rafmacalaba/data-use-mentions-extended huggingface dataset:
are productive enough would have the capability of exporting. It is possible, then, that the strong positive association between productivity and participation in export markets reflects the selfselection of the better firms into export markets and not the effect of exporting on productivity. In fact, many empirical studies using plant-level data have found support for this alternative causal interpretation.<sup>1</sup> Yet, self-selection and learning-by-exporting are not mutually exclusive possibilities, as high-productivity firms that can afford the sunk cost of entry to export markets may, in principle, continue to improve their productivity as a result of their exposure to exporting. Several studies have found support for learning-by-exporting, even after controlling for selfselection effects.<sup>2</sup> Despite the large and growing literature on this subject, we believe that the lack of conclusive evidence on learning-by-exporting warrants further investigation. In this paper, we revisit a basic question: how to define learning-by-exporting? To answer this question we consider the parallels between learning-by-exporting and learning-by-doing. In his classical work on learning-by-doing, Arrow (1962) suggests two main characteristics of learning. First, “learning is the product of experience. Learning can only take place through the attempt to solve a problem and therefore only takes place during activity” (p. 155). Second, “learning associated with repetition of essentially the same problem is subject to sharply diminishing returns... To have steadily increasing performance, then, implies that the stimulus situations must themselves be steadily evolving rather than merely repeating” (pp. 155-6).

We believe that Arrow’s general characterization of learning applies to domestic firms

> 1 Bernard and Wagner (1997), Clerides et al. (1998), Bernard and Jensen (1999), Aw et al. (2000), Isgut (2001), Fafchamps et al. (2002), Delgado et al. (2002), Arnold and Hussinger (2004), Alvarez and Lopez (2004).

2
consumption and expenditure surveys (HCES) that are our main data source for the seven adequacy dimensions. Also, we outline how we harmonize the individual variables in these HCES to ensure comparability across countries.

# **_3.1 Housing Adequacy Dimensions_**

The construction of the _AHI_ is based on the aggregation of seven adequacy dimensions which have frequently been found to be a key determinant for socio-economic and health outcomes (cf. Section 2.2), which are the key dimensions reflected in the Agenda 2030, and which are consistently available in micro-level household surveys which are our primary data source (Section 3.2): (1) access to improved water; (2) access to improved sanitation; (3) adequate living space; (4) durable material and good structural quality; (5) security of tenure; (6) access to electricity; and (7) access to clean cooking. All seven adequacy dimensions are coded as dummy variables differentiating adequate access (1) and inadequate access (0). The following paragraphs outline how we define and operationalize adequate access and how we harmonize these variables across surveys. We apply a uniform coding framework that allows for comparability across countries (a full, countryspecific coding framework is available in the supplementary material upon request).

We align our coding of access to water (1) to the classifications of the WHO/UNICEF Joint Monitoring Programme (JMP). JMP defines improved drinking water sources as having the potential to deliver safe water by nature of their design and construction, including piped water, boreholes, or tube wells, protected dug wells, protected springs, rainwater, and packaged or delivered water (JMP 2020, Annex 1). We consider HHs that have access to improved drinking water to be adequate. We assume that HHs have inadequate access to water if they only have unimproved facilities at their disposal. Some countries’ HH surveys capture the difference in access to water for dry and wet season (e.g., Tanzania
Breadwinners and Caregivers: Examining the Global Relationship between Gender Norms and Economic Behavior<sup>∗</sup> Markus Goldstein<sup>†</sup> Paula Gonzalez<sup>‡</sup> Talip Kilic<sup>§</sup> Sreelakshmi Papineni<sup>¶</sup> Philip Wollburg<sup>‖</sup> Gender, Attitudes, Norms, Labor, Global [JEL] J16, J20, O12

> ∗We thank Rachael Pierotti, S Anukriti, Ha Nguyen and Lili Mottaghi for their helpful comments and guidance. This paper uses data from the Gender Equality at Home surveys - a collaborative effort between Facebook Data For Good, the World Bank and other development partners. We thank Samhir Vasdev, Safaa Amer, Bronwen Raff and Anna Lerner at Facebook Data For Good. We gratefully acknowledge the financial support from the World Bank Group’s Umbrella Facility for Gender Equality (UFGE) and the Office of the Chief Economist for the Middle East and North Africa (MNACE) under the regional Labor and Gender Research Programs. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent.

