rafmacalaba/datause-encoder-data huggingface dataset:
reasons for going into business, on whether or not the business operates out of the home, and on whether or not their friends and family consider the owner an organized person. None of these characteristics are significant when interacted with the treatment effect, and the female interaction stays large, negative, and significant. We thus conclude that differences in entrepreneurial ability, however measured, do not explain the low returns to females.

# _5.5. Differences in Risk Aversion_

We measure risk aversion as the implied coefficient of relative risk aversion obtained by playing lottery games for real money with the firm owners (see de Mel, McKenzie, and Woodruff 2008a for details). Although there is a common presumption that women are more risk averse than men in many countries, we find that Sri Lankan female microenterprise owners are more likely to take risky gambles in these lottery games than male owners (Table 6). Since theory would predict that returns are higher for more risk averse individuals if missing insurance markets cause them to underinvest, the results of these lottery games suggest that differences in risk aversion will not explain the low returns for females. Indeed, we see this in column 8 of Table 7, where controlling for the interaction with risk aversion does not change the female interaction. This result is also robust to an alternative measure of risk aversion. We also followed the German Socioeconomic Panel in asking firm owners about the overall willingness to take risks in life, on a 10 point scale. This variable has a coefficient of -0.28 (s.e. 0.88) when interacted with the treatment amount, and the female interaction with treatment amount is -8.84 (s.e. 4.26), which is not significantly different from the baseline model. Thus differences in risk aversion do not explain the low returns to females.

# _5.6. Differences in Industry and Ability to Expand the Business_

The large differences in treatment effects by gender do not appear to be explained by differences in access to capital, differences in ability, differences in risk aversion or differences in other entrepreneurial attitudes. The remaining potential reason for differences in returns according to our theoretical model is that there are differences in production technologies across gender.

23

-  -
8 increased menstruel bleeding (and therefore iron-deficiency anemia) and occasionally perforate the uterus. Unintin'ded pregnnncies with an IUD in place are more likely to result ia miscarriage and septic abortion. Removal of the IUD when pregnancy occurs reduces tha risk of septic aboxclon (Population Reports, 1984).

# Barrier Methods

Condoms, spermicides and diaphragms generally are without serious health risk to the user. These methods provide protection against sexually tratismitted diseases, pelvic inflammatory disease and cervical cancer. They occasionally cause minor local irritation. Otherwise, the main hea'lth risks are those of pregnancy, since these methods have a higher failure rate than oral contraceptives or the IUD.

# Natural Family Planning

The chief benefit of periodic abstinence (the 'rhythm method") r. - be as a )ol for sex education. A few couples can, with extensive tre g, use this method successfully. But for the majority, the failure raL. is unacceptably high. It represents a useful alternative for couples with side effects or religious objections to other methods. However, the low acceptance and high trairing costs make it expensive.

## SterilizaLiogn

Severe or long-lasting complications of male sterilization (vasectomy) are quite rare, and mortality occurs very rarely and only with poor surgical technique (Grimes, 1982). Female sterilization (tubal ligation) also has a very low risk of severe complications or death, and is far safer than childbearing, especially for older women and/or those of high parity, or those with other risk factors which make pregnancy especially dangerous. Sterilization is a highly appropriate method for couples who want no more children, or in those cases where the woman's health status makes another pregnancy life-threatening. As with decisions about other major life events, a small but significant proportion of women will become dissatisfied with their decision to use this method. The likelihood of dissatisfaction increases when the woman is unduly influenced by others or makes the decision at a very young age.

# Induced Abortion

Abortion, especially carried out by well trained personnel in the first trimester by the suction method, is far safer than childbearing, and carries a relatively low risk of serious morbidity and mortality (Tietze, 1983; Rochat, 1986). Crudely induced abortion is an extremely dai.gerous method of fertility control, especially after the first trimester.

# Conclusion

Overall, fertilitv control cai. Aignificantly improve the health of women, especially poor women in developing countries, where pregnancy complications often account for more than one quarter of all deaths to women in the reproductive age group. Although many contraceptive methods have the potential to impair the health of women, and several (oral contraceptives, the IUD, sterilization) can result in fatal complications, most are also associated with substantial non-contraceptive health benefits. Except in
pensioners have chosen variable rate annuities. Annual pension amounts are still very small, however, due to the very short coverage time and the gradual transition rules.

