rafmacalaba/datause-encoder-data huggingface dataset:
# **Appendix 8: LATE Impacts for Primary Outcomes**

|**Appendix Table 3: LATE Imp **|**acts on Pri**<br>|**mary Outco**<br>|**mes**<br>||||||
|---|---|---|---|---|---|---|---|---|
||Firm<br>Survival|Daily<br>Sales|Weekly<br>Sales|Main Product<br>Sales|Weekly<br>Profits|Main Product<br>Profits|Photo<br>Inventories|**Aggregate**<br>**Index**|
|**Impact of Receiving Training**|**, Allowing f**|**or Spillover**|**s**||||||
|Received Training*1 Year|0.007|202**|355|187|97|65|597|0.061*|
||(0.012)|(85)|(318)|(370)|(86)|(113)|(421)|(0.032)|
|Received Training* 3 Years|0.038**|212**|1283***|562*|273**|192|1017|0.108***|
||(0.016)|(104)|(428)|(329)|(108)|(119)|(1087)|(0.039)|
|Spillover Group * 1 Year|0.002|32|‐476*|157|‐65|‐16|336|‐0.011|
||(0.011)|(70)|(268)|(327)|(66)|(93)|(343)|(0.026)|
|Spillover Group * 3 Years|0.013|1|25|181|‐30|5|670|0.002|
||(0.014)|(85)|(328)|(269)|(79)|(94)|(867)|(0.029)|
|Sample Size<br>Notes: Robust standard erro<br>*, **, and *** indicate signif<br>All regressions control for ra<br>Receipt of training instrume|13508<br>rs in paren<br>icance at th<br>ndomizatio<br>nted with a|12943<br>theses, clus<br>e 10, 5, and<br>n strata fix<br>ssignment t|12909<br>tered at the<br>1 percent l<br>ed effects, th<br>o training.|12064<br>market level.<br>evels respectivel<br>e baseline valu|12881<br>y.<br>e of the ou|11985<br>tcome, and sur|5598<br>vey round fix|12923<br>ed effects.|

47
# **Competitiveness of Caribbean Producers**

Relative sugar production costs for ACP countries are shown in Figure 5 based on LMC International’s cane sugar production costs model. The estimated costs are the average during 2000-2002 of growing and processing sugar cane, transporting the raw sugar to the port, and loading it on the vessel. Costs are shown as an index relative to the highest cost prevailing among the world’s leading free market exporters (Australia, Brazil, Colombia, Guatemala, South Africa and Thailand), who between them account for approximately 60 percent of the world’s free market exports. This reference cost is shown as 100 in Figure 5. According to these estimates, Guyana is the lowest cost producer in the Caribbean with costs that are about 50 percent higher than the reference followed by Belize with slightly higher costs. Other Caribbean producers, such as St. Kitts & Nevis and Barbados, have costs that are more than twice the reference costs, while Jamaica and Trinidad & Tobago have costs that are more than triple the reference. These estimates should be viewed with caution because production costs are dependent on many factors, such as weather and exchange rates, and these factors can change significantly from one year to another. For example, the period used for the estimates does not reflect the current situation in Jamaica because that was the period immediately following the failed privatization when production was severely depressed and costs extremely high. However, the overall results confirm the high cost nature of the Caribbean sugar industry. Based on these relative costs, none of the Caribbean producers are competitive with low-cost world producers or major exporters. However, the industries in Guyana and Belize are the most competitive in the region and parts of these industries may be globally competitive.

**Figure 5. Raw Sugar Production Costs of ACP Producers, Average of 2000-2002 (f.o.b. basis)**

<!-- Start of picture text --> 400<br>Trinidad/Tobago<br>Madagascar<br>Jamaica<br>300<br>Barbados<br>Mauritius<br>Belize<br>St. Kitts &<br>200<br>Zambia Nevis<br>Fiji<br>Cote d'Ivoire<br>100<br>Tanzania<br>Swaziland Guyana Congo<br>Malawi<br>Zimbabwe<br>0<br>0.0 1.0 2.0 3.0 4.0<br>Production (million tonnes, raw value)<br>Full Costs (Exporters maximum = 100)<br><!-- End of picture text --> Source: LMC International & Oxford Policy Management, 2004.

