rafmacalaba/data-use-mentions-extended huggingface dataset:
of logical programming commands (“If-Then-Do”statements) that designate unambiguously what actions the machine will perform and in what sequence at each contingency to achieve the desired result.”While Autor et al (2003) use routineness to designate which jobs can be easily performed by computers, the jobs that are classi...ed as routine also include the jobs in manufacturing that we typically think of as being o¤shorable. These jobs include: attaching hands to faces of watches, sewing fasteners and decorative trimming to articles and, though not mentioned explicitly in their paper, include services tasks that we think of as o¤shorable such as answering telephones.

We can contrast this occupation-based approach to a well-known alternative, which is to examine the changes in import penetration across industries (what Goldberg and Pacvnik refer to as the “di¤erential exposure approach”). A di¢ culty with that approach is that, in the event that workers can change industries more easily than occupations, such an approach will miss the main e¤ect; industry premia will be largely arbitraged away, but premia to each occupation can be large and very much a¤ected by trade. Ebenstein et al address this problem by calculating an occupation-speci...c measure of o¤shoring, import competition, and export activity, and show that although international trade has not had large e¤ects on industry premia, it has had large, signi...cant e¤ects on occupation-speci...c wages for routine workers.

Ebenstein et al merge Current Population Survey (CPS) data on US wage earners from 1983 through 2002 with data on import competition, export activity, and o¤shoring employment of U.S. multinational ...rms to show that the impact of o¤shoring on labor-market outcomes depends both on the location of o¤shore activity and on the routineness of the task performed by the worker. Expansion in o¤shore employment in low-income locations is associated with wage reductions for
# **1. Introduction**

The existence of large informal labor markets in developing countries has attracted renewed attention because of its connection to poverty, low productivity and lack of social protection. One issue of concern is whether non-contributory programs introduced to address the lack of social safety nets for those not in the formal sector are providing perverse incentives for formal sector workers (Levy, 2008).<sup>2</sup> Formal sector workers could now avoid having to contribute to the formal social security program (SS) by moving to the informal sector while receiving (at least some) services under the new program. We propose to test this hypothesis by looking at the effect of rolling out _Seguro Popular_ ( _SP_ ), a non-contributory health program for informal households in Mexico from 2000(Q2) - 2009(Q2), using longitudinal data constructed with rotating panels of households.

This issue is of particular relevance in Mexico as other work has shown a relatively high degree of mobility of workers in Mexico between the formal and informal sectors. This feature has often been raised as evidence that formal and informal sectors are not segmented. Maloney and Bosch (2006) show high labor mobility and that entry and separation rates are not significantly different across the two sectors. In addition, the probability of movement between sectors does not depend on the age of the worker, which seemingly contradicts the hypothesis that informal workers queue to get formal jobs. Maloney (1999) finds that wages sometimes increase and sometimes decrease as a worker moves from one sector into the other, and that the substantial flows in both directions persist even in periods of economic expansion. Madrigal and Pagés (2008) and Maloney (2004) find that workers value features of informal work such that it should not necessarily be taken as an inferior or residual employment option. What remains a question is whether the existence of _SP_ has motivated some households to stop paying into SS to be able to qualify for free health insurance. Or, alternatively, if the
Business and the Law (WBL) database (Hyland et al., 2020, 2021). The WBL database captures inequality in legislation across eight categories – mobility, workplace, pay, marriage, parenthood, entrepreneurship, assets, and pensions. Reforming gender discriminatory laws is associated with increased female labor force participation, business ownership, and may enable women to take up better jobs such as being the top manager of a formal establishment (Amin and Islam, 2015; Islam et al., 2019; Htun et al., 2019). Similar to how firm entry can be restricted through burdensome regulations (Djankov et al., 2002), we hypothesize that burdensome and unequal regulations may restrict entry of women-owned businesses in the formal sector, pushing them into the informal economy.

