rafmacalaba/datause-encoder-data huggingface dataset:
_improved seeds_ , _line seeding_ and _lime_ . For each technology, a dummy variable taking the value of one defines if the household has applied the respective practice in the 2017 main cropping season on any plot and for any crop type.

We construct an _overall ISFM knowledge_ score based on questions on each of the individual ISFM components (excluding questions on lime). It ranges from zero to one, with one standing for full knowledge, i.e., having answered all questions correctly.<sup>15</sup> Since the aim of the video treatment was to increase farmers’ knowledge on _why_ ISFM is important (and not on _how_ to implement it), we also construct two individual indicators for _principles_ and _how-to knowledge_ , depending on whether a question was on the purpose (the ‘why’) of a technology, or its mode of implementation (the ‘how-to’), which also range from zero to one. For the how-to score, twice the weight is given to knowledge on how to correctly produce compost, since this is a more complicated process than the implementation of the other ISFM practices. The principles score gives equal weights to all ISFM components, and includes one indicator for the general understanding of the necessity to integrate organic and inorganic soil inputs.<sup>16</sup> For the analyses, the household heads’ knowledge score is used.

# Estimation strategy for intent-to-treat effect using RCT design

In order to assess the effects of the experimental interventions on ISFM adoption and knowledge, regressions of the following form are estimated: where Yij denotes the respective outcome variable for household or individual _i_ in mws _j_ , measured at endline. T1j is a dummy variable indicating whether the mws was assigned to the extension intervention, and T2j indicates whether the mws was assigned to the combined

> 15 Since the number of questions is not the same for all practices, we first calculate a knowledge score for each component individually and then combine it to an overall score, so that each ISFM dimension is included with the same weight. Farmers who were not aware of a practice in the first place, were immediately given a value of zero in the respective follow-up questions. 16 This is based on the respondent selecting the following statement as being correct: “The soil needs both organic and inorganic inputs to be healthy and fertile”.

13
assembly. Because of variation in the extent to which headmasters effectively disseminated information about the scholarship, there was a sense that awareness was inadequate in some areas, and as a result the NGO held additional community meetings in September and October to reinforce knowledge about program rules in advance of November 2001 district exams. After these meetings, enumerators began collecting school attendance data during unannounced visits.

The 2002 student survey indicates that girls had excellent knowledge of the program: 88% of cohort 1 and 2 girls in Busia district claimed to have heard of the program, and knowledge levels were only slightly worse in Teso district (85%). Girls had somewhat better knowledge about program rules governing eligibility and winning than boys: Busia girls were 8 percentage points more likely than boys to know that “only girls were eligible for the scholarship” (86% to 78%) and 7 percentage points more likely to know exactly how many scholarships would be awarded (32% to 25%), and patterns are again similar in Teso district (not shown). Girls in Busia were only slightly more likely than boys to report that their parents had mentioned the program to them at home (72% to 70%).

In June 2001, a tragic incident occurred in which lightning struck a primary school in Teso district (Korisai Primary School), severely damaging the school, killing seven students and injuring 27 others. Because ICS had been involved with an assistance program in that school, and due to certain strange coincidences (the names of certain lightning victims were the same as the names of ICS staff members who had recently visited the school) the deaths were associated with ICS in the eyes of some community members, and the incident led several schools to pull out of the Girls Scholarship Program. Of the original 58 sample schools in Teso district, five pulled out of the program at that time, and one Busia district school located near the Teso border also pulled out. Figure 1 presents the location of the lightning strike and of the schools that pulled out of the program, several of which are located near the lightning strike. Three of the six schools that pulled out of the program were treatment schools. We discuss implications of this tragedy for econometric inference in Section 4.2 below.

9
children’s academic success. _Child Development, 83_ , 1180 –1195. http://dx.doi.org/10.1111/j.1467-8624.2012 .01761.x Solomon, D., Battistich, V., Watson, M., Schaps, E., & Lewis, C. (2000). A six-district study of educational change: Direct and mediated effects of the Child Development Project. _Social Psychology of Education_ , _4_ (1), 3-51.

- Stage, S. A., & Quiroz, D. R. (1997). A meta-analysis of interventions to decrease disruptive classroom behavior in public education settings. _School Psychology Review, 26_ (3), 333-368.

- Stallings, J. A. (1976). How instructional processes relate to child outcomes in a national study of follow through. _Journal of Teacher Education_ , _27_ (1), 43-47.

