rafmacalaba/data-use-mentions-extended huggingface dataset:
controls (except for location and time fixed effects) and the second column including controls for age, gender, education, and length of unemployment. As can be seen from this table, employability ratings are an important determinant of access to matching services. Being rated _employable_ (relative to _less employable)_ increases the likelihood of receiving matching by 5-6pp. Similarly, being rated _highly employable_ increases the likelihood of receiving matching 5-7.4pp (though given the small sample size, this effect is not statistically significant). Providing matching services is costly for the private employment service provider. Unsurprisingly, therefore, they are more likely to provide these to jobseekers who, in their assessment, are most likely to be formally employed as a result of these services. As was shown previously, despite a lower likelihood of receiving matching, treatment effects are positive for _less employable_ jobseekers, suggesting that the counselors make use of additional information (for example what they learn during the profiling interviews and demand for the specific skills of the jobseekers) to identify those most likely to benefit from matching.

Given the importance of jobseeker employability rating we analyze correlates with the rating in Table 12, which marginal effects predicted from an ordered logit model (coefficient estimates are presented in Appendix Table A.1). The first set of marginal effects (in the first three columns) are based on a model including basic demographic characteristics from administrative data. The second set (middle three columns) adds household size, income and previous employment status as additional variables, and the third set (last three columns) includes the “Big 5” personality traits (measured in the baseline survey). First, we note that, consistent with random assignment, treatment is uncorrelated with employability assessments. Second, while gender has no impact on employability assessments, younger jobseekers, those with lower levels of education and the long-term unemployed are likely to have lower employability assessments. In terms of marginal effects, relative to younger jobseekers, jobseekers above the age of 30 are 5
recognized that GNI per capita does not measure welfare or success in the fight against poverty, GNI per capita is found to correlate closely, in terms of both values and rankings, with a number of accepted indicators of development outcomes such as secondary school enrollment, stunting (malnutrition), births attended by skilled staff, and the poverty headcount ratio (see Table 3). Heckelman, Knack and Rogers (2011) also find that it is highly correlated with broad-based measures of institutional development and creditworthiness.

There is an important practical consideration for the regular production of a country classification: data availability. Both GNI and population estimates are readily available on an annual basis for most countries, with GNI compiled by countries using the international standard System of National Accounts (SNA), and population data available from the United Nations Population Division and national sources. While some users have suggested a new classification more closely aligned with poverty incidence rates and with new measures of shared prosperity, current data availability for most countries of interest is far less than the annual frequency desired for classification purposes.

There are, however, issues of data quality related to the GNI estimates that may result in systematic bias. First, infrequent adjustment of the national accounting framework in countries

> 10 In order to increase sample size we take five‐year averages between 2006 and 2010 for the selected indicators.

16
property in Hindu, Buddhist, Jain, and Sikh families would be bequeathed only by male family members. However, reforms initiated in the states of Andhra Pradesh, Tamil Nadu, Maharashtra, and Karnataka ensured that sons and daughters would have equal rights to ancestral property. To estimate the causal impact of these reforms on intergenerational transfers in the four reform states, Deininger et al. (2013) draw on data from the 2006 Rural Economic and Demographic Survey (REDS), and use a difference-in-difference approach to compare the inheritance of land by males and females in the same household from fathers who died before and after the reforms were passed.<sup>12</sup> The evaluation results suggest that following the reforms, daughters were more likely to inherit family property, and parents increased investments in daughters’ schooling. What is noteworthy here is that parents increased both physical capital and human capital transfers to

> 11 There is evidence (see Bhalotra et al. (2016)) to suggest that inheritable land rights increases the motivation to exercise son preference in contexts where the tradition is for sons to inherit land. Following from this, it could be argued that if land rights could be passed on to male _and_ female children, then the incentive to exercise son preference would diminish.

> 12 These comparisons were augmented by looking at differences across Hindu families and non-Hindu families in reform states, and differences across reform states and non-reform states.

