rafmacalaba/datause-encoder-data huggingface dataset:
The Ghana questionnaire asks about the assets of up to three enterprises. The assumption is that the assets were purchased, since it asks when each was obtained and the purchase price. It would be useful to check if this approach is appropriate by asking how the items were acquired and allowing for the option of inheritance, gift or transfers. The value questions are appropriate, since the questionnaire asks how much each asset could be sold for today.

_Beyond the minimal questions_ . Since it is not necessarily the case that the owner of the business also owns all of the individual assets that are part of the business, the next step would be to ask about the individual ownership of the individual business assets. This could be done by simply adding a column next to the questions about the value of the business assets.

In addition, we recommend adding questions about the acquisition of the business and the business assets. Asking how the owner acquired the business would allow policy makers to understand the patterns of business formation at the individual level, so that gender is taken into account. For detailed asset analyses, it would be useful to ask how the key business assets were acquired. In particular, it would be useful to know whether there are gender differences in the purchase or inheritance of business assets.

Questions on decision-making within the business are also not typically included in the LSMS surveys. Questions on who makes the decisions about the business and who provides the labor would allow for separation of ownership and control in analyzing the impacts of the businesses.

5.5. Other Physical Assets _Minimal questions_ . Other physical assets include both consumer durables and agricultural equipment. These are typically covered in separate sections of the LSMS surveys. The minimum that should be asked of major physical assets is the owner and their value. Many of the LSMS surveys ask about the value in some way, but none ask about individual or joint ownership of physical assets.

In the Guatemala questionnaire, questions about the ownership of important physical assets, including kitchen articles, personal articles and those for amusement, other household articles, and vehicles, are asked at the household level. (The questionnaire does not specify, however, who should respond to these questions, but it seems designed to be answered by only one person.) The survey asks how many the household has of the particular type of item, how old it is, whether it was acquired new, and the value of the item (the most recent item if there are multiple ones) if it were sold today. We recommend simply adding a question to identify the owner of each asset, which would be sufficient to allow calculation of individual asset ownership in this section.

Questions about agricultural equipment are included in the agricultural section of the Guatemala survey. These questions are asked at the household level: whether the household owns various pieces of agricultural equipment, how many are owned, how 36
Table A.11: Robustness checks, introducing illegality in the return migration equation. Estimating the effect of migrants’ legal status on hourly wages after return, unconditional on return migration

||(1)<br>Migrate|(2)<br>Illegal|(3)<br>Return|(4)<br>Log of<br>hourly wage|
|---|---|---|---|---|
|Age|0.012***|-0.076**|-0.015**|-0.001|
||(0.001)|(0.034)|(0.007)|(0.005)|
|Age squared|-0.000***|0.001**|0.000***|0.000**|
||(0.000)|(0.000)|(0.000)|(0.000)|
|No education|0.019***|0.483***|-0.025|-0.445***|
||(0.004)|(0.117)|(0.025)|(0.026)|
|Primary or preparatory|0.032***|0.473***|0.061**|-0.419***|
||(0.004)|(0.125)|(0.026)|(0.025)|
|Secondary|0.017***|0.355***|0.037*|-0.285***|
||(0.003)|(0.101)|(0.021)|(0.020)|
|Rural|0.009***|0.250***|0.011|-0.028*|
||(0.003)|(0.083)|(0.017)|(0.016)|
|Oil prices|0.013***<br>(0.000)||||
|Diplomatic exchange||-0.178*<br>(0.101)|||
|Confict|||0.047***<br>(0.014)||
|Illegal status|||-0.066<br>(0.096)|-0.220***<br>(0.053)|
|Legal status||||0.196***<br>(0.045)|
|Observations|14,879|1,955|2,071|8,054|
|Parental controls|Yes|Yes|Yes|Yes|
|Decades of migration dummies|Yes|Yes|Yes|No|
|Labor market controls in Egypt|No|No|No|Yes|
|Predicted log wage: Non-mig.=1|.515; Illegal mig.|=1.341; Legal|mig.=1.786||