In its first year of operation, in 2000, there were 4.4 million participants in the PPM scheme. By the end of 2007 the number had increased to 5.8 million (Table 1). When the scheme reaches maturity, some 8-9 million participants are projected to be covered by the scheme, given present net immigration patterns. Note that individuals retain their balances even after emigrating from the country. At end 2007 there were about 450,000 pensioners in the PPM plan, about a quarter of all pensioners.

The annual flow of new funds into the system has been about one percent of GDP. The overall portfolio’s market value fell considerably below its purchase value with the dot.com equity crash in 2001-2002 and did not fully recover until 2005, as Table 1 shows. At end 2007, total assets equaled 308 billion SEK – equivalent to about 10 percent of GDP. The average nominal rate of return from 1995 through 2007 was 5.8 percent (with a rate of inflation of around 2 percent), according to the PPM’s Annual Report for 2007. Recall that, until the autumn of 2000 money was invested in government bonds, awaiting the first portfolio choice. This together with the dot.com crash shortly after fund choices were made has undoubtedly held down the average return.

When the first individual portfolio choices were made in 2000, about two thirds of all participants chose funds actively. They chose about 3.4 funds per person. The number of funds held per person has remained slightly above 3 since then. Persons with previous investment experience, higher income and higher education were more inclined to choose, whereas the youngest participants were the most inclined to passively let their money go to the default option (Engström and Westerberg (2003)). About 90 % of all PPM funds were originally invested in equities. The percentage has fluctuated since then, dropping as low as 70 percent with the dot.com decline in equity prices in the early 2000s.

**Table 1.  Number of participants and assets in the PPM scheme**

|Year|New entrants|Number of<br>participants|Total assets on<br>As percent|December 31.<br>age ofGDP|
|---|---|---|---|---|
||||Purchase value|Market value|
|2000|4 400 000|4 400 000|2.5|2.3|
|2001|493 000|4 900 000|3.2|2.8|
|2002|196 000|5 100 000|4.0|2.5|
|2003|150 000|5 200 000|4.7|3.8|
|2004|129 000|5 300 000|5.3|4.9|
|2005|117 000|5 410 000|6.1|7.2|
|2006|114 000|5 570 000|7.4|9.4|
|2007|133 000|5 840 000|8.5|10.0|
|Source.|The PPM||||

The number of active choosers among new entrants has steadily declined since 2000 and in 2007 it reached a new low of only 2 percent, following a change in the information procedures of the PPM. The fact that most new PPM participants do not choose funds actively has drawn considerable attention both in Sweden and internationally. Upon closer reflection, however, this is not so surprising since many new entrants are in their teens and early twenties, often students or others with intermittent earnings. In fact, these days, Swedes reach 12
# <u>Dynamics of price for horticulture crop</u>

<!-- Start of picture text --> Banjarmasin Lampung Makassar Mataram<br>914.185<br>314.185<br>Menado Semarang Surabaya<br>914.185<br>314.185<br>mydate<br>Graphs by prov<br>2004m12005m12006m12007m12008m12009m12010m1<br>2004m12005m12006m12007m12008m12009m12010m1 2004m12005m12006m12007m12008m12009m12010m1 2004m12005m12006m12007m12008m12009m12010m1<br>hort<br><!-- End of picture text --> (Source) Bulog, BPS Figure 2: Prices of rice, maize, cassava, estate crop, and horticulture crop in Indonesia 38
Table 1 shows the results of regressing GVA on electricity consumption and nighttime light intensity. Columns 1 and 2 show that electricity consumption and GVA move together closely both in levels and as deviations around a trend. In both cases the relationship is statistically significant at the one percent level. For each percentage point increase in electricity consumption, GVA grew 1.3 percentage points. This relationship is very similar to the one-to-one relationship Cicala (2020a) finds for the United States, including during the global financial crisis, and even closer to the elasticity of 1.4 that Chen et al. (2020) find in Europe.<sup>13</sup> Columns 3 and 4 replicate the regressions for nighttime light, showing that it also follows the evolution of GVA very closely.<sup>14</sup> However, GVA shares more of its variation with electricity consumption than with nighttime light intensity, as reflected in a lower R2 of the latter regression. This could be due to larger measurement errors in nighttime lights compared to electricity consumption. Since both move together with economic activity, they are related. Consequently, nighttime light turns out not to be significant when we include both electricity and light in the same regression (column 5). In columns 6 and 7, we demean the data by regressing GVA, electricity consumption and nighttime lights on year and quarter fixed effects. We then regress the residuals of GVA on the residuals of electricity and lights. This allows us to understand the relationships between the quarterly fluctuations of GVP, electricity and lights. Columns 6 and 7 confirm that both electricity and lights are able to track quarterly fluctuations, with both coefficients turning out to be significant at the one percent level. Finally, we regress electricity on lights to examine how strongly they are correlated in India. Columns 8 and 9 show a strong relationship both in levels and around a common trend. A 1 percent increase in light intensity is associated with a 1.2 percent increase in electricity consumption.

