rafmacalaba/datause-encoder-data huggingface dataset:
Table 9: Robustness to Adjustments for Gender-Specific Comparative Advantage

|Model:|Benchmark|With Comparative Adv.|
|---|---|---|
||(1)|(2)|
|All Gender Barriers|28.28|20.77|
|Gender Norms Only|23.68|17.28|
|Wage Discrimination Only|4.39|3.12|

_<u>Notes:</u>_ This table reports the share of real GDP growth, which is explained by changes in gender barriers between the 1970s and 2010s. The shares are calculated as described in the notes of Table 4. We average across the six countries in our core sample. The columns compare the results from our benchmark model (Column (1)) and from a model that adjusts for a gender-specific comparative advantage across occupations-sector pairs (Column (2)). We measure such comparative advantage from a benchmark economy – the United States in 2015 – which we assume to have no wage discrimination.

productivity effects. Measuring true productivity differences across genders in each occupation-sector pair and disentangling them from gender barriers is challenging (if not impossible), as it would require detailed data on labor input and output, separately for men and women. Such granular data does not exist for a large set of occupations, sectors, years, and countries. Instead, we implement two analyses to examine the potential role of gender-specific comparative advantage and its implications for our results.

First, we examine whether our estimates of _τojct_ show greater variation across occupation-sector pairs, or across country-years. This information provides insights into the underlying factors that _τojct_ reflects, as gender-specific productivity differences (unlike gender barriers) are expected to vary more across occupation-sector pairs and less across country-years.<sup>27</sup> Regressing our estimates of _τojct_ on occupation, sector, or occupation-sector fixed effects explains at most 20% of the variation in _τojct_ with _R_<sup>2</sup> values ranging from 0.01 to 0.2. This finding indicates that a substantial part of the variation in our _τojct_ estimates is driven by variation across country-years, making them more likely to reflect gender barriers than systematic gender productivity differences within occupation-sector pairs.

In a second exercise, we repeat our counterfactual analysis while explicitly accounting for a gender-specific comparative advantage in each occupation-sector pair. To do so, we select a benchmark economy, the United States in 2015, where we assume no wage discrimination (Lee, 2024). Under this assumption, any observed gender wage

> 27More specifically, it is reasonable to assume that the relative ranking of occupation-sectors in terms of a potential male (or female) comparative advantage is consistent across countries and over time. For example, agricultural jobs are likely to be consistently more brawn-intensive, which can benefit men relative to women, than office jobs.

37
_Role of NGOs in Health Delivery Afdca Health Policy Study_ 11 .

(Baldwin 1988). Moreover, such PVOs must continually spend dme and staff resources to solicit funding.

30. One further consequence of such external financial dependence is the pressure brought to bear on NGOs to appeal to heterogeneous interests in developed countries. This is manifest, for example, in the portrayal of images to developed country 'udiences. These may not truly reflect the real nature of NGO activities. The "foster a child" message, for example, espoused by several NGOs, belies the fact that contribudons are allocated more to community development than to individual children. Thus, however fiavorable the latter approach Is, NGOs, like for-profit enterprises, may feel compelled to distort their public image, although the motivations for the two types of Institudons obviously differ.

31. External dependence may also be due to a preponderance of expatriate staff, many of whom are seeking overseas experience for a few years but will return to their home countries. While in the past many missionaries and other NGO employees were wiNling to spend their careers serving underprivileged communities, this generadon of idealists may in fact be disappearing and with it the continuity of care that was the hallmark of mission health services. While it is difficult to generalize about the proportion of expatriate staff, indications are that at least in missions they are predominant. Among the church facilities linked through the Private Health Association of Malawi, **for** example, only 30 percent of the senior staff are Malawi nationals.

# _Lack of Documentation_

32. Partly because of their small scale and weak resource base, NGOs characteristically fail to document their activities, whether failures or successes. Often, they do not conduct baseline studies or evaluations, or collect critical health information (USAID 1986). These shortcomings reduce any potential for replicating their successes on a larger scale and certainly do not aid governments in their assessment of national or regional needs. The lack of information is also an impediment to coordination with other NGOs, let alone with govemment.

33. On the other hand, donors may be overly stringent in their requirements for documentation as a condition of funding. This forces NGOs to comply with time. consuming administrative tasks which derive from the donors' own bureaucratic structure. There is little evidence that the ability to produce reports acceptable to agency bureaucracies corresponds with a capacity for community empowerment (USAID 1986).

