rafmacalaba/datause-encoder-data huggingface dataset:
5 Our results also contribute to the vast literature documenting the strength – and rise – of comovement in asset prices and capital flows (Fratzscher, (2012), Raddatz and Schmukler (2012), Jotikasthira et al. (2012), Ghosh et al., (2014), Broner et al. (2013), Rey, (2013), Puy (2016), Claessens, Cerutti and Puy (2015)). Most of the debate has focused on the importance of global (or external) factors for (local) asset price movements, and the role of foreign investors in propagating shocks across countries. Broadly speaking, our results support the view that external events matter and are in general stronger than local factors. In particular, global news sentiment contributes significantly to global asset prices comovement, through its impact on international investors’ behavior. However, we do not find evidence that this phenomenon has increased over time or affects more EMs than AEs.

Finally, from a technical perspective, we are connected to the recent and fast-growing literature that links textual information to both economic and financial outcomes (see Gentzkow, Kelly, and Taddy (2017) for a review). Among many others, Baker, Bloom, and Davis (2016) develop an index of economic policy uncertainty from US newspaper articles, showing that it forecasts declines in investment, output, and employment.<sup>3</sup> Using daily Internet search volume from millions of households in the US, Da, Engelberg and Gao (2015) found that the volume of queries related to household concerns (e.g., “recession,” “unemployment,” and “bankruptcy”) could predict short-term return reversals, temporary increases in volatility, and mutual fund flows out of equity funds and into bond funds.

The rest of the paper is constructed as follows. Section II presents the data used in this paper, and the text analysis we use to construct sentiment measures. Section III presents the empirical framework and key results. Section IV provides further results on the properties of the global news sentiment index. Section V reports extensions and robustness. The last section concludes.

> 3 Our results are orthogonal to the various EPU indexes constructed by Baker, Bloom and Davis (2016). Results available on request.
27 Tablc I

# GENERAL CHARACTERISTICS OF REGIONAL GROUPINGS IN SSA! 1989 UNLESS OTHERWISE INDICATED

|_Nan_c of Regional<br>3rouping|Date<br>Created|Number of<br>_Members_|Total Population<br>(millions)|Total<br>GNP<br>(bil.S)|Per capita GNP<br>(US S)|Degrce of openneu<br>((X+M)IGNP)|Share o|f Inur-gro|up Expo<br>Exports|rt Trmde i|n Toul|Trade w<br>As%o<br>exp|ith SSA<br>f total<br>olta|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
||||||||1970|1975|1930|1985|1990|t9S0|1990|
|WEST AFRICA<br>ECOWAS||||||||||||||
|<br>CEAJ1|1975<br>1973|16<br>7|195<br>50|64<br>24|326<br>476|50<br>|2.9<br>|4.0<br>|3.5<br>|5.3|5.7|3.6|6.4|
|mt,|1980|<br>3|<br>12|<br>4|<br>355|46<br>|6.3<br>|12.7<br>|1.9<br>|3.7|10.5|13.2|15.0|
|||||||46|0.2|0.4|0.5|0.4|0.1|0-9|2.9|
|CENTIALAFRICA<br>UDEAC||||||||||||||
|<br>CEPtiL|1976<br>1932|6<br>3|24<br>47|19<br>12|806<br>|42<br>|4.3<br>|2.7<br>|1.6|iAe|3.0|2.1|5.9|
|EAST|||||260|21|0.4|0.3|01|0.1|0.2|4.1|7.6|
|ANT)<br>SOUTHII?RNAFRICA<br>PTA||||||||||||||
|<br>SADt'C-C|1981<br>1980|IS<br>10|212<br>S0|5S<br>25|274<br>311|40<br>|3.0<br>|9.3<br>|7.6<br>|5.5|5.9|8.4|7.6|
|SACIP-|1910|<br>5|<br>39|<br>K9|<br>2294|55<br>|2.6<br>|3.7|2.1|3.9|4.1|3.5|6.3|
|||||||54|**nVA**|na.|**na.**|**na.**|**na.**|**n.a.**|**na.**|
|TOTALSSA||47|480|162|340|43||||||2.S|6t)|

_1I_ SSie auniformly deruied to exclude South Afuica.

