rafmacalaba/datause-encoder-data huggingface dataset:
show that a transfer recipient’s _perception_ of a donor’s wealth affects the value of the transfer between them, conditional on the donor’s actual wealth. Social pressure is clearly a factor in determining patterns of redistribution, and buying small quantities may be a useful way to deter requests from one’s social network.

A particular feature of the data allows us to estimate a proxy for household-specific social tax rates and test whether buying in bulk is associated with higher social taxes. In addition to recording purchases, diary keepers also recorded the item description, quantity, unit, and estimated value of items sold or given away.<sup>21</sup> These disposal events are recorded on the household’s daily transaction log, in the same manner as the purchases. To estimate a proxy for the household-level social tax rate, we sum the total value of items outgoing over the two-week study period, and divide by the total value of items incoming. Because we are calculating a proxy for a household-level variable, we use every row of the transaction diaries for this calculation, not just the rows associated with the 19 items that are the focus of the rest of this paper. To our knowledge, this is the first accounting measure of social taxes—one based on diary records from a large sample of households—in the literature.

Table 10 shows descriptive statistics for the social tax estimates. The uppermost panel shows the value of resources outgoing in the form of sales or gifts, divided into subcategories. The most important group is “meals and snacks,” which accounts for 40% of outgoing resource flows. The largest share of entries under “meals and snacks” are those for “full meals”—guests at the household table (see Appendix section S6 for details about the item categorization). The lower part of the table shows the value of incoming resources. The mean tax rate is 14.4% (s.d. = 26.5%).<sup>22</sup> It is clear both that redistribution is widespread, and that there is significant heterogeneity between households in the implied social tax rate.

How does the existence of social taxes affect a household’s incentives to purchase in

> 21It is not possible to determine whether an item was sold or given away. This could be problematic if many households re-sell consumer items. That does not appear to be the case. Other households in the study villages—not the households that filled out consumption diaries—were randomly selected to participate in a survey experiment dealing with measurement of labor supply. These households were able to indicate their sectors of work, with varying degrees of detail. The share of respondents that indicated “buying and selling” as their primary sector of work ranged from 5–8% across survey modules. Hence, even if every purchase made by such households was for the purpose of re-selling—which is surely not the case—for the vast majority of disposal events it is still reasonable to assume that items “sold or given away” are in fact “given away.”

> 22A small number of estimated tax rates are over 100%. All results are robust to winsorizing by replacing rates above 60% with 60%.

28
_7_ _Fiscal Crisis in Central Europe_ <!-- Start of picture text --> Flgure 2.1 Figure 22<br>Fiscal Flows In olcdeed Eastem Eurpean counblec. 1 356. Fisca' vows In EC couni,tl 1965.<br>(pefeentag oI GOPF Lefcentage af GOP!<br>' :- .ESWfS- ElNtURPUSES<br>Th 1asr To guvn eament Crvnsipaeecoe Sat taxsp fruce m p bt<br>qEIRN.qQNMEhr<br>_ _ ' 0dX 1D __ _ Alel etCj# f<br>:F,:<br>| ~~~~~Coo,9t1e T's WI* i |8 8<br><!-- End of picture text -->

The main sources of guvermunent revenues<sup>in planned economies are</sup><sup>**profit**taxes from public</sup> enterprises, sales (turnover) tax and social<sup>security contributions.</sup> 4 In market economies, sales taxes and social security contributions<sup>are also significant, whereas profit taxes are considerably</sup> less important (in relative terms) and are<sup>replaced, as main source of revenues, by the personal</sup> income tax. Most of the tax flows are<sup>paid for or intermediated by the SOE sector in socialist</sup> economies, if nothirg else because the size<sup>of the private sector - although changing across time</sup> and countries - is rather small, never<sup>having accounted for more than about 25 percent of GDP</sup> (or even being very close to zero as in<sup>Czechoslovakia).</sup> 5 On the expenditure side, socialist economies<sup>devote a disproportionate percentage of the</sup> government budget to consumer and<sup>producer subsidies. The latter ones, combined with large</sup> profit taxes, result in a massive inter-enterprise<sup>cross-subsidization -mediated through the</sup>

> On govemment revenues in socialist economies,<sup>see Tanzi</sup><sup>**(1991)**and</sup><sup>**Gandhi and**Mihaliek (1992).</sup>

> **See** for example Komai (1992, Table<sup>**5.1).**</sup>
Lopez, Ricardo A. (2005), “Trade and Growth: Reconciling the Macroeconomic and Microeconomic Evidence,” _Journal of Economic Surveys_ , 19(4): 623-648.

