rafmacalaba/data-use-mentions-extended huggingface dataset:
# 4. Discussion

This study has demonstrated that there are major hidden costs of HAIs in SSA. Every day, millions of Africans receive inpatient care in a healthcare facility – whether for a chronic illness or acute disease, surgical procedures or for labor and delivery and postpartum services – but in their vulnerable state an estimated 10% or more of these people become infected by a microorganism while receiving medical care, a high proportion of which are resistant to first, second- and even third-line drugs.

By quantifying the major costs associated with these infections at national level – direct healthcare costs of treatment, productivity losses for the patients, and the value of lost lives – this study shows that the economic costs exceed 1.14% of the GDP of nine countries in Eastern and Southern Africa and the direct healthcare costs exceed 7% of total health spending in these countries.

While efforts were made to select data sources that best reflect the national contexts in the countries of study, there are still some methodological weaknesses, excluded impacts and data limitations associated with a multi-country desk study that is reliant on secondary data sources.

This study adopted a standard cost-of-illness methodology (Morel et al, 2020; Shrestha et al, 2018). While previous studies have assessed the direct healthcare costs of HAIs in SSA (Aerts et al, 2022; Schäferman et al, 2020; Gidey et al; 2023; Otieku et al, 2023), none have included the indirect costs to the patient. Hence, standard economic approaches were used to value the loss of productive time due to a longer time spent away from work or home. In some instances, this loss may be incurred by a caregiver or family member– for example, a woman who has just delivered a baby is unlikely to return to work immediately, but the HAI she contracts may result in a loss of earnings or productive time for a partner or relative.

Quantifying the cost of premature death due to HAI is important, given that a significant proportion of HAIs lead to
We also check whether our results are affected by augmenting our baseline model with a triple interaction ( _CF × Large × PC_ ). The coefficient of the triple interaction captures whether political connections have a different effect in small and large firms. A negative coefficient would signal that connections are more helpful for large than small firms. We find that the triple interaction is not statistically significant (suggesting that connections exert the same influence in large and small firms), more interesting for our purposes, we find that controlling for this triple interaction does not alter our baseline results (column 4, Table 4).

Next, we check whether our results are driven by a particular country by estimating the different models of Table 4 by allowing different coefficients for the six countries included in our sample. The top left panel of Figure 1 reports the results for the baseline model (this is equivalent to column 2 of Table 4). It shows that the interactive effect is always negative, ranging between -0.12 for Bulgaria and -0.63 for the Slovak Republic, and statistically significant in 5 of the 6 countries included in our sample. Moreover, for the 5 countries for which the interactive effect is statistically significant, we also find similar point estimates (ranging from -0.4 for Serbia and the Russian Federation to -0.63 for the Slovak Republic). Bulgaria is the only country for which the coefficient is not significant and, at -0.12, substantially lower (in absolute value) than in the other countries in our sample. This result is likely to be due to the fact that our PEP data set identifies a surprisingly small number of political connections for Bulgaria (only 36 firms are identified as politically connected). Hence, the statistically insignificant results are likely to be due to a mix of lack of power and to the presence of substantial measurement error.

The top right and bottom panels of Figure 1 show that the results are unchanged if we control for the interaction between cash flow
mode of transport, and streamlining operations. The RIC survey data shows that product innovation/improvement was accomplished by 5.6 percent of farm entrepreneurs and 11 percent of nonfarm entrepreneurs, whereas process innovation/improvement was accomplished by 3.7 percent of farm entrepreneurs and 8.4 percent of nonfarm entrepreneurs.

Second, entrepreneurs need training to obtain the skills and business management knowledge. The survey data indicate that obtaining skills was identified as an important motive for starting a business. However, only 19 percent of farm managers received training before starting a business, whereas 36 percent of nonfarm managers received training. Given the limited availability of skills training, it is essential that the specific skills are needed by local farm and nonfarm businesses.

