rafmacalaba/data-use-mentions-extended huggingface dataset:
Figure 4: Value of Agriculture in the Sudanese Economy

- (a) Agricultural Exports since 1990

<!-- Start of picture text --> 6<br>Cotton Sesame seed and oil Groundnuts and oil<br>5 Sugar Sorghum Meats<br>Other Agricultural products<br>4<br>3<br>2<br>1<br>0<br>1990 1995 2000 2005 2010 2015<br>(100 millions)<br>constant international US$<br><!-- End of picture text -->

- (b) Agricultural Exports and Oil Production since 1990

<!-- Start of picture text --> Oil production index (2010 = 100)<br>Agriculture export index (2010 = 100) Succession of South Sudan<br>250<br>200<br>150<br>100<br>50<br>0<br>2000 2005 2010 2015<br>Index (2010 = 100)<br><!-- End of picture text --> _Source:_ FAOSTAT 2019<sup>5</sup> and IMF 2018.<sup>6</sup> Agriculture, particularly crop farming, is an important source of livelihood for Sudanese households, particularly in rural areas (Figure 5). In 2014, 40 percent of rural households identified crop farming as their main livelihood. Despite the decrease from 50 percent in 2009, crop farming still represents the most common source of livelihood in rural Sudan. In urban areas, only around 5 percent of households engage in crop farming (which is likely to be peri-urban farming). Around 5 percent of rural households identified animal husbandry as their main source of livelihood. Agriculture’s importance to households in rural Sudan links the study of the rural economy with understanding the agricultural decisions and outcomes of these agrarian households.

> 5 <u>http://www.fao.org/faostat/
Figure 1 Poverty Incidence at USD 6.85 a day 2017 PPP for LAC Countries, Actual vs. Projected <!-- Start of picture text --> 10.00<br>5.00<br>0.00<br>2017 -5.00<br>-10.00<br>ARG BOL BRA CHL COL CRI ECU SLV HND PAN PER PRY URY<br>Old - With Re-scaling New - With Re-scaling New - No Re-scaling<br>10.00<br>5.00<br>0.00<br>2018<br>-5.00<br>-10.00<br>ARG BOL BRA COL CRI DOM ECU SLV HND MEX PAN PER PRY URY<br>Old - With Re-scaling New - With Re-scaling New - No Re-scaling<br>10.00<br>5.00<br>0.00<br>2019 -5.00<br>-10.00<br>ARG BOL BRA COL CRI DOM ECU SLV HND PAN PER PRY URY<br>Old - With Re-scaling New - With Re-scaling New - No Re-scaling<br>10.00<br>5.00<br>0.00<br>2020<br>-5.00<br>-10.00<br>ARG BOL BRA CHL COL CRI DOM ECU MEX PER PRY URY<br>Old - With Re-scaling New - With Re-scaling New - No Re-scaling<br><!-- End of picture text --> Source: Own estimations based on SEDLAC.

Note: Actual data excludes COVID-19-related mitigation measures when the survey includes the program beneficiaries and the amount received.

17
Programme, and the Japanese International Cooperation Agency. Benu Bidani managed the fielding and analysis of the TLSS (World Bank (2003)). ” Timor-Leste is divided into 13 major units called Distritos (districts). These are further subdivided into 67 Postos (sub-districts), 498 Sucos (villages) and 2,336 Aldeias (hamlets) (Munoz (2001)).
Policy, Planning, and Reilch Intbmdonal Tmde'|

Laboi-intensive goods are the strongest export items for developing countries - and the United States is the developing countries' biggest export martet.

In 1965 the National Bureau of Economic Research predicted that developing countries would specialize in the manufacture and export - of labor-intensive goods and prepared a list of those goods.

A study of actual exports for 1965-1986 revealed that with few exceptions, export performance of those labor-intensive goods was superior in developing countries - which increased their.market shares for those items despite generally declining shares of world trade.

