rafmacalaba/datause-encoder-data huggingface dataset:
social and economic characteristics, and political aliation of each victim. Most importantly, I extract exact geographical location (village) and the date of the incident.

Table 1 reports descriptive statistics of the war fatalities. In total the INSEC data set contains information on 14,982 victims; most (13,210) are fatal casualties. More than 60% of the casualties are perpetrated by the state. The CPN Maoists deny exploiting the grievances among ethnic groups regarding political, social and economic exclusion to advance their agenda. However, the majority of their cadres belonged to ethnic groups such as Magars, Gurungs, and Dalits of the hills and mountains. It is, therefore, not surprising that the majority of casualties among the Maoists are ethnic minorities (60% not reported) and more than half of the total victims are also from the minority groups. Apart from attacking security forces, the Maoists also frequently targeted upper caste civilians, especially Bramins and Chhetris; these upper castes the Maoists labeled as counterrevolutionary elements. The average age of the victims is 28.3 years and almost 90% are male. Many were actively involved in politics- 54% are aliated to either the rebel party or other political parties.

The conict intensity varied greatly over time. I summarize the number of monthly casualties and major events that helped shape the insurgency in Figure 1. As illustrated, the period after 2001 when the country was under the state of emergency and the RNA was actively involved was the bloodiest. The conict lasted for total of 131 months from February 1996 to November 2006. Using information on each victim's village and date of incident, I dene months of war _v_ in a village, _v_ , as the baseline conict intensity variable, constructed as follow: and subscripts _v_ and _m_ index a village and a month since the beginning of the war i.e. m takes the value of 1 for February 1996 and 131 for November 2006. Variable casualty _vm_ is number of casualties in a village _v_ in a month _m_ .

Villages in Nepal experienced dierent levels of conict as illustrated in Figure 2, which depicts the number of months each village experienced conict out of the total 131 months of the war. The intensity of the conict varied substantially across villages within districts. Dening the conict 9
between vaccination coverage – here the share of children with a BCG vaccine<sup>6</sup> – and the reduction of child mortality. This holds roughly across time as well as across countries. All countries that are (almost) on track in terms of U5M reduction (Niger, Madagascar, Mozambique, and Uganda) have been considerably extended BCG vaccination coverage (somewhat less in Madagascar). In two of the countries that are seriously off-track, Kenya and Mali, the share of vaccine children has declined.

**Figure 8: Share of children with BCG vaccine and U5M rates**

<!-- Start of picture text --> 260 2<br>Gui<br>240<br>0 Ni Mal<br>220<br>-1 0 1 2 3 4 5 6<br>200 -2 Mal<br>Ke<br>180<br>Ug Gui Moz<br>-4<br>160<br>Sen<br>Moz<br>140 -6 Ug<br>Mad<br>120 Mad Ke<br>-8<br>100<br>Ni<br>80<br>-10<br>60<br>0.40 -12 0.50 0.60 0.70 0.80 0.90 1.00<br>Share of children with bcg vaccineAnnual GDP pc growth<br>U5M in final year<br>Annual % point change in U5M<br><!-- End of picture text --> Source: Authors’ calculation from DHS surveys. Note: The arrows point from the first survey year to the second for each country.

In sum, the preceding descriptive analysis certainly tells us that the pathways to achieving child mortality reductions are very different across countries. While income growth often goes along with reduction in child mortality, it does not seem to be a necessary condition for reductions in child mortality. Despite the well-documented beneficial effect of mother’s education on child survival, this relationship can hardly be recovered from the aggregate data. The effect of access to tap water on child mortality is even less clear from our cross-country comparison. This would suggest rather weak complementarities between MDGs 1, 2, 3, and 7, on the one hand, and 4, on the other. In contrast to all these rather weak correlations, the aggregate figures suggest that expanding vaccinations is a key factor for

> 6 Bacillus Calmette-Guérin (or Bacille Calmette-Guérin, BCG) is a vaccine against tuberculosis.

