rafmacalaba/datause-encoder-data huggingface dataset:
collected only at the community level. The rules governing marriage are crucially important in understanding the dynamics of individual asset accumulation.

All three LSMS surveys ask about marital status but not about the marital regime under which the adults in the household were married. The Guatemala questionnaire includes the most detailed questions about marital status (in the demographic module) with the choices being: consensual union, married, separated from marriage, separated from union, divorced, widow/widower or single.

Other useful demographic information concerns the parents of individual respondents. The Vietnam questionnaire collects information about each parent’s education and type of work. This would be an appropriate place to add questions about the number of siblings each household member has and whether any has inherited or received property from parents or other relatives. It would also be useful to include a question about assets (especially land and housing) owned by each parent separately or jointly. These questions are useful as instruments in econometric analyses, for example, where it may be necessary to estimate the determinants of women’s land rights in order to use such an estimate to measure the impact of women’s land rights on household outcomes.

The Ghana questionnaire does ask whether any income from dowry or inheritance was received by the household in the past 12 months, but does not collect the more specific information needed to analyze marital and inheritance regimes.

Additional questions about inheritance patterns and expected inheritances to be received would provide some additional information that would provide insights into understanding household decisions.

# 5. 10. Knowledge of Property Laws

As the formal laws in many countries are changing with respect to women’s rights to own and manage property, it could be useful to ask additional questions about people’s knowledge of individual property rights.

The Guatemala questionnaire includes a section on social capital, asking about collective action, exclusion, and perception of welfare, but only the household head is asked to respond to these questions. This would be an appropriate place to incorporate questions about knowledge of property rights. It would be more useful, however, to ask these questions of all of the adults in the household, rather than simply the household head.

# **6. Conclusion**

This paper has set out a systematic framework for the collection of data on individual level asset ownership. It made the case that individual level data on key assets – land, housing, non-farm businesses, financial assets, and other physical assets – is critical for country and global monitoring of progress toward MDG3 and for policies to reduce poverty, provide social protection, and promote pro-poor economic growth. We then 41
inaccessible pre‐war region, and included the nomadic population, interviewing a total of 6,092 households in December 2017 (Table 1).

_Table 1: Number of interviews by population type, Somali High Frequency Survey_

|**Population type **|**Wave 1 households**<br>**Wave 2 households**|
|---|---|
|Urban|2,864<br>4,011|
|Rural|822<br>1,106|
|IDP|431<br>468|
|Nomadic|0<br>507|
|Total|4,117<br>6,092|
||Source: Authors’ calculations.|

The analysis excludes nomadic households and IDPs within and outside IDP settlements to avoid invalid comparisons between wave 1 and wave 2. Large‐scale drought‐related displacement implies that IDP populations before the drought in wave 1 were different from IDP populations surveyed during the drought in wave 2. Nomadic households do not have a permanent place of residence, so that a geographical exposure measure cannot be assigned in a meaningful way. The final data set contains 5,852 urban and 1,594 rural households. The data include information on consumption and key household and individual characteristics and perceptions, as well as information on shocks and vulnerabilities. Poverty is measured against the international poverty line of US$ 1.90 per capita per day, derived from the spatially and intertemporally deflated consumption aggregate (Pape and Wollburg, forthcoming).

The Normalized Deviation Vegetation Index (NDVI) is used to determine the exposure of households to the drought. The NDVI is derived from satellite images measuring the health of vegetation. Below‐average NDVI values imply drier‐than‐usual conditions, indicating the vegetation health is also below‐average. NASA’s MODIS Terra and Aqua platform provides the daily global NDVI data at 500m resolution, which serve as the source of data for this analysis (Schaaf, 2015). While four consecutive rainy seasons delivered poor rains in 2016 and 2017, the severe rainfall deficits in the second rainy season of 2016 and first rainy season of 2017 were the key drivers of the 2016/17 drought in Somalia (FEWSNET, 2018).<sup>2</sup> Hence, each household’s level of drought exposure is defined in this analysis as the percentage deviation of the NDVI during these two seasons from the pre‐drought 2012 to 2015 average,<sup>3</sup> within a 25km radius around each household. The levels of drought exposure range from NDVI values of 6 percent above average to 20 percent below average in wave 1, and from 4 percent above average to 36 percent below average in wave 2, reflecting the overall spectrum of drought severity (Figure 1).

