rafmacalaba/datause-encoder-data huggingface dataset:
<!-- Start of picture text --> The Standard International Trade Classification (SITC Rev.1) The Harmonized System (HS 1988)<br>100% 100%<br>80%, 2 /~~ ==" NN - ts -i, me tse et 80% f' aTe - ee --- poctsecn \v:<br>U<br>f<br>i,<br>LF<br>eo 60% e 60%<br>s sures =<br>€ yea Nt* . = denende--=4,<br>y or Lawl Y Sf errr<br>o yy o ¢<br>a 40%'7 a 40% L' -<br>1<br>=] 4 4<br>4<br>20% 20%: + z 4<br>ir<br>£<br>4<br>0% 1970 1980 1990 2000 2010 2020 0% 1990 1995 2000 2005 2010 2015 2020<br>Year Year<br>— Dual recording - Aggregated — Import value with dual recording - Aggregated<br>= «Disaggregated = «Disaggregated<br>Most disaggregated Most disaggregated<br>The Standard International Trade Classification (SITC Rev.1) The Harmonized System (HS 1988)<br>100% 100%<br>&&<br>aa<br>33<br>&.=+<br>Z80% Z 80%<br>s£ |Ss 4<br>oa&co<br>°°<br>J2<br>&&<br>22£5 60% 25 60%<br>=—<br>H40% H 40%<br>==**<br><=°°<br>:2<br>é& 20% 2& 20%<br>&&<br>
2<s<br>cia 1995 2000 2005 2010 2015 O% 2002 2004 2006 2008 2010 2012 2014 2016 +2018<br>Year Year<br>95% Confidence Interval — Mean<br><!-- End of picture text -->
# Research Clonents of World Bank Education<sup>Projects.</sup> since 1982.

|Ar|I<br>Country and Loan/Credit<br>INumer<br>I|Approved<br>I|kesarch Components<br>I|Current Status of Studies.<sup>including</sup><br>Coapleted Documnts/Data|
|---|---|---|---|---|
|LAC|Bahams LN 3L04-U|1969|Second Technict**and**Vocational<sup>Training</sup><br>Project. Estabtisheent of a gradate<sup>tracer</sup><br>**system**by Dec 1989, to evaluate<sup>National</sup><br>training Council and Bahms<sup>Hotel Training</sup><br>College training program<sup>(para</sup><br>3.7 p.1 S).|Project just initiated.<br>Ho studies begun.|
|LAC|Barbdw LN 2688-BAR|1i96|Second Education nd Training.<sup>Study the</sup><br>formulation of cost saving<sup>andefficient</sup><br>use of<br>facilities<br>to cover:<br>(i)the selection procedures<sup>for public</sup><br>exminstions;<br>(ii)<br>the mrketing output of the<sup>technicall</sup><br>vocaticnal systm;<br>(iii)<br>mintenance costs;<br>(iv) areas of post-secondary<sup>educationwhere</sup><br>savings can be realized (para.<sup>2.06.b p.11)</sup><br>(due Dec 1966).|Capleted.<br>Goverent<br>ofBarbados.*Statusof studies<br>assessment of cost ndfinuncing."<br>(doc.<br>*GIZZIS)<br>|
|LAC|BrazilLN2412-SR|1984|Urban Basic Education. (i)<sup>School mpping study</sup><br>(pars. 3.16 p.19);<br>(ii)<br>funding of pre-investment<sup>studies</sup><br>(pars. 3.20 p.20);<br>(iii)<br>Projectsin:teaching literacy<sup>Grades</sup><br>1<br>and 2;<br>(iv) techniques for training<sup>untrained</sup><br>teachers (pars. 3.21 p.20);<br>(v) increasing item for student<sup>learning;</sup><br>(vi) improving school level<sup>adinistration;</sup><br>(vii)<br>monitoring nd evaluation;|i) HNping exercises have<sup>been conducted</sup><br>throughout project life.<br>Studies" are revised<br>armuaty by theBanksupervision<sup>mission (architect)</sup><br>(il)-vl):<br>not initiated<br>(vii)<br>Joao Pinhiero Foundation has<sup>udertaken</sup><br>for_ative evaluation (project<sup>monitoring). Final</sup><br>sotive<br>evaluation is in pleming<br>**asse;**<br>(viii)<br>studies of direct and indirect<sup>cost of</sup><br>schooling have beer oamiissioned<sup>by unit inside</sup><br>SEB. Some**reports have**been<sup>coupleted</sup><sup>**and are**in</sup><br>LAC files<br>(notfound).<br>Others related to indirect<br>costs**are**under preparation.|

