rafmacalaba/data-use-mentions-extended huggingface dataset:
.2%|80.8%<br>91.6%|
|Employees,agriculture(% of employment)|44.3%<br>43.8%|68.1%|41.8%|39.2%|31.6%|74.8%<br>83.2%|

Sources: World Development Indicators, UNDP, OECD, CIA Fact Book Years: Indonesia 2005 (2004 when not available), Bangladesh 2007 (2005 when not available), Sri Lanka 2003 (2002 when not available), Ethiopia 2006 (2005 or closest year when not available) a The SIGI was measured in 102 countries in 2009. It includes 12 indicators on social institutions, which are grouped into 5 categories: Family Code, Physical Integrity, Son Preference, Civil Liberties and Ownership Rights (0=low/no discrimination, 1=high discrimination).

b The Gender Inequality Index was measured in 138 countries in 2010. The index incorporates the following indicators: Labor force participation, educational attainment, parliamentary representation, adolescent fertility and maternal mortality (higher values indicate lower achievement).

51
levied on imports originating in Mercosur countries (Brazil, Paraguay, and Uruguay). Our source for this exercise is the Commercial Liberalization Program included in the Asunción Pact (1991). This program established a progressive, automatic and linear reduction in the tariffs assigned to imports from the Mercosur countries.

First, we computed the share of the imports from the Mercosur in the year 1990, prior to the signing of the agreement. Next, we adjusted the original import tariffs considering the estimated ratio and the scales of tariff reduction established by the Asunción pact: Import Tariffit = Intrazone Tariffit ∗ Ratio + Original Import Tariffit ∗ (1—Ratio), where i is a 3-digit ISIC code and t is a year.

In order to provide some external consistency check on our tariff series, we compared our data with some of the indicators provided by Berlinski (1994) and Berlinski (2003). These are some of the most comprehensive accounts of the history of trade policies in Argentina. Overall, the numbers on tariff protection reported by Berlinski are quite similar to our numbers. For example, he reports that the average tariff before the liberalization of the 1970s was 99 percent (our estimate is around 100 percent). For the 1990s, Berlinski’s estimates of the average tariff fluctuate around 16-19 percent, and our averages are around 18 percent. During the 1980s, he reports estimates for 1988, before the reform of the late 1980s and early 1990s, of 48 percent. We instead find that the average tariff is close to 30 percent. Even though there are differences in methodologies, mostly in aggregating the average tariffs, it is clear that our estimates are pretty consistent with those in Berlinski. It is important to remark that while Berlinski built tariff measures for selected years, in this paper we need a full time series of historical trade data. The series produced here are, we believe, an important contribution of our work.

# The Permanent Household Surveys

Data on wages and worker characteristics come from the Encuesta Permanente
health progress in Sweden throughout the 19<sup>th</sup> century, however, its cyclicality is completely reversed in the second half of the 20<sup>th</sup> century, when economic growth negatively affects health progress. Studies applying Ruhm’s (2000) framework also established pro-cyclical relationships between mortality and unemployment in other countries (for example, Gerdtham & Ruhm (2006) for OECD countries, Lin (2009) for Pacific-Asian countries, Gonzalez and Quast (2011) for Mexico, Ariizumi and Shirle (2012) for Canada).

On the other hand, some studies found no impacts of unemployment on health. Schmitz (2011) used the German Socio-Economic panel of 1991-2008 and relied on fixed-effects methods and plant closures to establish causality. The author found no negative effect of unemployment due to exogenous unemployment. Similarly, Salm (2009) used business closure to control for reverse causality, and found no causal effect of job loss on various measures of physical and mental health.

Others have found some components of health to deteriorate during economic downturns. Ettner (1997) discovered that non-employment increased alcohol consumption and dependence symptoms. Sullivan and von Wachter (2009) established that individuals who experience a job loss via a mass-layoff experience a substantial increase in their mortality hazard that persists for 20 years. Ruhm (2015a) also found that deaths due to poisoning are counter-cyclical.

While the literature has mostly focused on a time-series relationship between unemployment and mortality, our identification strategy allows us to explore the cross-section relationship between unemployment and mortality across U.S. counties. With this approach, we can analyze the impact of unemployment on health during the Great Recession- a topic of great interest.

