rafmacalaba/datause-encoder-data huggingface dataset:
homogeneous future increase of 10% in extreme water levels during tropical storms. In all likelihood, some regions of the world may experience a smaller increase and others a larger increase. Better local modeling of the impact of climate change on storm intensities will further fine tune future forecasts.

In the next section, we describe the methodology and data sources used to estimate the impact of storm surges in developing countries. Results are presented in Section III first at the global level, and then for each of the five regions. The above 6 indicators are further presented individually for each country comprising each of the five regions. Section IV concludes.

# **II. Methodology and data sources**

This section briefly discusses the methodology and data sources pertaining to the delineation of storm surge zones, and then discusses the methodology and data sources for the impact indicators used in this paper.

# **II.1 Storm surge zones**

# **(i) Methodology**

Recently released hydrologically conditioned version of SRTM data (part of the HydroSHEDS dataset) was used for elevation in this analysis. All 5ox5o coastal tiles of hydrologically conditioned version of 90 m SRTM data were downloaded from http://gisdata.usgs.net/Website/HydroSHEDS/viewer.php. Conditioning of the SRTM data refers to a series of processing steps that alter elevation values in order to produce a surface that drains to the coast (except in cases of known internal drainages). These steps include filtering, lowering of stream courses and adjacent pixels, and carving out barriers to stream flow. Despite known limitations, SRTM represents the best available high resolution global elevation model and, to our knowledge, there is no global dataset of shoreline protection.

5
minerals including crude oil are retained by the center. In 1993, the center retained the revenue from personal income tax as well, but in 1994 this source was assigned to the provinces except for Ba Ria-Vung Tau (where there is oil). The provinces are assigned the revenues from land and housing tax, slaughter tax, license fee, registration fee, depreciatL n and tax on local enterprises, revenue from lotteries, and other minor fees and taxes. In 1993, agricultural tax was shared with the provinces, but in 1994 it was entirely assigned to the provinces. Similarly, in 1994, 50 per cent of profits tax collected in 8 provinces will be retained by the center, though until 1993, all the provinces retained the entire amount."L The turnover tax is the major balancing item which is shared wiLh the provinces in both years though, until 1993, all the provinces received the entire amount. As already mentioned, the share of turnover tax forms the balancing (ap-filling) factor.'<sup>2</sup> In 1994, 14 provinces will receive less than 100 per cent of turnover tax and the remaining 39 provinces will get cash grants in addition.(plus 100 per cent of the tax).

As noted earlier, in an ideal system, a mix of general purpose and specific purpose transfers would likely be required. General purpose transfers would be designed to ensure that fiscally disadvantaged provinces would be able to provide a minimum "national sEandard" package of public services at a reasonable tax rate. Such grants should generally be structured to take into account both the "needs' of different provinces and their "capacity" to meet their needs out of their own resources. If properiy designed, such nequalization" grants can also ensure that local fiscal efforts are maintained at reasonable levels.'<sup>3</sup>

- The eight rich provinces receiving 50 per cent of the share are, Ho Chi Minh City, Ha Noi, Ba Ria-Vung Tau, Long An, Kien Giang, Dong Nai, Song Be and Quang Ninh.

- 12 Thus, a province's share of turnover **tux** is given by (ErR,) /T, if (E,-RR) > 0 where E,, Rt and Ti respectively represent expenditures, assigned revenues and revenue from tumover tax of the i* province.

- 3 For an example of such a grant scheme, see Bird and Wallich, Financing Local Govermnent in Hungary, WPS, 19 869, 1992.

23
**Table 4.1.1 : Other Antidumping User Countries with Initiation Information Only in the Database**

