rafmacalaba/datause-encoder-data huggingface dataset:
# **Table 6**

Dependent Variable: Female Labor Force Participation Rate

|VARIABLES|(1)<br>OLS-FE|(2)<br>OLS-FE|(3)<br>IV-FE|(4)<br>IV-FE|(5)<br>IV-FE|(6)<br>IV-FE|(7)<br>IV-FE|(8)<br>IV-FE|(9)<br>IV-FE|(10)<br>IV-FE|
|---|---|---|---|---|---|---|---|---|---|---|
|POST|0.04|-0.02|0.10|1.32|-0.34|-0.35|1.00|2.76|-0.34|-0.35|
||(0.22)|(0.24)|(5.45)|(5.24)|(0.35)|(0.34)|(6.80)|(6.30)|(0.35)|(0.34)|
|Time|0.11**|0.15**|0.24|0.13|0.28***|0.26***|0.18|0.03|0.28***|0.26***|
||(0.05)|(0.06)|(0.41)|(0.38)|(0.05)|(0.06)|(0.52)|(0.46)|(0.05)|(0.06)|
|Timesq|0.01***|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|
||(0.00)|(0.00)|(0.00)|(0.00)|(0.00)|(0.00)|(0.00)|(0.00)|(0.00)|(0.00)|
|WorkingAgePop||0.00||-0.00||-0.00||-0.00||-0.00|
|||(0.00)||(0.00)||(0.00)||(0.00)||(0.00)|
|rGDP||0.00||0.00||0.00||0.00||0.00|
|||(0.00)||(0.00)||(0.00)||(0.00)||(0.00)|
|Observations|1,419|1,322|960|960|960|960|960|960|960|960|
|Number of Countries|72|72|62|62|62|62|62|62|62|62|
|R-squared|0.07|0.19|||||||||
|Partial R-squared|||0.01|0.01|0.41|0.41|0.01|0.01|0.41|0.41|
|Hansen J p-value|||0.40|0.39|0.48|0.35|0.58|0.57|0.48|0.36|
|Kleibergen-Paap F<br>statistic|||8.40|8.12|1945.14|1934.15|2.79|2.71|1904.93|1898.33|

Note: Robust and clustered standard errors at the country level are in parentheses. *** p<0.01, ** p<0.05, * p<0.1. POST is instrumented with the debt-to-GDP ratio, terms of trade, and five-year change in democracy score in columns (3) and (4). In columns (5) and (6) the instruments also include lagged POST. POST is instrumented with external debt-to-GDP ratio interacted with the change in world interest rates, terms of trade, and five-year change in democracy score in columns (7) and (8). In columns (9) and (10) the instruments also include lagged POST.

32
Figure 15: Sweden saw a big increase in the number of newly registered limited liability companies after the financial crisis <!-- Start of picture text --> 20<br>18<br>16<br>14<br>12<br>10<br>8<br>6<br>4<br>2<br>0<br>2004 2005 2006 2007 2008 2009 2010 2011 2012<br>Denmark Finland Norway Sweden Iceland<br>1,000 working-age people (15-64)<br>Number of newly registered companies per<br><!-- End of picture text --> Source: World Bank Group Entrepreneurship Database, 2013 edition.

Having come through the crisis, Sweden now faces the challenge of sustaining and boosting entrepreneurship. Although the creation of new enterprises is crucial to foster economic and employment growth, firms’ ability to grow is even more important. In Sweden 87 percent of manufacturing firms are microenterprises—firms with fewer than 10 employees. Among OECD countries only Poland, the Czech Republic and Greece have higher percentages of microenterprises in manufacturing (Figure 16).

The presence of a high share of microfirms is not a bad sign in itself. Small businesses can be important drivers of growth and innovation and can contribute significantly to employment levels and employment growth. As several studies have shown, however, most of the observed economic growth is driven by the growth of existing firms rather than by the creation of new ones (Rajan and Zingales, 1998; Kumar et al., 1999). Understanding the conditions and institutional factors, including labor market regulations, under which firms can grow is therefore extremely important. Isolating the effect of labor market regulations from the effect of other factors in hampering firms’ growth in Sweden is beyond the scope of this paper. But a sign of their relevance seems to come from the smaller share of micro firms in manufacturing in countries with more flexible labor market regulations, such as Denmark (71 percent), New Zealand (69 percent) and the United States (60 percent).