# _Incompatibility_

34. A further barrier to coordination between NGOs and governments is incompadbill. ty between training which prevents transfer of personnel between health care insdtudons. In Malawi, after some discussion, the government agreed to allow government staff to be
**TABLE 3: Impacts on Child Assessments - 18-Month Follow-Up**

|||**Depend**<br>**To**|**ent Variab**<br>**tal**|**le: Malaw**<br>**Tool**<br>**Langua**|**i Developm**<br>**Score**<br>**ge Skills**|**ental Asse**<br>**Fine**<br>**Perc**<br>**Sk**|**ssment**<br>**Motor /**<br>**eption**<br>**ills**|
|---|---|---|---|---|---|---|---|
|||**(1)**|**(2)**|**(3)**|**(4)**|**(5)**|**(6)**|
|T2 (careiver trainin)||-0.092|-0.063|-0.041|-0.031|-0.134*|-0.107*|
|g g||(0.080)|(0.060)|(0.079)|(0.063)|(0.074)|(0.059)|
|T3 (T2 + careiver incentives)||0.013|-0.003|0.088|0.085|-0.081|-0.115*|
|g||(0.081)|(0.067)|(0.084)|(0.072)|(0.075)|(0.065)|
|T4 T2 + rntin trinin||0.115|0.126*|0.183**|0.185**|0.008|0.012|
|( paeg ag)||(0.086)|(0.067)|(0.087)|(0.071)|(0.075)|(0.061)|
|Ld Ddt Vribl Bli|||0.510***||0.426***||0.444***|
|agge epenen aae (asene)|||(0.033)||(0.031)||(0.034)|
||T2=T3|0.191|0.367|0.131|0.106|0.454|0.889|
|F-test for Equality of Parameters (p-value)|T2=T4 0|.007***|0.002***|0.005***|0.001***|0.033**|0.049**|
||T3=T4|0.195|0.058*|0.266|0.168|0.199|0.045**|
|District-bin Fixed Effects?||Yes|Yes|Yes|Yes|Yes|Yes|
|Lagged Dependent Variable and Age Dummies?||No|Yes|No|Yes|No|Yes|
|Number of observations||1,936|1,936|1,936|1,936|1,936|1,936|

Notes: .01 - ***; .05 - **; .1 - *; OLS regressions at the child level using standardized test scores at the 18-month follow-up and baseline covariates with standard errors (SEs) in parentheses. SEs are clustered at the CBCC level and observations are weighted using sampling weights and tracking weights (for 42 observations randomly assigned to tracking).

45
# **APPENDIX A: TEST OF MISREPORTING WEEKS PREGNANT AT 1**<sup>**ST**</sup> **PRENATAL VISIT**

One concern is that the financial incentives may cause clinics to misreport the week of pregnancy at the first visit. In this appendix we report the results of test for this behavior. Recall that in our main analysis we construct the week of pregnancy at the first visit using the date of the first visit and the last menstrual date (LMD) as reported by the women. If the latter is not available we use the estimated date of birth (EDD) as recorded by the physician in the first visit. The EDD is calculated off the LMD as reported by the women during her first visit. While clinic medical records should contain both dates, about 10% of records are missing the LMD.

One possible way of misreporting the week of pregnancy at the first visit is to change the LMD and the EDD in the patient’s clinical medical record. For instance, if a woman is in her 21<sup>st</sup> week of pregnancy at the first visit, the physician could add 7 days to the LMD and EDD so that the visit falls into the 20<sup>th</sup> week of pregnancy. Both would have to be changed in order to deceive the auditors.

To test for this possibility we use gestational age at birth (GAB) in weeks measured by physical examination at the time of birth, registered in the hospital medical record. We then compare the weeks elapsed from the first prenatal visit to the delivery date based on GAB to weeks elapsed from first visit to the delivery date based on EDD. While EDD is collected by the clinic who has an incentive to misreport, the GAB is collected by the hospital at time of delivery where there is no incentive to misreport.

