rafmacalaba/datause-encoder-data huggingface dataset:
# Introduction

## The continental perspective

The Africa Infrastructure Country Diagnostic (AICD) has gathered and analyzed extensive data on infrastructure in more than 40 Sub-Saharan countries, including Uganda. The results have been presented in reports covering different areas of infrastructure—information and communication technology (ICT), irrigation, power, transport, and water and sanitation—and different policy areas, including investment needs, fiscal costs, and sector performance.

This report presents the key AICD findings for Uganda over the period 2001 to 2006, allowing the country’s infrastructure situation to be benchmarked against that of its African peers using data collected over the same period, and providing a baseline against which to assess Uganda’s subsequent progress in the infrastructure sectors. Uganda is a low-income state that has recently discovered oil; therefore, both low-income and resource-rich benchmarks will be used to evaluate its performance. Detailed comparisons will also be made with immediate regional neighbors in the East African Community (EAC) in some cases.

Several methodological issues should be borne in mind. First, because of the cross-country nature of data collection, a time lag is inevitable. The period covered by the AICD runs from 2003 to 2009. Most technical data presented are for 2009 (or the most recent year available), while financial data are typically averaged over the available period to smooth out the effect of short-term fluctuations. Data on benchmark countries, however, typically relate to the somewhat earlier period 2001 to 2006. Second, to make comparisons across countries, it was necessary to standardize the indicators and analysis so that everything was done on a consistent basis. This means that some of the indicators presented here may be slightly different from those that are routinely reported and discussed at the country level.

## Country context

Despite conflict, political unrest, and various geographical disadvantages, Uganda has sustained relatively high and robust growth rates over two decades. Annual gross domestic product (GDP) growth rates averaged 7 percent in the 1990s and accelerated to more than 8 percent over the first seven years of the 2000s. Growth was around 6.1 percent in 2010, and is predicted to grow to over 7 percent in the foreseeable future. But due to rapid population growth, real GDP growth per capita averaged only 3.4 percent in the 1990s and around 4 percent in the 2000s.

Strong growth performance has contributed to a substantial decline in poverty levels. The proportion of people living in poverty fell from 57 percent in 1992–93 to 31 percent in 2005–06. However, 3
Skoufias, E., Vinha, K., & Beyene, B. M. (2021). Quantifying Vulnerability to Poverty in the DroughtProne Lowlands of Ethiopia. _Policy Research Working Paper_ ; No. 9534. World Bank, Washington, DC. © World Bank. https://openknowledge.worldbank.org/handle/10986/35107 Sulla-Menashe, D., & Friedl, M. A. (2018). _User guide to collection 6 MODIS land cover (MCD12Q1 and MCD12C1) products_ . USGS: Reston, VA, USA, 1, 18.

Socio-Economic Database for Latin America and the Caribbean (2022). <u>https://www.cedlas.econo.unlp.edu.ar/wp/en/estadisticas/sedlac/. CEDLAS and The World Bank.</u> Retrieved March 2022.

Solano-Rodríguez, B., Pye, S., Li, P. H., Ekins, P., Manzano, O., & Vogt-Schilb, A. (2021). Implications of climate targets on oil production and fiscal revenues in Latin America and the Caribbean. _Energy and Climate Change_ , 2, 100037. <u>https://doi.org/10.1016/j.egycc.2021.100037</u> Stampini, M., & Tornarolli, L. (2012). The growth of conditional cash transfers in Latin America and the Caribbean: did they go too far? _IZA Policy Paper_ . No. 49 ThinkHazard! Platform (2022). https://thinkhazard.org/. Global Facility for Disaster Reduction and Recovery (GFDRR Labs). The World Bank. Retrieved March 2022.

UNDP (2022). Social Protection in Times of Uncertainty. _Technical Note: Recalibrating... Getting Back on Track Towards the SDGs_ . XIV Ministerial Forum for Development in Latin America and the Caribbean.

Ward, P. J., Blauhut, V., Bloemendaal, N., Daniell, J. E., de Ruiter, M. C., Duncan, M. J., Emberson, R., Jenkins, S. F., Kirschbaum, D., Kunz, M., Mohr, S., Muis, S., Riddell, G. A., Schäfer, A., Stanley, T., Veldkamp, T. I. E. & Winsemius, H. C. (2020). Natural hazard risk assessments at the global scale. _Natural Hazards and Earth System Sciences_ , 20(4), 1069-1096.