Finally, our paper is also related to the literature that utilizes the Bartik instrument. The instrument was first developed by Bartik (1991) to isolate exogenous shifts in labor demand in a local community. Therefore, the instrument is sometimes referred to as Bartik instrument. The 6
g. whether formal procedures are implemented, workers fulfill their responsibilities, or stakeholders have substantive input into decision processes).

Measures of governance performance in public health care provision can be gathered through facility and population surveys. Facility surveys can directly measure certain aspects of governance performance, such as the share of workers who are absent without legitimate excuses. While population surveys are less direct, they can still elicit information about the performance of health facilities in terms of absenteeism or informal payments. The existing literature contains a manageable number of governance performance measures for public health care provision that could form the basis for a ______________________________________________________________________________________

-35-
(Ranson et al. 2002). However, analyses of cost-effectiveness tend to focus on the perspective of the public sector provider or financing entity and leave aside the costs borne by individual households.

A recurrent policy concern is the potentially regressive effects of tobacco taxes. Lower-income households usually allocate larger shares of their budgets to purchasing tobacco products. Hence, relative to wealthier households, low-income households face larger negative shocks to budgets when taxes translate into higher tobacco prices. However, this presents only a partial picture of the more complex effects of raising taxes on tobacco. Several benefits of tobacco taxes arise via improvements in people’s medical condition and productivity. Such gains may contribute to offsetting the direct negative price shock. The net impact on household welfare of raising taxes on tobacco involves the aggregation of these costs and benefits. Furthermore, it is mediated by the degree of pass-through of the tax burden to consumer prices, the responsiveness of consumers to the price shock, and the initial distribution of tobacco consumption across population groups. The medium- and long-term effects will likely differ from the immediate short-term outcomes if the benefits and behavioral responses take time to kick in.

While the net effect remains an empirical question, a growing body of research within countries supports the conclusion that the benefits of raising taxes on tobacco offset the costs. Denisova and Kuznetsova (2014) and Verguet et al. (2015) find that, across the population and, specifically, among low-income groups, the future benefits of nonsmoking outweigh the losses attributed to tobacco taxes. Other country-specific studies based on household microdata find that the distributional incidence of raising taxes on tobacco can be progressive, most often because of the benefits derived from averted medical expenses (Fuchs and Del Carmen 2018; Fuchs, Del Carmen, and Genoni 2018; Fuchs, Del Carmen, and Mukong 2018; Fuchs, and Matytsin 2018; Fuchs and Meneses 2017a, 2017b, 2018; Fuchs, Orlic, and Cancho 2019).

# **d. The price elasticity of tobacco consumption*
ZAMBIA’S INFRASTRUCTURE: A CONTINENTAL PERSPECTIVE Tanzania now has one of the most vibrant domestic air transport markets in Africa, offering competing services on all routes.

**Table 4. Air transport**

|Country|Angola|Zambia|Tanzania|Botswana|Namibia|Zimbabwe|Mozam-<br>bique|
|---|---|---|---|---|---|---|---|
|TRAFFIC (2007)||||||||
|Domestic seats<br>(millions per year)|1.20|0.44|1.87|0.24|0.08|0.24|1.14|
|Seats for international travel within Africa<br>(millions per year)|0.48|1.46|1.27|—|—|1.11|0.58|
|Seats for intercontinental travel (millions<br>per year)|0.59|0.11|0.59|—|0.24|0.18|0.09|
|Seats available per capita|0.13|0.17|0.9|—|—|0.11|0.09|
|QUALITY||||||||
|% of seat-km in older aircraft|0.1|19.8|17.1|0|1.1|15.5|16.3|
|% of seat-km in newer aircraft|59.6|63.8|79.3|100|79|71.4|57.0|
|% of seat-km in aircraft of unknown age|40.2|16.4|3.6|0|19.9|13.0|26.7|

_Source:_ Bofinger, 2009. Derived from AICD air transport database downloadable from
ted**|**S**|**patially **|**defate**|**d**|
|**Poverty status:**||Non-|poor|Po|or|Non-|poor|Po|or|
|**DB:**||Urban|Rural|Urban|Rural|Urban|Rural|Urban|Rural|
|**DOU:**||||||||||
|Non-poor|Urban|90.9|2.6|0.0|6.5|93.1|6.6|0.3|0.0|
||Rural|29.4|27.9|0.0|42.7|56.0|41.4|2.0|0.6|
|Poor|Urban|0.0|0.0|96.6|3.4|6.9|0.3|90.1|2.8|
||Rural|0.0|0.0|43.9|56.1|1.1|2.2|58.3|38.5|

Source: International Urban Poverty Database. Note: WorldPop 250m is used for the DOU and DB methods. Poverty is measured using the $2.15 poverty line. 18 countries are included. Bangladesh is an outlier and is not included. In Panel (A), welfare is deflated using official spatial deflators. In Panel (B) and (C), welfare is deflated using our updated spatial deflators.