- Stefanou, C. R., Perencevich, K. C., DiCintio, M., & Turner, J. C. (2004). Supporting autonomy in the classroom: Ways teachers encourage student decision making and ownership. _Educational Psychologist_ , _39_ (2), 97-110.

- Stipek, D. J., & Kowalski, P. S. (1989). Learned helplessness in task-orienting versus performance-orienting testing conditions. _Journal of Educational Psychology_ , _81_ (3), 384-391.

- Stronge, J. H., Ward, T. J., Tucker, P. D., & Hindman, J. L. (2007). What is the relationship between teacher quality and student achievement? An exploratory study. _Journal of Personnel Evaluation in Education_ , _20_ (3-4), 165-184.

Stronge, J. H. (2018). _Qualities of effective teachers._ ASCD.

Strong, M., Gargani, J., and Hacifazlioğlu, Ö. (2011). "Do we know a successful teacher when we see one? Experiments in the identification of effective teachers." _Journal of Teacher Education_ , 62(4) 367-82.

Sutherland, K. S., & Wehby, J. H. (2001). The effect of self-evaluation on teaching behavior in classrooms for students with emotional and behavioral disorders. _The Journal of Special Education_ , _35_ (3), 161-171.

- Tajfel, H. (1979). Individuals and groups in social psychology. _British Journal of Social and Clinical Psychology_ , _18_ (2), 183-190.

- Taylor, R. D., Oberle, E., Durlak, J. A., & Weissberg, R. P. (2017). Promoting positive youth development through school‐based social and emotional learning interventions: A meta‐analysis of follow‐up effects. _Child Development_ , _88_ (4), 1156-1171.

- Taylor, B. M., Pearson, P. D., Peterson, D. S., & Rodriguez, M. C. (2003). Reading growth in high-poverty classrooms: The influence of teacher practices that encourage cognitive engagement in literacy learning. _The Elementary School Journal, 104_ (1), 3-28.

- Trako, I., & Molina, E. (2018). The learning crisis in Tanzania. Working Paper. World Bank, Washington, D.C.

61
|... (log of distance)|0.036*|0.049***|0.032|-0.024|0.046***|0.053***|
|---|---|---|---|---|---|---|
||(0.020)|(0.008)|(0.021)|(0.049)|(0.014)|(0.009)|
|Observations|449,922|3,275,053|333,842|116,066|952,400|2,322,653|
|R-squared|0.865|0.821|0.872|0.821|0.831|0.817|

Note: Robust standard errors clustered at the cluster exporter-importer-product level are in parentheses. All specifications include importerexporter-product, importer-year, and exporter-year fixed effects. The samples include the top 15 producers of automobile or top 15 exporters of final electronics other than Japan.

*** p<0.01, ** p<0.05, * p<0.1

Table 4 presents the estimates of Equation (4) focusing on fundamentals: distance, size and level of development. The negative and significant effect on GDP per capita indicates that in the years following the shock, developing countries were more likely to be the new destinations for imports of auto and electronics. For instance, results in columns 1 and 2 suggest that an increase in GDP per capita from the level of the median upper-middle income to the median high income country decreases exports by around 10 percent.<sup>18</sup> Similarly, imports tended to relocate to larger countries, especially for auto parts (column 3) and electronics (columns 5 and 6), perhaps to take advantage of economies of scale. The results do not indicate that closer countries benefited from the relocation. For electronics, imports tended to relocate to more distant suppliers reflecting relatively low trade and transport costs.