12
Khalid, FA. "Automation in a Special Library in Kuwait." _Infomuon Teduin o d LAvwke% 2(4),_ 1983, Wp. 351-63.

Klausner, S&Z. 'A Professoes-Eye View of the Egyptian Academy." _Jaow naf dff4 IAadon7_ (4), 1986, pp. 163-77.

Marks, L.H.; Smith, W.F.; & Weld, Jr. W.E. "Notes on U.S-Middle East Exchanges." _In&nadovwIEduaCm CQdauu&chw 8(3),_ 1980, pp. 1-10.

Massialas, B.G. & Janrar, S&A. _Ewam in daeAnab Wodd._ Buffalo, New York Praeger Special Studies, 1983.

Pickering, S. "Pedagogica Deserna Memoir of a Fulbright Year in Syria." _Ameim Sodw, 50_ (2), 1981, pp. 163-77.

Prange, W.W., Jowett, D. & Fogel, B. _Tomorrow's Universities: A Wodde Look at Educadonaw O7wnge._ Boulder, Colorado: Westview Press, Inc., 1982.

Qubain, Fl. _EAwaLkm and Scime in dweAmb World._ Baltimore, Maryland: The Johns Hopkins University Press, 1966.

Qubaysi, IL "An Introducoy Study about the Geographical Distnbution of Arab Scientifc Researchers." In _ce ofa Snbkaa Arabl ain Dhran_ organized by ECWA. Beirut Center of Arab Unity Studies, 1981, pp. 197-207. (In Arabic) Safi A.Q. -Kuwait University and its Evaluation Program." _HMwEducad 15,_ 1986, pp. 421-47.

Safi, A.Q. & Mitler, RI. "Student Evaluations of Courses and Instructors at Kuwait University." _lua EAwa&m RePvik_ 18(3), 1986, pp. 17-25.

Saleh, MA "Development of Higher Education in Saudi Arabia." _HiwE4adiwa, 15,_ 1986, pp. 17-23.

Salmi, J. "Language and Schooling in Morocco." _InhnadnaIJaual ofEtuadonal Dereopmag_ 7 (1), 1987, pp. 21-31.

Shaheen El. & Kniebes, D.V. "Ttaining and Gas Engineering at the Algerian Petroleum Institute." _Owmicd Erqje nneAw4Ww,_ Summer, 1978, pp. 118-21.

Szyliowicz, _!S. Edicadon and Modnmzatkwin teMidd*eEast._ Ithaca, N.Y.: Cornell University, 1973.

> **_UNESCO._** _Reformand DvelopmentofHigherEducadorn UnitedArabRepublic._ Paris: UNEScO, 1969.

UNESCO. _Stadtsta Yewbooks 1977& 1986._ Paris: UNEsCO.

> **_UNESCO._** _Cwrent Swvys and Research in Stastcs._ CSR-E-54, January, 1987.

Vogler, R. 'Space for Technical Education How to Plan It (and How not to)." _Plnningfor}H*erF4acA&wij 8_ (3), 1980, pp. 1-10.

_32_
Kaplan, David, Eduardo Piedra, and Enrique Seira. 2011. “Entry regulation and business start-ups: Evidence from Mexico” _Journal of Public Economics_ 95(11-12): 1501-15.

Klapper, Leora, Luc Laeven and Raghuram Rajan. 2006. “Entry regulation as a barrier to entrepreneurship”, _Journal of Financial Economics_ 82(3): 591-629 Klapper, Leora and Inessa Love (2011) “The impact of business environment reforms on new firm registration”, Mimeo. World Bank McKenzie, David (2012) “Beyond Baseline and Follow-up: The Case for more T in Experiments”, _Journal of Development Economics_ , 99(2): 210-21.