|**Country Code**<br>**(3-letter CTY)**|**Country Name**|**Excel Workbook**<br>**File Name**|**Spreadsheet**<br>**Names within**<br>**Country**<br>**Workbook**|**Available**<br>**Years of**<br>**Data**|**Current**<br>**Version**<br>**(last updated)**|
|---|---|---|---|---|---|
|BGR|Bulgaria||AD-BGR-Master ,|||
|CHL|Chile||AD-CHL-Master ,|||
|CHN|China||AD-CHN-Master ,|||
|CRI|Costa Rica||AD-CRI-Master ,|||
|CZE|Czech Republic||AD-CZE-Master ,|||
|ECU|Ecuador||AD-ECU-Master ,|||
|EGY|Egypt||AD-EGY-Master ,|||
|GTM|Guatemala||AD-GTM-Master ,|||
|IDN|Indonesia||AD-IDN-Master ,|||
|ISR|Israel||AD-ISR-Master ,|||
|JAM|Jamaica||AD-JAM-Master ,|||
|JPN|Japan||AD-JPN-Master ,|||
|LVA|Latvia|AD-OTH-10xls|AD-LVA-Master ,|1995-2003|v1.0|
|LTU|Lithuania|v..|AD-LTU-Master ,||(8/2005)|
|MYS|Malaysia||AD-MYS-Master ,|||
|NIC|Nicaragua||AD-NIC-Master ,|||
|PAK|Pakistan||AD-PAK-Master ,|||
|PAN|Panama||AD-PAN-Master ,|||
|PRY|Paraguay||AD-PRY-Master ,|||
|PHL|Philippines||AD-PHL-Master ,|||
|POL|Poland||AD-POL-Master ,|||
|SVN|Slovenia||AD-SVN-Master ,|||
|TWN|Taiwan||AD-TWN-Master ,|||
|THA|Thailand||AD-THA-Master ,|||
|TTO|Trinidad and Tobago||AD-TTO-Master ,|||
|URY|Uruguay||AD-URY-Master|||

The WTO data was originally collected and described in Miranda, Torres and Ruiz (1998) and has since been updated as part of the WTO’s Rules Division Antidumping database.<sup>14</sup> We report only the information available in the WTO dataset on investigations for other WTO members, as detailed in the table below, with one “Master” sheet per using country:

> 14 The data for the WTO Rules Division Antidumping database is taken from the Semi-annual reports Members are obliged to submit to the WTO Committee on Anti-Dumping Practices. Thanks to Raul Torres and Johann Human for making this database available.

37
**Table 5: Estimated benefit withdrawal rates by city**

|Regression coefficient of DB<br>receipts on income net of DB|n|OLS|IV|
|---|---|---|---|
|Beijing|1242|-0.0574***<br>(0.0213)|-0.2727***<br>(0.045)|
|Shenan|918|-0.0955***|-0.1817***|
|yg||(0.009)|(0.024)|
|Jinan|856|-0.0718***|-0.0846***|
|||(0.011)|(0.029)|
|Wh|846|-0.0885***|-0.1438***|
|uan||(0.008)|(0.028)|
|Chnin|1187|-0.0460***|-0.0633**|
|ogqg||(0.004)|(0.030)|
|Tihi|480|-0.0444***|-0.1535***|
|ansu||(0.016)|(0.056)|
|Pili|475|-0.1227***|-0.1073**|
|ngang||(0.018)|(0.045)|

<u>Note: Whole sample. BWR estimated by regressing DB payments on income net of DB. IV estimates use lagged</u> formal salary and lagged property income as the IVs. Robust standard errors in parentheses. ***: significant at 1%; **significant at 5%; *: Significant at < 10%.

**Table 6: Poverty transitions with and without the** **_Dibao_ program**

|||Actual tr<br>in 2<br>Above<br>line|ansitions<br>009<br>Below<br>line|Simulat<br>DB=0 i<br>Above<br>line|ed with<br>n 2009<br>Below<br>line|Simulated<br>DB=0 i<br>Above<br>line|with∆<br>n 2009<br>Below<br>line|
|---|---|---|---|---|---|---|---|
|2007|Above<br>line|1944|32|1751|225|1905|71|
||Below<br>line|84|9|52|41|63|30|

<u>Note: The cut-off line is set at 1.5 times the local DB line.</u> 24
eat _healthy_ and nutritious foods, (4) _ate less_ than should have eaten, (5) had _skipped_ a meal, (6) _run out_ of food, (7) was _hungry_ but did not eat, (8) went without eating for a _whole day_ . All estimations use sampling weights to capture systematic non-response and attrition in phone surveys. Standard errors, clustered at district (woreda) level, are given in parentheses.<sup>*</sup> _p_ < 0.10,<sup>**</sup> _p_ < 0.05,<sup>***</sup> _p_ < 0.01.

Finally, Table 8 presents the disaggregated DID estimates for labor market and livelihood outcomes. We use data from rounds 1-10 of the surveys for this analysis, where rounds 1-8 represent the pre-war and rounds 9-10 represent the post-war-onset periods. Again, these results confirm that pre-war trends of participation in various labor market and livelihood activities are generally statistically similar trends across households affected and unaffected by the armed conflict, as evidenced by the coefficients of the interaction between Round 2 – Round 8 dummies and the indicator for Tigray region. Furthermore, immediately after the outbreak of the war households from Tigray experienced a significant reduction in economic activities, with the war reducing participation in any economic activity by 20 - 21 percentage points.

