rafmacalaba/datause-encoder-data huggingface dataset:
exchange rate against the US dollar E _푡 퐸푥푐h푎푛푔푒푟푎푡푒푖,푡_ +2, using _Consensus Forecast_ . As foreign investors may be measuring returns in exchange rate adjusted terms, currency depreciation would cause them to demand this risk premium. Ebeke and Lu (2015) control for the two-year-forward exchange rate of each currency against the US dollar.

# **3. Estimation results**

## **3.1 Baseline results**

Table 2 shows the baseline results. The tests for nonlinearity are significant with p-values smaller than 0.01.<sup>17</sup> Thus, we employ the IT, PSTR and GPSTR models instead of the linear model. This result illustrates that debt composition plays an important role on the non-linear behavior of the long-term interest rate.

### **3.1.1 Marginal impact of the expected public debt**

The main parameters of interest here are _훽_ 0 and _훽_ 1. As expected, _훽_ 1 is larger than _훽_ 0 in the IT, PSTR and GPSTR models. These results illustrate that the more public debt is financed by foreign private investors, the greater the marginal impact of the expected public debt on interest rates. Figure 6 shows this marginal impact ( _휕_ E _휕푡_ E _퐷푒푏푡푡 퐿푖,푡푖,푡_ + _푛_ + _푛_<sup>).One striking feature of this chart is that this impact, estimated through the GPSTR model,</sup> increases exponentially and significantly as the foreign private holdings ratio exceeds the location parameter, whereas the corresponding impact estimated through the IT model increases constantly and through the PSTR model becomes flattened. The right panel of Figure 6 shows if the share of foreign investors are 20, 30 and 40 percent, the marginal impacts of public debt on the interest rate are 1.7, 3.3 and 5.5 percentage points, respectively.<sup>18</sup> The result of the GPSTR model is consistent with DSGE studies, such as Schmitt-Grohe and Uribe (2003), Adolfson et al. (2007), and García-Cicco et al. (2010) that assume an exponential relationship between risk premia and foreign debt.

By contrast, when the foreign private holding ratios are below about 20 percent, the result of the GPSTR

> 17In the linearity test, we follow Luukkonen et al. (1988) and Terasvirta (1994), replacing the transition function _푔_ (·) of the PSTR and GPSTR models with the first-order Taylor expansion (please see Appendix A.1 for details). The conversion gives the IT model. Hence, the tests of the IT, PSTR and GPSTR models for nonlinearity show the same results.

> 18Following Driscoll and Kraay (1998), standard errors are corrected for serial correlation, heteroskedasticity, and cross-sectional dependence.

13
of the developing world (Figure 16). This relationship between trade and growth persists after controlling for reverse causality from growth to trade and for changes in other institutions and policies (Dollar and Kraay, 2002b).

Figure 16. Convergence and divergence in the 1990s <!-- Start of picture text --> GDP per capita growth rates, 1990s (ppp)<br>6%<br>5%<br>4%<br>2%<br>2%<br>-1%<br>0<br>Rich countries Globalizers<br>Rest of developing<br>world<br><!-- End of picture text --> A third type of evidence about integration and growth comes from firm-level studies and links us back to the quote from Paul Romer. Developing countries often have large productivity dispersion across firms making similar things: high productivity and low productivity firms coexist and in small markets there is often insufficient competition to spur innovation. A consistent finding of firm-level studies is that openness leads to lower productivity dispersion (Haddad 1993, Haddad and Harrison 1993, Harrison 1994). High cost producers exit the market as prices fall; if these firms were less productive, or were experiencing falling productivity, then their exits represent productivity improvements for the industry. While the destruction and creation of new firms is a normal part of a well-functioning economy, too often attention is simply paid to the 36
# **1 Introduction**

The dramatic rise in pirate attacks off the coast of Somalia over the years 2005-2011 stunned the international community. In total, 1,101 reported attacks have been attributed to Somali pirates, resulting in the hijacking of 217 vessels and their crews and an estimated US$338m paid in ransoms. Equally astonishing was its collapse in 2012, which has been largely sustained until now. The eradication of Somali piracy has been attributed to the deployment of naval assets in the Western Indian Ocean, celebrated as a rare show of international military collaboration, and to the increased use by shipping companies of private security contractors on board vessels sailing through pirate-infested waters.

