rafmacalaba/datause-encoder-data huggingface dataset:
**Table 1: Sovereign and Banking Episodes in EMDEs, 1970‐2017**

||Number of Total<br>Crises<br>(sovereign or<br>banking)|Number of<br>banking crises<br>followed by<br>sovereing crises<br>in a 3‐year<br>period|Number of<br>sovereign crises<br>followed by<br>banking crises in<br>a 3‐year period|Number of bank<br>and sovereign<br>crises starting<br>simultaneously|Number of bank<br>only crises|Number of<br>sovereign<br>only crises|
|---|---|---|---|---|---|---|
|EAP|12|1|0|1|7|2|
|ECA|41|1|0|2|28|8|
|LAC|61|5|0|4|22|26|
|MENA|12|1|0|1|6|3|
|SAR|4|0|0|0|4|0|
|AFR|66|1|2|2|38|21|
|**Total**<br>Source:<br>Note: In<br>column,|**196**<br>Laeven and Valencia<br>second column, eac<br>sovereign and bank|**9**<br>(2018). Own calc<br>h crisis (sovereig<br>ing crises starting|**2**<br>ulations.<br>n or banking) is co<br>simultaneously ar|**10**<br>unted as a single c<br>e counted as one|**105**<br>risis episode. In th<br>crisis episode.|**60**<br>e fifth|

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ECCAS’S INFRASTRUCTURE: A REGIONAL PERSPECTIVE The loss in the total estimated seats between 2001 and 2007 can be largely attributed to the collapse of Cameroon Airlines and Air Gabon. The collapse of Air Afrique also had an impact.

Domestic connectivity is largely absent in the CEMAC countries, except for Cameroon and Gabon. Looking at the broader ECCAS grouping, Angola and the Democratic Republic of Congo are connected to a modest number of city pairs. The absence of domestic city pairs in CEMAC may simply be because the countries are physically small, but it more generally reflects low traffic volumes and limited purchasing power in the domestic market. This makes it difficult for air transport to compete with surface transport alternatives, such as roads. International city pairs are also relatively few in number. The Central African Republic connects to two international city pairs and Burundi and São Tomé and Príncipe connect to four. All countries have at least one intercontinental city pair (table 2.8).

**Table 2.8. Domestic, international, and intercontinental city pairs, 2007 (number)**

||Total city pairs|Intercontinental city pairs|International city pairs|Domestic city pairs|
|---|---|---|---|---|
|Angola|42|9|12|21|
|Burundi|5|1|4||
|Cameroon|28|8|17|3|
|Central African Republic|3|1|2||
|Chad|8|1|7||
|Congo, Rep. of|22|2|19|1|
|Congo, Dem. Rep. of|49|3|21|25|
|Equatorial Guinea|19|4|14|1|
|Gabon|22|1|12|9|
|São Tomé and Príncipe|5|1|4||

_Source:_ Bofinger 2009.

By and large, each country in CEMAC has one daily connection with Cameroon. Gabon and Cameroon have the strongest connectivity in the regional economic community with 18 flights daily. The origin-destination matrix for the ECCAS countries shows the minimal levels of air connectivity that are prevalent in the region. It is also striking that connections between the CEMAC countries and the rest of ECCAS barely exist. For example, Angola is connected with the Democratic Republic of Congo, Equatorial Guinea, and São Tomé and Príncipe with at least one daily flight. But Angola does not have any air transport connectivity with the rest of the CEMAC member countries. The Democratic Republic of Congo’s only connection with CEMAC is a single daily flight to Cameroon and three flights to Equatorial Guinea, and São Tomé and Príncipe’s connectivity with CEMAC is with Gabon.

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<!-- Start of picture text --> Average household utility level with subsidy compared to lump sum ccp<br>1 —— ES SS<br><!-- End of picture text --> <!-- Start of picture text --> 0.99<br><!-- End of picture text --> <!-- Start of picture text --> 0.98<br><!-- End of picture text --> <!-- Start of picture text --> 0.97<br><!-- End of picture text --> <!-- Start of picture text --> 0.96<br><!-- End of picture text --> <!-- Start of picture text --> 0.94<br>-100 -90 -80 -70 -60 -50 -40 -30 -20 -10 0 10 20 30 40 50 60 70<br>Subsidy rate %<br><!-- End of picture text -->
# I. **Introduction**

