rafmacalaba/datause-encoder-data huggingface dataset:
climate assessment indicated a 7% loss in production or merchandise value due to power outages or surges from the public grid.<sup>10</sup> Alcott et al. (2014) argue that shortages reduce average output by about 5%, but because most inputs can be stored during outages, productivity losses are much smaller. The result is different for plants without generators, who have much larger losses, and because of economies of scale in generator capacity, shortages more severely affect small plants. Similarly, Hulten et al. (2006) find that about 50% of productivity growth in Indian manufacturing between 1972 and 1992 is attributable to the growth of roads and electric generation capacity. Khandker et al. (2012) and Rud (2012a,b) study the impact of rural electrification in India.

The organization of the energy sector also explains many of the problems with the sector. First, planning for electricity supply in India is managed centrally by the Planning Commission, but its implementation is split across different ministries. Second, subsidies, such as that on agriculture, introduce significant inefficiencies in the allocation of electricity.<sup>11</sup> Third, there have been substantial losses in transmission and distribution, rising from 5% in 1997-1998 to 30% in 19992000, vis-à-vis neighboring countries where such losses are close to 10% (Modi, 2005).

The Electricity Supply Act of 1948 marked the importance of electricity policy in postindependence India. This act established the Central Electricity Authority (CEA) as an advisory body on national power planning, policy making, and monitoring progress, and created state electricity boards (SEBs)—state-level vertically-integrated utilities responsible for power generation, transmission, and distribution, and for setting most tariffs. India’s power sector has seen extreme changes in the last few decades. A slew of policies and regulations followed the Electricity Act of 2003 to facilitate an accelerated growth in the sector. The process started with the restructuring of power distribution utilities, with some states corporatizing the functional entities for power generation, transmission, and distribution. The states of Orissa and Delhi went a step further by privatizing the distribution sector. Another important aspect is to provide clean and convenient “lifeline” energy, critical for the well-being of deprived. Meeting the energy

> 10 Similar results are found in Lall and Mengistae (2005) who use the World Bank’s investment climate survey data to argue that power shortages severely hold back productivity of Indian manufacturing firms.

> 11 More generally, fuel subsidies are common in India and amount to around 2% of GDP. While often motivated by a desire to help the poor, they can prove otherwise given the majority of fuel consumption by richer households (http://blog-imfdirect.imf.org/2013/06/24/for-richer-not-poorer-energy-subsidies-in-india/).

10
# Table 2: Descriptive Statistics for Land Titling Samples

|||_Benin_|||_Rwanda_|||_Ghana_||
|---|---|---|---|---|---|---|---|---|---|
||Obs.<br>(1)|Mean<br>(2)|S.D.<br>(3)|Obs.<br>(4)|Mean<br>(5)|S.D.<br>(6)|Obs.<br>(7)|Mean<br>(8)|S.D.<br>(9)|
|_Panel A: Characteristics of the_|_househol_|_d_||||||||
|Household size|2,327|6.94|3.27|1,925|5.33|1.85|755|4.32|1.69|
|Women is head of household|2,327|0.08|0.27|1,925|0.02|0.15|755|0.47|0.50|
|_Panel B: Characteristics of the_|_woman_|||||||||
|Age|2,327|33.00|7.62|1,925|33.91|7.617|755|35.38|7.48|
|No education|2,327|0.90|0.30||||490|0.01|0.12|
|Completed primary school|2,327|0.07|0.26||||490|0.32|0.47|
|Completed middle school|2,327|0.02|0.15||||490|0.36|0.48|
|Completed high school|2,327|0.00|0.06||||490|0.20|0.40|
|Completed higher education|2,327|0.00|0.00||||490|0.03|0.16|
|Nb of children at baseline|2,327|3.35|2.49|1925|3.24|2.02|755|1.47|1.65|
|Married|2,327|0.97|0.17|1,925|0.77|0.42|755|0.71|0.45|
|_Panel C: Characteristics of the_|_partner_|||||||||
|Partner age|2,151|41.56|11.06|1,905|38.97|11.03|462|41.47|10.15|
|No education|2,151|0.69|0.46||||377|0.00|0.00|
|Completed primary school|2,151|0.19|0.39||||377|0.18|0.38|
|Completed middle school|2,151|0.09|0.28||||377|0.23|0.42|
|Completed high school|2,151|0.02|0.14||||377|0.43|0.50|
|Completed higher education|2,151|0.02|0.13||||377|0.07|0.26|
|Farmer/ farm worker||||1,921|0.83|0.38||||
|Self employed||||||||||
|Employed||||1,921|0.05|0.23||||
|Unemployed||||1,921|0.02|0.14||||
|Other||||1,921|0.07|0.25||||
|_Baseline_||NO|||YES|||NO||

