rafmacalaba/data-use-mentions-extended huggingface dataset:
successive primary deficits. The same holds true for the aggregate performance of states; figure 6 shows that the fiscal correction phase in states also coincides with a higher GDP growth rate and lower rate of interest paid on state debt. This was also in part the result of fiscal correction, which led to a reduction in government dis-savings and debt. This, however, masks the varied fiscal performance of individual states, which has been mixed over the period, causing concern in the context of the global crisis.

<!-- Start of picture text --> Figure 6: Differential between GDP growth rate and interest rate on state debt<br>25.0<br>Onset of deterioration<br>where g<r Period of correction<br>20.0 with g>r<br>15.0<br>10.0<br>5.0<br>0.0<br>Nominal GDP Growth (g) Average Interest on Debt (r )<br><!-- End of picture text --> Source: authors‘ calculation with base data from RBI

# **Section 5: Impact of the Global Financial Crisis and Going Forward**

Although, the immediate impact of the global financial crisis on state finances was somewhat subdued, there are implications going forward. The challenges will be more on the resource side through reduced central transfers, accentuated by the low-cost recovery by states. These may well render difficult the achievement of the Thirteenth FC road map. Going forward, sustainable finances require states to undertake reforms to maintain solvency via, among other things, increases in own taxes, implementing the goods and services tax (GST), and revising tariffs.

Assessing the impact of the crisis on the center, the immediate impact was relatively ―muted‖ (Milan 2011<sup>44</sup> ; RBI 2011). Although there was a setback in the growth of the economy,

> 44 Milan et al. (
access in IPC 4 regions demonstrated above.

And third, as discussed above, the time following the 2017 IPC announcement was a very turbulent time in Yemen that affected all households (see Figure 1). The strong conflict-related shocks in the rest of 2017 and the beginning of 2018 might have had much stronger adverse impacts on access to food had there not been an increase in the share receiving food assistance following the 2017 IPC announcement, and this allowed households only to maintain food access. Additionally, it is possible that these shocks could have impacted IPC 4 regions more than the rest of the country given potentially more vulnerable households, and this impact could further have neutralized whatever additional increase in assistance was targeted to those regions.

Although all three of the above explanations could each contribute to the lack of a stronger and more immediate impact on food access, we are able to find additional empirical support for the last explanation. Given data and information constraints, it is not possible to estimate the impact of all the conflict-related shocks that affected the country. However, Tandon and Vishwanath (2020) were able to demonstrate that the complete air and sea blockade in November 2017 harmed food access and access to basic services using the individual-level data from the mVAM survey that month.<sup>39</sup> Using that same individual data from the November 2017 mVAM, we are able to demonstrate that the blockade did have stronger adverse consequences on IPC 4 regions than the rest of the country. Specifically, we estimate:

# (2)

_ln_ ( _Food_ _~~A~~ ccesshrd_ ) = _ρr_ + _β_ 1 _IPC_ 4 _r_ + _β_ 2 _Post_ _~~B~~ lockadehrd_ + _β_ 3 _Post_ _~~B~~ lockadehrd∗IPC_ ~~4~~ _r_ + _εhrd_ where _Food_ _~~A~~ ccess_ denotes either the household FCS or rCSI; _Post_ _~~B~~ lockade_ is an indicator equaling one if the household was interviewed after November 6th, which is the
|0.219|0.327|0.396|

_Source_ : Authors’ calculations based on data from the Socioeconomic Database for Latin America and the Caribbean, World Bank and Center for Distributive, Labor and Social Studies of the Universidad Nacional de La Plata (CEDLAS) (http://sedlac.econo.unlp.edu.ar/eng).