> †World Bank (on leave) `mgoldstein@worldbank.org`

> ‡World Bank and The Graduate Institute, Geneva `pgonzalezmartine@worldbank.org`

> §World Bank Development Economics `tkilic@worldbank.org`

- ¶World Bank Africa Gender Innovation Lab `spapineni@worldbank.org (Corresponding Author)`

- ‖World Bank Development Economics `pwollburg@worldbank.org`
Figure 3.16 Percentage of vocational upper secondary school enrollment by province, 2013 versus 2016 <!-- Start of picture text --> 60.0%<br>50.0%<br>40.0%<br>30.0%<br>20.0%<br>10.0%<br>0.0%<br>% voc 2013 % voc 2016<br>普普 Guangxi 普普 Shanghai 普普 Beijing 普普 Fujian 普普 Sichuan 普普 Hainan 普普 Anhui 苏普 Jiangsu 普普 Qinghai 普普 Zhejiang 普普 Hebei 普普 Yunnan 东普 Guangdong 普普 Total 普普 Henan 普普 Hunan 东普 Shandong 普普 Ningxia 普普 Tianjin 贵普 Guizhou 普普 Jiangxi 庆普 Chongqing 普普 Shanxi 辽普 Liaoning 普普 Xinjiang 陕普 Shaanxi Inner Mongolia 龙普 Heilongjiang 肃普 Gansu 普普 Jilin 普普 Hubei 普普 Tibet<br>普<br>普普普<br><!-- End of picture text --> _Sources_ : <u>http://www.moe.edu.cn/s78/A03/moe_560/jytjsj_2016/2016_gd/201708/t20170828_312534.html http://www.moe.edu.cn/s78/A03/moe_560/jytjsj_2016/2016_gd/201708/t20170828_312546.html http://www.moe.edu.cn/s78/A03/moe_560/s8492/s8494/201412/t20141216_181697.html http://www.moe.edu.cn/s78/A03/moe_560/s8492/s8494/201412/t20141217_181848.html</u> _Note_ : 2013 is the earliest year with provincial-level data.

Labor market returns do not lend support to the efficiency argument for the tracking policy. There is an argument that the tracking arrangement and selective promotion to tertiary education increases the efficiency of investment in education by matching the different levels and types of schooling with labor market need. There is however a lack of empirical evidence on this. The moderate labor market returns to higher education in recent years in China (World Bank, forthcoming) not only signal
of Table 4 shows that import barriers have a far more important impact than do subsidies on global agricultural trade as well, accounting for 85 percent of the trade-reducing impact of the three measures. Domestic support measures explain the rest, apart from a small contribution of the opposite sign by export subsidies. Freeing all

> 16 This 5 percent relative contribution to global welfare corresponds to an upper bound estimate, as the GTAP database does not differentiate non-coupled to production payments, and the GTAP model partially restricts the use of land in alternative agricultural uses (see Dimaranan and McDougall 2005; Keeney and Hertel 2005).
br>in large private sector organizations|

A well-known study by (Lazear 2000) uses individual-level worker data from a glass company and estimates a 44% increase in productivity after switching to a piece-rate salary schedule. In a structurally similar setting, the introduction of piece-rate pay in a Canadian tree planting business has also been found to strongly affect worker productivity and profits (Paarsch and Shearer 1999).

However, production jobs, as well as procedural jobs, are of limited relevance to the public sector. Rather, given that the loci for incentive schemes, following the principal-agent literature, are mostly in contexts where actions are not easily observable but outcomes may or may not be, the focus of this paper will be on jobs in the right hand column of Table 1. Note that some of the studies of the private sector that have focused on incentives for rank-and-file ―knowledge workers‖ in large organizations can also be classified in this right hand column and will be included in the discussion.

