rafmacalaba/data-use-mentions-extended huggingface dataset:
Table 5. Probit **on Private School Attendance**

|**Explanatory**|**Coefficient**||**Marginal**|
|---|---|---|---|
|**Variable**|||**Effect**|
|Per capita income|0.78|*|0.064|
|Years of schooling of head|0.03|*|0.002|
|Area_(rural)_|0.80|*|0.046 +|
|Age|0.16|*|0.014|
|Age squared|0.00|*|0.000|
|Gender_(female)_|-0.12|**|-0.010 +|
|Number of rooms|0.09|*|0.008|
|Floor_(notfinishedfloor)_|0.40|*|0.037 +|
|Sewage_(notsewage)_|0.32|*|0.024 +|
|Number of Children|-0.10|*|-0.008|
|Trigger Variable|-0.09|*|-0.008|
|Constant|-7.56|*||

_Source:_ Own calculations based on ENIGH 96 and DGPyP, SEP

* Significant at 5%

** Significant at **10%o** _Italics_ indicates the reference category for dichotomous variables

_(+)_ dF/dx stands for the discrete change in the dummy variable from 0 to I The first column on table 5 has the coefficient and the second shows the marginal effects as estimated from the probit.<sup>7</sup> Notice that all explanatory variables are significant at 5% level, except for gender. In addition, all explanatory variables show the expected sign on the probability to attend private school. For instance, the probability
the hollow points in Figure 1 for the 1990-1994 period for the population aged 15-54, the effect is quite small at most (relatively lower) mortality levels and only meaningful in the case of very large mortality events. Indeed, the points on the right of the graph are data from Rwanda—in the midst of a genocide at that point. While feasible to implement this approach for the adult population as a whole, our experience was that this adjustment became very unstable when considering more narrow age

> 5 Note that we also weight each sibling observation by the survey weight associated with the responding sibling assigned on the basis of the original sampling strategy.  Therefore, each sibling observation is weighted by the survey weight divided by the number of surviving female siblings.

> 6 Appendix 1 provides a simulation of how various approaches to weighting affect the results and reduce the biases, particularly when mortality and the number of siblings are correlated.  In addition, it shows how including the respondent herself in the mortality calculations is an important part of removing bias in the estimation of mortality.

6
H. C. Johnson, F. L. Oswald, D. A. Pinzón Hernandez, A. Tiwari, S. De Martino, and K. Trzesniewski. 2021. “Are growth mindset, mastery orientation, and grit promising for promoting achievement in the Global South? Psychometric evaluations among Indonesian adolescents.” _Manuscript. Revise and resubmit_ . USA: University of Illinois at Urbana-Champaign, University of Zurich, University of California, Davis, and the World Bank. March 17 version available at: https://psyarxiv.com/dx4et

- OECD (Organisation for Economic Co-operation and Development). 2015. _Skills for Social Progress: The Power of Social and Emotional Skills_ . OECD Skills Studies. Paris, FR: OECD Publishing.

- Outes-León, I., A. Sánchez, and R. Vakis. 2020. “The Power of Believing You Can Get Smarter: The Impact of a Growth mindset intervention on Academic Achievement in Peru.” _World Bank Policy Research Working Paper_ 9141. Washington, DC: World Bank.

- Ray, D. 2006. “Aspirations, poverty and economic change.” in A. Banerjee, R. Benabou, and D. Mookherjee (eds.). Understanding Poverty. pp. 409–22. Oxford: Oxford University Press.

- Riley, E. 2022. “Role models in movies: the impact of Queen of Katwe on students' educational attainment.” _Forthcoming at the Review of Economics and Statistics_ . June 2021 version available at: https://bit.ly/3gP9nQQ

- Ross, P. H. 2019. “Occupation Aspirations, Education Investment, and Cognitive Outcomes: Evidence from Indian Adolescents.” _World Development_ 123: 104613.

