Benefitsto**<br>**registered**|
|---|---|---|---|---|---|
||**Total**|**Toregistered**<br>**unemployed**|**Passive**<br>**(UIAbenefits)**|**Active**|**unemployed**<br>**(Total)**|
|**1991**|NA|NA|NA|NA|NA|
|**1992**|2,218|1,526|1,711|3,812|3,237|
|**1993**|3,120|2,200|1,859|1,107|4,059|
|**1994**|5,134|3,824|1,710|1,896|5,534|
|**1995**|5,517|4,058|2,181|3,899|6,239|
|**1996**|5,510|3,850|3,063|4,290|6,913|
|**1997**|5,891|4,154|3,989|3,098|8,143|
|**1998**|7,978|5,813|5,484|2,289|11,297|
|**1999**|11,599|8,790|7,292|474|16,082|

**Source:** _Social Policy._ Ministry of Labor, Social Affairs and Family. A Unemployment Insurance.

||**TableIVPersonsin**|**MaterialDestitut**|**ionReceivingSoc**|**ialAssistance(SA**||
|---|---|---|---|---|---|
||**Personsin**<br>**material**<br>**destitution**|**Recipientsof**<br>**SA**<br>**(Total)**|**Recipientsof**<br>**SA**<br>(%)|**Coupleswith**<br>**dependent**<br>**children**|**Individualsor**<br>**couplesw/o**<br>**dependent**<br>**children**|
|**1991**|NA|NA||_||
|**1992**|NA|NA||||
|**1993**|NA|NA||-||
|**1994**|442,544|199,127|44.99|89,214|90,718|
|**1995**|408,507|176,705|43.25|79,525|83,364|
|**1996**|378,637|160,788|42.46|72,679|78,443|
|**1997**|392,927|174,971|44.53|71,153|97,255|
|**1998**|506,400|222,655|43.96|NA|NA|
|**1999**|584,941|297,688|50.89|93,799|202,805|

**Source:** _Social Policy._ Ministry of Labor, Social Affairs and Family.

49
only allows an even more coarse spatial disaggregation, at macro-region, and is available only from 2005 onward, well after the most important phase of internet rollout. These data are also repeated cross-sections, preventing us from following the same firm over time. Finally, Census data, which contain questions on internet availability at the household level, are only available for 2000 and 2010.

The School Census is an administrative record filed by all preschool, primary and secondary schools in the country, both public and private. Since 2000, the school level form has included a question on internet availability at the school. The question on internet access has been available in all rounds of the School Census since 2000. We aggregate the data at the municipal level, using the share of schools with internet access as a proxy for internet availability in the municipality. The reliability of this measure is based on the assumption that the share of schools that have internet access reflects general accessibility of internet connections, and that internet access is not discretely off and then on at the municipality, but rather changes continuously over time. Our results are robust to the alternative of defining internet access in a municipality as discretely on for the first year in which more than 10 or 25% of schools report internet access, but in our primary estimations we maintain the share measure as our principal regressor. Table 1 contains summary statistics of the combined data set.

**Table 1: Summary statistics**

|**Variable**|Municipality-y<br>**Mean**|ear variation<br>**SD**|**Min**|**Max**|**Obs**|
|---|---|---|---|---|---|
|Average firm size (employees)|21|30|1|5,313|77,749|
|SD of firm size|83|104|0|11,766|77,298|
|Total new hires|3,600|36,624|0|3,033,010|77,749|
|Total workers fired|3,187|33,022|0|2,839,354|77,749|
|Total employment|9,830|104,288|1|8,087,258|77,749|
|Average monthly wage (real R$)|946|335|8.016|14,182|77,749|
|Share of schools with internet access|0.49|0.36|0|1|74,184|

Note: Summary statistics based on RAIS employee-employer records aggregated by municipality and year. Internet access from School Census.

There are 5,574 unique municipalities across 14 years of data from 2000 to 2013, with the mean municipality-year observation having approximately 465 firms employing more than 9,000 workers with an average firm size of just over 21 employees. Figures 1 and 2 show municipalities that had internet connections in 1999 and 2009, respectively (note that these are descriptive, and are not representing our measure based on the Schools Census).

6
governance and opinions on current events. Observations are also spatially identified at the municipality and again we focus on variation in the Venezuelan share of the population at the province level.

_Gallup World Poll (GWP)_ is a nationally representative opinion survey and has been conducted annually since 2006 in a wide range of countries around the world. The sample collected in Peru is a repeated cross-section of about approximately 1,000 observations each year. For our analysis, we use data from 2013 to 2020. The survey questions are centered around politics, governance and opinions on current events. We make use of several opinion indices provided by Gallup that measure individual opinions on various domains. Observations are spatially identified at the region level for Peru, which is our level of analysis in this case (there are 25 regions in Peru).