'The literature suggests that roughly<sup>half of cross-countrydifferencesin per capita</sup> income and growth are driven by<sup>differencesinTotalFactorProductivity,generally</sup> associated with technological<sup>progress.2Thisfact movestocenterstageanabiding</sup> question in economic development:<sup>whydodevelopingcountries,withgreatpotential</sup> gains from adopting technologies<sup>from theindustrialized countries,failto do so?Infact,</sup> perversely, the countries generating<sup>newtechnologiesat thefrontierappear to have faster</sup> TFP growth in manufacturing<sup>andagriculturethanthepoorcountrieswhocould,in</sup> theory, simply adopt.<sup>3</sup> However, recent work in innovation<sup>stressesthatadoptingexistingtechnologyis</sup> not without cost. Firms and countries need to<sup>developan"absorptive"or"national</sup> learning" capacity which, in<sup>turnarehypothesizedtobe functionsofspendingon</sup> research and development (R&D).<sup>4</sup> Though often considered relevant<sup>only forbasic</sup> science, Cohen and Levinthal (1991)<sup>amongothersstresslearning--knowingwherethe</sup> frontier is and figuring out what<sup>adaptationsarenecessary--asthe"secondface"of</sup> R&D. In fact, Pavitt (2001) argues<sup>that investmentin pure research is alsoimportant for</sup> developing countries. First, those<sup>most familiarwiththefrontiersof basic science will</sup> best train the applied problem solvers<sup>inthe privatesector.Second,evenbasicresearch</sup> does not flow easily or costlessly<sup>acrossborderssodevelopingcountries cannotsimply</sup> rely on what is being generated<sup>in theadvancedcountries.</sup> This paper investigates three outstanding<sup>issuesthatarecentraltounderstanding</sup> the links between innovation and<sup>development.We firstgenerate stylized patternsof the</sup> evolution of R&D spending over<sup>the courseof developmentemployinganewpaneldata</sup> set- constructed by Lederman and<sup>Saenz(2003).Theevidenceshowsthat R&Drises</sup> exponentially with the level of<sup>development measuredby GDP per capita.Provocatively,</sup> we also identify several striking<sup>outlierssuchas TaiwanandKorea inEast Asia,Finland</sup>

> **2** See Hall and Jones (1999), Dollar<sup>andWolf (1997).</sup>

> 3 Martin and Mitra (2001)

> _4At_ the firm level, see Cohen and<sup>Levinthal (1990), Forbesand Wield (2000), Griffith,Redding and Van</sup> Reenen (2003), Pavitt (2001) at<sup>the national level see,for example, Baumol, Nelsonand Wolf (1994).</sup>

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## **High-Skilled Migration from Myanmar: Responses to Signals of Political and Economic Stabilization**

Yashodhan Ghorpade, Muhammad Saad Imtiaz, and Theingie Han

**Abstract:** In recent years, Myanmar has witnessed considerable economic and political instability, leading many young people, particularly the higher-skilled, to consider migrating abroad for improved prospects. This paper employs an innovative method to quantify migration intentions among high-skilled youth by analyzing the take-up of migration at different wage premia. A randomized survey experiment then evaluates how hypothetical political and economic stabilization scenarios impact these intentions. The findings show that 35 percent of the respondents would be willing to take a similar job abroad for pay equal to their current income. Randomization within the survey indicates that political stabilization would potentially reduce high-skilled workers’ desire to migrate by about 15 percent, especially among men, those living in high-conflict areas, and persons with lower absolute income but higher perceived relative income. In contrast, prospects of economic stabilization do not have a significant effect on migration intentions. In the absence of political stability and a reduction in conflict, economic stabilization is unlikely to reduce talent outflows among the young.

# 1. Introduction

Emigration from Fragile and Conflict-Affected States (FCAS) is driven by political and security considerations in addition to the standard economic drivers of labor mobility. Economic theory postulates migration as an effective means for labor to realize higher returns arising from spatial differences in income earning opportunities. Classical models have described migration as an outcome of wage differences, which in turn is determined by wages, costs of migrating, and the probability of finding a job (Todaro, 1969; Harris and Todaro, 1970; Fields, 1975). The New Economics of Labour Migration posits three main motivations for economic migration: (i) relative deprivation, whereby poorer individuals migrate to increase household income; (ii) investment: as migration aims to enhance household investments through remittances directed towards agriculture or enterprises; and (iii) insurance, where migration serves as a means to safeguard against risks through the diversification of income sources (Stark, 1980; Stark and Bloom, 1985; Lucas and Stark, 1985). On the other hand, the literature on migration from FCAS has tended to focus on forced displacement aspects. Factors such as crime, conflict, violence, human rights violations, acute economic hardship, and climate and environmental factors have been identified as the main drivers of involuntary movements of people within and across borders ( <mark>Ibáñez</mark> 2014).