Electricity consumption seems to have a somewhat stronger relationship, especially when both variables are combined. We therefore rely on electricity consumption to track economic activity at the country and state level, for which electricity data is available, and rely on nighttime light intensity for districts and cities.

> 13It is also in line with other estimates in the literature (Stern 2018).

> 14With 1.5, our coefficient is much larger than the one Henderson et al. (2012) find in an annual panel regression using the DMSP-OLS data (their Table 2, column 1). One reason could be that VIIRS data allows for greater comparability over time as explained in section 3.2.

10
ity growth. Using US Bureau of Labor Statistics data from 1992-2000, they ...nd that service o¤shoring has a signi...cant positive e¤ect on labor productivity growth, accounting for approximately 10 percent of average growth in this factor. While material o¤shoring also has a positive e¤ect, it is smaller in magnitude— accounting for 5 percent of average growth in labor productivity— and not signi...cant across all speci...cations. They conclude that service o¤shoring does have a positive impact on labor productivity growth in the US and speculate that the smaller and less signi...cant values for material o¤shoring may be due to possible decreasing returns from scale and over time from this sector.

Liu and Tre‡er (2008) analyze the impact of not only o¤shoring but also inshoring— the sale of service produced in the US to una¢ liated buyers in China and India— across several indicators: workers’change of occupation and industry; weeks spent unemployed as a share of total weeks in the labor force; and earnings. They ...nd that the total net e¤ect of inshoring and o¤shoring is positive. However, for those workers in industries exposed to o¤shoring and those workers who are less educated the e¤ect is either less positive or negative.

A di¤erent approach is explored by Ebenstein, Harrison, McMillan, and Phillips (2009), who focus on the e¤ects of trade across di¤erent types of task, as measured by the routineness of di¤erent occupations. Typically, highly routine occupations are associated with workers who have lower educational attainment, while less routine occupations are associated with higher skills and educational attainment.

Why should routineness matter? Grossman and Rossi-Hansberg (2008) posit that improvements in technology make o¤shoring less costly. Cost reductions are much more likely for routine tasks, which are more easily codi...ed and can be communicated and consequently transferred to overseas a¢ liates. Ebenstein et al test this hypothesis by assessing the empirical relationship between the routine nature of a task and o¤shoring. Their measure of routine is based on Autor, Levy, and Murnane (2003) who describe routine jobs as “tasks that can be expressed using procedural or ‘rules-based’logic, that is codi...ed in a fully speci...ed sequence 36
# **Figure 1  Results‐based Chain ‐ Application in Education**

**Program objectives                   Inputs Intermediate Inputs** Improve quantity, Educational spending by Enrollments, student‐quality, and access teacher ratio, class size to education Age, sex, urban/rural; services spending by level; teachers, staff, facilities, tools, books

|**Outputs**|**Outcomes**|**Impact**|**Reach**|
|---|---|---|---|
|Achievement<br>scores,<br>graduation<br>rates, drop- out<br>rates|Literacy rates,<br>supply of skilled<br>professionals|Informed<br>citizenry, civic<br>engagement,<br>enhanced<br>international<br>competitiveness|Winners and<br>losers from<br>government<br>programs|

Source: Shah, 2005.