2/ Dat for SADCC and SACU exclude Namibia.

ECOWA4S CEAO - Communaute Economique de L'Afrique de L'Oueat, includes. Benin, Burkina Faso, C6oe d'lvoire, Mali, Mauritania, Niger and Senegal.= Econoinic Conmnunity of Weasem African Statee, includes: CEAO and MRUn membecr plus Cape Verde, **Ganmbia.** Ghana. Guinea Biaaau, Nigeria and Togo. MRU = Mano River Union, includee: Guinea, Liberia, Sierra Leone UDEAC' Union Duanifre el Econornique de L'Afrique Centrale, includes: Cameroon, Central African Republic, Chad, Congo, Equatorial Guinea **and** Gabon. CEPGL = Communaute Econonmique des Pays des Grands Lacs, includes: Burundi, Rwanda And Zaire. ffA Tanzania, Uganda, Zambia, Zimbabwe.Preferential Trade Area for Eatem and Southern African States, includer: Angola, Burundi, Comors, Djibouti, Ethiopia, Kenya, Lesotho, Malawi, Mauritiuu, Mozanbique, Rwanda, Somalia, Sudan, Swaziland, SADCC SACU ; - Southem African Cuatoma Union, includes: Botswana. Lerotho, Naiibia, South Africa, and SwazilandSoutheem African Developnent Coordination Conference, includes: Angola, Botawana, Leootho, Malawi, Mozatmbiqte, Namibia, Swaziland, Taneania, Zambia, Zinmbabwe.

Souree: Fomutan (1992), Tables 2 **and 3.**
countries would still be on the rise in 2030. At higher income levels, the shift into livestock products is complete and the tendency for all income elasticities of demand for food to decline identified by Timmer _et al._ (1983, p57) results in elasticities of 0.1 or lower in high-income countries such as the United States.

This relationship between income elasticities and income levels suggests that income growth in middle-income countries—where food demand has begun its shift towards the animal products that are much more demanding in terms of resource requirements—may be particularly important for food demand growth measured in resource requirements rather than calories.

The last row of Table 1 reports the estimated CE consumption changes between 2009 and 2050. Using <mark>the middle-ground GDP and population projections from the IIASA SSP,</mark> per capita CE consumption in 2050 was computed using 2050 GDP projections at the country level, multiplied by 2050 population projections and added up to the global level to compute global food demand in 2050. Global CE food consumption is projected to grow at an average rate of 1.72 percent per year between 2009 and 2050, more than doubling food demand (up 102 percent) by 2050. <mark>Our estimate is much larger than the 70 percent increase in food demand projected by FAO (2009) and 69 percent projected by Pardey</mark> _<mark>et al.</mark>_ <mark>(2014). But it is in line with Tilman</mark> _<mark>et al</mark>_ <mark>. (2011) who projected a food demand increase of 100 to 110 percent between 2005 and 2050, considering the caloric and protein content of crops used for human foods and livestock/fish feeds.</mark> Decomposing the projected food demand growth rate, we see an increase in the growth rate of per capita consumption—to 1.03 percent per year—and a sharp decline in the population growth rate, to 0.68 percent per year on average. Overall, Table 1 reveals an increasingly important role of per capita income growth relative to population growth in contributing to global food demand growth. Between 2009 and 2050, about 60 percent of projected food demand growth comes from per capita demand growth, as against 24 percent in the 1980s, 34 percent in the 1990s and 39 percent in the early 2000s. <mark>Baldos and Hertel (2016, p31), using an indicator of food market pressure that includes developments on both the demand and supply sides, also find an increase in the importance of income relative to population growth, concluding that income growth will, for the first time in history, rival population growth as a source of demand for food.</mark> Appendix Table A1 reports the twenty countries which contributed the most to the actual CE food demand increases for each of the past three decades, along with the projected top twenty 11
tax evasion, so it likely represents a lower bound.