24
intermittent but do not employ any scarce minerals in electricity generation.<sup>7</sup> However, their conversion eciency is smaller and their manufacturing cost is larger as compared to conventional PVs. The CSP with storage technology neither depends on scarce minerals nor is intermittent, however its manufacturing cost, which includes highly expensive electricity storage facilities, is larger compared to organic PVs. Other electricity generation technologies include coaland natural gas red plants. As explained earlier, we do not include large-scale hydro and nuclear generation plants, which are not assumed to compete with solar electricity in the nal dispatch.

The key exhaustible primary resources employed in these electricity generation sectors are coal, natural gas, silver and indium. While the reasons for including fossil fuels are straightforward, our choice of metals requires additional explanation. Silver is commonly used as an electrode material the rst-generation crystalline Si-based PV cells, which currently take the largest market share of solar electricity. According to a recent study by the Silver Institute (2011), since the expansion of PV technology in the early 2000s, silver otake for production of solar panels has expanded dramatically, from around 3 million ounces (Moz) in 2004 to nearly 50Moz in 2010. Currently, silver end use for thick-lm PV accounts for nearly 10 percent of the total industrial demand for silver. Feltrin and Freundlich (2008) argue that if the decit of silver is not addressed, crystalline Si solar cells will hardly surpass the few terawatt range in the coming century. Similarly, indium is a critical input in indium tin oxide (ITO) transparent conductor lms, which constitute the base for the second-generation thin lm PVs. Indium has very scarce reserves, and the its price reached a high of $1,000/kg in 2008 and continues to grow. Fthenakis (2009) argues that even in the optimistic scenarios, thin lm PVs would not be sustainable if the price of indium increases by more than about 10 times above its current maximum price.

To quantify the signicance of market mediated responses to potential deployment of solar photovoltaics, we focus on the consumer electronics segment of consumer goods. The Silver Institute (2011) estimates that the electrical and electronic industry accounted for 243 Moz of silver, or 50 percent of total industrial silver demand in 2010, of which 41Moz of silver were used in the pro7This assumption requires additional clarication. While organic PV cells themselves do not contain any scarce materials, the metal back electrodes and the transparent conductive front electrodes both do. However, as mineral requirements for organic PVs are considerably lower than for conventional PVs (and are likely to be even lower in the future), we treat them as not dependent on scarce minerals.

11
39 they would have otherwise spent on the activity. These decreases can occur either through a budgetary reallocation by recipient governments to increase other types of spending or through a diminished level of ownsource revenue effort.

The own-source revenue response by recipient governments is of particular interest to analysts and granting governments. If an objective of a grant program in a developing country is to increase local government spending, this objective can not be achieved if the recipient government simply diminishes its own taxing effort.

The issue has been most extensively considered in developed countries using traditional economic analysis. The common formal approach to these analyses relies on the assumption that local communities have a welldefined preference function for government (G) and private goods (X) as exhibited in the indifference curve shown in Figure 1. At equilibrium E, the community consumes OX private goods and OG government goods. These public expenditures are financed through local tax and nontax revenues amounting to XX', or a tax rate of XX'/OX.

See, for example, Edward M. Gramlich, "State and Local Governments and Their Budget Constraint," International Economic Review, Vol. 10 (June 1969), pp. 168-182; Edward M. Gramlich and Harvey Galper, "State and Local Fiscal Behavior and Federal Grant Policy, Brookings Papers on Economic Activity, Vol. 1 (1973), pp. 15-54; James Henderson, "Local Government Expenditures: A Social Welfare Analysis," The Review of Economics and Statistics, Vol. 50 (May 1968), pp. 156-163; Enid Slack, "Local Fiscal Response to Intergovernmental Transfers," The Review of Economics and Statistics, Vol. 62 (1980), pp. 364-370; David L. Smith, "The Response of State and Local Governments to Federal Grants," National Tax Journal, Vol. 21 (September 1968).
Table 5a: Estimations of financial loan levels by asset holdings and district-level banking conditions