_Table 5: Other country-specific characteristics_

||(1)|(2)|(3)|(4)|(5)|(6)|
|---|---|---|---|---|---|---|
||A|ll|Auto||Electro|nics|
||Auto|Electronics|Intermediate|Final|Intermediate|<br>Final|
||log of<br>imports|log of<br>imports|log of<br>imports|log of<br>imports|log of<br>imports|log of<br>imports|
|(Dummy share 2004-2010 > 10)|0.177***|0.098***|0.123***|0.087|0.197***|0.073***|
||(0.035)|(0.011)|(0.040)|(0.080)|(0.021)|(0.012)|
|(Dummy share) * ...|||||||
|... (log GDP pc pre)|-0.024|-0.051***|-0.037*|-0.004|-0.061***|-0.047***|
||(0.018)|(0.008)|(0.021)|(0.038)|(0.014)|(0.009)|
|... (log of pop. Pre)|<br>0.050***|<br>0.026***|<br>0.060***|<br>0.010|<br>0.029***|<br>0.024***|
||(0.011)|(0.005)|(0.012)|(0.026)|(0.009)|(0.005)|
|... (log of distance)|-0.061**|0.025**|-0.052*|-0.041|0.020|0.029**|
||(0.026)|(0.012)|(0.029)|(0.060)|(0.022)|(0.014)|
|... I(Contiguity)|0.082|0.053|-0.003|0.456**|0.106|0.020|
||(0.095)|(0.036)|(0.100)|(0.215)|(0.073)|(0.042)|
|... I(Same Region)|-0.318***|0.008|-0.196**|-0.071|-0.005|-0.003|
||(0.076)|(0.031)|(0.085)|(0.167)|(0.058)|(0.036)|
|... I(High Vulnerability to Natural Disasters)|0.026|0.043|0.011|0.096|0.054|0.025|
||(0.061)|(0.027)|(0.072)|(0.110)|(0.052)|(0.031)|
|... I(Top 4 supplier pre)|-0.911***|-0.440***|-0.950***|-0.811***|-0.398***|-0.465***|
||(0.097)|(0.033)|(0.105)|(0.206)|(0.059)|(0.039)|
|... (RCA pre)|0.250***|-0.066***|0.303***|0.158*|-0.139***|-0.036|

18 In 2010, the median GDP per capita for upper-middle income economies was USD 5,789 versus USD 33,700 for high income countries.

18
to these elasticities, one need to know how climate will change in the future, what the GPD per capita (or income) trajectory would be in the absence of climate change, and how population will grow. In general, papers in this section differ with respect to how they estimate these elasticities and the type of information they use about future projections.

# **_2.1 Backward looking approach_**

A number of recent studies have opted for a ―backward looking‖ approach to analyze the effects of climate change on economic activity, and ultimately on poverty. These studies, mimicking the approach emphasized in the growth and development literatures, examine the relationship between climate and aggregate economic variables in cross-sections of countries or regions. One advantage offered by this approach is that by examining aggregate outcomes directly, it is possible to avoid relying on _a priori_ assumptions about which mechanisms to include in the climate-economy interactions and how these mechanisms might interact, and ultimately influence macroeconomic outcomes. Another advantage derived by the use of cross-sectional data is that they yield estimates of the long-relationship between climate and aggregate output taking into account historical adaptation.

One such study is by Dell et al. (2009) who use cross-sectional data from 134 countries to examine the effects of temperature on the level of GDP. Their output-climate elasticity estimate, based on historical data, reveals that each additional degree Celsius is associated with a statistically significant reduction of 8.9 percentage points of per capita GDP. The authors also provide evidence of this elasticity at the sub-national level by considering the temperatureincome relationship using data at the municipal level for twelve countries in the Latin America and Caribbean region. Remarkably, they find a negative relationship between income and temperature when looking within countries, and even when looking within states within countries.<sup>3</sup> However, they make no attempt to either simulate the impacts of the predicted temperature increase on income, or estimate its effect on poverty.

In a similar vein, Andersen and Verner (2010) examine the relationship between temperature and welfare at the municipality level within five countries in Latin America

> 3 The within-country cross sectional relationship is substantially weaker than the cross-country correlation, but it remains statistically significant and of an economically important magnitude, with a 1 degree Celsius rise in temperature associated with a 1.2-1.9 percent decline in municipal per capita income (not GDP).

4
overall loan portfolios, as well as changes in corporate, consumer, and residential mortgage loans. In particular, we compare results for a sample of countries from two regions: Latin America (Argentina, Brazil, Chile, Colombia, Mexico and Peru) and Eastern Europe (Bulgaria, Croatia, Czech Republic, Hungary, Poland, Romania, Slovakia, and Slovenia). We selected these regions because they have important similarities, but also interesting differences. Both regions include middle-income countries that have among the highest levels of foreign bank participation in developing countries (Claessens and van Horen, 2012). However, there are also contrasts in the types of foreign banks that entered the two regions and in the role and size of state-owned banks. For example, in Latin America the dominant foreign players were Spanish banks, who are said to have funded most of their operations in those countries with local deposits, and extended most of their loans in local currency (Kamil and Rai, 2010). In Eastern Europe, (non-Spanish) banks from neighboring Western European nations were the dominant foreign players. These banks mainly resorted to wholesale funding from non-local sources and denominated most of their loans in foreign currencies. With regard to government-owned banks, though both regions entered the 1990s with sizable government bank participation, governments in Eastern Europe had divested their shareholdings more fully than those in Latin America by the late 2000s.<sup>5</sup> Our paper is related to an extensive literature on the effects of foreign bank participation in developing countries during crises. In particular, the impact of foreign bank ownership during earlier crisis episodes that originated in developing countries has been well-studied and generally indicates that foreign banks were a stabilizing force in terms of credit supply.<sup>6</sup> With specific