Notes: This table reports descriptive statistics of the sample of women under study. The first column of each country reports the number of observations in the sample at follow-up 1 non-attrited for the given variable, the second column reports the variable mean in the control group at baseline, or at follow-up 1 if there is no baseline. The variable married equals one if the woman declares she is formally married. For the number of children at baseline, when we have no baseline we take the number of children born before the beginning of the treatment. The level of education displayed is the highest level of education completed.

15
# **2. Literature review**

This research relates to two strands of literature: first, studies that consider the impact of sovereign rating changes including regional spillovers and the recent literature on relative risk ratings; and second, the push and pull factors in international capital flows including recent research that analyzes the role of highly accommodative monetary policies in advanced economies and global risk conditions during the post-2008 period. Rather than taking a comprehensive view, the literature on capital flows, sovereign ratings, and spillovers has focused on particular forms of capital flows or specific high-frequency financial indicators. Moreover, prior studies have generally considered push and pull factors including absolute sovereign ratings but have not accounted for changes in relative ratings. To address these gaps, this research seeks to take an encompassing view of net and gross capital inflows when considering the impact of sovereign ratings and relative risk ratings on the allocation of international capital flows during the post-financial crisis period.

_2.1 Impact of sovereign rating changes, including regional spillovers, and relative risk ratings_ Several studies have explicitly considered the impact of sovereign ratings on capital flows, bond spreads, and equity prices. Kim and Wu (2008) find strong evidence that sovereign credit ratings affect financial sector development and capital flows. Kim and Wu (2011) find that sovereign credit rating revisions have significant and positive influences on international bank flows of G7 countries to 55 emerging markets. Furthermore, there are regional spillovers: rating improvements in one EM region tend to reduce bank flows to other regions. Cai, Gan, and Kim (2018) using bilateral data on foreign direct investment (FDI) flows from 31 OECD countries to 72 recipient countries find that sovereign credit ratings in both source and recipient countries impact FDI flows. The authors find a positive impact of credit ratings of recipient countries on FDI inflows, suggesting the importance of the overall investment climate as indicated by the sovereign rating. The authors also find that lower-rated FDI donor countries are likely to engage in FDI to high-rated recipient countries. Several studies have examined links between sovereign credit ratings and bond yield spreads. Reisen and Maltzan (1999) use an event study to explore market responses 30 trading days before and after rating announcements and find a significant impact of imminent upgrades and implemented downgrades despite anticipation of rating events. Gande and Parsley (2005) study the effect of a sovereign rating change of one country on sovereign credit spreads of other countries. They find evidence of asymmetric effects whereby negative rating events are particularly correlated with an increase in spreads.

5
# **4. The Effect of Firewood Consumption Reduction on CO2‐Equivalent Emissions**

To make the link between estimated firewood collection reductions and reduced CO2e emissions, we use emission factors for each pollutant emitted from traditional wood‐fired cookstoves taken from the scientific literature collated by (Pandey et al. 2014) per kg of firewood burned. These are then multiplied by the 100‐year Global Warming Potentials (GWPs) for each pollutant to arrive at tonnes of carbon‐dioxide equivalent emissions per Kg of wood burned. The results are presented in Table 3 below.

The GWP for CO2 is, by definition equal to 1. However, the CO2 saving from not burning a kg of wood depends on whether the wood is harvested unsustainably (in which case the saving is 100% of the GWP) or sustainably (in which case the saving is zero).<sup>12</sup> While the extent of unsustainable harvesting is unknown, in Nepal, where many forests are still recovering from over‐harvesting during the 40 years or so following nationalization in the 1950s, it is plausible that reduction of harvesting of branches for firewood would result in carbon sequestration in increased branch volume. Accordingly, we assume that 50% of the wood is harvested unsustainably and adjust the GWP of CO2 down to 0.5.

