rafmacalaba/datause-encoder-data huggingface dataset:
The port efficiency measures by Blonigen and Wilson show that, in East Asia, Japanese ports are generally more efficient. Those in Korea, Taiwan, Singapore and Hong Kong are less efficient. And those in Southeast Asia and China are the least efficient. However, their ranking of the port efficiency may attract an observation on the nature of the measurement. Some of the most technically advanced ports in East Asia, such as Singapore and Hong Kong come in the middle of the list<sup>11</sup> . As shown in Figure 1, the ports in the developing countries in East Asia chronically congested. The leading ports in the region, such as Singapore and Hong Kong generally charge higher port tariffs, reflecting their market power, high demands and superiority in technology. On the other hand, the ports in Japan that are higher-ranked in efficiency generally maintain idle capacity with smaller demands.

As such, the measure of port efficiency appears to strongly reflect not merely the technical efficiency, but the costs in total, including both pecuniary port tariffs and charges and the implicit time costs from the congestion and inefficiency in all the process in the ports. Moreover, the higher demand and technical efficiency may bring about rent on the port tariffs. Reflecting them, the port efficiency measurements by Blonigen and Wilson cover more than “the inherent technical efficiency of a port”, reflecting other non-technical factors to determine the costs around the ports, as also observed by the authors. Our research objective calls for direct measurements to reflect the physical capacity of port infrastructure, instead of adopting their measurement. Notwithstanding, their measurements provide a good reference with rich information on the cost efficiency of the ports in a wider sense.

A survey article by Hummels (2007) also addresses the determining factors of _ad valorem_ transport costs<sup>12</sup> from the U.S. statistics. In the regression, the dependent variable is the _ad valorem_ transport cost on the SITC 5-digit commodity base; and the independent variables include distance, weight per value, and fuel costs; running two separate regressions, namely air shipments and ocean shipment. The specification of the regressions of air shipments includes time-trend and an interaction term between distance and time trend, in addition, while that of ocean shipment includes containerized share of trade. The regression does not contain any

> 11 For example, Singapore continues to take the top in the ranking of port infrastructure quality index in _The Global Competitiveness Report_ .

> 12 Defined as: (Import Charge) / (Import in FOB price). This measure is analogical with the _ad valorem_ tariff rate.

14
**Figure 4: Emerging market private corporate bond issuance by quarter**

<!-- Start of picture text --> Subprime<br>crisis<br><!-- End of picture text --> <!-- Start of picture text --> $billion Private corporate bonds<br>Subprime<br>45 140<br>crisis<br>40<br>120<br>35<br>Asian Number of 100<br>30<br>25 crisisFinancial Deals (right axis) 80<br>20 60<br>15<br>40<br>10<br>20<br>5<br>0 0<br><!-- End of picture text --> Data source: Dealogic DCM analytics

# **_Large emerging-market corporate refinancing needs_**

Corporations based in emerging markets now face the challenge of servicing their substantial debt obligations in an environment of sluggish global growth, high currency volatility, shrinking bank credit, and intensified competition from sovereign borrowers in advanced economies. Of the key drivers of emerging-market corporate bond issuance volume in the next few years, the need to refinance a large volume of foreign currency debt will be the strongest. Approximately $951 billion of emerging-market corporate debt is due to mature in the bond and bank loan markets between 2010 and 2013, with the bulk of that amount—about 75 percent— originating from the syndicated loan market.

Given the fragility of the international banking industry, a full rollover of emergingmarket bank loans seems unlikely, leaving bond markets to absorb a portion of such loans. Several factors will dictate the amount of maturing loans that make their way into bond markets: rating status, other available financing options (including those in equity markets), and loanspecific characteristics and covenant clauses. Assuming 25 percent of borrowers with an investment-grade rating in their home countries decide to refinance in bond markets, issuance volumes originating from this source would be in the order of $54 billion in 2010, $46 billion in 2011, and $30 billion in 2012.

