rafmacalaba/datause-encoder-data huggingface dataset:
The remainder of the paper is organized as follows. In section 2, we provide a detailed description of the data employed and provide summary statistics. In section 3, we present our identification strategy for examining the impacts of exporting on the share of workers trained, and present the corresponding results. In section 4, we use the worker-firm information to examine whether technical upgrading is associated with higher labor earnings for the corresponding workers within exporting firms. Section 5 concludes.

# **2 Data**

## **2.1 Data description**

The analysis in this paper links and examines three main sets of administrative data for the Brazilian manufacturing sector in the period 2009-2012. _Rela ̧c ̃ao Anual de Informa ̧c ̃oes Sociais_ (RAIS) is a longitudinal census gathering administrative social security records for employees and employers. It is collected by the Ministry of Labor in a compulsory survey of all firms and their registered workers, and covers a total of around 230 thousand formally registered firms and over 3.5 million workers each year in the manufacturing sector. RAIS provides information on workers’ demographics (age, gender, schooling, race), job characteristics (occupation, wage, hours worked), as well as hiring and termination dates. It also includes information on a number of firm-level characteristics, notably number of employees, geographical location and industry code. Unique identifiers for workers and firms make it possible to follow them over time. We have performed extensive checks to guarantee the accuracy of the worker data using information on gender, date of birth, and maximum schooling level achieved. Only full-time wage earners with complete information on demographics and job attributes were kept for the analysis.<sup>2</sup> Using the unique firm identifiers, we have merged these data with customs records on export transactions collected by _Secretaria do Com ́ercio Externo_ (SECEX) of the Ministry see Greenaway and Nelson (2000), Bastos and Silva (2009), Falvey, Greenaway and Silva (2008, 2010) and the references therein.

> 2In particular, we kept for analysis employees working more than 20 hours per week, aged between 16 and 65, and earning at least the national minimum wage.

5
to academic knowledge. However, we note that the results presented below should be interpreted as the reduced form impacts of PAL transfers, as they combine both the direct and the indirect effect of the program. In particular, there are likely dynamic complementarities among inputs (Heckman and Cunha, 2007). For example, children of PAL recipients might attend better (and more expensive) schools (a higher _Qi_ 2) because transfers increased the family budget, or, they may attend better schools because the returns to school quality are increasing in child health investments ( _HIi_ 1).

# **5.1 Health stock and health inputs**

We use information from the evaluation follow-up survey in order to study whether PAL, either in the in-kind or cash modality, had an effect on proxies for health status and parental health investment of children aged 0 to 6 at the baseline. When looking at the health stock we focus on four indicators: 1) the caregiver reported probability that the child was sick in the four weeks prior to the interview; 2) the child height per age, expressed as a z-score; 3) the child weight per age, expressed as a z-score; 4) whether the child was anemic or not, based on the analysis of a blood sample.<sup>19</sup> The impacts of PAL on these variables are reported in Table 8. For each outcome, we present results for two specifications. In the first one, we present our baseline specification for the whole sample (column 1, 3, 5, 7), in the second one we restrict the sample to those children for which we observe at least one ENLACE test score during the time period between 2007 and 2013 (columns 2, 4, 6, 8). For the probability of being sick, height per age and weight per age, we find effects that are close to zero, both for the in kind and the cash modality, irrespective of whether we consider the full sample or the sample of children for which we observe at least one standardized test scores. We do find that both children in the in kind and the cash group were about 3 percentage point less likely to be anemic than those in the control group. The relative size is sizable when compared to the prevalence of anemia in the control group (19 percent), but the effect is not statically different from zero.

In Table 9 we look at the effect of PAL on the calorie consumption, the intake of one macronutrient (protein) and five micronutrients (vitamin C, iron, zinc, calcium, and retinol). For each outcome we present the two specifications discussed above. Only in-kind children display an increase in the calorie consumption, but the effect is not statistically different from zero. The program had no effect on the intake of protein. We do find a large and statistically

> 19Results not reported for space reasons show for the control group that the anemia status is a strong predictor of the performance test scores. In particular, children who were found with anemia in the follow-up survey scored on average 0.2 standard deviations lower than non-anemic children both in math and Spanish.