59
<!-- Start of picture text --> Private Corporate Sector Investment as Public Sector Investment as a percent<br>a percent of GDP of GDP<br>18 10.0<br>16 9.0<br>14 8.0<br>7.0<br>12<br>6.0<br>10<br>5.0<br>8<br>4.0<br>6<br>3.0<br>4 2.0<br>2 1.0<br>0 0.0<br>2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017<br><!-- End of picture text --> Note: Data is from CEIC and presented for fiscal years. Investment rate is defined as gross fixed capital formation in percent of GDP.

Investment slowdown pervades across several sectors of the economy, most prominently in manufacturing and construction (Figure 19). Overall, the investment rate declined by approximately 4.9 percentage points during 2007–08 and 2015–16, driven by manufacturing, with the investment rate declining by 3.7 percentage points, followed by construction. Investment rates declined in other sectors too, but increased in trade, hotels, and restaurants.

**Figure 19: Decline in Average Investment Share of GDP between 2007–08 and 2015–16**

<!-- Start of picture text --> 3 1.7<br>2<br>1<br>0<br>-1 -0.4 -0.4 -0.2 -0.1 -0.1<br>-2 -1.2 -1.1<br>-3<br>-4<br>-5 -3.7<br>-6 -5.5<br>Total<br>etc Agriculture<br>Construction Water etc<br>Manufacturing Community, Social, Mining and Quarrying Electricity, Gas and Financial, Real Estate, Transport, Storage etc Trade, Hotel and Restaurants<br><!-- End of picture text --> Note: Data is from CEIC. Figures show the difference between the average rate in 2015 and 2016 and 2007 and 2008.

35
# 6.1 Depression and Anxiety (PHQ‐ADS)

## **6.1.1 PHQ‐ADS Score (Intensity)**

The Patient Health Questionnaire‐ Anxiety and Depression Scale (PHQ‐ADS)<sup>8</sup> is a measure where a score of 10 or above indicates prevalence and levels of anxiety and depression. Lower PHQ‐ADS scores, therefore, indicate lower intensity of experiencing symptoms of anxiety and depression. Intent‐to‐treat (ITT) estimates show that entrepreneurs in the treatment arm have PHQ‐ADS scores 0.74 lower than the scores of SME entrepreneurs in the control group at the 5‐weeks (from a baseline average of 6.94). At the 3‐month mark, the PHQ‐ADS score for the treatment arm entrepreneurs goes down even more‐ by 1.36‐ relative to the control group. This suggests that intensity or level of depression and anxiety reduced for entrepreneurs in the treatment arm compared to the control arm, and the results improved over time. The 3‐month results are statistically significant at the 10% level (p=0.087). Table 4 reports the Intention to Treat (ITT) estimates of the effect of the intervention on PHQ‐ADS scores.

This also holds true when results are pooled across both rounds. On average, those in the treatment group experience a 1.07 reduction in PHQ‐ADS score relative to the control group. The effect is statistically significant at the 10% level (p=0.057). When standard errors are clustered, results are not statistically significant.