The United States absorbed nearly 55 percent of labor-intensive products in 1986 ($70.2 billion, comi red with only $34.4 billion in the EC). And mole than 40 percent of total U.S. imports of labor-intensive goods came from developing countries (compared with orAy 12 percent in the EC).

Many of the products the National Bureau identified as labor-intensive remain so, and therefore remain suitable for production and export by developing countries.

Clothing, footwear, leather products, wood manufactures, and some primary metal manufac- tures became relatively more labor-intensive so producers in industrial countries can expect increased competition from the developing countries in these products in the 1990s.

This paper is a product of the Intemational Trade Division, Intemational Economics Department. Copies are available free from the World Bank, 1818 H Street NW, Washington DC 20433. Please contact Jean Epps, room S8-037, extension 33710.

The PPR Workung Paper Series disseminates the fidings of work under way in the Barks Policy, Plaming, and Research Complex. An objective of the series is to get these flndinigs out qliickly, even if presentations are less then fully polished. The findings, interpretations, and conclusions in these papers do not necessarily represent of ficial policy of the Bank.

Produced at the PPR Dissenimnation Center
|
||_g p yp y_||(1.0)|(2.4)|(2.6)||
|_8_|<sup>_Share of people who report at least one_</sup>|0-100%|72.5|82.6|10.1|6808|
||_type of exposure to COVID-19_||(2.2)|(5.8)|(6.2)||

Notes: For all indicators, higher values indicate more severe outcomes. Indicator 2 is based on the Food Insecurity Experience Scale (FIES); Indicator 4 is based on the 12-item short form of the Buss-Perry Aggression Questionnaire (BPAQ-SF); Indicator 5 is based on 12-Item General Health Questionnaire (GHQ-12); Indicators 6 and 7 are based on WHO-5 Well-Being Index (WHO5). See World Bank Group et al (2022) for further detail on indicator choice and construction. All indicators except conflict and COVID exposure include only complete responses to the module; conflict and COVID exposure indicators include partial responses to the module. Clustered standard errors are reported in parentheses.

This systematic difference in overall results could stem from multiple sources. Part of it is likely driven by who makes up the Facebook survey sample. A small fraction of the people who clicked on the Facebook survey link completed the questionnaire, and this sample almost certainly overrepresents people who are relatively more interested in the psychological conditions of Palestinians and the effects of the May 2021 4
Development Bank.

- Nini, G. P. (2004). The Value of Financial Intermediaries: Empirical Evidence from Syndicated Loans to Emerging Market Borrowers. International Finance Discussion Paper 820, Board of Governors of the Federal Reserve System.

- OECD (2018). ODA by sector (indicator). doi: 10.1787/a5a1f674-en (Accessed on 29 November 2018).

- Oster, E. (2019). Unobservable Selection and Coefficient Stability: Theory and Evidence. _Journal of Business & Economic Statistics_ , 37(2):187–204.

22
they have experienced household tension in the last six months (1=No, not at all to 4=Yes, a lot). We construct a summary _relational outcomes composite index_ across all other-oriented outcomes.

**_Other._** We assess _redistributive preferences_ with three items assessing sharing-oriented attitudes and behaviors (how much alms respondents have given to the less fortunate in their community in the last two months, what percentage of any extra yields would they share with

> 17 This index included three additional variables than those pre-registered in order to match the construction of the business outcomes index in Bossuroy et al. (2022). These included measures of the number of days worked, having a business, and healthy business practices index.