30
# **Figure 4: Teledensity (total telephone subscribers/1000 people)**

<!-- Start of picture text --> 500<br>400<br>300<br>200<br>100<br>0<br>SACU Botswana Lesotho Namibia South Africa Swaziland<br><!-- End of picture text -->

**Figure 5: Phone Faults (reported faults/100 mainlines)**

<!-- Start of picture text --> 80<br>70<br>60<br>50<br>40<br>30<br>20<br>SACU Botswana Lesotho Namibia South Africa Swaziland<br><!-- End of picture text --> 11
# **5.2  Results**

Table 7, column 2 presents unadjusted probit estimates for the complete dataset of 993,401 observations. The results are all consistent with our expectations: The probability of a GSM cell tower location in a grid square increases significantly with population and the degree of competition, and decreases significantly with higher levels of installation and maintenance cost factors (higher elevation, steep slope, longer distance from the main road, longer travel time to the nearest major city).

Column 3 of Table 7 presents results from our MCMC estimation that adjusts for spatial autocorrelation. The large, significant spatial error estimate at the bottom of column 3 is consistent with significant spatial autocorrelation. As expected, the reduced data sample and MCMC adjustment change the coefficient estimates and substantially reduce the t-statistics. However, the signs and significance of the coefficients remain unchanged except for elevation, which retains the expected sign but loses significance.

Table 7, column 4, reports unadjusted probit estimates for the 400 100-km grid cells. These results are quite close to those in column 3, indicating that the differences in coefficients and t- statistics between column 2 and columns 3-4 are primarily due to reduction in the number of observations rather than spatial error. The small impact of the spatial error (despite its significance) may be due to a homoscedastic variance structure produced by our uniform weights matrix (Fleming, 2004; Anselin, 2002, Thomas, 2007).

Map a presented in Fig 2 documents the probability of cell phone coverage predicted by the probit estimates from our full spatial dataset (Table 7, column 2).

10
particular appear to have benefited most.<sup>18</sup> This is consistent with the descriptive statistics in table 3 that suggested that school attendance and boys’ work in agriculture are negatively correlated with each other. This could indicate that the school conditionality, by guaranteeing that children are in school at the moment they otherwise would be working in the field is helping compensate for the higher number of hours that older boys were working, when compared to their sisters, and their younger siblings. At the same time, there is evidence of increased intra-household specialization of older girls in nonagricultural activities and domestic work for households who received the productive investment package.

# _IV.2 Past academic achievement_

We now consider whether the program helped compensate for lags in past academic achievement, and in particular whether reductions in child labor are larger for children that were lagging behind. The variables we use to measure past academic achievement are a dummy variable indicating whether the child was below the grade level that corresponds to its age at baseline, and a variable indicating the number of years the child was below grade level at baseline. These variables are likely to capture innate capabilities, academic skills (or lack thereof), and past disadvantages that might have led the children to have lower academic performance than their siblings. For example, a child might have been disadvantaged because of a drought shock in early childhood that affected his or her cognitive development during a critical stage (see e.g. Alderman, Hoddinott and Kinsey, 2006). Such disadvantage might afterwards have been aggravated (or not) by resource allocation decisions of the parents. Or children with lower cognitive abilities might themselves have been more likely to drop out of school, and therefore might have higher child labor participation. On the other hand, parents of children with very low abilities might not make them work, as the returns to their work might be very low.

> 18 These findings resonate with findings from the randomized evaluation of the Mexican _Progresa (Oportunidades)_ program, as Skoufias and Parker, 2001 show significant reductions in labor participation for boys and significant decreases on leisure time for girls. Findings of another CCT program in Nicaraguan ( _Red de Proteccion Social)_ show larger reductions of child labor for older children (Maluccio, 2003).