- Ross, P. H., P. Glewwe, D. Prudencio, B. Wydick. 2021. “Developing Educational and Vocational Aspirations through International Child Sponsorship: Evidence from Kenya, Indonesia, and Mexico.” _World Development_ 140: 105336.

- Roy, S.,
we examine two aspects of utilization, namely measures of dietary diversity and consumption of a key macronutrient – protein.

Several salient findings emerge from the household-level food security analysis. Prior to and during the large increase in food prices from August 2007 to September 2008, the descriptive statistics reveal a decline in the real food consumption of approximately 33

> 8 While census data does not exist for Afghanistan, the pre-cursor to the census, a national household listing was undertaken from 2003 to 2005 by the Central Statistics Organization. This listing forms the basis for the current official population estimates and also serves as the sampling frame for the NRVA 2007/08.

> 9 The NRVA 2007/08 is the third round of the survey; fieldwork took place from August 2007 to September 2008. The first two rounds (2003, 2005) were each conducted during a single season, leading to seasonallybiased estimates, e.g., poverty estimates during or immediately after harvest will be lower than during lean periods. The NRVA 2007/08 was implicitly stratified over time during the year-long fieldwork so that estimates of wellbeing could account for seasonal variations.

> 10 FAO(2006)

4
Using a sample of 23 manufacturing sectors during the period 2002‐2010, we provide evidence on the extent to which competition in the GCC banking systems affects economic growth of financially dependent industries. We do so by using a panel data specification of the empirical setup developed by Rajan and Zingales (1998) to study the effects of financial development on growth, and adapted by Cetorelli and Gambera (2001), Claessens and Laeven (2005), Fernandez de Guevara and Maudos (2011) and Liu et al. (2014), among others, to assess the relationship between banking system competition and value added growth of financially dependent industries. The use of panel data follows Dell’Ariccia et al. (2008), who study the effect of banking crises on financially dependent industrial sectors. In our context, panel data are preferred to cross‐section regressions as in, e.g., Rajan and Zingales (1998), because of the limited number of observations in our sample, i.e. industry‐country data for GCC economies, as well as by the need to account for time‐variation in bank competition.

We then generalize our baseline framework in several directions to address a number of potential criticisms, which would apply to ours as well as to any similar study. First, to avoid a possible bias in our policy conclusions originating from the measure of bank competition employed, we use both structural indicators (five‐ and three—bank concentration ratio) and direct measures of market power (Lerner index and Boone indicator). Second, to avoid potential misspecification bias due to a potential nonlinear relationship between the degree of competition in the banking sector and real activity, as highlighted in the theoretical and the empirical literature on banking crises (see Martinez‐Miera and Repullo, 2010, and Beck et al., 2013, respectively), we test for the presence of nonlinearities by adding squared terms of our measures of bank market power. Third, since the baseline results can be driven by
groups, taking the median based on all private sector workers, irrespective of their age. The share of workers at high-productivity firms is very similar in the treatment and control groups. Finally, in the bottom panel we examine the industry composition of treatment and control workers. Again, we find very small differences suggesting that the treatment and the control groups are similar.

> 22To estimate the firm wage premia, we use all sample years of the linked employer-employee administrative data. We regress wages on individual and firm fixed effects, controlling for year fixed effects, age squared, age cubed, and firm size.

> 23The earliest age to retire was age 58 until 2011, but that possibility was abolished then. To retire at age 58, someone needed to have a long term employment relationship and at least 37 years of employment history. Note that all workers aged between 52 and 57 between 2012 and 2015 (our main estimation sample) could only retire at the normal retirement age, and so workers in our sample were not affected directly or indirectly through anticipation effects in our main sample. Nevertheless, workers who turned 58 before 2012 will have lower employment rate and higher retirement rate than workers who turned 58 after 2012. By restricting the treatment ages to 55-57 in our analysis we make sure our employment changes are not affected by the change in retirement rules instituted one year before our policy change.

16
independently and jointly, are relatively consequential. I discuss this in more detail by comparing the changes in real labor earnings. Unlike GDP per capita, real labor earnings in the model match transparently to the data.