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namely Hausmann and Rodrik (2003), which is concerned about product innovation for exports in developing countries, where most product innovations are presumably not patentable as they entail the production of existing products that are nevertheless not yet produced in a country. To assess this hypothesis we use data on the accumulated number of patents granted by the U.S. patent agency to inventors residing in different countries.

# The Market Structure literature

One strand of the economics literature focused on industrial organization can be traced to the Schumpeterian idea of creative destruction, whereby innovation can be seen as both cause and consequence of competitive pressures characterized by Market Structure. The empirical literature linking firm innovation and market structure has assessed two issues, namely whether innovation rises with the size of the firm or with market concentration in terms of the market share of firms (Cohen and Levin 1989). This literature has produced only ambiguous results with various studies finding contradictory evidence.

An important theoretical contribution to this literature was Reinganum (1985). The main insight concerned an ambiguous relationship between the extent of market competition and innovation by incumbent firms. The threat of firm entry with new or higher quality products can affect incumbents’ incentives to invest in R&D or other investments associated with product innovation. In Reinganum’s model, every firm has a temporary monopoly over its product, which dissipates when a challenging firm introduces an improved version of that product. The theoretical model proposed by Aghion _et al._ (2005) builds on the types of models pioneered by Reinganum by allowing incumbent firms to innovate. Market competition through new entrants therefore can have different effects on incumbents’ decisions to innovate, depending on each firm’s assessment of the expected difference between profits before and after innovation. Laggard firms that are far from the technological frontier need to spend a lot of resources to move them towards that frontier, and therefore could choose to reduce their expenditures in innovation to reduce costs. In contrast, firms close to the frontier need to spend relatively little to keep them ahead of potential new entrants, and thus could increase their innovation efforts in the face of rising competition. These contradictory effects on firms that differ in terms of their technological capabilities yield the socalled inverted-U relationship between competition and innovation. We call these the Market Structure hypotheses, and we test them by examining the role of firm size and the regulatory environment that affects the costs and timing of firm entry.

4
_COTE D’IVOIRE: Growth, Specialization and the Terms of Trade_ West African Economic and Monetary Union. Figure A-8 shows a graph of annual per capita growth in real output for Cote d’Ivoire, as well as the arithmetic average for the western eight CFA countries which share the CFA franc. Table 6 provides the same information in greater detail, showing the per capita growth rates for each country.

Looking at the graph, we see that Cote d’Ivoire tracks the average of the eight western CFA countries, moving more or less in line with them all, but has lower growth on average than the group. The west CFA group responded to the December 1994 devaluation of the CFA with strong growth, which continued for a few years and then died out. Looking at Table A-5 reveals considerable variation.

**Table A-5: Per Capita Real Growth Rates in CFA West Zone Countries, 1993-2002**

||1993|1994|1995|1996|1997|1998|1999|2000|2001|2002|Averag|
|---|---|---|---|---|---|---|---|---|---|---|---|
|Benin|3.52|4.37|4.60|5.55|6.15|4.54|4.70|5.76|5.02|6.01|5.02|
|Mali|(2.14)|0.91|6.21|3.22|6.76|6.03|6.73|(3.35)|13.29|4.37|4.20|
|Burkina Faso|4.60|1.00|4.60|7.10|5.20|1.00|6.70|1.60|4.60|4.60|4.10|
|Senegal|(2.22)|2.87|5.17|5.14|5.04|5.74|5.00|5.58|5.57|1.10|3.90|
|Niger|1.45|4.00|2.61|3.42|2.75|10.42|(0.57)|(1.41)|7.10|2.98|3.28|
|Cote d'Ivoire|(0.19)|0.81|7.13|7.73|5.72|4.75|1.58|(2.47)|0.35|(1.82)|2.36|
|Togo|(15.10)|14.98|7.85|8.84|4.25|(2.10)|2.38|(1.91)|(0.21)|4.61|2.36|
|Guinea-Bissau|2.10|3.20|4.40|11.60|6.50|(28.10)|7.80|7.50|0.20|(7.20)|0.80|
|BCEAO Average|(1.00)|4.02|5.32|6.57|5.30|0.29|4.29|1.41|4.49|1.83|3.25|

Cote d’Ivoire is a relatively weak performer within this group, averaging 2.36% average annual growth per capita versus 3.25% for the group. Benin, Burkina Faso, Senegal, Mali and Niger all grew faster than the Cote d’Ivoire. Only Guinea-Bissau grew more slowly. The fact that Cote d’Ivoire posts slower growth than other nearby CFA countries suggests that the currency arrangements and exchange rate issues have not been the only causes of Cote d’Ivoire’s slow growth. Most other nearby countries with the same currency managed to grow faster in the last decade.

