rafmacalaba/data-use-mentions-extended huggingface dataset:
- 16 -

In the clusters in Vietnam and Tanzania, we also offered on-site training several months after the classroom training was completed.<sup>9</sup> The assignment to on-site treatment was random and independent of the random assignment to the classroom training. Thus, some entrepreneurs received both types of training. The follow-up survey was conducted a year later in Cluster 2, but in the other clusters, it was conducted only three months after the on-site training was completed.

From these experiments, we have learned that entrepreneurs of MSEs have little awareness of basic management practices, that they soon understand the usefulness of such practices and become willing to learn how to apply them, and that roughly half of the participants put the new knowledge into practice. Indeed, in all these clusters, the estimated impacts of the training effects on the adoption of various management practices that were taught in the program are positive and statistically significant. Another impact of the training program is found on the longevity of the firm. In Cluster 2, while not a few firms in the control group stopped operation or completely closed down, there was no incidence of exit among the participants. The difference was statistically significant.<sup>10</sup> As shown in Table 2, the estimated effects of training on the participants’ value added are insignificant or marginally insignificant, except for the on-site training in Tanzania. Note, however, that the follow-up data in Vietnam and Tanzania were taken only six months after the classroom training and three months after the on-site training was completed.<sup>11</sup> It is no wonder that the estimated effect is statistically weak. Moreover, these estimates neglect to take into account the favorable effect of the training on non-participants through knowledge spillovers. Thus, the estimated effect on value added is likely to be only a small part of the social benefit of the training program.

In our observation, participants expressed deep appreciation to the management training programs almost without exception. Suzuki and Sonobe
takes place between September and November. Following the main harvest, food stocks gradually decline until the lean season (MayAugust) that is typically characterized by lower food reserves, low demand for agricultural labor and rising food insecurity. The magnitude of these seasonal patterns is largely determined by the quality of the rainy season and drought conditions therefore exacerbate lean season food insecurity peaks. The lagged effect of the rainy season quality on food consumption is a feature of interest because it implies some degree of predictability of the forthcoming impact on households as soon as the quality of the RSQ is observable, which can be exploited to support early action.

When tested against historical data, the prediction model produces national food insecurity estimates with a mean absolute error of 1.2 p.p., with historical rates ranging between 29% and 42% over the period 2011-2015. At the regional-level, model predictions yield a mean absolute error of 4.9 p.p. and a correlation coefficient of 0.84. More importantly, the methodology allows to uncover the fact that inter-year variations in rural

> 3Source: authors calculations based on the 2012 Food Security Monitoring Survey.

5
frequency of antenatal care visits, significantly lowers perinatal mortality, and pays dividends even among uneducated and low socioeconomic groups.

The previous evidence suggests that involving men in reproductive healthrelated issues has a positive effect on women’s welfare. However, the magnitude of this effect and its external validity are difficult to assess because research has been limited to a small number of country case studies.

# **<<B>>** _Reducing Domestic Violence_

In recent years, there has been a growing recognition that the role of men is crucial in changing unequal power relations. In particular, actions that involve men in movements to end violence against women focus on men’s roles and responsibilities and emphasize men as part of the solution to combat gender violence have received increased attention. Local, national, and international laws, conventions, and agreements define genderbased violence and legislate against those who use it. There has been more public education, awareness, and acceptance of the problem and a larger number of institutions acting in accordance with the laws.

The evidence in the previous section indicates that empowering women is not always a solution to eradicate gender violence. There is growing awareness that men can play a significant role in ending violence; thus, violence prevention programs should be addressed to men. Reviews of the literature suggest that sexual assault prevention programs for college men can effectively improve attitudes that may put men at risk for committing violence against women, although these attitudinal changes are often limited to periods of a few months. In contrast, programs that focus only on providing information have not been found to be effective. The evidence suggests that these programs are more effective in all-male groups. For example, Brecklin and Forde (2001) conducted a comprehensive meta-analysis of 43 college rape prevention program evaluations and concluded that both men and women experienced more beneficial changes in single-gender groups than in mixed-gender groups.

