rafmacalaba/data-use-mentions-extended huggingface dataset:
The other variable we use from the financial accounts database is the number of employees reported by firms. We calculate mean employment in new firms. And we also calculate the oneyear employment growth rate. Both variables are first calculated at the firm level and the average across court region-years cells.

Finally, we calculate the one- and two-year survival rates of new firms. Here, we first construct an indicator for whether a firm appears in the database again one or two years later and we then average these indicator variables across court region-years cells.

The distrust data are coded from responses in the 2006 Life in Transition Survey conducted by the European Bank for Reconstruction and Development (EBRD), in collaboration with the World Bank (see Synovate, 2006, for a description of the survey). This survey asks, “To what extent do you trust courts?” Answers are coded as follows: (1) complete distrust; (2) some distrust; (3) neither trust nor distrust; (4) some trust; (5) complete trust; (6) difficult to say. As our measure of distrust, we use the fraction of respondents choosing “(1) complete distrust” or “(2) some distrust”.

Table 4 shows the number of respondents in each court region and the fraction of these respondents that report complete or some distrust in courts. The survey does not include any respondents in the court regions of Sremska Mitrovica and Čačak, which is why these regions are dropped out of our analysis. For two regions, Leskovac and Užice, the survey only includes 20 respondents each and the distrust numbers fall outside the range of those in other courts. We thus believe that 20 respondents are too few to obtain a reliable measure of distrust and drop these two court regions from the analysis. We are left with 12 court regions for which we have new firm and distrust data. Table 5 shows summary statistics for all variables used in the analysis.

9
around the developing world? _World Bank Research Observer_ , 29:48–82.

- McKenzie, D. and Woodruff, C. (2017). Business practices in small firms in developing countries. _Management Science_ , 63:2967–81.

- McKenzie, D., Woodruff, C., Bjorvatn, K., Bruhn, M., Cai, J., González-Uribe, J., Quinn, S., Sonobe, T., and Valdivia, M. (2021). Training entrepreneurs. _VoxDevLit_ , 1(2).

- Reich, J. and Ruipérez-Valiente, J. A. (2019). The MOOC pivot. _Science_ , 363:130–131.

- Rivard, R. (2013). Measuring the MOOC dropout rate. _Inside Higher Ed_ , March 8.

- Sheridan, M. B. (2021). Mexico’s pandemic policy: No police. no curfews. no fines. no regrets. _Washington Post_ .

- Van Lieshout, S. and Mehtha, P. (2017). The next 15 million: Start and improve your business global tracer study 2011–2015. _International Labour Organization_ .

14
# References

- Akbulut-Yuksel, M. (2017). War during childhood: The long run eects of warfare on health. Journal of health economics, 53:117130.

- Akresh, R., Bhalotra, S., Leone, M., and Osili, U. O. (2012). War and stature: growing up during the nigerian civil war. American Economic Review, 102(3):27377.

- Akresh, R., Bhalotra, S., Leone, M., and Osili, U. O. (2018). First and second generation impacts of the biafran war. NBER Working Paper 23721, National Bureau of Economic Research.

- Akresh, R., Caruso, G. D., and Thirumurthy, H. (2014). Medium-term health impacts of shocks experienced in utero and after birth: Evidence from detailed geographic information on war exposure. NBER Working Paper 20763, National Bureau of Economic Research.

- Akresh, R. and De Walque, D. (2008). Armed conict and schooling: Evidence from the 1994 Rwandan genocide. The World Bank.

- Almond, D. (2006). Is the 1918 inuenza pandemic over? long-term eects of in utero inuenza exposure in the post-1940 us population. Journal of political Economy, 114(4):672712.

- Almond, D. and Currie, J. (2011). Killing me softly: The fetal origins hypothesis. Journal of economic perspectives, 25(3):15372.

- Almond, D., Currie, J., and Herrmann, M. (2012). From infant to mother: Early disease environment and future maternal health. Labour Economics, 19(4):475483.

- Bargain, O. and Zeidan, J. (2017). Stature, skills and adult life outcomes: Evidence from indonesia. The Journal of Development Studies,
percent of Mexico's cultivated land required regular irrigation. Because of the high cost of irrigation, the government has emphasized expanding production on existing farmland rather than expanding the area under irrigation. Although corn is grown on almost half of Mexico's cropland, the country became a net importer of grain during the 1970s.

Agricultural practices in Mexico range from traditional techniques, such as the slash-and-burn cultivation of indigenous plants for family subsistence, to the use of advanced technology and marketing expertise in large-scale, capital-intensive export agriculture. Government extension programs have fostered the wider use of machinery, fertilizers, and soil conservation techniques. These diverse agricultural practices call for a diverse rural labor market.