Third, inputs and raw material should be procured locally whenever available to eliminate paying additional costs for transportation and intermediation for goods procured outside the area. Keeping cost of inputs low leaves more room for profits. If inputs are needed to modify or differentiate with existing products/services, these should be procured locally whenever possible. In Yemen, only 31 percent of farm entrepreneurs and 21 percent of nonfarm entrepreneurs procured inputs within their own community. In addition, 17 percent of farm entrepreneurs and 13 percent of nonfarm entrepreneurs procured inputs from the same and neighboring districts. There is a total of 52 percent of farm and 66 percent of nonfarm businesses that procure inputs outside of the district. Management services should provide guidelines to develop products or services using local inputs.

Fourth, managing expenses or wages is an important part of running a business. 27 percent of workers in farm enterprises are paid, whereas only 8.9 percent of workers are paid by nonfarm enterprises. Even if no formal wages are paid, entrepreneurs should make sure to set aside an amount equivalent to wage money to run their businesses. In this way, informal enterprises can prepare to grow and become successful, formal enterprises.

Fifth, accessing market information and knowledge by using telecommunication tools and technology is important. In Yemen, penetration
Lucas 1988; Fafchamps 1999; Foster and Rosenzweig 2001). Theoretically this can be modeled as subjective satisfaction that individuals receive from participation.<sup>8</sup> The satisfaction can stem from the

> 6 For example, Chandrasekhar, Kinnan and Larreguy (2011, 2012), using field experiments from Southern India find that limited commitment reduces transfers by 10 percent and hidden income by 40 percent.

> 7 See Kinnan (2012) for such exercise with data from rural Thailand.

> 8 In the context of limited commitment, we can re-write the right-hand side of Equation (3) as uA −A, where A captures such satisfaction (Fafchamps, 1999; Foster and Rosenzweig, 2001; De Weerdt and Fafchamps, 2011).

8
) entered in 2010 with a Customs Union tariff of zero, while the WTO bound rate is five percent.

> 17 The WTO (2011) Secretariat estimated that the un-weighted average bound tariffs of Russia will be 7.8 percent in 2020.  Our estimates are slightly higher for two reasons.  Due to data limitations, the WTO statistical office had to calculate the ad valorem equivalents of the specific tariffs at the eightdigit level, rather than at the ―ten digit‖ tariff line level of the tariff schedule of the Russian Federation. We had the more detailed ten digit data available, which allows more accurate calculations. See WTO (2007) for more details on their methodology for calculating the ad valorem equivalents of specific tariffs. Further, also due to data limitations, the WTO calculations ignored specific tariffs on a limited number of tariff lines where the specific tariffs and the import data were in different units, an omission which leads to a downward bias in the WTO estimates.  This problem arises in the case of motor vehicles. We obtained concordance from using information in other parts of the tariff classification that allowed the concordance (as explained above). Thus we estimated the tariff equivalents of the specific tariffs for all ten digit tariff lines.

> 18 These categories are 8707101000 (auto bodies), 8708291000 (parts and accessories) and 8708402001 (gear boxes).

18
||is...|green<br>occupati<br>ons|are<br>green by<br>GTI|green<br>occupati<br>ons|are non-<br>green by<br>GTI|green<br>occupati<br>ons|are<br>green by<br>GTI|green<br>occupati<br>ons|are non-<br>green by<br>GTI|
|---|---|---|---|---|---|---|---|---|---|
||GSI = 0|723|178|50|46|106|19|53|51|
||GSI < 0.1|512|167|261|246|89|17|70|66|
||GSI < 0.25|396|148|377|343|61|16|98|93|
|x|GSI < 0.5|284|124|489|431|42|13|117|109|
|nde|GSI < 0.75|207|101|566|485|31|11|128|118|
|GSI i|GSI < 1<br>GSI > 1|155|84|618|520|24|11|135|125|

Although the skills database may not be the most appropriate tool for identifying green occupations, it can still be very useful in understanding the skills (both green and non-green) that are required in green jobs identified through the task database. This skills profile can then be used to inform training programs. This is discussed further in application #2 in the next section.