32
**Figure 15: Small Island States Internal Air Market**

<!-- Start of picture text --> a. Overall traffic within the islands b. LIAT’s seat capacities & frequencies, direct flights<br>1,600 3,000 60,000<br>1,400<br> 2,500 50,000<br>1,200<br> 2,000 40,000<br>1,000<br> 1,500 30,000<br>800<br>600 1,000 20,000<br>400 500 10,000<br>200<br> - -<br>0<br>Seats Flights<br>Flights<br>Estimated Seats, thousands<br>Estimated Seats, thousands<br>2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012<br><!-- End of picture text --> _Source: Authors’ calculations based on data from Diio (2014)._ _Note: In figure (a) Traffic with Barbados and Trinidad is included, since they both act as hubs. However, since neither countries are not part of the small island states group, traffic among them are excluded, i.e. only traffic between them and the OECS is measured._ First, there has been a consolidation in capacity: LIAT competed with Caribbean Star at first, but in the end took over the airline. In 2007, the combined capacity of the two airlines exceeded 3.6 million seats. In 2012, after the consolidation and with Caribbean Star no longer operating, LIAT showed 2.2 million seats.

Second, after having peaked in 2008, both the frequencies (number of flights) and LIAT’s related seat capacity have gone down sharply. The curves follow each other tightly because the fleet has consisted of generally identical aircraft with identical seat configurations in recent years.

Finally, anecdotally, LIAT faces operational challenges that include schedule integrity and luggage delivery issues related to (a) the complications of servicing and operating an aging fleet in a geography consisting solely of islands, and (b) operational inefficiency in the basic hub system. With respect to the latter, significant delays can be encountered in flying or luggage delivery due to the security screening of transit passengers and suitcases. In addition, as mentioned earlier, LIAT cannot currently interline with larger airlines bringing tourists into the region, hindering LIAT’s efforts to become an effective distribution system for arriving tourists. LIAT is reportedly addressing the fleet issue by planning to purchase new ATR 72 aircraft from Europe, and is also looking at investing in interlining capabilities.

The latter point is extremely important for the development of the islands’ internal connectivity. Ultimately, however, the air transport markets are very intertwined with the tourism and hotel industry, which see air transport as a vital pipeline for arrivals. It is widely accepted that the hotel industry sees the quality of air transport within the Caribbean and particularly within the small islands as a barrier for a more unified tourism strategy for the region.

The general consensus is that connectivity between the islands is relatively poor, while each of the islands manages their own connectivity to the outside world. This may be in part because each island sees itself as an independent market from the rest, and therefore competes with its neighbors for tourism traffic.

41
46 _Table .3.2: Indonesia: Share of Energy In Total Costs andIndex ofManufacturing Production by Selected Industry Group, 1981-88_

||||Inde|x Manuf|aching|Output (|1975 =|100)||
|---|---|---|---|---|---|---|---|---|---|
|Description|Cost<br>shar|1981<br>e|1982|1983|1984|**_1985_**|1986|1987|1988|
|Food processing, milk|1.82|235|239|261|220|207|197|212|229|
|Malt liquor and malt|1.37|147|170|144|107|119|125|141|138|
|Clove cigarettes|0.26|180|187|196|224|246|267|296|317|
|Yamrandihread|2.13|126|121|114|123|111|115|125|125|
|Weavingmills|2.13|139|130|121|125|127|132|154|166|
|Knitting mills|1.00|89|81|82|80|84|89|64|75|
|Footwear|1.41|123|124|153|179|173|174|176|191|
|Plywood|2.21|471|424|438|418|387|429|557|648|
|Papermanufacturc|2.31|152|152|129|164|182|206|219|335|
|Basic chemnicals|3.71|127|130|i32|147|149|155|170|175|
|Paint, vamish, and|1.25|159|168|147|164|189|199|160|178|
|Tires andtubes|1.41|301|294|300|300|311|329|356|417|
|Glass and glass products|7.99|257|209|227|247|250|244|348|417|
|Cement|2.93|395|419|566|616|686|767|806|858|
|Structral metal products|1.66|188|196|203|197|214|218|252|291|
|Radio,TVs|1.17|349|333|351|279|243|217|208|261|
|Motorvehiclcs|0.93|256|227|198|179|183|211|233|218|
|Motorcycles,three|0.93|161|187|130|93|100|128|117|102|
|General index||214|_214_|229|241|258|275|290|299|

_Source:_ Central Buneau of Statistics.
Among initial household characteristics, we find that education seems to matter most to the change in real income per capita of households. This is true for both the household head’s education and spouse’s education. Several education variables are highly significant compared to the reference education group (i.e. those without primary education). This reflects an important role of education on taking advantage of job opportunities.