41
<!-- Start of picture text --> 7 Rangpur =~<br>P=]© 6 @- Barisal / oh<br>Ee 5 ~ Khulna<br>G4 oe @ Rajshahi<br>d A<br>m3 @ Sylhet —>~<br>c —<br>ce 2 @ Dhaka ~ ><br>L<br>re a ya Chattogram<br>1 2 3 4 5 6 7<br>Ranking 2016 before imputation<br><!-- End of picture text --> <!-- Start of picture text --> 7 Rangpur * 7<br>2a 6 L -@ Barisal<br>£5 @ Rajshahi<br>Ga @ Sylhet<br>a ZA<br>a3 =~ @- Khulna<br>c A<br>a2 . ® Chattogram<br>1» eZADhaka .<br>1 2 3 4 5 6 7<br>Ranking 2016 before imputation<br><!-- End of picture text --> <!-- Start of picture text --> re}<br>=<br>zoo=<br>c<br>©<br>Q »<br>°<br>0.55 0.60 0.65 0.70<br><!-- End of picture text --> <!-- Start of picture text --> 2 i)<br>o<br>c<br>(a)<br>Qo<br>2<br>°<br>0.22 0.24 0.26<br><!-- End of picture text -->
municipalities’ needs may also affect spending ability. Our visits suggested that communities with more basic needs may find it easier to identify their needs during stakeholders’ consultations, and that the types of projects implemented in these municipalities may ease spending since they tend to be smaller, and of simpler design.

In spite of the strong attention that fiscal decentralization has received in the academic and policy literature, existing quantitative studies limit themselves at looking at specific constraints, and fail to assess the relative importance of the various factors highlighted above. On the other hand, more comprehensive studies reviewing factors affecting decentralization, which tend to be more of a policy nature (see, among many, Smoke, 2001; Tanzi, 2001; and Eaton _et al._ , 2010), remain for the most part qualitative. In this paper we bridge these two strands of literature by assessing quantitatively the relative importance of each factor in determining spending ability. In looking at spending ability, our research also complements existing literature looking at the extent to which various factors, such as gender, elite capture, or revenues from natural resources affect the type of spending (Chattopadhyay and Duflo, 2004; Araujo _et al._ , 2008; Caselli and Michaels, 2009) and spending efficiency (De Borger and Kerstens, 1996; García-Sánchez, 2006; and Balaguer-Coll _et al._ , 2007). While it would be of great interest to complement the analysis of spending ability with information on spending efficiency, to the best of our knowledge these data currently only exist for high income countries.

# **III. Data**

The analysis draws on a combination of particularly rich databases containing information at the municipal level. For each of the more than 1,830 municipalities in Peru we have information on public spending undertaken by the municipality, population, staffing levels at the municipality, poverty, reported social conflicts, and a number of features of the political process.

The public expenditure data at the municipal level is particularly detailed. For each municipality in
# **II.   DATA CONSTRUCTION**

The analysis focuses throughout on the developing countries in East Asia and the Pacific (EAP, or “East Asia” for brevity), as defined by the World Bank.<sup>4</sup> The starting point of our data set is a set of harmonized household survey data by the World Bank, which we supplement with additional data from PovcalNet.<sup>5</sup> In total, we use 60 surveys, with 31 surveys directly from the microdata and the remainder from PovcalNet. Because most countries do not conduct annual surveys, we match these surveys to a number of benchmark years – 1988, 1992, 1997, 2002, 2007, and 2012.<sup>6</sup> Due to limited availability of microdata, all information for the first two benchmark years is entirely based on PovcalNet. For China, no microdata are available, so all data come from PovcalNet.

Our database includes around 10 surveys per benchmark year out of a total of 19 EAP countries, and 92% of the surveys are consumption surveys (Table 1).<sup>7</sup> Given our interest in estimating the EAP distribution of consumption expenditure, it is of course important that the surveys included in our database cover as much of the region as possible. On average, we cover about 98% of regional GDP, and at 97% a slightly lower share of the regional population (Table 1).<sup>8</sup> While we have a good coverage of EAP as a whole, our coverage of Pacific countries is relatively low and unstable.<sup>9</sup> The Appendix includes a robustness check using only those countries that are available in all benchmark years.

Each national distribution is approximated by the average consumption of the 100 percentile groups. For the microdata, percentile groups are computed directly from the household survey. PovcalNet also reports percentile groups whenever it has access to micro
(CPI).<sup>9</sup> To derive this index, TI collects data on corruption from a number of other sources,<sup>10</sup> standardizes them, and calculates the simple average by assigning equal weights. The assessment also combines data from a few past years to reduce abrupt variations in scoring.