29
**Survey (Sakernas).** More specifically, the analysis utilizes data from the August wave of Sakernas for each year between the years 2016 and 2023. The analysis explores the relationship between the labor market outcomes – that is, employment rates, unemployment rates, hours worked, and income – of younger persons and older persons at the province level using ordinary least squares (OLS) regression. The employment rate for a given age group is calculated as a share of the population within the age group, while the unemployment rate for a given age group is calculated as a share of the labor force within the age group. The sample is divided into three age groups: 15 to 24 (“youth”), 25 to 54 (“prime-aged”) and 55 to 64 (“old”). This relationship will be analyzed by gender, education level, and sector of employment, as shown in Figure 13. Formally, the basic model that will be analyzed is as follows:<sup>10</sup>

where Ypt is the labor market outcome of interest for province p in year t, that is, employment rate (as a share of the population), formal employment rate (as a share of employment), unemployment rate (as a share of the core labor force, i.e. those working and those looking for a job), hours worked in the previous week, and income of the young and prime-aged. The independent variable of interest is captured by oldemppt, which captures the employment rate of older persons in a given province and year. The vector Xpt includes a set of province-specific, time-varying explanatory variables, namely GRP per capita, GRP growth, the provincial unemployment rate, the provincial poverty rate, the structure of the economy (i.e. the relative shares of the industrial and service industries), the share of younger persons in the relevant age group (i.e. youth aged 15 to 24 or prime-aged persons aged 25
# **5. Why does formality matter?**

There are a number of potential reasons why formality has a positive impact on firm profits. The literature highlights several possible channels, including improved access to credit (Straub, 2005); ability to attract more customers by issuing receipts and lowering the costs of corruption (McKenzie and Sakho, 2010); ability to attract/retain qualified workers, opportunities to participate in government SME support programs, and access to contract enforcement mechanisms (Perry et al, 2007). In this section, we consider the role of some of these channels in enhancing firm profitability in Ecuador using the EMES data as well as the outcomes of the focus group discussions.

According to firm owners, the main benefit of formalizing is to “follow the rules.” As shown in Figure 9, more than 40 percent of respondents mention “following the rules” ( _estar en regla_ ) as the main motivation for complying with regulatory requirements.<sup>18</sup> Similar sentiments were also expressed during focus group discussions, especially with owners of larger businesses (more than 10 employees) who indicated that they could not imagine operating their firms without having taken some steps towards formality. More generally, firm owners of all sizes felt that in order to grow and compete successfully for larger contracts, “having everything in order” and “following the rules” is a necessity.

**Figure 9: Benefits of registering with tax authorities and the municipality**

<!-- Start of picture text --> Advantages of having a tax identification number (RUC) Advantages of having a municipal license<br>0 10 20 30 40 50 0 10 20 30 40 50<br>Follow the rules Follow the rules<br>Avoid fines<br>Avoid fines<br>Issue tax receipts<br>Ability to obtain RUC<br>Improve access to credit<br>None<br>Deduct VAT on purchases<br>Improve access to
I POLICY RESEARCH WORKING PAPER 1759

# Summary findings

Case studies and anecdotal evidence have suggested that uncertainty about policies, laws, and regulations has hampered development of the private sector in many developing countries. Brunetti, Kisunko, and Weder present results from a new cross-country survey that provides comparable data on local investcors' problem in dealing with the state. The survey was conducted in 69 countries and covers more than 3,600 entrepreneurs.

The questionnaire asked 25 questions about investors' perceptions about such issues as the predictability of laws and policies, the reliability of the judiciary, corruption in bureaucracies, and security of property rights. It also asked about general obstacles to doing business and the quality of state-delivered services.

Brunetti, Kisunko, and Weder discuss their methodology and present many findings. Among them: - In less developed countries the majority of entrepreneurs constantly fear policy surprises and unexpected changes in rules that can seriously affect their business. Entrepreneurs in Asia have the most trust in government announcements of policy changes and changes in rules; entrepreneurs in the Commonwealth of Independent States are the most cynicai about new announcements; and half of businessmen surveyed in Latin America and Central and Eastern Europe do not believe government announcements.

* Entrepreneurs worldwide feel that the cost of doing business is substantially increased by theft and crime and in many developing countries the business community feels that authorities do not adequately guarantee their personal safety and do not reliably enforce their property rights.

* Unreliable judiciaries are perceived as major problems in many developing countries. This applies in particular to the Commonwealth of Independent States and to Latin American countries.