World Bank (2022). _Hoja de ruta para la acción climática en América Latina y el Caribe 2021-2025_ .

Zhang, H., Zhao, Y., & Pedersen, J. (2020). Capital assets framework for analyzing household vulnerability during disasters. _Disasters_ , 44(4), 687-707.

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2005; Patel et al., 2004). Evidence of such costs in other dimensions of welfare such as education also exist (Kessler et al., 1995).

If, as the comparative research project suggests, negative shocks lead to worse mental health which in turn may decrease labor supply and increase expenditures on health care then this chain of events raises the possibility of a behavioral poverty trap. Clearly additional research is needed to better understand the causal mechanisms and dynamic phasing at play including study of the long and short-term effects of negative and positive shocks to mental health. Research into the cost-effectiveness of interventions targeted towards those in poor mental health will also shed needed light on the rationale for publicly financed mental health interventions. The clustering of mental health outcomes within households and communities raises the possibility that such treatments targeted at the level of the _household or community_ may be more cost-effective than those targeted to individuals and this should be investigated.

An important limitation of this study and of the household-survey based methodology is our inability to differentiate common from severe mental disorders. Although both disorders are a cause of personal misery, a clear distinction has been remarked on in the literature, especially in the context of findings that the annual prevalence of common mental disorders exceeds 10 percent in many countries, and is as high as 16.9 percent in Lebanon, 17.8 percent in Colombia, 20.4 percent in Ukraine and 26.3 percent in the United States (WHO World Mental Health Survey Consortium, 2004). Severe mental health (such as schizophrenia), brought on by bio-genetic causes and possible interactions with environment, have much lower prevalence and require specialized studies rather than multipurpose surveys to identify as well as most likely require a separate policy response. In several low-income countries, the institutional capacity for treating such disorders is very poor with frequent human-rights violations of the severely mentally ill (WHO, 2001).

A final limitation of this study – one mentioned throughout the text – is that, in the absence of an experimental setup, the associations presented are consistent with multiple interpretations. For instance, the concordance of mental health outcomes within households could reflect unobserved household-level shocks, assortative matching (where those in poor mental health are more likely to marry each other), genetic links between parents and children, or a “contagion” effect, whereby caring for a mentally ill person in the household in turn affects the mental well being of others. Longitudinal data and experimental mental health interventions are needed to try and separate these disparate channels and to explore the link between mental health outcomes and broader measures of welfare that incorporate risk and vulnerability in their construction.

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21

# Table I

The Average Level of Financial Develcipment and the Contemporaneous Growth Rate of Real Per Capita GDP: 1960-1989

||Very<br>fast|Fast|Slow|Very<br>slow|Correlation<br>with growth|(P-value)|
|---|---|---|---|---|---|---|
|LLY|0.60|0.38|0.29|0.22|0.55|(0.001)|
|BANK|0.81|0.73|0.71|0.60|0.44|(0.001)|
|PRIVATE|0.70|0.56|0.61|0.51|0.37|(0.001)|
|PRIVY|0.35|0.27|0.20|0.13|0.50|(0.001)|
|GROWTH|0.045|0.026|0.014|-0.005|||

Very fast: GROWTH > 0.03 Fast: GROWTH > 0.02 and < 0.03 Slow: GROWTH > 0.005 and ' 0.02 Very slow: GROWTH < 0.005 LLY = Liquid liabilities to GDP BANK = Deposit money bank domestic credit divided by deposit money bank + central bank domestic credit PRIVATE = Claims on the nonfinancial private sector to total domestic credit PRIVY = Gross claims on private sector to GDP GROWTH = Average annual real per capita growth 1960-1989 Observations: Approximately 20 in each of the four categories.
Hanasaki, N., Yoshikawa, S., Pokhrel, Y., Kanae, S. (2018) A global hydrological simulation to specify the sources of water used by humans. Hydrol. Earth Syst. Sci. 22, 789-817.

- Khan, A.E., Ireson, A., Kovats, S., Mojumder, S.K., Khusru, A., Rahman, A., Vineis, P. (2011) Drinking water salinity and maternal health in coastal Bangladesh: implications of climate change. Environmental Health Perspectives 119, 1328-1332.