The reliability of each figure is improved by including only countries that have been included into three polls at minimum. An indicator for the overall reliability of the index can be drawn from the high correlation between the sources (see Appendix A). Standardization of the index ensures that the inclusion of a source consisting of a certain subset of countries should not change the mean and standard deviation of this subset of countries in the CPI. The reason is that the aim of each source is to assess countries relative to each other, and not relative to countries not included in the source. This includes the idea that a country must not be punished for being compared with a subset of relatively uncorrupt countries, nor rewarded for being compared with a subset of relatively corrupt countries.

# **_Independent Variables:_**

# _1. The Role of the State in the Economy_

We use a variety of measures to capture different aspects of the state:

- _Size of Government_ : is proxied by public investment as a share of GDP, including investment by public enterprises, local authorities and consolidated central government.

- _Tax System_ : Efficiency and equality of tax system, tax rates, enforcement of tax regulations, and the tax system as an incentive mechanism are used. Our measure comes from the 1997 World Development Report, which examines the burden of tax regulations and high taxes. This information is used to measure the overall quality of tax management.

> 9 For details see http://www.transparency.org/surveys/index.html

> 10 Of these, five are for business executives of international or business companies, two by the relevant organization’s staff,
6<br>.4 .4<br>.2 .2<br>0 0<br>45-46 49-50 53/54 57/58 61/62 65/66 69/70 45-46 49-50 53/54 57/58 61/62 65/66 69/70<br>age age<br>Pension Eligible Working/Total Pension Eligible Working/Total<br>Rural Male Rural Female<br>1 1<br>.8 .8<br>.6 .6<br>.4 .4<br>.2 .2<br>0 0<br>45-46 49-50 53/54 57/58 61/62 65/66 69/70 45-46 49-50 53/54 57/58 61/62 65/66 69/70<br>age age<br>Pension Eligible Working/Total Pension Eligible Working/Total<br>(Only Include Adults Who Directly Reported To The Employment Survey)<br>Panel C Korea<br>Korea<br>Urban Male Urban Fmale<br>1 1<br>.8 .8<br>.6 .6<br>.4 .4<br>.2 .2<br>0 0<br>45-46 49-50 53/54 57/58 61/62 65/66 69/70 45-46 49-50 53/54 57/58 61/62 65/66 69/70<br>age age<br>Pension Eligible Working/Total Pension Eligible Working/Total<br>Rural Male Rural Female<br>1 1<br>.8 .8<br>.6 .6<br>.4 .4<br>.2 .2<br>0 0<br>45-46 49-50 53/54 57/58 61/62 65/66 69/70 45-46 49-50 53/54 57/58 61/62 65/66 69/70<br
Galor, O. and D. N. Weil. (1996), ‘The Gender Gap, Fertility and Growth,’ _American Economic Review_ , **86** , 374-387.

General Statistics Office. (2010), _Statistical Yearbook of Vietnam 2010_ , Hanoi: Statistical Publishing House.

Glick, P. and F. Roubaud. (2006), ‘Export Processing Zone Expansion in Madagascar: What are the Labour Market and Gender Impacts?’ _Journal of African Economies_ , **15** , 4, 722-756.

Goldin, C. and K. Sokoloff. (1982), ‘Women, Children, and Industrialization in the Early Republic: Evidence from the Manufacturing Censuses,’ _The Journal of Economic History_ , **XLII** , 4, 741-774.

Heckman, J. (1979), ‘Sample Selection Bias as a Specification Error,’ _Econometrica_ , **47** , 153161.

Heyman, F., F. Sjöholm and P. G. Tingvall. (2007), ‘Is There Really a Foreign Ownership Wage Premium? Evidence from Matched Employer-Employee Data,’ _Journal of International Economics_ , **73** , 355-376.