17
**Policy, Research, and External Afflrs**

# **Nlonal Economic Management**

WPS 713 'T'his paper- aproduct of thc National Economic Management Division, Economic Development Institute - is part of a larger effort in PRE to analyze the sources and dynamics of inflation in transitional socialist economies. Copies are availablc free from the World Bank, 1818 H Street NW, Washington, DC 20433. Please contact Olga Del Cid, room M7-047, extension 39050 (62 pages, with figures and tables).

Commander and S,aehr address the issue of how wages are determined in socialist economies.

They distingL.sh between different types of economic regime, in terms of how much decentralization is permitted and how extensive are market-based features or rules.

Wages are commonly assumed to be exogenously given in socialist systems, regardless of regime. Commander and Staehr show that this assumption is not warranted, given the use of incentive-based systems in thcsc cconomies.

Both the classical planned economy and the partially reformed regime face the problem of motivating workers in thc absence of monitoring and of such conventional penalties as unemployment. How do these regimes try to resolve the incentive problem?

In a centrally planned cconomy, the piecerate mechanism is an attempt to stimulate more effort among workers. But Commander and Stachr show, using game-theorctic models, that in cooperative settings the outcome can be lower productivity than desired and that in noncooperative settings the outcome can be higher wages than warranted.

They interpret the partially reformed socialist economy as an attempt to refine the motivational ,tructure by introducing a manager between the planner and the workcrs. One objective is to provide a framework in whichl workers and managers engage in a cooperative game to determine wages and output with the incentive structure given in effect by the planner. They show how this can yield undesired results, when managers and workers cooperate, playing a noncooperative game with the planner.

They present a preliminary treatment of an economic regime such as the one that existed in Poland after January 1990, where market-based rules almost fully predominate. Their objective is to provide coherent foundations for wage equations that can be tested empirically.

They prepare estimates for the partially reformed economies of Hungary and Poland.

Data and other limitations limit thc conclusions that can be drawn. But Commander and Stachr show wages to be strongly associated with prices and rather less strongly associated with productivity. Hence, wages should not be considered fully exogenous, even if institutional and other factors indicatc more exogeneity than would exist in a standard market economy.

Thc PRE Working Papcr Series disseminates the findings of work under wiay in the Bank's Policy, Research, and External AffaitsComplex. An objcctie eofthc scries is to getthcsc findings out quickly. cven ifprcsentations are less than fully polished. The findings, interpretations, and conclusions in thcse papers do not necess.arily represent official Bank policy.

Produced by the PRE Dissemination Center
to some $500 per capita on average for the CEECs, $1,000 for the Czech Republic, and exports in the $150-250 range for Morocco, Syria, and Lebanon; $400 for Tunisia, and $550 for the UAE. Kuwait has the highest per capita exports of manufactures in the region after Israel--mostly petrochemicals. Algeria and Egypt have very low per capita export figures; the former less than $20, the latter $30. Per capita exports of non-oil products to the world over 1989-93 have been falling for Egypt (minus 3.5 percent per year), Jordan (minus 5 percent), Syria and the UAE (rninus I and 0.5 percent, respectively). Exports to the EU declined for Algeria, Egypt, and Lebanon.

**Table 2: Non-Oil Exports to EU, 1989 and 1993 (ECU million)**

|**Country**|**Va**|**lue**|**Market**|**Share**|**Growth**<br>|
|---|---|---|---|---|---|
||**1989**|**1993**|________-<br>**1989**|**1993**|**Rate**|
|MENA|9,940|12,010|2.68|2.83|4.8|
|Jordan|86|268|0.02|0.06|32.9|
|Lebanon|100|66|0.03|0.02|-10.0|
|Syria|90|177|0.02|0.04|18.5|
|Israel|3,014|3,282|0.81|0.77|2.1|
|Egypt|790|790|0.21|0.19|0.0|
|Morocco|2,612|3,135|0.70|0.74|4.7|
|Tunisia|1,596|2,343|0.43|0.55|10.1|
|Algeria|219|151|0,06|0.04|-8.86|
|Saudi Arabia|890|1,057|0.24|0.25|4.4|
|Kuwait|131|149|0.04|0.04|3.3|
|U.A.E.|414|593|0.11|0.14|9.4|
|CEEC|10,336|19,145|2.79|4.51|16.7|

Source: EUROSTAT.

