rafmacalaba/data-use-mentions-extended huggingface dataset:
and doctor-driven demand at the margin between severe treatment and simple treatment. Within our model, doctor-driven demand at the margin of any versus no treatment is not possible because doctors cannot force patients to buy unwanted treatment (although doctor-driven demand inducement through influencing the patient’s beliefs, which is independent of the experimental interventions and therefore not part of our model, might still occur).

While our predictions work on different margins, finding evidence of demand driven by one side suggests that this side has a stronger preference for treatment than the other. For example, in the presence of patient-driven demand as in prediction (2), doctors have a weaker preference for simple treatment than patients, and so there would not be doctor-driven demand at this margin. Similarly, if there is doctor-driven demand for severe over simple treatment as in prediction (3), it implies that patients have a weaker preference for severe and so there would not be patient-driven demand for severe treatment.

All proofs are in Appendix A, where we also discuss additional results on prescribing simple treatment without using the voucher, and on doctors who are purely revenue motivated. We now turn to the experiment we designed to identify the role of patient and doctor preferences in driving demand for malaria treatment.

# **3 Experimental Design and Sample**

## **3.1 Experimental Design**

**Sampling Frame.** At the outset of our study, we obtained an administrative list of all CSComs in the city of Bamako and nearby Kati and Kalaban Coro in Koulikoro. After conducting a census of these clinics, we dropped clinics that had closed or were more than 15 kilometers away from Bamako, and removed 21 clinics that were working with a local NGO to offer subsidized, improved care to mothers and children. This yielded a final sample of 60 clinics. Four health workers at each clinic were invited to attend a refresher training that covered Mali’s official malaria guidelines and a hands-on training on how to administer an RDT. The training materials
of the coefficients assigned to municipalities that split during the period of analysis; (ii) other distortions in the application of the FPM allocation procedure, which is not audited.

# **2.2 Data on FPM transfers and population**

We use data on FPM transfers received by each municipality and the IBGE population estimates (the key variables of the FPM revenue-sharing mechanism). Data on FPM transfers for 2000-2006 are made available online by _Tesouro Nacional_ , while population estimates can be obtained in the IBGE website. Using these data, we apply the allocation rule described above to construct the “theoretical transfers” that each municipality should receive in each year. The amount of federal transfers that each municipality receives should be computed according to the IBGE population estimates sent to TCU in the previous year. Hence we use yearly population estimates for the period 1999-2005.

The third and fourth columns of Table 1 report summary statistics by population interval on actual and theoretical FPM transfers. We observe that average actual transfers within intervals are closely aligned with theoretical transfers. We also observe that municipalities in the proximity of the first four thresholds account for about 87% of the observations. Figure 1 plots actual and theoretical FPM transfers over the period 2000-2006 against the corresponding population estimates. The upper-left (lower-left) figure in this figure depicts effectively received (theoretical) transfers, while the seven vertical lines mark the position of the FPM population thresholds. The right panel displays similar associations, but where FPM transfers (actual or theoretical) are averaged over cells of 100 inhabitants, as well as the smoothed average of transfers (represented by the solid line) computed independently within each interval. All diagrams show clear discontinuities at the FPM thresholds. These are somewhat more noisy in the case of actual transfers, suggesting that there exist some cases where FPM transfers are imperfectly assigned to municipalities.<sup>7</sup>

> 7Theoretical transfers exhibit some heterogeneity within intervals due to the different share received by each state.

8
5 Price transmission to the domestic market has differed markedly from country to country. In the case of petroleum products, aside from price differences due to transportation costs and differences in fuel quality, international crude oil and petroleum product prices are broadly uniform across all regions, so that differences in government pricing policies account for much of the differences in end-user prices. The price differences are significant: a recent price survey showed that the retail prices of four petroleum products in 65 developing countries in January 2012 varied by two orders of magnitude, with the lowest prices found predictably mostly in major net oil exporting countries (Kojima 2012). As in the years immediately following rising oil prices in 2004, which saw suspension of pricing policies linked to world price movements (Baig et al. 2007), some governments responded to high oil prices in 2011 and 2012 by freezing prices.

Many interlinked developments have affected costs, availability, and prices paid for petroleum products in recent years:

- Recent high oil prices have exacerbated the poor financial states of the national oil companies in some countries with price subsidies, leading to the inability to procure petroleum products on time, acute fuel shortages, and high black market prices.