_Note:_ Each column reports regression results of the effect of the listed variable on log wages. Individual characteristics include the interactions of worker’s gender, five education categories (primary completed or less, high school dropouts, high school graduates, college dropouts, and college graduates or more), and fiveyear intervals of experience. Supplementary online appendix S1.1 provides a list of the sectors and occupations. Countries included coincide with those in figure 7 with the exception of Chile and Paraguay, where harmonized information on occupations is not available, and therefore, results for column 3 cannot be computed. Results in columns 1 and 2 are qualitatively similar when including these countries and available from the authors upon request. Country weights are used, but they were re-scaled so that each country has the same weight in the regression. Robust standard errors in parenthesis: ***p _<_ 0.01, **p _<_ 0.05, *p _<_ 0.1.

these penalties, but they remain high, at -.339 (-.434) log points for informal employees (selfemployed).<sup>20</sup> The interaction terms in the regression suggest that these gaps declined between 2002 and 2015, possibly contributing to the decline in inequality. According to column 3, the informal (self-employed) wage gap declined by approximately 11 (12) log points. Amarante and Arim (2015) study wage structure effects associated with changes in formality status across the distribution of wages in five Latin American countries during the 2000s in a sample that concentrates on wage employees (excluding the self-employed
4.8||0.2|
|Air Afrique|32.0|||
|Ghana Airways Corp.|14.8|15.0||
|Cameroon Airlines|1.4|5.4||
|_Market concentration measures_||||
|Concentration top 3|54.1|41.4|44.1|
|Herfindahl index|13.8|10.0|9.9|

with air traffic control and weather information. Further regional cooperation could help to improve oversight and safety, through the pooling of scarce human resources and greater regulatory independence. About half of the ECOWAS member countries already belong to the Agence pour la Sécurité de la Navigation Aérienne en Afrique et à Madagascar (ASECNA), which, with support from France, provides some measure of air traffic safety. There is scope to broaden and deepen such collaborative arrangements.

The aging of the West African aircraft fleet is another aspect of the safety issue. In contrast to elsewhere in Africa, the West African fleet has aged significantly between 2001 and 2007. Across Africa, there has been substantial investment in new aircraft, leading to an overall renewal. This is not observed in West Africa, where the percentage of the fleet that is classified as ―western old‖ has increased from 36 to 43 percent between 2001 and 2007 (figure 2.13).

In the ECOWAS region, as well as throughout Africa, the need for new airports is not as great as the need for maintenance and additional capacity at existing facilities. In the case of Dakar, for example, calls for a new airport miss the point that a parallel taxiway could alleviate many of the runway constraints. In addition, a more efficient regional system could be envisioned if Lagos, for example, were turned into a regional hub, with turbo-prop flights into neighboring countries. Any such plans would most likely have to include substantial investment in terminal capacity.

40
In some of my specifications, to control for _Zis_ , I include the wage bill for each sector and location with a census-tract fixed effect to capture _qi_ . Then, I estimate the following equation using the Economic Censuses in 1999, the omitted category is the formal sector, where _γi_ is the census-tract fixed effect, _γI_ is an informal sector dummy variable, and _γ_ is a constant term. From the optimal number of firms, we have that _γI_ = ln( _σI FI_ ), and _γ_ = ln _β_<sup> ̃</sup> + ln( _σF FF_ ).

Table C8 reports the results for this estimation for different specifications. I run the previous equation, including state and municipality fixed effects, and in the even columns, I control for the wage bill. I obtained that on average, the value of _β ≈_ 0 _._ 7. I also find that the entry fixed cost for a firm into the informal sector is approximately 0.15, and into the formal sector is 1.1. This means that the fixed cost to enter into the formal sector is more than five times the one to enter into the informal sector. This result is consistent with the fact that the average size in terms of workers of informal firms is lower, but that there are more informal firms in the economy.

# **C.3 Algorithm**

In this section, I explain the main algorithm to solve for the general equilibrium model. The system of equations is described in section 4. The sub-index _t_ represents simulation. The algorithm is based on Alvarez and Lucas (2007) and it is a contraction mapping. It is as follows:

1. Guess an initial vector of wages _⃗w_<sup>0</sup> , and number of residents in each location _⃗L_<sup>0</sup> .

2. Given a vector _⃗w_<sup>_t_</sup> and _⃗L_<sup
<!-- Start of picture text --> Number of Destinations per Exporter - GDPpc Entry Rate - GDPpc<br>MWI LAO YEM<br>BEL TZA<br>UGA CMR IRN<br>KHM<br>SWE BFAMLI DOM EST<br>MWI NERUGATZABFABGDMLI KENLAOPAKSENNICYEMCMR EGY MARGTMJORSLVECUALBPERIRNMKDBGRDOMCOLZAFCRIMUSLBNTURMEXCHL ESTPRT NZLESPKWT NOR BGDKHMKENPAKSENNIC MARGTMJORSLVECUALBPERMKDBGRCOLZAFCRIMUSBWA TURMEXCHL PRT NZLESP BELSWE NOR<br>BWA EGY<br>R2=0.37 BRA R2=-0.44<br>6 7 8 9 10 11 6 7 8 9 10 11<br>Ln GDPpc Ln GDPpc<br>Exit Rate - GDPpc Survival Rate - GDPpc<br>MWI BGD<br>KHM PAK<br>YEM BRATUR<br>IRN EGY<br>LAO JOR ZAFCRI<br>UGATZABFAMLI KENLAO SENNICCMR MAR ECUALBPERMKDBGRDOM BWA MEXCHL EST ESP NOR BFAMLI KEN SENNIC MARGTMSLVECUALBPERIRNMKDDOMCOLMUSBWA MEXCHL PRT NZL BEL<br>KHM PAK EGY GTMJORSLV COLZAFCRIMUS TUR PRT NZL BELSWE MWI UGATZA EST ESP<br>BGD BRA R2=-0.36 CMR R2=-0.02<br>6 7 8 9 10 11 6 7 8 9 10 11<br>Ln GDPpc Ln GDPpc<br>2<br>.5<br>1.5<br>.4<br>1<br>Entry Rate<br>.3<br>.5<br>Ln Number of Destinations per Exporter<br>0 .2<br>.6 .6<br>.5 .5<br>.4 .4<br>Exit Rate<br>Survival Rate<br>.3 .3<br>.2 .2<br><!-- End of picture text --> Notes: The measures plotted are based on measures in the country-year level dataset (file CY.dta) averaged across the 2006-2008 period for each country for each country except Kuwait for which data is for 2009 and Portugal for which averages are across the
of Iacovone and Javorcik (2010) who showed the importance of churning at the firm level in response to exogenous opportunities provided by increased globalization. Alvarez and L ́opez (2008) used Tobit regressions to study the determinants of industry-level rates of entry and exit into exporting using a 10-year panel of 5’000 Chilean plants. They found that within-industry heterogeneity, measured (inter alia) by the dispersion of firm-level productivity levels, played an important role in explaining firm turnover in and out of exporting. By contrast, trade costs, factor intensities, and exchangerate fluctuations were found to have only marginal impacts. Carballo and Volpe (2008) used a 6-year panel of firm-level Peruvian exports at the HS10 level to explore how diversification strategies (in terms of products and markets) affected the survival of firm-level exporting activity. They found that both geographical and product-wise diversification raised survival, but geographical diversification more so—presumably because it proxies for product quality.

# **3 Data**

## **3.1 Qualitative evidence from a World Bank survey**

Preliminary indications on how African exporters venture and survive (or not) on foreign markets can be gleaned from a 2009 survey focusing on export survival conducted by the World Bank in four African countries.<sup>3</sup> The survey, which had three sections (basic information on the firm, constraints on survival, and opportunities and plans for future expansion), asked exporters specific questions on their initial entry into and survival on export markets. On the basis of the information provided, respondents were classified into three categories: (i) current exporters, (ii) past exporters (who failed), and (iii) intermittent exporters.

As shown by Table 7 in the appendix, roughly two thirds of the respondents (a bit more among regular exporters) identified their first client through relatives, friends, intermediaries and suppliers. More formal or technologyrelated channels (e.g. trade fairs or online research) came only second, and
10.6|6.6|
|Japan|1.5|4.8|8.2|11.1|12.3|-1.3|12.4|2.4|9.8|
|United States|4.3|9.9|13.1|12.8|10.4|3.7|9.1|5.4|5.4|
|Total: above<br>Industrial Co.|3.3|8.1|11.8|11.3|12.7|1.6|9.7|5.8|6.9|

Note: Data is based on two-year averages of 1991-92, 2001-02, and 2007-08.