15
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# TABLE 9

The demand for tasks, exports and export destinations (log employment) IV-FE

||(1)|(2)|(3)|(4)|
|---|---|---|---|---|
||export<br>intensity|average per<br>capita GDP|exporter<br>dummy|high-income<br>exporter dummy|
|A) Skilled and Unskilled Labor|||||
|log highly-skilled|0.33***|0.15***|0.53***|1.91***|
||(0.111)|(0.055)|(0.197)|(0.619)|
|log skilled|0.27***|0.12**|0.44***|1.56***|
||(0.085)|(0.050)|(0.146)|(0.556)|
|log unskilled|-0.36***|-0.34***|-0.57**|-3.95***|
||(0.136)|(0.041)|(0.226)|(0.461)|
|B) Production and Non-Production Labor|||||
|log production|0.02|0.01|0.03|0.15|
||(0.020)|(0.017)|(0.034)|(0.175)|
|log non-production|-0.02|-0.09*|-0.02|-0.95**|
||(0.048)|(0.046)|(0.080)|(0.466)|
|C) Tasks|||||
|log managers|-0.13|-0.01|-0.20|-0.21|
||(0.104)|(0.043)|(0.173)|(0.486)|
|log engineers|0.43***|0.15**|0.68***|2.08***|
||(0.139)|(0.064)|(0.248)|(0.716)|
|log services|0.13|-0.18***|0.22|-1.68***|
||(0.111)|(0.060)|(0.174)|(0.603)|
|log blue-collar|-0.37**|-0.38***|-0.60**|-4.37***|
||(0.151)|(0.046)|(0.250)|(0.516)|
|log maintenance|-0.09|0.07|-0.14|0.63|
||(0.112)|(0.066)|(0.184)|(0.728)|
|_N_|20544|20544|20544|20544|
|Firms|5226|5226|5226|5226|
|frm and year FE|Yes|Yes|Yes|Yes|
|log employment|Yes|Yes|Yes|Yes|
|industry-specifc trends|Yes|Yes|Yes|Yes|
|frm-specifc trends|Yes|Yes|Yes|Yes|
|imported inputs|Yes|Yes|Yes|Yes|

NOTES: IV-FE regressions of (log) employment on export intensity (exports/sales) and the average per capita GDP of a firm’ export destination. Columns (1): estimates of export intensity; column (2): estimates of average per capita GDP; column (3): estimates of an export dummy; column (4): estimates of a high-income export dummy. All regression include firm fixed-effects and year fixed-effects, log total employment (firm size), firm-specific trends, and the share of imported inputs. Data are from the Encuesta Nacional Industrial Anual (National Annual Industrial Survey), Chile 2001-2005.

23
# **Table 7: A comparison of domestic and international wage gaps unexplained by intrinsic worker productivity**

||**Domestic wage**<br>**discrimination**|**Wage ratios**<br>**w/o borders**|**Wage ratios**|**with borders**||
|---|---|---|---|---|---|
|**Comparison**|δ<br>+<br>1|(<br>)(<br>)<br>_n_<br>_s_<br>δ<br>δ<br>+<br>+<br>1<br>1|**_Re_ (****_equal_**<br>**_productivity_)**|**_Ro_ (****_observably_**<br>**_equivalent_) **|**Based on source**|
|White v. Black,US 1995|1.1||||Altonji and Blank(1999)|
|Others v. Sched. castes,India 1976|1.1||||Banerjee and Knight(1991)|
|Men v. Women,US 1995|1.3||||Altonji and Blank(1999)|
|Hawaii/Guam v. Micronesia 1997||~1.1–1.4|||Akee(2007b)|
|Max. ratio btw. US states 1999||1.4|||Table 5|
|Chinesev. Malay,Malaysia 1988|1.4||||Schafgans(1998)|
|Other v. Indigenous,Bolivia 1989|1.4||||Patrinos and Psacharopoulos(1993)|
|Men v. Women,Madagascar 2001|1.4||||Median|coeff.|on female,–0.33|
|Urban v. rural,43 countries 1999||1.4|||Pooled coeff. on rural,–0.3|
|US v. Puerto Rico 1999||1.5|||Table 5|
|US v. Mexico 1999|||~1.3|1.9–2.0|Table 2|
|US v. Italy,circa 1920||~1.5|||Williamson(1997)|
|White v. Black,US 1939|1.6||||Sundstrom(2007)|
|Asian v. African,Tanzania 1971|1.9||||Knight and Sabot(1991)|
|US v. Jamaica 1999|||~1.9|2.8–3.0|Table 2|
|US v. Bolivia 1999|||~2.7|4.0–4.1|Table 2|
|Men v. Women,Pakistan 2001|3.1||||Max.|coeff.|on female,–1.14|
|US v. India 1999|||~3.2|4.5–5.2|Table 2|
|New Zealand v. Tonga,2005|||4.9|6.1|McKenzie,Gibson,and Stillman(2006)|
|US v. Nigeria1999|||~8.4|11.7–13.4|Table2|
Serti, Francesco and Chiara Tomasi. 2007. “Self Selection and Post-Entry effects of Exports: Evidence from Italian Manufacturing firms.” LEM Papers Series No. 2007/20.