The calibration of the model ensures that the labor earnings of all cohorts match the data in 2015. Besides, the earnings of the young in all years and those of the middle cohorts except in 1995 in the model are the same as in the data. Panel B of table 6 reports the relative labor earnings under the various counterfactual scenarios and in the data.

The figures in columns (1)-(8) of panel B are close to those in panel A. However, the actual figures in columns (9) and (10) vary considerably across the two panels highlighting the survey nature of the household data. The discrepancies are particularly substantial for Costa Rica. Like GDP per capita, labor earnings have grown substantially over the decades. Since 1995, the growth ranges from 50 percent in El Salvador to more than 600 percent in Costa Rica. Though smaller, the shift over the last decade is also not trivial.

First, let me consider the joint effect of the three channels. Together they provided support for earnings expansion in two of the three economies. For Costa Rica, this represents 24-35 of the actual increase. The channels are even more active in Panama. The thrust they generate accounts for more than the actual change. In contrast, the changes in barriers and preferences over time have led to a fall in earnings. The negative impact boils down to 6 and 41 percent of the actual change since 1995 and 2005 respectively.

Now, let's look at the channels individually. The findings are in line with the previous discussion. In Costa Rica, the human capital channel overpowers the negative effects generally spawned by the others. The labor market channel generates significant drag on earnings in Panama. However, the other channels more than offset it. The human capital channel is factors
Figure 11: Education profile of Temporary employees. (Mid-1990s/Mid-2010s) <!-- Start of picture text --> 80%<br>70%<br>60%<br>50%<br>40%<br>30%<br>20%<br>10%<br>0%<br>Argentina Brazil Chile Mexico El Salvador<br>Incomplete primary (starting point) Incomplete primary (ending point)<br>Primary (starting point) Primary (ending point)<br>Secondary (starting point) Secondary (ending point)<br>Tertiary (starting point) Tertiary (ending point)<br><!-- End of picture text --> Source: Own calculations based on Household surveys However, it should be noted that the improvement of the educational profile of workers is a generalized trend in the countries considered and cannot be considered a specific characteristic of non-standard employment since it is also observed in standard wage employment and self-employed workers. Statistics regarding the educational profile of standard employees are included in Annex II of the paper.

Figure 12 presents the Kernel distribution of the labor income per working hour by country and type of employment. When we analyze what has happened at the salary level and distribution in the period under analysis, two important conclusions emerge. On the one hand, a shift to the right of the wage distribution is observed in all the countries analyzed, indicating an increase in their average. This growth in wages is simply a consequence of the economic growth experienced by these economies. Note that this average wage increase is also observed in the counterpart of standard employment in all cases..6 The second trend identified as generalized in the countries of study is the increase in the variance of the wage distribution. In fact, in most of the countries considered, non-standard employment wages currently show a significantly greater dispersion than that registered a decade ago. The only two exceptions are Chile and Peru in which the
Finally, the average household-level crop cutting-based annual cassava yield estimate stands at 8,958 kg/ha across all sample households (Panel C), while the comparable D1, D2, R1 and R2 estimates are 5,208; 6,218; 5,798; and 4,671, respectively (Panel B). The estimation of Equation 3, as reported in Panel C of Table 6, implies that the diary and recall survey treatments, on average, underestimate cassava yield compared to crop cutting, as expected given the reasoning provided in section 3.4. The extent of foreknown underestimation, as a percentage of the crop cutting based yield, stands at 25 percent under D2, 40 percent under D1, 33 percent under R1 and 47 percent under R2. The inter-relationships between the 4 core treatment arms are the same as those reported in Panel B.