Table 4. Impact of Treatment on PHQ‐ADS Score

||**(1)**|**(2)**|**(3)**|**(4)**|
|---|---|---|---|---|
||**ANC**|**OVA**|**Poo**|**led**|
||**5 weeks**<br>**PHQ‐ADS score**|**3 months**<br>**PHQ‐ADS score**|**Pooled**<br>**PHQ‐ADS score**|**Clustered SEs**<br>**PHQ‐ADS score**|
|Treatment|‐0.736|‐1.358*|‐1.070*|‐1.070|
||(0.801)|(0.788)|(0.560)|(0.672)|
|Baseline score|0.434***|0. 429***|0.432***|0.432***|
||(0.0460)|(0.0457)|(0.0323)|(0.0591)|
|Round‐ ERKF|1.249|‐0.714|0.309|0.309|
||(0.826)|(0.830)|(0.583)|(0.635)|
|Age|‐0.00995|‐0.0197|‐0.0153|‐0.0153|
||(0.0383)|(0.0374)|(0.0267)|(0.0308)|
|Education|0.0326|0.00303|0.0164|0.0164|
||(0.0991)|(0.0984)|(0.0696)|(0.0858)|
|Constant|1.604|3.149|2.430|2.430|
||(2.178)|(2.164)|(1.530)|(1.967)|
|Observations|206|200|406|406|

_Note:_ Standard errors in parenthesis.

> 8 <mark>PHQ‐ADS is a measure where a score of 10 or above indicates prevalence and levels of anxiety and depression. It is a composite measure of PHQ‐9 (depression) and GAD‐7 (anxiety). The PHQ‐9 measures whether a person had difficulty in sleeping, felt hopeless/down, felt tired, had trouble falling asleep, had poor appetite, felt bad about him/herself, had difficulty concentrating, had been slow or restless, and had suicidal thoughts.</mark> The GAD‐7 measures whether a person felt nervous or anxious, could stop worrying, worried too much, had trouble relaxing, was very restless, became easily irritable, and felt afraid about bad things happening.

16
# **REFERENCE**

- Ades, Alberto, and Rafael Di Tella, 1997. "National Champions and Corruption: Some Unpleasant Interventionist Arithmetic." _Economic Journal_ 107 (443), 1023-42.

- Ades, Alberto, and Rafael Di Tella, 1999. "Rents, Competition, and Corruption." _American Economic Review_ 89 (4), 982-993.

- Alam, M. Shahid, 1990. "Some Economic Costs of Corruption in LDCs." _Journal of Development Studies 27_ (1), 89-97.

- Andvig, Jens Christopher, 1991. "The Economics of Corruption: A Survey," _Studi Economici 46_ (43), 57-94.

- Bacon, Robert, 1999. _Global Energy Reform in Developing Countries: A Scorecard._ Mimeo, World Bank Energy Sector Management Assistance Program, World Bank, Washington DC.

- Bardhan, Pranab, 1997. "Corruption and Development: A Review of Issues." _Journal of Economic Literature_ 35 (3), 1320-1346.

- Barzel, Yaram, 1974. "A Theory of Rationing by Waiting." _Journal of Law and Economics 17_ (1), 587-605.

- Baumol, William, 1990. "Entrepreneurship: Productive, Unproductive, and Destructive." _Journal of Political Economy_ 98 (5), 893-921.

- Beck, Thorsten, George Clarke, Alberto Groff, Philip Keefer, and Patrick Walsh, 2001. "New Tools in Comparative Political Economy: The Database of Political Institutions." _World Bank Economic Review 15_ (1), 165-176.

- Becker, Gary S., 1968. "Crime and Punishment: An Economic Approach," _Journal of Political Economy_ 76 (2), 169-217.

- Becker, Gary S., and George J. Stigler, 1974. "Law Enforcement, Malfeasance, and Compensation of Enforcers." _Journal of Legal Studies 3_ **_(,_** 1-19.

- Bertrand, Marianne and Sendhil Mullainathan, 2001. "Do People Mean What They Say? Implications for Subjective Survey Data." _American Economic Review: Papers and Proceedings_ 91 (2), 67-72.

- Bliss, Christopher, and Rafael Di Tella, 1997. "Does Competition Kill Corruption," _Journal of Political Economy_ 105 (5), 1001-1023.

- De Long, Bradford J., and Andrei Shleifer, 1993. "Princes and Merchants: European City Growth before the Industrial Revolution." _Journal of Law and Economics_ 36 (2), 671701.