In this study we explore whether reforming discriminatory laws affects the choice of a female entrepreneur to start a business in the formal or the informal sector. We achieve this by tracing the origins of formal businesses surveyed in the World Bank Enterprise Survey database (WBES). Three important pieces of information are gathered – (i) the start date of the business; (ii) whether the business was formal (registered) at start; and (iii) whether the business is owned by a woman or a man. We match the year of birth of the business to the legal environment in the same year using the WBL database that documents unequal laws over the last 50 years. Piecing these data sources together allows us to estimate whether unequal laws increased the likelihood that a business with female owners would start operating informally vis-à-vis a business entirely owned by men. We further explore whether starting a business informally has any differential effect on subsequent firm performance depending on the gender of the owner(s). We find that discriminatory laws increase the likelihood that firms with female participation in ownership will start an informal business; as anticipated, the relationship does not hold for enterprises that are solely owned by men. The global finding appears to be driven by
estimation of statistical precision, meaning that the estimated SEs obtained using the private NSO coordinates will arguably provide more accurate estimates of precision.

||BP (NSO)|BP (Public)|OLS (Public)|
|---|---|---|---|
|EA|0.155|0.165|0.186|
|TA|0.039|0.0.038|0.036|
|Region|0.0245|0.0199|0.011|
|National|0.0230|0.0178|0.0075|

Table 8: Mean standard errors (SEs) of poverty estimates from BP (NSO), BP (Public), and OLS for different levels of aggregation.

Provided that the spatial correlation structure is only partially destroyed by scrambling the coordinates, this explanation would predict that SEs obtained with public coordinates would be higher than SEs obtained using OLS which would fully ignore any spatial correlation structure in the errors, yet lower than SEs obtained with the private NSO coordinates (where the spatial correlation structure is fully accounted for). Fully ignoring the spatial correlation structure, as the OLS model does, would lead to a comparatively larger downward bias in SEs at more aggregate levels (as errors are – incorrectly assumed to average out) relative to SEs obtained with the spatial regression models. Both predictions are born out, as can be seen in Table 8 (which also includes estimates of SEs obtained with OLS). Standard statistics measuring the degree of spatial correlation found in the residuals are reported in Table 6, which confirm that the errors from the regression model with public coordinates exhibit a weaker spatial correlation structure.

# **5 Concluding remarks**

This study investigates whether an accurate poverty map could be obtained by combining remote sensing data that are available in the public domain with household consumption survey data. This approach to poverty mapping takes advantage of the fact that geo-referencing survey locations (i.e
# 1. **Introduction**

There is little available knowledge on what determines money wages in sub-Saharan Africa, or indeed on whether there exists a stable relationship among wages, productivity, GDP, inflation, policy changes and unemployment or informal sector activity. In this paper, we study how wages are affected by short- and long-run changes in the aforementioned variables in the case of Zimbabwe. The importance of knowing the answer to this question may be illustrated by considering economic reforms. Structural adjustment programs may cause reductions in aggregate demand due to decreased government spending and increased real interest rates. If wages are downwards-rigid, and, therefore, unable to adjust to changes in aggregate demand then the unemployment rate or informal sector activity increase. On the other hand, if wages are flexible, then the decrease in aggregate demand may be mitigated by falling wages and, therefore, causing a more limited increase in unemployment or informal sector activity. In the latter case the labor market is characterized by a macro-wage curve.

The main questions addressed are the following: (1) are wages affected by increased productivity, economic activity, prices, policy changes and unemployment; (2) does there exist a macro wage-curve; and, (3) did the economic structural adjustment program (ESAP) cause a structural change in the labor markets. The main findings are that wages are flexible-both upwards and downwards. Hence, the labor market is able to adjust to economic shocks. The main cause of falling real wages in Zimbabwe is reduced economic activity.