Matsuura, K. & Willmott, C. J. (2012a). Terrestrial Air Temperature: 1900-2010 Gridded Monthly Time Series (V 3.01), ~ <u>http://climate.geog.udel.edu/ climate/html_pages/Global2011/README.GlobalTsT2011.html</u> Matsuura, K. & Willmott, C. J. (2012b). Terrestrial Precipitation: 1900-2010 Gridded Monthly Time Series (V 3.01), ~ <u>http://climate.geog.udel.edu/ climate/html_pages/Global2011/README.GlobalTsP2011.html</u> McKee, Thomas B., Nolan J. Doesken, and John Kleist. (1993), “The relationship of drought frequency and duration to time scales.” _Proceedings of the 8th Conference on Applied Climatology_ . Vol. 17. No. 22. Boston, MA: American Meteorological Society.

Moyo, Busani (2011), “Do Water Cuts Affect Productivity? Case Study of African Manufacturing Firms,” _Water SA_ 37(3): 349-356 Neves, Josemir (2015), “Package ‘SPI’” February 2015. URL: https://cran.rproject.org/web/packages/spi/spi.pdf Olley, G. Steven and Ariel Pakes (1996), “The Dynamics of Productivity in the Telecommunications Equipment Industry” _Econometrica_ 64(5): 1263-1297.

Pless, Jacquelyn, and Harrison Fell (2017), “Bribes, Bureaucracies, and Blackouts: Towards Understanding How Corruption at the Firm Level Impacts Electricity Reliability,” _Resource and Energy Economics_ 47: 36-55.

Roller, Lars-Hendrik and Leonard Waverman (2001), “Telecommunications Infrastructure and Economic Development: A Simultaneous Approach.” _American Economic Review_ , American Economic Association, 91(4): 909–23.

Shioji, Etsuro (2001), “Public Capital and Economic Growth: A Convergence Approach.” _Journal of Economic Growth_ 6(3): 205–27.

Tybout, James R. (2000), “Manufacturing Firms in Developing Countries: How Well Do They Do, and Why?” _Journal of Economic Literature_ 38(1): 11-44.

Wang, Hung-Jen, and Peter Schmidt (2002), “One-Step and Two-Step Estimation of the Effects of Exogenous Variables on Technical Efficiency Levels” _Journal of Productivity Analysis_ 18: 129-144.

World Bank (1994), World Development Report 1994: Infrastructure for Development. Oxford: Oxford University Press.

World Bank (2016), High and Dry: Climate Change, Water, and the Economy. Washington DC: World Bank 20
**Table 1: UK NEST Building Block Fund Range**

|**Fund**|**Investment Approach**|**Benchmark/ Target**|
|---|---|---|
|**Global Equity Fund**|**Passive**|**FTSE All World Developed**<br>**Index**|
|**UK Gilts Fund**|**Passive**|**FTSE Actuaries All Stocks**|
|**UK Index Linked Gilts Fund**|**Passive**|**FTSE Actuaries Index Linked**<br>**Gilts over 5 years**|
|**Low-risk Liquidity Fund**|**Active**|**7-day LIBID**|
|**Diversified Beta Fund**|**Mostly Passive**|**UK Risk Free Rate +2%-+4%**|
|**F&C Stewardship**|**Active**|**MSCI World**|
|**HSBC Life Amanah Pension**<br>**Fund**|**Passive**|**Dow Jones Islamic Titans 100**|
|**Sterling Corporate Bonds**|**Active**|**GBP iBoxx**|
|**UK Direct Commercial**<br>**Property**|**Active**|**IPD**|
|**Global REITS**|**Passive**|**FTSE/NAREIT Index**|

Source: NEST

# **Regulatory Benchmarks**

53. Pension regulators in various countries are also moving towards using a benchmarking approach to monitor and measure the performance of the pension industry as a whole. This approach is being considered by several regulators which oversee DC pension systems managed by competitive private pension funds.

# **<u>Latin America</u>**

54. Various regulators across Latin America have been researching the benchmarking approach. The multifond system in place across much of the region, while an improvement on the ‘blunt’ tool of asset class restrictions, is still designed to protect against short-term volatility rather than working towards a longer-term pension income goal. Likewise, the VaR system in Mexico has proven to introduce short-term distortions into the system and is no longer used.

