rafmacalaba/datause-encoder-data huggingface dataset:
employment opportunities for them, outside the garment sector. Column 1 of table 3 suggests that the same is true for low-skilled men; men with below median education increase their wages by 5.4% more than those with above-median education, and their working conditions also particularly increase (column 5). We also find that wages of men who are older, married, and have a child particularly increase. It is either plausible that they also have more inelastic labor supply if their demographics make it harder to move to find other jobs<sup>15</sup> , or that they have an stronger inward shift in labor supply (which also leads to particular increases in wages if workers are not perfect substitutes) if safety concerns are particularly salient given that they have families to support.

# **7 Conclusion**

The Rana Plaza collapse of April 2013 killed over 1000 Bangladesh garment workers and injured many more. In response, international scrutiny on the garment sector increased, leading to a push by retailers to improve working conditions, an increased hesitancy for export factories to subcontract to smaller factories, and a minimum wage increase. This paper studies the net effects of these post-Rana Plaza responses on labor market outcomes of garment workers, using six rounds of the Bangladeshi Labor Force Survey and a triple difference identification strategy that compares garment workers to non-garment workers, in garment-exporting districts versus non-exporting districts, pre versus post Rana Plaza.

We find that increased international scrutiny achieved its goal of improving working conditions, while also leading to average wage increases for garment workers in treated factories. We did not find average impacts on hours of work or the receipt of written contracts. These results suggest that garment manufacturers had scope to increase total compensation, compared to a model of compensating differentials in a perfectly competitive labor market in which improvements to working conditions come at the cost of reduced wages. While a commonly voiced concern is that, in a highly competitive global garment sector market, pushes to improve compensation will lead to firms to leave one country for one with even cheaper labor costs (Haq, 2018), we still find the

> 15Menzel and Woodruff (2021) find that mobility is an important component of wage increases in the Bangladeshi garment sector.

29
is restricted to households with at least one school-aged child (5-17 years). Almost 95% of such households report a positive expenditure on education. All other outcomes are computed for households with at least one child under the age of 18. Average per-capita food consumption at ~~P~~ 12,659 is higher than non-food consumption ( ~~P~~ 9,292) and also has a lower standard deviation. While only 14% of households in this sample are extremely poor (at the US$1.90 poverty line), 40.59% are at their respective provincial poverty line and 49.35% at the poverty line for lower middle income countries (US$3.20).

To assess whether the 4P helped limit the damage suffered from Yolanda, results will be presented for a triple differenced specification. The three dimensions are: Before vs. after, being (more) affected by the typhoon vs. being less/not affected, and being a program beneficiary vs. being a nonbeneficiary. The data contain self-reported beneficiary status in the 4Ps, which is received by 40.74% of households. Not shown in the table, but nonetheless of interest, this proportion is 52.83% for households with incomes lower than ~~P~~ 20,000, 31.93% for those with incomes between ~~P~~ 20,000 and ~~P~~ 50,000, and still 8.22% for those between ~~P~~ 50,000 and ~~P~~ 80,000. Again, showing the imperfect targeting of the 4Ps. The other two dimensions used in the triple distance specification are both well-balanced. The average distance to the storm path is 94.53km and 55.36% of observations fall inside the 100km band. Moreover, 48.39% of the observations come from the 2015 round.

15
cook reported whether they could do the activity easily, whether they could do it by themselves but with some difficulty, whether they needed assistance, or whether they could not perform the task at all. We included difficult activities such as walking 5km or carrying a heavy load, tasks known as intermediate ADLs, as well as basic ADLs such as standing from sitting and performing routine housework.

Measurement of indoor air pollution in the cooking areas during the follow-up wave was collected in a random subsample of 204 of the 480 households. Particulate matter with an aerodynamic diameter of 2.5 micrometers or less (PM2.5) was recorded using light-scattering sensors and gravimetric pumps and filters.<sup>6</sup> The health module and indoor air pollution measurements were not collected in the baseline survey and added only for the follow-up wave. In the empirical analysis that follows, we pay particular attention to this fact and provide evidence that it does not bias the identification of our causal treatment estimates given the randomized design of the study.

