rafmacalaba/data-use-mentions-extended huggingface dataset:
27 earlier findings by Blau (1986) regarding self-employed urban males; on the other hand, Blau finds that the other sub-groups of own-account workers indeed had lower earnings (i.e. urban females, and rural males and females).<sup>1 4</sup> Although detailed information on the occupational codes is unavailable, the broad single-digit categories are known, and are included as explanatory variables in order to eliminate any omitted variable bias introduced by differential pay lines across sectors of production. The composition of employment is fairly disperse across the 10 occupation categories, as shown in Table 5. This dispersion is corroborated by data from the 1995 labor force survey (Malaysia Department of Statistics, 1996). The coefficients on occupations 1 through 9 are measured relative to the income of a worker with similar characteristics in occupation 0, which consists of the police and the armed forces. The returns to the various occupational categories are large in magnitude, especially for agricultural workers (occupation 6) and unskilled workers (occupation 9) who earn far less, indicated by negative coefficient values.

|**Tab**|**le 5: Employment Composition by Occupation**||
|---|---|---|
|**Occupation Category**|**Description**|**Share (%)**|
|Occupation 0|Police and armed forces|3.6|
|Occupation 1|Managers, senior officials|4.1|
|Occupation 2|Professionals|4.1|
|Occupation 3|Technicians, associate professionals|6.1|
|Occupation 4|Clerks|8.0|
|Occupation 5|Service workers, shop and market sales|9.1|
|Occupation 6|Skilled agricultural workers|18.0|
|Occupation 7|Craft-related workers|4.8|
|Occupation 8|Plant and machine operators|7.0|
|Occupation 9|Elementary occupations: sales, services
categories that we call business functions (BF). To this, we add a vertical dimension that represents the range of technologies that can be used to perform the key tasks in each business function. The grid encompasses 1Since the classic work of Ryan and Gross (1943) and Griliches (1957) on hybrid corn, many have applied this approach to measuring technology in establishments in other sectors. For example, Davies (1979) studies the diffusion of 26 different manufacturing technologies, each typically relevant in only a single narrow sector, Trajtenberg (1990) measures the presence of CAT-scanners in hospitals, Brynjolfsson and Hitt (2000); Stiroh (2002); Bresnahan, Brynjolfsson and Hitt (2002); Akerman, Gaarder and Mogstad (2015) measure the presence of some ICTs such as computers or access to the internet. Other efforts include the Survey of Manufacturing Technology by the Census Bureau discontinued after 1993, which covers 17 specific technologies, including numerically-controlled machines, computer-aided design or engineering technologies, programmable controllers and local area networks (see Dunne (1994)); or the Canadian Survey of Advanced Technologies with 41 and 50 technologies, depending on the round (see for example Boothby, Dufour and Tang (2010)). More recently, the Advanced Business survey, Acemoglu et al. (2022), also administered by the US Census Bureau and that focused on five generic, frontier technologies: AI, robotics, dedicated equipment, specialized software and cloud computing. Unlike the previous studies, the Advanced Business Survey asks for the intensity with which the firm uses these advanced technologies.

1
# **5 Concluding Remarks and Policy Considerations**

This study provided one of the first comprehensive investigations of the data availability and data constraints associated with a more systematic application of the UNICEF conceptual framework emphasizing the interrelationship among access to adequate food security, environment and health, and child care practices in the prevalence of malnutrition rates among children in developing countries. Using detailed demographic and health survey data from Bangladesh, Bolivia, Cambodia, Ethiopia, Indonesia, Nepal and Zimbabwe, a comparison is carried out of the ideal variables summarizing the various dimensions or components of food security, environment and health, and child care against the measures available from current household surveys. These comparisons serve to highlight the limitations of most data sets and the potential gains associated with the collection and availability of additional information.

Bearing in mind the limitations imposed by the data available, the report also provided a practical diagnostic framework of the main correlates of child malnutrition that could be applied to identify potential “binding constraints” towards the effort to reduce child malnutrition. Specifically, the UNICEF conceptual framework is “operationalized” by serving as a guide for investigating the relationship between the prevalence of malnutrition in the country and inadequate levels and access to the three pillars summarizing the underlying causes of malnutrition. Next, for each indicator available from the survey used in country, a definition of “adequacy” is constructed using thresholds based on accepted international standards. The report aims to provide a “helicopter view” of the extent to which nutritional outcomes, as measured by a child’s height‐for‐age Z score (HAZ) at any given point in time, as well as over time, are associated with inadequate food security, inadequate environment and health, and inadequate child care practices. In consideration of the complexity of the linkages between the underlying causes of malnutrition and the economic situation of the family, the analysis is also carried out separately for resource‐rich (top 60%) and resource‐poor (bottom 40%) households based on an
The implementation of the projects was done by the PPH, under supervision from the Ministry of Housing. No specific evaluation of the administrative simplicity is known. However, the responsible unit within the ministry of Housing consisted in an administrative, project-by-project, follow-up. At the beginning of the 1990s, a computer database was developed at the Ministry of Housing which included all project records. However, no permanent evaluation and monitoring framework existed.