# **4. Application of Green Task Intensity to Indonesia**

The GTI index at the 4-digit occupational level can then be applied to datasets from
Figure 2: A 310% increase in the number of taxpayers declaring foreign assets <!-- Start of picture text --> Number of<br>tax returns<br>(2015=100) 2009 2013-15 2016<br>Amnesty Amnesty Amnesty<br>400<br>Assets located<br>abroad<br>300<br>200<br>Assets located<br>in Argentina<br>100<br>0<br>2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021<br><!-- End of picture text --> _Notes:_ this figure plots the number of taxpayers declaring assets owned domestically and abroad. The series is indexed to equal 100 in 2015, before the 2016 amnesty. Neither the 2009 nor 2013–15 amnesties affected the number of people reporting assets to the tax authority. By contrast, there was a 310% increase in the number of taxpayers reporting to own foreign assets in 2016, which persisted even five years later, consistent with offshore evasion being the primary form of evasion. _Source:_ authors’ calculations using data from the AFIP statistical yearbooks.

25
the consumption distribution.<sup>16</sup> We scale this consumption value by the total population. Our benchmark budget is set to equal 5% of this total value, and we experiment with a higher budget of 10% of this figure as well.

Gains from targeting also vary with the choice of poverty line. In this study, we select as benchmark poverty line, that line which yields a 20% headcount rate in each of our three countries.<sup>17</sup> For comparison we experiment as well with a higher poverty line corresponding to a headcount rate of 40%.

# **IV. Results**

# _Optimal targeting_

Tables 2a-2c present the basic results from our simulations with the optimal targeting scheme in Ecuador, Madagascar and Cambodia. There are five main observations. First, in all three countries, the availability of disaggregated data on poverty can help to improve on a uniform lump-sum transfer across the entire population. Targeting transfers to poor localities, in accordance with the optimization scheme outlined above, yields lower values of the national FGT2 than when the budget is transferred as a uniform lump-sum transfer to the entire population. Second, the more disaggregated the poverty map, the greater the improvement over the uniform lump-sum transfer. Traditional household surveys are generally able, at best, to provide estimates of poverty at the first administrative level. The simulations here suggest that with estimates of poverty at the 2<sup>nd</sup> or 3<sup>rd</sup> administrative level, further improvements in terms of impact on the FGT2 with a given budget are attainable, and are non-negligible. Third,

> 16 The consumption distribution is constructed on the basis of the average, across _r_ replications, of household-level predicted percapita consumption in the population census.

> 17 Within each replication _r_ , the predicted per-capita consumption level associated with a 20% headcount rate is identified.  The average across the _r_ replications of this predicted consumption level is then taken as poverty
both the groups of affected and non-affected countries for the analysis among any pair or group of countries that appear in the sample subject to data availability; and (ii) because it allows for the researcher to explicitly control for all observable bilateral determinants of trade. Third, the approach is _comprehensive_ because, by construction, the border estimates will account for all trade costs that have not been captured explicitly by other control variables that are observable to the researcher. Note that, in addition to the border variables, our method allows for the inclusion of tariffs, FTAs, and all other variables for which data are available. Finally, the method is implemented within the standard empirical structural gravity equation and, therefore, the partial equilibrium estimates that it delivers can be integrated within a wide class of _new quantitative trade models_ , c.f., Arkolakis, Costinot and Rodriguez-Clare (2012); Costinot and Rodriguez-Clare (2014), or even complex computational general equilibrium models, such as the standard GTAP model. We demonstrate that in Section 4.2, where we obtain general equilibrium (GE) welfare effects corresponding to our partial equilibrium estimates.