# **3. Empirical Approach**

Our baseline analysis compares outcomes across treatment and control households with the control group representing the counterfactual if the treatment group had not been offered _Mirt_ stoves. We complement this difference approach when examining child growth by exploiting the physiology of child development where height is only sensitive to interventions in the first three years of life (Cusick and Georgieff, 2016; Martorell and Habicht, 1986). This allows us to exploit variation between younger and older siblings to identify the effect by a difference-in-difference between children within a household.

# **3.1 Baseline treatment and control comparison**

Our baseline models estimate the difference across individuals in treatment and control households. For a given individual _i_ in household _h_ and community _c_ , we estimate the following model: y��� �β� � β�I�Treatment�� �δX�� �μ� �ε��� (1) where _y_ is a health outcome and β� is the coefficient of interest that captures the causal effect of one’s household being assigned to the treatment group. As treatment was randomly assigned and orthogonal to the vector of additional control variables measured at baseline, _X_ , the inclusion of controls aids only in improving the precision of the estimates. Additional covariates include the following: gender;

> 6 See Bluffstone et al. (2018) for additional details on the protocol, collection, and analysis of PM2.5 readings.

8
people who do not hold a permanent Tashkent propiska; temporary registration does not suffice. Enforcement of propiska rules is conducted through several channels, the most important include local governments (called _mahallas_ ), and when individuals pass through checkpoints where domestic passports are reviewed (though this latter practice has become less common since 2017, qualitative interviews conducted as part of the L2CU project suggest that systematic checks of registration documents often precede major holidays).

In January 2019, several reforms of the propiska system were adopted in a presidential decree entitled: O _n Measures to Fundamentally Improve the Processes of Urbanization_ . Until that time, it was illegal in Uzbekistan for a person to apply for a job outside of the region in which they were registered. This was especially binding in the case of Tashkent. However, the new decree established that people may apply for formal work in urban areas (and especially Tashkent) without a propiska, and upon receiving a formal employment contract, apply for temporary status. Qualitative interviews completed as part of the L2CU study highlighted that since the decree was issued, it has become substantially easier to obtain and renew temporary status. However, there remains no official method to obtain permanent registration in Tashkent based on employment, outside of limited exceptions for certain government employees.<sup>16</sup> Continued propiska restrictions on registering a business outside of one’s place of permanent residence have downstream consequences on migration behavior and economic activity. As there has been less business registration in urban areas than there would have been absent any restrictions, physical and financial capital have also been much less mobile. This relationship is endogenous; less migration leads to less business formation, and less business formation leads to less migration. In a counterfactual scenario in which people were permitted to move, more businesses would likely move and/or start to serve a larger customer base. This suggests that propiska restrictions likely have efficiency costs stemming from effects on the spatial arrangement of capital and economic activity, beyond the direct costs associated with limited labor mobility.

Internal mobility restrictions are not unique to Uzbekistan, and the effects of similar limits have been studied in several cases. Research in this area consistently finds that barriers to internal migration come at very high costs, and that large welfare gains have resulted from dismantling them. One notable example comes from China, where a series of economic and social reforms paved the way for one of

> 16 For a more complete discussion of the de jure and de facto applications of the propiska system, please see the qualitative review that accompanies this paper.

20
allows us to examine the distributional consequences of any particular set of pension system rules and assumptions.

# Funded pensions in LIFEMOD

Table 8 presents distributional outcomes for the LIFEMOD population of males, on the basis of a real rate of return of _3%_ per annum and real earnings growth of 1.5% per annum. The first four columns show, for a range of retirement ages, the average pension capital accumulated over the life course for males according to their position in the lifetime earnings distribution. The amount accumulated with four different rates of contribution from 5% to 20% of earnings are reported. These capital sums are then compared with the appropriate annuity costs in Table 6 to determine the percentage of average male LIFEMOD earnings that would be replaced by contribution rates of 5%, 10%, 15% and 20%; the figures are presented in the final four columns.