This paper is the first in a series of papers studying Zimbabwean labor markets. Another paper analyzes wage and productivity determination in Zimbabwe but in contrast to this paper, the study is based on findings from micro level data (see Verner, 1998). The findings, using data on employees matched with data on firms, can be summarized as: (1) female employees are paid less than males and the negative wage premium do not match a corresponding negative productivity premium; (2)
buttressed it with a data protection agency (DPA). Certain countries, such as France, have had a DPA since the 1970s, when large state-owned datasets were the main concern of the public. While most DPAs are independent agencies, some countries have embodied them with ministries or policymaking bodies (Makulilo 2016).

|**Table 14: Cybe**|**rsecurity meas**<br>**Encryption**|**ures around t**<br>**Internal**<br>**policy**|**he word**<br>**Data manager**|**Risk**<br>**assessment**|**Breach**<br>**notifications**|**Supervisory**<br>**authority**|
|---|---|---|---|---|---|---|
|**Albania**||**●**||||**●**|
|**Armenia**|**●**|**●**|||**●**|**●**|
|**Bangladesh**|||||||
|**Burkina Faso**||**●**||||**●**|
|**Canada**||**●**|**●**||**●**|**●**|
|**Colombia**||**●**||**●**|**●**|**●**|
|**France**|**●**|**●**|**●**|**●*
Figure 2: Regression Discontinuity First Stage (a) Sample Frame (N=5,554) <!-- Start of picture text --> −.5 −.4 −.3 −.2 −.1 0 .1 .2 .3 .4 .5<br>Hectares from acre or hectare cutoff<br>14<br>13<br>12<br>11<br>10<br>9<br>Log relief<br>8<br>7<br>6<br>5<br><!-- End of picture text --> (b) Surveyed Households (N=2,897) <!-- Start of picture text --> −.5 −.4 −.3 −.2 −.1 0 .1 .2 .3 .4 .5<br>Hectares from acre or hectare cutoff<br>13<br>12<br>11<br>10<br>9<br>Log relief<br>8<br>7<br>6<br><!-- End of picture text --> Notes: Panel (a) plots the log relief amount for households benefiting from 100% debt relief (left) and conditional 25% debt relief (right) for all 2,897 surveyed households. The estimated discontiˆ nuity at _x_ = 0 is _γ_ = 1 _._ 330, SE( _γ_ ˆ) = _−._ 064. Panel (b) plots the log relief amount for households benefiting from 100% debt relief (left) and conditional 25% debt relief (right) for all 2,897 surˆ veyed households. The estimated discontinuity at _x_ = 0 is _γ_ = 1 _._ 330, SE( _γ_ ˆ) = _−._ 064. Dashed lines represent local linear regressions with a bandwidth of .01 ha to each side of
Based on survey data and applying dynamic analysis and a Markov-chain approach for predictions, Hanousek and Palda (2008) find that in the Czech Republic between 1995 and 2006, the percentage of tax evaders first increased, then leveled off and they suggest that it is now falling along a quadratic path.

**Table 3: Prevalence of undeclared work in the New EU Member States according to the EU Commission**

|1. Estonia|7.3 % of GDP in 2004, a decline by 2.7 percentage points since<br>2000.|
|---|---|
|2. Czech Republic|9-10%ofGDP,no change in recentyears|
|3. Slovakia|13-15% of GDP estimated in 2000 and moderate decline in recent<br>years|
|4. Poland|12-15% of GDP after 14 % in 2003|
|5. Lithuania|6% of total employment. Slight decrease from 8 % of total<br>employment and 15-19% of GDP in 2003|
|6. Slovenia|17%ofGDP,no change in recentyears|
|7. Hungary|18% of GDP,no change in recentyears|
|8.Latvia|18%ofGDP,no change in recentyears|
|9.Romania|16-21%ofGDP,no change in recentyears|
|10. Bulgaria|22-30% of GDP estimated in 2002/2003; survyeys indicate a<br>marked increase in recentyears|
|Undeclared work in selected<br>other EU countries|Sweden: 5% of GDP and 11% of workers<br>Denmark: 3% of GDP<br>Spain: 12.3% of GDP<br>Greece: above 20% of GDP|

_Sources:_ EC 2007; Undeclared Work in an Enlarged Union (Renoy et al., 2004); Statistics Estonia.