To demonstrate the effectiveness of our methods we study the integration between the countries from the Central European Free Trade Agreement (CEFTA) and the European Union (EU). The integration of the CEFTA countries has been an extremely important goal for the governments of those nations but also from the perspective of the European Union, especially after the EU released a new strategy for the Western Balkans countries.<sup>3</sup> We offer further details on the background on CEFTA and EU accession process and status in Section 3.1. Data limitations have been the main obstacle to study the impact of the potential CEFTA integration with the EU. We overcome this challenge by being the first to utilize the new International Trade and Production Database for Estimation (ITPD-E), which was construced by Borchert et al. (2021 _a_ ) for the U.S. International Trade Commission.
results of estimation for tax outcomes using Arellano-Bond Dynamic Panel Estimation, allowing a full range of covariates to vary across our models. Participatory institutions remain statistically significant determinants of tax outcomes in these models, along with measures of local administrative capacity and local GDP per capita. Participatory institutions are positive determinants of tax outcomes. Councils are consistently connected to tax outcomes. Other variables we use in the matching exercises above are not statistically connected to tax outcomes in these models.

# **Conclusion**

Our results demonstrate broad connections between participatory institutions and local tax outcomes in Brazil. Policy management councils and participatory budgeting programs are both statistically significant determinants of a variety of tax measures after accounting for local economic and political conditions as well as proxies for the capacity to enforce tax regulations and facilitate tax collection. Participatory

> 10 Data available in separate appendix.

27
natural log of a country’s population size and government consumption as a share of GDP; the latter is the most widespread measure of government size (Adsera and Boix, 2002; Alesina and Wacziarg, 1998; Rodrik, 1998).

Tax compliance is also related to the government’s ability to effectively detect and punish tax avoiders, tax evaders, and tax arrears. Although an imperfect measure of states’ deterrent capacity, Afrobarometer includes two survey questions on perceptions of government enforcement and monitoring capacities. One question probes respondents on how often ordinary people who break the law go unpunished. The other probes respondents on how often officials who commit crimes go unpunished. This latter question is also a measure of perceived government fairness - the extent to which a government implements the law evenly across all social groups.

# **6.2.5 Procedural Justice**

I include two indicators of procedural justice. The first probes respondents on how often people are treated unequally under the law. The next taps citizens’ perceptions of the government’s treatment of their ethnic group. Specifically, respondents were asked how often their ethnic group is treated unfairly by their government.<sup>9</sup>

# **6.2.6 Donor and Non-State Actor Provision of Services**

I include a measure of who citizens believe is responsible for collecting income taxes. I expect citizens who perceive tax collection to be the responsibility of non-state actors to be less likely to be willing to pay taxes to the state’s tax department than citizens who perceive tax collection to be the responsibility of the state.

Perceptions of the effectiveness of donor and non-state actor provision of services are assessed using the following items. Respondents were probed on how much they believe the following non-state actors and donors do to help their country: the United Nations; international donors and NGOs; international businesses and investors; China; and the United States.

> 9 I also include Freedom House’s political liberties and civil rights ratings for the
labor-force status.

The sample of interest is given by two cohorts of individuals aged 14 by the time the law passed. The first cohort, which we consider the comparison group, includes individuals who turned 14 before the ban of December 1998. The second cohort, defined as the eligible group, consists of individuals who turned 14 after the change in the minimum legal age. These two cohorts are compared from ages 13 to 29.

> 18 We would like to thank an anonymous referee for pointing this out.

> 19 In a very short paper Piza and Souza (2016) combined RDD with difference-in-differences methods to control for cohort effects. The results are almost identical to the ones we found for incidence in paid work activities.

> 20 The survey documents provide the month (September), week (last of the month) and day (usually 27th) as the period of reference for the Brazilian PNAD.