> 2 Somalia has two main rainy seasons: the main Gu rains from April to June and the short Deyr rains from October to December. Significantly below‐average rainfall started with the 2016 Gu rains and extended to the 2017 Deyr rains.

> 3 In 2010‐11, there was a severe drought in Somalia. The reference period was chosen to start after the 2010‐11 drought to preclude this unusual event from interfering with the series average, following World Bank (2018).

3
more extensive information on past migration episodes, including timing and country of destination.

Finally, to ensure that household conditions prior to migration are recorded, it is useful to collect other selected information within the recall period. For example, one could collect information on occupations or assets in the household prior to, during and after the migration spell of any household member who had migration experience. Other information, often subjective, might also be worth collecting for individuals who may be return migrants, such as whether or not they plan to leave the household again; and the reasons for return. Some potential reasons for return, such as health of household members, can be corroborated in other parts of the survey. While the design of a questionnaire is important to ensuring that the ‘right’ information is gathered for a study, a survey is only as good as its sample and sampling frame.

# **_Tracking migrants_**

Another approach to collecting more exhaustive information about emigrants would be to track them. This requires detailed contact information to reach the migrant. Such methods have been used to examine the impacts of internal migration on welfare in Tanzania via a health and development panel data set (Beegle et al., 2011), and in Ethiopia combining a rural household survey with a migrant tracking survey (de Brauw et al., 2013). Given the high mobility of migrants, the tracking survey would ideally occur within weeks of the survey at the sending destination. Internationally, tracking surveys of this type have been carried out in a few countries, including between Mexico and the USA, and between 19
The total assets were about DM 65.6 billion in 1994 corresponding to about 2 percent of GDP. More than half of the assets were invested in bonds, 12 percent in mortgages, 15 percent in equities and other securities, 9 percent in real estate and 9 percent in term deposits.<sup>9</sup>

# **III. Supplementary Pensions**

Coverage of supplementary pensions in Germany is relatively low compared to other OECD countries; this is a consequence of the design of the public pillar which is meant to replace a significant share of earnings rather than to provide only a modest pension. Supplementary pensions are provided predominantly through occupational pension plans. In 1990, approximately one third of all companies offered occupational pension schemes to their employees; the plans covered 46 percent of all dependent employees. The expenditure for occupational pension plans corresponded to 4.9 percent of total gross wages. Public sector employees who are not civil servants are covered by a mandatory supplementary pension scheme. Of today's pensioners about 40 percent receive supplementary occupational pensions.

A survey conducted in 199310 found that participation in occupational pension plans was declining when measured as number of workers covered (but constant in terms of companies offering occupational schemes). Coverage in industry declined from 70 to 66 percent of all workers, and in trade and services from 29 to 28 percent between 1990 and 1993.

The total reserve capital to cover pension promises was estimated to be about DM 460.6 billion in 1993 corresponding to about 15 percent of GDP. This figure, however, is subject to considerable uncertainty because the reserves of life insurance related to occupational pension plans are not separated from the ordinary life business in the statistics and thus are based on an estimate.

There are four different types of occupational schemes: (i) pension plans financed through book reserves, (ii) support funds, (iii) pension funds set up as separate legal entities, and (iv) life insurance contracted by the employer on behalf of the employee ("direct insurance"). Supplementary pension plans can be established through an individual employment contract, company agreements for all employees or through collective employment agreements. All occupational pension plans are subject to the 1974 Occupational Pensions Act which establishes minimum standards of vesting and portability and regulates other areas to protect members' interests.