87
systematically between the treated and non-treated sectors with respect to tax incentives. Nonetheless, we measure access to electricity, road and railway station at the town and village-level using data from the India Census 2011 and introduce these variables as additional controls in Equ.(3) to check the robustness of our estimates. The results regarding total employment are reported in the top panel of table 10. Both _Target_ and the interaction term _Target X Treat_ remain positively associated with employment. And the magnitudes of the estimates are comparable to those reported in table 9.

**Table 10. Within-sector effects with heterogeneous central excise tax incentives, robustness checks**

**<u>(2013, town-sector level)</u>**

||Log (e<br>|mployment),<br>|controllingf<br>|or access to i<br>|nfrastructure<br>|<br>||
|---|---|---|---|---|---|---|---|
||(1)<br>40 kms|(2)<br>50 kms|(3)<br>60 kms|(4)<br>70 kms|(5)<br>80 kms|(6)<br>90 kms|(7)<br>100 kms|
|_Target_|0.2191***<br>(5.31)|0.1556***<br>(4.23)|0.2215***<br>(6.33)|0.1630***<br>(5.16)|0.1519***<br>(5.16)|0.1844***<br>(6.63)|0.2061***<br>(7.76)|
|
diverse altitudes, all of these characteristics make it suitable for important temperature fluctuations, which might be related to our study. From an analysis of average monthly temperatures for Ethiopia (blue) and Addis Ababa (red) between 2005 and 2013, as shown in Figure 11, we observe that while there is some substantial cyclical variation in temperature, there does not seem to be an exceptional increase in either the level or the volatility of temperatures over the period of the policy change.

In addition to this, natural disasters might lead to a change in the marginal value of public/private infrastructure and affect financial markets. The year of the policy change, 2011, was indeed marked 32
- Osorio, Lyda, Jim Todd, and David J Bradley (2004). Travel histories as risk factors in the analysis of urban malaria in Colombia. The American journal of tropical medicine and hygiene 71.4, pp. 380386.

- Oster, Emily (2012). Routes of Infection: Exports and HIV Incidence in Sub-Saharan Africa. Journal of the European Economic Association 10.5, pp. 10251058.

- PNLP, INFORM, LSHTM (2015). Senegal: A Prole of Malaria Control and Epidemiology.

- Prothero, R Mansell (1977). Disease and mobility: a neglected factor in epidemiology. International Journal of Epidemiology 6.3, pp. 259267.

- Ross, Ronald (1910). The prevention of malaria. Dutton. Ruktanonchai, Nick W et al. (2016). Identifying malaria transmission foci for elimination using human mobility data. PLoS Comput Biol 12.4, e1004846.

- Russell, Paul F and Domingo Santiago (1934). Flight range of the funestus-minimus subgroup of anopheles in the Philippines. The American Journal of Tropical Medicine 14.2.

- Senegal Ministry of Health (2016). M-Diabete: Le Mobile au Service de la Lutte contre le Diabete. url: http://www.mdiabete.sante.gouv.sn/.

- Siri, Jose G et al. (2010). Signicance of travel to rural areas as a risk factor for malarial anemia in an urban setting. The American journal of tropical medicine and hygiene 82.3, pp. 391397.

- Smith, David L, Chris J Drakeley, et al. (2010). A quantitative analysis of transmission eciency versus intensity for malaria. Nature communications 1, p. 108.

- Smith, David L and F Ellis McKenzie (2004). Statics and dynamics of malaria infection in Anopheles mosquitoes. Malaria Journal
Luxembourg, Austria, France, Denmark, Sweden and the Netherlands, the largest effect is observed in the fourth quintile.

_Figure 5: Composition of automatic stabilizers_ <!-- Start of picture text --> LU DK SE EE CZ BG RO NL FI BE LT ES LV CY PT PL SI HR FR HU DE SK EL MT AT IT IE<br>Unemployment Social assistance Other Taxes SIC<br>6<br>4<br>2<br>0<br>-2<br><!-- End of picture text --> Note: See Figure 5 in the Appendix for results by income groups. Other benefits include housing benefits, family and education benefits, health benefits as well as old-age and survivor benefits. Source: Own calculations based on EUROMOD I4.0+.