# **3. The Role of Taxes According to Opinion Polls**

13. In a survey, launched by the EU
OPTIMAL SIMPLE FISCAL RULES 31

- [8] Garcia-Cicco J and E. Kawamura (2015), “Dealing with the Dutch disease: Fiscal rules and macro-prudential policies” _Journal of International Money and Finance 55_ 205-239

- [9] Garcia-Cicco J, R Pancrazi, and M Uribe (2010) “Real Business Cycles in Emerging Countries?" _American Economic Review_ 100, 5: 2510-2531.

- [10] Gonzalez G., F. Munoz and K. Schmitt-Hebel (2013) “Optimal Dynamic Fiscal Policy with Applications to Chile and Norway”, Working Paper PUC-Chile.

- [11] Kumhof M. and D. Laxton (2013) “Simple fiscal policy rules for small open economies” _Journal of International Economics_ 91 113-127

- [12] Jeanne O. and D Sandri (2016) “ Optimal Reserves in Financially Closed Economies”, NBER Working Paper 22139

- [13] Pieschacon A (2012) “The value of scal discipline for oil-exporting countries”, _Journal of Monetary Economics_ 59 250–268

- [14] Schmitt-Grohe S. and M. Uribe (2003) “Closing small open economy models” _Journal of International Economics_ 61(1) 163-185

- [15] Schmitt-Grohe S. and M. Uribe (2017) “Open Economy Macroeconomics”, Princeton University Press

# Appendix A. The Persistence of Commodity Price Shocks

The persistence and volatility of the price shocks are calibrated to different commodity prices, reported in Table 7. We estimate an AR(1) process for the natural log of real prices of beef, coffee (Robusta), soy beans, bananas and coffee (Arabica) using annual data from World Bank’s “Pink Sheet” on commodity prices.<sup>36</sup> We complement our estimates with those of BJS2013 who use commodity price data from the International Finance Statistics (IFS) to estimate the persistence of petroleum, copper, gold and sugar. For the sake of comparison, we report the estimates in Cashin _et al_ (2000) (
estimating the _ex-post_ standard errors of poverty and inequality measures from HBSs, that is, _complex measures_ from _complex surveys_ . In this way, it allows the evaluation of the impact of the so-called _implicit stratification_ (or _hidden_ ; Wolter, 1985), which is present when PSUs are selected with systematic sampling from one or more lists that are ordered according to some variables correlated with the phenomenon under investigation.

The present paper is composed of five sections. Following this introduction, Section 2 presents the theory behind the estimation of standard errors in complex surveys. Attention is paid to the two-stage stratified sampling design, where, in the first stage, selection of PSUs is performed with systematic sampling, i.e., where implicit stratification is present. Since systematic sampling can be seen as a random selection of a single PSU from each implicit stratum, it is not possible to derive a consistent estimator of the sampling variance (Wolter, 1985). Therefore, recent replication methods have been developed and implemented for estimating the variance of complex measures from complex surveys. Among the most adopted methodologies are bootstrap, Taylor Linearisation, Jack-knife Repeated Replications (JRR) and Balanced Repeated Replications (BRR). On this basis, the second part of Section 2 briefly presents the recent methodology of Verma and Betti (2011) for the implementation of a variant of JRR in the case of systematic selection of PSUs and the possibility of decomposition of the design effect in several components (Kish, 1965; Verma, 1991; Liu _et al._ , 2002).

The definition of these components is useful for highlighting the proposed implicit stratification. As previously mentioned, we aim to introduce a further implicit stratification by selecting the PSUs with a systematic sampling within each explicit stratum. PSUs are ordered by their relative ranking in terms of the per capita consumption expenditure obtained from the poverty mapping approach. Therefore, Section 3 is devoted to a brief presentation of the World Bank methodology.