- Khan, A.E., Scheelbeek, P.F.D., Shilpi, A.B., Chan, Q., Mojumder, S.K., Rahman, A., Haines, A., Vineis, P. (2014) Salinity in Drinking Water and the Risk of (Pre)Eclampsia and Gestational Hypertension in Coastal Bangladesh: A Case-Control Study. PLoS ONE 9, e108715.

- R Core Team, (2017) _R_ : A language and environment for statistical computing (R version -

- 3.4.3). R Foundation for Statistical Computing, Vienna, Austria. URL <u>http://www.R project.org/.</u>

Rahman, A.A., Ravenscroft, P., (2003) Groundwater resources and development in Bangladesh. The University Press Limited, Dhaka, p. 446.

- Ravenscroft, P., (2003) Overview of the hydrogeology of Bangladesh, in: Rahman, A., Ravenscroft, P. (Eds.), Groundwater resources development in Bangladesh. The University Press, pp. 43-86.

- Ravenscroft, P., McArthur, J.M., Hoque, M.A. (2013) Stable groundwater quality in deep aquifers of Southern Bangladesh: The case against sustainable abstraction. Sci Total Environ. 454-455, 627-638.

- Rusydi, A.F. (2018) Correlation between conductivity and total dissolved solid in various type of water: A review. IOP Conf. Series: Earth and Environmental Science 118, 012019.

Shamsudduha, M., (2018) Impacts of Human Development and Climate Change on Groundwater Resources in Bangladesh, in: Mukherjee, A. (Ed.), Groundwater of South Asia. Springer Hydrogeology, Singapore, pp. 523-544.

- Shamsudduha, M., Chandler, R.E., Taylor, R.G., Ahmed, K.M. (2009) Recent trends in groundwater levels in a highly seasonal hydrological system: the Ganges-BrahmaputraMeghna Delta. Hydrol. Earth Syst. Sci. 13, 2373-2385.

- Shamsudduha, M., Taylor, R.G., Longuevergne, L. (2012) Monitoring groundwater storage changes in the highly seasonal humid tropics: validation of GRACE measurements in the Bengal Basin. Water Resour. Res. 48, W02508.

- Shamsudduha, M., Zahid, A., Burgess, W.G. (2018) Security of deep groundwater against arsenic contamination in the Bengal Aquifer System: a numerical modeling study in southeast Bangladesh. Sustainable Water Resources Management, doi.org/10.1007/s40899-40018-40275-z.

- Smith, A.H., Lingas, E.O., Rahman, M. (2000) Contamination of drinking water by arsenic in Bangladesh: a public health emergency. Bulletin of the World Health Organization 78, 1093-1103.

- Taylor, R.G., Scanlon, B., Doll, P., Rodell, M., van Beek, R., Wada, Y., Longuevergne, L., Leblanc, M., Famiglietti, J.S., Edmunds, M., Konikow, L., Green, T.R., Chen, J., Taniguchi, M., Bierkens, M.F.P., MacDonald, A., Fan, Y., Maxwell, R.M., Yechieli, Y., Gurdak, J.J., Allen, D.M., Shamsudduha, M., Hiscock, K., Yeh, P.J.F., Holman, I., Treidel, H. (2013) Ground water and climate change. Nature Climate Change 3, 322-329.

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Table 10 Earnings differentials between teachers and other wage workers by contract type

||<br>Mon|<br>thly<br>i||<br>Ho|<br>urly<br>i|
|---|---|---|---|---|---|
||Permanent|Fxed term<br>/temporary||Permanent|Fxed term<br>/temporary|
||(1)|(2)||(3)|(4)|
|Burkina Faso|0.474***|0.042||0.656***|0.416|
||(0.107)|(0.305)||(0.110)|(0.311)|
|Côte d'Ivoire|0.567***|-0.154||1.009***|0.351*|
||(0.161)|(0.190)||(0.173)|(0.208)|
|DR Congo|-0.061|-0.152***||0.089*|0.020|
||(0.045)|(0.054)||(0.048)|(0.058)|
|The Gambia|||N.A.|||
|Ghana|||N.A.|||
|Liberia|||N.A.|||
|Malawi|||N.A.|||
|Namibia|0.393***|0.279**||0.566***|0.478***|
||(0.062)|(0.123)||(0.066)|(0.132)|
|Niger|-0.098|-0.252||0.157|-0.039|
||(0.165)|(0.231)||(0.169)|(0.240)|
|Nigeria|||N.A.|||
|Senegal|0.234***|0.178||0.568***|0.417***|
||(0.059)|(0.114)||(0.063)|(0.122)|
|Sierra Leone|-0.558***|-0.709**||0.016|0.493|
||(0.137)|(0.322)||(0.171)|(0.461)|
|Tanzania|-0.141***|-0.258*||0.011|-0.210|
||(0.041)|(0.152)||(0.045)|(0.168)|
|Uganda|-0.192**|-0.180*||0.020|-0.100|
||(0.097)|(0.104)||(0.118)|(0.123)|
|Zambia|0.589***|0.036||0.762***|0.179|
||(0.048)|(0.109)||(0.053)|(0.122)|
|**Average **|**0.121**|**-0.117**||**0.385**|**0.201**|