> 5 The average share of assets held by government-owned banks in the 8 Eastern European countries we focus on fell from 71 percent in 1995 to 10 percent in 2010, while among the 6 Latin American countries, average government bank ownership dropped from 41 percent to 19 percent.

> 6 For example, a study of 1,565 banks from twenty emerging markets from 1989 to 2001 finds weak evidence that foreign banks’ credit levels were less sensitive to monetary conditions in the host country, while their lending and deposit rates were less volatile than those of domestic banks during crises (Arena, Reinhart, and Vazquez, 2010).

3
|Past 1 year|1. Vehicle rental for<br>personal use: car,<br>moto/vélo etc.<br>2. Domestic and foreign<br>air transport<br>3. Purchase of personal<br>transportation (car,<br>moto,bicycle,etc.)|1. Bicycle<br>2. Motors, Pick-ups<br>3. Motorcycles|
|---|---|---|

# **Annex 2. Detailed Information on Transport Expenditures in LSMS Surveys (18 Countries in LSMS-tagged Collection)**

|**Survey Question**|**Afghanistan**|**Armenia**|**Benin**|**Bhutan**|**Burundi**|**Cameroon**|
|---|---|---|---|---|---|---|
|**_Non-food Expendi_**|**_tures during..._**||||||
|Past 7 days|||||||
|Past 1 month|1. Transportation fare -<br>bus and taxis<br>2. Fuel for car/motor bike<br>(do not include business<br>vehicles)|||1. Bus/ taxi fare &<br>other transport fare<br>2. Potter, pony<br>charges, etc.<br>3. Air fare<br>4. Rail/train fare<br>5. Transport (car,<br>motorcycle, etc.)<br>exclude power tiller,<br>tractor<br>6. Fuel and lubricants<br>for personal transport<br>(petrol, diesel, mobil,<br>etc.)<br>7. Spare parts and<br>accessories for<br>personal transport<br>(tire, brake pad, etc.<br>8. Maintenance and<br>repair of cars (service<br>charges only)|||
|Past 3 months|||1. Vehicle purchases:<br>a. Automobiles<br>b. Motorcycles<br>c. Bicycle<br>2. Vehicle operating<br>expenses:<br>a. Spareparts and||1. User expenses of<br>vehicle:<br>a. Fuel and lubricant<br>b. Maintenance of<br>passenger cars<br>2. Transport services:<br>a. Rail transport for|(Include a lot of detailed<br>subcategories)<br>Transport services:<br>a. Rail passenger transport<br>b. Road passenger transport<br>c. Air passenger transport<br>d. Otherpassenger transport|

31
worker search frictions and unemployment into a standard trade model, showing that such frictions can lead to a substantive revision of the distributional e¤ects of trade. For example, the Stolper-Samuelson theorem does not extend to an environment of that sort when formulated as a statement about the incomes of employed factors, but it does extend to such an environment when formulated as a statement about the expected lifetime income of searching factors. A wide range of e¤ects of search frictions on labor-market outcomes in trade models are gathered in Davidson and Matusz (2009).

