rafmacalaba/datause-encoder-data huggingface dataset:
# **2. Literature Review**

There is a large body of work in the survey literature about reporting errors in survey data; Sudman and Bradburn (1974) summarize the extensive work in this area from the 1950s and 1960s. Retrospective data, in particular, introduce various data quality issues linked to recall errors. Over time, respondents may not be able to accurately recall details of events. Accurate remembrance of events will depend not only on the duration of the recall period, but also on the nature of the event being reported. The literature generally categorizes three main types of recall error in household survey data: telescoping, heaping, and recall decay. Telescoping refers to inaccurately identifying the date of events, either forward or backward into the recall reference period. Heaping refers to the use of estimation by respondents that places large numbers of responses at particular points, such as an expenditure of about $100 or dating an event about 6 months ago. Recall decay refers to forgetting details of events. Since the focus of our study is farm input usage and harvest size, rather than the timing of events, we do not focus on telescoping. However, there are areas within agricultural statistics where telescoping would be relevant, such as dates of fertilizer application or input purchase.

It is also difficult to consider the issue of “heaping” because agricultural data are naturally heaped in that both inputs and products are sold in uniform quantities (e.g. 50 kg sacks, oxcarts, etc.), as opposed to variables such as reported age, where one does not expect to find heaping and can then look for it as evidence of reporting errors. Although there is considerable variation in the units reported across the crops and countries we study here, we nonetheless find that most of the quantities are reported in heaped quantities reflecting the normal patterns one would expect for these measures. For example, in the data used in this study from Kenya on maize harvest, more than 90 percent of reports are in terms of numbers of 50 or 90 kilogram bags. For coffee, more than 97 percent of reports are in kilogram amounts divisible by 10. Likewise, in Rwanda, the vast majority of maize kilogram reports are in multiples of 20 or 50, and sorghum reports are in multiples of 10 and 100. In Malawi, more than 90 percent of maize production reports are in terms of 50 kg bags, 90 kg bags, or ox carts.

Recall decay bias can occur in two ways. First, respondents may altogether forget having performed certain activities, biasing frequency estimates downward. While there is little empirical work on the subject related specifically to agriculture, the topic is covered in guidelines for marketing and social research questionnaires. This literature describes salience as an 4
levels, productivity and welfare rise for everyone because the distortionary effect of taxes is more than compensated for by the beneficial effect of public services (which, of course, are tax financed). Government would want to raise the tax rate up to the point where productivity of public services is maximized. However, this optimal rate must be below the threshold rate; oterwise, the presence of the informal sector would add to the distortionary effect of taxes and this rate would no longer be optimal. To ensure that the threshold rate is at least as high as the optimal tax rate, government can increase penalties and prevent informals from using public srices, thus making- informality less profitable.

Bureaucracy d Ioformalit From the anaiysis in the previous section we learn that, for given parameters, an appropriate reduction of the tax rate and a sufficient severity towards the informal sector eliminate the incetives for economic agents to become informal. If everyone is better off without an informal sector, why may govermnent not pursue a policy to eliminate it?

We have treated government as an impersonal entity. In reality government is managed by a bureaucracy. This bureaucracy has the power to collect taxes and penalties and to administer the use of public services.

The bureaicracy collects penalties from informal agents. We have assumed that these penalties are not used to produce public services. If in fact the bureaucracy appropriates at least some of the penalty revenues, it has the incentive to promote the formation and growth of the informal sector. If the informal sector were to disappear, bureaucrats would lose their special rents.

The behavior of the bureuascy depends on the degree of cohesion and coordination

-24-
The annual Townsend Thai Survey (TTHAI) we use, does not link household businesses from round to round. It does hence not provide information about survival of a given firm that has been identified in one of the survey rounds to later rounds. In order to code whether a business observed in a given round survived or not, and in the latter case, whether a new firm was started, we needed to match reported businesses between rounds based on a number of business characteristics. For simplification, we decided to only include firms of households in our sample who never operated more than one enterprise in any of the three survey rounds.

We then coded the business of a household reported in a given survey round as surviving to a given follow-up round, if a business was reported for the same household in the follow-up round, and:

- firm ages coincided across the two waves; or

- the sector of the business was the same across the two waves, and the age of the business reported in the follow-up round was not less than the time difference between the two survey waves; or

- at least one of the household members identified as the business owners was the same across the two waves, and the age of the business reported in the follow-up round was not less than the time difference between the two survey waves.