In this paper, we focus on the tension between the two aforementioned forms of protection against crime, one publicly- and the other privately-provided, which led to its demise. To do so, we set up a structural model of Somali piracy, which we estimate using novel and rich data on incidents attributed to Somali pirates. On the one hand, the effect of international navy patrols is found to have been modest overall. On the other hand, the private provision of security was instrumental and characterized by both deterrence and crime displacement externalities.

The Somali piracy business model that we look at is exclusively a kidnap-and-ransom model, whereby the sole purpose of hijacking a vessel is to “sell” her back in her entirety to the shipping company as opposed to cargo and vessel theft, more prevalent elsewhere in the world. Attacks are launched against vessels sailing through the Gulf of Aden and beyond. When successful, vessel and crew are brought back to Somalia’s shores and a separate team takes over to protect and maintain the ship and feed the crew while negotiation with the shipping company for their liberation takes place.

Therefore, we model pirates as infinitely-lived agents who, in each period, decide whether to launch an attack against ships sailing off the coast of Somalia and when they do, choose what vessel to target. If successful, a bargaining game with asymmetric information is played between the pirates and the shipping company, which determines duration of captivity and ransom amount. Protective measures against crime come in two forms: navy patrols are a public good in that they uniformly lower the probability 2
points, with 95 percent confidence intervals approximately +/- 4 percentage points. These are thus small effects relative to the 30 to 34 percent of respondents in Figure 1 who said that COVID-19 had made them less likely to want to migrate when asked directly.

Why did the salience intervention not have more effect? One potential reason is that we asked about migration intentions over a five-year time horizon, and so COVID-19 might affect when individuals expect to migrate within this window, but not whether they will migrate. However, we believe the more important reason is that COVID-19 was likely already very salient to individuals even without the priming and salience treatment, and that the video appears to have not resulted in new knowledge accumulation.

Table 5 looks at awareness, knowledge, and risk perceptions about COVID-19, and compares them for the salience (B) and salience plus video (C) treatment groups. Comparing these responses gives the treatment effect of the video. First, there is almost universal awareness of COVID-19: 99.7 percent of respondents say they had heard of COVID-19 before our visit. Second, while knowledge is incomplete, especially with regard to some health issues (only 39 percent knew that the virus is not mainly spread by infected food, and only 50 percent knew that young children are not most at risk), 90 percent or more know social distancing is important, that the borders have closed with Senegal, and that Italy and Spain have been badly affected. That is, they already knew many of the key facts that influenced migration decisions. Finally, while 40 percent thought there was some risk that a household member in the village could get infected, 72 percent believed the risk in the village was either negligible or very low, and the video resulted in only a small increase in the perceived risk. These findings are very much consistent with the small effect of the salience intervention.

# **5 Conclusions and Implications**

In order to assess the impact of COVID-19 on migration intentions, we use a large-scale panel survey of Gambian young males conducted in May 2019 (pre-pandemic) and 18 months later. Consistent with a simple theoretical framework describing the different channels through which the COVID-19 pandemic may have changed migration intentions, we find that migration intentions to both Europe and especially to Senegal decreased. We find that the desire to migrate decreased especially for two groups of individuals: those who were at the margin, i.e. those who were unsure about migrating pre-COVID-19; and poorer individuals for whom COVID-19 may have made 18
resolve some of them. First, we provide some arguments in favor of our aggregation procedure and overall analysis of the data. Second, we make a critical assessment of the data we have available.

# 5.1 Alternative aggregation techniques

Transparency, simplicity and possibility to tailor the assessment procedure for one’s research agenda are the main reasons behind adopting our aggregation procedure - taking weighted averages of citizens’ responses. Besides, some questions are relatively more important and comprehensive for assessing governance, which cannot be detected by mechanized data mining algorithms. In addition, many of our findings and conclusions concern directly separate governance outcomes (responses on a separate question), which does not depend on aggregation procedure.

Nevertheless, we use alternative aggregation techniques to test the robustness of our results. In particular, we apply uniform weights to our data, as well as we use averaging over percentile rankings (the way it is done in the Doing Business project - Djankov, 2007). Naturally, both methods produce slightly different rankings comparing to our main methodology. In particular, European countries lose some positions and East Asian countries gain - the result of increased reliance on the governance outcomes, which are related to trust and confidence in governmental institutions. However, only 11 of 51 countries in case of uniform weights (10 out of 51 in case of averaged percentile rankings) significantly change their standing (according to classification provided in the Figure 1, wave 3 - when country changes one of three categories).