(iii) Trade and innovation. A small cluster of theoretical work shows that innovation can be an important channel through which trade a¤ects income distribution, in ways that are very di¤erent from a comparative advantage approach. For example, Dinopoulos and Segerstrom (1999) study a two-country growth model with a continuum of industries, in each of which ...rms compete through research and development (R&D) for technological supremacy. In each industry, the ...rm with the best technology captures the entire market, but its price is limited by the marginal cost of the next-best available technology. At any moment, a large number of ...rms conduct R&D to obtain a breakthrough and become the new leader. Each country exports the products for which the industry leader happens to be, at the moment, one of its domestic ...rms, and each country initially maintains a uniform tari¤ against anything its consumers might import from the other country. The tari¤s cut into the market leader’s pro...t margins, reducing the jackpot that results from being the market leader, and thus reducing the incentive for any ...rm to do R&D to become the market leader. As a result, trade liberalization increases R&D, and growth, in both countries. Now, to the point about income inequality: If R&D is skilled-labor intensive relative to manufacturing, given its reliance on scientists and engineers, then trade liberalization will raise the relative demand for skilled labor in both countries, increasing income inequality all around. A related approach is provided by Neary (2003, section 9), in which identical countries with a large number of Cournot oligopolies open to trade. Each oligopolist now has an incentive to do R&D to lower its marginal cost 7
to return the completed letter to us. Participants were randomized into three groups.<sup>14</sup> The control group received only this reminder, while the other two groups received one of the following additional messages:

- “ _Research suggests reference letters almost double chances of getting a job interview_ .” (Information)

- “ _To compensate your costs, you get 100 Rand airtime after sending us the completed letter._ ” (Compensation)

# **4 Results**

This section reports and discusses the empirical findings from our three experiments. We begin with the results from the audit study (Exp. 1), where we recover the value of reference letters to both job seekers and hiring firms from a within-subject identification strategy. We then move to Exp. 2, where we can account for changes in job search behavior by study participants and obtain treatment effect estimates for employment. We conclude by presenting the results from Exp. 3 (as well as additional evidence from baseline data and focus groups) to discuss potential reasons behind the low usage of reference letters in equilibrium.

## **4.1 Audit study**

Experiment 1 tests the effect of reference letters on firm demand using within-subject randomization. We use two measures of employer response: (i) a narrow measure of interest that captures interview requests and (ii) a broader measure of interest that captures either an interview request or a different employer response (most commonly, firms asked questions, requested specific documents, or provided more information about the job and asked if job seekers were still interested). Throughout the analysis we will report results for both outcomes.

To estimate the effect of the reference letter, we estimate the following model:

> 14Comparing observable characteristics between the treatment and control group suggests that randomization was successful (Table A.5).

14
far higher share than for the others where the average is between 4-11 percent.<sup>8</sup> Concerning sector affiliation, there are differences depending on method of identification, but they are not that significant. The share of firms in wholesale and retail trade, as well as professional and scientific, is clearly higher for the PN Method, while the reverse is true for financial and insurance services. Comparing connected and non-connected firms, the former are mostly under-represented in manufacturing, construction and trade while being over-represented in all countries in professional and scientific activity.

Table 2 provides mean and median values for a range of firm characteristics and performance indicators distinguishing between connected – as measured by FN+PN – and nonconnected firms. These variables are taken from _Orbis_ and comprise levels of assets, capital, sales, employment, wage bill and wage per worker, output per worker, as well as the return on assets (ROA) – defined as the ratio of net income to total assets – leverage (a proxy for access to debt financing) and the tax rate.

For a number of variables, connected firms are consistently larger than non-connected ones. This discrepancy is mostly the case for sales but also for employment and average wages. In the case of ROA, connected firms mostly have lower values than non-connected ones. For leverage, mostly there is little difference although for both Hungary and Romania, connected firms are on average less leveraged. There is no clear pattern for the tax rate. The table also indicates that for both groups of firms, there is a large difference between mean and median values that indicates skewness to the right.

Finally, given that widespread evidence shows that politicians are particularly prone to trying to influence the actions of state owned enterprises (SOEs), such as the amount of hiring, _Orbis_ data show that for employment, the SOE share is particularly large in Serbia and Bulgaria (18-21%) and, to a lesser extent in Russia. The employment share for Spain ( _<_ 6%) is roughly comparable to Hungary and the Slovak Republic. For sales, the SOE share is huge in Russia ( _>_ 58%) and also substantial ( _>_ 18%) in Serbia. Elsewhere, the share falls in the range of 4-6%.

# **4 How are connections configured?**

Connections are rarely atomistic tending, rather, to have strong network dimensions. In this section, we try to understand more about the properties of such networks and, in particular, the links running from individuals and/or entities to firms, both private and state-owned. We are interested in identifying the scale of network connections, the factors – that appear to sort individuals into networks such as kinship or allegiance to a political

> 8Country level size and sector breakdowns are available on request.

8