We coded the business reported at baseline as closed, if:

- no business was reported in the follow-up round.

Otherwise, we coded survival/closure as missing.

We coded a new firm start, if:

- the age of the business reported in the follow-up round was less than the time difference between the two survey waves.

We coded the variable _newfirmstart_ to zero, if:

- the business reported in the baseline round survived; or

- no business was reported in the follow-up round and the business of the baseline round was coded as closed; or

- the age of the business reported in the follow-up round was not less than the time difference between the two survey waves.

Otherwise, the variable _newfirmstart_ was coded to missing.

For businesses for which _survival_ and _newfirmstart_ remained unclear or inconsistent, we inspected the characteristics on a case-by-case basis, taking into account information on firm age, type of activity, and ownership reported in all survey waves in which we observed these unclear cases. In addition, we used information on whether the household decided to stop running any business in the past 12 months, and if so, the type of activity they were no longer running, as well as whether the business reported in a given round had been founded in the past 12 months, which was provided in the household business modules of the follow-up questionnaires.

Finally, we included one owner per firm in our sample, in case we had identified more than one owner for a given firm, either because we had identified more than one owner in one or more waves, or because different owners were reported in different waves. In these cases, we decided to include the owner, who was reported as the owner in all of the waves in which we observed the firm. If this was the case for both owners, we included the owner, 45
# **Table S13: Effects of Parent Insurance on Health Indicators by Child Eligibility**

||Checkup|Ever Sick|Times Sick|
|---|---|---|---|
|Panel A: Effects on Parents|(1)|(2)|(3)|
|Parent Enrolled|0.127*|-0.035|0.841|
||(0.072)|(0.042)|(1.935)|
|Observations|1,614|1,614|1,614|
|R-squared|0.029|0.014|0.013|
|Panel B: Effects on Children|(1)|(2)|(3)|
|Parent Enrolled|-0.040|0.014|0.676**|
||(0.071)|(0.064)|(0.336)|
|Parent Enrolled*Ineligible|-0.009|-0.192|-1.740***|
||(0.111)|(0.144)|(0.613)|
|Ineligible|0.028|0.062|0.456**|
||(0.034)|(0.048)|(0.215)|
|Observations|2996|2996|2996|
|R-squared|0.045|0.09|0.079|
|P-value of Enrolled + Enrolled*Ineligible|0.638|0.198|0.053|

_Notes:_ The sample in Panel A is all parents with a child aged 15 and under (N=1614); the sample in Panel B is all children aged 15 and under (N=2996). Children age 12-15 are "Ineligible" and children under 11 are "Eligible". Above regressions are estimated coefficients from 2SLS-IV estimates where "Parent Enrolled" is instrumented with random assignment status; Ineligible*Parent Enrolled is instrumented with random assignment status*Ineligible. The dependent variable are various measures of health status: whether the child had a checkup in the past year, whether the child had ever been sick in the past year, and the number of times sick. Regressions control for household size, household size squared, the inverse hyperbolic sine of parental income, parent's years of education, age of child, age of child squared, gender, whether the child was sick in the past year, the number of times sick, total number of health visits, and survey round and market fixed effects. Individuals without valid income data were imputed to be the median and regressions were run with a dummy variable indicating the missing value. Robust standard errors in parentheses, clustered at the family level. *** p<0.01, ** p<0.05, * p<0.1 _Source:_ Authors’ analysis based on data described in paper.

13
role of multinationals might therefore be expected to reduce antidumping activity, at least for countries and industries particularly prominent in global supply chains.

But there are additional channels through which the changing nature of global trade could also influence antidumping activity and its consequences. Antidumping may provide an important incentive for multinationals to substitute local subsidiary production in a foreign market for exports, i.e., “antidumping-jumping” foreign direct investment (FDI).<sup>25</sup> The important role of multinational firms in world trade also complicates the political economy of antidumping because it opens the door to new types of strategic behavior on the part of vertically integrated firms. Once a firm has established production in the former export market via FDI, its incentives with respect to antidumping or other trade barriers are likely to change. Trade barriers faced by other foreign suppliers can improve the firm’s own position relative to competitors that rely on arm’s-length transactions for imported inputs or that continue to serve the same market via exports. The firm may even increase its own exports from a foreign location in an attempt to trigger an antidumping investigation that will hamper competitors that lack local production capacity.<sup>26</sup> The cases shown in Table 2 illustrate the potential relevance of these issues for emerging markets. We searched the World Bank’s _Temporary Trade Barriers Database_ (Bown 2012a) for cases in which the same 6-digit Harmonized System (HS-06) products and firm names were involved in antidumping investigations initiated in different countries. Table 2 reports a number of examples in