Nevertheless, the average crop cutting-based yield estimate, which should be understood as the _upper-bound_ for the cassava yield realized on the farm during the 12 months of interest, is still significantly lower than the FAOSTAT estimates shown in Figure 1, and the MoAIWD APESbased 2015/16 national cassava yield estimate of 17,564 kgs/ha.<sup>34</sup> The latest (2014) FAOSTAT estimate of national cassava yield in fact stands at 24,800 kgs/ha – nearly three times the size of the CVIP crop cutting-based yield estimate, and four times the size of the D2-based counterpart.F<sup>35</sup>

# **6. Conclusions**

In household and farm surveys across the low- and middle-income countries, the prevailing (and most cost-effective) approach to data collection on the production of root, tuber and tree crops is to field a single visit and collect information either specific to an agricultural season or with a 12month recall. In turn, there is worry that the existing survey methods may elicit unreliable and incomplete information on harvests cutting across seasons, taking place over extended periods, and
the structure of employment and job tenure.

The bottom panel of <u>Table 5</u> shows the estimation of the impact of ICT-related technological change on the probability of having jobs of different duration (as in equation 5). We use the growth rate in the per capita ICT capital stock, derived from the KLEMS database (Jorgenson 2012), as a proxy for the penetration of technological innovations and digitalization in the economy. The estimations demonstrate an overall positive association between a higher ICT capital stock and the share of short- and medium-tenure jobs. The ICT-related technological change appears to increase these shares more among female, better-educated, and more senior workers. Shorter job tenure among better-educated workers may reflect increased job mobility and voluntary movement to better job matches; the larger share of short-term jobs among senior workers could indicate higher dismissal 22
. Additionally, large commercial banks and multilateral development banks are beginning to issue gender bonds with concessional elements. Blended finance instruments show promise in benefitting larger women-led businesses. However, there is a lack of robust impact evaluations for these products.<sup>22</sup> One notable exception is a recent study by Aydin et al. (2023) that used quasi-experimental methods (synthetic difference-in-differences) to analyze the impact of a blended finance program for female entrepreneurs in Türkiye. The program provided credit lines to banks, risk mitigation through a first-loss risk cover, and technical assistance. The study found that participating banks significantly increased lending to female entrepreneurs, and female clients of treated banks experienced positive outcomes such as increased borrowing, investment and business performance.

19 Friedson-Ridenour and Pierotti (2019) demonstrate, based on answers to qualitative surveys, that women in Ghana may choose to conceal income from their husbands and might even prefer to limit their business expansion if it jeopardizes their ability to secure economic support.

20 Several studies indicate that women are less likely than men to participate in competitions; however, they are more likely to enter competitions when they are competing against other women rather than men (Campos et al. 2019). This suggests that designing women-only competitions might significantly increase participation.

21 Cai and Szeidl (2022) found that the positive effects of a loan program in China were offset by negative impacts on competitors that did not receive the loan. This suggests that financial expansion programs should carefully consider possible negative spillover effects on firms that are not program participants.

22 Several large initiatives are focused on channeling funding to women entrepreneurs. Two examples are the Women Entrepreneurs Finance Initiative (We-Fi) and the Women Entrepreneurs Opportunity Facility (WEOF). WeFi invests in the design and evaluation of interventions that increase WSMEs’ access to finance, training, mentorship, networks, and markets, and it works to improve the enabling environment. As of 2022, it has provided $1 billion in direct financing for women entrepreneurs and mobilized
in terms of market competition, gender equality, upward mobility, and trust. As in OECD (2011), however, they base the analysis on self-perceived status.

Fischer and Torgler (2007) use data for 26 countries from the 1998 International Social Survey Programme to examine the association between relative income position and several measures of social capital, such as generalized trust, confidence in institutions, compliance with social norms, and civic engagement. Relative position is measured as the difference between an individual’s income and the reference group income at the aggregate level (national or regional). They find that relative income matters for most measures of social capital, such that social capital rises with an improved relative income position and declines with a disadvantage in the relative income position. The strongest effect is observable for happiness, compliance with social norms, and generalized trust.