Using the best estimate of the reduction in wood consumption per biogas plant of 1,000 kg/year, we arrive at the figures in the fifth column of Table 3. We note that about three‐quarters of the annual savings of 1.6 tonnes of CO2e per biogas plant come from the saving from unsustainable harvested wood and reduced emissions of black carbon (BC).

Our estimate of the total saving of CO2e per year is about one‐half of that assumed by aid agencies that support Nepal’s biogas subsidy program.<sup>13</sup>

> 12 Firewood used for cooking is in principle carbon neutral if equivalent trees are replanted or allowed to grow.  This is how the term “sustainable” is used in this context.

> 13 See http://www.ashden.org/files/BSP%20case%20study%20full.pdf. Accessed January 29, 2015.

12
Figure 11: Projected monetized value of deaths from drought-induced PM2 _._ 5 <!-- Start of picture text --> 2000 2020 2040 2060<br>Year<br>Observed SSP1−2.6−APS SSP2−4.5−STEPS SSP3−7.0−RES<br>60000<br>40000<br>Losses (millions $US 2019)<br>20000<br><!-- End of picture text --> _Notes:_ The figure plots the evolution of monetized losses from premature deaths in LAC. Between 2000 and 2020, it plots the average losses. Details of this calculation are presented in Section 4.2. Between 2016 and 2059, it plots 66 projections of losses (22 models _×_ 3 SSP-electricity scenarios). These calculations follow the same methodology but use runoff projections from the climate models, demographic and economic growth projections from the SSPs, and electricity scenarios from the IEA. To better visualize the overall trends, we also plot a LOESS curve for the observed premature deaths and the projections under each SSP-electricity scenario.

28
**Table 1: Summary Statistics of Data**

||**Obs.**|**Mean**|**St. Dev.**|**Min.**|**Max.**|
|---|---|---|---|---|---|
|Emigrants from i to j|992|3,890|17,208|16|470,693|
|Population|992|2,848,697|2,440,552|375,494|11,170,796|
|Distance|992|19.27|12.42|1|64.88|
|Distance sq.|992|525.98|660.95|1.00|4209.00|
|Prices|992|100.00|16.55|66.99|138.15|
|log Prices|992|4.59|0.16|4.20|4.93|
|Unemployment|992|2.99|1.04|1.46|6.64|
|Nominal wages|992|1787|345|1208|3036|
|log Nominal wages|992|7.47|0.18|7.07|8.01|
|Amenities|992|2.11|1.00|0.10|4.72|
|FDI|992|268.00|386.00|0.04|1617.00|
|log FDI|992|4.35|2.15|-3.11|7.38|
|Exports|992|1452|2130|19.82|8578|
|log Exports|992|6.14|1.69|2.98|9.05|
|Imports|992|844|1219|5.52|4176|
|log Imports|992|5.51|1.84|1.7084|8.33|
|Maquila|306|97,681|129,480|1,029|453,211|
|logMaquila|306|10.57|1.51|6.93|13.02|

27
Finally, we found that, overall, the impact of China's WTO accession on the regional economies is small, but showed that trade-induced productivity gains could amplify these results substantially. There is also a consensus among institutional economist that transaction cost saving could also be substantial.5 Thus, this and other studies generally underestimate the impact of China WTO accession on China and the rest of East Asia.

> _55_ Based on conmments by Lu Ding during Trade and Poverty Workshop, Institute of Southeast Asian Studies, September 20-21, 2002.

21
reservations in local areas through the set-aside programs increased the desire of women for more educational attainment and stronger careers. It is possible that our results are a reflection of these greater aspirations. An inspiration stimulus would again be mostly neutral, and thus could align well with the industry patterns we observe. A strong factor favoring this channel is that an inspiration account would also naturally connect to the smaller-scale nature of our entry patterns given that the inspiration stimulus is plausibly most likely to influence entry choices at the smaller end of establishment sizes (i.e., those who would not have otherwise entered without the inspiration are likely to be those starting smaller firms than those who would enter regardless).

While both of these hypotheses are appealing, we are cautious to note that we cannot differentiate between them. We likewise cannot completely separate them from other state-year factors that could be tied to the reservations (e.g., women-oriented policies promoted by local governments). Our comparative advantage in this project compared to the emerging literature stream overall is that we are able to quantify the economic patterns for the full Indian manufacturing sector. Administrative datasets, however, have natural limits for measuring subtler factors like women-oriented public goods or inspiration. We hope to encourage future research at the village level to pick up on these entrepreneurship dimensions. To date, we are not aware of any village-level studies that have collected information about women’s entrepreneurship, and our study highlights the high potential return for doing so.