25
Policy Research Working Paper 10012

# **Abstract**

This paper estimates the impact of a large negative childcare shock on gender gaps in entrepreneurship using the shock created by national COVID-19 school closure policies. The paper leverages a unique data set of monthly enterprise data collected from a repeated cross-section of business owners across 50 countries via Facebook throughout 2020 and in 2021. The paper shows that, globally, female-led firms were, on average, 4 percentage points more likely to close their business and experienced larger revenue declines than male-led firms during the COVID-19 pandemic in 2020 (male firms closed at a rate of 17 percent in 2020, and 12 percent in 2021). The gender gap in firm closures persisted into 2021. The closing of schools, a key part of the care infrastructure, led to higher business closures, and women with children were more likely to close their business in response to a school closure policy than men with children. Female entrepreneurs were found to take on a greater share of the increase in the domestic and care work burden than male entrepreneurs. Finally, the paper finds that women entrepreneurs in societies with more conservative norms with respect to gender equality were significantly more likely to close their business and increase the time spent on domestic and care responsibilities in response to a school closure policy, relative to women in more liberal societies. The paper provides global evidence of a motherhood penalty and childcare constraint to help explain gender inequalities in an entrepreneurship context.

This paper is a product of the Africa Region, Gender Innovation Lab and the Development Research Group, Development Economics. 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://www.worldbank.org/prwp. The authors may be contacted at mgoldstein@worldbank.org; pgonzalezmartine@worldbank.org; spapineni@worldbank.org; and jwimpey@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
# **Figure 2:  Position in the distribution of per capita household consumption**

<!-- Start of picture text --> All Low and Middle Income Countries<br>17<br>32<br>37 38<br>42<br>64<br>35<br>33<br>36 34<br>33<br>25 49<br>35<br>25 27 28<br>12<br>Wage and Salary Non-Paid Employee Employer Own Account Agriculture Not Employed<br>tercile1 tercile2<br>tercile3<br>100<br>80<br>percent 60<br>40<br>20<br>0<br><!-- End of picture text -->

# **Figure 3: Percent of men and women in each employment category**

<!-- Start of picture text --> male 4 2 0 44 11 38<br>ECA<br>female 110 33 7 58<br>male 13 4 1 44 16 22<br>LAC<br>female 10 1 2 32 4 51<br>male 7 4 2 39 20 28<br>MENA<br>female 201 11 18 68<br>male 15 1 3 26 37 19<br>SA<br>female 2 02 5 19 72<br>male 13 2 2 29 34 20<br>EAP<br>female 10 1 4 17 20 49<br>male 12 1 1 13 45 28<br>SSA<br>female 13 1 2 5 40 40<br>0 20 40 60 80 100<br>percent<br>own_account employer<br>non_paid_employee wage_and_salary<br>agriculture not_employed<br><!-- End of picture text --> 30
China’s system for assigning fiscal revenues and expenditures gives its central government significant control over the country’s fiscal resources and creates strong incentives for subnational government to seek resources from the center. Therefore, at the inception of the crisis, with the fiscal buffers built up in normal times, the central government was in a strong position to allocate and leverage fiscal resource to implement a large and speedy countercyclical stimulus.

If the global economy slows down sharply or enters another deep recession—as a result of the crisis in Europe or other events, such as a sudden and large increase in international oil prices— China could consider another large fiscal expansion to avoid a substantial slowdown in its economy. A massive stimulus would support both regional and global growth. Although the debt to GDP ratios at both the central and subnational levels rose markedly in 2008–10, China’s fiscal space remains large. Some recent OECD estimates suggest that Chinese policy makers have also begun to relax their fiscal stance. The government debt ratio (including the contingent liabilities of all off-budget entities) dropped substantially in 2011. Some recent estimates suggest that the overall debt ratio could decline to about 44 percent of GDP by the end of 2012 compared with 54 percent in 2010 (OECD 2012).