|||Full sample||Estimation wit<br>Districts|h state-year and i<br>with below medi|ndustry-year FE<br>an banking|Districts|with above medi|an banking|
|---|---|---|---|---|---|---|---|---|---|
||Baseline<br>estimation|Considering<br>owners of land<br>and buildings|Considering<br>renters of land<br>and buildings|Baseline<br>estimation|Considering<br>owners of land<br>and buildings|<br>Considering<br>renters of land<br>and buildings|Baseline<br>estimation|Considering<br>owners of land<br>and buildings|<br>Considering<br>renters of land<br>and buildings|
||(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|(9)|
|Total output|0.267+++|0.255+++|0.277+++|0.277+++|0.275+++|0.262+++|0.254+++|0.239+++|0.277+++|
||(0.010)|(0.011)|(0.015)|(0.019)|(0.019)|(0.027)|(0.012)|(0.013)|(0.018)|
|Total employees|0.055+++|0.043+++|0.094+++|0.053++|0.036|0.108+++|0.063+++|0.052+++|0.095+++|
||(0.015)|(0.015)|(0.021)|(0.025)|(0.026)|(0.030)|(0.018)|(0.019)|(0.026)|
|Indicator for young plant|-0.009|0.031|-0.114+++|0.001|0.043|-0.098+|-0.010|0.029|-0.114++|
||(0.024)|(0.027)|(0.039)|(0.034)|(0.040)|(0.059)|(0.031)|(0.034)|(0.052)|
|Indicator for rural/urban|0.031|0.034|0.007|0.059+|0.050|0.036|0.004|0.011|-0.014|
||(0.020)|(0.022)|(0.027)|(0.032)|(0.032)|(0.041)|(0.025)|(0.028)|(0.034)|
|Land and building assets|0.174+++|0.219+++|0.119+++|0.229+++|0.276+++|0.167+++|0.150+++|0.189+++|0.100+++|
||(0.011)|(0.012)|(0.012)|(0.013)|(0.017)|(0.018)|(0.011)|(0.013)|(0.013)|
|Plant machinery assets|0.199+++|0.188+++|0.192+++|0.189+++|0.177+++|0.182+++|0.201+++|0.192+++|0.195+++|
||(0.006)|(0.008)|(0.008)|(0.012)|(0.013)|(0.014)|(0.007)|(0.008)|(0.009)|
|Other assets|0.098+++|0.088+++|0.128+++|0.084+++|0.071+++|0.124+++|0.106+++|0.097+++|0.130+++|
||(0.004)|(0.004)|(0.007)|(0.006)|(0.006)|(0.010)|(0.005)|(0.005)|(0.010)|
|Observations|137434|83784|53650|45687|28654|17033|91382|54881|36501|
|Adjusted R-squared|0.499|0.490|0.518|0.552|0.537|0.588|0.468|0.462|0.474|

Notes: Table shows regressions of financial loan levels for ASI plants. Estimations consider the log amount of financial loans for each plant as a function of basic plant traits. Estimations include state-year and industryyear FE, with additional controls added as indicated by column headers. The second and third columns of each triplet partition the sample by whether the plant owns its land and buildings. Columns 4-6 and 7-9 partition the sample by whether the district's banking conditions in 2000 are above or below the median in terms of household banking access as reported in Census. Observations are weighted by ASI sample weights. Estimations cluster standard errors by district. +, ++, and +++ indicate statistical significance at 10%, 5%, and 1% levels, respectively.
Figure 7: Change in sales: Relative Shapley decomposition <!-- Start of picture text --> 60 58.6 59.7<br>40<br>32.8 32.9<br>30<br>21.6<br>20 17.2<br>13.3 12.8<br>7.6<br>.2 1 2.6 0 .9 1.4 1.5 .1 1.3 2.2 2.4<br>0<br>Round 1 Round 2 Round 3<br>Informality Size<br>Age Sector<br>Female-led Severity of the crisis (weighted Google mobility index)<br>Initial prod.<br>R2 explained by group<br>Relative Shapley Value (%) - Change in sales<br><!-- End of picture text --> Notes: The regressions also control for the country, but only the relative contribution of firm-level characteristics, including informality, are presented here. Source: Authors’ calculations using data from the World Bank Business Pulse Survey (BPS).