Van Biesebroeck, Johannes. 2005. “Exporting Raises Productivity in sub-Saharan African Manufacturing Firms.” _Journal of International Economics_ 67(2), 373-391.

Van Biesebroeck, Johannes. 2006. “The Sensitivity of Productivity Estimates: Revisiting Three Important Productivity Debates.” _Journal of Business and Economic Statistics_ ( _forthcoming_ ).

Wagner, Joachim. 2007. “Exports and Productivity: A Survey of the Evidence from Firmlevel Data.” _The World Economy_ 30, 1, 60-82.

World Bank, 2005. _Doing Business 2005._ Washington, DC. World Bank, 2007. _World Development Indicators_ , Washington, DC.

26
While all auditors were offered more expensive products, experienced auditors, especially those that claimed to have a lower offer from a competing bank, appear to receive a cheaper credit product.

Why do staff provide little information voluntarily and offer relatively more expensive products? Table 7 tries to address this question by reporting results from the staff survey. About 60 percent of the staff in each country have university degrees. We asked the same interest rate question as in Lusardi and Mitchell (2014) and Atkinson and Messy (2012) and found that 62 percent answer the question correctly. Despite servicing about 18 clients per day, 96 percent of the staff claims to voluntarily provide all the information related to products offered. Yet, their income is subject to incentive schemes that reward the number of sales of certain products. About 46 and 41 percent of the staff report being influenced by their incentive schemes when deciding which credit and savings products to offer respectively. This explains why clients are rarely offered the cheapest product that met their needs.

# **7. Conclusions**

This study follows the protocols in Giné and Mazer (2017) to assess the quality of information that financial institutions in Colombia provide to potential customers seeking savings and credit products as well as the adequacy of products that are offered and finds similar results to those in Mexico, Peru and Ghana. We find that consumers who do not actively engage the staff, are not provided enough cost information. In contrast, experienced auditors who were instructed to ask specific questions about the product if the staff did not disclose the information voluntarily end up better informed. This finding underscores the gap between enacted regulation and its enforcement and how this gap may persist as financial institutions have strong incentives to undermine disclosure initiatives.

In any event, financial disclosure regulation in Colombia could be improved. For example, basic guidance could be provided to consumers on the key questions to ask when looking for a credit or savings product. In addition, information could be provided more transparently as tested in a follow-up to this study in Mexico and Peru (Giné, Martinez and Mazer, 2017). Of course, lenders may choose in equilibrium to spend little time with low-income customers because they are expensive to service, but aggregate terms such as the APR and APY should be adequately disclosed voluntarily as required by law.

This study covers consumer credit and savings products contracted at the branch and may therefore be expensive to offer, especially to low-income populations. A promising avenue is the take-up of low-cost mobile or online savings accounts where interactive channels are available to provide information on a regular basis at a relatively low-cost, or access to financial products as a byproduct of government-toperson payment programs.

Finally, this study focuses on the disclosure of information during the period until the product is contracted (pre-sale period). While the terms of the credit products studied cannot be changed, those of 15
# **1. Introduction**

The lack of labor demand is the main problem in Sub-Saharan Africa (SSA), while labor supply is not a big problem. This consideration along with recent adverse terms of trade movements for SSA key export products call for flexibility of labor markets.