# **Methodological approaches**

The vast empirical literature on PRP utilizes a range of methodological approaches. Early studies on performance pay in the public sector were largely qualitative case studies. As elements of civil service reform and incentive schemes were introduced in OECD countries throughout the 1980s and 1990s, academics and policy experts wrote initial studies and reports that summarized the main descriptive feature of reform attempts, and chronicled the reform process and implementation. Overall evaluation of the success of incentive schemes was based on qualitative impressions of practitioners. Later studies 11
The CDR for low and middle income countries as a whole is estimated to be 9 deaths per year per 1,000 people in 2001 (World Bank, 2004).<sup>4</sup> This has been quite stable over recent years; the CDR was also 9 per 1,000 in 1990. (These data should not be considered very reliable. Vital registration systems are weak in many developing countries though censuses and surveys have provided some useful validation data.) While estimates are readily available for overall death rates, that is not the case for death rates conditional on income or other socio-economic variables. An instructive exception is for the United States, where the National Longitudinal Mortality Study (NLMS) surveyed over one million adults from multiple waves of the Current Populations Surveys, thus allowing mortality data to be linked directly to socio-economic data including incomes. The data reveal death rates for the poor that are two-three times higher than for upper-income households for most agegender groups (Sorlie et al. 1995).<sup>5</sup> However, surveys such as the NLMS are not available in any developing country to my knowledge. The surveys used to measure poverty typically have adequate sample sizes for that purpose, but cannot provide reliable estimates of relatively low-frequency events such as adult deaths. Censuses can help as a source of mortality data (if the appropriate questions are asked), but they typically do not include the data needed for measuring poverty. Thus we generally do not get data on deaths and living standards for the same sampled households.

An important new source of information on socioeconomic differences in health indicators has been developed by Gwatkin et al., (2000), based on the Demographic and Health

> 4 In standard statistical sources, the CDR is measured as the number of deaths in the last year relative to mid-year population.  The calculations in this paper ignore the difference between mid-year population and end-of-year population.

> 5 Earlier estimates by Pappas et al., (1993) for 1986
We incorporated up to 12 lag periods to capture the delayed effects of climate shocks, consistent with studies such as Tang et al. (2021) and Prather et al. (2023). Economic variables like agricultural wages, fuel prices, domestic food prices, exchange rates, and global food prices often respond to climatic shocks with time lags, as indicated by Schmidhuber and Tubiello (2007).

The system includes many parameters, and to assess the cumulative impact of various factors, we sum the coefficients across all lags. This approach provides insights into the combined influence of these factors over time. For the logit equations, we convert the parameter estimates into marginal effects to aid interpretation, calculated over the full-year effects. Robust standard errors are used for all parameters to address potential heteroscedasticity. Finally, the estimated parameters allow us to predict the probabilities of food stress and food crisis, generating averages for each administrative area. This enables mapping variations in food insecurity risks between 2009 and 2023.

# 5. Results

This section presents the results of the logit regressions estimating the impact of climatic and economic shocks on food security. The results are presented in stages. First, we examine the direct effects of climatic shocks, particularly rainfall and NDVI anomalies, on food stress and food crisis. Next, we evaluate the role of economic factors, such as changes in food prices and agricultural wages, in influencing food insecurity, with a focus on how these variables react to climatic shocks.

## 5.1 Logit Regression Estimates for Food Stress and Food Crisis Drivers

Table 2 reports the results of the logit regressions for two thresholds of food insecurity: IPC phase 2 or greater (food stress) and IPC phase 3 or greater (food crisis). The model includes climatic variables (rainfall and NDVI anomalies), economic factors (food prices, agricultural wages), and a set of control variables to capture structural determinants of food security. The model is estimated using monthly data with twelve lags. To summarize, the coefficients
- Lo Bello, S., M. L. Sánchez-Puerta, and H. Winkler. 2019. “From Ghana to America: The Skill Content of Jobs and Economic Development.” World Bank Policy Research Working Paper 8758, World Bank, Washington, D.C.

- Mazza, Jacqueline, Wendy Cunningham, Nga Thi Nguyen, and Audrey Stienon. 2019. “Functional Review of Employment Services Centers in Vietnam: Analysis and Recommendations.” World Bank, Washington, D.C.

