rafmacalaba/datause-encoder-data huggingface dataset:
One would expect similar findings for other South Asian migrants, as the lack of access to credit is an important constraint to entrepreneurship in the region (Bossavie, Gorlach, et al. 2022). In addition, spending several years abroad in lower skilled occupations may reduce access to wage employment for return migrants, reducing the opportunity cost of entrepreneurial activities.

We first examine the choice of employment type by return migrants and nonmigrants descriptively, unconditional on workers’ characteristics (Table 2). In Bangladesh and Pakistan, the incidence of self-employment, particularly of non-farm self-employment, is significantly higher among return migrants than nonmigrants. The difference between the two groups is statistically significant in both countries. In Nepal, however, there is no statistical difference in the unconditional likelihood of being self-employed among return migrants. This may indicate that migrants from Nepal do not benefit as much from their migration experience compared to workers from Bangladesh or Pakistan, or that starting up self-employment after return is not a driver of temporary migration as it is in Bangladesh and Pakistan.

We then estimate a pooled multinomial logit occupational choice model to assess whether the highest propensity to become self-employed among return migrants is robust to controlling for workers’ observable characteristics, such as age or educational attainment. As shown in Table 7, being a returnee remains significantly associated with non-farm self-employment in Bangladesh and Pakistan, and the association is especially large in Bangladesh. In addition, in all three countries, age significantly increases the likelihood of being self-employed in the non-farm sector, which likely reflects the need to accumulate sufficient assets over the life cycle to start up a business.

In addition to being more likely to be self-employed, return migrants are also more likely to hire paid employees in Bangladesh and Pakistan (to be an employer), as opposed to being own account workers without any employees (Table 2). The difference in the share of workers who are entrepreneurs among return migrants and nonmigrants is quite large and statistically significant in Bangladesh and Pakistan. The association between return migrant status and entrepreneurship is robust to controlling for observable characteristics in a multinomial logit regression setting (Table 8). Self-employed individuals hiring paid employees in developing economies have been categorized as ”successful” entrepreneurs by the literature (Piracha and Vadean 2010; Gindling and Newhouse 2014). This suggests that return migrants also contribute to job creation in the home economy, in addition to being able to start their own account enterprise.

In all three countries, higher levels of education are associated with an increased probability of being in non-farm self-employment, except at the tertiary level. This finding is consistent with the work by Ilahi (1999) using earlier data on return migrants from Pak15
<mark>the employment contraction. In the Philippines and South Africa, on the other hand, poverty increases using employment elasticities range between 40% and 70% of the increases obtained</mark> using 2020 employment levels.

# **Figure 9. Poverty, vulnerable population, and middle-class projected changes between 2019** **<mark>and 2020 using different employment data. In percentage points</mark>**

<!-- Start of picture text --> 6.0<br>4.0<br>2.0<br>0.0<br>-2.0<br>-4.0<br>-6.0<br>Actual data Elasticities Actual data Elasticities Actual data Elasticities Actual data Elasticities<br>Turkey Philippines South Africa Brazil<br>US$ 2.25/day US$ 3.65/day US$ 6.85/day Vulnerable Middle class<br><!-- End of picture text --> Notes: Vulnerable defined as a household per capita income between 6.85 and 13 USD a day (2017 PPP). Middle class defined as a household per capita income between 13 and 70 USD a day (2017 PPP). Table A5 in the Appendix present the values of the estimated rates when using employment elasticities.

<mark>These results highlight the importance of using accurate employment data to simulate the distributional impacts of a shock.</mark>

# **<mark>4.2 Validation in Brazil</mark>**

The availability of 2020 household survey data for Brazil allows us to test how close our previous simulations are from the observed poverty rates during 2020. Using data from the PNAD-C collected during 2020, we present a validation exercise where we compare our projections of the average changes in income between 2019 and 2020 by quintiles of the initial per capita household income with the observed values according to the PNAD-C. We present two calculations: the first one excludes the Auxilio Emergencial transfer program (because our macro-micro simulation methodology does not consider government transfers), and the other one includes this program as part of household income.

23
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43
Trujillo, L. and Nombela, G. - _Privatization and regulation of the seaport industry_ ports _(Administraci6n General Portuaria, AGP),_ and the transfer of ports to regional governments. Small ports were transferred to municipal governments, while the large port of Buenos Aires was split into three separate zones: _Dock Sud,_ transferred to the province of Buenos Aires; _Puerto Sur,_ which is still to be developed; and _Puerto Nuevo,_ which remains in the hands of the central state.