> 9Data provided by the Association of Professional Previsional Institutions, 1996 **10** ifo Institut far Wirtschaftsforschung 1993

12
# **1. Introduction**

Approximately 85 percent of the global refugees are hosted in developing countries (UNHCR, 2020). Sub-Saharan Africa (SSA) hosts about one-third of them (Ruiz & Vargas-Silva, 2017). UNHCR (2019) asserts that the number of refugees in the region increased threefold between 2010 and 2019. This rise has been mainly attributed to persistent conflicts in the region (Verwimp & Maystadt, 2015; Kasozi, 2017 & Ivanova et al., 2018). Protracted conflict has also led to long refugee stays; an average of 9-21 years according to Hunter (2009). Hosting refugees could have far-reaching consequences in areas already struggling to ameliorate their own economic situation (Maystadt et al., 2019).

There has been a booming literature assessing the consequences of hosting refugees (Meyer et al., 2011; Ruiz & Vargas-Silva, 2017; Maystadt et al. 2019). Although the literature highlights that refugees can have a positive effect on economic development but with likely distributional consequences, the evidence from individual studies is mixed (Ruiz and Vargas-Silva 2017; Maystadt et al. 2019; Verme and Schuettler 2021). In their review, Verme and Schuettler (2021) argue that the direction of impact depends on which economic dimension is studied. For instance, they find that beneficial impacts are less likely if the outcome of interest is host employment or wages. By contrast, it is more likely if the outcome of interest is well-being measured in terms of income, consumption or wealth (Verme & Schuettler, 2021). Furthermore, they stress that few studies have employed panel data to study the impact of hosting refugees on the host communities.

Based on panel data collected between 2009 and 2012, we assess the impact of hosting refugees in Uganda on material welfare, measured by the consumption per adult equivalent. Our main outcome variable differs from studies such as Alix-Garcia and Saah (2009), Alix-Garcia et al. (2012), and Loschmann et al. (2019), which focus on market prices, host employment and household assets. Alix-Garcia et al. (2018) is one exception since they use cross-sectional data on consumption to validate their results based on night light indexes. Other studies on SSA using longitudinal data on consumption include Maystadt and Verwimp (2014), Ruiz and Vargas-Silva (2017), and Maystadt and Duranton (2018) on the Kagera region of Tanzania; and Alloush et al. (2017) on the Congolese refugees in Rwanda. However, all these studies investigate the economic impacts of refugees living in camp settings.

Uganda is an interesting case study. According to the unique Ugandan refugee policy, refugees are not settled in camps but rather live in settlements. According to Betts et al. (2017), Betts et 2
inequality of wealth leads to the adoption of rules that preserve the initial inequality of wealth.<sup>4</sup> In this explanation, institutions matter only to the degree that they establish and enforce rules. However, sociologists and anthropologists argue that institutions also play a “schematizing role.” They shape intuitions and what people believe to be the natural order of things. In this sense, institutions are a way of seeing the world (Douglas 1986; Fourcade 2011).

A study of clientelism in the Indian state of Maharashtra suggests that a mental model may play a role in making oppressive institutions legitimate (Anderson, François, and Kotwal forthcoming). All villages in this state have formal democratic structures but differ, by historical accident, in the extent of the land owned by the traditional elite caste. In villages where the traditional elite owns the majority of land, village leaders manage to control village governance and use it against the interests of the poor majority. Pro-poor programs offered by the national – government of India are 75 100 percent less available in villages in which the traditional elite owns the majority of land than in those in which it does not. However, surveys indicate that the poor in the elite-dominated villages view the situation as acceptable and even quite satisfactory. They are 14 percent more likely to trust the large landholders in villages in which the government is dominated by the traditional elite than in villages not dominated by the traditional elite. It seems that in the villages dominated by the traditional elite, individuals expect little from the dominant class as a whole, get more or less what they expect, and so consider themselves fairly treated. “Legitimacy follows power” in part because power shapes the way people see the world.<sup>5</sup>

# _The culture of honor affects the efficiency of coordination_

Coordination problems occur in every society. Consider the well-known example discussed by Schelling (1960): Two individuals independently decide where to try to meet in New York City when no meeting point has been established in advance. The players gain utility only if they choose the same location. Multiple equilibria exist since all that matters is that players make the same choice. It is necessary to bring in sociological and psychological

> 4 T he dominant contributors are Engerman and Sokoloff and Acemoglu and colleagues.  References and a review are in Hoff 2003.

