rafmacalaba/datause-encoder-data huggingface dataset:
economies. We use the following indicators; the cost of starting a business (percent of per capita income), cost of obtaining a license (percent of income per capita), the minimum capital requirement to start a business (percent of per capita income), cost of registering property (percent of property value), the level of tax on profit and on labor and the employment cost. A more detailed description of the each variable and how each country performs in the region follow.

The World Bank Institute’s _Worldwide Governance Indicators_ measure, for over 200 countries and territories worldwide, six dimensions of governance: voice and accountability political stability and absence of violence, government effectiveness, regulatory quality, rule of law, and control of corruption. These indicators are based on several hundred individual variables measuring perceptions of governance, drawn from 37 separate data sources constructed by 31 different organizations. We are interested in measures of the government’s capacity to enforce its laws fairly, consistently, and effectively. In our model we include one governance indicator; government effectiveness.

# **1.1 The dependent variable**

The Enterprise Surveys contain sets of questions that obtain opinions on the difficulty of overcoming regulatory obligations and other important obstacles that managers must navigate around in running their businesses. The data we use measure the relative impediment of informal competition on manufacturing firms in the formal sector based on the opinions of managers asked to name rank the severity of obstacles to their operations. More specifically, firms in all countries are asked to rank the top-three obstacles that affect operation and growth of their establishment. A list of sixteen (16) potential obstacles is provided; access to finance, access to land, business licensing and permits, corruption, crime, theft and disorder, customs and trade regulations, electricity, functioning of the courts, inadequately educated workforce, labor regulations, political instability, macroeconomic instability, practices of competitors in the informal sector, tax administration, tax rates and transportation.

For each country, we record whether a manager of a firm ranked “Practices of competitors in the informal sector” as either the first, second or third biggest obstacle. We construct a variable that takes on the value of one (1) if the manager ranked the obstacle in the top three and zero (0) otherwise. The hypothesis is that formal firms that rank the informal competition as a top three obstacle are most likely to resemble informal firms since they compete in the similar sectors, in the same market, using similar technologies.
# **III. Methods**

52 of the 88 EAs in the comparison group of the larger experiment were randomly assigned to receive HTC between the months of June and September in 2009.<sup>9</sup> Then, between the months of March and August 2010, i.e. after an average of approximately 10 months, all 88 EAs were offered HTC. The sample used in this paper therefore consists of 1948 females in 88 comparison EAs, of which 1122 in 52 EAs were offered HTC in 2009, with everyone offered HTC in 2010. In the remainder of this paper we refer to the group that was offered testing and counseling in 2009 as the _HTC_ group, and those who were offered HTC only in 2010 as the _control_ group.

HTC took place at the homes of the core respondents where they were invited to receive counseling and rapid testing for HIV, HSV-2, and syphilis by a trained counselor.<sup>10</sup> Overall acceptance of HTC was high at 98%, with no differences between the two study arms. Malawian nurses and counselors certified in conducting rapid HIV tests through the Ministry of Health HIV Unit HCT Counselor Certification Program conducted HTC. Testing and counseling was performed in a private location at or near the participant’s house. Whole blood samples were obtained using a finger-stick. The teams conducting HTC at follow-up were blinded to the testing treatment status of the subjects and were independent of the survey teams that conducted household surveys and administered achievement tests (discussed below).<sup>11</sup> Ethics review committees at the National Health Sciences Research Council (Malawi), the University of California at San Diego (USA), and George Washington University (USA) approved the study design. Further details of the HTC procedures can be found in Appendix A.

> 9 Details of the randomization for the HTC experiment can be found in Baird et al. (2012).

> 10 Rapid tests for syphilis were only performed during the first round of HTC as its prevalence in this sample was found to be less than 1%. The effects of this intervention should be considered noting that the subjects were invited to receive counseling and testing not only for HIV but for HSV-2 and syphilis as well.

> 11 HTC counselors could deduce the HTC treatment status of the subjects who had tested positive for HIV or HSV-2 at baseline. To avoid unnecessary burdens on the subjects, re-testing for the previously positive test was avoided in such circumstances, meaning that the HTC counselor could deduce that the individual had been tested before for the foregone STI test. Furthermore, to protect the privacy of all individuals, every individual in both the HTC and control groups were visited at follow-up: those who had tested positive for only one STI were tested for the other, while those who had tested positive for both were given a short survey. The counselors were blinded to the treatment status of everyone else, i.e. those in the HTC group who tested negative at baseline or those in the control group who were not tested at baseline.