> 25 An important early example of the relationship between administered protection and foreign direct investment came in the voluntary export restraint agreement negotiated between the United States and Japan in autos in 1981.  In their support for protection, an explicit goal of the United Auto Workers was to encourage Japanese companies to establish factories in the United States.  Likewise, although the gap left by European VERs on Japanese autos was initially filled by traditional European suppliers in Italy and Germany (De Melo and Messerlin 1988), VER-jumping Japanese FDI soon followed.  On antidumping-jumping FDI, see Blonigen (2002).

26 Blonigen and Ohno (1998) provide a theoretical model of “protection-building trade” in which foreignheadquartered firms locate production in the home country and then increase their own exports to the home country so as to _increase_ protectionist pressures that would result in higher barriers against other foreign competitors in the future.

23
Policy Research Working Paper 8944

# **Abstract**

Despite dramatic global gains in access to education, 130 million girls of school age remain out of school. Among those who do enter, too many do not gain the essential skills to succeed after they complete their schooling. Previous efforts to synthesize evidence on how to improve educational outcomes for girls have tended to focus on interventions that are principally targeted to girls, such as girls’ latrines or girls’ scholarships. But if general, non-targeted interventions—those that benefit both girls and boys—significantly improve girls’ education, then focusing only on girl-targeted interventions may miss some of the best investments for improving educational opportunities for girls in absolute terms. This review brings together evidence from 270 educational interventions from 177 studies in 54 low- and middle-income countries and identifies their impacts on girls, regardless of whether the interventions specifically target girls. The review finds that to improve access and learning, general interventions deliver gains for girls that are comparable to girl-targeted interventions. At the same time, many more general interventions have been tested, providing a broader menu of options for policy makers. General interventions have similar impacts for girls as for boys. Many of the most effective interventions to improve access for girls are household-based (such as cash transfer programs), and many of the most effective interventions to improve learning for girls involve improving the pedagogy of teachers. Girl-targeted interventions may make the most sense when addressing constraints that are unique to girls.

This paper is a product of the Office of the Chief Economist, Africa Region and the Education 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 devans@cgdev.org and fyuan@g.harvard.edu.

_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 International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
Table 2. Descriptive statistics for those in the rural China sample that were laid-off (and re-hired) <u>between September 2008 and April 2009.</u>

||Sample|Whether lost off-farm<br>job after September<br>2008 (1=yes, 0=no)<sup>a, c</sup>|Whether lost off-farm<br>job after September<br>2008 and did not find a<br>new one till April 2009<br>(1=yes, 0=no)<sup>b, c</sup>|
|---|---|---|---|
|Total|1,415|0.18<br>(0.37)|0.09<br>(0.28)|
|By sex||||
|Male|946|0.17<br>(0.37)|0.08<br>(0.28)|
|Female|469|0.18<br>(0.36)|0.10<br>(0.29)|
|By age group||||
|<=30 years|529|0.21<br>(0.39)|0.10<br>(0.29)|
|30~50|629|0.15|0.07|
|years||(0.35)|(0.25)|
|>50|257|0.17|0.13|
|years||(0.38)|(0.34)|
|By education level||||
|Elementary school or less|420|0.20<br>(0.40)|0.13<br>(0.33)|
|||0.17|0.07|
|Middle school|763|(0.36)|(0.26)|
|High school or higher|232|0.14<br>(0.35)|0.07<br>(0.27)|

a This includes long-term laid-offs (those that were working off-farm in September 2008 and not in April 2009) and re-hirees (those that were working off-farm in September 2008, was laid-off, but, were reemployed off-farm by April 2009). b This includes only long-term laid-offs. c Standard deviation in the parentheses.

Data source: Authors’ own data (CNRS dataset).