However, the impacts vary by type of livelihood activity. Relative to the baseline, households from Tigray experienced 20 - 22 percentage point reduction in participation in nonfarm business activities in the aftermath of outbreak of the armed conflict (December 2020 and January 2021). Similarly, war-affected households reported 19 - 20 percentage point reduction in participation in wage-related activities in the first two months after the outbreak of the conflict.<sup>30</sup> The sizes of these impacts are comparable to the aggregated results in Table 5. Consistent with the aggregated results in Table 5, farm activities, however, appear to be unaffected. These findings are intuitive because relative to smallholder farming, the war has led to massive destruction of business enterprises, infrastructure, and disruptions of major public services (electricity, telephone, banking and transport services), which are essential sources of these activities. This is consistent with evolving evidence that agriculture in general and smallholder farming activities can be resilient to covariate shocks such as armed conflict and pandemic. For example, some recent macro and microlevel studies show that farming activities are relatively resilient to the COVID-19 pandemic and associated mobility restrictions (e.g., Amare et al., 2021; Josephson et al., 2021; Khamis et al., 2021).

> 30 We note that the parallel trends assumption does not appear to hold for non-farm activities, with pre-war trends in Tigray indicating an already deteriorating environment. This may have to do with an increasingly worsening security situation on highways leading to Tigray with vigilante groups reportedly confiscating goods being transported to Tigray through Amhara region prior to the start of the war in November 2020.

32
**<mark>Table 18 Exploring the Presence of Omitted Variable Bias in Base OLS Regression Results Underlying the Mean Decomposition South, Male Category of Additional Covariates Integrated to the Base Regression</mark>**

|_VARIABLES_|**Category of Ad**<br>_Base South_|**ditional Covariates**<br>_Manager_<br>_characteristics_|**Integrated to the Ba**<br>_Plot_<br>_characteristics_|**se Regression**<br>_Geospatial_<br>_characteristics_|_Crop fixed effects_|_Community_<br>_characteristics_|
|---|---|---|---|---|---|---|
|Female manager=1|||||||
|Age|-0.000624|-0.0318|0.00119|0.00252|0.0173|0.00878|
||(0.0240)|(0.0320)|(0.0241)|(0.0246)|(0.0252)|(0.0261)|
|Age Squared|8.49e-05|0.000386|5.98e-05|6.32e-05|-0.000117|-8.65e-06|
||(0.000210)|(0.000290)|(0.000210)|(0.000217)|(0.000226)|(0.000230)|
|Years of schooling|-0.0121|-0.00762|-0.00680|-0.00800|-0.0131|-0.0152|
||(0.0155)|(0.0157)|(0.0152)|(0.0156)|(0.0146)|(0.0157)|
|Manager is nonmuslim†|-0.246|-0.0524|-0.191|-0.161|-0.426|-0.533|
||(0.401)|(0.423)|(0.393)|(0.390)|(0.395)|(0.424)|
|Manager has nonfarm activity†|0.125|0.122|0.141|0.0873|0.204|0.171|
||(0.157)|(0.163)|(0.157)|(0.163)|(0.154)|(0.160)|
|Household female adult size (age 12-60)|-0.108**|-0.219**|-0.112**|-0.0981*|-0.0985**|-0.102**|
||(0.0521)|(0.108)|(0.0533)|(0.0517)|(0.0490)|(0.0519)|
|Household male adult size (age 12-60)|0.122**|0.00757|0.112*|0.128**|0.0955|0.0601|
||(0.0603)|(0.0906)|(0.0608)|(0.0614)|(0.0585)|(0.0583)|
|Child dependency ratio|0.131|-0.0758|0.106|0.158|0.0856|0.159|
||(0.131)|(0.246)|(0.129)|(0.134)|(0.121)|(0.138)|
|Log [GPS-Land Area (HA)]|-0.804***|-0.816***|-0.830***|-0.810***|-0.780***|-0.852***|
||(0.140)|(0.138)|(0.132)|(0.155)|(0.137)|(0.168)|
|Log [GPS-Land Area (HA) Squared]|-0.0418|-0.0437|-0.0484*|-0.0448|-0.0399|-0.0459|
||(0.0275)|(0.0265)|(0.0260)|(0.0303)|(0.0267)|(0.0313)|
|Plot distance to household|0.000748|0.000741|0.000768|0.000432|0.00310*|0.000372|
||(0.000898)|(0.000968)|(0.000862)|(0.000818)|(0.00178)|(0.000890)|
|Access to extension†|0.284|0.296|0.274|0.210|0.220|0.237|
||(0.280)|(0.289)|(0.282)|(0.275)|(0.253)|(0.285)|
|Grows cash crop†|<br>-0.0357|<br>-0.000977|<br>0.442|<br>0.0101|<br>0.382|<br>0.163|
||(0.236)|(0.241)|(0.277)|(0.251)|(0.352)|(0.239)|
|Only one crop on plot †|<br>-0.573***|<br>-0.540***|<br>-0.580***|<br>-0.524***|<br>0.317|<br>-0.577***|
|Robust standard errors in parentheses. *** p<0|(0.163)<br>.01, ** p<0.05, * p<0|(0.176)<br>.1. State fixed effects|(0.166)<br>not displayed. † indi|(0.172)<br>cates dummy variable|(0.221)|(0.169)|