- Moroz, Harry, Nga Thi Nguyen, and JJ Naddeo. 2021. “Digital Skills in a Digitizing Vietnam: Assessing the Demand for Digital Skills in Vietnam _._ ” World Bank, Washington, D.C.

- Moroz, Harry, Nga Thi Nguyen, and Lan Chu. 2019. “Skills Profiling of Priority Occupations in Vietnam _._ ” World Bank, Washington, D.C.

- Moroz, Harry, Nga Thi Nguyen, and Lan Chu. 2019b. “Using Targeted Labor Market Information Tools To Improve Employment Services in Vietnam.” World Bank, Washington, D.C.

- OECD. 2016. _The Survey of Adult Skills: Reader’s Companion._ Second Edition. OECD Skills Studies. Paris: OECD Publishing. <u>http://dx.doi.org/10.1787/9789264258075-en</u>

- Peterson, N.G., M.D. Mumford, W.C. Borman, P.R. Jeanneret, and E.A. Fleishman (Eds.). 1999. _An Occupational Information System for the 21st Century: The Development of O*NET_ . American Psychological Association. <u>https://doi.org/10.1037/10313-000</u>

- Pierre, G., M.L. Sanchez Puerta, A. Valerio, and T. Rajadel. 2014. _STEP Skills Measurement Surveys Innovative Tools for Assessing Skills_ . Social Protection and Labor Discussion Paper
main forms of violence against women in Peru. The authors also find that early-life exposure to alcohol-induced IPV is indeed associated with lower test scores in vocabulary. Our results suggest that maternal depression is a mechanism through which alcohol induced IPV leads to worse child vocabulary outcomes.

The remainder of the paper is organized as follows. In the next section, we describe our research design, including details on the data we are using for our analysis and some descriptive statistics. In Section 3, we describe and motivate the use of instrumental variables as an empirical strategy. In Section 4, we present the main results, including some robustness checks. Finally, in Section 5 we discuss to the policy implications and conclude.

# **2. Research design**

In this section, we briefly describe the data we use to assess the impact of maternal depression on early child vocabulary in Peru. Then, we present some descriptive statistics of the different rounds of data use in our analysis. Since we restrict our study to the sample that has information across all rounds, we also briefly describe the results from the sample attrition analysis.

# **2.1 Data**

# **_A. Description_**

To measure the effects of MMH on child development, we use the first three rounds of the Young Lives Peru Survey (YL), conducted by the University of Oxford with core-funding from the UK Department for International Development.<sup>7</sup> This is a rich longitudinal survey that includes a complete set of individual, parental, household and community characteristics, including early developmental, economic and demographic indicators, as well as information about social assistance programs in every community. The baseline sample of YL is cluster stratified, with 20 districts randomly selected across the country.<sup>8</sup> Within each of the selected districts, 100 households with at least one child born between 2001 and 2002 (index child) were chosen randomly to participate in the project. The baseline round was
people|0.6|34<br>47|33.3|
|International bandwidth|bits/capita|0.2|13<br>153|34|
|Internet|users/100 people|0.3|6<br>13.9|5.1|
|Landline|subscribers/100 people|0.6|2.2<br>13.6|1.5|
|||Cameroon|Lower-middle income<br>countries<br>Sub-|Saharan Africa|
|||2009|2008|2008|
|Price of monthly mobile basket|US dollars|14.7|8.4<br>11.8||
|Price of monthly fixed-line basket|US dollars|14.7|4.8<br>11.6||
|Price of monthly fixed broadband|US dollars|104|31<br>100.1||
|Price of a 1-minute call to US|US dollars|0.8|—<br>0.9||
|Price of an inter-Africa call per minute|US dollars|0.9|—<br>1.0||

Source: AICD database. — = data not available 36
key impact which varies widely across urban and rural floods, flood scale, type, speed of onset and development scale. Jonkman and Kelman (2005) have estimated that two-thirds of immediate deaths from flooding worldwide are from drowning, with the remaining one-third arising from physical trauma, heart attack, electrocution, carbon monoxide poisoning or fire. Other, more indirect, deaths are caused by disease, disruption of food supplies, ill-health or shock after the event and are also related to flood and development characteristics. Annex 2 details some of the most devastating events in terms of loss of life globally over the last century.