It is immediately apparent from Table 8 that lifetime earnings histories have a significant impact on individual ability to accumulate a fund sufficient to provide an adequate pension annuity. From Table 7c we can see that, for contribution beginning at age 21 with retirement at age 65, and with real interest rates at 3% and real earnings growth at 1.5% per annum, the LIFEMOD average fully-employed male needs to contribute 12% of earnings to produce a pension replacement rate of 50% in retirement. From the third panel of Table 8, however, we can see that even with a contribution rate of 15%, only the top four deciles of the lifetime earnings distribution reach this 50% replacement target, and the bottom two deciles fall below the 33% replacement level. If we look at the experience of women under the same contribution and retirement conditions (the third panel of Table 9), we can see a more extreme picture. Not only is the pension replacement rate much lower, with only the top decile accumulating a fund sufficient to purchase a pension annuity equal to 50% of average male LIFEMOD full-time earnings, but the distribution is also more skewed that for men, with the ratio of highest to lowest replacement rate standing at 7.57:1 for women compared with 4.27:1 for men.

41
**Table 6.** MNL of employment outcomes, without gender role attitudes and personality traits

||(1)|(2)|(3)|
|---|---|---|---|
||Pooled sample|Women|Men|
|**Employed**<br>||||
|Male|-0.082|-|-|
||(-0.99)|||
|Age|0.321***<br>|0.346***<br>|0.248***<br>|
||(14.62)<br>|(13.13)<br>|(7.87)<br>|
|Age_sq|-0.004***<br>|-0.004***<br>|-0.003***<br>|
||(-14.00)|(-12.18)|(-8.28)|
|Married|0.684***|0.471***|1.410***|
||(5.51)|(3.27)|(5.03)|
|Secondaryeducation|0.429***|0.181|0.703***|
||(3.95)|(1.28)|(4.28)|
|Male head|0.322**|-0.528|1.248***|
||(2.05)|(-1.36)|(4.42)|
|Muslim|-0.001|-0.266|0.319|
||(-0.01)|(-1.36)|(1.57)|
|Spousepresent|-0.681***|-0.029|-0.885***|
||(-3.75)|(-0.07)|(-3.14)|
|Household size|-0.027|0.001|-0.039|
||(-1.52)|(0.07)|(-1.54)|
|Poor|-0.404***|-0.317**|-0.580***|
||(-3.29)|(-1.98)|(-3.67)|
|Urban|0.757***<br>|0.758***<br>|0.753***<br>|
||(4.17)|(3.45)|(3.74)|
|Ashanti(b:Northern)|0.219|0.044|0.496**|
||(1.53)|(0.22)|(2.29)|
|**UNEMPLOYED**||||
|Male|-0.460**|0.000|0.000|
||(-2.40)|(.)|(.)|
|Age|0.177***|0.138***|0.243***|
||(4.62)|(2.84)|(3.87)|
|Age_sq|-0.002***|-0.002***|-0.003***|
||(-4.95)|(-3.13)|(-4.25)|
|Married|0.629***|0.704**|0.490|
||(2.85)|(2.50)|(0.98)|
|Secondaryeducation|0.355|0.071|0.778**|
||(1.63)|(0.27)|(2.20)|
|Male head|0.584**|-0.333|0.475|
||(2.08)|(-0.87)|(1.15)|
|Muslim|0.204|-0.028|0.548|
||(0.64)|(-0.07)|(1.26)|
|Spousepresent|-0.934***|-0.074|-0.884|
||(-3.06)|(-0.18)|(-1.55)|
|Household size|-0.030|0.001|-0.079|
||(-0.72)|(0.02)|(-1.09)|
|Poor|0.117<br>(055)|0.194<br>(075)|0.021<br>(006)|
|Urban|.<br>1.159***|.<br>1.777***|.<br>0.344|
||(2.93)|(4.77)|(0.62)|
|Ashanti(b:Northern)|0.662*|0.579|0.880**|
||(1.85)|(1.28)|(2.03)|
|_N_|4497|2474|2023|
|Odds ratios reported; t statist|ics in parentheses: * p<0.10 **|p<0.05 *** p<0.01; Errors c|lustered at cluster-level. Base|
|<br>category is “Not in the Labor|,<br>Force”|,||