Total non-oil/gas exports by the CEECs to the EU rose by 16.7 per cent per year on average between 1989 and 1993, from ECU 10 billion in 1989 to 19 billion in 1993 (Table 2). In this period, 14
Fathoming Shipping Costs: An Exploration of Recent Literature, Data, and Patterns<sup>*</sup> Adina Ardelean<sup>†</sup> Volodymyr Lugovskyy<sup>‡</sup> Alexandre Skiba<sup>§</sup> David Terner<sup>¶</sup>

**Keywords:** Maritime Shipping, Freight Rate, Ports **JEL Classification:** L9, F1, R4

> *This paper was prepared as a background paper for the Global Transport Practice Flagship report _Shrinking Economic Distance,_ led by Matias Herrera Dappe. We thank Matias Herrera Dappe, Jan Hoffman, David Hummels, Ahmad Lashkaripour, Mathilde Lebrand, Alejandro Molnar, Aiga Stokenberga, and participants of the World Bank 2022 Workshop for the Transport Flagship Report _Shrinking Economic Distance_ for helpful comments.

> † Department of Economics, Santa Clara University; e-mail: atardelean@scu.edu

> ‡Department of Economics, Indiana University, Wylie Hall Rm 301, 100 S. Woodlawn, Bloomington, IN 47405-7104; e-mail: vlugovsk@indiana.edu

> §Department of Economics and Finance, University of Wyoming, Dept 3985, 1000 E University Ave, Laramie, WY 82071, e-mail: askiba@uwyo.edu

> ¶Department of Economics, Indiana University, Wylie Hall Rm 101, 100 S. Woodlawn, Bloomington, IN 47405-7104; e-mail: dmterner@iu.edu
whether women were more likely to work outside the home, in full-time occupations and in those with higher requirements for participation.

# **III. Ethiopia**

Ethiopia is one of the poorest countries in the world, although it has made progress in reducing poverty and achieving other Millennium Development Goals in recent years. It had an estimated GDP per capita of $400 in 2012 (IMF 2012). Ethiopia ranked 171 of 182 countries in the UNDP’s Human Development Index in 2009 (UNDP 2009) and 89 of 102 on its Social Institutions and Gender Index (SIGI 2009). Ethiopia is the second most populous country in SubSaharan Africa, and also among the most ethnically diverse. The country is a federal republic, with nine regions and two city councils.<sup>8</sup> Table 1 provides some information on differences across geographic areas in the country. While there are similarities between areas in recent rates of population growth, there are significant differences in urbanization rates as well as population density. Given the correlation between urbanization and education, there is also high geographic variation in education. In our analysis, it is important to capture the effects of these differences across geographic areas. We do so by including dummies for the various regions and chartered cities. We also repeat our results excluding the large cities to be sure they are not driving the results and the findings hold.

Ethiopia’s labor market is characterized by significant gender gaps in participation and in remuneration. Gender differences in the labor market are also present. In a 2004 survey report on urban employment, there is a significant gender difference in the employment-to-population ratio in the urban areas of all regions (CSA 2004). For women, the employment-to-population ratio is

> 8 In our analysis, we treat the two city councils (Addis Ababa and Dire Dawa) as their own geographic areas since they are administered separately from the other regions. As a result, we end up 11 geographic areas in our analysis.

12
# **6. Principal Issues with the Existing System**

The China’s fiscal transfer system is remarkable for transferring large sums of money in an objective manner to sub-national governments. This has enabled provincial-local government to deliver quantity and quality of public services better than most developing and emerging market economies. Yet the system has a number of obvious limitations.

1). _Complex and opaque system_ . The equalization system is overly complex and there are large number of transfer programs designed in an ad hoc manner as short term palliatives to deal with emerging issues/crisis but allowed to continue in perpetuity without any serious review. The system is opaque and hardly a handful of experts have knowledge of all programs and their underlying allocation basis.

> 2). _Piecemeal approach to gap filling_ .  The vertical fiscal gaps created by the existing assignments at provincial and sub-provincial levels are quite large (see Table 6) and a large number of transfer programs are implemented to deal with this gap. These programs gives the appearance of fiscal dentistry as multitude of programs such as the tax by tax sharing, tax rebates, transfer for increasing wage expenditure of public employees, the transfer for rural tax-for-fee reform, the transfer for abandoning agriculture tax etc, are designed to fill fiscal gaps (cavities) partially.