The only experimental evidence on the impact of women’s economic status on domestic violence comes from a randomized intervention combining microfinance with violence education in South
normal distribution: 2 0 1 , where, represents a univariate truncated � normal distribution with mean cc,h,tt, variance gg2GGh  , and lower and upper bounds ggGGh 0, and 0, respectively. 22 We account for four important results regarding Pearson’s correlation coefficients pooling our original 1980–2014 ggGGh  uu ~TTNN�μμ ggGGh , σσ , ππ , ππ TTNN(∙) μμ σσ ππ ππ observations by the studied country classifications. First, the significant correlation coefficients of the average growth rate of the Gini coefficient and the average growth rate of per capita consumption vary between -0.077 and -0.048 across the studied country categories. Second, in the case of the growth rate of the Gini coefficient and the growth rate of GDP per capita, all the correlation coefficients are found nonsignificant across the country classifications whereas they vary close to zero in magnitude: from -0.68 to 0.067. Third, few significant correlation coefficients between the Gini coefficient growth rate and the growth rate of the mean income are found across the country typologies: 0.14 pooling all country observations, 0.181 for NROC economies, 0.16 for MOGCs, and 0.4 for LOGCs. Fourth, all the correlation coefficients of the growth rate of the Gini coefficient and the growth rate of the mean income become almost null and/or statistically nonsignificant across the study typologies when we complete our 1980–2014 panel data set using per capita consumption growth rates—or GDP per capita growth rates in the alternative case.

Page **12** of **45**
**Table 3: Effect of the Interventions on Behavior Change**

||**Province lev**|**el intervention**||**District leve**|**l intervention**||
|---|---|---|---|---|---|---|
||**Mass med**|**ia treatment**|**Community tr**|**eatment sample**|**School co**|**mponent sample**|
||Control mean|Effect of treatment|Control mean|Effect of treatment|Control mean|Effect of treatment|
|**Handwashing facilities**|||||||
|HW Facilities stocked with water and soap|0.653|-0.019|0.653|0.032|0.67|0.062|
|||(0.057)||(0.048)||(0.043)|
|Water and soap anywhere in the house|0.787|-0.025|0.787|0.0267|0.768|0.065**|
|||(0.040)||(0.037)||(0.032)|
|||||||[8.4%]|
|**HW hand cleanliness**|||||||
|Hands Cleanliness Index|7.527|-0.178|7.527|0.278*|7.403|0.210|
|||(0.166)||(0.161)||(0.151)|
|||||[3.6%]|||
|**Self-Reported handwashing behavior**|||||||
Policy Research Working Paper 7686

# **Abstract**

This paper investigates differences in the composition of employment between exporting and non-exporting firms. In particular, it asks whether exporting firms hire more engineers relative to blue-collar workers than non-exporting firms. In a stylized partial-equilibrium model, firms produce goods of varying quality and exporters tend to produce higher quality goods, which are intensive in engineers relative to blue-collar workers. Firms are heterogeneous and more productive firms become exporters and have a higher demand for engineers. The paper provides causal evidence in support of these theories using the Chilean _Encuesta Nacional Industrial Anual_ , an annual census of manufacturing firms. The results from an instrumental variable estimator suggest that Chilean exporters indeed utilize a higher share of engineers over blue-collar workers.

This paper is a product of the Office of the Chief Economist, Latin America and the Caribbean Region. 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 dlederman@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 papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
frm IDs||11,453|
|Share of observations with 0 months worked per year||19.0%|
||**Pane**|**l B: Firm panel**|
|**_Outcomes_**|||
|Total employment (log)|4.6|2.4|
|Total real wages (log)|11.8|2.1|
|Avg. wages (log)|7.8|0.6|
|Net revenue (log) (2009-2014)|59.9|103.5|
|Materials (log) (2009-2014)|2.4|1.5|
|Materials per worker (2009-2014)|-1.1|1.1|
|Capital (log) (2009-2014)|3.5|1.0|
|Capital per worker (2009-2014)|0.0|0.6|
|Labor productivity (2009-2014)|60.5|105.4|
|Proft rate (2009-2014)|-1.5|1.6|
|**_Firm shock_**|||
|Firm shock in 2008 (negative of growth in GDP of destinations)|-3.2|2.7|
|Total number of frm-year observations||119,189|
|Total number of unique frm IDs||15,087|

_Note:_ The worker-level statistics are based on the sample of workers in firms with a non-missing GFC firm shock measure in 2008 used in the main regressions. For Bolsa Familia, unemployment insurance, and training programs the statistics are based only on beneficiaries. Real wages are expressed in local currency in 2010 prices. The firm-level statistics are based on all firms with non-missing GFC shock measure in 2008 used in the main regressions. All statistics for which a time period is not shown in parentheses cover the 2009-2017 period.

34
# **2. Literature on Stability of Preferences**

There are a small number of studies that examine the temporal stability of contingent valuation and choice experiment studies but the results on the stability of preferences are mixed. Brouwer and Bateman (2005) studied the temporal stability of WTP responses from two contingent valuation studies (on flood control and wetland conservation) administered five years apart. They find that when examining WTP values over an extended time period, there is a statistically significant decrease in how people value flood control and wetland conservation attributes over time. They attribute these results to the five-year gap in the survey administration, which is much longer than the test-retest period that most researchers use, and also to the utilization of expanded models to include more, ad hoc transitory factors.