* Entrepreneurs in industrial countries perceived the greatest obstacles to doing business to be tax regulations and high taxes, labor regulations, safety or environmental regulations, financing, regulations for starting new businesses and operations, and general uncertainty about the costs of regulation.

Entrepreneurs in South Asia and Southeast Asia ranked the top obstacles to doing business as high taxes and tax regulations, inadequate infrastructure, inflation, labor regulations, and regulations for starting new businesses and operations
(Chart 5)48 Virtually all twelve countries experienced a decline in the confidence in the banking sector during banking crises, as measured by the currency to deposit ratio. Confidence did not recover in all the countries after the crises. Among the _CEEs,_ there was recovery in confidence (that is, the ratio fell) only in _Macedonia_ and _Poland,_ while in the _CIS_ countries, there was recovery only in _Georgia._ On the other hand, in all three _Baltics_ states, and in particular in _Estonia,_ confidence in the banking sector rose after crisis resolution. In 1998, confidence in the banking sector as measured by the currency to deposit ratio was similar in the _CEEs_ and the _Baltics,_ where the ratio was between 90 to 95 percent in these countries, compared with around 30 percent in OECD countries. The confidence in the banking sector was much lower in the _CIS,_ where the ratio was over 400 percent.

Data on the ratio of MI to M2 shows a generally positive experience for all the countries. With the exception of _Macedonia,_ all the countries showed a decline in the ratio in the aftermath of bank crisis resolution, reflecting an increase in confidence in the banking sector.

> **47** See Appendix Table 11 for data on currency deposit ratios for the twelve countries and for OECD countries. 48 See Appendix Table 12 for data on MI/M2 for the twelve countries and for OECD countries.

46
The coefficients of interest in this regression are 1, 2, and 3, which give the impact of each treatment on the difference in outcomes before and after the individual intervention in Group C ββ ββ ββ villages.

The advantage of the within-subject design is that it potentially improves power by controlling for individual-specific levels of the outcome pre-intervention. However, the disadvantage is that there could be an anchoring effect, since individuals are asked the questions only about one hour apart. They may therefore anchor their post-intervention responses on their pre-intervention responses and not change them as much. The across-subject design is not subject to this concern, but may have larger variance.

# **4.2 Follow-up survey data**

Our primary hypothesis was that our three treatments would reduce the likelihood of backway migration from The Gambia, increase the likelihood of migration to Senegal and internal migration, and improve the well-being of the young men in our sample. We pre-specified primary outcomes in three domains to test this. The first domain consists of measures that capture steps, attempts, and actual backway migration to Europe. The second domain consists of measures of migration to Dakar and other parts of Senegal, and of internal migration. The third domain consists of broader measures of well-being, such as life satisfaction, experiences of violence, and monetary income. Appendix B details how these outcomes are measured.

These outcomes were measured by a three-step endline survey, which took place between September and November 2020, approximately 18 months after the information intervention, and approximately six months after COVID-19 had led to border closures worldwide. We first conducted phone calls to obtain the current location of half of the youth who were interviewed in the baseline survey. In case of repeated unsuccessful call attempts, the household head was contacted and surveyed. This provided a first data point on migration for those contacted, as well as helped plan the logistics for in-person surveying. We then conducted face-to-face surveys, attempting to interview in-person all youth interviewed in the baseline survey. These surveys asked detailed questions about
2013|4.23|20.53|16.67|19.38|18.43|-0.09|-4.34|
|2014|2.19|20.82|20.67|20.36|19.14|0.81|-5.15|
|2015|3.78|20.46|20.81|18.29|19.79|1.88|-1.76|
|2016|2.72|20.49|19.18|19.45|22.76|-0.82|-5.67|
|2017|2.82|19.49|22.33|18.53|21.32|0.35|-6.27|
|2018|2.93|18.04|19.39|18.82|21.74|0.46|-6.55|
|2019|4.85|21.11|20.93|19.00|22.87|0.76|0.58|
|2020|2.84|18.19|22.17|19.97|18.84|1.95|-4.90|
|2021|0.53|19.69|19.51|17.56|21.55|2.02|-1.84|

_Notes:_ Based on data from EH 2007-2021.