**Table 6  Vertical Fiscal Gap in China: 2003**

|_Governmental_|_Share_|_of_|_Share_|_of_|_Fiscal_|_Surplus_|
|---|---|---|---|---|---|---|
|_order_|_Revenues_||_Expenditures_||_(Gap)_||
|Central|71.0||30.1||40.9||
|Provincial|5.7||18.5||(12.8)||
|Subprovincial|23.3||51.4||(28.1)||
|All orders|100.0||100.0||0.0||

Source: Authors’ calculations based upon unpublished data from the Ministry of Finance, China.

29
# **Table 3b: Industry traits for unorganized services**

|||Male esta<br>cou|blishment<br>nts|Female est<br>cou|ablishment<br>nts|Female est<br>count|ablishment<br>share|Female es<br>share, em|tablishment<br>ployee wtd.|
|---|---|---|---|---|---|---|---|---|---|
|Indu|stry|2001|2006|2001|2006|2001|2006|2001|2006|
|55|Hotels and restaurants|1,787,571|1,710,376|203,699|175,414|0.10|0.09|0.09|0.08|
|60|Land transport (via pipelines)|4,232,335|3,845,576|19,170|26,722|0.00|0.01|0.01|0.01|
|63|Supporting transport activities, travel agencies|81,125|101,809|3,582|2,739|0.04|0.03|0.04|0.04|
|64|Post and telecommunications|488,737|1,657,523|84,340|166,487|0.15|0.09|0.15|0.09|
|70|Real estate activities|73,854|166,775|2,369|20,338|0.03|0.11|0.04|0.09|
|71|Renting of machinery, personal goods|479,824|434,540|13,039|11,796|0.03|0.03|0.02|0.02|
|72|Computer and related activities|13,865|37,075|2,220|1,731|0.14|0.04|0.12|0.06|
|74|Other business activities|542,091|569,636|28,597|23,541|0.05|0.04|0.05|0.04|
|80|Education|734,963|570,631|289,579|280,349|0.28|0.33|0.22|0.24|
|85|Health and social work|1,116,677|841,686|123,450|126,647|0.10|0.13|0.11|0.13|
|90|Sewage and refuse disposal, sanitation, etc.|5,529|27,264|37,609|20,374|0.87|0.43|0.76|0.39|
|91|Activities of membership organizations n.e.c.|43,534|323,938|1,107|1,287|0.02|0.00|0.02|0.01|
|92|Recreational, cultural and sporting activities|336,950|219,814|10,776|7,298|0.03|0.03|0.09|0.02|
|93|Other service activities|2,246,662|2,022,703|237,157|287,952|0.10|0.12|0.09|0.12|
||**Totals and weighted averages**|**12,183,718**|**12,529,347**|**1,056,693**|**1,152,673**|**0.08**|**0.08**|**0.09**|**0.09**|
||**Unweighted averages**|**870,266**|**894,953**|**75,478**|**82,334**|**0.14**|**0.11**|**0.13**|**0.10**|

Notes: Descriptive statistics taken from National Sample Statistics.
# DIAGRAM C1

MARGINAL REVENUE<sup>PRODUCT OF CAPITAL</sup> SAMPLE VALUES:<sup>ALL ENTERPRISES</sup> <!-- Start of picture text --> Cf0.0129<br>!~~~~~~~~~~~~~~~~~~~~~~~~~~<br>I 0.0099<br>~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~C.:C<br>1le 7X j<br>~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ I~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~I<br>~~~~~~~~~~~~~~~~~~~~~~~~~~~~0.0079<br>A* f O.D069<br>/<br>4<br>j<br>:.rr X / _ __- "- 0.0039<br>_o----8zH ~ ~ ~ ~ ~ ~- - O.Ot<br>- - ~~~~~~~~~~~~~~~~~~~~0.0019<br>100 200 300 400 500 600 700 800 900 1000 1100<br>ENTERPRISES ORDERED SY NAP Of CAPITAL<br><!-- End of picture text -->
on the 1990s of 0.0067, indicating that the change in capital-skill complementarity alone explains very little of the acceleration (1 - .0067/.0071 = 6 percent).