McKenzie, David and Yaye Seynabou Sakho. 2010. “Does it pay firms to register for taxes? The impact of formality on firm profitability”, _Journal of Development Economics_ 91(1): 15-24.

Mullainathan, Sendhil and Philipp Schnabl, 2010. “Does less market entry regulation generate more entrepreneurs? Evidence from a Regulatory reform in Peru”, pp. 159-177 in Josh Lerner and Antoinette Schoar (eds.) _International Differences in Entrepreneurship_ , National Bureau of Economic Research, Cambridge, MA.

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|90th<br>1<br>1<br>0<br>0<br>1<br>0.64<br>1<br>1<br>1<br>40<br>25675<br>1171<br>167<br>0.66<br>1<br>9.5<br>7<br>20<br>0.64<br>1<br>1033<br>11785<br>1.1|
|---|
|75th<br>1<br>1<br>0<br>0<br>1<br>0.55<br>0<br>1<br>0<br>28<br>11374<br>505<br>83<br>0.57<br>1<br>3<br>2<br>5<br>0.17<br>1<br>171<br>3806<br>0.57<br>e Distribution|
|50th<br>0<br>0<br>0<br>0<br>1<br>0.36<br>0<br>0<br>0<br>18<br>4596<br>187<br>42<br>0.43<br>0.5<br>0.5<br>0.5<br>0.5<br>0<br>0<br>0<br>68<br>-0.36<br>of Baselin|
|25th<br>0<br>0<br>0<br>0<br>0<br>0.18<br>0<br>0<br>0<br>10<br>1877<br>36<br>18<br>0.32<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>-0.72<br>Percentiles|
|10th<br>0<br>0<br>0<br>0<br>0<br>0.09<br>0<br>0<br>0<br>5<br>700<br>6<br>6<br>0.24<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>-0.72|
|Std<br>Dev<br>0.50<br>0.50<br>0.28<br>0.29<br>0.49<br>0.22<br>0.36<br>0.50<br>0.31<br>13.9<br>23564<br>1492<br>106<br>0.16<br>0.50<br>8.43<br>3.22<br>21.19<br>0.48<br>0.49<br>1170<br>25128<br>0.83|
|Treatment<br>0.47<br>0.46<br>0.07<br>0.10<br>0.58<br>0.38<br>0.14<br>0.44<br>0.15<br>20.4<br>11853<br>659<br>68<br>0.43<br>0.49<br>3.26<br>1.70<br>7.32<br>0.23<br>0.34<br>341<br>5922<br>-0.04<br>100<br>ans|
|Control<br>0.46<br>0.43<br>0.10<br>0.09<br>0.58<br>0.36<br>0.17<br>0.52<br>0.07<br>20.1<br>11416<br>399<br>77<br>0.46<br>0.51<br>4.18<br>2.18<br>9.05<br>0.17<br>0.44<br>336<br>7617<br>0.04<br>100<br>Me|
|_Variables used in Stratification_<br>Small Firm<br>Medium Firm<br>Large Firm<br>Outlier in export data<br>Exported in last three years<br>Export Practices Index<br>_Other Variables_<br>Firm located in Antioquia region<br>Firm located in Cundinamarca region<br>Firm located in Valle de Cauca region<br>Firm age (years)<br>Firm sales in 2016 (millions of pesos)<br>Firm profits in 2016 (millions of pesos)<br>Number of employees in 2016<br>Business Practices Index<br>_Administrative data on exports_<br>Exported at all in 2017<br>Winsorized number of products exported 2017<br>Winsorized number of countries exported to in 2017<br>Winsorized number of country-products in 2017<br>Number of other firms in same country-product in 2017<br>Exported a new country-product in 2017<br>Free on board export value 2017 (1000s of USD)<br>Exports per worker in 2017<br>Overall Export Performance Index in 2017<br>**Sample Size**|