# **The Labor Force**

The analysis now turns to an examination of data on economic activity and occupation in order to obtain a “snapshot” overview of the farm and nonfarm sector in rural Mexico during the 1990s and early 2000s. The analyses are based on ENE survey data.

The share of the workforce in the formal sector experienced a large long-run decline from the late 1980s to the mid-1990s, followed by a partial recovery in the late 1990s, while the 1994/95 crisis and the 2000/02 period of stagnation tended to increase both unemployment and informality. Since 1995, Mexico's rural workforce has decreased by 0.5 million reaching around 9.3 million in 2003; of these 9.2 were employed, down by 0.3 million since 1995 (see Appendix A). The main explanation is migration of the younger age cohorts to urban areas or abroad. This is causing an increase in the average age of the work force (Table 2.2).<sup>3</sup> Women, according to data, comprise a relatively small part of Mexico's rural workforce; only 27.0 percent are women (calculations based on ENE 2003 survey). However, this estimation is likely to under-represent the female share of the work force. The way the question is phrased
Policy Research Working Paper 9396

# **Abstract**

This paper uses Multiple Indicator Cluster Surveys data from the Republic of Congo and São Tomé and Príncipe to study the relationships between child stature, mother’s years of education, and indicators of early childhood development. The relationships are contrasted between two empirical approaches: the conventional approach whereby control variables are selected in an ad-hoc manner and the double machine-learning approach that employs datadriven methods to select controls from a much wider set of variables. Overall, the findings based on the preferable double machine-learning approach differ across the two countries depending on the measures of early childhood development and child stature (height-for-age Z-score and stunting) used in the analysis. Double machine-learning estimates for the Republic of Congo suggest that heightfor-age Z-score and stunting have a direct causal effect on early childhood development. In contrast, for São Tomé and Príncipe, no relationship is found. Thus, country-specific policy advice based on the relationships observed from data in other countries may be quite risky, if not misleading. Double machine-learning provides a practical and feasible approach to reducing threats to internal validity to derive robust inferences based on observational data for evidence-based policy advice.

This paper is a product of the Poverty and Equity Global Practice. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contacted at eskoufias@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the
*|2.3***|
|(Percentage points of GDP per year)|[1.1, 3.7]|[2.6, 6.4]|[1.0, 2.9]|[1.3, 5.3]|[4.4, 8.4]|[1.2, 3.9]|

Note: Table shows medians, as well as interquartile ranges (i.e., two numbers in brackets), based on 515 private debt booms, of which 100 debt booms are in advanced economies and 415 are in EMDEs. Amplitude is the trough-to-peak change in the private debt-to-GDP ratio during a private debt boom. Speed is the ratio of the amplitude to the duration. *, **, and *** denote that medians between advanced economies and EMDEs in all debt booms, and between completed and ongoing booms or between completed debt booms with and without crises in respective country groups, are statistically significantly different at the 10 percent, 5 percent, and 1 percent levels, respectively.

34
Jin et al. (2011); g. data from EB (2009), but because North China is suitable for both sweet sorghum and sweet potato, unused land here is assumed to be divided evenly between both crops; h. data from Shi (2011);

# **3.1.2 Supply cost**

The production of ethanol from starch and sugar crops is a relative mature technology, widely employed at commercial scale. The economic viability of these processes largely depends upon the price of feedstocks as feedstock accounts for over 50% of the total cost (see Table 4). Although the production costs of fuel ethanol are higher, they have certain cost advantage 7
able to signal their good intentions to international donors and thereby generate further external support.

# **6. CONCLUSIONS**

**Our report highlights the strategic economic importance of the Kinshasa-Brazzaville conurbation, both through its sheer population size and through its position as the regional transport hub.** We have provided evidence to support the view of the river crossing between the two capitals as a major bottleneck: traffic volumes are small, transport costs are high, administrative obstacles abound, and cross-border differentials in retail prices are significant.

**We find bilateral official trade volumes between DRC and RC to be derisorily small.** Formal trade between DRC and RC is lower now than in the 1980s. Recorded transit trade volumes are small too, mainly from Matadi to Brazzaville. However, we have also found evidence of significant informal trading activity. It is impossible to accurately quantify the volume such trade.

**We observe statistically significant price differences between markets in Kinshasa and Brazzaville.** While we observe no significant price differentials within cities, shipping goods across the river appears to systematically increase retail prices in both cities. This points toward unexploited arbitrage opportunities.