Source: Computations based on UN COMTRADE Statistics (trade data) and UNIDO database (production data).

Table 4 shows the shares of imports from developing countries in the total gross absorption (demand) of the five industrial countries, growth rate of these imports, and the decomposition of the import growth between demand and market share changes. Import growth rates from developing counties (about 11 and 13 percent p.a.) are much higher than their import growth rates from the rest of the world shown in Table 2. Import growth rates from developing countries are almost identical for the two periods while world trade growth has doubled during this time. Especially during the first period when the demand increases in industrial countries amounted to only 1.6 percent per annum, imports from developing countries increased by more than 11 percent p.a. Most of the import growth was caused by market share changes rather than demand increases. During the second period, despite higher demand growth, market share changes are still greater than demand changes. For this group of industrial countries, market share changes explain the bulk of the growth of imports from developing countries.<sup>11</sup> Of course, market penetration of almost 10
Policy Research Working Paper 9706

# **Abstract**

Prices for several intermediate inputs, including cement, are higher in developing economies—particularly in Africa. Combining data from the International Comparison Program with a global directory of cement plants we estimate an industry equilibrium model to distinguish between drivers of international price dispersion: demand, costs, conduct, and entry. Developing economies feature both higher marginal costs and higher markups. African markets are not characterized by higher barriers to entry and, if anything, feature relatively more competitive conduct. The small size of many national markets, however, limits entry and competition and explains most of the higher markups. Policy implications are discussed.

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 treed@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
easy entry and exit allow poorly performing firms to leave the market and dynamic new ones to enter.

Exit of un-restructured enterprises has proven key for putting the assets, including the real estate, of loss-makers back to productive use. It has been especially helpful to the important SME sector, where entrepreneurs are in particular need of the land and storefronts, as well as other assets, so often controlled by non-productive large firms. Exit in the sense of stopping production activity (plant closures) is not enough. What is also needed is the reallocation of the assets that are freed up, and this is what a good bankruptcy framework facilitates. Although the capacity utilization rate depends on many factors, including business sector, market conditions or business cycle, the high rates of excess capacity reported by the PICS data – 30-40percent - indicate that the exit mechanism is not working. Persistent and large scale excess capacity indicates that there are plants with obsolete machinery that is unlikely ever to be used again on a large scale, and many of these plants are occupying buildings and land and located next to infrastructure (electricity, water and sewage connections) that can be better used in other productive activities.

Access to land is another pre-requisite for the movement of factors of production across enterprises, a source of productivity growth. Lack of clear title and uncertain ownership claims remain a major constrains to the investment climate in Serbia. There is a need to 16
**Figure 3:** Sovereign bond yields during Zambia’s hidden debt saga

<!-- Start of picture text --> 10,000<br>Protracted default, data reconciliation<br>9,000 and<br>restructuring process<br>Creditors reject<br>8,000<br>restructuring over<br>transparency concerns<br>7,000<br>Zambia asks banks<br>6,000<br>for restructuring<br>advice on $11.2bn<br>5,000 of external debt<br>4,000<br>First rumors<br>about hidden debt<br>3,000<br>emerge<br>2,000<br>1,000<br>0<br>Jan 2018May 2018Aug 2018Dec 2018Apr 2019Aug 2019Dec 2019Apr 2020Aug 2020Dec 2020Apr 2021Aug 2021Dec 2021Apr 2022Aug 2022Dec 2022Apr 2023Aug 2023Dec 2023Mar 2024<br>(in basis points)<br>Sovereign bond yield spread<br><!-- End of picture text --> _Sources:_ Financial Times (2020, April 1) _“Zambia’s bonds drop on expected restructuring”_ , Financial Times (2020, September 30) _“Bondholders balk at Zambia’s plan to delay debt payments”_ , Financial Times (2021, November 10) _“Zambia’s new president tackles debt mountain and empty treasury”_ and J.P. Morgan (2024). _Notes:_ The figure plots the EMBI+ spread for Zambia from January 2018 until April 2024.