Price et al. (2016) and Bliem et al. (2012) find differing results from Brouwer and Bateman (2005) in their analysis of the stability of WTP values obtained from stated preference surveys regarding the health effects of tap water consumption. Price et al. (2016) conducted their survey in 2004 and again in 2012 using multiple survey formats. Their findings show that there is no significant difference in WTP between the two survey formats, and they support the transfer of non-market benefits over extended time periods. Bliem et al. (2012) test for the temporal stability of individual preferences by using two identical surveys for a restoration project of a stretch of the Danube River in Austria repeated over a one-year period. The researchers find that the preferences are stable across the one-year time frame.

Mørkbak and Olsen (2014) test the reliability and stability using an incentivized test-retest choice experiment. In their study, they use a choice experiment for a market good with real economic incentives, and sample respondents using the exact same questionnaire twice within a two-week lag time. Analysis of the data shows that error variances between the two identical surveys do not differ significantly, but the larger the utility difference in a choice task, the larger the probability
!-- End of picture text --> Source: Own elaboration based on IES. Notes: Weighted average includes Mozambique, Zambia and Zimbabwe.

The difference in average sales and profits by firm types masks the high variance, and significant overlap, in the distributions. LE-SE firms have the lowest average monthly sales (250 USD PPP adjusted) as compared to HE-SE (600 USD) and employers (800 USD) (Figure 15, Panel A). However, an exploration of the left tail of the distribution shows that while half of LE-SE firms sold, on average, less than 200 USD in the previous month, a significant share of HE-SE (25 percent) and employers (30 percent) also had low sales. At the other extreme, 35 percent and 30 percent of HE-SE and employers, respectively, sold at least 600 USD in the last month on average while the share is 10 percent for LE-SE. When accounting for firm costs, average profits are particularly high for employers, earning an average of 302 USD monthly as compared to 31 USD for LE-SE and 42 USD for HE-SE. However, there is a bimodal distribution among employers, where profits for the larger sub-group is similar to average profits of the other firm types (Figure 15, Panel A).

On a per worker basis, HE-SE stand out as having higher and more concentrated profits, a proxy for productivity, than the other firm types. The average monthly value of sales per worker is 464 USD in HE-SE firms, as compared to 224 USD and 276 USD for LE-SE and employers, respectively (Figure 15, Panel B). LE-SE and employers also have a similar distribution of sales per worker. The similar pattern between these two firm types is because LE-SE combine a low value of sales with a workforce of small size. Employers, on the other 30
5

# **A** **_._** _Trade in goods and services_

Five general features of Turkey’s long term trade performance since 1985 stand out. First, except for contraction in 1999, the value of total exports of goods and services has been steadily expanding at the average rate of growth (least square estimate) of 10 percent over 19862004.

Second, imports were highly volatile over 1986-2004 and strongly correlated with GDP growth indicating that exchange rate crises and sharply falling incomes in 1994, 1999 and 2001 have been responsible for contraction in imports (Figure 1). Bursts or implosions in GDP growth rates in nominal terms accompanied similar changes in imports. The coefficient of correlation of annual changes in imports of goods and services and GDP growth rates in 1985-2003 was 88 percent. The same coefficient for exports of goods and services and GDP was 35 percent.

**Figure 1:** _Annual rates of growth in value of exports, imports and GDP in 1990-2004 (in percent)_

<!-- Start of picture text --> 60<br>50<br>40<br>30<br>20<br>10<br>0<br>-10<br>-20<br>-30<br>Imports of goods and services GDP Exports of goods and services<br>1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004<br><!-- End of picture text --> Source: Derived from the World Bank’s Development Indicators database.

Third, Turkey’s integration and dependence on global markets for goods and service has significantly increased over the last decade. Exports of goods and services as percent of GDP (both in current prices) almost doubled from an average of 16 percent in 1985-90 to 30 percent in 2000-2004. Trade in goods and services in terms of the GDP strongly expanded in the 1990s. The corresponding ratio of 60 percent
belongs was attributed, as was the case with transfers for early childhood care and school meals. For Más Familias en Acción and Colombia Mayor, the incentive value provided by the government to its beneficiaries was assigned, according to the municipality or department in which they reside.<sup>36</sup> Programs, such as rate subsidies or interest forgiveness, were excluded since access to each of these loan types and debt forgiveness depends on the score from the Targeting Selection System (SISBEN III). Programs targeted through the SISBEN, such as BEPS or Ser Pilo Paga, were also excluded, although their magnitude is low.<sup>37</sup> Likewise, housing or interest rate subsidies for the purchase of housing, rural housing, or income generation programs in rural areas were not considered.