56
# **3.1 Variable definition, construction, and underlying data**

We begin by identifying the set of disputed products at the Harmonized System’s 6-digit (HS-06) level from policies described in WTO dispute settlement documentation and other national government sources,<sup>9</sup> which we then match against import data at the HS-06 level from UN Comtrade made available via the World Bank’s World Integrated Trade Solution (WITS) database. The HS-06 level is the most disaggregated level of imports that is consistently defined across countries, and in any given year in our sample there are slightly more than 5000 such products potentially imported by any country.<sup>10</sup> While our approach is also capable of handling the many disputes that take place at higher levels of aggregation than the HS-06 level, it is necessarily imperfect in that it will tend to overstate the dollar value of trade at stake for a few disputes in which the respondent country’s alleged policy was applied at its more narrowlydefined (e.g., HS-08 or HS-10) level of aggregation.

We construct and examine a number of different measures characterizing the bilateral data for the international trade under dispute. We first define each variable of interest here; more detailed information on each variable is included in the Appendix.

Our first variables characterize the _scope_ of products and the _levels_ of import market access for the products subsequently under dispute. The scope of products is defined as the count of HS-06 product codes and may be used to proxy for the range of a particular policy in order to assess how difficult to overcome would be the collective action problem involved in, say, politically organizing affected firms both within and across potential complainant countries (Olson, 1965).

Next, we characterize market access levels so as to also allow for potential bilateral variation by considering the respondent country’s imports from complainants, third parties, and non-participants. One measure is simply the value of bilateral imports of the disputed product in constant (2005) US dollars. An alternative measure that helps normalize issues related to importing country size is the bilateral share of the respondent’s import market for the disputed product. Finally, in some applications we also examine

> 9 For disputes involving allegations of WTO-inconsistent use of antidumping, countervailing duties, and safeguards, we also rely on information from the World Bank’s _Temporary Trade Barriers Database_ (Bown, 2013).

> 10 Cross-country comparisons of counts of products beyond the HS-06 level are not meaningful because countries have discretion in how to establish their HS-08, HS-10 (etc.) lines.

12
19 substantially relaxed to make firing decisions by firms easier. While labor productivity (measured as percentage growth of GDP per person employed) is reported to have increased from -5.3 in 1990-1992 to 4.4 in 2005-2008, the employment to population ratios did not show much change: in 2008, it was still averaging 64 percent for the entire population (15 years and older), the same level observed in 1991. For the youth (ages 15-24), it has declined slightly in that twenty-year period, from 50 to 49 percent.<sup>13</sup> Clearly, the labor market reforms have not led to the creation of new formal sector employment opportunities.

The dynamics of population growth makes things even more challenging (Figure 3). With population growth projected to be 2.2 percent in the next 25 years and about 2-3 million young people entering the labor force every year, Africa’s workforce will grow by 11-14 million a year for the next couple of decades. The African private sector faces the challenge of creating employment opportunities to absorb the youth bulge: about two-thirds of the Region’s population is under the age of 24 and is underemployed—including those with college and university degrees. Most workers are trapped in very low productivity activities in subsistence agriculture and the informal sector. Sub-Saharan Africa will have to generate large employment opportunities annually in order to accommodate the high rate of population growth.

**Figure 3: Population by age groups and sex** (absolute numbers)

> 13 Source: World Development Indicators.
data. Hence, the time-varying determinants of domestic and foreign firms’ exports _Z_ must also be considered.

