rafmacalaba/datause-encoder-data huggingface dataset:
Table **/Results** of the 1919 U.S. Tariff Commission survey to detect dumping and unfair foreign competition

|Item|Number of responses|
|---|---|
|Enterprises surveyed directly|562|
|Responses received|281|
|Reported foreign practices||
|No unfair foreign competition or dumping|135|
|Foreign competition|146|
|Dumping|23|
|Severe competition|97|
|Threats|1|
|Trademark violations|_5_|
|Patent violations|1|
|Counterfeiting of articles|7|
|Deceptive labeling|4|
|Undervaluation to avoid customs duties|8|

Source: U.S. Tariff Commission (1919, 12, 13).

- 43 -
<!-- Start of picture text --> 90<br>8070 <A<br>60 A<br>50 oS<br>40 +4<br>30 ee<br>2010 <A .<br>) STRI_Q4<br>Qp1 gps Q<br>pio 4s STRI_Q3<br>QP25 q ps0 QP75 g<br>p90 0 pos STRI_Q2<br>Q_p99<br><!-- End of picture text -->
Helmy, Imane, Hebatallah Ghoneim and Khalid Siddig (2019). Implementing Cash Transfer Programmes in Egypt Differently: An Economic Impact Analysis. International Conference on Economic Modeling and Data Science (EcoMod2019), Portugal held on July10-12, 2019.

<u>https://www.researchgate.net/publication/334710756_Implementing_Cash_Transfer_Pro grammes_in_Egypt_Differently_An_Economic_Impact_Analysis</u> (Downloaded on October 8, 2022).

International Energy Agency (IEA). (2022). Fossil fuel subsidy database. <u>https://www.iea.org/reports/fossil-fuels-consumption-subsidies-2022.</u> Jiang, Z., X. Ouyang and G. Huang (2015). The distributional impacts of removing energy subsidies in China. China Economic Review 33: 111–122.

- Lofgren, H. (1994). Egypt's Experience from CGE Modeling: A Critical Review. Working Paper. Economic Research Forum for Arab Countries, Iran and Turkey. <u>https://www.researchgate.net/publication/254411235_Egypt%27s_Experience_from_CG E_Modeling_A_Critical_Review</u> (Downloaded on 30 Sept. 2022).

- Mosa, A. A. (2019). Non-agricultural activities and household time use in Ethiopia: a computable general equilibrium model analysis.

- Nicholls, R.J., P.P. Wong, V.R. Burkett, J.O. Codignotto, J.E. Hay, R.F. McLean, S. Ragoonaden and C.D. Woodroffe (2007): Coastal systems and low-lying areas. Climate Change 2007: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, M.L. Parry, O.F. Canziani, J.P. Palutikof, P.J. van der Linden and C.E. Hanson, Eds., Cambridge University Press, Cambridge, UK, 315-356.

Rausch, Sebastian, Gilbert E. Metcalf and John M. Reilly (2011). Distributional impacts of carbon pricing: A general equilibrium approach with micro-data for households. Energy Economics 33 (Supplement 1): S20-S33.

- Serag, Eman, Fatma Ibrahim, Zainab El Araby, Mona Abd El Latif, Mahmoud El Sarawy, Dalia El Zaabalawy, Saad Allah El Dib, Kotb Salem, Clemens Breisinger and Mariam Raouf (2022). A 2019 Nexus Social Accounting Matrix for Egypt. Working Paper, International Food Policy Research Institute (IFPRI). https://doi.org/10.2499/p15738coll2.134544.
The BVC proprietary data consist of all the transactions in Colombian stocks during the 2006-2017 period. The data contain detailed execution information, including a time stamp (to the second), price, direction, quantity, and the broker routing the trade.<sup>9</sup> Each transaction record has a unique investor identification number. In addition, the BVC classifies investors into three broad groups – domestic individuals, domestic institutions, and foreign investors.<sup>10</sup> The stock exchange further classifies domestic institutions into mutual funds, pension funds, non-financial corporations, brokers trading on their own accounts, and other institutions.

To obtain a more detailed classification of foreign investors we proceed as follows. For the exclusive purpose of this project, the BVC discloses the name of foreign institutions involved in the transactions. We search manually on the web and cross-reference the names with Factset Ownership – a database with extensive global coverage on institutional investors – and classify each foreign investor into one of the following groups: Active mutual funds, passive mutual funds, pension funds, exchange-traded funds (ETFs), hedge funds, government institutions (e.g., sovereign wealth funds and central banks), and investment firms. Other investors include foreign individuals, trust funds, and private endowments.