Finally, Figure 4 shows that additional COVID-19-emergency reforms to taxes and benefits (red bars in Figure 4) play only a small role in most countries. The effect of additional policies is particularly important in Ireland, accounting for a 4 percent increase in household income. COVID-19-emergency policies also play a role in Austria (1.6 percent), Czechia (1.6 percent) and Italy (1 percent), whereas they contribute by less than 0.6 percent in all other countries. In general, their effect is concentrated in the lower part of the distribution (Figure A4 in the Appendix).

# **Decomposition results for the most affected by the crisis**

Figure 6 shows the same decomposition but zooms in on those severely affected by market income shocks, leading to quite pronounced decompositional differences compared to the total population (shown in Figure 4).

By definition, the role of market income changes is more pronounced for those more severely hit by the pandemic. However, there are notable differences between the overall population and those severely affected. While Scandinavian countries as well as Bulgaria show comparably low drops in market incomes overall, the role of market incomes is significantly
The attenuation of clientelist ties caused by urban land titling reduced local incumbents’ vote share in Mexico (Larreguy _et al._ 2018).<sup>20</sup> While further study is warranted, economic and political considerations thus seem to favor a focus on regulatory and institutional reform which would benefit all land owners rather than just a narrow set of the population; demonstrably enhance activity in land and financial markets; and be sustainable rather than short-lived.

# **5. Conclusion**

Although land titling programs are often seen as a way to improve land and financial market functioning and thus to contribute to urban structural transformation, we know of no study that would document credit market impacts of urban land titling. Employing administrative rather than household survey data to identify impacts of titling and regulatory as well as institutional reforms separately suggests that policy reform, but

> 18 See the 2020 ‘Doing Business’ figures at https://www.doingbusiness.org/en/data/exploretopics/registering-property. 19 Despite the associated productivity losses, rural reforms awarded insecure and often non-transferable rights in cases such as Zimbabwe (Deininger _et al._ 2004), Kenya (Hassan and Klaus 2020), Colombia (Albertus 2019), Peru (Albertus and Popescu 2020), Mexico (Albertus _et al._ 2016), and the Philippines (Adamopoulos and Restuccia 2020). Clientelist relationships were often reinforced by establishing vast bureaucracies dedicated to provide services to beneficiaries.

> 20 Fear of similarly negative consequences may explain why, rather than focus on urban areas with high land values and potential impacts, titling efforts supported by donors and IFIs were mostly directed to rural aeras with more limited potential and scope for sustained impact.

19
and in some cases strongly).

Demographic pressures in many ECA countries stem from low labor force participation, especially among those living in rural and underserved areas. Precarious employment and low-quality jobs contributed to a high incidence of undeclared work in some ECA economies, including those in Central Europe where informality tends to be lower than in other parts of the region (El-Ganainy et al. 2021; Ohnsorge and Yu 2021). Employment opportunities for women, especially migrants, were more limited than those for men with similar levels of tertiary education (Frattini and Solmone 2022). This was most evident in Romania. As a result of these challenges, labor activity rates in many ECA countries have remained below those of EU peers. Because of these trends, the average contribution of labor force growth to potential output growth in ECA remained modest though stable between 2000-10 and 2011-21.

The accumulation of human and physical capital lost momentum in the last decade— weighing on potential TFP growth. Gains in both life expectancy and educational achievement leveled off, with educational reform losing momentum after the large strides of the early 2000s (Patrinos 2022). Although school enrollment rates in ECA have been high for decades and the average number of years of education is the highest among EMDE regions for both males and females, quality-adjusted years of education and PISA scores trail the EU average in many cases, with some backsliding even in the decade prior to the pandemic (figure 8.E; World Bank 2020d). The levels of basic skills in reading, mathematics, and science, as measured by PISA scores, fell between 2006 and 2018,
before, during and after the CIV civil war. To guard against possible serial correlation, we follow the suggestion of Bertrand et al.