As often, slum upgrading projects generated incentives for households which affected the program efficiency. First, the government’s public commitment to dealing with slums gave households an incentive to migrate to slums, in the hope of finding cheap housing in future. Locally, when a State program was initiated in a particular slum area, the resident population would suddenly increase, which made budget and physical forecasts obsolete. Furthermore, households granted _relogement_ units had strong incentives to sell them immediately and return to living in the slums. Frequently, _relogement_ and _recasement_ operations were not accompanied by sufficiently rigid measures to prevent redevelopment of the vacated slums. In this regard, lack of coordination with municipalities whose responsibilities were not clearly defined, became a definite problem. Local governments had no incentives to eradicate slums because these were seen as a trigger for State intervention measures, resulting in construction of housing units in their jurisdictions through national budget financing.

Efficiency was also low. A study by the Ministry of Housing on the projects managed by the PPH from 1983 to 1995 revealed the following: projects included distribution of serviced land plots ( _recasement_ ) and completed housing units ( _relogement_ ). Although 80% of the land plots had been distributed to beneficiaries before 1987 and 96% before 1990, 29% of the parcels were not constructed in 1997, and only 46% included completed and occupied dwellings. The population living in the parcels represented only 30% of initial program projections. In the case of _relogement_ programs, the rate of completion was higher (80% of the projected housing units had been constructed) and vacancy rates were
allowing a more robust comparison of living standards. Adequate measurement of living standards has long underpinned the frequent surveys of consumer goods prices and less frequent microeconomic surveys of household expenditure, which in turn have allowed calculation of poverty and inequality measures themselves often based on an elaborate and sophisticated axiomatic framework (Atkinson and Bourguignon, 2000).

When it comes to micro analysis of individual firms, including financial institutions, conventional business accounts – increasingly harmonized worldwide -- provide a unifying format. To take the case of banks, by simply assembling published financial accounts of the major banks worldwide (and not requiring any special survey effort), a commercial firm (Bureau van Dijk) has produced the large _Bankscope_ database that has been extensively used for analyzing international differences in banking conditions and performance. (More systematic cross-country compilations for various national aggregates of banking institutions are included in the OECD _Profitability of Banks_ publication – though only for 30 industrial countries).

The hallmark of these systems is the attempt to cut through inessential or superficial differences in national concepts by define a reduced set of primitive concepts and provide guidance as to how to map national measures onto the primitive concepts. It is in this spirit that the proposed development of national basic financial access indicators should be seen.

The task of assembling data on financial access and microfinance still awaits its guiding conceptual framework. It is not enough to measure financial service usage. We also need to understand it. To do so, what could be more natural than to distinguish between the demand and supply side of the question? First, of what benefit is financial access; second, what hinders access?

# _The demand side: Benefits of access_

In principle, and given enough knowledge, poor and low income households should be willing to pay for financial services up to the cash equivalent of the services value to them. There will be external benefits also, but the direct benefits are likely to dominate. This is why, although private and public sector perspectives on the benefits of access might initially seem far
about aggregate education and training costs. The employer-employee dataset allows detailed analyses of hypotheses related to both firms and individuals.

Unfortunately, many of the variables in the 1994 round of the Ghana RPED dataset have very few observations. This is the case, for example, for the share of exports in output, expenditures on research and development, and foreign licenses. Hence, these variables are excluded, so that the regression analysis includes relatively few enterpriselevel controls.

I use the so-called general-to-specific econometric methodology in the regression analysis. I apply this methodology by formulating a general model and then reducing it to a parsimonious specification by eliminating statistically insignificant variables one by one, while focusing mainly on the determination of wages. The more parsimonious specification includes only statistically significant variables in the wage equation.

The general wage model contains explanatory variables in levels and some are also included in quadratic form, hence allowing for nonlinearities in the data. The natural log wage equation or the production function may be quadratic in variables such as experience. This way of modeling may capture that the return to experience is not constant but rather decreasing over the life cycle. Additionally, I introduce dunmmy variables that take the value of one if, for example, the worker is a member of a trade union and zero otherwise. Inclusion of this variable may reveal whether there is a wage or productivity premium related to union membership.