7
# **1 Introduction**

Consumer protection, in the broader sense, refers to the laws and regulations that ensure fair interaction between service providers and consumers. Government intervention and regulation in the area of consumer protection are justified on the basis of inherent information asymmetries and power imbalances in markets, with producers or service providers having more information about the product or service than the consumers. A consumer protection framework generally includes the introduction of greater transparency and awareness about the goods and services, promotion of competition in the marketplace, prevention of fraud, education of customers, and elimination of unfair practices.

Consumer protection frameworks in the financial service industry are evolving as products become more complex and a greater number of people rely on financial services. An effective consumer protection framework includes three complementary aspects. First, it includes laws and regulations governing relations between service providers and users and ensuring fairness, transparency and recourse rights. Second, it requires an effective enforcement mechanism including dispute resolution. Third, it includes promotion of financial literacy and capability by helping users of financial services to acquire the necessary knowledge and skills to manage their finances.

The recent crisis highlighted shortcomings in the existing consumer protection frameworks in high income countries and prompted a number of broad-ranging reforms. The crisis also made apparent the low levels of financial capability among users of financial services in developed countries. Lack of effective disclosure and the existence of deceptive advertising on the provider’s side, and failure to understand financial products on the user’s side contributed to the collapse of the sub-prime mortgage market in the United States. However, the problem is not limited to developed markets with highly complex products. In emerging markets, the challenge in this area is even greater.

Most countries have witnessed an unprecedented expansion of the financial services industry in the decade preceding the crisis. Hundreds of millions of people opened bank accounts, started transferring payments electronically and took out consumer loans. In most cases, the development of the retail financial services industry preceded the development of consumer protection legislation. Bosnia and Herzegovina, Morocco and some states in India saw indebtedness rise sharply among microfinance borrowers in 2009, threatening sustainability of these markets.<sup>1</sup> Continued progress in expanding financial access requires introduction of basic protections for the clients of financial services. Knowing that their rights are effectively protected may bring in new customers to the financial sector, and encourage the uptake of new

> 1 See Gokhale (2009), Reuters (2009), and Reille (2009).

2
procyclically, downgrading countries during bad times and upgrading them during good times. We will not be able to disentangle these two observationally equivalent hypotheses, but we are able to observe whether downturns and rallies take place before downgrades and upgrades. Dynamics effects are also interesting because the effect of upgrades and downgrades can dissipate over time.

The event study looks at country risk and stock market spreads (domestic stock markets prices relative to the U.S. S&P500 index) in a 10-day window around an upgrade or downgrade. All spreads and prices are set to 100 at day –10, in that way we can easily measure the cumulative effects over time and we can, at the same time, compare spreads across countries.

To perform the event studies we work with “clean events,” i.e. upgrades and downgrades that do not overlap in windows of +/- 10 days. This distinction is important when considering an event window, to be able to isolate the effect of each change in rating. Figure 1 plots the ratings over time for three major rating agencies for a sample of countries. The figure suggests that many upgrades and downgrades across rating agencies occur simultaneously across agencies. In particular, the East Asian countries are downgraded during the Asian crisis and upgraded afterwards. Only few changes take place before the crisis in the case of Malaysia and South Korea.<sup>5</sup>

# **3. Data**

Our data set contains daily series of EMBI spreads, stock returns, interest rates, and credit ratings. We work with 16 emerging markets including East Asian, Eastern

> 5 For a detailed study on how ratings are changed, see Cruces (2001).