As far as indirect taxes are concerned, it is assumed that consumers exclusively pay the burden of indirect taxes. The amount paid in respect to indirect taxes was estimated by applying the rates established in law to each article present in the ENPH, which was acquired from a formal retailer. Additionally, given the existence of informality and goods excluded from the payment of this tax, the Cost-Push model was used to estimate the “embedded VAT” to finally calculate the effective tax rate for VAT (calculated as the total VAT collections divided by total private consumption by households). For the national consumption tax and taxes on alcohol and tobacco consumption identified in the ENPH, only the rates established by law were used, which allowed estimating the direct burden of these taxes on households.<sup>38</sup>

> 33 The CREE replaced employers’ contributions for their workers with incomes below ten monthly minimum wages.

> 34 For the details on the tax law applicable to direct taxes and social security contributions, see annex II , in Nuñez et, al. (2019).

> 35 The only exception is victimization transfers, the value of which was taken directly from the survey having been unable to clarify
**Nigeria**|2004-|$438|Niger Delta|
|**Pakistan **|1971|$275|Bangladesh|
|**Pakistan **|1974-77|$280|Baluchistan|
|**Russia**|1999-2001|$1613|Chechnya|
|**Sudan**|1983-2005|$293|South|
|**Turkey**|1984-|$2091|Kurdistan|
|**Yemen**|1994|$443|South|

_Source:_ conflict data are drawn from Gleditsch et al. (2002); income data are from World Bank (various), with missing figures taken from Maddison (2009).

place (Indonesia, Yemen). The other eight conflicts broke out in petroleum-rich regions of countries that did not cross the $100 per capita threshold – either because oil had been discovered but not yet extracted (in PakistanBangladesh, Bangladesh-Chittagong Hills, Nigeria-Biafra, and Sudan), or because oil was relatively scarce at the national level, even though it was abundant in the secessionist region (in China, India, Pakistan-Baluchistan, and Turkey).

Interestingly, none of these conflicts occurred in Latin America. In Latin America, oil is statistically associated with governmental conflicts but not separatist ones. This is not because Latin American petroleum has unusual properties, but because the region is uniquely secession-proof: there have been no separatist conflicts in Latin America for over a century. For more on the Latin American anomaly see Ross (2010). Other types of mineral wealth, including copper and gold, have sometimes been linked to secessionist movements in exceptionally poor regions – for example, on the Papua New Guinea island of Bougainville, and in Indonesia‘s West Papua province (M. Ross 2004a).

4
.023|1362|
|Egypt, Arab Rep.|0.588|0.018|2934|Senegal|0.588|0.040|354|
|Jordan|0.551|0.015|5047|Sierra Leone|0.515|0.026|1139|
|||||South Africa|0.501|0.043|578|
|South Asia||||Tanzania|0.484|0.030|1213|
|Afghanistan|0.591|0.011|4857|Togo|0.519|0.038|410|
|Bangladesh|0.609|0.018|1712|Uganda|0.552|0.021|1710|
|India|0.631|0.003|72192|Zambia|0.620|0.018|2011|
|Nepal|0.588|0.024|1317|Zimbabwe|0.625|0.037|518|
|Pakistan|0.679|0.009|5583|||||

_Notes_ : This table presents the sibling correlation estimates for each of the 53 developing countries in the Demographic and Health Surveys (DHS) using the 1990s birth cohort sample.

42
enumerators to all the plots. Even if they were, the operational costs and travel time required to record GPS measures for all plots are likely to be prohibitive for most survey operations. This raises some analytical concerns, in the form of biased estimates, if the plots that are not measured are systematically different from the ones that are measured. We do find evidence of such bias in our data, and in the next section we discuss how we dealt with the issue.

# **3. Data source and descriptive statistics**

The data for this paper come from the Uganda National Household Survey (UNHS) round implemented by the Uganda Bureau of Statistics (UBOS) in 2005-2006. The UNHS is a multi-purpose household survey with a sample of 7,500 households, selected following a stratified sample design that identified 753 enumeration areas (UBOS, 2009). One special feature of this survey that makes our analysis possible is that it contains plot level information on agricultural land area measured through both GPS and farmers‟ own estimates.

Some 5, 714 of the survey households are located in rural areas and cultivate land. The total number of plots with self-estimated measure is 13,959 and about 65 percent of these (9,173 plots) have a corresponding GPS measure<sup>3</sup> . The agricultural production section, however, only contains information gathered at the household/farm level. Thus, the analysis in this paper is carried out partly at the plot level, and partly at the household/farm level. We use the former to analyze the difference between land area measurement using farmers‟ estimate and GPS, since it is at the plot level that the two measures are collected. The household/farm level analysis is more suitable to investigate the consequences of the bias in land measurement on the IR, since key farm input and output data are only available in the survey at this level, not allowing the calculation of plot-specific productivity measures.

To be able to run the analysis maintaining