29
BOTSWANA’S INFRASTRUCTURE: A CONTINENTAL PERSPECTIVE competitor to the BTC. The privatization of the BTC had also been postponed until 2011 due to the uncertainty of the global economy.<sup>8</sup> Internet penetration is low, some six times less than the upper-middle-income average. According to the most recent survey, carried out between 2007 and 2008, Internet penetration among those aged 16 years and older was 5.8 percent (Gillwald and Stork 2008). Broadband pricing is below the Sub-Saharan Africa average but nonetheless remains high for most of Botswana. The BTC charges Internet service providers (ISPs) a fee to provide broadband service over fixed telephone lines, which is allegedly not cost based. Furthermore, since the BTC also provides retail broadband service there is a perception that it is favoring its own Internet subsidiary, Botsnet.

Despite a relatively high level of international bandwidth (figure 14), connectivity remains a challenge due to Botswana’s landlocked situation. The BTC has a national fiber backbone with connections to the SAT-3 undersea cable. Greater redundancy is planned through connections to the Eastern Africa Submarine Cable System (EASSy) and West Africa Cable System (WACS). The BTC’s control over almost all fixed Internet infrastructure has resulted in high wholesale costs, with a number of ISPs using alternative VSAT<sup>9</sup> connections (Kende and Gibb 2009). The liberalization of the sector should see mobile operators creating alternate international gateways to support their recently launched wireless broadband services. It is expected that this will inject greater wholesale and retail competition into the broadband market.

Other factors contributing to low Internet penetration are exogenous to the ICT services sector. Home computer penetration is only 7 percent (Central Statistics Office 2009), the level of digital literacy is low, and there is a lack of local content. Another problem is a lack of electricity in certain areas.

Although mobile performance has been impressive, there is still room for improvement. Mobile tariffs have not decreased substantially in local currency terms. While mobile coverage is relatively high, there are still pockets of rural areas that do not have a signal. The government’s Nteletsa project aims to remedy this by providing subsidies to mobile operators to extend coverage in rural areas.

> 8 ―The privatization effort, initiated in 2006 was postponed in 2008, due to unfavorable capital markets. Deteriorating global capital markets mean privatisation transactions can not take place at the present time‖ (BTC 2009). An IPO began in 2011 (see: <u>http://investing.businessweek.com/research/stocks/private/snapshot.asp?privcapId=13775542).</u>

> 9 Very small aperture terminal.

29
To characterize the relative importance of individual commodities, we first measure the implications of one hundred-percent price increases for key food commodities and present the results in Table 7. We also measure the poverty implications of changes in various food items that cause identical, 10-percent, changes in the World Bank’s food price index. To do this, we multiply a 10-percent price increase by the reciprocal of that commodity’s weight in the index. The list of the commodities and their respective weights are shown in Table 8. We report the resulting changes in global poverty in Table 9.