33
Table <u>6. Placebo effects of COVID-19 restrictions on educational outcomes (</u> _<u>continued</u>_ <u>)</u>

||(1)|(2)|(3)|(4)|
|---|---|---|---|---|
|_C. Switched to public school_|||||
|Warning index x 2019|-0.001|-0.000|-0.000|-0.000|
||(0.000)***<br>[0.004]|(0.000)***<br>[0.012]|(0.000)***<br>[0.004]|(0.000)***<br>[0.004]|
|Warning index x 2020|0.002|0.002|0.002|0.002|
||(0.000)***|(0.000)***|(0.000)***|(0.000)***|
||[0.001]|[0.001]|[0.001]|[0.001]|
|Pr(2019=2020)|0.000|0.000|0.000|0.000|
|Mean outcome|0.010|0.010|0.010|0.010|
|Adjusted R<sup>2</sup>|0.006|0.014|0.107|0.105|
|Observations|12,342,065|12,294,413|12,341,959|12,294,343|
|_D. Switched to private school_|||||
|Warning index x 2019|0.000|0.000|0.000|0.000|
||(0.000)|(0.000)|(0.000)|(0.000)*|
||[0.130]|[0.146]|[0.130]|[0.087]|
|Warning index x 2020|-0.003|-0.003|-0.003|-0.003|
||(0.000)***|(0.000)***|(0.000)***|(0.000)***|
||[0.001]|[0.001]|[0.001]|[0.001]|
|Pr(2019=2020)|0.000|0.000|0.000|0.000|
|Mean outcome|0.032|0.032|0.032|0.032|
|Adjusted R<sup>2</sup>|0.003|0.053|0.069|0.103|
|Observations|12,342,065|12,294,413|12,341,959|12,294,343|
|Controls|No|Yes|No|Yes|
|Year effects|Yes|Yes|Yes|Yes|
|Fixed effects|Municipality|Municipality|School|School|

_Source_ : Authors’ calculations from Guatemalan educational administrative records.

_Notes_ : The table reports placebo estimates of the effects of differential exposure to COVID-19. For this procedure, we drop data from 2021. Then, we assign the warning index values from 2020 to 2019 and the warning indices from 2021 to 2020, as if the pandemic began one year earlier. Each column presents results from a separate regression for each outcome. Clustered standard errors by municipality are shown in parentheses. Columns 1 and 3 estimates Equation (1) with no controls, Columns (2) and (4) include controls for gender, urban residence, level of schooling, grade, and whether the school provides bilingual instruction. We present q-values that adjust for multiple hypothesis testing in brackets, calculated using the method by Benjamini and Hochberg (1995) that controls for the false discovery rate described in Anderson (2008).

Significance levels: ***p<0.01; **p<0.05; *p<0.10.

28
and innovation partners being the most important types of linkages for technology diffusion.

# **4.1 Empirical specification**

In this sub-section we outline the baseline empirical specifications for examining the concentration of technology hiring in pioneer firms and how it dissipates over time, and the role of pre-existing supply chain linkages to pioneer firms in technology diffusion. For every specification within this section, we aggregate the matched dataset of establishments to the firm level as we have supply chain linkages data only at the firm level, resulting in a final firm-technology-year panel dataset.<sup>13</sup>