10
**Table 7: Sales price regressions for agricultural land**

||**By type**|**of land**||**Commercia**|**l agric. land**||
|---|---|---|---|---|---|---|
||**Commercial**|**Personal**|**With reg**|**istry data**|**With bu**|**yer data **|
|Area (ha)|0.1081***|-0.2159***|0.2584***|0.2377***|0.1897***|0.3439***|
||(0.0022)|(0.0046)|(0.0052)|(0.0054)|(0.0086)|(0.0158)|
|Area^2|-0.0241***|0.0563***|-0.0946***|-0.0911***|-0.0554***|-0.1083***|
||(0.0015)|(0.0019)|(0.0043)|(0.0042)|(0.0063)|(0.0129)|
|Buyer is legal entity|0.2607***|0.4668***|0.2095***|0.2685***|||
||(0.0051)|(0.0136)|(0.0131)|(0.0198)|||
|# transactions|<br>-0.0121***|<br>-0.0427***|<br>-0.0073*|<br>-0.0107**|0.0043|-0.0523***|
|in village|(0.0015)|(0.0029)|(0.0042)|(0.0042)|(0.0080)|(0.0179)|
|Field area (ha)|-0.0034|-0.0063***||0.0269***|-0.0088|0.0152|
||(0.0028)|(0.0024)||(0.0075)|(0.0093)|(0.0290)|
|Field area^2|<br>0.0050***|<br>0.0096***||<br>0.0011|<br>0.0036**|<br>-0.0001|
||(0.0004)|(0.0005)||(0.0011)|(0.0016)|(0.0040)|
|Unmapped area|<br>-0.3055***|<br>-0.0351||<br>-0.1825***|<br>-0.3038***|<br>0.1545|
|share|(0.0197)|(0.0236)||(0.0649)|(0.1099)|(0.2026)|
|<1% of area||||<br>0.0045||<br>-0.0050|
|unregistered||||(0.0097)||(0.0268)|
|1-10% of area||||-0.0003||-0.0263|
|unregistered||||(0.0086)||(0.0239)|
|> 10% of area||||-0.0631***||-0.0944**|
|unregistered||||(0.0117)||(0.0375)|
|Owner area <1%||||-0.0122||0.1030***|
|||||(0.0136)||(0.0358)|
|Owner area 1-10%||||-0.0189**||0.0045|
|||||(0.0076)||(0.0221)|
|Owner area > 10%||||<br>-0.0091||<br>0.0967*|
|||||(0.0156)||(0.0518)|
|Largest user’s||||<br>0.2054***||<br>0.3306***|
|<br>cult. area share||||(0.0203)||(0.0654)|
|Buyer is the largest||||-0.0987***||-0.1227***|
|<br>user in field||||(0.0227)||(0.0366)|
|>5 registered users||||0.0120||0.0120|
|||||(0.0121)||(0.0385)|
|Buyer's area (ha)|||||-0.0667***|<br>-0.0566|
||||||(0.0095)|(0.0810)|
|Buyer's area^2|||||0.0147***|0.0215**|
||||||(0.0014)|(0.0084)|
|Buyer uses <33%|||||<br>-0.2075***|<br>-0.2691*|
|<br>of village land|||||(0.0348)|(0.1456)|
|<br>Buyer uses 33-50%|||||<br>-0.2922***|<br>-0.2200|
|<br>of village land|||||(0.0384)|(0.1565)|
|<br>Buyer uses >50%|||||<br>-0.3082***|<br>-0.3289**|
|<br>of village land|||||(0.0377)|(0.1554)|
|<br>No. of obs (farms)|173,651|97,111|25,719|25,719|<br>9,166|<br>2,135|
|AdjR-squared|0.3820|0.5067|0.4904|0.4999|0.6649|0.8173|

_Note:_ Parcel characteristics, year dummies, OTG fixed effects and a constant included but not reported (see appendix table 5 for estimated coefficients). Standard errors in parentheses (* p<0.10, ** p<0.05, *** p<0.010).

28
Table 1: Daily Resting Energy Expenditure (REE) and Activity Level (AL) <u>estimates</u>

|Panel A: REE (calories/day) from National Family Health|Survey (NF|HS)|
|---|---|---|
|Ever married women 15-49<br>Women 15-49|Men 15-54|Children 0-3|
|1998 (NFHS-2)<br>1128<br>.|.|502|
|1998 Rural<br>1114<br>.|.|499|
|1998 Urban<br>1169<br>.|.|513|
|2005 (NFHS-3)<br>1145<br>1140|1496|492|
|2005 Rural<br>1126<br>1122|1471|485|
|2005 Urban<br>1189<br>1177|1542|517|
|2015 (NFHS-4)<br>1180<br>1169|1531|514|
|2015 Rural<br>1161<br>1151|1510|507|
|2015 Urban<br>1221<br>1205|1570|532|
|Panel B: AL (rest=1) from Time Use Survey (TUS)|1998-1999||
|Men 15+<br>Women 15+|Boys 6-14|Girls 6-14|
|1998-99 mean<br>1.93<br>1.89|1.49|1.51|
|1998-1999 SD<br>0.47<br>0.34|0.23|0.23|
|1998-99 Rural mean<br>2.03<br>1.96|1.50|1.53|
|1998-99 Urban mean<br>1.69<br>1.71|1.47|1.46|