These findings provide policy makers with a much clearer picture of just how widespread tax evasion is by registered firms in Indonesia. To date, there have not been precise estimates of the underlying level of tax evasion as only limited audit data exists, and surveys asking directly about tax compliance and/or tax morale can have substantial issues. Further, while analyses based on tax administrative data can provide valuable insights about the tax-paying behavior of firms, they do not necessarily shed light on intentional tax evasion in the same way that a double list experiment can. Arguably, the findings we present, which are based on nationally representative data and are internally consistent, provide among the best estimates of the levels of tax evasion by firms in Indonesia. Existing studies using single-list experiments to estimate tax evasion have typically focused on individuals as opposed to firms, and in these instances, reported tax evasion has been lower than what we observe (e.g., see Genest-Gr ́egoire et al., 2022 and Iraman et al., 2022). At a minimum, our findings suggest substantial increases in tax revenue are feasible if the government could increase the compliance of registered firms.

The double list experiment also provides unique insights for policymakers into the types of firms that are more likely to be non-compliant,<sup>11</sup> by extensively exploring heterogeneity and identifying three key dimensions. Firstly, there are higher rates of tax evasion among firms that do not export. A potential explanation for this heterogeneity is that exporting firms are more likely to have a paper trail of their economic activity (e.g., from custom licenses), which means that the volumes of sales of these firms are easier to monitor. In contrast, firms that do not export may perceive that the revenue authority has less third-party information about their business activities. Consequently, they are more willing to evade taxes. Secondly, firms that find tax administration to be a major obstacle to their business activities are much more likely to admit to evading tax. This suggests efforts to minimize the complexity and,

> 11The optimal targeting of enforcement activities would extend beyond just evasion rates, including the ease of detecting/proofing evasion, expected recovery rate on outstanding tax due, and deterrence value of enforcement.

16
(15.5%). The proportion of firms that use the web across the ECA region in 2005 is 67.4%, ranging from 83.5% in the EU-8 countries to 49.2% in the “Other CIS”.

Table 1 shows a substantial degree of heterogeneity in technology adoption across sectors, with firms in the manufacturing sector being significantly more likely to be ISO-certified and use the web in their operations than firms in other sectors. Firms in the mining and quarrying and construction industries are significantly more likely than the rest of the sample to have adopted ISO certification but are around the average for web-use. In contrast, the share of firms in other services sectors that adopted either of these technologies is significantly lower (with some exceptions such as the real estate industry) despite the evidence that ICT has led to substantial productivity gains recently in the services sector in the US and Europe. Our findings on ISO certification are consistent with global experience whereby certification is more prevalent in the manufacturing sector where signals of quality are important for export competitiveness.

We should note that we find ISO certification and web-use to be strongly correlated with firm performance both in the 2002 and in the 2005 samples. ISO-certified firms and web-users exhibit higher average value-added per worker faster sales growth, and pay higher wages than firms that do not adopt those modern technologies.<sup>9</sup>

# **IV.  Main Results**

In this section, we discuss our main results obtained from probit estimation of Equation (2) for ISO-certification and for web-use. To proxy for complementary inputs, we consider measures of worker skills and managerial capacity, R&D efforts, access to finance, and the quality of infrastructure - electricity and telecommunications. To proxy for market incentives, we consider the type of ownership of the firm (private or recently privatized), the degree of control by majority shareholders, firm size, measures of competition, and an index measuring the quality of governance based on the quality of contract enforcement, the predictability of government regulations and the bureaucratic burden felt by firms. To proxy for access to international knowledge, we consider foreign ownership (full or through a joint venture) and the firm’s participation in export markets. All variables are defined in Appendix Table 1.

Our probit regressions include GDP per capita which controls for country heterogeneity in technology adoption that is not captured by complementary inputs, market incentives, nor access to

> 9 These findings are obtained from regressions that control for industry fixed effects and for GDP per capita. The regression results are available from the authors upon request.