_PTP_ We measure the location of Venezuelan immigrants on a monthly basis from January 2015 to December 2020 using administrative data on the district Venezuelan immigrants register at with the Peruvian authorities to obtain access to social services. There are strong incentives to register as this is also a prerequisite for applying to obtain the PTP. This data only records monthly gross arrivals so we do not know the outflows of Venezuelans to other locations within Peru or out of the country entirely. However, in ENPOVE, 84% of Venezuelan immigrants in Peru report having lived in the same district during their entire time since arriving in the country. The data shows the arrival of 511,223 Venezuelans as of December 2020, which, while somewhat lower than estimates of the actual number of Venezuelans living in Peru, is quite substantial.

We also use data from the _National Census 2007 and 2017_ . We use the 2017 Census data to measure the share of workers in the formal and informal sector in each centro poblado as well as the total local population in each centro poblado, province and region. We use the 2007 data to construct both of our instruments discussed in more detail below as well as to create additional controls for the local economic environment. More specifically, in the first part of our analysis, we use information on the industrial distribution (using detailed four-digit codes) in each centro poblado, while in the second part, we use information on the total number of Venezuelans in each province in Peru.

To construct the _Trade shock_ instrument for the first part of our analysis, we also use trade data from the reports of TradeMap. From this website, we are able to identify export and import values for Peru on a monthly basis since 2006 at the HS 6-digit product revision. In addition, correspondence tables of HS 6-digit product revision to ISIC 3.1 revision (United Nations) are used to harmonize products with their corresponding industry sector in order 9
turnover, and (iii) value chains (i.e. demand and assistance effect, diffusion effect, availability and quality effect). The focus of this paper is on value chains.<sup>3</sup> Spillovers through global value chains emerge, e.g., when local firms become input or service suppliers of multinational firms. Specifically, FDI spillovers can be generated through the demand of multinationals for better and/or more diverse inputs ( _demand effect_ ). Hereby, multinational affiliates might help local producers to upgrade their technological capabilities directly through sharing of production techniques and product design and assisting with technology acquisition ( _assistance effect_ ) (Paus and Gallagher 2008). Spillovers to supplying industries may also be generated through personnel training, advance payment, leasing of machinery, provision of inputs, help with quality assurance and organization of product lines (Lall 1980; Crespo and Fontoura 2007; Javorcik 2008).

While the demand and assistance effects are intentional, unintentional knowledge spillovers can occur, e.g., through technology leakages to other supplying firms in the sector ( _diffusion effect_ ). Finally, while the previously described effects refer to backward spillovers from multinationals to suppliers, there is also the case where a multinational firm supplies to a local producer in downstream sectors. This increases the availability, variety, and reliability of higher-quality inputs ( _availability and quality effects_ ) (Javorcik 2008). Given our data sample which covers surveys of suppliers that produce inputs for multinationals, we are only able to examine demand and assistance effects in the following.

# **3 Which Foreign Investor Characteristics Increase the FDI Spillover Potential?**

This section focuses on the role of foreign investor characteristics for the FDI spillover potential. Section 3.1 presents the dataset being used in this section. Section 3.2 evaluates if there are differences between foreign investors and domestic producers in terms of their potential to generate positive spillovers. Section 3.3 examines if there are differences in the extent of FDI spillover potential between different groups of foreign investors, depending on their characteristics.

> 3 Note that the general managers experience in other foreign-owned firms at home or abroad in the strict sense could also be considered part of the transmission channel “labor turnover“.

9
control for differences in financial structure, we use stock market capitalization over GDP and bank deposits over GDP (Beck, Demirgüç-Kunt, and Levine, 2000). We may expect to see differences in co-dependence in bank vs. market based systems. We also include liquid assets ratio and capital ratio to control for the funding liquidity of the domestic financial system (Beck and Demirgüç-Kunt 2004). Overall liquidity in the financial system may reduce or eliminate some channels of contagion which increase co-dependence. Finally we control for the log of the number of banks in the sample, since correlation may be mechanically linked to the number of cross-sectional observations (Morck 2000). We also exclude countries with less than 7 banks from the analyses. The regressions include country fixed effects ( ) and we report robust standard errors clustered at the country level.

Cross-sectional regression results are reported in Table 7. As expected we find the coefficient on the bank-crises dummy to be significant and positive. That is co-dependence increases significantly during crises periods. As mentioned earlier, consistent with the prior literature we find gdp per capita growth to reduce co-dependence, although the level of GDP per capita is insignificant. We find stock market capitalization over GDP to increase co-dependence. One possible explanation is that more market based systems have more potential channels of contagion. Surprisingly, the coefficient on the liquid assets ratio is negative and significant. The capital assets ratio is insignificant.