Table 3: Oaxaca Blinder decomposition

|Dependent variable: Change in sales|(1)|(2)|
|---|---|---|
||Conditional|Cont. initialproductivity|
|Diferential|||
|Prediction formal|-32.80***|-31.27***|
||(0.404)|(0.446)|
|Prediction informal|-44.81***|-44.94***|
||(0.600)|(0.747)|
|Diference|12.01***<br>(0.724)|13.67***<br>(0.870)|
|Decomposition|||
|Endowments|7.625***|9.297***|
||(0.641)|(0.762)|
|Coefcients|2.535***|2.499***|
||(0.772)|(0.898)|
|Interaction|1.845***|1.875**|
||(0.681)|(0.780)|
|Observations|13,364|10,066|

**N** otes: All continuous variables are winsorized at the 1% and 99%. Robust standard errors in parentheses

* p<0.10, ** p<0.05, ** p<0.01 Source: Authors’ calculations using data from the World Bank Business Pulse Survey (BPS).

# **5.4 The adjustment response of informal firms to the crisis is lower even after accounting for their lower initial capabilities**

Although physical distancing imposed during the pandemic accelerated the adoption of digital technologies, it also disproportionately benefited the larger firms and widened the digital divide with smaller firms (Cirera et al., 2021; Avalos et al., 2023). Given the negative 20
allows for a change in both intercept and slope at time _Tb_ , which is made perfectly correlated with the data. A potential problem with the Perron (1997) test is that it assumes no structural break under the null of unit root. Lee and Strazicich (2001) show that this assumption can result in spurious rejections. The two-break minimum LM unit root test, due to Lee and Strazicich (2003), is unaffected by whether or not there is a break under the null hypothesis. The results are reported in Table 1.

**Table 1 – Unit root tests**

|||**MADF**<sup>**GLS**</sup>|||**MPP**<sup>**GLS**</sup>||
|---|---|---|---|---|---|---|
||**Z={1}**|**Z={1, t}**|**_lags_**|**Z={1}**|**Z={1, t}**|**_lags_**|
|_t_<sup>_g_</sup>|-0.280|-3.391*|5; 1|-0.678|-2.607|5; 1|
|_t_<sup></sup>|-0.626|-1.379|4; 4|-0.811|-1.142|4; 4|
|_t_<sup>_i_</sup>|-1.282|-1.472|0; 0|-1.192|-1.254|0; 0|
|_t_<sup>_e_</sup>|-1.770|-2.029|0; 0|-1.539|-1.796|0; 0|
|_t_<br>_op_|-0.814|-2.472|3; 0|-1.123|-1.940|3; 0|
|**5% cv**|-1.95|-3.19||-1.98|-2.91||
|||**Per**<br>|**ron (1997)**||||
||**Model**|**Statistic**|**_Lags _**|**Break**|**5% cv**||
|_t_<sup>_g_</sup>|IO2|-250.14**|12|2004:03|-5.59||
|_t_<sup></sup>|IO2|-28.525**|12|2007:03|-5.59||
|_t_<sup>_i_</sup>|IO1|-4.381|10|2004:03|-5.23||
|_t_<sup>_e_</sup>|IO2|-223.96**|12|2007:04|-5.59||
|_t_<br>_op_|AO|-5.413*|1|2004:02|-4.83||
|||**Lee e S**|**trazicich (200**|**3)**|||
||**Model**|**Statistic**|**_Lags _**|**Break 1**|**Break 2**|**5% cv**|
|_t_<sup>_g_</sup>|2|-8.479**|3|2004:3|2007:3|-5.29|
|_t_<sup></sup>|2|-8.024**|3|2002:3|2006:1|-5.29|
|_t_<sup>_i_</sup>|2|-5.483*|4|2003:3|2006:1|-5.29|
|_t_<sup>_e_</sup>|2|-5.860*|2|2003:3|2007:2|-5.29|
|_t_<br>_op_|2|-10.099**|1|2004:4|2007:3|-5.29|

Note: * and ** mean that the null of unit root is rejected at the 5 and 1% significance level, respectively. cv stands for critical value.