Notes: Each column reports the coefficient in the regressions of ln (monthly/hourly earnings) on (a dummy for) a type of teachers with controls. The comparison group are other wage workers. Controls include gender, age, agesquared, urbanicity and (a dummy for) post-secondary education. Sample is restricted to workers with secondary education or more. Surveys in The Gambia, Ghana, Liberia, Malawi, and Nigeria did not report whether a worker was on a permanent or fixed term/temporary contract. Standard errors in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Source: Surveys listed in Table 1.

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of financial constraints for the same set of firms over time. More importantly, we use the reported severity of financial constraints on a firm‘s operations as our dependent variable, whereas Brown et al. (2011) use measures of access to and use of credit. The reported constraints variables are likely to be forward-looking about the potential effects of the crisis, whereas the access/use variables better summarize the financial situation of firms before the crisis.

Other papers have used firm, bank, and country-level data to study past crises within the ECA region. Using data from large multinational banks from 1991 to 2004, de Haas and van Lelyveld (2010) find that their lending did not slow during systemic crises in a host country, which they attribute to the support received by subsidiaries from their parent banks. Similarly, domestic banks contracted their credit base during crises from 1993 to 2000, whereas greenfield foreign banks did not (de Haas and van Lelyveld, 2006). Furthermore, a study of banks and firms in 13 countries in Eastern Europe from 2000 to 2005 shows that lending relationships for foreign banks tended to be more stable than those of domestic banks in that foreign banks were less likely to drop their clients, even in the aftermath of an acquisition, and that the presence of foreign banks was associated with a lower probability of crisis in the ECA region (Giannetti and Ongena, 2009 a,b). Of course, the financial crisis episodes studied in those papers grew within ECA countries themselves, and thus the recent global crisis, which emanated from the banking sectors of advanced economies, offers an opportunity to test whether foreign affiliates behave differently when their parent banks face difficulties in their home markets.

Another strand of recent literature focuses on capital flows, particularly the cross-border component of bank flows, measured at the country level to assess the effects of the crisis (Cetorelli and Goldberg, 2009, 2011; Milesi-Ferretti and Tille, 2011; Hermann and Mihaljek, 2011). A number of those studies suggest that strong ties between home and host countries made it more likely that foreign banks would act to stabilize credit during the recent crisis within the ECA region.<sup>3</sup>

> 3 Hermann and Mihaljek (2011) find that greater financial and monetary linkages between lender and borrower countries were stabilizing forces, and many countries in ECA had relatively strong links to advanced economies. Similarly, cross-border bank-to-bank flows to Eastern European countries with a higher foreign bank asset share were more stable during the crisis than flows to other emerging markets (Vogel and Winkler, 2011). Based on the

3
The fact that log GDP per capita and ...xed assets per capita tend to be higher for municipalities which adopted the reform earlier does not per se invalidate the identi...cation strategy since the identi...cation strategy relies on changes over time being similar across municipalities. Thus, Table 3 also compares changes in log GDP per capita, log economic establishments per capita, log ...xed assets per capita, and log investment per capita from 1994 to 1999. The averages for early and late adopters are in Columns 1 and 2 in Panel B of Table 3. Columns 3 and 4 show that the changes in the Economic Census variables are not signi...cantly di¤erent across early and late adopters and that they do not follow a speci...c pattern of implementation over time. This adds plausibility to the argument that changes of outcomes in these municipalities would have been similar in the absence of the reform. To further support the identi...cation strategy, in the following section, I illustrate that there is no pattern of adoption related to pre-reform outcome data.