**Table 7: Estimated Wage-bill Share Equations -State  Manufacturing  1984-98 Pooled sample of three digit industries for 22 states.**

|**Dep. variable:**Change<br>in non-manual wage-bill<br>share|**1984-89**|**1990-98**||**Pool**|**ed 1984-89 /**|**1990-98**||
|---|---|---|---|---|---|---|---|
|1990s indicator|||**0.0073**<br>(.0010)|**0.0066**<br>(.0013)|**0.0038**<br>(.0014)|**0.0044**<br>(.0013)|**0.0043**<br>(.0015)|
|d Log capital/value<br>added|0.0024<br>(.0079)|**0.0343**<br>(.0067)||**0.0132**<br>(.0060)|0.0024<br>(.0079)|0.0018<br>(.0079)|0.0045<br>(.0072)|
|d Log capital/value<br>added x 1990s|||||**0.0320**<br>(.0104)|**0.0278**<br>(.0104)|**0.0250**<br>(.0101)|
|d Log value added|-0.0001|**0.0283**||0.0111|-0.0001|-0.0002|0.0044|
||(.0088)|(.0084)||(.0065)|(.0088)|(.0081)|(.0081)|
|d Log value added||||||||
|x 1990s|||||**0.0284**<br>(.0121)|**0.0219**<br>(.0104)|**0.0240**<br>(.0120)|
|Constant|**-0.0043**|-0.0005|**-0.0042**|**-0.0048**|**-0.0043**|**-0.0042**|**-0.0046**|
||(.0009)|(.0011)|(.0008)|(.0009)|(.0009)|(.0008)|(.0008)|
|State effects||||||X||
|Industry effects|||||||X|
|**R**<sup>**2**</sup>|0.001|0.10|0.14|0.15|0.17|0.21|0.24|
|**Observations**|453|495|948|948|948|948|948|

**Note:** Figures are annualized changes for 3-digit manufacturing (ISIC) industries in twenty one state groups. Heteroskedasticity-consistent standard errors are reported in parentheses. Coefficients significant at the 5% level are in bold face. Regressions estimated by weighted least squares with wage-bill shares averaged over the period as weights. See equation (4) in text.

Table 7 reports sharper estimates using the richer dataset available by using variation across both states and industries. The results are qualitatively the same as those in Table 6: capital-skill complementarity is much stronger in the 1990s after the reforms, the coefficient increasing by an order of magnitude, from 0.0024 to 0.0343. The two rightmost columns report 23
61

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-45-

# VI. Policies for Poverty Alleviation.

This section is concerned with the design of government programs to alleviate poverty. The objective is to construct a poverty program whose various components deal most effectively with the different dimensions of poverty. Since policy must be based on the behavioral characteristics of the target population, I begin in sub-section VI.A with a discussion of the needs and behavior of the extremely-poor and the moderately-poor. I next turn in sub-section VI.2 to discuss four considerations that affect the nature of government intervention in poverty alleviation. In sub-section VI.3 I pull together these two strands to identify the objectives of government intervention in poverty alleviation, and the various components of a poverty program. Sub-sections VI.4 and VI.5 discuss the specific components of the poverty program.

# VI.l Needs. Behavior. and Policy.

Policies to help the extremely-poor and the moderately-poor must take as departure point their characteristics; this allows to identify each group's needs and directs policies to the relevant margin. Seven characteristics of the extremely-poor merit attention.

One, the extremely-poor have higher fertility ratios and more children per household (Lipton (1983b), Birdsall and Griffin (1988); table 3 above)74. In these households children play the role of insurance policies for the future and, after age 5 or 6, additiona **l** abor force75. There is growing evidence that high fertility is a result of the characteristics associated 741 was unable to find any studies linking fertility to income levels in Mexico. The tabulations that I obtained from the 'Encuesta Nacional de Fecundidad y Salud' carried out by the Ministry of Health in 1987 only classify women into urban and rural groups. Global fertility ratios for urban (rural) women for the period 1981-86 were 3.6 (5.6), respectively. 75What is not clear is how out-migration changes this situation. If migrants send remittances, the initial investment by parents is recuperated while household size falls; else migration can reduce average incomes for extremely-poor households.