**We also find substantial potential for cross-border trade in locally produced goods** , based on our company survey. We estimate that a general reduction in general trade costs would stimulate exports even more than imports, and thus improve the trade balances of DRC and RC. Trade

36
# **_Abstract_**

Massive privatizations of housing in Europe and Central Asia transition countries have significantly reduced rental tenure choice, threatening to impede residential mobility. Policymakers are intensifying their search for adequate policy responses aimed at broadening tenure choice for more household categories through effective rental housing alternatives in the social and private sectors. While the social alternative requires substantial and well-balanced subsidies, the private alternative will not grow unless rent, management, and tax reforms are boldly implemented and housing privatization truly completed.

The primary authors of this report are _Hans-Joachim Dübel_ , _W. Jan Brzeski (Team Leader)_ , and _Ellen Hamilton_ , Infrastructure Department, Europe and Central Asia Region, World Bank.

# **Acronyms and Abbreviations**

|ECA|Europe and Central Asia|
|---|---|
|EU|European Union|
|GDP|Gross Domestic Product|
|HOA|Homeowners Association|
|HBS|Household Budget Surveys|
|HLM|Habitation à Loyer Modéré (French social housing system)|
|LSMS|Living Standards Measurement Surveys|
|M-F|Multi-family (building)|
|PPP|Public-Private Partnership|
|TBS|Towarzystwo Budownictwa Spolecznego (Polish social housing system)|
|USAID|United States Agency for International Development|
|VAT|Value Added Tax|
_and registration:_** at present, there is little or no coordination between the maintenance of land records, which is the responsibility of revenue inspectors and tehsildars; and land registration, which is the responsibility of sub-registrars. Measures to coordinate and integrate these two services and enhance their efficiency through computerization promise to go a long way towards stimulating the land market. Of utmost importance is to combine registration and mutation processes, and provide a 'single-window' facility for the registration of sale deeds, correction of the record of rights in land, and issue of land title. Land records and the registration administration system should integrated through a computer network to facilitate information exchange for this single-window approach. This should help to reduce the currently high, informal transaction costs to individuals in the land market. Existing registration fees and stamp duties should also be reassessed, as it is possible that their reduction, hand in hand with proper valuation, could lead to a net increase in state revenue.

- **_Survey and_** _settlement_ **_operations:_** in the context of the computerization of land records, the continuing relevance of survey and settlement operations is questionable. There is substantial evidence that survey and settlement operations discriminate systematically against the rural poor and socially excluded, whose interests would be far better served by an efficient service for registration of land sales, mutation and issuance of title.

- _Simplification_ **_and_** _transparency_ **_in_** _land_ **_administration:_** Many of the individual stages involved in land administration currently operate to the disadvantage of the rural poor and socially excluded groups. The complexity of the existing legal framework and a perverse incentive structure provides considerable scope for rent-seeking by the lower-level government officers with whom landholders come into direct contact, while village elites are better able to manipulate the system to their own

62
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collected for up to three different units at the item-vendor level, with the units determined by the vendor based on the most common units of trade. This was done for three vendors per market, with 1-3 visits per vendor. The team repeated the exercise at multiple markets if there was more than one in a village.

While writing this paper we collected two types of additional data. The first came from informal interviews and focus groups in Tanzania, during the years 2012-2015. We conducted 10 interviews with consumers or shopkeepers, and held three informal focus groups, each with 5-6 people. These discussions helped us identify hypotheses for why households might forego bulk discounts, and provided relevant anecdotes about consumer behavior. Our second data collection effort was an on-line survey conducted in June-July 2016. This short survey was sent to a group of Tanzanians with extensive knowledge of household decisionmaking around economic issues. We describe this survey in the relevant subsection of Section 5.

# **4 Quantifying the value of forgone consumption**

In this section we estimate the value of consumption that households forego by not buying in bulk. The first subsection describes the bulk discounts and the estimated expenditure schedules. The next subsection uses the estimated expenditure schedules to provide estimates of the financial losses and quantity losses, and examines heterogeneity.

## **Bulk discounts in the data**

While our main analysis uses focal points in the diary data to estimate price schedules (as described in Section 2), it is easy to see that bulk discounts are present in simple linear models. We first estimate such regressions using the market price survey data, which was collected in tandem to the diaries. Columns 1–3 of Table 3 show slope coefficients from itemspecific, transaction-level regressions, with log unit price as the dependent variable and log quantity as the independent variable. These regressions include district (column 1), village (column 2), or vendor (column 3) fixed effects, with standard errors clustered at the village 13
with shared kitchen and electrical meter. After matching with An Thinh’s customer records, we verified that 267 households or 16 percent of the population were unconnected to piped water as of July 2015, at which time we offered them free connections (i.e., waived the connection fee). While almost all of these 267 households eventually did connect, only about half did so in time for the baseline survey (see below).