- 8 -
through post offices and state banks. Table 7 illustrates the degree to which enabling regulatory frameworks have been introduced for financial inclusion in the MENA region.

**Table 7. Enabling Frameworks for Financial Inclusion**

|**Country**|**MF Specific**<br>|**Investor-**<br>|**De**|**posit-taking allowe**|**d?**|
|---|---|---|---|---|---|
||**Legislation**|**friendly MFI**<br>**legal form?**|**By MFIs**|**By Post Office/**<br>**Post Bank**|**By Credit**<br>**Unions**|
|**Algeria**|-|-|-|-|Yes|
|**Egypt **|Yes|Yes|-|Yes|-|
|**Iraq**|-|-|-|-|-|
|**Jordan**|-|Yes|-|Yes|-|
|**Lebanon**|-|Yes|-|-|-|
|**Morocco**|Yes|-|-|Yes|-|
|**Syria**|Yes|Yes|Yes|-|-|
|**Tunisia**|Yes|-|-|Yes|-|
|**West Bank & Gaza**|Pending|-|-|-|Yes|
|**Yemen**|Yes|Yes|Yes|Yes|-|

Sources: M Khaled 2010; Sanabel/CGAP/MIX, 2010

# **Egypt has introduced regulations for non deposit-taking MFIs, while Syria and Yemen**

**have introduced laws permitting the establishment of deposit–taking MFIs** , and Jordan allowed MFIs to register as not-for-profit companies.  Egypt has approved a new Non-Bank Financial Institutions Licensing and Regulatory Bill, to be supervised by the Egyptian Financial Services Authority (EFSA), which will set the regulatory framework for microfinance, leasing, and factoring institutions, as well as standards in accounting, transparency and corporate governance, and lay the foundation for a new category of non-bank microcredit companies. Allowing the creation of supervised microfinance companies can unlock potential investment, while also raising standards for transparency and corporate governance for microfinance institutions.  This regulatory reform does not allow for deposit services to low income persons, although Egypt Post does provide fairly extensive access to microsavings services.

**Social Financial Banking Institutions (SFBIs) have been allowed in Syria since 2007** , with a minimum capital requirement of approximately USD 5 million. SFBIs are allowed to provide various financial services, including microlending, deposit-taking and micro insurance.  In Yemen the 2009 Microfinance Banks Law allows these „banks‟ to mobilize voluntary microsavings. A microfinance supervisory unit is being established.  However, in Syria and Yemen only a few institutions have applied for licenses, which may be related to what are reported to be lengthy registration and licensing procedures as well as lack of clear prudential guidelines. (Khaled, 2010) The business case of such deposit-taking MFIs is also unclear, as they would be competing with well-established postal savings networks. Other countries considering microfinance legislation to allow deposit-taking institutions include Iraq and Morocco.

20
# **MORE BENEFITS, FEWER CHILDREN: HOW REGULARIZATION AFFECTS IMMIGRANT FERTILITY**<sup>*</sup>

Catalina Amuedo-Dorantes<sup>†</sup> Ana Mar ́ıa Ib ́a ̃nez<sup>‡</sup> Sandra V. Rozo<sup>§</sup> Salvador Traettino<sup>¶</sup>

## **JEL Classification:** F22, O15, R23

**Keywords:** Migration, Refugees, Amnesties, Latin America.

> *Ib ́a ̃nez acknowledges financial support from the Inter-American Development Bank. We would also like to thank IPA Colombia for its support in collecting data for this project. The authors have no conflicts of interest to report. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the Inter-American Development Bank or the World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent. All errors are due only to the authors.

- †University of California Merced. E-mail:camuendo-dorantes@ucmerced.edu

- ‡Inter-American Development Bank. E-mail: anaib@iadb.org

- §World Bank, Development Research Group. E-mail: sandrarozo@worldbank.org

- ¶Inter-American Development Bank. E-mail: salvadort@iadb.org
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