# **7.  Conclusions**

The implementation of political reservations had strong effects for empowering women in India in many spheres. While we do not see much evidence that this increased women’s employment in manufacturing, we do identify that women are more likely to start new establishments in the unorganized sector after the reforms. This growth in entrepreneurship was concentrated in industries that women have traditionally been active in and at the household-establishment scale.

This study provides among the first evidence of how political reservations can affect economic outcomes for women. This linkage is important given that many long-term gains and entrenchment of the empowerment benefits from political reservations can be aided by better economic opportunities that grow in parallel with political voice. These linkages may also affect economies in other ways, given the rise in women’s participation. In related work for example, 29
Overall, such country-specific results suggest that energy and environmental policies should recognize the differences in the energy consumption-growth nexus in order to maintain sustainable economic growth in a given country.

Our study contributes to the literature through its particular focus on the intersection of economic geography and electricity usage patterns. Beibei et al. (2010) consider China’s spatial patterns of energy production, but this type of work is in general quite rare. Our analyses and decompositions provide novel insight on how patterns of regional development impact aggregate electricity usage, which is often lost in macro-level tests. Second, by building up from plant-level surveys, we provide a foundation for understanding and evaluating the heterogeneity that exists below the aggregate figures. These contributions help policy makers consider the energy usage consequences of other policies that they may wish to pursue, which is key for avoiding or at least mitigating unintended consequences of otherwise well-motivated policy choices.

# **III. Data Description**

# _Data Sources_

This project draws upon five surveys from two major sources of data: the Annual Survey of Industries (ASI) and National Sample Survey Organization (NSSO). ASI is a survey of the organized sector undertaken annually by the Central Statistical Organization (CSO), a department in the Ministry of Statistics and Program Implementation, Government of India. Under the Indian Factory Act of 1948, all establishments employing more than 20 workers without using power or 10 employees using power are required to be registered with the Chief Inspector of Factories in each state. This register is used as the sampling frame for the ASI. The ASI extends to the entire country, except the states of Arunachal Pradesh, Mizoram, and Sikkim and Union Territory (UT) of Lakshadweep.

The sampling design followed in in most ASI surveys is a stratified circular systematic one. All factories in the updated frame (universe) are divided into two sectors: Census and Sample. Census Sector are comprised of industrial units that belong to the six states/UTs that are less 12
# WPS4128

**Foreign Bank Participation and Crises in Developing Countries**<sup>∗</sup>

Robert Cull Finance and Private Sector Development Research Group The World Bank María Soledad Martínez Pería Finance and Private Sector Development Research Group The World Bank

## **Abstract**

This paper describes the recent trends in foreign bank ownership in developing countries, summarizes the existing evidence on the causes and implications of foreign bank presence, and re-examines the link between banking crises and foreign bank participation. Using data on the share of banking sector assets held by foreign banks in over 100 developing countries during 1995-2002, the results show that countries that experienced a banking crisis tended to have higher levels of foreign bank participation than those that did not. Furthermore, panel regressions indicate that foreign participation increased as a result of crises rather than prior to them. However, post-crisis increases in foreign participation did not coincide with increased credit to the private sector, perhaps because in many cases foreign banks acquired distressed banks. <u>Keywords:</u> foreign banks, crises <u>JEL classification: F23, F36, G21</u>

## World Bank Policy Research Working Paper 4128, February 2007

_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 view of the World Bank, its Executive Directors, or the countries they represent. Policy Research Working Papers are available online at http://econ.worldbank.org._

> ∗ We are grateful to Soledad Lopez for outstanding research assistance. Contact information: Robert Cull, Senior Economist, Finance and Private Sector Development Research Group, World Bank, 1818 H Street, N.W., MSN MC3-300. Email: rcull@worldbank.org. Maria Soledad Martinez Peria, Senior Economist, Finance and Private Sector Development Research Group, World Bank, 1818 H Street, N.W., MSN MC 3-300. Email: mmartinezperia@worldbank.org.