The labor market in Côte d’Ivoire has been deregulated but few studies analyze the possible existence of labor market distortions both before and after the start of reforms.<sup>1</sup> Rama (1998) analyzes wage misalignment in RCI. He concludes that minimum wages are no source of distortion in the Ivorian labor market; real minimum wages in 1996 accounted for only about 35 percent of their level 20 years earlier.<sup>2</sup> In this study we focus on two possible sources of labor market distortions in Côte d’Ivoire in the mid-late 1990s. First, we investigate the possible effects of unions on the individual income generation in the private manufacturing sector. Even though this sector involves only a small part of the labor force, it still plays an important role since a large part of exports originates from this sector, and since any export commodity dispersion is likely to come from this sector.<sup>3</sup> Second, we analyze the possible existence of efficiency wages arising from employer-size wage effects.

Furthermore, the paper aims at analyzing the characteristics of the small group of private manufacturing sector workers—who to some extent may be viewed as role models—and how they differ within and between occupational groups. This may have implications for educational policies, for example, and is an important complement to the household-based analysis by Verner (1999c), which found that union effects cannot be analyzed in the 1990s due to survey changes.

One reason for the lack of studies that look at union effects in RCI is that the topic can only be satisfactorily analyzed by firm level data. This paper presents one of the first studies of employer-employee data, the so-called Regional Program on Enterprise Development (RPED) data set on Côte d’Ivoire from 1995 and 1996. This type of data represents a clear advantage to prior studies of the labor market, which rely on household surveys that are rather sparse on

> 1 Appendix E contains an overview of labor market studies in RCI that makes use of regression techniques, based on individual data, to analyze wage/income generation.

> 2 This drop is in line with market average wages which fell 60 percent in the 1985-95 period (Verner, 1999). 3 Rama (1998) quotes ILO numbers, estimating 300,000 individuals as being union members in 1995 out of a total labor force of 7,063,000, which is equivalent to 4.25 percent of the entire labor force.  These numbers are only estimates and highly uncertain.

2
up of new restructuring mechanisms in Poland.

# 4. Structural policies to boost equitable growth

EMDEs have seen potential growth slow to 4.7 percent in the 2013-18 period, down by 1.2 percentage points compared to 2003-07 (Figure 8; World Bank 2018e). Part of the slowdown is due to lower productivity growth, attributable to several factors including slower investment growth; diminishing gains from factor reallocation as the pace of urbanization slows; and a stabilization of global value chains. Demographic trends have turned from tailwinds to headwinds as the share of the working-age population stabilized in EMDEs around 2010, following more than four decades of steady increases. At this point, all major economies face demographic trends that slow potential growth prospects: economies with rising working-age populations accounted for 19 percent of global GDP in 2013-17, sharply down from 60 percent of global GDP in 2003-07. At current trends, potential growth in EMDEs is expected to continue to slow, to 4.3 percent a year in the next decade, with 60 percent of EMDEs experiencing a slowdown. Demographic trends alone would account for almost one-half of this slowdown and would weigh most heavily on potential growth prospects in EAP and ECA.

Ambitious, credible reform agendas that improve productivity and boost human and physical capital are needed to offset the decline in potential growth over the next decade. Many EMDEs face similar barriers to reaching the efficiency frontier, including poor governance; inflexible labor markets; constraints on human capital arising from poor provision of education, training, and health-care; uncompetitive product markets; inadequate contract enforcement; and cumbersome regulations and tax frameworks. Breaking down these barriers is strongly associated with faster growth (Abiad et al. 2012; Berg, Ostry, and Zettelmeyer 2012; World Bank 2018e).

The benefits are greatest when there is an appropriate mix of policies supporting each other: the potential benefits of new road and port infrastructure to promote exports, for example, will be achieved only if customs and other border procedures are also streamlined. The timing and sequencing of reforms also matter: product and labor market reforms may be more effective when combined with monetary or fiscal policies that support demand (Bordon, Ebeke, and Shirono 2018; IMF 2019b). Some structural reforms may benefit growth but worsen income inequality, thus involving a tradeoff for policymakers that they may need to address by offsetting policies in other areas (Ostry, Berg, and Kothari 2018).

# 4.1 Evolution of structural reforms in EMDEs

Since the global recession, there have been reforms to strengthen business climates (which lost momentum since 2010), improve access to finance, strengthen financial supervision, reduce trade costs, and lower energy subsidies (which were mostly sustained). In contrast, governance has deteriorated in EMDEs and they have become less open to international capital flows.<sup>21</sup>

> 21 See IMF (2019b) for a complementary discussion of the evolution of structural reforms.