Robust standard errors in parentheses. *** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1 _Notes_ : Equation 1 is the probability of temporary migration. Equation 2 is the probability of undocumented migration. Equation 3 is the probability of return migration. Equation 4 models the logarithm of hourly wages upon return. The model additionally controls for illegality in the return migration equation (3). For identification of equation (1), we use the inflation adjusted historical oil prices (in US dollars). For identification of equation (2), we use diplomatic exchange between Egypt and the countries of destination of Egyptian migrants at time of migration. It is a dummy variable equal zero if there is no evidence of diplomatic exchange neither in Egypt, nor in the country of destination and is equal one if there is evidence of diplomatic exchange either in Egypt or in the country of destination at the level of charg ́e d’affaires, minister, ambassador or other. For identification of equation (3), we use the number of active armed conflicts that is both country and year specific from the Uppsala Conflict Data Project (UCDP). Equation (4) estimates the effect of illegality of the logarithm on hourly wages, unconditional on return migration. The predicted logarithm of hourly wages for non-migrants, illegal migrants and legal migrants are reported in the last row.

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<!-- Start of picture text --> Box 5: The UK Pool<br>Expected demand<br>Price<br>Poolprice<br>QantSEIT<br>5SET7<br>T~~~~~~~~~~~~<br>|GBET 3<br>GENSET<br>I<br>Quantity,<br><!-- End of picture text -->

The price in the Pool in England and Wales is determined on the day ahead of operation. The price is determined by ranking the bids (the price at which it will generate and the quantity it can generate at that price) of each generating turbine (genset) in the system. The price is determined by taking the highest price bid needed to meet expected demand in every half-hour period in the day ahead as shown in the diagram above. The Pool price is therefore determined for every half-hour period on a given day. A sample of prices taken from Financial Times is shown below.

Note that this is a very simplified explanation of the mechanism. In practice, there are other elements to the price and the bids are complex non-linear functions.

<!-- Start of picture text --> UK Pool Prices 01/23/96<br>200 l<br>180.<br>140<br>' 12O0<br>100<br>a 80-<br>o 60.<br>0L<br>0 40-<br>20_<br>1.2-Hour Period Ending<br>Source Fnergy Settlements and Informnation Services Limited, 01/23/96<br><!-- End of picture text --> It might be argued that one could define and enforce capacity rights in systems with directed flow like natural gas transmission. However, trades may still be too complex to obtain efficient gas transmission on the basis of trade in capacity rights. In effect, the notion of trade in capacity rights entails that a complete path for the transport of gas from seller to buyer be obtained through purchase of a series of capacity rights, which are available at the time they are needed. Constructing such a system of "straws" through a pipeline system that efficiently matches capacity rights with energy delivery may be so complex that efficient solutions may not obtain. The experience of the deregulated U.S. gas industry is suggestive in that there are efficient spot markets for interruptible gas supply, i.e. supply flowing in times when pipeline capacity does not impose an
38 countries can be identified by criterion (i). Criterion (ii) reduces the coverage to 24 countries, and entails dropping primarily countries in Africa and Latin America. In addition, data are available for only part of the time period chosen for any one country.

The Appendices contain a detailed description of the data sources. The general strategy was to rely to the maximum extent possible on the same statistical sources, including the World Bank _Debtor Reporting System_ (DRS) and the IMF _Government Financial Statistics._ The same approach is used to measure foreign and domestic interest costs-namely, the calculation of an effective interest rate. For the foreign interest rate, total annual dollar interest payments (INTP$) plus the change in interest arrears as reported to the DRS by the debtor (INTA$) are taken as a percentage of average annual dollar DOD. Arrears are included because we assume that countries face given world rates of interest, thus including arrears allows us to obtain an estimate of the "normal" cost of borrowing.<sup>2 2</sup> The DRS includes in interest payments any front-end or other fees where these are known: there were no rescheduled interest payments on commercial debt in the years and countries included in our sample. Thus the nominal effective dollar interest rate _(EFFINT$) is:_