Statistics (IDS) and its predecessor publications. This subsection explains why we focus on the World Bank debt statistics and how we compile our new database.

**Why focus on the World Bank IDS?** The World Bank’s International Debt Statistics is uniquely suited for the purpose of our measurement approach. First, it is the most widely used source for developing and emerging market country
Policy Research Working Paper 7672

# **Abstract**

Inadequacies in Tanzania’s education and training systems compromise the quality of workforce skills, giving rise to skill shortages, and constraining the operations and growth of formal sector firms in the country. This study addressed these concerns using data from a unique Enterprise Skills Survey that asked Tanzanian employers about the education, training, and occupational mix of their workforce, the skill gaps in cognitive, noncognitive, and job-specific competencies affecting their operations, and the strategies they are using to overcome these skill gaps. The study investigates the consequences for firm productivity of employers’ choices about their optimal skills mix, and their strategies to mitigate shortfalls in skills supply. Compared with noninnovators and firms primarily serving the domestic market, exporters and innovators face greater skill demand and suffer from skill shortages that are more likely to constrain their operations in such areas as quality assurance, use of new technology, and introducing new products and services. In analyzing firm performance and its relation to skill mix, the study found that firms with higher shares of tertiary-educated workers are more productive; it found no impact, however, from secondary education and technical vocational education and training qualifications, possibly reflecting the universally acknowledged poor quality of secondary education in Tanzania. Employers use a range of strategies to address skill deficiencies, from hiring new workers, to training current workers in-house or externally, using high-skill expatriate workers, or outsourcing professional services. Almost all were associated with higher labor productivity. The exception, employer provided inhouse training, had no measurable impact on productivity.

This paper is a product of the Education Global Practice Group. 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://econ.worldbank.org. The authors may be contacted at sbashir@ worldbank.org and ntanaka1@worldbank.org.

_The Policy Research Working Paper Series
12 to put a premium on the old age security motive for children?, and (3) how much of the need for old age support is financial and how much is emotional and thus the desire to live with children in old age may not be a financial motive? Each of these questions are important for designing policy. Some survey data can provide insight into these factors, but relatively little work has been done.

The most thorough examination of the motives for child bearing in developing countries is the Value of Children Study. Table 7 summarizes some data from that study and Figure 3 traces through the salience of various motives for childbearing at different levels of fertility. This data seem to indicate that husbands and wives express the same relative importance to the need for children for old age support and this declines in about the same way as national fertility declines. Another interesting finding of this study is shown in Table 7. In those countt-xes where there is not a strong preference for sons (the Philippines and Thailand), the extent to which people expect old age support from sons and daughters are about equal. In countries such as Korea and Taiwan where sons are valued much more than daughters, there is a wide difference between the extent to which husbands and wives rely on sons rather than daughters for old age support. These data are extremely valuable, but cannot address the issue of causation.

There are several interesting questions that need to be addressed with such data:(1) what are the determinants of such attitudes towards the utility of children?, (2) whether the desire for old-age support affects family size preferences?, and (3) whether the desire for old age support affects behavior?
***|**-0.348*****|**-0.761*****|
|Seychelles||||||||
|South Africa|0.445***|0.574***|0.597***|0.321***|0.633***|0.656***|-0.064|
|Swaziland||||||||
|Tanzania|0.097**|0.217***|**-0.157****|0.223***|0.019|-0.015|0.234***|
|Zambia<br>Zimbabwe|**-0.093****|0.077|**-0.158****|-0.114|-0.171**|-0.037|-0.124|
|N|161|161|161|161|161|161|161|
|R<sup>2</sup>|0.825|0.774|0.848|0.615|0.796|0.741|0.68|
|DSADC|-0.017|0.04|-0.045|0.067|0.023|-0.005|-0.196**|

**Notes:** The Logistics Performance Indicator data are obtained from Logistics performance survey data (2009). * p<.1; ** p<.05; *** p<.001

25