Cárdenas, Kharas and Henao (2011) are among the few studies looking at how absolute income levels relate to values. They define the middle class as people with per capita daily income falling between $10 and $100 in PPP terms, and analyze the middle class’ attitudes and values using the World Values Survey data for Peru. Contrary to previous findings, the authors suggest that the middle class in that country sees taxes as a redistributive transfer from them to the poor and are not inclined to support them. Furthermore, the middle class was found to have a high preference for free markets and support for private industry and competition. Their results also show a relative decline in the support for state-owned enterprises and the government as the owner of business, and a primacy of growth policies, which suggests that the middle class may be optimistic about their own potential but skeptical of the role of the state. The income variable is however characterized by strong measurement errors as it is based on large income bands. Moreover, only 1 percent of the Peruvian population earns above U$100 a day, which questions the representativeness of the population sample they use to estimate the
Policy Research Working Paper 7835

# **Abstract**

Creating productive jobs is one of the greatest challenges in Ghana. This paper looks at job creation and its relationship with firm productivity and the quality of jobs among registered firms in the Ghanaian private sector, based on the 2013 World Bank Enterprise Survey. The study looks at the typology of firms in the industry and service sectors, identifying those that have created the most jobs, and the relative quality of these jobs in terms of productivity and firms’ average wage bill. Although the formal private sector employs only a tiny share of total employment, the results show that larger and older firms account for the majority of workers, and formal jobs density is highest in Accra (Accra Metropolitan Area and Tema). Large firms also pay higher wages on average, are more productive, and account for most of the aggregate net formal job creation between 2010 and 2012. However, the relationship between size and productivity is positive and statistically significant, mostly driven by the upper part of the firm size distribution, pointing to potential market segmentations as micro, small, and medium firms create fewer jobs and are less productive. Removing barriers to the growth of micro, small, and medium size enterprises, and to the allocation of resources toward more efficient firms should be a key priority for policy makers.

This paper is a product of the Social Protection and Labor Global Practice Group. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The authors may be contacted at dfrancis@worldbank.org and mhonorati@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished
the private sector could reflect more precarious employment relations among Iranian women. As shown in Table 8, while women working as private sector employees have lower probability to be employed in micro-businesses, they have significantly shorter job tenure compared to their male counterparts, which possibly puts them at a disadvantage in times of crisis. Motherhood and maternity related leave/inactivity spells could further play a role in determining observed differences between men’s and women’s tenure and experience. Moreover, prevailing gender norms could further reinforce women’s disadvantage on the labor market during recessions. As evidenced in the World Values Survey, close to 70 percent of Iranians believe that men should have more right to a job than women when jobs are scarce (Figure 3).

**_Table 8: Changes in the distribution of_** **_<u>private sector employees by firm size, tenure and experience by gender</u>_**

|**2019-20**|**2**|**020-21**|**D**|**iff yoy**|
|---|---|---|---|---|
|**men**<br>**women**|**men**|**women**|**men**|**women**|
|**Firm size**|||||
|1-4<br>54.4<br>47.0|55.3|43.4|0.9|-3.6|
|5-9<br>18.7<br>22.9|18.2|25.5|-0.5|2.5|
|10-19<br>11.0<br>16.0|10.8|16.0|-0.2|0.1|
|20-49<br>
(0.01)|
|N|674|645|1319|144|200|344|2583|1754|4337|

_Note:_ Standard errors in parentheses; * denotes the male-female difference is significant at 10%, ** at 5%, *** at 1% level. The estimates for Ghana refer to individuals whose main occupation is in agriculture, while the estimates for Malawi and Nigeria refer to individuals who worked at least one hour in agriculture during the reference week (see footnote 14). Based on the Ghana and Malawi Agricultural Labor Surveys and Nigeria GHS Panel Wave 3.

The increase in farmers’ employment between the start and the end of the season (reported in Table 1) may reflect changes in the self-reported intended use of output. However, since not all individuals were

> 22 It should be noted, however, that the estimates for Ghana and Malawi are not nationally representative – so the differences across countries are partly driven by the purposive selection of the districts (which were more commercialized and connected to markets in Ghana than in Malawi).

14