If well managed, an infrastructure investment–focused plan could once again generate large multipliers in the short run and increase production capacity and the rate of growth of productivity in the long run. Going forward, emphasizing rural infrastructure, as well as urban infrastructure to facilitate sustainable urbanization, which had been impeded due to the strategy of prioritizing heavy industries, to support investment and consumption remains crucial for the rebalancing of the economy (Lin 2012). Due to the rapid urbanization since the 1980s, there is a large gap in the provision of basic infrastructure in urban areas and massive investments are required (World Bank 2012). These investments can continue to finance themselves, thus nullifying the Ricardian equivalence–type effects and avoiding the tax today or tax later dilemma.

<mark>The success of China’s fiscal stimulus offers several useful lessons for both advanced and emerging economies.</mark> 22
experienced a crisis (as indicated by the insignificant coefficient on the banking crisis variable). We also observe that more developed and more populous countries are more likely to adopt Basel III capital regulations, even after controlling for regional peer effects.

**Table 5: Peer effects and the adoption of capital regulations**

|VARIABLES|(1)<br>Basel III<br>adoption - Yes<br>=1|(2)<br>Countercyclical capital<br>buffer adoption - Yes =1|(3)<br>Capital conservation<br>buffer adoption - Yes<br>=1|
|---|---|---|---|
|Banking Crisis|-1.039|0.458|-0.318|
||(0.811)|(0.897)|(0.700)|
|Average dependent variable - Region|3.947***|4.669***|3.382**|
||(1.314)|(1.360)|(1.380)|
|ln (GDP per capita) 2010|0.975***|0.099|0.642|
||(0.361)|(0.397)|(0.440)|
|Inflation 2010|0.114|-0.184*|-0.235**|
||(0.082)|(0.095)|(0.095)|
|ln(population) 2010|0.824***|0.758***|0.573***|
||(0.209)|(0.192)|(0.164)|
|Regulatory Quality 2010|0.775|0.715|-0.144|
||(0.654)|(0.542)|(0.506)|
|Constant|-23.707***|-14.111**|-15.247***|
||(4.810)|(5.532)|(5.331)|
|Observations|117|98|98|

Note: *, **, and *** represent statistical significance at 10%, 5%, and 1% two-tailed level, respectively. Robust standard errors for heteroscedasticity appear in parentheses. Off-shore financial centers included in the computations.

# **4 Summary and conclusions**

In this paper we summarize recent developments in bank regulation and supervision across 159 economies. Three main conclusions follow from the analysis of the World Bank’s 2019 BRSS. First, reforms after the crisis led to an increase in capital requirements and regulatory capital holdings at financial institutions. However, these increases were accompanied by shifts toward asset categories with lower risk weights. The accuracy of those risk weights is therefore crucial for understanding whether increases in regulatory capital holdings are a reliable signal of greater banking stability. The quality of capital may not have improved significantly, as most authorities now allow a wider array of instruments to satisfy Tier 1 35
# **b. Change in the likelihood of receiving remittances by consumption deciles of 2005**

<!-- Start of picture text --> Rural areas Urban areas<br>1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10<br>Consumption decile in 2005 Consumption decile in 2005<br>95% confidence intervals 95% confidence intervals<br>40 40<br>30 30<br>20 20<br>10 10<br>Change in the likelihood of receiving remittances<br>0 0<br><!-- End of picture text --> Source: IHDS, 2005 and 2012

**Figure 9. Share of households receiving benefits and changes over time**

- **a. Likelihood of receiving benefits by consumption deciles in 2005**

<!-- Start of picture text --> Rural areas Urban areas<br>1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10<br>2005 2012 2005 2012<br>60 60<br>50 50<br>40 40<br>30 30<br>Percentage of households (%) 20 20<br>10 10<br>0 0<br><!-- End of picture text --> _(Continues in the next page)_ 24
study of nations. And in the U.S. Zahran et al. (2006) find that “respondents living within 1 mile of the nearest coastline at negative relative elevation to the coast are less (not more) likely to support government-led climate initiatives (p 783). Again in relation to the hierarchy of needs argument, consider the earlier discussed negative relationships between wealth and concern at individual, state level and national data (e.g. Sandvik 2008).