55. In Chile, the regulator has been working on and modeling the concept of pension risk, analyzing the probability density function of replacement rates.<sup>41</sup> Since 2005 the pension supervisor in

> 41 See (Berstein et al 2013).

16
O.A.M.D.G.

USD per month. Both measures are distributed normally around their means, but the savings from income (1) with a higher variation, as can be expected. Note that negative savings rates are by no means unusual for the income strata we are studying. Poterba (1994) reports negative savings rates in the lowest income quintiles of Germany and Canada.

|Savings statistics|Savings (1) in COP|Savings (2) in COP|
|---|---|---|
|Mean|306,708|-213,658|
|Standard Deviation|1,386,227|248,167|

# Data Table 3: Some basic savings statistics

_Note: Savings (1) are calculated as head monthly salary + sum of monthly payoffs of the assets in the household’s portfolio – total consumption. Savings (2) are calculated as head monthly salary – total monthly expenditure (not including household self production for food), for waged households only._ Households that accumulate savings rarely store the money in a bank (only 232 households report saving in a bank), but invest the money immediately in consumer durables and other assets. When relating household savings to the age of the household head, we observe rising savings with age.

<!-- Start of picture text --> Figure 1:<br>Savings and<br>age of<br>household<br>head<br>10 20 30 40 50 60 70 80 90<br>age of household head<br>1500000<br>1000000<br>500000<br>mean household savings<br>0<br>-500000<br><!-- End of picture text -->
which happen to correlate with exposure to US and retaliatory tariffs. We attempt to address this concern by running a placebo test on the pre-trade war period. To do this, we keep only the 2017 data and lag the 2018 tariff exposures by one year to see whether job postings respond to these changes in 2017 when there were in fact no tariff changes. If the baseline results capture medium-term trends that are not related to tariff exposure then we would expect to see similar results in this placebo test. Insignificant results would support the claim that it is in fact the tariff changes that matter.<sup>20</sup> Table 9 in the Appendix presents the results of this placebo test. The resulting coefficients are not significant across all specifications, suggesting that this impact was not observed prior to the start of the trade war.

# **6.2 Alternative tariff exposure measures**

The particular form of the exposure measures used in this paper follows examples such as Blanchard et al. (2019) and Autor et al. (2013), but there are a range of ways in which tariff exposure can be calculated. We additionally consider five other formulations to check robustness, and the results are presented in Table 10 in the Appendix along with full definitions of the measures. Column (1) repeats the main measure used in the paper, while column (2) adjusts this measure applying the weighting to _ln_ (1 + tariff rate _pc,t_ ) rather than directly to the US or retaliatory tariff rates. Column (3) takes a similar approach but applies the log transformation to the measure after the trade and employment weighting is already applied. Column (4) weights only by import shares rather than incorporating sectoral labour.

Columns (5) and (6) weight by sectoral output rather than employment. For example, the sectoral output tariff exposure (later weighted by CZ employment shares) for the specification in column (5) is constructed as follows: where _c_ is the county of origin, and _p_ is the 10-digit HS product. Column (5) is similar but 20It may be worth nothing that an alternative interpretation of this placebo test is that tariff changes were not anticipated 12 months in advance of their implementation.

32
the underlying value for area B increases. Unless it increases enough to surpass area A the ranking will not change even though the increase in the value of the ranked characteristics may directly affect fertility.

There are two major advantages to this approach. First, the instruments are easy to create from readily available secondary data like a census or, possibly, even from the primary data set itself. Secondly, the instruments are intuitive in that they mimic expectations about the underlying resource allocation process. In other words, ranks likely reflect what policy makers care about when distributing programs, but are not directly related to fertility.<sup>7</sup> Furthermore, the process is agnostic about which characteristics actually determine placement.

The paper makes three contributions to the literature. First, it uses a novel but widely available set of instruments to identify the effect of family planning on fertility. Second, it examines the effect of a family planning program of limited means in a very poor setting that experienced little economic growth during much of the period of study.<sup>8</sup> As seen above, the scant evidence in the literature so far comes from very ambitious, costly programs (Matlab) or dynamic macro-economics settings (Indonesia and Colombia). Yet, it is in more stagnant low-income settings that high fertility often poses the more important obstacle to accelerating development. Third, this study focuses on how the effect of access to family planning is critically dependent on the education level of women.