**African Countries in Conflict** :  Civil strife and war are prevalent in Sub-Saharan Africa, providing yet another benchmark for comparison.  Table A-6 provides real per capita GDP growth rates for eleven Sub Saharan countries, which experienced either civil war or war with a neighboring country during the 1992-2002 period.  These conflicts range in scale, intensity, duration and timing.

These results may be skewed by the inclusion of Liberia, which experienced strong growth in the mid 1990s as the country began to recover from it’s brutal civil war. Cote d’Ivoire performed below the average in this sample, ranking below the mid point, based on the ten-year average. Liberia, Ethiopia, Eritrea, Sudan, Rwanda and Angola all averaged faster growth over the decade. Cote d’Ivoire outperformed Congo (Brazzaville), Sierra Leone, Burundi and Congo (Kinshasa).

39
technologically (low R&D stocks). Consequently, from the viewpoint of technology diffusion and productivity growth, it would seem more advantageous for LAC countries to enter into North-South rather than South-South regional trade agreements as the former are likely to generate greater international flows of technological knowledge than the latter (Schiff and Wang, 2006).

# <u>Reference</u>

Abowd, John M., John Altiwanger, Julia Lane, Kevin McKinney and Kristin Sandusky. 2007. "Technology and the Demand for Skill: An Analysis of Within and Between Firm Differences." IZA Discussion Paper No. 2707 Barrow, Robert J. and Jong-Wha Lee. 2005. “International Data on Educational Attainment: Updates and Implications. CID Working Paper, Harvard University

> Coe, David T., and Elhanan Helpman. 1995. “International R&D Spillovers.” _European Economic Review_ 39 (5): 859-887.

______, _____ and Alexander W. Hoffmaister. 1997. “North-South R&D Spillovers”, _Economic Journal_ 107, 134-149.

> Grossman, M. Gene, and Elhanan Helpman. 1991. _Innovation and Growth in the Global Economy._ The MIT Press, Cambridge, MA: London.

GTAP. 2003. _Global Trade, Assistance, and Protection: The GTAP Data Base_ . Center for Global Trade Analysis. Purdue University.

Kaufmann, Daniel, A. Kraay and P. Zoido-Lobaton. 1999. “Aggregating Governance Indicators.” <u>World Bank Policy Research Working Paper</u> No. 2195. World Bank. Washington, DC. <u>www.worldbank.org/wbi/governance.</u> ________, ____ and <u>Massimo Mastruzzi. 2009. “Governance Matters: Aggregate and</u> Individual Governance Indicators, 1996-2008. <u>World Bank Policy Research Working Paper</u> No. 4978. World Bank. Washington, DC. www.worldbank.org/wbi/governance Lumenga-Neso, Olivier, Marcelo Olarreaga and Maurice Schiff. 2005. “On ‘Indirect’ Trade-Related Research and Development Spillovers.” _European Economic Review_ 49 (7): 1785–98.

Nicita, Alessandro and Marcelo Olarreaga. 2001. “Trade and Production, 1976-99.” <u>World Bank Policy Research Working Paper</u> No. 2701, World Bank. Washington, D.C. (November). <u>www.worldbank.org/research/trade</u> 18
# _5.4 Impact of the reform on tax compliance by previously registered firms_

In order to study the impact of the reform on tax compliance by previously registered firms, we use the basic RDD analysis around the GEL 30,000 threshold described in Equation 2. This analysis compares revenue declared in 2010, 2011, and 2012 to revenue declared in 2009 (as specified in Equations 3 through 5). If firms start declaring less revenue to continue being eligible for the micro firm tax regime, we should see a downward jump in declared revenue at the GEL 30,000 threshold in 2010, 2011, and 2012. As shown in Figures 17a – 17c, we observe a downward jump at the threshold in 2010, but not in 2011 and 2012.