Figure A1 plots the number of weeks to delivery from the time of the 1<sup>st</sup> visit based on GAB (y‐axis) to the one based on EDD (x‐axis). If there is no difference between the two measures, then all of the dates should fall on the 45‐degree blue line. There should be some differences as EDD is an estimate that assumes no prematurity at birth, and there could be data entry in GAB and EDD and recall errors in EDD. Figure A1 shows that almost all of the data embrace the blue 45‐degree line and most of the observations off the line are situated above it, consistent with prematurity explaining the differences.

If the clinic changes the EDD in order to capture higher payments, we would expect greater differences, for the treatment group, between GAB and EDD below the 12‐week thresholds than above it during the intervention period when the incentives are in force, but no differences in the pre‐intervention period. In order to test this, we estimate the following difference in difference regression: 42
results indicate that extreme rainfall events experienced during infancy, particularly droughts for the district fixed effect models, hamper the physical development of women. Affected women are around 0.5-0.7 centimeters shorter than the comparison unaffected women, on average.

Suggestive evidence of positive returns to health in Mozambique is found, implying that uninsured weather shocks that worsen nutrition status also lead to lower productivity. The existence of a positive association between improved nutrition and increased productivity is often assumed and has been widely demonstrated in the empirical literature. Good health is particularly important in agricultural settings in developing countries, where the structure of employment requires strong physical development, particularly among men. To contextualize the negative effects of weather shocks on adults’ height, this study provides non-parametrical estimates of the unconditional relationship between height and school attainment and wealth for adult women in Mozambique (Figure 6). The results show a quasi-monotonic relationship between women’s height, human capital, and wealth accumulation. This suggests that the physical development lost due to extreme weather is likely to translate into lower productivity and, ultimately, lower welfare.<sup>3</sup>

# **5. Conclusions**

Mozambique’s economy is dominated by agriculture, and therefore farmers are largely exposed to unpredictable rainfall. In developing countries, agriculture can be a very risky activity: where financial and insurance systems are underdeveloped, farmers’ exposure to risk is higher. Since the agricultural sector constitutes the backbone of the Mozambican economy, accounting for a quarter of GDP and representing the main source of employment for the vast majority of the population, weather shocks tend to have devastating impacts on the livelihoods of Mozambicans.

Mozambique is also one of the countries most affected by natural disasters, both on a regional and on a global scale, and this intensifies farmers’ vulnerability. Mozambique is frequently hit by severe droughts, cyclones, and floods. Rainfall data for Mozambique spanning several decades indicate that years with precipitations levels well below or above the historical mean are common

> 3 The relationship is estimated with much less precision for women above 175cms because of the low number of observations in this height range .

13
# <mark>CONCLUSIONS</mark>

Firm-level data analysis reveals that the share of politically-connected firms in the Ukrainian economy is unusually high, ranging between 15 and 20 percent of employment and turnover. Two approaches were used to identify politically-connected firms: one identifying firms solely on the basis of formal owners, managers and ultimate beneficiaries being politically-exposed persons; the second approach uses data from investigative journalism to identify links between the owners of business groups and officials in key state institutions. The economic weight of politicallyconnected firms is similar using both approaches and the firm-level analysis shows robust results for both approaches to the identification of politically-connected firms.

The politically-connected firms reap the benefits from preferential treatment when interacting with the state and limiting market competition. A case study of the administration of VAT refunds shows that politically-connected firms were 61 percent less likely to be audited when requesting a VAT refund during February 2016 - March 2017, thus enjoying lower costs for paying taxes than other firms. The case of air transportation shows how regulations restricting competition and granting preferential access to benefits have helped firms secure and maintain market dominance.

12
BENIN’S INFRASTRUCTURE: A CONTINENTAL PERSPECTIVE percent in 2006, a 65 percent increase. At this pace, the Millennium Development Goal of 75 percent sustainable water supply coverage in urban areas will likely be met.

Following significant institutional reforms, in particular in the tariff policy, important progress has been achieved in the financial performance of the national utility. In 2003 the water and energy sectors were reformed, and the operation of these services, previously managed by SBEE (Société Béninoise d’Electricité et d’Eau) was separated. SONEB (Société Natiaonale des Eaux du Bénin), a public utility, was created to provide water supply and wastewater treatment for the urban and peri-urban areas of the country. Since the reform, systematic adjustments of tariffs have been carried out. Between 2005 and 2009 operating cost recovery increased from 80 percent to 105 percent (table 9). The overall gap between the average effective tariff and average total costs has declined, but a difference remains. In 2009 the average total cost was reported at $1.10 per m3 and the average effective tariff at $0.72 per m3. The absence of cost-recovery tariffs has led to underinvestment and delays in asset maintenance, which in turn translates into high system losses.