As mentioned earlier we are particularly interested in the impact of financial and economic openness and integration on co-dependence. We are also interested in the extent to which banking de-regulation and banking supervision can explain cross-country differences in co-dependence. We use a number of different variables to measure integration and financial openness. The first measure is stock market turnover which has a positive statistically significant effect on co-dependence. Trade over GDP has been previously used in the literature to measure economic integration (Bekaert and Wang 2009). We do not find it to be significant after controls. The Chin-Ito measure quantifies capital control policies and other regulations and restrictions on capital flows (Chin and Ito 2008). It shows up positive and significant. We also consider the impact of social and political integration. We use the KOF political and social 13
**Table I5: Relationship between food security measures and weight-for-age z-scores (Uganda): Limited Controls Version**

||(1)|(2)|(3)|(4)|(5)|
|---|---|---|---|---|---|
|VARIABLES||Weig|ht-for-age z-s|cores||
|1-SSEXR|0.073**<br>(0.031)|||||
|FCS||0.127***<br>(0.028)||||
|DDS|||0.036<br>(0.031)|||
|PC expenditure||||0.104***<br>(0.033)||
|Food Share|||||-0.023<br>(0.029)|
|Rural|-0.407***|-0.397***|-0.433***|-0.387***|-0.450***|
||(0.077)|(0.074)|(0.077)|(0.078)|(0.075)|
|Kampala|-0.114|-0.139|-0.096|-0.166|-0.058|
||(0.162)|(0.160)|(0.165)|(0.163)|(0.161)|
|Central without Kampala|0.024|0.029|0.031|0.024|0.059|
||(0.085)|(0.084)|(0.088)|(0.083)|(0.083)|
|Eastern|-0.006|0.003|0.004|0.015|0.037|
||(0.085)|(0.082)|(0.088)|(0.081)|(0.081)|
|Northern|-0.216**|-0.121|-0.163**|-0.126|-0.148*|
||(0.085)|(0.080)|(0.081)|(0.079)|(0.080)|
|Constant|-0.407***|-0.441***|-0.405***|-0.450***|-0.412***|
||(0.087)|(0.086)|(0.087)|(0.088)|(0.087)|
|Observations|2,009|2,008|2,009|2,009|2,009|
|R-squared|0.026|0.033|0.024|0.029|0.023|

Source: Authors’ calculations. Note: Robust standard errors in parentheses. *** p<0.01, ** p<0.05, * p<0.1 1-SSEXR is the expenditure share of non-starchy staple food in total food expenditure, FCS is the food consumption score, DDS is the household level dietary diversity score, PC expenditure is the per capita expenditure, and Food share is the share of food expenditure in total expenditure.

108
**Figure 7.2: Comparing speed of diffusion of power sector reform measures across decades**

||Percentage of countries implementing reforms in time<br>period:|1995‐05|2005‐15<sup>17</sup>|
|---|---|---|---|
|Regulation|Creation of regulatoryentity ******|43|18|
|Restructuring|At least some degree of restructuring (at least partial<br>vertical unbundling)*|33|17|
||Partial vertical unbundling|5|4|
||Full vertical unbundling*|20|7|
||Full vertical unbundlingand horizontal unbundling|8|6|
|Competition|At least some degree of competition(at least IPPs)*|41|33|
||Adoption of Monopoly+ IPPs|15|15|
||Adoption of Single Buyer Model*|11|4|
||Adoption of Third PartyAccess|5|5|
||Creation of wholesalepower market******|8|6|
||Creation of retailpower market|2|3|
|Private Sector|Private Sector Participation ingeneration******|34|8|
|Participation|Private Sector Participation in distribution******|19|7|
||Divestiture ofgeneration companies******|17|4|
||Divestiture of distribution companies******|12|4|
||Private Sector Participation in transmission|6|7|
||Divestiture of transmission companies|4|1|

Source: Own elaboration based on RISE 2015 and World Bank PPI 1990‐2015 databases ****** Differences are statistically significant at the 5% level ***** Differences are statistically significant at the 10% level

> 17 The denominator for these percentages excludes those countries that had already implemented the respective reform in the 1995‐2005 period.

43
to allow for good estimates of gross product before the mid-1830s. And by that time the U.S. economy was already growing at high, modem rates.

When did modern economic growth begin in the United States? The returns that investors in the United States earned on stocks and bonds suggest that a great upsurge of economic growth began sometime around 1815. Although the financial returns data show cyclical downturn around 1824, on closer inspection this drop seems to be an interruption in very rapid growth: returns grew to be extremely high by 1824 and then fell to a "mere" 10 percent in succeeding years. Even in the depression of the 1 840s the real return on stocks was 5 percent on a ten-year moving average.

Economic historians debate when modem economic growth really took off in the United States. From the financial returns evidence, I conclude that sometime after the War of 1812 there was a great upsurge, a great bull market, which lasted until about the middle of the nineteenth century. This trend is seen in both the stock (equity) and bond markets. As I note later in more detail, stocks and bonds tend to deliver better long-run returns when effective government is in place. That is one lesson of U.S. history.

# Securities Markets and **Economic Development**

What role can securities markets play in economic development? Like all financial markets they link "deficit units"-people, enterprises, or governments-which want more funds than they currently have to "surplus units," which have more funds than they currently need. In more colorful, if less comprehensive, terms securities markets provide a meeting place for investors and borrowers who want to invest money in business (real productive assets) and the savers and lenders who seek financial returns. The users of capital-government and businesses-are the issuers of securities, whereas the providers of capital are the buyers of securities.

2