Since, in general, we believe that any new methodological proposal is useful
919**|3.799***|8.834***|-0.013|
||(2.124)|(2.471)|(0.886)|(1.043)|(1.467)|(1.000)|
|Growth in GRP per capita|-0.113|-0.137|0.159|-0.154**|-0.190|0.050|
||(0.097)|(0.205)|(0.120)|(0.071)|(0.128)|(0.079)|
|Observations|237|238|238|238|238|238|
|R-squared|0.309|0.721|0.677|0.580|0.820|0.718|
|Year dummies|Yes|Yes|Yes|Yes|Yes|Yes|

Source: Author’s calculations using Sakernas data Notes: Robust standard errors in parentheses. ***p<0.01, **p<0.05, *p<0.1 22
Policy Research Working Paper 8825

# **Abstract**

This paper characterizes the trade-off between the income gains and the inequality costs of trade using survey data for 54 developing countries. Tariff data on agricultural and manufacturing goods are combined with household survey data on detailed income and expenditure patterns to estimate the first-order effects of the elimination of import tariffs on household welfare. The paper assesses how these welfare effects vary across the distribution by estimating impacts on the consumption of traded goods, wage income, farm and non-farm family enterprise income, and government transfers. For each country, the income gains and the inequality costs of trade liberalization are quantified and the trade-offs between them are assessed using an Atkinson social welfare index. The analysis finds average income gains from import tariff liberalization in 45 countries and average income losses in nine countries. Across countries in the sample, the gains from trade are 1.9 percent of real household expenditure on average. We find overwhelming evidence of a trade-off between the income gains (losses) and the inequality costs (gains), which arise because trade tends to exacerbate income inequality: 45 countries face a trade-off, while only nine do not. The income gains typically more than offset the increase in inequality. In the majority of developing countries, the prevailing tariff structure thus induces sizable welfare losses.

This paper is a product of 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 brijkers@worldbank.org, eartuc@worldbank.org, and guido.porto@depeco.unlp.edu.ar.

_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
We take advantage of the availability of panel data for these households and make a comparison between 1997 (before the program started) and 2000. For the sequential probit regressions we take three dependent dichotomous variables: first, it takes value 1 if the child goes to school and does not work; second, it takes value 1 if the child goes to school and works; and third, if the child does not go to school and works. We omit the case where the child does not go to school and does not work. We also run a multinomial logit equation for three cases of interest compared to a child that goes to school and does not work: the probability that the child goes to school and works, does not go to school and works, and does not go to school and does not work. Finally, we take several poverty and inequality measures among indigenous, bilingual and Spanish-speaking households for both years. For a better examination of the depth and severity of poverty in indigenous, bilingual and Spanish groups, the Foster-Greer-Thorbecke index is used.

# **5. Data Description**

The data used here are the PROGRESA/OPORTUNIDADES survey instruments that ask the question whether the person speaks an indigenous language. They also include information on earnings, household structure, school, work and social transfers. Examination of this data set gives valuable policy information on whether or not government programs are useful for decreasing inequality, particularly by pulling up the lower tail of the distribution, where indigenous people largely reside. PROGRESA/ OPORTUNIDADES in Mexico is one of the most comprehensive demand-side financing (or conditional cash transfer) programs in the world. The program provides cash stipends to poor families in exchange for ensuring their children’s school attendance. Parker and Skoufias (2001) indicate that PROGRESA has led to significant improvements in educational indicators and outcomes. In fact, the program has led to higher school attendance rates and lower school dropout and repetition rates. There is also evidence of reduced child labor. PROGRESA has nearly
|6.59|
|N|18,138|18,139|18,139|

_Source_ : Author’s analysis based on data from the Ethiopian Demographic and Health Survey (in years 2005, 2011, and 2016). _Note_ : The dependent variable in each column is an indicator that equals 1 if the statement is believed to be true and 0 otherwise. The sample includes all married women born between 1970 and 1988. A 2SLS � model is estimated where Years of Schooling _izy_ is the predicted level of schooling, instrumented with the free primary education (FPE) intensity measure _Izy_<sup>FPE</sup> , two mother tongue instruction (MTI) intensity measures _Izy_<sup>MTI-T</sup> and _Izy_<sup>MTI</sup> , which denote the measures for MTI regions without and with script change, respectively, and the interactions for regions in which two interventions occurred. All regressions include birth year and zone fixed effects, zone-specific linear trends, and a cubic for age. Each estimate is from a unique regression. Standard errors are clustered at the zone level and shown in parentheses; _p_ -values are shown in square brackets.

A.31