Other characteristics of the reform process were the deregulation of all port services, including those related to berthing such as pilotage and towage, and the elimination of restrictive working practices. Most importantly, the reform has introduced significant private participation in building and operating port infrastructure. Given its special role within the maritime transport industry, special attention has been devoted to the development of container terminals, and the reform has attained large improvements in terms of the volume of traffic and productivity.

The port of Buenos Aires has been one of the more innovative world experiences in port reform. The State part of the infrastructure _(Puerto Nuevo)_ was split into six terminals and concessioned for periods between 18-25 years. Initially, the proposed structure was to have _5_ different operators, since terminals 1 and 2 were included in a single concession. As was mentioned above, the selection process was designed to avoid the concentration of terminals in the hands of a single operator, by forcing bidders to win at most only one terminal each.

In 1998, market conditions have changed the situation, and there are only two terminals competing in the container market (terminals 1-2 vs. 5) within _Puerto Nuevo._ Terminal 4 is relatively small and dedicated to general cargo, while terminal 3 is multi-purpose (general cargo, cars and passengers). Lastly, terminal 6 was forced to close down. Even though the reduction in the number of operators indicates that the process could have been better designed and was probably implemented too fast, its results in terms of port outcomes have been extremely positive, as can be observed in _Box 11._ For example, between 1991 and 1997, the volume of TEUS increased by 241%, and the productivity per worker has almost been multiplied by four.

**_Box 11._ Port of Buenos Aires indicators**

|**Indicator**|**1991**|**1997**|
|---|---|---|
|Cargo (thousand ton)|4.000|8.500|
|Containers (thousand TEUS)|300|1.023|
|Capacity (thousand containers per year)|400|1.300|
|Cranes|3|13|
|Operations area (ha)|_65_|132|
|Productivity (ton per employee, annual)|800|3.100|
|Average container time at port (days)|2,5|1,3|
|Charges per container ($/TEU)|450|120|

_Source:_ Estache, Carbajo y De Rus (1998) _35_
# **Location of business operation and value of assets**

It seems that business owners who are renting their business premises are more likely to consider tax formalization (See Figure 10)<sup>10</sup> . They may be at highest risk from their landlords declaring their rental income and thereby being discovered by SARS. Landlords may also want to see tax clearance certificates as part of their credit clearance. The value of assets does not seem to significantly influence the likelihood for registering for tax (t-test does not result in a statistically significant difference), and as Figure 11 suggests, it seems to be the lowest among businesses with the lowest value of assets.<sup>11</sup>

**Figure 10: Location of business operation and likelihood for tax registration**

**Figure 11: Value of assets and likelihood for tax registration**

<!-- Start of picture text --> Place of business 59 More than 200K Rand 64<br>changes<br>71K - 200K Rand 67<br>Separate premises - 74<br>rented<br>31K - 70K Rand 68<br>Separate premises - 65<br>ow ned<br>11K - 30K Rand 72<br>Same premises 62<br>w here you live 10K Rand or less 55<br>Total 66 Total 66<br>50 55 60 65 70 75 80 50 55 60 65 70 75<br>Percentage of informal businesses likely to register Percentage of informal businesses likely to register<br>Value of assets<br>Place of business operation<br><!-- End of picture text -->

# **Customers’ method of payment**

As expected, the survey data supports the supposition that cash payments from customers have a negative influence on likelihood for tax registration. Businesses reporting using only cash payments tend to report that they are likely to register less frequently than those paid with other methods<sup>12</sup> .

**Figure 12: Payment method and likelihood for tax registration**

<!-- Start of picture text --> At least some 72<br>account<br> Cash only 64<br>Total 66<br>50 55 60 65 70 75<br>Percentage of informal businesses likely to register<br>Customers paying method<br><!-- End of picture text --> 10 Chi square = 12.999, significant on 1% level 11 Only visual inspection of the figure suggests this assessment. Statistical tests do not demonstrate statistical significance.

12 Chi square = 5.414, significant on 5% level 10
18 Anne 1.1 _Average Diferences Between Domestic and Border Prices for Diesel In Selected Countries. Subsidy (-), Tax (+)_ <!-- Start of picture text --> 200.00 -<br>150.00 D<br>-50.00<br>-100.00*<br><!-- End of picture text --> _Avage Differenes Between Domestic and Border Prcesjfr Gasoline In Selected Couwnes, Subsidy_ **_(-),_** _Tax (+)_ <!-- Start of picture text --> 350.00-<br>300.00 -<br>250.00-<br>200.00-<br>-50.00<br>0 * *90 Ca<br>jE1980-84 0 1985-8<br><!-- End of picture text -->
# **1 INTRODUCTION**

The body of knowledge in the field of export survival analysis is growing with the development of new concepts that explain and capture the dynamics of the process, but also with the slowly increasing availability of relevant data. This paper contributes to the latter by bringing to light previously unreleased customs transactions data from the Lao PDR. These data lend themselves rather well to survival analysis of the kind carried out in only a few countries so far, but also form an interesting window into the composition of, and the mechanisms behind, exporter behavior in a small developing country such as Laos. The paper borrows from the export survival analysis methodology in work by Cadot, Iacovone, Rauch and Pierola (2010), which investigates survival mechanisms among the exporter populations of Malawi, Mali, Senegal and Tanzania using very similar data sets, and which additionally serves as a rare and valuable reference for comparisons.