Pursuit of cross-border M&A as part of multinational companies’ growth and expansion strategies is also expected to contribute to the rebound in emerging-market corporate bond issuance in the coming years. While detailed data on the payments of M&A deals involving emerging-market companies are not disclosed, in practice, such deals can be funded through cash, 8
at marriage is consistently declining in Gujarat relative to its neighboring states, 2 years after the riots. According to Appendix A, figure A.2, the probability of women getting married before 18 increased after the Gujarat riots.

# **7.2 Synthetic Controls Approach**

The results from the event study approach (Figures 1(a) and 1(b)) suggest that there were some differential trends between Gujarat and the control states even before the riots of 2002 for a few years. To address this concern, we examine the effects of the Gujarat riots by employing the synthetic controls approach suggested by Abadie and Gardeazabal (2003). Using a combination of other Indian control states or the donor pool, we first construct a synthetic Gujarat that best approximates the characteristics of women in Gujarat before the riots of 2002. More specifically, synthetic Gujarat is constructed as a weighted average of the donor pool, with weights chosen so that the resulting synthetic Gujarat best reproduces the values of a set of predictors of women’s age at marriage in Gujarat before the riots in 2022. We then use the post-riot outcomes for synthetic Gujarat to estimate the outcomes that would have been observed in Gujarat in the absence of the riots of 2002. Next, we compare the outcomes of synthetic Gujarat to actual Gujarat after 2002.

We collapse the individual-level data in a state-year panel for the synthetic controls method. To approximate the outcomes (age at marriage and proportion of child marriages) at the state level, we use the proportion of women who reside in rural areas, reside in households with male heads, belong to rich or poor households, are Hindus, and are scheduled castes/scheduled tribes/other backward classes. Appendix E, table E.1 shows that Gujarat and synthetic Gujarat are similar across several demographic characteristics.<sup>3</sup> The results from the synthetic control methods are presented in Appendix B, figures B.1 and B.2. Figure B.1 suggests that the age at marriage in Gujarat is identical to that in synthetic Gujarat before the riots of 2002 and begins to decrease two years after the riots. These findings are similar to what we find using the event study method in figure 1(a). The probability of child marriage also increased after 2002 (Appendix B, Figure B.2).

# **7.3 Alternative estimator**

An emerging literature documents several problems associated with using the traditional difference-in-difference methods. However, since most of these problems arise in the case of staggered treatment timings, we have used the traditional difference-in-difference methods for our main estimation. The majority of the new methods are mostly applicable only with

> 3Synthetic Gujarat consists of all other Indian states except Gujarat with varying weights.

13
9 TabLe 2. Population Growth by Geographic Region, 1985-2025

||Poput<br>(millio|ation<br>ns)|Growt<br>(perc|h rate<br>ent)|Birth<br>(per|rate<br>1,000)|Death<br>(per|rate<br>1,000)|
|---|---|---|---|---|---|---|---|---|
|Region|1985|2025|1985-90|2020-25|1985-90|2020-25|1985-90|2020-25|
|World|4,843|8,262|1.73|0.96|27.1|17.8|9.8|8.2|
|Africa|560|1,508|<br>3.06|<br>1.76|<br>44.8|<br>24.3|<br>14.2|<br>6.6|
|America|667|1,040|1.55|0.72|23.2|15.3|7.9|8.1|
|Asia|2,821|4,815|1.84|0.91|27.7|17.2|9.2|8.0|
|Europe, U.S.S.R.|771|864|0.48|0.14|15.0|12.9|10.3|11.5|
|Oceania|25|35|1.41|0.56|19.9|14.7|8.1|9.1|

Note: In all tables, figures may not add up to given totals because of rounding.

more people are now being added to the planet every year than ever before, even though the peak population growth rate (2.1 percent in 1965-70) is past. In 1987, about 88 million people were added, and this number will increase for another decade, eventually reaching about 92 million.

In the next century, the projections indicate that world population will continue to grow, though more slowly. Not until the 22nd century do the projections show population stabilizing. At that point, world population will probably be well above 10 billion. Changes in the oroiections Table 3 indicates that these projections involve important changes since the 1980 projections, but only minor changes since last year.