29
Policy Research Working Paper Series

||Title|Author|Date|Contact<br>for paper|
|---|---|---|---|---|
|WPS100|6 Preparing Muitiyear Railway<br>Investment<br>Plans: A Market-Orient<br>Approach|Jorge M. Rebelo<br>ed|October 1992|A. Turner<br>30933|
|WPS100|7 Global Estimates and Projections<br>of Mortality by Cause, 1970-2015|Rodolfo A. Bulatao<br>Patience W. Stephens|October 1992<br>|0. Nadora<br>31091|
|WPS100|8 Do the Poor Insure? A Synthesis of<br>the LXterature<br>onRisk and<br>Consumptio**n**<br>i Developing<br>Countrie|Harold Alderman<br>Christina H. Paxson<br>s|October 1992|C. Spooner<br>32116|
|WPS100|9 Labor and Women's Nutrition:<br>A Study of Energy Expenditure,<br>Fertility, and Nutritional<br>Status in Gha|Paul A. Higgins<br>Harold Alderman<br>na|October 1992|C. Spooner<br>32116|
|WPS101|0 Competition<br>and Efficiency<br>in<br>Hungarian<br>Banking|Dimitri Vittas<br>Craig Neal|October 1992|W. Pitayatonakarn<br>37664|
|WPSI 011|How Tax In^entives Affect Decision<br>to Invest in Developing<br>Countries|s Robin Boadway<br>Anwar Shah|November 1992|C. Jones<br>37754|
|YVPS10|12<br>The Brady Plan, the 1989 Mexican<br>Debt Reduction<br>Agreement,<br>and Ban<br>Stock Returns in the United States<br>and Japan|Haluk Unal<br>k Asli Demirg0g-Kunt<br>Kwok-Wai<br>Leung|November<br>1992|W. Patrawimolpon<br>37664|
|WPS1 013|The Impact of Mexico's Retraining<br>Program on Employment<br>and Wages|Ana Revenga<br>Michelle Riboud<br>Hong Tan|November 1992|D. Young<br>30932|
# **Table 1 Taxonomy of Grants and Their Conceptual Impacts**

||_Incom_|_e effect_<br>|<br>|_Price_|_(substit_<br>_effect_<br>|_ution)_<br>|_To_|_tal effe_<br>|_ct_<br>||_Rank_<br>_Increases_<br>|_by objective func_<br>_Accountability_<br>|_tion_<br> <br>|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|_Type of grant_|a1|A|U|a1|A|U|a1|A|U|∂A/∂<br>G|_in_<br>_expenditure_|_for_<br>_results_|_Welfare_|
|_Conditional (input based) matching_||||||||||||||
|Open-ended|↑|↑|↑|↑|↑|↓|↑↑|↑↑|↑↓|> 1|1|3 (none)|3|
|Closed-ended||||||||||||||
|Binding constraint|↑|↑|↑|↑|↑|↓|↑↑|↑↑|↑↓|≥ 1|2 or 3|3 (none)|4|
|Nonbinding constraint|↑|↑|↑|n.a.|n.a|n.a.|↑|↑|↑|≤ 1|3|3 (none)|2|
|Conditional nonmatching|↑|↑|↑|n.a.|n.a.|n.a.|↑|↑|↑|≤ 1|3|3 (none)|2|
|Conditional nonmatching output-||||||||||||||
|based|↑|↑|↑|n.a.|n.a.|n.a.|↑|↑|↑|≤ 1|3|1 (high)|1|
|General nonmatching|n.a.|↑|↑|n.a.|n.a.|n.a.|n.a|↑|↑|<1|3|3 (none)|1|

_Note_ : 1 = highest score, 4 = lowest score. ↑ = positive impact; ↓ = negative impact; _a_ 1 = assisted subfunction; _A_ = assisted function; _U_ = unassisted function **;** _G_ = grant; n.a. = not applicable.

_Source_ : Adapted from Shah (1994b).
Although this figure amounts to only a small proportion of total health spending in the US, the savings are nevertheless impressive for three reasons. First, the savings pertain to only fifteen treatments drawn out of a large universe. Given that patients from the US and UK are traveling to India for major procedures such as cardiac surgery (see e.g., Srinivasan, 2005), the list of tradable procedures is arguably much wider. Identifying the universe of tradable treatments would be a useful exercise but is beyond the scope of this paper. Second, our estimate of cost savings is understated to the extent that we have used Medicare payment rates to calculate US prices, which are lower than those paid by private insurers and the uninsured, as noted above. Third, patient volume data was not available for all procedure categories, and a fuller accounting would certainly magnify the estimate of savings.