# 5.2 Adjusting the data

In our estimation we use survey data from countries around the world, and the public opinion in a country - especially about the issues related to the government - might be influenced by factors, which we would definitely like to account for. One of the factors is so-called ”intimidation” effect, when people are afraid to express their true - negative - opinion about their government, because they think they could be punished for that. Another factor, frequently mentioned in the literature, is the ”indoctrination” effect, when mass media in a country praise the government so much, that it has a significant positive impact on public opinion. Another factor is the degree of citizen activism and perceived role of government in a country. In particular, Norris (1999) argues about the emergence in the 70s in developed countries of the class of so called ”critical citizens” - people, who were becoming more and more critical and demanding towards their governments despite their obvious successes.

Taking into account 3 factors mentioned above (”intimidation”, ”indoctrination”, ”critical citizenship”) we conclude that in general a response on a question about governance outcome of an individual might be affected not only by the quality of governance in a country. The true model can be rewritten in the following way: 18
WPS7326 Policy Research Working Paper 7326 Community Managed Forest Groups and Preferences for REDD+ Contract Attributes A Choice Experiment Survey of Communities in Nepal _Sahan T. M. Dissanayake Prakash Jha Bhim Adhikari Rajesh Bista Randall Bluffstone Harisharan Luintel Peter Martinsson Naya Sharma Paudel E. Somanathan Michael Toman_ Development Research Group Environment and Energy Team June 2015
|DGE-based output<br>informality|Dynamic General Equilibrium (DGE) model-<br>based estimates on informal output in percent<br>of official GDP, calibrated as in Elgin and<br>Oztunali(2012).|Elgin et al.<br>(2021)|156|2000<br>-18|2,924|30.86|12.02|
|---|---|---|---|---|---|---|---|
|Share of self-<br>employment|Survey-based self-employment in percent of<br>totalemployment.|Elgin et al.<br>(2021)|163|2000<br>-18|1,906|31.88|21.67|
|MIMIC-based<br>output informality|Multiple Indicators Multiple Causes (MIMIC)<br>model-based estimates of informal output in<br>percent of official GDP.|Medina<br>and<br>Schneider<br>(2019)|155|2000<br>-17|2,790|29.67|12.38|
|DGE-based output<br>informality,<br>calibrated to survey-<br>based self-<br>employment|Dynamic General Equilibrium model-based<br>estimates on informal output in percent of<br>official GDP, calibrated using survey-based<br>self-employment (see Appendix for details).|Authors|155|2000<br>-18|2,283|43.55|31.11|

18
<mark>Related to this, an emerging literature argues that initial founding conditions are an important determinant of entrepreneurial success.</mark> Ayyagari, Demirgüç-Kunt, and Maksimovic (2017) use Indian census data and show that initial size (proxy for initial skills) is a key determinant of how large a firm is during the early lifecycle. Using US data, Maksimovic, Phillips and Yang (2013) show that initial size and productivity predict subsequent acquisition activity and the decision to go public. Ayyagari and Maksimovic (2017) also show that the initial skill of an establishment strongly predicts the future skill and growth of US manufacturing establishments.

Business training has emerged as one of the most common forms of capacity building provided to small firms around the world, but until recently there has been very little rigorous impact evaluation of these training programs. Bloom et al. (2013) run a field experiment where they provide free consulting on modern management practices to a randomly chosen set of Indian textile firms, and find that adoption of these practices increases productivity. Drexler, Fischer, and Schoar (2014) show that for micro entrepreneurs, simple rule of thumb training had a bigger impact on firms’ financial practices and revenues compared to standard accounting training.

To summarize, these studies provide suggestive results that managerial capital can be a limiting factor in the growth of firms in developing countries, and that this managerial capital could be transmitted through consulting services. Greater research is needed to understand what specific types of managerial capital are important for SMEs and how to overcome market failures that are preventing more SMEs from availing these services.

39
'igure 3: PRICE ANi LtLLFAKL EFFECTS OF A SifIFT I-<sup>**THE**SUPPLY CUMYE</sup> <!-- Start of picture text --> '~ Sm }ligure 3A<br>PP<br>C1l<br>T X 1<br>I I.<br>r i ipure<br>IT~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~<br>l.n t . _ _ _ _ 5 |-_ ~~~~~~~~~~~~~Dw<br>Ci'"t<br>'~~~~~~ _ _ _ , , =_ _ _ I. // _ _ _ = _ _ _,<br><!-- End of picture text -->
12 In this section we will investigate 7rhether seigniorage levels were in effect excessive in Argentina based on an estimation of the demand for money. Using Cagan's demand for money function we will attempt to determine the value of the revenue maximizing rate of inflation and the corresponding level of seigniorage.