## **4.1.1 Concentration of technology hiring in pioneer locations over time**

Following our definition of pioneer firms in Section 2.3.1, we define the dummy variable _Pioneeri,_<sup>_T_</sup> _t_<sup>as taking the value of 1 if firm i is a pioneer firm for technology T in year t, and</sup> 0 otherwise. For each technology T, firm i and year t, we run the following regression with firm, technology and year fixed effects: _Yi,_<sup>_T_</sup> _t_<sup>=</sup><sup>_α_+</sup><sup>_β_1</sup><sup>_Pioneer_</sup> _i,_<sup>_T_</sup> _t_<sup>+</sup><sup>_β_2(</sup><sup>_Pioneer ∗years since emergence_)</sup><sup>_T_</sup> _i, t_<sup>+</sup><sup>_μT_+</sup><sup>_θt_+</sup><sup>_δi_+</sup><sup>_εT_</sup> _i, t_<sup>(6)</sup> where _Yi,_<sup>_T_</sup> _t_<sup>measurestechnologydiffusion,proxiedbythenormalizedshareoftechnology-</sup> related job postings. Apart from the dummy _Pioneeri,_<sup>_T_</sup> _t_<sup>, we also interact the variable with</sup> the number of years since a technology emerged to test for the persistence of this hiring concentration in pioneer firms.

## **4.1.2 The role of supply chain linkages to pioneer firms**

We proceed by estimating a series of specifications that allow us to examine the role played by _ex ante_ firm-to-firm linkages to pioneer firms in technology diffusion. In particular, we examine whether being linked to pioneer firms prior to the technology’s emergence i.e., whether being a supplier, buyer, innovation partner, or affiliate of a pioneer firm, results in faster diffusion of technology jobs after the technology emerges.

Table 5 shows that in total 43% of entities in the Lightcast-FactSet matched dataset are connected to at least one firm in a pioneer city for at least one technology through supply chain relationships in the two years before the technology’s emergence. Pioneer firms for

> 13Unlike the firm-level data from Factset, the establishment-level data derived from Lightcast does not contain sufficient information on exact location, industry and foundation year, which is needed to identify pioneers.

21
Tunisia is known for being the regional front runner with respect to women’s rights: the country abolished repudiation and polygamy upon the passage of its 1956 civil code (LatteAbdallah, 2012). Abortion was legalized in 1973, earlier than in France and Italy. Women have outnumbered men in higher education since the late 1990s (Assaad et al., 2017 and World Bank, 2022a) and have reached top positions in the public and private sector. In 2021, Nejla Bouden became the first female prime minister of the Arab world (Terriennes, 2021). Yet, gender discrimination remains problematic, especially when it comes to women’s labor market participation and property rights. Policy makers and human rights activists in Tunisia and the larger MENA region have argued that legal dispossession increases women’s vulnerability and hinders sustainable development. Women often cede the share of the bequest which they are legally entitled to male family members (see Conseil National des Droits de l’Homme, 2015) for the case of Morocco). According to a mixed method study conducted by Khodary (2018) in Egypt, this is especially common when the inheritance concerns agricultural land. The author argues that improving women’s access to inheritance is likely to have a very positive impact on development outcomes, but her results are mostly correlational.

In 2000, the Tunisian women’s rights advocate Yosra Frawes started a first unsuccessful petition in favor of gender equality in inheritance (Dahmani, 2018). The Tunisian Revolution ended the regime of Ben Ali and started a process of democratization in 2011. Article 21 of the 2014 constitution confirmed gender equality _before the law_ : “All citizens, male and female, have equal rights and duties, and are equal before the law without any discrimination” (Constitute Project, Org., 2014).<sup>2</sup> For progressive observers, President B ́eji Ca ̈ıd Essebsi’s creation of the COLIBE Committee in 2017 therefore seemed the logical continuation of the country’s reform efforts. Among other things, the Committee proposed an attenuated inheritance law reform according to which the family head would be allowed to bequeath a larger share to his male descendants if he expressed the wish to do so in a written testament. In the absence of explicit action, gender equality would be applied. Conservative voices, however, claimed that this proposal contradicted the first article of the constitution, which confers the status of state religion to Islam. A heated political discussion emerged and spilled over to other MENA countries where Tunisia has been perceived as a political role model (Constitute Project, Org., 2014, Blaise, 2019 & Zaireg, 2018). By contrast, the proposal for

> 2Some Tunisian legal scholars contest that gender equality _in terms of citizenship_ as defined in the constitution of 2014 establishes the right to equal inheritance rights, one reason being that inheritance falls into the _private sphere_ , not the public sphere, to which the constitution applies (see for example Verdier„ 2020).