14
Congress/Administration<br>|National application<br>(Passed/Introduced)|Enactment<br>rate|Local application<br>(Passed/Introduced)|Enactment<br>rate|
|---|---|---|---|---|
|8<sup>th</sup>/Aquino(1987-92)<br>|191/5,237|3.6%|809/30,183|2.7%|
|9<sup>th</sup>/Ramos(1993-95)<br>|156/3,184|4.9%|306/11,448|2.7%|
|10<sup>th</sup>/Ramos(1996-98)<br>|147/3,785|3.9%|393/6,766|5.8%|
|11<sup>th</sup>/Estrada(1998-2001)<br>|67/4,197|1.6%|348/8,738|4.9%|
|12<sup>th</sup>/Arroyo(2001-04)|89/2,920|3.0%|84/3,764|2.2%|
|Total|650/19,323|3.4%|1,940/60,899|3.2%|

Source: Kawanaka (2010) For comparison, legislative data for Mexico for 1991-97 show how a government run by a disciplined single party can produce results in stark contrast to the Philippines’ “low legislative productivity.” While the legislative “productivity” in Mexico declined in 1997 when the ruling party lost the majority in the

> 22 It is also asserted that a majority of legislators, especially the members of the Lower House, represent “traditional elite” interests and fail to champion progressive causes
APPENDIX Homer, Sidney (1967) _A History of Interest Rates_ . Sydney: Princeton University Press.

- Martin, Joseph G. (1886) _Martin’s Boston Stock Market: Eighty-eight Years from January 1, 1798 to January 1886_ . Boston.

- Morgan, Edward V. (1952). _Studies in British Financial Policy, 1914-1925_ . London: Macmillan.

- Neal, Larry (1990) _The Rise of Financial Capitalism: International Capital Markets in the Age of Reason._ Cambridge: Cambridge University Press.

NBER Macrohistory database.

- Rostow, Walt W. and Anna J. Schwartz (1953) _The Growth and Fluctuation of the British Economy 1790-1850_ , Oxford: Oxford U.P.

- Salomon Brothers (1995). _Analytical Record of Yields and Yield Spreads._ New York: Salomon Brothers.

- Schwert, William (1990) Indexes of United States Stock Prices from 1802 to 1987 _, Journal of Business_ , 63(3), 399-426

- Smith, K.C. and G.F Horne (1934) _An index number of securities: 1867-1914_ , London: Royal Economic Society.

- Thomas, Ryland and Nicholas Dimsdale (2017) _A Millennium of UK Data_ , Bank of England OBRA dataset

<u>Newspapers: The Economist, Financial Times, Hunt’s Merchants Magazine.</u> <u>Periodicals: Investors Monthly Manual, Banker’s Magazine, The Financial Review.</u>

- <u>Datasets: Eurostat, US Bureau of Labor Statistics, Federal Reserve Bank National Monetary Statistics,</u> Standard and Poors.

A3
grounds. The advantage of looking at measures such as import refusals is that they are implemented on a country- and product-specific basis, rather than being the same de jure for all exporters. Most standards and regulations are effectively most-favored nation (MFN) measures, which makes it difficult to identify their effects on exporters by exploiting cross-country variation in outcome measures, such as trade flows. Focusing on a country- and product-specific measure, such as import refusals, provides a potentially much richer source of data in which identification can be based on cross-country as well as cross-product and through-time variation.

In addition to exploiting new data on US import refusals, this paper makes a number of contributions to the existing literature. First, we provide some of the first explicit evidence of reputation effects in the enforcement of sanitary and phyto-sanitary (SPS) measures. Specifically, we show that even after controlling for the size of import flows and other factors, a history of compliance is associated with fewer current import refusals. Second, we show that it is not just reputation for a particular product that matters, but sector-wide reputation (i.e., there are cross-product spillovers in enforcement): a product tends to suffer from more import refusals if closely related products are also subject to refusals. Third, we investigate, and find evidence to support, the hypothesis that the reputation of neighboring countries also matters for SPS enforcement. Our results suggest that imports are more likely to be refused if the same product from neighboring countries has also been subject to refusals. We interpret this finding as evidence in favor of geographical spillovers in enforcement of refusals.

To our knowledge, the three reputation effects we are investigating have not been explicitly considered before in the literature. Baylis et al. (2009) use similar data to ours to analyze the determinants of US import refusals over the period 1998-2004. Their core hypotheses are that: countries with greater experience exporting food to the US experience fewer refusals (the “learning curve” effect); and import refusals are