Since 1980, the world population for the year 2000 has been revised upward by 2 percent, because of a substantial upward revision for Africa and a smaller upward revision for Asia, only partly balanced by downward revisions for America and Europe. The current projections give a population for the entire continent of Africa in the year 2000 that is 8 percent larger than in the 1980 projections. This is based on ample recent evidence that fertility levels are more resistant to change than had earlier been assumed. For Asia, the change in the projections mainly concerns China. A recent upswing in the birth rate makes it less likely that Chinese fertility will soon dip below replacement and stay below for an appreciable period. In contrast to Africa, Latin America has shown larger fertility declines than previously projected. For Europe and other developed countries, the revision has mainly involved stretching out the period of below-replacement fertility.
Asia’s numbers are aided by a large population served by self-help groups in India (SHGs) subsidized by the National Bank for Agriculture and Rural Development (NABARD).<sup>8</sup> In 2013, SHGs funded by NABARD accounted for 54.4 million customers in the Microcredit data, 43.5 million of whom were among the poorest (Table 8, Microcredit Summit 2015).<sup>9</sup> We calculate that in percentage terms the NABARD group accounts for 33 percent of all customers in Asia and the Pacific in 2013. In global terms, NABARD alone accounts for 26 percent of the total. According to MIX Market (2017, p. 32), lenders in Bangladesh in total account for another 24 million active borrowers.

||**Total**<br>**Clients**<br>**(million)**|**Percenta**<br>**Women**|**ge within ea**<br>**Poorest**|**ch region**<br>**Poorest**<br>**Women**|
|---|---|---|---|---|
|Sub-Saharan Africa|15.9|53.8%|54.7%|36.8%|
|Asia and Pacific|166.9|81.0%|60.8%|51.2%|
|Latin America and|17.4||||
|Caribbean||61.6%|15.8%|11.5%|
|Middle East and N. Africa|5.3|52.8%|23.7%|17.2%|
|**"Developing World"**|205.5|92.0%|55.5%|45.9%|

# **Table 2. Microfinance heterogeneity**

Customers by region, gender, and poverty level Data as of December 31, 2013. Adapted from Table 7, Microcredit Summit Campaign, _State of the Summit Report 2015_ 8 For a recent survey on microfinance in India (arguing that there’s “still much to do”), see Sinha et al (2017). For an inquiry into SHGs in South India (and further references), see <mark>Guérin</mark> et al. (2010). See also www.nabard.org.

9 Since some SHGs are accounted for independently in the Microcredit Summit data, the NABARD numbers net out the overlapping institutions. The SHG fraction of the whole is thus slightly higher (by about 3 percent) when the other SHGs are also included (Microcredit Summit 2015).

9
**<u>Table 6:  Biomass and Per Capita Consumption Expenditure After Controlling for other Variables</u>**

||Coeff Biomass|Coeff Bioma<br>Squared|ss|Mean Biomass<br>@(cumper ha)|Elasticity|
|---|---|---|---|---|---|
|Overall|0.0010209<br>**|-0.0000194|***|20.22|0.005%|
|Non-Poor|0.0000051|-0.0000040||19.35||
|Poor|0.0015476<br>***|-0.0000200|***|21.20|0.01%|
|Rural North|0.0016728|-0.0000176|*|42.97||
|Rural Center|-0.0001699|-0.0000079||13.70||
|Rural South|0.0025929<br>***|-0.0000347|***|18.61|0.02%|

@ These numbers differ from Table 3 because of averaging differences.