Finally, in the empirical strategy, I take into account that log GDP per capita and log ...xed assets per capita di¤ered across early and late adopters in 1999 by controlling for 1999 Economic Census variables interacted with a linear time trend. It is not possible to control for contemporaneous Economic Census variables or Economic Census variables closer to the year of ...rst implementation (2002) since the Economic Census in Mexico is only conducted every ...ve years and there is no higher frequency data on GDP at the municipality level. To explore Mexico’s economic situation at the time around the reform in more detail, Figure 6 displays the time series of quarterly real GDP (in 1993 Mexican pesos). The time series shows that the Mexican economy experienced a downturn between 2000 and 2002. Then, GDP started increasing again, and it grew at higher rates from 2004 on. To account for these non-linear patterns and for the possibility that they may di¤er across municipalities, I re-ran the main regressions of the paper controlling for Economic Census variables interacted with a linear time trend and with time trends of higher powers, up to power 4. The results change only minimally and are not reported in the paper.

# 5 Mexican Employment Survey Data

My main outcome data comes from the Mexican National Employment Survey (ENE). The ENE is the survey that the Mexican government relies on for calculating unemployment statistics and for calculating the size of the informal sector. It has been conducted quarterly since 2000-II and covers a random sample of approximately 150,000 households. Each household remains in the survey for ...ve consecutive quarters. I use data for 2000-II to 2004-IV (19 quarters in total). After 2004-IV, the ENE was changed to a new survey, whose results have not been made publicly available.

14
Table 4 reports the results for the share of land allocated to coffee. We report the fixed effects tobit regression results, as well as the random effects tobit findings. Table 5 presents a probit with robust standard errors and a random effects probit, explaining transfer rights at the plot level. This regression is used subsequently as the first stage regression in table 4 for instrumenting transfer rights. The first regression in table 4 shows that modes of acquisition matter. Relative to the base group, land allocated by the government, farmers are growing about 49 percent less coffee on sharecropped plots. The latter result may seem self-evident, but in the data sharecropped plots often still have coffee on them. While non-sharecropped plots have about 22 percent of the land allocated to coffee on average, sharecropped plots have on average about 9 percent of land with coffee.<sup>10</sup> Furthermore, and most important for our analysis, farmers grow about 9 percent more coffee on inherited plots, than in government allocated plots.

Column (2) shows the impact of using perceived transfer rights, rather than the more indirect route of modes of acquisition, to discuss the impact on coffee growing. It can be seen that transfer rights make a difference, and farmer grow typically 13 percent more coffee on plots with reported transfer rights relative to one without these rights. This regression uses however the uninstrumented transfer rights. Both the reverse causality bias (endogeneity of transfer rights since tree planting may increase rights) as well as measurement error may affect this estimate, so we decided to instrument this variable. Table 5 presents probit regressions, one with robust standard errors and another one with random effects, explaining transfer rights. Recall that we have plot level transfer right data available for the two latest rounds used in the analysis. Identifying instruments used are modes of acquisition (sharecropped, inherited, purchased and a very small number of other means of acquisition, all defined relative to land allocated by the government) as well as the number of years the plot has been used or owned. We observe significant effects on sharecropped plots (as expected, reducing perceived transfer rights), and inherited plots and the number of years the plot has been owned (both raising transfer rights), besides a number of other characteristics.<sup>11</sup> The predicted values of the random effects model are

> 10 This is not so in the case of eucalyptus or chat, with less than 1 percent of land with these crops if the plot is sharecropped.

> 11 Marginal effects show for example that 10 years longer use or ownership of a plot increases perceived transfer rights by 4 percent and an inherited plot was 9 percent more likely to be perceived to be transferable, relative to a plot allocated by the government.

18
Stango, V. Zinman J. 2011. "Fuzzy Math, Disclosure Regulation, and Market Outcomes: Evidence from Truth-in-Lending Reform" _Review of Financial Studies_ 24(2): 506-534.

Thaler R, Sunstein C. 2008. _Nudge, Improving Decisions about Health, Wealth, and Happiness._ New Haven: Yale University.

World Bank. 2008. _Finance For All? Policies and Pitfalls in Expanding Access._ Washington, D.C.

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