The conditioning set _Z_ is composed of three categories of variables. First, following the gravity literature, the demand-side determinants of new export linkages are controlled for by the destination country’s import value, defined at the four-digit product level taken from the BACI world trade dataset<sup>5</sup> and the GDP per capita of the importing country.<sup>6</sup> Second, supplyside determinants are taken into account by introducing proxies for provincial and Chinese comparative advantages and export intensity. In the absence of firm-level data, these controls are crucial to account for the time-varying ability of different provinces to export different products to different countries. Hence, the log of the province total export sales, the provinceproduct export sales, and the China-product export sales in year _t_ are introduced. Because the regression also includes year fixed effects, which account for the evolution of total Chinese exports, controlling for these variables amounts to introducing the elements of a Balassa index of “revealed comparative advantage” at the province-product level. The total bilateral exports from province _i_ to country _j_ and the total Chinese bilateral exports to country _j_ are also introduced to control for specific relationships between the province/China and the destination country. This step is important given the use of business and trade agreements by the Chinese authorities to manage their diplomacy. Finally, the province GDP per capita is used to take into account the supply-side determinants of exports such as workers’ skills.<sup>7</sup> Third, to ensure that the decision of domestic firms to start exporting does not capture the intrinsic dynamics of exports at the product level or at the country level, the lag values of Chinese and province _i_ ’s exports at the product level and at the destination country level are included, as well as the

> 5This dataset, which is constructed using COMTRADE original data, provides bilateral trade flows at the six-digit product level (Gaulier and Zignago 2010). BACI is downloadable from http://www.cepii.fr/anglaisgraph/bdd/baci.htm.

> 6The world countries’ GDP per capita are taken from the World Development Indicators database (World Bank).

> 7The provincial GDP per capita are taken from the China Statistical yearbooks.

10
a policy matters even if no individual's utility is affected) are also found in the current maingtream approaches, albeit at the periphery.

Another difference between HPA and some other vLews is evident Ln the importance Dreze and Sen attach to human resource development through the public provision of social services, There is an emerging consensus in recent literature that human resource development, through improved nutrition, health, and basic education, must be given a higher priority than in the past; see, for example, World Bank (1989, 1990), and UNDP (1990). There 4q less sign of consensus on two further questions, both of which reist be resolved if we are to act successfully in this itr.tant area -f social polic: i) What weight should be attached to investme.at in human resources versus current consumption, and other forms of investment? While one may agree that human resource development hai been neglected, the optimal level of investment is unclear.

ii) What is the relative importance of private versus public provision as instruments for achieving human resource development? Many of the inputs to developing and maintaining human resources arc essentially private goods (in that the benefits are exclusive to the individual consumer), and so there is a possibility for efficient provision through markets. Human resource development will then require that people want and can afford these goods. The case for direct public provision then depends on the adequacy of policy instruments influencing incomes and their distribution, or on the existence of relevant market failures. (For example, some :jredients of basic health care do have the properties of public goods, leading to under-provision by m.vkets. There may also be economies of scale in public provision.) 8
Finally, we should point out that our decomposition of performance in terms of style and flows does not rule out informational advantages across investors. For instance, unsophisticated individual investors seeking exposure to global markets might optimally self-select into index funds. In fact, the positive relation between flows across passive funds suggests that investors of these funds might be less informed, and perhaps more likely to purchase or redeem shares in their index funds at the same time. On the other hand, active foreign investors in our sample generate yearly returns that are 3.66 to 4.28 percentage points greater than active funds managed domestically. These results are consistent with an advantage for this group, perhaps because they are more skilled or have access to valuable information form their presence in several markets (Albuquerque et al., 2009).

The rest of the paper is organized as follows. In section 2 we provide some background on the Colombian institutional setting and describe the data. In section 3 we document the general trading patterns across different investor types and styles. We study the relation between distance, style, and performance in Section 4 and analyze the role of flows on performance in Section 5. We conclude in Section 6.

# **2 Background and Data**

## **2.1 The Colombian Stock Exchange (CSE)**

Our data span the time between January 2, 2006, and January 29, 2016. During this period, the CSE implemented several changes in order to meet international standards. Before February, 2009, the market operated as a continuous trading system from 8:00 to 13:00 (local time) on weekdays where participants were only allowed to place limit orders. After February 9, 2009, a new trading platform was launched, allowing market and stop orders. In addition, a batch auction was introduced during the last five minutes of each trading day. During this interval, trades are collected and the system estimates an adjudication price at the maximum volume allocated among the tenders, with the auction closing randomly in +/- 60 seconds around the daily closing time. The auction price is also the daily closing price for each stock. Starting January 3, 2011, the trading session was extended to run from 8:30 to 15:00 with other rules remaining the same. Finally, on February 6, 2012, the market synchronized its daily trading session with the New York Stock Exchange, from 9:30 NYT 5