41
the identification information, and instead use the variation arising from the intervention to study spillover effects on other outcomes. This paper shows the important relationship between identification and collection capacity: whereas making the tax base legible is an essential first step, it is insufficient to significantly increase revenues; information on penalties for noncompliance as well as signals of a greater likelihood that those penalties will be enforced are key complements to translate discovered tax liabilities into tax revenues.<sup>4</sup> These results directly inform policy. Distinguishing between identification, detection, and collection capacity is crucial for improving tax collection because it allows the tax authority to determine which capacity is binding and target its investments and policy instruments accordingly. For example, a lack of commensurate increases in detection and collection capacity may be responsible for the disappointing revenue impacts of mass taxpayer registration campaigns (Gallien, Occhiali and van den Boogaard, 2023; Mascagni et al., 2022; Moore, 2023). Whereas many policy conversations on tax administration reform are centered around adopting new technology and improved databases to better understand the tax base,<sup>5</sup> these results emphasize the unavoidable need for investment in the state’s ability to enforce tax laws and collect unpaid liabilities, which are often more politically difficult policies to implement. More broadly, this paper also relates to a large literature on the challenges of making the tax base more legible through firm formalization and business registration initiatives (Bruhn and McKenzie (2014) and Floridi, Demena and Wagner (2020) review this literature).

In addition, this paper contributes to our understanding of how technology can improve tax administration in emerging economies, complementing recent papers on how technology interventions in property taxation could improve the effectiveness of tax collectors (Dzansi et al., 2022) and the accuracy of property valuation (Knebelmann, Pouliquen and Sarr, 2022).<sup>6</sup> Finally, this paper contributes to a vibrant literature on interventions conducted in collaboration with tax authorities to understand different approaches to promoting tax

> 4 Besides the potential revenue impacts from expanding the tax base, strengthening identification capacity may also improve horizontal equity, for example, by ensuring that taxpayers in the formal sector are treated similarly to those of same income in the informal sector.

> 5 For example, in 78 percent of countries with an approved World Bank tax project from 2010 - 2022, the project included a tax digitization component (author’s analysis of World Bank projects). 6 Okunogbe and Santoro (Forthcoming) provide a review of this literature and Knebelmann (2022) describes applications for property tax in particular.

6
# **2.1 Health data**

We choose infant mortality as our primary health outcome. This choice conveys at least two significant statistical advantages. First, as noted by Chay and Greenstone (2003), infant survival is a shortterm measure; other measures of health stock, captured later in life, necessarily reflect the effect of many more health shocks experienced in an individual’s lifetime. Second, complete birth histories are available in certain Indian demographic surveys, so we can construct long pseudo-panels of infant survival to maximize statistical power. In contrast, morbidity variables such as diarrhea incidence and low birth weight are only available cross-sectionally from the time of survey; too few of such surveys have been completed for us to construct a meaningful panel. Panel variation in infant mortality allows us to include detailed temporal and cross-sectional fixed effects in regression analyses, which account for time-varying shocks to national infant health and time-invariant characteristics of specific areas, respectively.

We focus primarily on deaths within the first month of life, i.e., neonatal mortality, although we also test for a policy impact on one- _year_ mortality. The first month is the most vulnerable period of an infant’s life (United Nations Children’s Fund 2015). Globally, neonatal mortality accounts for over half of all infant deaths (World Development Indicators 2017); in our own data from India, its share of under-one mortality is 70 percent. Furthermore, several existing studies of pollution – in both water and air – and child health show that the largest impacts occur within one month of birth (Chay and Greenstone 2003; Gluckman et al. 2008; Currie and Almond 2011; and Brainerd and Menon 2014). While neonatal mortality is not a complete measure of the health costs imposed by water pollution, it nonetheless represents a very large loss of life, especially in the Indian context.

Our infant health data come from the Reproductive and Child Health II (RCH-2) module of the District-Level Household Survey II (DLHS-2), a national demographic survey conducted in two phases from 2002 to 2005. In the RCH-2 module, mothers report age and survival for all of their children; from these birth histories, we create a panel of child-month mortality in the first year. The full national dataset spans the years 1967-2004. The first four years of this range includes 2, 0, 0, and 6 reported births nationally; starting in 1971, the reported birth count rises roughly monotonically from 42 towards its peak of 80,961 in 1998. Because of the lack of data from 1967-1970, we drop these years from the sample. This leaves us with with 1,393,330 birth observations from the years 1971-2004, 647,865 of which are to mothers living within the Ganga Basin (240 districts) at the time of survey.