# _EFFINT$(t)_ = _[INTP$(t) + INTA$(t)] [(DOD$(t -_ 1) _+ DOD$(t))/2]_

where _DOD$(t)_ indicates dollar debt outstanding and disbursed at the end of year t, and the average debt outstanding and disbursed during the year t is estimated through linear interpolation.<sup>2 3</sup> LIBORbased borrowing of the central government only is used to determine the foreign cost except for Algeria, Greece and India, where LIBOR-based borrowing of public corporations is used as a proxy.

For the domestic interest rate, annual local-currency interest payments on central government domestic debt _(INTP)_ are taken

> **2 2 To the extent that actual arrears are greater than reported arrears, the normal cost of foreign borrowing-and hence the government revenue reported below-will be understated.**

> **231t is possible to perform a rough check of the accuracy of our method by comparing the effective interest rate we obtain with LIBOR. This comparison indicates that our estimates covary closely with LIBOR. Discrepancies are likely to arise because our estimates, correctly, include any comnmercial fees as part of the cost of the loan, and other reasons discussed elsewhere in this section.**

11
17 on implementing adjustments to the basic average years of schooling to account for the above-mentioned deficiencies to obtain a better proxy for the human capital stock.

# **Accounting for Rates of Return to Education**

To transform a measure of the average years of schooling into a human capital stock variable, we follow the specification used by Woessmann (2000): where

- _h_ is the average per worker human capital stock

- _r_ is the Mincerian rate of return to an additional year of schooling

- _s_ is the number of years of schooling.

Mincer (1974) proposed a method to estimate the market rates of return to education and this method is currently known as the “basic” earnings function method. This method involves fitting a semi-log ordinary least squares regression with the natural logarithm of earnings as the dependent variable, and the years of schooling and years of labor market experience and the square of years of labor market experience as independent variables. In this semi-log earnings function specification the coefficient on years of schooling can be interpreted as the average private rate of return to one additional year of education<sup>26</sup> .

Country specific data on Mincerian rates of return to schooling were obtained from Psacharopoulos (1994) and Bils and Klenow (2000). The former provides estimates on the returns to schooling for 62 countries for different years, while the latter has estimates for 52 countries for different years. In order to have the widest global coverage, we incorporate both data sets, which results in estimates for 64 countries for different years<sup>27</sup> .

Given that there are more than 200 countries in the world, having Mincerian rates of return for just 64 countries would drastically reduce the potential number of

> 26 Note that the Mincerian rate of return does not take into account the educational level at which this additional year of schooling take place.  Due to current data constraints, we were not able to incorporate educational rates of return that varied by educational level into our human capital stock computations.  We will take up this challenge in the near future.

> 27 By “different years”, we mean that the year of the observation depends on the specific country.  For example, the estimate for Argentina was only available for 1989 while that of Sweden is available only 1981.
one’s ability to see the world from other points of view and to increase perspective taking (Stewart et al., 2003).<sup>4</sup> On the other hand, the video exposes participants to personal narratives that can emotionally “transport” the audience to a fictional world and spur changes in their beliefs (Green and Brock, 2000).

Immediately after the interventions, we applied a survey instrument that elicited attitudes and beliefs about migrants and assessed two prosocial behaviors: altruism and self-reported trust towards Venezuelans. We measured altruism through participants’ donation behavior in a dictator game. We told participants they would be given an amount of money and then we asked how they would allocate it among themselves, an organization that helps Venezuelan migrants, and a well-known Colombian nonprofit group that builds houses for vulnerable populations. A control group did not receive any treatment and only took part in the survey.