I use simultaneous single-level statistical models. These models may cause aggregation biases equivalent to problems produced in the learning achievement literature. In this literature, workers are the units of observation and firms are included in 6
# **B Abbreviations in Feature Names**

Figure S4 and Tables S8, S2, and S7 use a set of abbreviations in CDR feature names. This appendix lists the relevant abbreviations.

- BOC: Balance of contacts

- CD: Call duration

- IPC: Interactions per contact

- IT: Interevent time

- NOI: Number of interactions

- PPD: Percent pareto durations (percentage of call contacts accounting for 80% of call time)

- PPI: Percent pareto interactions (percentage of contacts accounting for 80% of subscriber’s interactions)

- RD: Response delay

- RR: Response rate

- WD: Weekday

- WE: Weekend

# **C Cost and Speed Calculations**

In the discussion section we provide a cost and speed comparison between targeting methods, as some of the value-add of the phone-based targeting approach relies on how cheap and quick it is compared to asset, consumption- or CBT-based targeting approaches. Administrative data on targeting costs was not collected as part of the TUP program, so we turn to other studies of program targeting to estimate the costs of CBT and asset-based (or PMT) methods. We treat the costs of an asset index-based and PMT approach as equivalent in this section, as they both require comprehensive household surveys.<sup>14</sup> We identify

> 14In practice, an asset-based approach may be slightly cheaper than a PMT, as it does not require conducting a consumption module for a subset of surveys to train a PMT.

31
15 15 with varying degrees of protectionism in government procurement.<sup>7</sup> As in the cross-country regression, we control for other importer-specific variables that are likely to correlate with both protectionism in government procurement and trade openness: dummies for membership in the WTO, WTO GPA, EU, and GDP (in logs), GDP per capita (in logs) and the average index of quality of institutions (fixed over time). These controls collected in the term are thus interacted with the internal trade dummy. Finally, we control also for the influence of time-varying determinants of bilateral imports that come from entry into trade ii,tt VV agreements: WTO membership and PTAs. Because of our interest in indicators that code national laws in government procurement, we include dummies for membership of both the importer and the exporter in the WTO, WTO GPA, PTAs without provisions on government procurement, PTAs with provisions in government procurement (except the EU) and the EU. The data on WTO and EU memberships come from the CEPII Gravity Database, whereas information on WTO GPA membership comes from the WTO website. Data on PTAs membership and provisions on government procurement are sourced from the Deep Trade Agreements Database (Mattoo, Rocha, and Ruta 2020).

Following the literature, the gravity models are estimated with the Poisson estimator (hence the exponential function in the gravity equation), which permits to include zero trade flows (around 30 percent of our sample) and accommodates heteroskedasticity in trade data (Silva and Tenreyro 2006). Following Egger and Tarlea (2015), we cluster the standard errors by importer, exporter and undirected country pair (the _ij_ and _ji_ pairs belong to the same cluster).

Unlike the literature that deals with estimation of trade effects of trade agreements (Baier and Bergstrand 2007; Piermartini and Yotov 2016), our empirical specification lacks bilateral fixed effects, because our variables of interest –indicators of protectionism in government procurement laws – are time-invariant (their interaction with the internal trade dummy would
Meon and Sekkat (2005) and Lambsdorff (2004) find evidence that the negative impact of corruption on economic growth and productivity, respectively, becomes worse as the quality of governance deteriorates. Similarly, Loayza et al. (2004) provide evidence that heavier regulation goes hand in hand with worse governance in adversely affecting economic growth and macroeconomic volatility. Salinas-Jimenez and Salinas-Jimenez (2007) show that corruption reduces both the level and growth rate of total factor productivity and the main channel of this effect is the reduction in technological change.

Among the micro-level studies, Fisman and Svensson (2007) is one of the early studies employing firm-level data from Ugandan Industrial Enterprise Surveys covering 243 firms in 1998. They investigate the impact of corruption and taxation on growth, instrumenting bribe and taxation with their industry-location averages to address a potential endogeneity problem. After excluding outliers, they find that a 1 percent increase in the bribe rate is associated with about a 7 percent decrease in growth. They do not find any significant relationship between taxation and growth. Another micro-level study, carried out by Aghion et al. (2016), employing data from the U.S. Census Bureau for 1983-2007, finds that higher corruption decreases the positive effect of taxation on growth, innovation, and entry.