This likely explains the significant variance (and weight) assigned to this component in the Principal Component Analysis. Furthermore, it is important to acknowledge that strict labor regulations limit the creation of formal jobs that provide access to the AFP. Only 5.6 percent of the country’s unemployed population (including the unemployed and low-income self-employed) secure formal sector employment in a given quarter. Combined with over twothirds of the population being self-employed or employed in micro
the transactions originate. Only a few banks or financial institutions in developing countries have branches or subsidiaries overseas that serve both senders and recipients of remittances.

The first issue this survey attempted to explore was to what extent the balance of payment statistics of developing countries reflect the volume of remittance flows that countries receive every year (third phase).<sup>2</sup> As shown in Table 2 below, the survey found that in many countries the coverage of remittances in balance of payments statistics is partial, because remittances

> 2 In the countries covered in this survey, remittance data for balance of payment statistics is collected by central banks. However, it is worth noting that in some other countries data is not collected by central banks but by national statistics agencies.

6
Figure 4: Event study for cohort births and classroom density <!-- Start of picture text --> 1 5<br>.8 4<br>.6 3<br>.4 2<br>.2 1<br>0 0<br>-.2 -1<br>-.4 -2<br>-.6 -3<br>-.8 -4<br>-1 -5<br>-6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6<br>Period Period<br>Birthrate relative to period t=-1<br>Classrooms relative to period t=-1<br><!-- End of picture text --> Figure 4a: Classrooms per 100 youth age 15–19 Figure 4b: Cohort birth rate (age 15–19) Notes: These figures plot the coefficients from an event study; the first observed secondary school introduction in a municipality is the “event”. Bars indicate 95% confidence intervals. All estimates condition municipality fixed effects. Includes all municipalities that received at least one new school over time (3,470 municipalities).

Source: Authors’ analysis based on school data from the 2002 wave of the Brazilian School Census; official population estimates from the Brazilian Census Bureau; births by age from Brazilian Vital Statistics.

29
Table 1 Poverty and inequality estimates using survey-to-survey imputations compared to 2018/19 NLSS

||Poverty rate<br>US$1.90<br>(percent)|Poverty rate<br>US$3.20<br>(percent)|Gini<br>coefficient|Mean Annual<br>Consumption<br>(US$2011PPP)|Median Annual<br>consumption<br>(US$2011PPP)|
|---|---|---|---|---|---|
|2010/11 GHS|43.54|72.88|35.65|81.49|64.25|
|2012/13 GHS|42.49|72.12|35.51|82.67|65.41|
|2015/16 GHS|40.75|70.44|35.88|85.62|67.44|
|2018/19 GHS|41.88|72.28|34.94|82.39|65.86|
|2018/19 NLSS|39.09|70.98|35.13|85.13|68.77|

Note: the table shows the results of the survey-to-survey imputation in each round of the GHS. We develop a consumption model using data on 23 non-monetary indicators and household consumption available in the 2018/19 NLSS. Using the estimated parameters, we then impute in each round of the GHS using the same non-monetary indicators and 100 imputations. The imputed consumption vector is then converted to 2011 PPP and poverty estimates are reported at the US$1.90 and US$3.20 poverty lines. Gini coefficients are calculated as the average of 100 estimates resulting from each imputation.

Table _1_ (and Table _9_ in the Appendix) shows the results of the survey-to-survey imputations in each round of the GHS. The imputed poverty headcount rate at the US$
have identified similarities between the US crisis and prior emerging market crises (e.g. Boone and Johnson, 2008; Krugman, 2009). Calvo and Kung (2010) label the US recovery as a new Phoenix Miracle while noting parallels between the US and past emerging market episodes. By contrast, Campello, Graham, Giambona, and Harvey (2011) and Campello, Graham, and Harvey (2010) use survey data to conclude that the US financial crisis limited but mostly did not preclude access to credit lines.