# **6. Are there good reasons to deny coverage for treatment abroad?**

Given that there are large gains from trade in health care, it is a puzzle that insurers in countries with expensive health care deny coverage for non-emergency treatment obtained abroad rather than encourage patients to seek care overseas. We consider possible reasons that have emerged from discussions with insurers.

_Insurer concerns about quality of overseas providers and malpractice law_ Insurers may care about the quality of the providers because of a potential negative spillover effect in the consumption of health care. A consumer’s decision to receive care from low-cost overseas providers may prove expensive to the insurer if the treatment worsens health problems and the insurer is obliged to cover the costs of subsequent treatment. The insurer may also be concerned that malpractice may occur in a foreign jurisdiction where the legal regime makes it difficult to sue care providers.

It would make sense to deny the consumer the _option_ of receiving cheaper treatment abroad for these reasons if two conditions hold true. First, the insurer cares more about potential future cost implications of poor provider quality than consumers care about the impact of provider quality on their own health. Second, the insurer is more concerned than the consumer about the difficulty in seeking compensation for malpractice abroad. These conditions cannot be ruled out but do not seem very plausible. Moreover, if these concerns really exist then it should be possible to write contracts that insulate the insurer from bearing any additional costs that arise from the consumer’s decision to go abroad.<sup>26</sup> Quality concerns can be more directly addressed by creating provider networks abroad, as we describe in section 7 below.

> 26 One response to high costs of malpractice insurance in the US has been for American doctors to simultaneously practice in two countries, offering routine care at home, and performing procedures with higher surgical risk offshore, or in a foreign country.  This practice is becoming more common, and could simultaneously allay both quality and legal concerns.

21
Table 7: Estimations of GQ improvements for spatial mismatch

||Organized|secto|r mismatch|Unorganize|d sec|tor mismatch|Total urban|spatial mismatch|
|---|---|---|---|---|---|---|---|---|
||Plants||Employment|Plants||Employment|Plants|Employment|
||(1)||(2)|(3)||(4)|(5)|(6)|
||A. Bas|e spat|ial horizon m|easuring effects|relati|ve to districts 50+|km from the|GQ network|
|Post GQ upgrades *|-0.011||-0.004|0.026||0.026|0.017|0.017|
|Nodal district|(0.010)||(0.011)|(0.024)||(0.018)|(0.025)|(0.025)|
|Post GQ upgrades *|0.001||0.014|-0.012||0.001|-0.007|-0.007|
|District 0-10 km from GQ|(0.010)||(0.013)|(0.019)||(0.020)|(0.018)|(0.018)|
|Post GQ upgrades *|0.002||-0.006|-0.009||-0.004|-0.007|-0.007|
|District 10-50 km from GQ|(0.011)||(0.018)|(0.029)||(0.031)|(0.026)|(0.026)|
|District and year fixed effects|Yes||Yes|Yes||Yes|Yes|Yes|
|Observations|912||912|1104||1104|1131|1131|
||B. Extend|ed spa|tial horizon|measuring effect|s rela|tive to districts 2|00+ km from|the GQ network|
|Post GQ upgrades *|0.001||0.006|0.030||0.022|0.026|0.005|
|Nodal district|(0.011)||(0.013)|(0.025)||(0.019)|(0.026)|(0.017)|
|Post GQ upgrades *|0.013||0.024|-0.009||-0.003|0.003|-0.001|
|District 0-10 km from GQ|(0.011)||(0.015)|(0.020)||(0.021)|(0.019)|(0.018)|
|Post GQ upgrades *|0.014||0.004|-0.005||-0.008|0.003|0.002|
|District 10-50 km from GQ|(0.012)||(0.020)|(0.030)||(0.031)|(0.027)|(0.024)|
|Post GQ upgrades *|0.031||0.019|0.027||0.007|0.038|0.014|
|District 50-125 km from GQ|(0.012)||(0.016)|(0.027)||(0.028)|(0.025)|(0.024)|
|Post GQ upgrades *|0.020||0.024|-0.013||-0.024|0.004|-0.009|
|District 125-200 km from GQ|(0.011)||(0.016)|(0.025)||(0.029)|(0.023)|(0.023)|
|District and year fixed effects|Yes||Yes|Yes||Yes|Yes|Yes|
|Observations|912||912|1104||1104|1131|1131|

Notes: See Table 6.

33