The first panel of Table 1 shows that, except for output growth under the MADF<sup>GLS</sup> test with constant and trend, the null of unit root is not rejected at the standard 5% significance level according to both tests. This result, however, might be due to the presence of structural breaks.

The Perron (1997) test reaches a different conclusion. The results, reported in the second panel of Table 1, indicate that all time series but nominal interest rate are stationary once a structural
SENEGAL’S INFRASTRUCTURE: A CONTINENTAL PERSPECTIVE

**Figure 1. Infrastructure has contributed much to economic growth—but could contribute much more**

<!-- Start of picture text --> a. Infrastructure’s contribution to annual per capita economic b. Potential contribution of infrastructure to annual per capita<br>growth in West African countries, in percentage points, 2001–05 economic growth in West African countries, in percentage points<br>5<br>5<br>4<br>4<br>3 3<br>2 2<br>1 1<br>0 0<br>-1 -1<br>-2 -2<br>Roads Electricity Telecom Roads Electricity Telecom<br>Percentage Points Percentage Points<br>n a go r e i us<br>Beni Cote d'Ivoire Mauritius Guinea Burkina Faso Senegal Ghan Mauritania T o Nigeria South Africa Gambia Nig Sierra Leone Guinea-Bissau Niger Togo Nigeria Burkina Faso Guinea-Bissau Sierra Leone Benin Mauritania Gambia Senegal Ghana Guinea Cote d'Ivoire South Africa Maurit<br><!-- End of picture text --> a. Infrastructure’s contribution to annual per capita economic growth in West African countries, in percentage points, 2001–05 _Source_ : Calderón 2009.

It is in this context that Senegal’s sustained growth has been driven not only by groundnut and fish exports and tourism and trade, but also by transport and primarily the development of telecommunication services (World Bank 2007a). Despite its weaker performance in 2006, between 1996 and 2006 Senegal’s economy grew at an average annual rate of 4.7 percent, above the average of Sub-Saharan Africa (table 1), but still short of the sustained 7 percent mark per year needed to make important progress in reducing poverty.

**Table 1. Economic indicators in Senegal and Sub-Saharan Africa**

||GDP growth<br>(1995–2005)|Inflation rate<br>(1995–2005)|Fiscal primary<br>deficit, % of GDP<br>(2000–04)|Gini Index|Aid ($) per capita<br>(1994–2004)|
|---|---|---|---|---|---|
|Senegal|4.7|2.5|2.2|41.3|56.4|
|Sub-Saharan Africa|3.8|7.0|5.4(*)|47.1|26.6|

_Source:_ World Bank 2007a. _Note:_ (*) West African Economic and Monetary Union (WAEMU) average. GDP = gross domestic product.

The rate of growth of the Senegalese economy, if the growth fundamentals were to be raised to the level of the leader in the region, Mauritania, would be 2.7 percentage points (figure 1b)—a marked increase from the current infrastructure contribution of 1.03 percentage points. Two-thirds of this would potentially come from improvement in the power generation, transmission, and distribution networks.

While in many aspects Senegal compares favorably with its neighbors in West Africa, poor infrastructure services have had a severe impact on the economy. Inadequate supply of key infrastructure services has contributed to low productivity in the private sector, coupled by rising transportation and electricity costs (World Bank 2007a). Evidence from enterprise surveys suggests that infrastructure constraints are responsible for about 58 percent of the productivity handicap faced by Senegalese firms 3
# **Table 16: Who will benefit and how: stakeholder analysis**