The participants in our intervention recently experienced a drastic change in the demographic composition of their communities due to a massive influx of Venezuelan forced migrants. In just six years, more than five million people have fled the humanitarian crisis in Venezuela and relocated in other countries, making Venezuelans the second-largest internationally displaced population after Syrians. Colombia is the main destination country for this contingent, hosting 2.89 million Venezuelans, and Bogot ́a is the main recipient city, accounting for almost 20 percent of Colombia’s Venezuelan population. Attitudes towards Venezuelans have deteriorated markedly in Colombia, as reported in the media and evidenced by the decline in Gallup’s Migrant Acceptance Index, which in Colombia had the third-largest drop in the world between 2016 and 2019.<sup>5</sup>

> 4In order to ameliorate demand effects, we (unlike many studies in social psychology) do not provide explicit instructions to intervention participants when they perform the activities.

> 5Gallup compared 140 countries between 2016 and 2019 (see footnote 1); the three largest declines in migrant acceptance took place in the main destination countries of the Venezuelan exodus (Per ́u, Ecuador, and Colombia). Surveys conducted locally also reveal increases in intolerance; see, e.g., the following report by _Semana_ magazine: https://s3.amazonaws.com/semanaruralvzla/documentos/ 1568067274_boletin7pdf.

4
Corrective Measures<sup>Matrix</sup>

||IMPORT<br>Pibl Cti<sup>Measures</sup>|-RELATED<sup>BARRIERS</sup><br>Progress with Curment<sup>Measures</sup><br>|Recommended<sup>Actions at Regional Level</sup>|
|---|---|---|---|
|Barriers|osse orrecve <br> <br>|<br> <sup>ki are</sup><br>|IM - Step up work<sup>of Maghreb task forces.</sup>|
|Inport Duties|- Harmonization<sup>of customs procedures and</sup><br>-<br>standardization<sup>of technical specifications.</sup><br> <br>- Radical revision<sup>(reduction, simplification) of</sup><br> <br>nomenclature of<sup>merchandise.</sup><br>t<br>- Gradual reduction<sup>of customs tariffs (on</sup><br> <br>transport vehicles).<br> <br>- Possible exemption<sup>of TIR and CKDs</sup><br> <br>equipment.<br>(<br>- Complete computerization<sup>of customs</sup><br> <br>procedures (airports,<sup>ports, border posts).</sup><br> <br> <br>|Within the Maghreb,<sup>worng groups</sup><br> <br>drawing up a customs<sup>nomenclature for the</sup><br> <br>Maghreb based<sup>on the Harmonized System;</sup><br> <br>his will be a prelude<sup>to drafting a</sup><br> <br>Maghrebian external<sup>tariff.</sup><br> <br>- Significant reduction<sup>in customs duties and</sup><br> <br>consolidation within<sup>the GATT framework</sup><br> <br>Tunisia-Morocco).<br> <br>- Algeria: General<sup>reduction in customs</sup><br> <br>duties through adjustment<sup>of the 1992</sup><br> <br>Tariff. Maximum<sup>rate is 60%.</sup><br> <br> <br><sup>it 40-</sup><br>|<br>EM - Step up negotiations<sup>for creation of</sup><br>EU/Maghreb free<sup>trade area.</sup><br>IM, EM - Develop<sup>procedure for</sup><br>computerization<sup>and connection of ports,</sup><br>airports, and border<sup>posts.</sup><br>- Develop Maghrebian<sup>interconnected</sup><br>information network<br>- Consultations<sup>between Morocco and</sup><br>Tunisia regarding<sup>smooth conduct of</sup><br>present negotiations<sup>with EU for creation</sup><br>of free trade area.<br>IM -Conduct study<sup>on maritime transport</sup>|
|Freight<br>Conference<br>Agreements<br>______________|- Continuing gradual<sup>liberalization of restrictions</sup><br>on charters for<sup>shipment of cargoes not within</sup><br> <br>the geographic or<sup>size limits of regular line</sup><br>services.<br>- Facilitation of<sup>cabotage (elimination of</sup><br>economic and<sup>financial obstacles to development</sup><br>of these lines<sup>- allocation of foreign exchange,</sup><br>reduction of port<sup>taxes, and so on).</sup><br>Implementation<br>of the Maghreb<sup>Convention.</sup>|<sup>- Conversion of 50-50 agreements no</sup><br> <br>40-20 agreements.<br>|<br>cost structures<sup>with view to optimizing</sup><br>freight rates while<sup>preserving shipping-line</sup><br>profitability and<sup>quality of service.</sup><br>NM - Foster creation<sup>of an entity to defend</sup><br>shippers' interests<sup>nationally and</sup><br>regionally, with<sup>view to consultations</sup><br>between shipowners<sup>and shippers.</sup>|