9
product nomenclatures of 2007, 2012, and 2017 to the HS combined version. Moreover, we exclude all firm observations from the mining sector (HS chapter 25–27). That helps to avoid potential bias from Latin America’s commodity price cycles during 2007–2017. Thus, our sample frame contains all Colombian exporting firms between 2007 and 2017, except those from the mining sector.

# **2.2 NTM Data**

We use NTM data from UNCTAD and the Latin American Integration Association (LAIA) for its 18 core members in LAC between 2007 and 2017.<sup>4</sup> The raw data is recorded at the reporter-national tariff line leveldestination-NTM, 4-digit, and year level. We apply two steps to process the data, resulting in a novel and unexploited dataset comprising an exhaustive and updated set of trade regulations in Latin America between 2007 and 2017.

First, given a change in the classification of NTMs in 2012 we reconcile two NTM classifications pertaining to the periods 2007–2011 and 2012–2017. To that end, we derive a correspondence table between the pre-2012 and post-2012 classification at the 1-digit NTM chapter level using LAIA’s data collection in both classifications in 2011 and 2012. Using the new classification as the reference, we reclassified NTMs between 2007 and 2011 at the chapter level, consistent with UNCTAD’s (2019) Mast Classification M5. As a result, we observe the number of NTMs of each type (e.g. SPS, TBT, PSI, quantity control) for all Latin American reporter-destinationproducts continuously in each year between 2007 and 2017.

Second, we aggregate NTM data from the national tariff line level to the HS 6-digit product level. The background is that NTM data are collected at the national tariff line at 10 digits. However, since we take into account exports to various destination countries that do not harmonize national tariff line classifications, our two datasets cannot be satisfactorily merged 4Argentina, Bolivia, Brazil, Chile, Costa Rica, Colombia, Cuba, Ecuador, El Salvador, Guatemala, Honduras, Mexico, Nicaragua, Panama, Peru, Paraguay, Uruguay and the República Bolivariana de Venezuela.

7
different deposit and loan products. However, to the extent standardized products are not offered across countries, it is difficult to overcome this problem.<sup>1</sup> Second, fees and charges might differ because of differences in the scope and quality of the services provided rather than because of differences in pricing strategies. Third, we focus on the largest banks, not on the whole banking system. While this seems a restriction, by focusing on the largest banks we capture the barriers encountered by a majority of customers in a country. Finally, the nature of our survey is such that we are not able to capture non-bank financial institutions, such as finance companies and microfinance institutions. In spite of these shortcomings, we see this paper as an important first step in the effort to create consistent cross-country indicators of barriers that households and firms face in accessing financial services.

The remainder of the paper is organized as follows. Section 2 discusses the survey used to collect bank-level information. Section 3 presents the indicators and discusses their crosscountry variation. Section 4 shows that these barriers are correlated with cross-country indicators of outreach and firms’ financing obstacles and section 5 offers back-of-the-envelope calculations that show the impact of some of these barriers on access. Section 6 relates our indicators to bank and country characteristics associated with the institutional, contractual and, competitive environment, and section 7 concludes.

# **2. The survey**

The dataset is constructed from a web-based survey with 75 questions that was sent to the five most important banks in 115 countries in 2004 and 2005.<sup>2</sup> We chose to focus on the largest

> 1 We also considered asking questions on standardized loans and deposits, yet decided to collect information on actual barriers as opposed to “hypothetical” ones based on products that might not exist in all countries.

> 2 We defined importance in terms of total assets or branches.  Data collected from bank regulators and analyzed by Barth, Caprio, and Levine (2004) indicates that on average the five largest banks in over 100 countries account for 73 percent of bank assets and deposits.

5