The BVC database has about 17 million records during our 12-year period. Domestic institutions represent over half of the traded value in domestic stocks. Consistent with international trends in cross-border portfolio investments (IMF, 2017), the presence of foreign investors in Colombia increases over time. The number of foreign investors rose from 324 in 2006 to almost 4000 at the end of 2017 and the share of total traded value by this group increased from 4.5% to 31.8%. In addition to the generalized growth of foreign flows to emerging markets after the 2008 global financial crisis, there are two key related events in Colombia in the period that contribute to explain the surge of foreign investors: (i) Colombian sovereign debt recovered its investment grade in June 2011, and (ii) in 2013, taxes on foreign investors’ earnings from domestic securities were reduced from 33% to 14%. Between 2012 and 2017, foreign mutual funds accounted for 7.8% of the total traded value, with investment banks, ETFs, and government funds representing each 5.2%, 3.5%, and 2.8% respectively (Table OA2, Panel A).

According to the annual statistics of the World Federation of Exchanges (WFE, 2019), at the end of 2017, Colombia had the fourth largest stock market in Latin

> 9Since February 2012, the market hours are synchronized with the New York Stock Exchange trading session, with a closing batch auction during the last five minutes of each trading day.

10In Colombia, there are no individual or aggregate ownership limits on foreign investors. Foreign individuals and institutions are allowed to either reinvest or transfer earnings such as dividends or capital gains with little restrictions.

6
local precipitation. Therefore, we use our river flow proxy dummies to isolate water-rich and water-poor years in a region. Additionally, we identify high and low river flow events in upstream areas and calculate dummy variables, _RFHU_ and _RFLU_ , respectively. As shown in the first column in table 6, regressing NPP measure on these as well as all other climatic variables shows that the upstream variables have no direct effect on local cropland productivity, whereas the local low river flow continues to have a negative effect.

To investigate how river flow may determine the impact of dams, we include our instrumented local and upstream dam variables and their interaction terms with the river flow dummies, initially for large dams only. As shown in the second column, although the average positive effect of large local and upstream dams is maintained, their overall impact is dependent, in part, on the available river flow. In particular, we find that low river flow reduces the overall impact of large dams by nearly one-third. In contrast, the upstream large dam effect is enhanced by larger river flow upstream.

One might expect that, given their much lower storage capacity, the benefits from small dams would be less dependent on local river flow. This assumption is confirmed in the third column, where we include the instrumented number of smaller dams, its interaction term with large local dams, and their interaction terms with local river flow anomaly events. Accordingly, the results for large dams as well as their dependence on local and upstream river flow hold as before. In contrast, the impact of small dams on their own does not depend on local annual mean river flow. Moreover, the additional benefits are not dependent on river flow.

38
decade there were 40% more mobile than fixed lines in La Paz and El Alto: a total of nearly 218,000 mobile subscribers versus 155,000 fixed line subscribers.

The introduction of pre-payment cards for cellular telephone in 1998 appears to have been a great stimulus to demand; indeed 86% of the increase in cellular penetration since 1997 took the form of prepaid telephones (Figure 3.4). Anecdotal evidence suggests that a significant proportion of these new clients are small entrepreneurs from the informal sector, although unfortunately there is no data to confirm this view<sup>4</sup> . By using prepaid telephones, these micro-entrepreneurs keep the running costs of the telephone to an absolute minimum but are still able to benefit from business-related in-coming calls.

**Figure 3.4: Growth of mobile telephony**

<!-- Start of picture text --> 250000<br>200000<br>150000<br>Prepayment<br>Subscribers<br>100000<br>50000<br>0<br>1996 1997 1998 1999<br>Sources : TELECEL and ENTEL (2000).<br>No. of mobile subscribers<br><!-- End of picture text --> Both ENTEL and COTEL are licensed to provide public telephone service in La Paz and El Alto, although ENTEL telephone booths only provide long distance service. The number of public telephones in La Paz and El Alto increased by a factor of 10 over the same period (Figure 3.5). About three quarters of these telephones are operated by ENTEL. COTEL has only installed the minimum number of telephones required to meet its contractual obligation of one public telephone per 200 private lines.

**Figure 3.5: Growth of public telephones**

<!-- Start of picture text --> 3000<br>2500<br>2000<br>COTEL<br>1500<br>ENTEL<br>1000<br>500<br>0<br>1996 1997 1998 1999 2000<br>No. of public telephones<br><!-- End of picture text --> 4 Interview with Bernardo Tribeño, Gerente Económico, TELECEL, 13th September 2000.