The results shown in Tables 7 and 9 confirm a large distribution of poverty impacts depending on which of the constituent commodities’ prices increase. A 100-percent price increase would increase global poverty most in the short-run most when affecting rice, wheat and vegetable oils. This importance reflects both the sizeable weights of these commodities in the consumption baskets of poor households, and the extent to which many consumers are net buyers, and hence vulnerable to price increases. However, because rice and wheat are also important production items for many of the rural poor, a sustained increase in their prices is likely to reverse the short-run poverty increase into a considerable poverty reduction. In the case of vegetable oils, which are rarely produced by poor households, no such reversal of the poverty results is observed. This latter result may overstate the poverty impacts of higher vegetable oil prices because it is likely that some poor households produce some oilseeds whose prices would likely rise at the same time as the price of vegetable oils. Higher dairy product prices also have a substantial adverse impact on poverty in the short run, despite the offsetting impact of higher incomes from milk production. Finally, we note that higher prices of maize appear to lower global poverty, even in short run, which is largely caused by the fact that maize is primarily grown as an animal feed crop rather than food in the most populous countries in our sample, which results in underestimating its poverty impacts in the context of food prices. When considering only the countries in Africa and Latin America, the implication of higher maize prices is a poverty increase in the short-run.

Moving to the long run impact of increases in individual commodity prices, we see some very substantial changes in the impact. Perhaps the most striking change is in the impact for rice, which goes from 1.5 percentage points to minus 8.2 percentage points. The reversals for wheat and dairy products are also substantial, with wheat changing from 1.2 percentage points in the short run to minus 2.5 percentage points in the long run., while dairy products changes from 0.8 19
29

**Table 4:  Community radio and French literacy among second graders**

||Bi-<br>variate|Base<br>controls|Base plus<br>other<br>radio<br>types|Base, villages<br>less than 32<br>km. from<br>nearest urban<br>center|Base, fewer than<br>53% of village<br>HHs report<br>incomes<<br> 30K|Base, in<br>vs. out<br>stations|Base,<br>robust<br>regression|
|---|---|---|---|---|---|---|---|
|Community radio|0.0361|0.0497|0.0541|0.06|0.047||0.0260|
|received by village|(0.05)|(0.02)|(0.02)|(0.03)|(0.08)||(0.09)|
|(# stations)||||||||
|Within-commune||||||0.150||
|community stations<br>received by village||||||(0.05)||
|Out-of-commune<br>community stations<br>received by village||||||0.0478<br>(0.02)||
|Literacy Center||-0.0648|-0.0614|-0.05|-0.053|-0.0672|-0.0310|
|Dummy||(0.12)|(0.13)|(0.26)|(0.19)|(0.11)|(0.36)|
|Village chief has||-0.0773|-0.0813|-0.08|-0.09|-0.0881|-0.0175|
|secondary education||(0.14)|(0.11)|(0.31)|(0.13)|(0.11)|(0.62)|
|Distance of village to||0.00153|0.00157|0.002|0.003|0.00171|0.00143|
|nearest urban center||(0.10)|(0.09)|(0.37)|(0.02)|(0.06)|(0.05)|
|Most common||0.0947|0.0843|0.10|0.07|0.0887|0.0832|
|language in village<br>and commune is the<br>same||(0.07)|(0.12)|(0.16)|(0.26)|(0.08)|(0.04)|
|Private commercial|||0.0147|||||
|stations received by<br>village|||(0.67)|||||
|Religious radio<br>stations received by|||-0.0553<br>(0.35)|||||
|village||||||||
|Public radio stations<br>received byvillage|||0.0642<br>(0.25)|||||
|Observations|210|199|199|152|151|199|199|
|_R_<sup>_2_</sup>|0.30|0.40|0.42|0.44|0.44|0.41|0.43|

**Note** :  All specifications include commune fixed effects, and have standard errors clustered by commune; _p_ -values are reported in parentheses.  Other control variables (none significant), not reported:  village population; whether village has a paved road; dummy for presence of secondary school; number of functional private schools; health or maternity center dummy; number of potable water sources built in 2007 or 2008; whether village chief has primary schooling; distance of village to nearest bus or train stop; fraction of households in village sample with income less than 30,000 CFA Francs; mean number of houses in village sample with brick walls; mean number of homes in village sample with cement floors; mean number of houses in village sample with more than five rooms; fraction of households in village sample with a mobile phone; probability that main language in any two households in the village is the same.