**Table 10. Evolution of operational indicators associated with SONEB**

||Water delivered|System losses|Collection<br>ratio|Average total<br>cost|Average<br>effective tariff|Total hidden<br>costs|Total hidden<br>costs|
|---|---|---|---|---|---|---|---|
||(millions of<br>m3/year)|(%)|(%)|($/m3)|($/m3)|($m/year)|(% revenues )|
|2000|24|20|100|1.00|0.42|11|139|
|2001|25|17|100|0.98|0.41|12|140|
|2002|28|20|92|1.00|0.46|13|113|
|2003|30|22|96|1.29|0.55|18|111|
|2004|30|23|77|0.88|0.60|10|51|
|2005|31|26|91|0.98|0.60|11|58|
|2006|33|24|92|1.09|0.61|15|61|
|2007|34|28|89|1.14|0.66|16|57|
|2008|37|24|87|1.18|0.71|17|49|
|2009|39|28|85|1.10|0.72|17|43|

_Source_ : Derived from Briceño-Garmendia, Smits, and Foster (2009).

The adjustment of tariffs has resulted in lower hidden costs. Whereas in 2000 underpricing of water services accounted for all hidden costs, in 2009 it was responsible for just 64 percent of them, still the highest share among the sources of hidden costs considered. During the period, hidden costs decreased from 139 percent of revenues to 43 percent (table 10). Comparing the aggregate average hidden costs of SONEB with those of other West African water utilities indicates that, in 2005 and even more in 2009, SONEB’s hidden costs were among the lowest in the region (figure 13b).

24
childcare, but these authors were unable to examine effects on uptake. Whether on-site childcare increases the chances of uptake of public works has not yet been studied.<sup>4</sup> Participants in the public works component were paid by direct deposit into bank accounts that they opened in their names. In some contexts where women have low bargaining power, lack of control over their earnings is one potential reason why they have chosen not to enter the labor market (Field et al., 2021). Therefore, by having participants open bank accounts in their own name, the public works program aimed to ensure that the women were free to exercise control over their own earnings.

The public works program entailed 50 days of work for four hours per day over the course of 2.5 months. At midline, women report working 4.8 hours per day, on average, which includes breaks. The program participants earned a daily wage of 1,000 FDJ (Djiboutian francs), which corresponds to approximately 80 percent of the official minimum wage, or 5.6 USD, or 9.9 USD 2021 PPP. Compared to the EDAM 2017 data, this wage is below the 25<sup>th</sup> percentile of the hourly wage rate for all workers in Djibouti. As noted previously, the public sector employs primarily skilled laborers and constitutes a high share of all wage work in Djibouti. Compared to private sector wages specifically, the public works program pays closer to the 30<sup>th</sup> percentile of the wage distribution in 2017. For workers with a primary education at most, the program pays at the 25<sup>th</sup> percentile, and for women without any education, wages are closer to the 40<sup>th</sup> percentile in 2017.<sup>5</sup> The potential income gains from the public works program are substantial in the context of low employment, even if the wage rate is not very high compared to those who were employed in the public or private sector at that time. Recall that only 10 percent of women in our study have any labor income at baseline. This income came mostly from selfemployment. In this context, the potential income from public works is about 3 times higher than women’s average weekly earnings from self-employment activities. On the other hand, women’s potential earnings from public works participation are less significant when compared to their husbands’ labor income: both the hourly wage and hours offered to such women are lower than what their working husbands receive. For husbands, the weekly wage offered by the public works program is just over half of their mean labor income. In this sense, prospective public works income has the potential to increase household income from any source by 50 percent.

> 4 The International Labour Office (2015) details a variety of ways in which public works programs can be adapted to address the constraints that women face.

> 5 These computations are based on the EDAM 2017 and include reported earnings from self-employment and salary/wage jobs, with population weights applied.