> 5 See Acemoglu, Reed, and Robinson (2013) for a related example.

20
# **FIGURES**

Figure 2.1: _Subjective perception of how easy (or difficult) is to start a business_ <!-- Start of picture text --> GCR : st art ing a business is easy<br>10.0<br>8.1<br>7.6<br>8.0 6.8<br>6.0<br>5.5 5.5<br>6.0 4.4 4.5 4.6 4.7 4.8<br>3.6 3.8<br>4.0 2.2 2.6 3.0<br>2.0<br>0.0<br>Bulgaria Romania Ukraine Russia Lithuania Poland Rep. Czech Latvia Rep. Slovak Turkey Europe Croatia Slovenia Hungary Estonia US<br><!-- End of picture text --> Source: Global Competitiveness Report (2002) Figure 2.2: _Bribes are rarely needed to obtain business licenses_ <!-- Start of picture text --> GCR: irregular additional payments are rare<br>10.0<br>8.0 8.1 8.1<br>7.3 7.4 7.4<br>8.0 6.7<br>6.0 4.7 5.0 5.1 5.1 5.4 5.7<br>3.7 3.8 4.3<br>4.0<br>2.0<br>0.0<br>Turkey Romania Ukraine Poland Russia Rep. SlovakRep. Czech Latvia Croatia Hungary Estonia Slovenia Bulgaria Lithuania US Europe<br><!-- End of picture text --> Source: Global Competitiveness Report (2002) Figure 2.3: _Ranking of countries according to the efficiency of courts to enforce contracts_ <!-- Start of picture text --> Contract enforcement index<br>12<br>9.7<br>10<br>8<br>6 5.2 5.45.55.55.65.86.16.77.07.07.17.17.47.67.97.98.08.18.18.28.38.48.48.48.68.88.9<br>4.5<br>4 3.6 3.7<br>2<br>0<br>Kyrgyz Serbia and Albania Slovenia Bosnia i SEE Poland Macedonia, Kazakhstan Bulgaria Uzbekistan ECA Romania Moldova CEE CIS Czech Rep. Hungary Slovak Belarus Azerbaijan Croatia Latvia Ukraine Europe Georgia Lithuania US Armenia Russia Turkey Estonia<br><!-- End of picture text --> Source: World Bank, Doing Business Database; Bank staff calculations 30
claims. Since sickness spells can and do frequently end without treatment, selection bias is pervasive.<sup>6</sup> For example, we show that children with the subsidy who visit the clinic have been actually sick weakly _longer_ , because the treatment succeeds at bringing children to the clinic whose parents tend to wait longer before seeking care.<sup>7</sup> In a companion paper (Dean and Sautmann, 2023) we report data from a follow up survey conducted in 2014 (see above). Unlike the 2013 data we use here, the 2014 survey did not include detailed health diary data, and so cannot be used to study healthcare demand conditional on health state, the central point of this paper. Instead, it focused on measures of health knowledge, use of preventive care, evidence of malnutrition, and diarrhea incidence and care. Using this broader set of measures, Dean and Sautmann (2023) do identify positive CHW effects, including complementary effects of CHW and subsidies, as we discuss in section 5.3.

Section 2 describes the policy environment and the RCT intervention and survey design. Section 3 discusses our use of the IMCI measures. Section 4 introduces a framework for demand for curative care and the effects of subsidy and information policies and section 5 describes the empirical results. Section 6 concludes with a brief discussion of policy implications.

# **2 Study Background and Data Collection**

The Malian health care system builds on a network of community health clinics or _centres de sant ́e communautaires_ (CSCOMs). A CSCOM has typically one or two trained doctors on duty and sells prescribed medications through an attached pharmacy. At the time of

> 6In most other spell data economists use, e.g. unemployment spells, there are no equivalent sources of censoring.