Diwan et al. (2015) employ data from 469 firms connected to the Mubarak regime in the Arab Republic of Egypt during 1996-2006 to analyze whether they received favorable regulatory treatment and had a negative impact on productivity. They find that those firms were more likely to benefit from trade protection, energy subsidies, access to land and regulatory enforcement and there was a slowdown in the employment growth and productivity in the industries after their entry into them, as that skewed the distribution of employment towards less productive and smaller firms. De Rosa et al. (2010) use firm-level data from the EBRD/World Bank Business 7
# V – Do Migration and Remittances Increase Well-Being and Satisfaction?

Like the other countries of Central Asia, Uzbekistan has high average life satisfaction for its income level. Figure (6) below presents the average levels of life satisfaction from the LITS 2016 survey, which was conducted in a comparable way across nearly all countries in Europe and Central Asia. By that measure, Uzbekistan has the highest average life satisfaction of any country in the region.

**Figure 6: Average Life Satisfaction in Europe and Central Asia**

<!-- Start of picture text -->
1.0<br>UZB<br> 0.9<br>TJK<br> 0.8<br>DEU<br> 0.7<br>KGZ<br> 0.6<br> 0.5<br>TUR<br> 0.4<br> 0.3<br>UKR<br> 0.2<br> 0.1<br> ‐<br>3.3 3.5 3.7 3.9 4.1 4.3 4.5 4.7 4.9<br>log GDP per capita<br>Overall Life Satisfaction<br><!-- End of picture text -->

_Source: Life in Transition Survey 2016_ Although it is measured using a different scale (from 1= not satisfied at all, to 5= completely satisfied), the finding that there is relatively high life satisfaction in Uzbekistan is largely replicated in L2CU. In any given round of the L2CU panel survey, about 90 percent of respondents were moderately satisfied to completely satisfied, while only about 10 percent of respondents were completely unsatisfied or not satisfied. However, although the aggregate statistics on life satisfaction remain quite stable at the national level, there is substantial churning at the individual level. The descriptive statistics presented in table (12) report transitions in life satisfaction at the individual level. Stability ranges from
exchange, which is the diplomatic representation of each country of destination of Egyptian migrants in Egypt at time of migration. It is a dummy variable equal zero if there is no evidence of diplomatic exchange and is equal one if there is evidence of diplomatic exchange at the level of charg ́e d’affaires, minister, ambassador or other. For identification of equation (3), we use the number of active armed conflicts that is both country and year specific from the Uppsala Conflict Data Project (UCDP). Equations (4a), (4b) and (4c) estimate the effect of illegality on the logarithm of hourly wages, conditional on return migration. Three models are separately estimated, relying on the percentile distribution of migration duration. In equation (4a), we consider individuals who belong to the lowest 33rd percentile of the distribution (with two years of migration duration or less). In equation (4b), we consider individuals who belong to the middle 33rd percentile of the distribution (with 3 to 5 years of migration). In equation (4c), we consider individuals who belong to the highest 33rd percentile of the distribution (with 6 years of migration or more). The predicted logarithm of hourly wages for illegal migrants, and legal migrants in equations (4a) to (4c) are reported in the bottom of the table.

46
22 Further, the product design captures damage from excessive rainfall independent of tank storage levels. Excessive rainfall invariably leads to crop damage, particularly in the crop flowering stage. It can also lead to flash-flooding and waterlogging. However, if localized flood data are available, there is scope to further refine the product by carrying out a multivariate correlation analysis between excess rainfall, flooding and tank storage levels. Such a study may show that the risks of excess rainfall affect irrigated and non-irrigated farmlands differently, since flash-floods are caused by inundation in tanks (from which non-irrigated lands would be immune). However, in the absence of localized flood data currently, no such conclusion can be drawn. Thus, the excess rainfall cover for the product has been structured independent of tank water levels.

# **9. Conclusion**

This paper captures the pilot experience of developing a weather index insurance product for irrigated agriculture in Sri Lanka, from a practitioner’s perspective. Our experience has shown that incorporating irrigation water levels contributes to an improved ‘hybrid’ index insurance product, thereby expanding the use of rainfall index insurance even to irrigated farmlands.

The results of the pilots in two districts show that the hybrid index product is better correlated to crop damage than the pure rainfall index for farmers with access to major irrigation. It is especially better at detecting the incidence and severity of actual losses.

It is important to acknowledge that there may be other types of indices (that may also improve correlation) which can be used in combination with tank storage levels, such as a yield index and a vegetative index in particular contexts, and their relevance in terms of costs and benefits can be compared.

While the pilot exercise was limited to a few seasons and regions, and the experience is too recent to draw general conclusions about the sustainable performance of the hybrid weather index insurance product, the experience so far in Sri Lanka suggests that index insurance can be successfully used in irrigation contexts with relevant improvements in product design, and the product is a