While it is unlikely that deaths from flooding can ever be entirely eliminated, the natural focus of flood mitigation programs naturally centers on the protection of human life. There is some evidence that such efforts have been successful. Identification of flood-related deaths is problematic as in many cases only immediate deaths from trauma are recorded. In addition, when examined over long time periods, loss of life statistics are dominated by a handful of disasters of epic proportions such as the large peak in 1999 relating to the Venezuelan (Caracas) disaster, which was a mud and debris flow event, and the 1931 Yangtze river flooding in China. This 8
sample|Count. Birth|National Stat.|25+|Avail.|Citizenship estimated on EC. Educ. attainment & share of 25+ on LFS|
|**United States**|Census 5% sample|Count. Birth|US Burau of Census(IPUMS)|25+|Avail.|IPUMS Sample 5%|

<u>Notes (*):</u> _EC = European Council data providing the immigration structure by country of citizenchip for European data_ _LFS = European Labor Force Survey data providing data on country of birth and educational attainment in EU-15 countries_
which 79 firms<sup>10</sup> received for a median of 35 hours, and operational productivity, which 71 firms chose and received for a median of 80 hours. Most firms in the program therefore received these two areas, and then were divided in their choice of a third area, with 34 receiving labor productivity, 32 quality, and 19 energy consulting.

# **5.2 Impacts on business and export practices**

The most immediate impacts of management consulting interventions are typically seen on management practices, as firms implement the changes recommended by consultants. We hired Innovations for Poverty Action to conduct a follow-up survey of firms between November 2019 and May 2020. This was able to collect data on 172 of the 200 firms (89 treatment and 83 control), and additionally confirm that 3 other firms were closed (2 control, 1 treatment). We measure impacts on 15 different export-oriented management practices, such as whether the firm participates in trade fairs, has received a quality certification for an export market, does direct marketing to international customers, or had received information about distributors abroad. In addition, we measure impacts on each of 40 different general management practices that cover the five areas of consulting, divided into operations practices (10), labor productivity practices (9), quality practices (6), energy practices (4), and commercial practices (11). Appendix C provides definitions of all measures, which were developed with feedback from the different consulting entities to ensure they covered the main areas of advice given. Our main measures of export practices and management practices are then defined as the proportion of these practices that are used by firms.

Figure 2 shows the estimated intention-to-treat effects of being assigned to consulting on these two indices of management and export practices, as well as on the five sub-components of the overall management practices index. We did not elicit priors on these outcomes, so only show frequentist point estimates and confidence intervals from estimating equation 4.1.<
Listed Company data:

- Advantages

- The data come from reported balance sheets and income statements and hence are likely to be more reliable than data from firm surveys.

- There are data on the stock of cash and hence it is possible to have an accurate measure of financial savings.

- The panel data for 2001-2008 are available.

- Disadvantages

- Small sample.

- Cannot disaggregate by type of firm.

- No data on investment (physical savings), but we can use an approximation as a change in PPE.

# **4.1 Construction of Variables for the ICA Data**

As discussed above, the main advantage of the ICA is data on investment, which allow us to evaluate one aspect of savings – i.e. physical savings.

We create several measures of physical savings. The first measure is the proportion of firms that make any investment into property plant and equipment in any given year. Second, for firms that have made any investment we estimate the size of the investment as a portion of existing machinery and equipment. We scale total investment by the net book value for existing machinery and equipment and refer to it as investment to capital ratio, IK. For international comparison purposes and over time we also scale investment by sales.<sup>4</sup>

> 4 Note that investment data include land and buildings purchases, and the net book value also includes land and building book values. In the data the land and buildings purchases are rare, and so they are lumped together with the machinery and equipment purchases.

7
. 24|
|Applying the Framework in the Lifelong Learning Project.................................. 24|
|2.3<br>Applying the Framework within a National Survey....................................... 26|
|2.3.1<br>Agency and Opportunity Structure........................................................... 27|
|2.3.2<br>Degrees of Empowerment......................................................................... 28|
|<br>2.3.3<br>Application at the National Level............................................................. 28|
|3.<br>Summary.................................