# **“All Is Well”**

A fourth explanation for the fact that people around the world have engaged in so little response to climate change is that they believe that everything is fine. This could be either because they do not think climate change is happening, believe that their governments will take care of things, or that international agreements on emissions reductions will be effective. This perspective could be a variation of either “climate skepticism,” “faith in government” or “technological optimism.” A sense of all being well can also be a reflection of faith in a higher power, or a sense of fate. Let us consider an in depth example in Norway: In the past decades, the Norwegian government has become visibly involved in the issue of climate change. Perhaps residents felt that things were in good hands? Norwegian sociologist Ottar Hellevik explores the possibility of faith in the government as a causal factor behind the national pattern of declining concern about climate change since 1980. He does not, however, interpret optimism as the force behind the trend in declining concern. Rather, “results from the Monitor surveys tend to contradict such a trend of optimism, however. The percentage disagreeing with the proposition – “When negative environmental conditions are revealed, business takes the problem seriously and cleans up as soon as possible” – rose from 45 percent in 1995 to 56 and 55 percent in 1997, 1999 and 2001 respectively. The public thus seems to have become _more_ rather than _less_ skeptical with regard to the environmental status of business leaders. Further, when queried in 2001 as to anticipated development trends for selected areas of society, only 14 percent of the population believed that the situation with regard to environment and pollution would improve, while 31 percent expected deterioration (43 percent replied, “no major changes” and 10 percent “don’t know” (Hellevik, 2002, 13-14).<sup>3</sup>

> 3 p.13 in Ottar Hellevik “Beliefs, Attitudes and Behavior Towards the Environment” pp 7-19 in Realizing Rio in Norway. This phenomenon is also reported in the United States (see, e.g., Immerwahr, 1999).

25
15 where _i_ ∈ [1,N] and _t_ ∈ [1,T] refers to country _i_ at time _t_ ; δ1 and δ2 are scalar parameters while δ<sup>'</sup> 3 , δ<sup>'</sup> 4 and δ<sup>'</sup> 5 are vectors; _Yit_ is the dependent variable; θ _it_ is the measure of decentralization; α _i_ is a vector for country fixed effects;<sup>λ</sup> _t_<sup>is a vector for</sup> time fixed effects; _X it_ is a vector of control variables; and ε _it_ is the error term that is assumed to be serially uncorrelated. Differences of magnitude in variables across observation units indicate a possible presence of heteroskedasticity in ε _it_ .

The major difficulty associate with using OECD surveys is that they have been conducted on an occasional basis and data are available only for three years (1997 to 1999 for Czech Republic, Estonia, Hungary, Latvia, Lithuania and Poland; and 1998 to 2000 for Bulgaria, Romania, Slovak Republic and Slovenia). Given the small size of the unbalanced panel sample of this study (30 observations), only simple basic econometric tools can be used for estimations. Feasible General Least Square correcting for panel heteroskedasticity is too costly in degree of freedom to be estimated (adding 10 more coefficients to estimate). The solution to this has been to ignore panel heteroskedasticity and to consider instead the sample as equivalent to a 30 observations cross-section heteroskedastic sample when using feasible GLS.

All the variables used in regressions are summarized in Table A-1. In the replication of the Davoodi and Zou model, the dependent variable ( _Yit_ ) is the annual per capita GDP growth rate. Davoodi and Zou only used one proxy for decentralization (θ _it_ ) in their study: subnational share of government expenditure, net of grants. Measures of decentralization from Ebel and Yilmaz as well as the new measures of this study will also be included as θ _it_ . As it was the case in the Davoodi and Zou study, countries fixed effects (α _i_ ) as well as time fixed effects (<sup>λ</sup> _t_<sup>) will be considered in this model. Joint</sup> significance F-test on both sets of dummies reveals that both effects are significant in this model. The set of control variables ( _X it_ ) included in the replication is the same one as in the original study, except for the tax rate variable, which was dropped due to non-