> 7One of the few data sets we are aware of that has panel spell data, the 1987 National Medical Expenditure Survey for the United States, includes only spells that lead to medical care use or work absenteeism. Gilleskie (1998) recognizes the selection problem but can only address it by estimating the probabilities of unobserved health events parametrically. With administrative data e.g. from insurance claims (Manning et al., 1987; Finkelstein et al., 2012), illness spells can only be studied indirectly, by grouping claims into treatment episodes, see Stoddart and Barer (1981); Hornbeck et al. (1985); Keeler et al. (1988); Santos Silva and Windmeijer (2001). A public health literature studies the covariates of the delay in seeking care for specific diseases (see Storla et al. (2008) and Nguyen et al. (2010) for reviews).

8
In exploring the existence and extent of the gender gap in a multivariate framework, the validity of findings largely depends on the plausibility of the ignorability and zero conditional mean assumptions, i.e. the extent to which the estimation strategy addresses possible unobservable household-/plot-level heterogeneity that jointly determines plot agricultural productivity and observable covariates, including whether a plot belongs to a household headed by a female. We attempt to lend as much support to the assumptions of overlapping support, ignorability, and zero conditional mean as possible by applying the added control approach and checking whether the estimations are robust to a range of sample alteration in order to see if the coefficients of interest change due to omitted variable bias. These sensitivity analyses are presented in the online appendix D.

Additionally, we consider the possibility of reverse causality. This is less of a concern for inputs as it is widely accepted in the literature that agricultural inputs may be regarded as predetermined vis-à-vis the level of output (Griliches, 1963; Dinar et al., 2007). This is due to the fact that agricultural production takes time to be completed and inputs are applied at the beginning of the season while the corresponding output is harvested at the end. It seems reasonable to assume that there is no correlation between the stochastic error and the predetermined inputs.

# 4. DATA

This study uses data from the Third Integrated Household Survey (IHS3), collected from March 2010 to March 2011 by the Malawi National Statistical Office, with support from the World 18
# **2.1 WIPO Green Patents**

We use information from the WIPO green patents data set for the period 2000-2021. This data set contains detailed information on green technology patents, inventions, and technologies from the WIPO Patentscope database, covering seven sectors: Energy, Water, Farming and Forestry, Pollution Waste, Transportation, Construction, and Products, Materials and Processes (PMP). Green technologies are defined by WIPO as “climate friendly technologies that protect the environment, are less polluting, use resources in more sustainable manner, recycle their wastes and products and handle residual waste in a more sustainable manner”. These technologies include know-how procedures, goods and services, and equipment as well as organizational and managerial procedures. WIPO systematically gathers patent data from 193 national Intellectual Property (IP) offices worldwide. The database provides information about the year of filling of the patent, the country where the IP office and the inventor are located, and technical description and status of the technology (e.g. in development, commercialization, etc.).

# **2.2 Earnings calls transcripts**

We use data from Refinitiv Eikon (formerly Thompson Reuters) on the transcripts from quarterly shareholder earnings calls meetings of publicly listed firms from 2012 to 2021, covering 10,554 firms in 82 countries. Earnings calls are key corporate events on the investor relations agenda in which senior management responds directly to questions from financial analysts and other market participants about the firm’s financial performance over the past quarter and, more broadly, discuss current developments (Hollander, Pronk, and Roelofsen, 2010; Hassan, Hollander, van Lent, and Tahoun, 2020). They consist of a management presentation and, importantly, a Q&A session which requires management to comment on subjects they might not otherwise have voluntarily proffered. The extent to which the adoption of green technologies is discussed in earnings conference calls serves as a proxy of their importance for both the firm’s management and market participants. Given that green technologies potentially account for a large share of firms’ investment decisions, they would be expected to feature in conference call discussions. In fact, these data have been increasingly used by researchers to measure firm uncertainty (Hassan, Hollander, van Lent, and Tahoun, 2019), firm sentiment (Hassan, Hollander, van Lent, and Tahoun, 2020), and proxies for whether new technologies are “disruptive” as inferred by being widely discussed in boardrooms (Bloom, Hassan, Kalyani, Lerner, and Tahoun, 2021).

4