- Fuel price subsidies in the face of high world prices have increased incentives for diversion to black markets and smuggling to neighboring countries. Both smuggling and black marketing can push up domestic prices markedly above the official prices.

- Power shortages in a number of countries have increased demand for diesel for emergency power generation, causing diesel fuel shortages in some markets and higher diesel prices. A growing cause of power shortage is declining rainfall, leading to falling hydropower generation in East Africa and elsewhere.

- Piracy in the Gulf of Aden and the Indian Ocean has increased insurance costs, led to shipping delays, and at times caused fuel shortages in East Africa.

- The challenges to the authorities mounted by citizens across the Middle East and North Africa since 2010 have stalled and sometimes reversed petroleum price reforms in several countries against the backdrop of declining
- -37-

- (I) assets were not properly revalued by utilitles In many cases following currency devaluations and In line with local Inflation; thus, average costs at completlon are understated;

- (II) depreciation rates allowed by governments often are unreallstically low; therefore, capital costs are understated and the weight of capital cost In the total cost of electricity Is also understated; and

- (lil) fuel cost Increases In many countries were not fully passed on to power utilities In line with International markets (neither have fuel prices been reduced In many cases when Internal prices fell).

On the oiher hand, pronounced economies of scale are evident In some countries (Bangladesh, for example, where growth has been a rapid 12-15% p.a.) and generating units and transmisslon voltage levels have now reached the level where economies of scale are most pronounced. Because of rapid growth, the Increasing percentage of recent plant additions at lower unit cost Is now being reflected In the annual operating costs.

Available data on operating ratios (the ratio of operating costs to operating revenues), given In Sectlon 2.7, Indicates that revenues have not kept up with costs during the 1970s and 1980s. The overall trend In operating ratio shows an Increase on average of about one percentage point a year. This finding Is borne out by data from a limited number of projects which Indicate that, tariffs In real terms decreased over the project period by an average of 12% (using the wholesale price Index as a deflator). Average tariffs had decreased for 60% of utilities and Increased for only 25%. In most countries, tariffs also declined compared to the average cost of living (using the consumer price Index as a defletor) until the late 1970s, when It appears that tariffs started to Increase more than the consumer price Index. However, more data Is required before this finding can be verified.
the census includes a specific housing module that may include data on the number of housing units, housing type, housing quality, and tenure. Typically, housing income and expenditure, housing rents and prices are not collected as part of a national census in developing countries, making it unlikely that housing affordability analyses can be performed with the data.

**_Household Income and Expenditure Surveys (HIES)._** The general objective of an HIES is to identify household income and expenditure patterns on a comprehensive range of goods and services, including housing. It may also cover a substantive amount of information on housing characteristics such as the type and quality of housing, tenure, and access to services. Such surveys are used to estimate poverty and income distribution variables and are often conducted on a periodic basis (e.g., every 3-5 years).<sup>14</sup> Notably, they are carried out on a sampling basis, and hence are limited in level of representativeness.

There are difficulties in collecting data on both income and consumption/ expenditure in household surveys. Income is a sensitive issue for many respondents, and non-responses or misreporting of some income components may be significant. In developing countries, high informality and a prevalence of self-employment or own-account workers also make accurate income data collection very difficult. In fact, in many developing countries outside Latin America, these surveys are limited to household expenditure data.

> 14 The Living Standards Measurement Study (LSMS) is a HIES established by the World Bank in 1980 that offers data for a subset of Bank client countries.

12
Fernando, A. Nilesh, Niharika Sing, and Gabriel Tourek. 2023. “Hiring Frictions and the Promise of Online Job Portals: Evidence from India.” _American Economic Review: Insights_ 5(4): 546–62.

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Goos, Maarten
that women do not always collect a majority of the fuel with the findings that they spend more time collecting when availability decreases. Interestingly enough, in the studies reported here, collection by women seems to be more sensitive to changes in availability than male collection.

> 18 Van‘t Veld et al (p.4) also point out that in most studies that estimate the relationship between time spent collecting and forest degradation, the measures of fuelwood availability are indirect (eg time spent to collect 20 kg) and likely endogenous. Since unobservable, household-level characteristics that affect the total time spent in collection are likely to affect the time spent collecting a fixed quantity of firewood in the same direction, these measures of scarcity are likely endogenous, and possibly biased towards finding the result that these studies report (i.e., that time spent collecting increases with scarcity). In contrast, Van‘t Veld et al uses a direct physical measure of firewood availability, namely, the volume of biomass available per household in the village. Köhlin and Amacher (2005) use distance to forest measured in a GIS from village to a certain quality of forest (NDVI based).