# **2.2 Pollution data**

To measure water quality, we use river pollution data collected under the auspices of India’s National Water Quality Monitoring Program (NWMP). These data were originally gathered by Greenstone and 7
49 Table 12 documents these relationships using the data from several transition economies. For Hungary and Poland, all individual relation are "right": the minimum wage, the minimum pension and the minimum unemployment benefit are all greater or equal to the poverty line (in both countries, the minimum pension is used as the “screening” poverty line). In Estonia, the individual relations are also "right" with the exception of unemployment benefit that is less than the poverty line. In Russia and Latvia, on the contrary, the poverty line for an adult is several times greater than either the minimum wage, the minimum pension or the unemployment benefit.

When we look at the situation of a "standard" family only in Hungary does it stay ahead of poverty regardless of whether its adults members are employed, unemployed or retired. This is due to relatively high family allowance.® In Poland and Estonia, however, a standard household would stay ahead of poverty only if both adults are employed. Otherwise, its income will be about 10-20 percent lower than the poverty threshold. In Latvia and Russia, the "standard" household is deeply below the poverty line (and thus can, at least in principle, try to claim social assistance) whether its members and unemployed, retired or work at low wages. The poverty lines are set unrealistically high. It clearly does not make sense to have a poverty line of $45-$50 per adult when the minimum wage is $25 as in Latvia, or about $15 as in Russia. In effect, Latvian government is in the process of revising the poverty line.*

> “The minimum income requirement for a standard 4-member household is, based on the OECD equivalence scale, assumed to equal 2.7 adult units.

> **The World Bank suggested lowering the current poverty line to about $22 per capita per month.
2 investment. In some of the literature, the view prevails that FDI can serve two purposes, namely, raise investment and relieve foreign exchange shortages.<sup>2</sup> Unless FDI. affects national saving, however, it can raise domestic investment or provide additional financing for a preexisting current account deficit or achieve some combination of the two, but these two effects must always sum to one. In other words, if $100 FDI increases capital formation by only $75, it would provide $25 for additional current-account financing. If it simply substitutes for an alternative type of capital inflow, however, FDI neither raises capital formation nor does it provide additional current-account financing.

This study examines the question of whether FDI to a sample of developing countries substitutes for other capital flows, increases capital formation, or provides additional foreign exchange for balance-of-payments support. Using James Meade's (1951) distinction between autonomous and accommodating capital flows, Philip Turner (1991, 91-95) addresses the question of whether or not net FDI flows are accommodating and hence constitute additional balance-of-payments financing by regressing components of the capital account on the current account financing requirement (both in first differences) for some OECD countries.

Turner's estimated equation takes the form: _AKFi = ao + a, AKFR,_ where AKFi is the year-on-year change in the net capital flow item expressed as a percentage of _GNP_ and _AKFR_ is the year-on-year change in the current account minus changes in official reserves also expressed as a percentage of GNP (both in current prices). Turner (1991, 92) finds that short-term bank flows are significantly correlated with the current account financing requirement with coefficients ranging from 0.27 (United Kingdom) to 0.88 (Canada) for seven of the 10 OECD countries. In the case of FDI, however, Turner concludes that this flow is much closer to being autonomous than accommodating; the coefficient is significant only in the case of France with a value of only 0.13.

Using Turner's. methodology with annual data on net capital flows from _International Financial Statistics_ CD-ROM for a sample of 16 developing countries<sup>3</sup> for the period 1975-

> 2For example, Laurence Cockcroft and Roger Riddell (1991, 3) note: "Two of the principal factors inhibiting higher levels of economic growth in Sub-Saharan Africa in the 1990s are low levels of investment and foreign exchange shortages. The first attraction of foreign investment lies in its potential to address both these constraints."

3 Argentina, Brazil, Chile, Egypt, India, Indonesia, Korea, Malaysia, Mexico, Nigeria, Pakistan, the Philip-