IM = Intra-Maghreb EM = Europe/Maghreb
common legal origin. Also, the matrix includes the share of bilateral trade between countries and a measure of geographical distance between home and host countries, measured in miles. We also included a dummy for whether the home and host where in a colonial relationship or colonized by the same country. All these variables come from the Central Intelligence Agency (CIA) _World Factbook_ .<sup>18</sup>

# **IV.   RESULTS**

Table 5 reports the results for the probit estimation of equation 1.<sup>19</sup> We present six alternative specifications including different proxies for political and economic risk. All regressions are estimated with robust standard errors allowing for the possibility that observations for the same parent bank may not be independent (i.e., we allow for clustered standard errors within parent banks).

Most coefficients are significant and have the expected sign. Since results are robust across specifications, in what follows we focus on our baseline regression labeled model (4).

The results can be summarized as follows. First, regulations matter. The variables describing host- and home-country restrictions on foreign branches both have the expected negative sign and are significant in all specification (often at the 1 percent level), indicating that more restrictions on branches lower the probability that banks adopt this organizational form. Host-

> 18 The variables included in the first stage equation (or equation (2) above) of the Heckman model that are not included in the equation for the organization form (equation (1)) are the exclusion restrictions which allow identification of the Heckman probit model. We tried a number of variations on these, and results remained largely unchanged. Furthermore, in separate probit estimations, available upon request, we verified that those variables included in the selection equation did not affect the second stage equation (i.e., the type of organizational form). 19 Note the sample size, which captures the number of bank affiliates (both branches and subsidiaries) drops to 240 observations instead of 247 as shown in table 2, because of missing data for 5 Brazilian banks (all investment banks), one Mexican, and one Polish.

14
93 Planning Association (FPASL) spearheaded an industry-based program where costs were shared by the FPA, government, and industry--both management and unions. The International Labor Office, a U.N. organization, has a long standing program to address access to private sources of family planning. Their efforts have focused on lobbying for expanded employee benefit packages to include family planning, and has included country studies, conferences and seminars, and documentation1of successful experiences (ILO, 1979, 1985; ILO Regional Office for Asia and the Pacific, 1974; Murthy, 1983). Much of ILO's work has been undertaken in collaboration with or with funding from the U.N. Fund for Population Activities (UNFPA). Among nongovernmental organizations (NGOs), Pathfinder Fund, International Planned Parenthood Federation (IPPF), Family Planning International Assistance (FPIA) and the Population Council have initiated employee-based schemes in a fey countries. Virtually all projects subsidize contraceptives and most have covered the costs of establishing and training personnel.

Although not a major player in this area historically, USAID has recently launched two large family planning projects vhose mandates are to promote the private sector in family planning. The subprojects of USAID's Technical Information on Population for the Private Sector (TIPPS) begun in 1984 and the Enterprise Program begun in 1985 are a mixture of innovative and new approaches, as well as expansion of existing employee benefit models. Both of these programs will be described in more detail and some specific examples will be given to innovative projects that have been undertaken. Another USAID'project, OPTIONS, is attempting to address the legal and other policy-related impediments to greater private sector activity in family planning. Tovether, these programs constitute the most significant concerted efforts in the area of private sector and family planning, and have quickly dominated the field.

**al.tp:aully** Plaiuing **Paper** (Whole