13
16 Bank of International Settlements. Its use is motivated by the fundamental instrumental variables idea of finding variables that are related with the lobbying variable ln(Lobbying) but not the error term in the baseline regression. Foreign lobbying is partly designed to attract US institutions and individuals to use the services of Caribbean financial institutions that are less stringently regulated than their developed country counterparts. Since such lobbying spending is likely to be correlated with the size of external assets, the external asset position is correlated with ln(Lobbying). However, foreign lobbying directed at increasing participation by US institutions and individuals in their financial sectors, for example offshore banking, is unrelated with the error term in the tourism regressions since shocks to the number of tourist arrivals (for example, due to inclement weather during a particular season) have little impact on financial sector participation. Further, there is no evidence in the literature of any significant participation of tourists in the Caribbean financial sector. To reduce any remaining doubt about its exogeneity, the one period lagged value of the external asset positions is used to instrument ln(Lobbying).

Foreign countries lobby in the US for several reasons, and there is no reason to expect lobbying for non-tourism related reasons to be correlated with the unexplained component of tourism arrivals in (1).<sup>12</sup> Thus, the second instrument we use is the log of FARA lobbying spending in sectors other than tourism (or media and advertisement), ln(Other Lobbying). The last instrument is the log of FARA lobbying spending in the media and advertising sectors, ln(Media&Advertising Lobbying). Both instruments are lagged one period to maximize its correlation with ln(Lobbying).

The validity of the three instruments depends on shocks to the value of a country’s fixed tourism resources being uncorrelated with shocks to other sectors of the economy _conditional_ on the exogenous variables. Consider an impending devaluation which dries up capital flows to the Caribbean, reducing the value of hotels by halting improvements or expansions. Since this macro shock is very likely to impact income, much of its impact should be conditioned out due to the per capita GDP variable. The most likely source of variation in changes in external asset position are source country-specific institutional changes -- laws about offshore financing in advanced countries, their differential tax rates – which are largely exogenous.

> 12 We are grateful to an anonymous referee for suggesting the use of this instrument.
# **References Cited**

Bartlett, C. and S. Ghoshal, 1990. Managing Innovation in the Transnational Corporation. In C. Bartlett, Y. Doz, and G. Hedlund, Eds., _Managing the Global Firm_ . Routledge: London.

- Bessen, J. and E. Maskin, 2000.  Sequential Innovation, Patents, and Imitation.  MIT Department of Economics Working Paper No. 00-01.

- Branstetter, L., 2000.  Is Foreign Direct Investment a Channel of Knowledge Spillovers? Evidence from Japan’s FDI in the United States.  NBER working paper no. 8015.

- Brune, N., G. Garrett, A. Guisinger, and J. Sorens, 2001. The Political Economy of Capital Account Liberalization.  Working Paper, Yale University.

- Carr, D., J. Markusen, and K. Maskus, 2000.  Estimating the Knowledge Capital Model of the Multinational Enterprise. _American Economic Review_ 91:  693-708.

- Clark, K. and T. Fujimoto, 1991. _Product Development Performance:  Strategy, Management, and Organization in the World Auto Industries_ .  Harvard Business School Press, Boston, MA.

- Cockburn, I. and J. Lanjouw, 2001.  New Pills for Poor People?  Empirical Evidence After GATT, _World Development_ 29:  265-89.

- Desai, M., C. Foley, and J. Hines Jr., 2004.  The Costs of Shared Ownership: Evidence from International Joint Ventures. _Journal of Financial Economics_ , forthcoming.

- Eaton, J. and S. Kortum, 1996.  Trade in Ideas:  Patenting and Productivity in the OECD. _Journal of International Economics_ 40: 251-278.

- Fors, G., 1997.  Utilization of R&D Results in the Home and Foreign Plants of Multinationals. _Journal of Industrial Economics_ 45: 341-358.

- Glass, A. and K. Saggi, 2002.  Intellectual Property Rights and Foreign Direct Investment. _Journal of International Economics_ 56:  387-410.

- Goto, A., 2003.  Kyoshinka no Process toshite no Nihon no Tokkyo Seido to Gijutsu Kakushin (The Co-evolution of Japan's Patent System and Technological Progress).  In A. Goto and S. Nagaoka, eds., _The Intellectual Property System and Innovation_ (in Japanese). University of Tokyo Press: Tokyo.

- Green, J. and S. Scotchmer, 1995.  On the Division of Profit in Sequential Innovation. _The Rand Journal of Economics_ 26:  20-33.