**Pre-experiment price linearization** Prior to the price randomization, starting in July 2015, we “linearized” the water tariff schedule once and for all to avoid having to deal with self-selection of households onto price blocks (as in, e.g., Reiss and White 2005, McRae 2015, and Szab ́o 2015). At the time, the official schedule had three blocks: for consumption below 10 m<sup>3</sup> , the price was VND5,300 per m<sup>3</sup> , increased to VND7,200 per m<sup>3</sup> for any consumption above 10 m<sup>3</sup> and below 20 m<sup>3</sup> , and again to VND8,000 per m<sup>3</sup> for any higher consumption.<sup>7</sup> With the linearization, every household in the three villages was charged a uniform VND5,300 per m<sup>3</sup> price and the water utility was reimbursed for the revenue loss relative to the block-price schedule. This linearized price schedule prevailed throughout the experiment, with randomized discounts applied at various points as described below. In June 2017, however, provincial authorities raised the water price to a uniform VND7,950 per m<sup>3</sup> , a 50 percent increase, which we passed on to all consumers and which was broadly announced by An Thinh.

**Baseline data collection*
less weight to individual defaulters (like Russia) or episodes that were particularly turbulent (like the Great Depression). We also disregard the (lower) returns of sub-sovereign bonds. Instead, we focus on external sovereign bonds and include all episodes for which price quotations exist, including spells with very high returns in the aftermath of wars and crises, as well as during the boom decades of the 1840s, 1860s, 1880s, 1940s, 1950s, 1990s, and the 2000s (many of these were not included in previous studies).

A necessary ingredient for the calculation of ex-post returns is to account for losses due to default or restructuring, which requires data on missed payments and recurring debt exchanges. The research on sovereign haircuts has been largely confined to the modern period (post-1970s), and this sample is dominated by defaults and haircuts on sovereign syndicated bank loans, plus about 20 recent restructurings of sovereign bonds. In pioneering work, Sturzenegger and Zettelmeyer (2006, 2008) compute investor losses in eight sovereign bond restructurings since 1998, finding haircuts in the range of 13%-73%. Using a similar approach, Cruces and Trebesch (2013), whose study encompasses 187 restructuring events of sovereign bonds and syndicated bank loans since 1978, calculate an average haircut of 38%. Moody’s (2012), Asonuma, Niepelt, and Ranciere (2017), and Fang, Schumacher, and Trebesch

> 18 Broner, Lorenzoni, and Schmukler (2013) use Bloomberg and JP Morgan EMBI data for eight countries between 1993 and 2003, covering two default spells. Borri and Verdelhan (2015) use EMBI aggregate indices for 41 emerging market countries over 1995-2011, including eight default events on sovereign bonds.

7
Because this paper focuses on the demand side, we assess a broad array of variables that influence the demands for national statistics and have dropped the SPI’s first pillar – Data Use from our analysis, given filling data gaps in the Data Use pillar underlying the SPI remains a work in progress.<sup>4</sup> For the remainder of the paper, we use this modified SPI comprised of the four remaining pillars that represent the supply-side activities related to NSS performance.

# **3. What the SPI Reveals**

One key improvement of the SPI over the SCBI is its ability to measure statistical capacity through a robust, internally consistent index score for any country in the world. For the first time, we can compare the strengths of well-regarded NSSs with the less-developed institutions in lower- and middle-income countries. With SPI scores available for the full spectrum of countries, we have a measure of the difference between low- and high-income countries in terms of their capability to produce and disseminate statistical products and services.

Figure 1 shows the histogram and nonparametric estimation of the four-pillar SPI’s density function for the sample of 215 countries. The distribution appears to be bimodal, with a group of high-capacity countries with SPIs falling in the range from 0.8 to 0.9. The remaining countries center on an SPI of 0.5. Few countries score between 0.62 and 0.75, suggesting that a discrete step may be necessary to reach the group of high-performing countries.

A cluster analysis of the four-pillar SPI scores indicates the presence of a stable cluster of 26 highcapacity counties with a mean SPI of 0.84 and another stable cluster of 30 low-performing counties with a mean SPI of 0.14. No clusters are identified in the region of 0.64–0.79, even when the number of clusters reaches 15.<sup>5</sup> This “statistical performance gap” is analogous to the concept of the middle-income trap in the development economics