1
lOa

# 'ab'le IL EFFECT OR NOMINAL IEVLUATION ON REAL EXCHANGE RATE

||NOMINAL|||||REAL EXR||||
|---|---|---|---|---|---|---|---|---|---|
|COUNTRY/YEAR|DEVALUATION||t-3|t-2|t-1|t|t+l|t+2|t+3|
|Argentina (1971)<br>Bolivia (1972)|25.00<br>68.35|(B)u/<br>(M<br>(B)|104.17<br>111.05<br>60.56|100.00<br>106 40<br>60.56|104.17<br>106.98<br>60.56|100.00<br>100.00<br>100.00|66.67<br>76.16<br>85.92|45.83<br>55.81<br>63.38|43.75<br>54.65<br>6338|
|||(M)|80.00|80.91|84.55|100.00|143.64|104.55|90.91|
|Brazil (1958)|6932|(B)<br>_(M_|na.<br>.|na.|n.a.|100.00|71.97<br>.|55.62<br>.|41.54|
|Costa Rica (1961)|17.75|<br>(B)<br>(M)|87.97<br>-|87.90<br>-|87.29<br>96.10|100.00<br>100.00|97.62<br>109.09|94.59<br>106.49|91.73<br>103.90|
|Costa Rica (1974)|28.87|(B)<br>(M)|86.47<br>90.11|86.32<br>92.31|84.95<br>90.11|100.00<br>100.00|93.07<br>101.10|94.12<br>102.20|95.88<br>107.69|
|Ecuador (1961)|20.00|(B)<br>(|88.06<br>.|88.33<br>-|86.95<br>94.12|100.00<br>100.00|97.44<br>106.86|91.74<br>101.96|88.35<br>100.00|
|Ecuador (1970)|38.89|(B)<br>(M)|76.07<br>94.95|74.75<br>91.92|73.05<br>88.89|100.00<br>100.00|95.34<br>118.18|92.26<br>117.17|92.38<br>121.21|
|El Salvador (1986)|100.00|(B)|91.03|83.42|67.93|100.00|82.34|71.47|63.59|
|||(M)|84.52|76.19|64.29|100.00|89.29|73.81|59.52|
|Nicaragua (1979) v|43.03|(B)|100.00|88.89|88.89|100.00|88.89|77.78|66.67|
|||_(M)_|-|.||,.||||
|Peru (1959)|13.11|(B)<br>(Nj)|85.74<br>-|82.15<br>-|99.43|100.00<br>.|88.95<br>.|83.85|78.56|
|Peru (1967)|44.30|(B)<br>(M)|91.34<br>120.97|80.00<br>106.45|75.92<br>100.00|100.00<br>100.00|86.11<br>109.68|84.20<br>106.45|83.06<br>106A5|
|Venezuela (1964)|38.20|(B)|74.17|74.69|73.64|100.00|103.18|101.76|101.93|
|||MNI)|<br>80.00|80.00|80.00|100.00|102.35|10235|103.53|

# NOTES:

- 1/ (NI) and (B) stand for the Multilateral and Bilateral (agan st the US dollars).

- 2/ Nicaragua alto had a one-time nominal devaluation of 3% in 1958, but CPI and therefor real exr is not available for these early yeas
TABLE 3 Baseline panel regression results

||All Sectors|Manufacturing<br>Sector|
|---|---|---|
|Liner Shipping<br>|-0.2299***|-0.2271**|
|Connectivity Index|(0.007)|(0.007)|
|Logistics Performance<br>|-0.5004***|-0.5156***|
|Index|(0.032)|(0.356)|
|Tariffs|0.3449***|0.4265***|
||(0.044)|(0.057)|
|trade agreement<br>|-0.0487***|-0.0567***|
|membership|(0.006)|(0.006)|
|Trade policy uncertainty|0.0907**|0.0902**|
||(0.004)|(0.005)|
||0.2605***|0.2687***|
||(0.007)|(0.007)|
|Common border|-0.4070***|-0.4125***|
||(0.033)|(0.035)|
|Common language|-0.1516***|-0.1369***|
||(0.013)|(0.141)|
|Observations|56,038|52,060|
||0.569|0.569|

Source: World Bank.

Note: * p<0.05, ** p<0.01, ***p<0.001. Robust standard errors are shown in parentheses. The table shows estimated coefficients from a gravity panel regression estimated for up to 95 countries using annual data for 2007-18 where the dependent variable is the log of bilateral trade costs. The regression includes time fixed effects. Standard errors are clustered by country pairs.