39
9 Thailand, and a spectacular 82% decline (from 0.643 in 1975 to 0.114 in 1995), in Indonesia, both achieved over shorter periods of time.<sup>17</sup>

**Table 2. Brazil 1981-2004: Three Poverty Measures for two Poverty Lines**

|**Year**|**Regi**|**onal Poverty Li**|**ne**<sup>**1**</sup>|**Admi**|**nistrative Poverty**|**Line**<sup>**2**</sup>|
|---|---|---|---|---|---|---|
||Headcount|Poverty Gap|FGT(2)|Headcount|Poverty Gap|FGT(2)|
|1981|0.399|0.163|0.090|0.296|0.124|0.070|
|1982|0.392|0.160|0.088|0.293|0.123|0.070|
|1983|0.512|0.229|0.133|0.383|0.170|0.099|
|1984|0.503|0.222|0.127|0.379|0.163|0.093|
|1985|0.435|0.183|0.102|0.317|0.133|0.075|
|1986|0.266|0.096|0.049|0.185|0.069|0.036|
|1987|0.405|0.171|0.097|0.297|0.127|0.073|
|1988|0.455|0.202|0.119|0.338|0.152|0.091|
|1989|0.437|0.194|0.114|0.315|0.142|0.084|
|1990|0.445|0.196|0.115|0.328|0.147|0.088|
|1992|0.456|0.209|0.128|0.325|0.150|0.093|
|1993|0.466|0.215|0.130|0.326|0.151|0.093|
|1995|0.380|0.164|0.095|0.277|0.117|0.070|
|1996|0.378|0.167|0.101|0.273|0.122|0.075|
|1997|0.370|0.162|0.096|0.273|0.116|0.071|
|1998|0.363|0.156|0.091|0.251|0.110|0.066|
|1999|0.375|0.161|0.094|0.256|0.112|0.067|
|2001|0.375|0.166|0.100|0.258|0.113|0.069|
|2002|0.365|0.156|0.090|0.245|0.102|0.060|
|2003|0.373|0.163|0.097|0.249|0.106|0.064|
|2004|0.345|0.145|0.083|0.222|0.093|0.054|

Notes: 1 - Rocha (1993) regional poverty lines. See Appendix 2 for details. 2 - The "administrative poverty line" is set as R$100 per person per month, in September 2004 values. Source: Authors' calculations from the PNADs.

Behind the overall decline, poverty dynamics in Brazil over the last two decades have been marked by considerable volatility, which largely reflected macroeconomic instability. Unsurprisingly, therefore, the volatility was more pronounced in the unstable decade of the 1980s, with a sharp increase during the 1981-83 recession, and a substantial decline during the recovery that took place between 1984 and 1986. All three measures are at their minimum in

> 16  See Foster, Greer and Thorbecke (1984).

> 17 The Thai (Indonesian) poverty incidence is calculated with respect to a poverty line of US$ 2-a-day  (US$ 1-aday), both in 1985 prices and using PPP exchange rates. See Ahuja et. al. (1997, pp. 7 and 33).
payments crisis.

As an alternative empirical specification of borrowers' characteristics, we implemented a procedure similar to Ozler<sup>and Tabellini</sup> (1990). For this specification the contract level data<sup>are aggregeted to</sup> annual level (annual weighted average of spreads are calculated<sup>where the</sup> weights are the amounts of Ican contracted for each contract<sup>**within**that</sup> year). Reserves to gdp, and ratio of exports **.o**<sup>**major creditors as a share**</sup> of total exports are incorporated to measure the<sup>**vulnera.ility of a**country</sup> to non-payment penalties. Agriculture **as a** share<sup>**of gdp is used as an**</sup> indicator of economic instability that affects **a borrowers capacity to** pay. Real gdp per capita, total debt to gnp, and presence of IMF<sup>stanby</sup> agreements are also incorporated.

# 2.2.b. Political Determinants of Spreads

An important addition to the set of economic<sup>variables discussed is the</sup> introduction borrowers' political characteristics. The<sup>theoretical model</sup> considered by Ozler and Tabellini (1990) isolates<sup>the discount factor</sup><sup>**as**an</sup> important parameter in a country's level of external borrowing.<sup>Previous</sup> work by Alesina and Tabellini (1989), and Cukierman,<sup>Edwards and Tabellini</sup> (1989) showed that the size of the discount factor<sup>for</sup><sup>**a**country</sup><sup>**reflects**an</sup> important feature of the political system: namely, the degree<sup>of political</sup> instability, defined as the probability of<sup>imminent goverment change.</sup> Accordingly, it is important to incorporate such<sup>political</sup><sup>**factors as**</sup> potential determinants of the spreads so as to ensure<sup>that the results in</sup> this investigation are robust to this c-Lsideration.