**Figure 17a: Declared revenue around GEL 30,000 cutoff – 2010 (post-reform)**

# **Figure 17b: Declared revenue around GEL 30,000 cutoff – 2011 (post-reform)**

<!-- Start of picture text --> Local Avg. + Polynomial in GEL 100 Intervals from Cutoff Local Avg. + Polynomial in GEL 100 Intervals from Cutoff<br>10000 20000 30000 40000 50000 10000 20000 30000 40000 50000<br>2009 Declared Revenue 2009 Declared Revenue<br>Figure 17c: Declared revenue around GEL 30,000<br>cutoff – 2012 (post-reform)<br>Local Avg. + Polynomial in GEL 100 Intervals from Cutoff<br>10000 20000 30000 40000 50000<br>2009 Declared Revenue<br>80000<br>60000<br>50000<br>60000<br>40000<br>2010 Declared Revenue 2011 Declared Revenue 40000<br>30000<br>20000<br>20000<br>100000<br>80000<br>60000<br>2012 Declared Revenue<br>40000<br>20000<br><!-- End of picture text --> The RDD regressions in Table 11 estimate Equations 3 through 5 to measure the size of the jump at the GEL 30,000 threshold in 2010, 2011, and 2012. In line with Figures 17b and 17c, the shaded rows in Panel B and Panel C show no statistically significant jump in declared revenue in 2011 and 2012 at the 29
groups comprising the landless, marginal landholders (less than 5 bighas), smallholders (between 5 and 15 bighas) and “large” landholders (more than 15 bighas).<sup>xix</sup> In this case, however, the ELMO statistic barely reaches 5%. This kind of analysis based on alternative group definitions can be refined further, but the initial impression is that caste is proxying a dimension of disadvantage that is distinct from education or asset levels (although probably not entirely unrelated). Indeed, the detailed fieldwork underpinning the Palanpur study does point to factors such as networks of contacts as important determinants of economic opportunity, and these networks are often linked to caste but not necessarily human capital or wealth (Lanjouw and Stern, 1998).

# **5.  Sugao: A Contrasting Western Indian Example**

Economic development in the village of “Sugao,” in Satara district Maharashtra, has not followed the same pattern as Palanpur (Dandekar, 1986). Sugao is located about 240 kms South-east of Mumbai, and 42 km from Satara town. Since the turn of 20<sup>th</sup> century, men from Sugao have provided a steady stream of labor for the textile mills of Mumbai and mill work was in this period a significant source of income for Sugao households. (With the decline of the mill industry in Mumbai in the 1980s and 90s it is unclear to what extent this is still the case). Professor VM Dandekar and his team at the Gokhale Institute of Politics and Economics in Pune conducted a socio-economic census of Sugao in 1942 which was repeated in 1958. Hemalata Dandekar, then a PhD student at UCLA, conducted another census of the village in 1977. There are thus over three decades of data on the village over, roughly, the same span as the Palanpur study.

Sugao’s population in that period expanded by 60 percent, from 1621 individuals in 1942 to 2578 individuals in 1977. The majority of people in Sugao are Marathas – who are 22
||components: the risk to operations, taxation, repatriation, and labor costs.|Country Risk Guide|
|---|---|---|
|Stick to Announced<br>Policies|“Do you expect the government to stick to announced major policies?”|World Bank: World Development<br>Report 1997<br>Q3|
|Efficiency of Public<br>Service Delivery|“How would you generally rate the efficiency of government in delivering services?”|World Bank: World Development<br>Report 1997<br>Q25|
|Protestantism|Ratio of protestant population in the country|La Porta et. al. (1998)|
|Colonial Past|Dummy variable which is equal to one if the country has a colonial past in the last two<br>centuries and zero otherwise|CIA World Fact, La Porta et.al (1998),<br>and Encyclopedia Britannica and the<br>World Handbook of Political and Social<br>Indicators|
|Decentralization|Ratio of employment in non-central government administration to general civilian<br>government employment. Non-central government administration encompasses all<br>government administration employees who are not specifically funded by the central<br>government. It includes municipalities, as also regional, provincial or state employment.|Schiavo-Campo et.al (1997)|
|Federal Structure|Sub-national elections in state or province level|IMF Government Finance Statictics1998|
|**Other**|||
|Ehnolinguistic<br>Heterogeneity|The probability that two randomly selected individuals in a country will belong to different<br>ethnolinguistic groups|La Porta et. al. (1998)|
|Wage/GDP|Average government wages to per capita GDP|Schiavo-Campo et.al (1997)|
|Social Development|Human Development Index of the United Nations. The index as crafted by UNDP includes<br>measures of mortality, education and economic activity.|United Nations Human Development<br>Report 1998|

33