# **6. On the spillover mechanisms**

**Table 6.1: Changes in employment in detailed service sectors**

||Δ<br>employment<br>in sales of<br>vehicles and<br>parts|Δ<br>employment<br>in wholesale|Δ<br>employment<br>in retails|Δ<br>employment<br>in hotels and<br>restaurants|Δ<br>employment<br>in<br>supporting<br>industries|Δ<br>employment<br>in real estate|Δ<br>employment<br>in<br>construction|
|---|---|---|---|---|---|---|---|
||(1)|(2)|(3)|(4)|(5)|(6)|(7)|
|**Panel A: Change in“ratio of num**|<br>**ber of employe**<br>|<br>**d members to**<br>|<br>**number of mem**|<br>**bers in workin**|<br>**g ages”**<br>|<br>||
|Change in provincial tariffs|-0.058<sup>***</sup>|-0.205<sup>***</sup>|-0.248|-0.056|-0.119<sup>***</sup>|-0.087<sup>**</sup>|-0.041|
||(0.019)|(0.063)|(0.163)|(0.112)|(0.021)|(0.036)|(0.123)|
|Share of vehicle sales jobs-1|<br>-0.578<sup>***</sup><br>(0.045)|||||||
|∆share of provincial vehicle sales|<br>0.006|||||||
|<br>workers between 2002 and 1998|(0.078)|||||||
|Share of wholesales jobs-1||-0.725<sup>***</sup>||||||
|||(0.035)||||||
|∆share of provincial wholesales||<br>0.190<sup>**</sup>||||||
|<br>workers between 2002 and 1998||(0.092)||||||
|Share of retail jobs-1|||-0.505<sup>***</sup><br>(0.016)|||||
|∆share of provincial retail|||<br>0.028|||||
|<br>workers between 2002 and 1998|||(0.057)|||||
|Share of hotel and restaurants||||-0.434<sup>***</sup>||||
|jobs-1||||(0.024)||||
|∆share of provincial hotel and||||0.157||||
|restaurants workers between 2002||||(0.120)||||
|and 1998||||||||
|Share of supporting industries|||||-0.674<sup>***</sup>|||
|jobs-1|||||(0.105)|||
|∆share of provincial supporting-|||||0.052|||
|<br>industry workers between 2002|||||(0.051)|||
|and 1998||||||||
|Share of real estate jobs-1||||||-1.003<sup>***</sup>||
|||||||(0.002)||
|∆share of provincial real estate||||||<br>-0.227||
|<br>workers between 2002 and 1998||||||(0.331)||
|Share of construction jobs-1|||||||-0.483<sup>***</sup>|

24
2014). Evidence also shows that the incentive to obtain quality certificates is higher among firms that belong to a larger organization, innovating firms, and firms that are keener on cutting costs, improving product quality, and increasing consumer satisfaction (Pekovic 2010, Hudson and Orviska, 2013). We are not aware of any previous study on how informal competition affects firms’ likelihood of obtaining quality certificates. In fact, there is very little evidence on how product market competition in general impacts firms’ incentives to obtain quality certificates.

# **3. Methodology for addressing endogeneity**

Identifying the causal effects of informal competition on certification is challenging because of the potential problems of reverse causality, omitted variable bias, and measurement errors. The empirical sections below provide several checks against these problems. The motivation for these checks is as follows.

# 3.1 _Cell averages_

In the firm-level surveys of formal firms (WBES) that we use, each firm was asked if it competes against informal or unregistered firms. Responses to the question cannot be directly used as explanatory variables in the regressions, as they may be affected by a firm’s decision to obtain quality certification (reverse causality) and/or correlated with firm characteristics that influence the certification decision (omitted variable bias). One solution suggested in the literature is to proxy firm-level responses with the average responses of firms within a given cell (country, industry) – the “cell average” method. The strategy of using cell averages to mitigate endogeneity concerns is extensively used in firm-level studies (see Ozler 2000, Dollar et al. 2006, Fisman and Svensson 2007, Aterido et al. 2011, Distinguin et al. 2016, Mendi and Costamagna 2017, Avenyo 11