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Korenman, S. and D. Neumark. (1991), ‘Does Marriage Really Make Men More Productive?’ _The Journal of Human Resources_ , **26** , 2, 282-307.

Krueger, A. B. and L. H. Summers. (1988), ‘Efficiency Wages and the Inter-Industry Wage Structure,’ _Econometrica_ , **56** , 2, 259-94.

Lemieux T., B. W. MacLeod and D. Parent. (2009), ‘Performance Pay and Wage Inequality,’ _The Quarterly Journal of Economics_ , **<mark>124</mark>**
were subject to 2 events, 2 banks to 3 events, 2 banks to 4 events, and one bank to 6 events. These 42 resolutions of financial distress could occur multiple times in a year for the same bank, where the most frequent action was government intervention in the form of bailouts (23 cases) followed by forced liquidation (9 cases), mergers (7 events), reorganization (2 events), and voluntary liquidation (1 event).

**Figure 1: Number of banks and events over the sample period (2009-2021)**

**A: Number of banks by year B: Number of events by year**

<!-- Start of picture text --> 40 38 39 38 38 38 38 8<br>37<br>35<br>33<br>32<br>30 28 27 6<br>26<br>4<br>20<br>2<br>10<br>0<br>2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021<br>0 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 Government intervention Liquidation Merged Reorganisation Voluntary liquidation<br>Number of events<br>Number of banks<br><!-- End of picture text --> Source: Own elaboration using data from the National Bank of Kazakhstan, National Wealth Fund Samruk-Kazyna, the Kazakhstan Sustainability Fund, and public news reports.

Note: In Panel A, the total number of banks is taken over each year, i.e., if a bank exits the market in a year, it is still counted in the total number of banks. In Panel B, government intervention is the sum of the events where the provision of equity, purchase of non-performing exposures, and the extension of credit to ailing institutions were recorded.

6
br>|
|---|---|---|---|---|
|**_Sector 1_**|y11<br>|y12<br>⋯<br>|y1n<br>|f1<br>|
|**_Sector 2_**|y21|y22<br>⋯|y2n|f2|
|⋮|⋮<br>|⋮<br>⋮<br>|⋮<br>|⋮<br>|
|**_Sector n_**|yn1<br>|yn2<br>⋯<br>|yn<br>|fn|
|**_Added Value (V)_**|v1<br>|v2<br>⋯<br>|vn<br>||
|**_Gross product (Y)_**|Y1|Y2<br>⋯|Yn||

Source: Own elaboration The third source of information, the Climate Watch/CAIT series, contains information about the level of GHGE by industry and end-uses from 1990 to 2018, following the Intergovernmental Panel on Climate Change (IPCC) reporting framework. Table 4 presents the sectors included in CAIT and the activities they

> 13 Available in https://www.climatewatchdata.org/ghg-emissions?end_year=2018&start_year=1990.

9
Table 7: Evidence from Customs’ Office Data

||(1)<br>N. Ship.|(2)<br>Val. per Ship.|
|---|---|---|
|Input PSI|-0.303***|0.189***|
||(0.016)|(0.071)|
|Input tarif|-0.816|-12.164|
||(1.355)|(11.637)|
|Observations|13,035|13,035|
|R-squared|0.863|0.789|
|Other NTMs|yes|yes|
|Importer FE|yes|yes|
|Year FE|yes|yes|

**Note:** This table shows the effect of inputs exposure to pre-shipment inspections (PSI) on the plant’s average number of shipments (col. 1) and the average value per shipment (col. 2), both in logarithmic scale, in the years between 2014 and 2018. _Input PSI_ is the share of the total value of imported goods covered by PSI. The impact of import tariffs is measured analogously. All specifications include controls for other NTMs applied on plant’s inputs, importer fixed effects and year fixed effects. Standard errors are robust to heteroskedasticity and clustered at the importer level. *, **, *** indicate statistical significance at the 10%, 5%, and 1% levels, respectively.