The measure of political instability employed<sup>here, which is an annual</sup> estimate of probability of government change,<sup>is the same asinOzler and</sup> Tabellini (1990), and similar to that of Cukierman,<sup>Edwards and Tabellini</sup>
are affected by the alternative trade exposure measures. We first estimate a specification in which, in addition to tariffs, we include industry measures of lagged import penetration and lagged export to output ratio.20 The results presented in column 2 suggest that high export to output ratio is associated with higher industry wages. This result is intuitive since higher industry exports likely increase the demand for workers in that particular industry. However, we find no statistically significant effect of lagged import penetration on wage premiums. In column 3 we add the interaction of tariffs with import penetration to the specification in column 2. The insignificant interaction coefficient suggests that import penetration does not impact wage premiums differentially in industries with lower tariffs. Finally, exchange rate fluctuation might also affect wages. Although year effects capture the exchange rate fluctuation over time, one would expect that the effect of exchange rates might vary depending on trade exposure of the sector. We thus interact the exchange rate with lagged trade flows. As our results in column 4 indicate, however, the inclusion of exchange rates does not affect any of our previous findings.

Overall, there is little evidence that Brazilian trade liberalization affected the industry wage structure and thus wage inequality between skilled and unskilled workers via this channel. This finding is consistent with the evidence from Mexico by Feliciano (2001), who finds no relationship between industry wages and tariffs, but is inconsistent with the evidence from Colombia by Goldberg and Pavcnik (2001), who find that tariff reductions are associated with declines in industry wages.

# **4.3 Industry Wage Premiums for Skilled Workers**

> 20 Because trade flows are likely endogenous (they depend on factor costs), we include the first lags of import and export measures in the estimation rather than their current values. Of course, to the extent that these variables are serially correlated, this approach might yield biased results, especially in industry fixed effects specifications with relatively small number of observations. Nevertheless, the inclusion of these lagged variables does not change our conclusions about the relationship between tariffs and industry wages.

23
# **1. Introduction**

Forced displacement causes abrupt changes in living conditions. Immediately after displacement, forcibly displaced people are often in a highly vulnerable situation due to the loss of assets, the disruption of family structures, the loss of support networks, and their limited access to labor markets and services. These changes occur within existing structures of gender inequality, and while men, women and children are all likely to be adversely affected, these changes may have different consequences for women and girls. However, we might also expect that the impacts of displacement may be mitigated over time as displaced people establish new homes and networks, find work, and integrate into their new communities. Empirical research on income poverty rates among displaced populations is growing, yet the impact of gender inequality on poverty among displaced populations is rarely discussed, nor is much known about the dynamics of poverty in situations of displacement, largely because of lack of data. This study seeks to fill this gap.

Understanding the impact of gender inequality on poverty rates among displaced populations is important as displacement changes social structures and access to opportunities in ways that differ for women and men. For example, during displacement, household composition changes due to separation, conflict-related mortality, or widowhood. This shock often results in the formation of new female-headed households. Evidence for Sub-Saharan Africa shows that female-headed households that have previously been highly dependent on male income – notably widow-headed households – are particularly prone to poverty, although other types of female-headed households may not be more likely to be poor than male-headed households (Brown & Van der Walle, 2020). For this reason, while it is important to analyze differences in poverty risk between households with female and male heads, it is also important to understand how different routes to female headship, and the changes in the household composition more broadly, impact poverty risks and expenditure levels.

This paper explores level and distributional changes in expenditure among Syrian refugee households in Jordan between 2013 and 2018 using a gender lens. By the end of 2018, UNHCR had registered more than 671,000 Syrians<sup>1</sup> who had fled their homes and settled in Jordan. At the end of the time period covered by this research, UNHCR’s 2019 Vulnerability Assessment Framework (VAF)

> 1 UNHCR’s data portal records 671,551 registered Syrian refugees residing in Jordan on January 13, 2019. See UNHCR (2022b) available at https://data.unhcr.org/en/situations/syria/location/36.

2
# **Elastic net Index: CPI in Costa Rica**

<!-- Start of picture text --> 2.5<br>cpi<br>ElasticNet GT Index<br>2.0<br>1.5<br>1.0<br>0.5<br>0.0<br>0.5<br>1.0<br>2006 2007 2008 2009 2010 2011 2012 2013<br><!-- End of picture text --> Figure 9: Elastic net model index created for CPI series from Costa Rica. Somewhere in between high variance OLS and low variance lasso.

23