In this paper, we use a database of listed firms in emerging markets to analyze the recovery process after a financing crisis. Specifically, we ask whether recovery of the financial 2
|(0.192)|(1.789)|
|Medium size frm|-0.0227|0.181*|0.124|0.131|
||(0.100)|(0.0900)|(0.0940)|(0.0894)|
|Inverse Mills Ratio||-7.106**||2.056|
|||(2.979)||(4.924)|
|Constant|-10.54***|-0.740|-16.70***|-2.740*|
||(1.729)|(0.545)|(2.174)|(1.312)|
|Observations|873|377|701|236|
|R-squared|0.446|0.176|0.548|0.098|
|Number of frm|82|61|141|95|
|Firm FE|Yes|Yes|Yes|Yes|
|Year FE|Yes|Yes|Yes|Yes|

**_Source:_** Author’s analysis based on data from the World Bank Regional Project on Enterprise Development (RPED) and Ghana Manufacturing Survey (GMES) from 1992 to 2003.The surveys were conducted by the Centre for the Study of African Economies (CSAE) at the University of Oxford, University of Ghana, and Ghana Statistical Service. The data on tariffs comes from the _Centre d’Estudes Prospectives et d’Informations Internationales_ (CEPII). **_Note:_** The sample in Columns (1)- (2) is confined to firms that remained active throughout the twelve years of the study, whilst that of Columns (3) - (4) is confined to firms the group of firms that either exited or entered latter. Robust standard errors clustered at three digit industry level in parentheses _∗∗∗_
Japan and the Tigers as ‘finished business’—all are likely to carry on exploring ways of financing and delivering health care more efficiently, if not also more equitably. But in the meantime, their existing arrangements and recent reform experiences all provide potentially useful lessons for East Asia’s developing countries, if not for one another.

# **References**

1. OECD Health Data [program]. Paris: OECD, 2005.

2. World Health Organization. World Health Report 2005: Make every mother and child count. Geneva: World Health Organization, 2005.

3. Lu J-FR. The Application of National Health Account Approaches in Estimating National Health Expenditures: Taiwan (China) Experience. Tao-Yuan: Department of Health Care Management, Chang Gung University, 2001.

4. O'Donnell O, Van Doorslaer E, Rannan-Eliya R, et al. Who pays for health care in Asia? EQUITAP Working Paper # 1, Erasmus University, Rotterdam and IPS, Colombo, 2005.

5. Lu JR, Hsiao WC. Does Universal Insurance Make Health Care Unaffordable? Lessons from Taiwan (China). _Health Affairs_ 2003; **22** (3 (May/June 2003)) **:** 77-88.
input reporting is assessed in two ways. First, as the total number of agricultural plots (or parcels) cultivated by the household. This variable is simply a count of the households’ agricultural plots (and parcels) which respondents list at the beginning of the agricultural questionnaire of the survey. This information sheds light on whether a longer recall period leads households to forget listing some plots (Gaddis et al., 2019). The median (mean) number of plots listed per household is 2 in Tanzania NPS 2012/13 (mean: 2.2 plots) and Malawi IHPS 2016/17 (mean: 2.1 plots) and 1 in Malawi IHS4 (mean: 1.6 plots; Table 2).

Second, as the difference between GPS-measured plot area and farmer self-reported plot area. Given the prevalence of measurement error in land area reporting, LSMS-ISA surveys, including the data used in this analysis, implement an objective, GPS-based area measurement, while retaining farmer self-reported plot area alongside. Comparing these two measures allows assessing whether recall decay exacerbates the error in self-reported land area. This variable is constructed by subtracting the plot area variable based on GPS measurement from the self-reported plot area variable, so that area under-reporting has a negative sign while area over-reporting has a positive sign.

Plot sizes, measured by GPS, differ substantially across the three data sets. In Tanzania NPS 2012/13, the average plot size of 1.23 hectares (median: 0.49 hectares) is much larger than in Malawi at 0.37 hectares in the IHS4 (median: 0.30 hectares) and 0.34 hectares in the IHPS data set (median: 0.26 hectares; Table 2).

6
8141|22.69024|4.82508|23.19447|3.920394|
|Average|143.1879|223.1681|94.40788|190.3666|99.42906|146.1093|136.3161|185.7742|

Pre = Pre-food crisis (from 2004m1-2006m12) Post = Post-food crisis (from 2007m1-2010m12) (Note) Autocorrelations and standard deviations are computed based on the de-trended series of each crop and province using pre- and post-crisis monthly price data. We remove linear time trend to construct de-trended price series. Average is the simple average.

(Source) Bulog, BPS