|**Policy Option**|**Government of**<br>**Orissa**|**Tehsil-level revenue**<br>**bureaucracy**|**NGOs**|**Large land**<br>**owners**<br>|**Small and**<br>**marginal farmers**<br>|**Landless**<br>**farmers**|**Women**|**Tribals**|
|---|---|---|---|---|---|---|---|---|
|Issue jointpattas to<br>husband and wife|Y<br>(Promotion of social justice)||.|N<br>(Reduced perceived<br>control over family<br>land)<br>________________|_N_<br>(Reduced perceived<br>control over family<br>land)<br>_____________________||y<br>(Increased access to<br>land and control<br>over land-related<br>~**~** **~**~deci|y<br>(Make land<br>alienation<br>more difficult)<br>sions)<br>_ _ _ _ _ _ _ _|
|Evaluate the role of DRE<br>andBOR,and of the RI|Y<br>(Increased work efficiency)|_N_<br>(Reduced potential for rent-<br>seeking)||N<br>(Reduced ability to<br>manipulate the<br>system)|(Reduced delays and<br>rent-seeking)|||_|
|Abolish survey and<br>settlement operations|Y<br>(Reduced costs)|N<br>(Reduced potential for rent-<br>seeking)||N<br>(Reduced ability to<br>manipulate the<br>system)|Y<br>(Reduced rent-seeking;<br>less potential for losing<br>land to powerful<br>interests)|||Y<br>(Make land<br>alienation<br>more difficult)|
|Combine registration and<br>mutation|Y<br>(Increased revenue with less<br>incentive to undervalue<br>property)|N<br>(Reduced potential for rent-<br>seeking)||Y<br>(Reduced<br>transaction costs)<br>|Y<br>(Reduced transaction<br>costs)<br>|Y<br>(Reduced transaction<br>costs in the event of<br>land purchase)|||
|Systematic<br>computerization of land<br>records|Y<br>(Increased work efficiency)|N<br>(Reduced potential for rent-<br>seeking)|Y<br>(Improved<br>access to land-<br>based<br>information|N<br>(Reduced ability to<br>manipulate the<br>system)|Y<br>(Improved access to<br>land-based information|||Y<br>(Make land<br>alienation<br>more difficult)|
|Involve NGOs in land<br>consolidation and<br>awareness-raising|Y<br>(Improvement<br>in land<br>consolidation and ag.<br>Productivity; Strengthening<br>of civil society)|N<br>(Reduced potential for rent-<br>seeking)<br>|Y<br>(Increased<br>recognition of<br>their role)||||||
|Strict monitoring of<br>encroachment|**V**<br>(Increased redistribution of<br>wasteland)|**N**<br>(Reduced potential for rent-<br>seeking)|**V**<br>(Reduced costs<br>of litigation)|N<br>(Lose_defacto_<br>access to<br>encroached land)|_N_<br>_(Lose defacto_access to<br>encroached land)|**V**<br>(Increased prospect<br>of getting rightful<br>access to land)||**Y**<br>(Make land<br>alienation<br>more difficult)|
|Tenancy de-regulation|Y<br>(Improved agricultural<br>productivity through secure<br>land access to efficient<br>farmers)|N<br>(Reduced potential for rent-<br>seeking)||N<br>(Gradual erosion of<br>power and social<br>status in village<br>society)|Y<br>(Increased access to<br>land and security of<br>tenure)||||

66
**Figure 1: China’s Top 10 Provincial Recipients in FDI**

<!-- Start of picture text --> China: Top 10 FDI Regional Destinations<br>35%<br>30% 1998<br>1999<br>25% 2000<br>2001<br>2002<br>20%<br>15%<br>10%<br>5%<br>0%<br>Guangdong Jiangsu Shandong Shanghai Fujian Liaoning Zhejiang Beijing Tianjin Hubei<br><!-- End of picture text --> _Source_ : China Statistical Yearbook ( _various years_ ) Building a municipal labor market that will be attractive for dynamic and well-managed firms requires close attention to the urban environment. This is also crucial for pulling in FDI into higher technology activities. The quality of the urban environment, the standard of services, and amenities provided and the level of housing facilities is a function of many factors.

Chief among them is administrative capacity and governance which remains variable throughout urban China and at the forefront of central government’s attention. Several cities, especially in East Coast, have made concerted efforts to reduce red tape, to enhance transparency and to ease transaction costs for businesses by introducing electronic websites and permitting electronic processing of certain transactions (see Table 5). These changes are mirrored by the business climate in these cities and the entry of firms both local and foreign.

25