There is no agreement, based on the existing literature on th. demand for money in Argentina, regarding the revenue maximizing rate of inflation. Fernandez and Mantel (1985), for example, estimated that this rate is in the 20 percent per month range, Rodriguez (1988)8 calculated numbers that are closer to 30 percent per month, while Demaestri and Duefias (1978) suggested that the rate is closer to 7 percent. Melnick (1988) incorporates a ratchet effect in the demand for money and estimates the revenue maximizing rate of inflation at 22Z when inflation exceeds previous levels and at 29Z when it does not.

In this vection we will investigate the characteristics of the demand for money in Argentina based on monthly data from 1979 to 1985. For estimation purposes we will divide the sample into three clearly differentiated periods. The first one, from January 1979 to January 1981, corresponds to the interval in which the government preannounced the value of the exchange rate (the otablita' period). The authorities started the preannouncement of the exchange rate on December 20, 1978 and the regime continued in place until February 1981, when a 10 percent unscheduled devaluation was effected. During this time there were no controls on 8 in Bruno et al, Inflation and Stabilization
**<u>Exhibit 2.8 – Leverage indicators</u>**

||**Current to**<br>**Total**<br>**Liabilities,**<br>**(%)**|**Total debt to**<br>**Equity, (%)**|**Total**<br>**liabilities to**<br>**Equity, (%)**|**EBIT / Total**<br>**Interest**<br>**Expense Ratio**|
|---|---|---|---|---|
|**Whole peer group (WS)**|||||
|Median|69.6|22.2|58.5|3.0|
|Mean|65.1|36.4|64.7|279.4|
|**LMI countries, excl. Egypt (WS)**|||||
|Median|69.6|19.9|55.3|2.4|
|Mean|64.4|35.6|58.8|458.8|
|**Top Tier, Egypt (WS)**|||||
|Median|78.6|31.7|89.8|5.3|
|Mean|74.2|45.0|93.5|85.6|

_Source: Worldscope; World Bank staff analysis_ Exhibit 2.10 shows statistical differences of indicators between Egypt and benchmark groups, adjusted for differences in industry composition of countries. Clearly, relative to the LMI group, the typical Egyptian firm has a 11.8 pp higher debt to equity ratio. It is still 7.3 pp higher compared to the peer group, but no longer statistically significant. The even higher total liabilities level, combined with a statistical significantly higher short term debt level, support the earlier finding of emphasis on short term maturities. Moreover, the significantly higher current liabilities level implies a strong reliance on trade finance.

**Exhibit 2.9 – Leverage analysis by industry**

_<u>Medians by year and average median and compounded average growth rate of period 2003-2007</u>_

||**Travel a**|**nd leisure**|||**Constru**|**ction and ma**|**terials**||
|---|---|---|---|---|---|---|---|---|
||**2003**|**2007**|**Average**|**CAGR**|**2003**|**2007**|**Average**|**CAGR**|
|**Current liabilities to total liabilities, %**|||||||||
|Peer group|50.9|55.8|53.5|1.9|57.8|53.2|59.4|-1.7|
|Egypt - Top tier|61.0|61.9|66.9|0.3|53.6|66.7|58.9|4.5|
|**Total debt to Equity, %**|||||||||
|Peer group|24.1|17.2|16.6|-6.6|14.3|27.5|21.5|14.0|
|Egypt - Top tier|74.5|44.3|59.1|-9.9|52.2|61.8|46.4|3.5|
|**Total liabilities to Equity, %**|||||||||
|Peer group|45.6|53.6|46.9|3.3|44.9|55.9|52.7|4.5|
|Egypt - Top tier|106.0|86.8|109.5|-3.9|81.5|89.3|76.1|1.8|
|**Short term liabilities to total liabilities, %**|||||||||
|Peer group|14.3|15.6|15.2|1.8|16.3|14.6|15.8|-2.1|
|Egypt-Top tier|18.4|24.3|19.7|5.7|20.1|30.9|19.5|9.0|
||**Consum**|**er staples**|||**Industri**|**al cyclical**|||
||**2003**|**2007**|**Average**|**CAGR**|**2003**|**2007**|**Average**|**CAGR**|
|**Current liabilities to total liabilities, %**|||||||||
|Peer group|71.7|69.0|70.1|-0.8|72.8|75.9|75.0|0.9|
|Egypt - Top tier|86.4|96.8|94.5|2.3|76.6|84.1|77.2|1.9|
|**Total debt to Equity, %**|||||||||
|Peer group|29.9|30.4|30.7|0.3|18.7|19.3|18.8|0.6|
|Egypt - Top tier|32.4|20.7|21.0|-8.6|30.6|16.3|42.7|-11.8|
|**Total liabilities to Equity, %**|||||||||
|Peer group|66.8|64.9|64.3|-0.6|58.1|57.0|59.5|-0.4|
|Egypt - Top tier|83.5|112.9|101.1|6.2|58.4|78.1|82.4|6.0|
|**Short term liabilities to total liabilities, %**|||||||||
|Peer group|90.8|96.0|94.5|1.1|20.7|17.2|19.3|-3.6|
|Egypt-Top tier|58.4|60.0|61.0|0.5|22.2|50.6|32.3|17.9|