We find that access to family planning in Ethiopia has a statistically significant and economically large impact on fertility of women with no schooling, while there are no discernible effects of family planning on fertility for women who have ever attended school. The reduction in completed fertility at more than 1 child is large compared to other studies.<sup>9</sup> These insights have important policy implications as 65 percent of women 30 years or older never attended school in Ethiopia (Central Statistical Authority of Ethiopia 2007). The reduction in fertility is concentrated among the youngest women and the oldest women indicating that access to family planning leads to a postponement of birth among younger women and a reduction in completed fertility through earlier completion of child bearing. Further analyses provide support to the direct effect of access to family planning on reduced fertility, as opposed to the indirect effect through improved child health and survival resulting from availability of the health facilitites in which the family planning

> 7A potential issue is that the rankings chosen may also explain other the distribution of other programs that may themselves affect fertility. The most obvious case is the placement of schools.

> 8Ethiopia’s GNI per capita in PPP went from just over USD 300 in 1980 to USD 480 in 2003.

> 9Unlike here, the results from these other studies represent an average across women with and without schooling.

3
11 (Figures 5 and 6). **'1** Black market exchange rate premiums are dervied from data on black market exchange rates in the World Currency Yearbook and the official exchange rates presented in the IFS (Figures 7 and 8).1" <!-- Start of picture text --> Regional Monthly Avera1es Monthly Average for Secondary Market Prices:<br>Latin America (LAC and Asia (ASIA) LtnAerica: 1988.01-1992.09<br>1988.01 - 1992.09<br>55 2<br>1988 198 1990 19S1 1992 1988 1989 1990 l9S1 19920<br>45<br>40<br>2 ~~~~~~~~~~~~~~~~~~~~~~50<br>eo --. ,-A ASS3.,.,,,,,........... -. .. .. ..... .. ... ...........<br>35~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~'<br>30 45<br>8,25 -40<br>109.. 1989.1990 1991 1992 1988 1989.1990.1 9 91 1992<br><!-- End of picture text --> Figure **S** Figure 6 '"The credit ratings are available on a semi-annual basis. For intermittent months, the semiannual ratings are kept at their latest value. The secondary market prices are end-of-month prices. Prices are not corrected for the fact that some of the claims are collateralized with riskfree assets, assets whose prices themselves depend on interest rates. Secondary market prices are not available for Asia (debt trades in general at par, except for the Philippines). Individual country credit ratings and secondary market prices are used in estimations.

"The premiums are occasionally negative as there is some non-synchroneity between the black market rates and the official exchange rates, as well as excess supply in the black market itself.
iv) The continuous growth of the North’s R&D over time has a positive impact on the South’s _long-term_ productivity growth, an impact that is substantially greater for small than for large states.

The remainder of the paper is organized as follows. Section 2 presents the empirical framework. Section 3 describes the data and Section 4 provides the empirical results. Section 5 concludes.

# 2. Empirical Framework

As discussed earlier, Coe and Helpman (1995) developed an empirical model to estimate the impact on _TFP_ of North-North trade-related technology diffusion. Their estimation equation is: log _TFPct_ = α + λ _c_ + λ _t_ + β _d_ log _RDctd_ + β _f_ log _RDctf_ + ε _ct_ ; β _d_ , β _f_ > ,0 (1) where λ _c_ (<sup>λ</sup> _t_ ) is a country (time) fixed effect, _RDctd_ ( _RDctf_ ) is the domestic (foreign) R&D stock, ε is an error term, and subscript _c_ ( _t_ ) denotes country (year).

Coe et al. (1997) use a similar model to explain North-South trade-related technology diffusion. However, due to lack of data for most developing countries, the equations they estimate do not include domestic R&D. They only use the foreign R&D stock _RD f_ , which is referred to in this paper as ‘North foreign R&D’ and is denoted by ‘ _NRD_ ’ in our study. Abstracting from domestic R&D is unlikely to be a major problem because most of the world’s R&D is performed in developed countries.<sup>2</sup>

> 2 In 1990, 96% of the world’s R&D expenditures took place in industrial countries (Coe et al., 1997). The share was 94.5% in 1995 (calculated from the World Bank database). Moreover, recent empirical work has shown that much of the technical change in individual OECD countries is based on the international diffusion of technology among the various OECD countries. For instance, Eaton and Kortum (1999) estimate that 87% of French growth is based on foreign R&D. Since developing countries invest much fewer resources in R&D

6
# **Water When It Counts: Reducing Scarcity through Irrigation Monitoring in Central Mozambique**