13
recently introduced the first version of their Global Internal Displacement Database (GIDD) that allows users to explore, filter and sort IDMC’s data to produce graphs and tables, and export underlying data.<sup>102</sup> Such platforms need to incorporate safeguards to protect the privacy and confidentiality of individuals’ data.

UNHCR and Statistics Norway are currently leading an initiative to improve forced displacement statistics with the participation of national statistical agencies. This process began with the presentation of the “Report on Statistics on Refugees and IDPs” at the 46th session of the UN Statistical Commission in March 2015,<sup>103</sup> followed by an international conference in Turkey in October 2015.<sup>104</sup> The conference set in motion a process for national statistical agencies to collaborate to develop a set of recommendations that both countries and international organizations can use to improve data collection, reporting, data disaggregation, and overall quality, including the preparation of International Recommendations for Refugee Statistics (IRRS). Progress on this agenda was discussed at the 47<sup>th</sup> session of UNSD held in New York in March 2016, where it was recommended that the expert group should also include IDPs in its scope of work (UNSD 2016).<sup>105</sup> The current initiative is focused on refugees, asylum-seekers and IDPs but would ideally be extended to host communities and returnees. Assistance might be directed to one or more of the following areas:

- (a) Support for addressing the lack of data and statistics on affected host communities and returnees.

- (b) Support for improving the scope of data collection activities to include data requirements for long-term development planning, in particular the mainstreaming of data on forced displacement in household surveys; and

- (c) Support to test and mainstream the use of more innovative mechanisms for data collection, analysis and dissemination.

For such efforts to be successful and sustainable, it is important to ensure they are
Once the demographic groups are matched, we formally compare the convergence or divergence of pair-wise wage differentials. Tables 5 and 6 contain summary statistics for the matched differentials. Table 5 contains the mean of the absolute value of the pair-wise differential across all demographic groups for each country and each of three periods (2000-2004, 2005-2008, and 2009-2013). In general, the results suggest that there has been significant wage convergence. The mean wage differentials for all but four of the 16 countries fall over time. In many of the countries the differentials fall by more than 10 log points.

Two exceptions – Mexico and Peru – experience falling differentials over the first two periods but rising differentials in the third period. The other two exceptions – Argentina and Honduras exhibit other patterns (constant for Argentina and consistently rising for Honduras). Given that Honduras is a low-income country, the rising differentials suggest that Honduras has been falling behind, which is a result not immediately apparent in the GDP per capita data.

Table 6 contains the mean year-on-year changes in differentials for the same three periods. Negative values here indicate convergence while positive values indicate divergence. The results are not surprisingly quite consistent with those of Table 5. Most countries exhibit convergence over the sample periods, and the same exceptions emerge.

To provide additional context for the size of the differentials, Table 7 contains a comparison of wage differentials across Latin American countries and wage differentials between cities within Mexico and states within the United States. The comparison shows the expected result that wage differentials within countries are much smaller than those across countries.

To more formally evaluate some of the driving forces associated with the changes in differentials over time, we first estimate equation (6) using wages that are matched across country pairs by demographic group. If education quality differs across countries, then matching the cells 15 | P a g e
Nottingham Research Paper_ , (2011/16).

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Edmonds, E.V., Pavcnik, N. and Topalova, P., 2010. Trade adjustment and human capital investments: Evidence from Indian tariff reform. _American Economic Journal: Applied Economics_ , _2_ (4), pp.42-75.

Elekes, Z., Boschma, R. and Lengyel, B., 2019. Foreign-owned firms as agents of structural change in regions. _Regional Studies_ , _53_ (11), pp.1603-1613.

Erten, B. and Leight, J., 2021. Exporting out of agriculture: The impact of WTO accession on structural transformation in China. _Review of Economics and Statistics_ , _103_ (2), pp.364-380.

Erten, B., Leight, J. and Tregenna, F., 2019. Trade liberalization and local labor market adjustment in South Africa. _Journal of International Economics_ , _118_ , pp.448-467.

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results are robust to excluding highly autocratic and highly developed countries.