_Source: Worldscope; World Bank staff analysis_ 10
Table **1.** Sectoral Features of the Semi-Industriat **Economy**

|Sector|Sharein<br>gross<br>output (X)|Exports/<br>output (X)|Imports/<br>domestic<br>sales (X)|<br>Elasticity of<br>substitution<br>in production|Export<br> <br>supply<br>elasticitya|Import<br>elasticity<br>of demanda|Cost dis-<br>advantage<br>ratio|Domestic price<br> <br>eLasticity<br>of demand|
|---|---|---|---|---|---|---|---|---|
|Primary<br>Fd|8.9<br>|4.9<br>|40.4<br>|2.5|0.75|1.8|--|--|
|oo products<br>C d|9.6<br>|2.5<br>|6.5<br>|1.5<br>|1.5<br>|2.5|--|--|
|onsumer goos<br>Pd d|14.4<br>|32.5<br>|14.2<br>|1.0<br>|1.5<br>|2.4|0.1|1.6|
|roucer goos<br>H id|20.1<br>|16.6<br>|19.2<br>|0.9<br>|1.5<br>|2.2|0.1|1.3|
|eavy nustry<br>|7.7<br>|31.9<br>|41.0<br>|0.9|1.5|1.9|0.1|1.4|
|Traded services<br>Ntdd i|13.2<br> <br>|24.4|7.5|1.5<br>|1.5|2.0|--||
|onrae servces|<br>26.1||--|_0.9_|--||--|--|

a. Expenditure-compensated price eLesticities. For imports (exports), expenditures (sales) on constant elasticity of substitution (transformation) a egate of domestic and import (export) goods held constant.

X b. The cost disadvantage ratio (difference between average and marginal costs divided by average cost) is a measure of unrealized economies of scale.
<!-- Start of picture text --> Figure 12<br>China<br>CO2 Emissions f rom Primary Aluminum Production<br>and f rom Alumina Production<br>(Million Metric Tons)<br>280<br>240<br>200<br>118 MMT CO2 Sav ed<br>160<br>120<br>80 76 MMT CO2 Sav ed<br>BAU CO2 Emitted Primary Aluminum<br>40 CO2 Emitted Primary Aluminum Af ter Technological Upgrading<br>CO2 Emitted Af ter Technological Upgrading in Alumina<br>BAU CO2 Emissions Alumina<br>0<br>80 82 84 86 88 90 92 94 96 98 00 02 04 06 08 10<br><!-- End of picture text --> Taken together, improvements in energy efficiency within existing technological regimes and technological upgrading of those regimes in China’s cement, aluminum, iron and steel, and pulp and paper industries have had a remarkable impact. Without these changes CO2 emissions from these four industries would have been nearly 2.3 times higher (5.04 billion metric tons in 2008 instead of actual emissions of 2.18 billion metric tons, figure 13). This would have pushed total CO2 emissions from fossil fuels up by nearly 45% to 9.41 billion metric tons in 2008.<sup>99</sup> <!-- Start of picture text --> Figure 13<br>China<br>CO2 Emissions from Cement,<br>Aluminum, Iron and Steel<br>and Paper Production<br>(Million Metric Tons)<br>6,000<br>5,000<br>4,000<br>3,000<br>2,000<br>1,000 CO2 Emissions Without Technological Change<br>CO2 Emissions After Technological Upgrading<br>0<br>80 82 84 86 88 90 92 94 96 98 00 02 04 06 08<br>Source: Authors Calculations<br><!-- End of picture text --> 99 Authors calculations where actual CO2 emissions from burning fossil fuels are from IEA Data Services on Line (2012).

27