Ever since the seminal work of Besedes and Prusa (2006), it has been known that new exporting spells in developing countries tend to be short-lived, with high “death” rates: several other studies have confirmed that the median duration of export spells is very short, typically two to three years (Obashi 2010). Efforts by others using both panel and customs data (Nitsch 2009, Alvarez 2008) have revealed that such spells play a critical role in the process of export growth, showing that besides volume growth (intensive margin) and diversification (extensive margin), there is also a fundamentally important “sustainability margin”, carved out of the intensive margin, which focuses on the extent to which new products and destination flows survive in later periods.

**Figure 1:** Three channels of export growth – the intensive, extensive and sustainability margins

<!-- Start of picture text --> Intensive margin: Higher volumes of existing products and destinations<br>New products<br>Export growth Extensive margin:<br>New destinations<br>Sustainability margin: Survival of new products and destinations<br><!-- End of picture text --> Given that traditional export promotion policy has tended to focus primarily on the extensive margin (i.e. helping would-be exporters find new markets and develop export-ready products), this literature suggests that such efforts may not yield significant results if flows of new products and destinations are not surviving in sufficient numbers. Thus, such information can be very helpful in the search for robust and policy-related determinants of export growth, in particular related to this third margin: survival and sustainability. Firm-level data, even if harder to obtain (Gorg 2008), has produced more detailed findings that complement the macro-level results, based on aggregated data, by identifying ways in which export-promotion agencies can overcome market failures and leverage synergies between national exporters in order to achieve a brand name for the country (Molina 2009). For example, Volpe and Carballo (2008) study the _Exporting from a small landlocked economy_ _2_
Differences in access to physical and reputational collateral for men and women are not accidental. They have to be understood in the context of the legal regulations and customary norms that shape the relationship between men and women and their relative access to resources. In this context, contract and property rights are of particular importance. These rights are often restricted for women and in turn affect the ability of lenders to collateralize assets and seize them in the case of default. In particular, women may not be deemed creditworthy because they do not possess the title to their land or house. Weak property rights or titles may be due to differential treatment under the law. Certain customs may also constrain women to enter contracts in their own name, control property, or receive an equal share of assets on divorce or in inheritance (Goheer, 2003; ILO/AfDB, 2004; GEM/IFC, 2005; Ellis et al., 2007b; Morrison, Raju and Sinha, 2007; Demirguc-Kunt, Beck and Honohan, 2008).

Differential treatment either under the law or customs extends beyond property rights. Other cultural norms that directly affect access to finance include requirements in many Middle Eastern and South Asian countries to have a husband or male family member co-sign a loan (Chamlou, 2008; Safavian, 2012). Laws might require married women to obtain their husband’s signature and approval for all banking transactions. Husbands’ adverse credit histories may also affect women as they might need to repay debt or could be denied future credit (Blanchard, Zhao, and Yinger 2005; Naidoo and Hilton 2006).<sup>4</sup> Women may also find it more challenging to obtain national identification documents (often required for opening an account). Overall, restrictions on mobility or interactions outside the home and across gender lines may limit women’s’ access to finance (IFC, 2011).

> 4 Although men may also have to repay their wife’s debt under the same circumstances, it is more likely that the husband has incurred previous debts.

7
8 The emphasis on FFS coupled with the distorted price schedule has resulted in providers generating demand for expensive care. Simple and non-invasive care tends to be under-provided, leading to concerns about low—and in some cases—falling coverage of key public health interventions, while high-tech diagnostics are over-provided. This is reflected in the rapid adoption of new technology in China’s health sector and the recent rapid growth of hospital revenue per patient episode. It is the latter rather than rising utilization that largely accounts for the rapid growth of health spending in China, which has averaged 12% per annum in real terms during the 1990s (Fig 1). Because of the markup pricing scheme that has long been in force, drugs are also profitable—hence their over-prescription. China’s high average length-of-stay (LOS) is another example of incentives at work—because hospitals that are paid of a FFS basis can claim reimbursement for the additional day, they have an incentive to keep patients in hospital.