Our results are more favorable about MTEF e¤ectiveness than the conclusions of prior work. Bevan and Palomba (2000), La Houerou and Talierco (2002), Holmes and Evans (2003), and Oyugi (2008), based on case studies of about a dozen African countries, conclude that the budget process has generally not improved after the adoption of an MTEF, while McNab, Martinez-Vasquez, and Boex (2000) and Oxford Policy Management (2000) raise questions of adequate implementation. However, Gleich (2003) and Ylaoutinen (2004) ...nd that MTEFs in Central and Eastern Europe alleviated the de...cits and debts that emerged in the second half of the 1990s. Wescott (2008) and Filc and Scartascini (2010), using data from Central and Latin America, found mixed results and emphasized the importance of piloting MTEFs in areas where they are likely to deliver the largest payo¤.<sup>6</sup>

> 5This taxonomy follows World Bank (2012) and borrows from Castro and Dorotinsky (2008) with the nesting concept as an added innovation.

> 6Drawing on extensive operational experience with MTEF implementation in developing countries,

4
. This effect is robust to controlling for lagged light growth in column (2). In columns (4) and (5) we show that these reductions in light per capita growth are composed by two factors; light growth falls dramatically and this is partially offset by a negative effect on population growth. However, column (3) also shows that there is some evidence for negative spill-overs from conflict at the country level. Conflict in other groups in the same country lower light per capita growth for other groups in the same country by 0.7 percentage points.

Again we interpret these estimates in terms of GDP growth following Henderson et al. (2012). If a decrease of night light by 1 percent implies a decrease of GDP of about 0.25 percent, then our result from column (1) in Table 2 can be translated into a reduction of GDP growth of about 1 _._ 8 percentage points.

Overall this suggests that local effects are important and comparatively large in comparison to spill-overs. This is important for our discussion as they define the challenge that the country faces in the recovery from civil wars. Local effects of violence imply that civil conflict leaves a legacy of regional economic divergence. Another way to understand the size of this relative decline is to perform a second simulation of the GDP loss that focuses on group-level economic performance, following the same steps described above. Figure 4 displays the distribution of conflict lengths in the sample for which we also have the night light per capita data (years 1992-2012). We estimated 13
asking about HIV status and whether the woman is taking any drugs. For the indicators representing non‐clinical quality of care, we do not find any correlation with wealth.

# 5. Price

A wealth‐quality gradient naturally gives rise to the question of a price‐quality gradient, and to the question of whether quality gaps mostly exist because wealthier women can pay or are more willing to pay for higher quality of care (and additional services). This section analyzes the exit interview data to explore the correlations between the price women reported paying and the quality of their consultation and between the price and wealth of users.

Table 6, columns 1 to 3, presents the results of regressions of the total price paid for the consultation on the quality index created from the exit interview data. Overall, there is a strong relationship between quality and price: each percent of content of care is associated with a price increase of CDF 28. Alternatively, each additional item performed is associated with an average price increase of CDF 219 (15 percent of the median price of CDF 1,500). The coefficient is statistically significant at the 99 percent level. The relationship remains statistically significant at least at the 95 percent level even after accounting for health zone and facility fixed effects. The size of the effect reduces to CDF 23 when health zone dummies are included and to CDF 18 when facility dummies are included.

Consistent with the positive correlations of quality with wealth and price, there is a positive correlation between wealth and the price paid for a first consultation. The regression estimates show that a one standard deviation increase in wealth is associated with an increase of CDF 325 (about 22 percent of the median price) in the price paid for the consultation (table 6, column 4). This effect decreases to CDF 207 (about 14 percent of the median price) when health zone dummies are included in the regression, but it remains statistically significant at the 99 percent level (column 5).

Sixty‐one percent
trast, firms operating in the Metals sector tend to restructure less on all three measures. The patterns for other sectors are less pronounced, and frequently the coefficients change signs. An exception is Chemicals, where the coefficients are always negative, albeit insignificant. The sectoral coefficients suggest a pattern often reported in other firn-level studies on transition - restructuring is less rapid in the heavy industry sectors.

# _5._ Conclusions

Using a stratified random sample of insider-controlled firms in Georgia and Moldova, we uncover an interesting stylized fact: restructuring is more rapid in enterprises bought-out by their managers as compared to enterprises privatized through voucher auctions where the control (direct or indirect) remains with their managers. We suggest that this may be due to the perception on the part of managers that ownership acquired through voucher privatization is a windfall gain. Further research is, however, necessary to help explain these findings and provide a consistent theoretical framework.

14