27
10 by the firm's replacement value (net fixed assets plus inventory).<sup>8</sup> Table 1, Panel C reports summary statistics. The mean Q across all five years is 0.81 which is very close to the 0.85 reported by MSV for their sample of US firms. There is a decline in mean Q over the years as the aggregate stock market went down after the initial surge in 1992. Agriculture is the only sector where mean Q increased over the period (Table A2). Typically, firms in high-skill intensive sectors and with valuable intangible assets will have high Qs, while firms in physical capital intensive industries and/or industries where the output prices are regulated will have low Qs. The sectoral dispersion of Czech firms' Qs is consistent with this: 7 of the top 10 firms (highest Qs) are in services, while 8 of the bottom 10 (lowest Qs) firms are in utilities.<sup>9</sup> Profitability is defined as gross (operating) profit over net fixed assets plus inventory. Table 1, Panel C reports summary statistics. It increases monotonically over time in all sectors (Table A2), varying between 12 % in 1992 and 17% in 1995 on average. 7 of the top 10 firms (highest profitability) operate in the engineering and architectural design, management, accounting sectors; six of the bottom 10 operate in the basic metals and the fabricated metal products (including armaments) sectors. The correlation between Tobin's Q and profitability goes up over time, which suggests that the market valuation becomes a better indicator of relative profitability as accounting data start to reflect the changes in the firms' performance.

# IV. **Regression Results**

We run the regressions using all years and all firms in each year, i.e., as an unbalanced panel. F-tests reject the hypothesis of a common constant term across firms. The Hausmanspecification tests indicate that either the fixed or
|R sq.|0.0761|0.7565|0.5825|0.9201|0.8192|0.5790|0.9009|0.7119|
|---|---|---|---|---|---|---|---|---|
|N|149|118|54|32|22|49|31|18|
|groups|19|15|||||||
|Method<br>|RE|RE|POOLED IV<br>2SLS|POOLED IV 2SLS|POOLED IV<br>2SLS|POOLED IV<br>2SLS|POOLED IV<br>2SLS|POOLED IV<br>2SLS|
|Wald test Chi<sup>2</sup><br>statistics p-<br>value|0.0022|0.0000|0.0000|0.0000|0.0000|0.0000|0.0000|0.0000|
|Chow test F<br>statistics p-<br>value|0|.0000||0.8832|||0.9534||

_Note: *** significant at 1% level, ** significant at 5% level, * significant at 10% level. RE - random effects generalized least squares estimation method, POOLED IV 2SLS - pooled two stage least squares procedure with instrumental variables on panel data; robust standard errors utilized. The detailed description of all the models applied in our analyses is given in Annex 4._ _Source: OECD, Eurostat, World Bank, Heritage Foundation, IZA, own calculations._

# _<u>Model 5 – Share of workers without a legal contract</u>_

The last model that we examine is Model 5 with share of labor force employed without a legal written contract as a dependent variable, the results of
to the International Classification of Standards (ICS) nomenclature, which allows for matching standards to trade data. The database allows differentiation between Chinese standards harmonized to international norms such as Codex Alimentarius and standards that are unique to China.<sup>8</sup> . International standards in our paper are defined as standards developed by international standards setting organizations (e.g. Codex Alimentarius Commision) which are adopted as Chinese national standards. A concordance table between the seven-digit ICS categories and the trade data in HS codes can be found in Table A.1 in the Appendix. The database allows us to construct four different standards variables according to two criteria: (i) mandatory vs. voluntary standards, and (ii) domestic vs. international harmonized standards.

Table 1 provides some examples to illustrate the different types of standards. The first example, the standard GB/T 19838-2005 for fish and fishery products is a voluntary domestic Chinese standard. It makes companies accountable for analyzing potential hazards

> 7 SAC obtained legal recognition by the Chinese government through the Standardization Law of the People’s Republic of China from 1988 (source: ISO).

> 8 SAC develops mandatory and voluntary standards. The prefix “GB” indicates mandatory standards and voluntary standards are prefixed “GB/T.

7