9
- Ross, L. and Ward, A., (1996).  ̳Naive realism in everyday life: Implications for social conflict and misunderstanding‘. In Reed, E.S., et al. (Eds.), _Values and Knowledge._ Lawrence Erlbaum Associates, Mahwah, NJ, pp. 103–135

- Saez-Marti, M. and Zilibotti, F. (2008).  ̳Preferences as human capital: Rational choice theories of endogenous preferences and socioeconomic changes‘. _Finnish Economic Papers_ , 2008, Vol. 21(2), pp. 81-94.

- Segall, M.H., Campbell, D. T. and Herskovits, M. J. (1966). _The Influence of Culture on Visual Perception_ , Indianapolis: Bobbs-Merrill Co.

- Starmer, C. (2000).  ̳Developments of non-expected utility theory – The hunt for a descriptive theory of choice under risk‘, _Journal of Economic Literature_ , vol. **37** , pp. 332 – 382.

- Stern, N. H., Dethier, J-J., and Rogers, F. H. (2005). _Growth and Empowerment: Making Development Happen_ , Munich lectures in economics, Cambridge, MA:  MIT Press.

- Stiglitz, J. E. (1985).  ̳Information and economic analysis: A perspective.‘ _The Economic Journal_ , vol. **95** , pp. 21-41.

- Stutzer, A., Goette, L. and Zehnder, M. (2011).  ̳Active decisions and prosocial behaviour: A field experiment on blood donation.‘ _The Economic Journal_ , in press.

- Sutton, J. (1990).  ̳Explaining everything, explaining nothing? Game theoretic models in Industrial Organisation‘. _European Economic Review,_ vol. 34(2-3), pp. 505-512.

- Swidler, A. (1986).  ̳Culture in action: symbols and strategies‘. _American Sociological Review_ , vol. **51** , pp. 273-286.

- Voors, M., Nillesen, M., Verwimp, P., Bulte, E., Lensink, R. and van Soest, D.(forthcoming).  ̳Does conflict affect preferences? Results from field experiments in Burundi. _American Economic Review_ .

23
Production”, _Journal of Political Economy_ , 107, 393-403.

- Apps, PF and R Rees (1997), “Collective Labor Supply and Household Production”, _Journal of Political Economy_ , 105, 178-190.

- Apps, PF and R Rees, (1996), “Labour Supply, Household Production and Intra-Family Welfare Distribution”, _Journal of Public Economics_ , 60, 199-219.

- Apps, PF and R Rees, (1988), “Taxation and the Household”, _Journal of Public Economics_ , 35, 155-169.

- Attanasio OP and J Banks (1998), “Trends in Household Saving: A Tale of Two Countries”, Working Paper Series No W98/15, Institute of Fiscal Studies, London.

- Becker, GS (1965), “A Theory of the Allocation of Time”, _Economic Journal_ , 75, 493-517.

- Becker, GS (1981), “Division of Labor in Households and Families”, in _A Treatise of the Family_ , Ch 2, 14-37, Harvard University Press.

- Behrman, JR (1997), “Intrahousehold Distribution and the Family”, in MR Rosenzweig and O Stark, eds., _Handbook of Population and Family Economics_ , Ch 4, 125-

- 187, Elsevier Science.

- Bergstrom TC (1997), A Survey of Theories of the Family”, in MR Rosenzweig and O Stark, eds., _Handbook of Population and Family Economics_ , Ch 2, 21-79, Elsevier Science.

- Blundell, RW, M Browning and C Meghir (1994), Consumer Demand and the Life-Cycle Allocation of Household Expenditures, _Review of Economic Studies_ , 61, 57-80.

- Blundell, RW, P-A Chiappori, T Magnac and C Meghir (1999), “Collective Labor Supply and Participation”, _Econometrica_ .

- Blundell, RW and MaCurdy (1999), “Labor Supply: A Review of Alternative Approaches”, O Ashenfelter and R Layard, eds., _Handbook of Labor Economics_ , Vol 111, Elsevier Science, 1559-1695.

- Blundell, RW, I Preston and I Walker, eds., (1994), _Measurement  of Household Welfare_ , Cambridge University Press, Ch 6, 140-163.

- Boskin, MJ and E Sheshinski (1983), Optimal Tax Treatment of the Family”, _Journal of Public Economics_ , 20, 281-297.

- Bourgiugnon, F (1999), “The Costs of Children: May the Collective Approach to Household Behaviour Help?”, _Journal of Population Economics_ , 12, 503-521.

59