**_Figure 1: Inpatient revenues have been rising largely because of rising costs of care_**<sup>**_*_**</sup>

<!-- Start of picture text --> 20%<br>15%<br>Hospital<br>10% revenue per<br>inpatient<br>5% No. inpatients<br>0%<br>Hospital<br>-5% inpatient<br>revenues<br>-10%<br>% change p.a. in real terms<br>1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001<br><!-- End of picture text -->

> * Source:  China National Health Economics Institute _China National Health Accounts Digest_ , 2002.  Data refer to large hospitals only.
|**Tabl**|**e 2: Robustness f**|**or other controls**|||
|---|---|---|---|---|
|Dependent variable:_Female_<br>_Workers_|**(1)**|**(2)**|**(3)**|**(4)**|
|Exports (%, cell average)|0.189***|0.154**|0.138**|0.149**|
||(0.059)|(0.063)|(0.066)|(0.068)|
|No. of Workers (logs)|0.959***|1.182***|0.812**|0.917**|
||(0.344)|(0.392)|(0.411)|(0.415)|
|Herfindahl-Hirschman Index|-1.344|-12.534**|-11.431**|-7.554|
||(3.792)|(5.142)|(5.708)|(5.838)|
|Age of Firm (logs)|-1.518***|-1.367***|-1.421***|-1.513***|
||(0.477)|(0.507)|(0.515)|(0.519)|
|Foreign Ownership (proportion)|-0.458|0.720|0.750|0.731|
||(1.163)|(1.443)|(1.475)|(1.484)|
|Female Ownership Y:1 N:0|6.504***|3.947***|3.876***|4.020***|
||(0.740)|(0.766)|(0.790)|(0.799)|
|Skills Obstacle (0-4)|0.791***|0.832***|0.827**|0.795**|
||(0.301)|(0.311)|(0.322)|(0.332)|
|How Much Of An Obstacle:|-0.028|0.005|0.009|0.030|
|Transport?|||||
||(0.232)|(0.268)|(0.272)|(0.278)|
|Firm Purchased Fixed Assets Y:1|-0.580|-0.745|-0.718|-0.928|
|N:0|||||
||(0.600)|(0.620)|(0.635)|(0.637)|
|Power Outages (days)|-0.129*|-0.066|-0.065|-0.049|
||(0.074)|(0.085)|(0.086)|(0.087)|
|Courts Obstacle (cell average)|-0.299|-0.395|-0.339|-0.314|
||(0.900)|(0.950)|(0.974)|(1.066)|
|Crime Losses Y:1 N:0|-1.179|-2.207**|-2.301**|-1.995**|
||(0.813)|(0.925)|(0.931)|(0.955)|
|Firm Inspected Y:1 N:0|-0.814|-0.859|-0.734|-0.552|
||(0.659)|(0.693)|(0.703)|(0.711)|
|How Much Of An Obstacle: Tax|-0.279|-0.305|-0.297|-0.314|
|Rates|||||
||(0.257)|(0.263)|(0.271)|(0.280)|
|How Much Of An Obstacle: Labor|0.080|0.061|0.009|0.089|
|Regulations?|||||
||(0.333)|(0.358)|(0.366)|(0.371)|
|GDP per capita (logs)|1.201|3.400|5.696|7.525|
||(6.818)|(8.539)|(8.715)|(10.362)|
|Population (logs)|-42.358***|3.824|5.107|3.793|
||(12.527)|(23.050)|(23.512)|(30.625)|

41
16. Supportive findings were produced from largely duplicated regression runs using data drawn from the 1983 Israel Census of Population, a source that was as yet unavailable at the time the original research reported in Neuman and Ziderman was undertaken. Thus, on the basis of a much more comprehensive data set (with 7703 and 2491 observations in the primary and secondary sectors, respectively), but lacking the important PRESWK variable, these regressions offered further support for the existence of dual labor markets in Israel. The human capital variables performed as predicted in each of the sectors, including those testing the cross-productivity effects of wife's education. These regression results based on the Census of Population are available from the authors, on request.

17. This section owes much to the helpful suggestions of an anonymous referee.

18. James J. Heckman, "The Common Structure of Models of Truncation, Sample Selection and Limited Dependent Variables and a Simple Estimator for Such Models", Annals of Economic and Social Measurement, (5, 1976), and James J. Heckman, "Sample Selection Bias as a Specification Error", Econometrica (47, 1979). For an application of this approach to dual labor markets, see James J. Heckman and Joseph V. Hotz, "The Sources of Inequality in Panama's Labor Market", Journal of Human Resources, (21, 1986).

19. These results are obtainable from the authors, on request.

20. We also tried adding the selectivity correction factor lambda to this 2SLS regression. Again, lambda was insignificant in both sectors.

15
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