> 14Total number of departments/communes in Burkina Faso is 374 and Mali 695. Some of the subdistricts lack data on building density and are dropped from the analysis presented here. When we repeat the analysis of employment shares without dropping those extra sub-districts and all results reported here are robust to the inclusion of those sub-districts. Using high resolution data that became available since the data construction of the Burkina Faso department boundaries, we slightly modified the urban boundaries to align with the expected location of urban areas using ancillary and satellite imagery keeping the same shape and resolution of the original data.

> 15The night-light data are collected from a series of DMSP-OLS satellites during the period 1992-2013. In order to enable temporal analysis, we correct for the lack of in-flight calibration using the method in Wu et al. (2013) to adjust for the differences between sensors, acquisition times, and saturation. A newer satellite VIIRS started in 2013. The data from the earlier satellite (DMSP) may not be comparable to that from the new satellite.

17
Anthropometry of older children or of adults, may give more information about the adequacy of food/nutrient supply and could for, an optional module. Dugdale (1985) has suggested that measurements made on all members of households may be particularly useful in helping to differentiate food deficit situations from those in which poor health status is determined by exposure to disease.

Depending upon the general design, a WHS could contribute valuable information about the significance of anthropometric indicators in relation to other health indicators. In particular, there is a need for more information about the influence of different infectious disease backgrounds. In addition, extension of measurements of weight and height to adults would be extremely valuable in helping to validate the use of indices such as Body Mass Index (weight-height' ) in situations where chronic undernutrition of working populations is suspected as a determinant of poor health and performance. In addition, BMI may well prove to be an important basis for constructing health/nutrition indicators which provide a 'profile' covering all members of a household or family. All of these objectives would however entail the use of 'in depth studies' as part of the WHS design.

Other modules might consider specific nutritional deficiencies. Vitamin A and iodine deficiencies are still considerable public health problems in many developing countries. In the Asian countries, high prevalence and large populations at risk combine to produce an estimated half million cases per year of children with active corneal lesions and 5 million non-corneal xeropthalmias. About 800 million people are at risk of iodine deficiency diseases which include endemic cretinism as well as goitre. Although it is possible to show approximate geographical distributions of populations 'at risk', there is a shortage both of national representative studies and of withincountry distributions. Methodologies for measurement of status are technically demanding and expensive. However, the magnitude and persistence of these problems might justify a fairly intensive effort, at least in some carefully selected countries.

32
in Table 1) and for the median index of competition, we get a total spillover effect of -0.14 and -0.20 for the value and count-based

> 20 The classification of sectors by domestic value added is restricted to manufacturing, and is based on ISIC data which we concorded with HS 4-digit data.

> 21 The same result holds for an alternative classification by share of processing exports (with high domestic value added products being those with low share of processing) due to Koopman et. al. (forthcoming).

21
# **Success and failure of African exporters**<sup>_∗_</sup>

Olivier Cadot,<sup>_†_</sup> Leonardo Iacovone,<sup>_‡_</sup> Denisse Pierola,<sup>_§_</sup> Ferdinand Rauch<sup>_¶_</sup> May 10, 2011 Keywords: Africa, Export survival, Externalities, Firms. JEL classification: F10, F14, O55.

> _∗_ This paper is part of a World Bank research project initiated by Paul Brenton and Denisse Pierola. Financial support from the BNPP Trust Fund on Improving the Survival of African Exports and from the World Bank Research Support Budget is gratefully acknowledged. We are also grateful to the Malawi Revenue Authority, the Direction G ́en ́erale des Douanes du Mali, the Direction G ́en ́erale des Douanes du S ́en ́egal, and the Tanzania Revenue Authority for their cooperation and willingness to share data. We thank Frances Aidoo, William Baah-Boateng, Sidiki Guindo, Anthony Mveyange and Nelson Nsiku for their assistance in the collection of the customs data used in this paper.

> _†_ University of Lausanne and Trade Division, World Bank, 1818 H Street, NW; Washington, DC, 20433, USA, CEPR and CEPREMAP. Email:ocadot@worldbank.org.

> _‡_ Private and Financial Sector Department, Africa Region, World Bank, 1818 H Street, NW; Washington, DC, 20433, USA. Email: Liacovone@worldbank.org (Corresponding author).

> _§_ Development Economics Research Group - Trade team, World Bank, 1818 H Street, NW; Washington, DC, 20433, USA. Email: mpierola@worldbank.org.

> _¶_ CEP, London School of Economics, Houghton Street, WC2A 2AE, London, UK. Email: f.g.rauch@lse.ac.uk