_By_ PAUL CHRISTIAN FLORENCE KONDYLIS VALERIE MUELLER ASTRID ZWAGER TOBIAS SIEGFRIED<sup>*</sup> _Keywords: water, irrigation, information, experiment, productivity, Africa_ _JEL Codes: O13, Q15, Q16, Q25, D83_

## **I. Introduction**

Irrigation systems are a common pool resource. When farmers fail to internalize the cost of their use on others, the allocation of water within the irrigation scheme may not only be inefficient but also affect water availability in the long term. Collective action over the management of a scheme is then necessary to ensure the sustainability of irrigation supply. Decentralized models of governance have evolved to formalize the delivery of water resources (Ostrom, 1990; Ostrom and Schlager, 1992). Yet, local institutions like water user associations may not yield efficient resource sharing if the main constraint users face is limited knowledge of water management (Plusquellec, 2002; Meinzen-Dick, 2007).

> * Author affiliations are: Christian: World Bank; Kondylis: World Bank; Mueller: Arizona State University, International Food Policy Research Institute; Zwager: World Bank; Siegfried: Hydrosolutions, Ltd. Corresponding authors are: Christian, `pchristian@worldbank.org` ; Kondylis, `fkondylis@worldbank.org` ; and Mueller, `Valerie.Mueller.1@asu.edu` . Luiza Cardoso de Andrade provided superb research assistance. We thank Mario Chilundo, Steven Glover, Robert Naudascher, and Euclides Tiago for excellent field assistance. We appreciate valuable comments received from Dawit Mekonnen and seminar audiences at IFPRI and the AAEA meetings. The team is grateful for the support of Pedro Arlindo, Mark Austin, Aniceto Bila, Mark Lundell, Paiva Munguambe, Eugenio Nhone, and Antonio Samuel. This project benefited from funding provided by the USAID mission and World Bank country offices in Mozambique, the CGIAR Research Program on Policies, Institutions, and Markets (PIM) led by the International Food Policy Research Institute (IFPRI), as well as the i2i trust fund financed by UKAID.

_1_
in Gujarat relative to other Indian states after the riots of 2002. The probability of women getting married before 18 increased by 4.4 percentage points or 14 percent after the riots in Gujarat compared with the control states. Also, the probability of getting married before the age of 18 is relatively higher among Muslim women, who were some of the primary victims of sexual violence during the riots (Khanna, 2008).

Our event study estimates suggest that the effects are prominent two years after the intercommunal violence, and the gap in terms of women’s age at marriage between Gujarat and the other Indian states has since increased. Our results are robust to synthetic control methods or restricting the control group to states that share their borders with Gujarat. We also conduct a few additional robustness checks to allay concerns about other shocks within Gujarat driving our results.

Next, to understand the implications of early marriage for women’s post-marital socioeconomic status, we check education and autonomy outcomes for women married after the riots compared to women married before the riots. Existing literature has established that marrying young or exposure to conflict can decrease women’s bargaining power within the marriage (Field and Ambrus, 2008; Jensen and Thornton, 2003). We find that women married after the riots had fewer years of education, were more likely to experience domestic violence, had less control over their income, and had lower autonomy regarding household purchases and visits.

Several mechanisms could explain our results. First, in the Indian culture, rape victims face the risks of being socially ostracized, which could worsen their position in the marriage market. Therefore, the fear inflicted by sexual violence on victims, their families, and the community living in the riot-inflicted regions can lead to early marriages of women. Second, distortions in sex ratios due to disproportionately higher mortality for men or women could also affect women’s position in the marriage market by altering their bargaining power (Becker, 1981; Teso, 2018; Abramitzky et al., 2011). Third, negative income shocks caused by the riots can also alter women’s marriage age due to the payment of dowry or bride prices at the time of marriage (Corno et al., 2020; Khanna and Kochhar, 2020). In this paper, we do not attempt to disentangle these different mechanisms but establish the effects of the riots on women’s age at marriage and explore its implications for women’s socioeconomic status and autonomy within the household. Our overall findings shed light on the importance of providing protection to the most marginalized, who also face the risk of sexual cruelty during violent conflicts, particularly women and girls.

The rest of this paper is structured as follows. Sections 2 provides a review of the literature and 3 discusses the background. Sections 4 and 5 discuss the data and the empirical strategy. Sections 6 and 7 discuss our main results and their robustness. Section 8 discusses 3