_Source_ : Authors’ analysis based on 1998-1999 India Time-Use Survey (TUS) and National Family Health Survey (NFHS) rounds 2, 3 and 4. _Note_ : Panel A is based on applying the equations in (Henry 2005) to heights and weights reported in NFHS. Panel B is based on using the matched activity factors from FAO (2001) and activities reported in the TUS (see Appendix Table S.2). Reported values are population statistics using survey sampling weights.

29
19

**Table S. 3 – continued from previous page**

|Sector<br>VARIABLES|Rural<br>Female 15+|Male 15+|Female 6-14|Male 6-14|Urban<br>Female 15+|Male 15+|Female 6-14|Male 6-14|
|---|---|---|---|---|---|---|---|---|
|dumcollectfood|0.058***||0.038*||0.057***||0.087*||
||(0.005)||(0.020)||(0.008)||(0.050)||
|dumhuskpaddy|0.182***||0.569***||0.070*||||
||(0.017)||(0.096)||(0.037)||||
|dumgrindgrain|0.006||0.197||0.077**||||
||(0.019)||(0.124)||(0.033)||||
|dumdung|0.021***||0.076**||0.036||0.212||
||(0.007)||(0.032)||(0.025)||(0.254)||
|dumcwater|0.048***||0.075*||0.030***||0.218*||
||(0.007)||(0.040)||(0.008)||(0.111)||
|dumkitchengarden|-0.034**||0.034||0.051||||
||(0.016)||(0.085)||(0.046)||||
|25.hh<br>~~n~~ic2|||||-0.047|0.158|0.006|0.248*|
||||||(0.070)|(0.186)|(0.178)|(0.135)|
|98.hh<br>~~n~~ic2|||||-0.120|0.013|||
||||||(0.223)|(0.219)|||
|16.hh<br>~~n~~co2|||||0.090|0.236|-0.136||
||||||(0.094)|(0.158)|(0.147)||
|29.hh<br>~~n~~co2|||||0.024|0.101||0.049|
||||||(0.057)|(0.110)||(0.143)|
|92.hh<br>~~n~~co2|||||0.032|0.011|0.087|0.044|
||||||(0.037)|(0.062)|(0.101)|(0.095)|
|82.pr<br>~~n~~ic2|||||-0.401|-0.302***|||
||||||(0.300)|(0.113)|||
|9.hh<br>~~n~~ic2||||||-0.342|||
|||||||(0.506)|||
|41.pr<br>~~n~~ic2||||||-0.189|||
|||||||(0.192)|||
|71.pr<br>~~n~~ic2||||||0.171|||
|||||||(0.114)|||
|72.pr<br>~~n~~ic2||||||-0.161<br>(0.333)|||
|98.pr<br>~~n~~ic2|||||||-1.099***<br>(0.337)||
|Constant|3.846***|0.923|0.195|-0.558|5.609***|3.620**|3.098|2.069|
||(0.898)|(1.101)|(2.313)|(2.011)|(1.081)|(1.781)|(2.694)|(2.500)|
|Observations|17,346|17,930|3,666|4,242|8,014|8,482|1,507|1,763|
|R-squared|0.630|0.619|0.481|0.433|0.567|0.529|0.370|0.589|

_Source_ : Authors’ calculations using India Time-Use Survey 1998-1999. _Note_ : Standard errors in parentheses. *** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1. All regressions use sample weights. National Industry Classification (NIC) uses 1987 codes while National Classification of Occupations (NCO) uses 1968 codes, with 100 where missing <u>(e.g.</u> students or women not in the labor force).
- 19 -

# IV. PROJECT CIATA

4.01 CIATA, a second major effort at property tax reform, differs from the Rio case in several respects. First, it is a program involving a large<sup>number</sup> of municipalities rather than a one-time effort in a single city. Second,<sup>it</sup> is administered by the federal government. Third, it is primarily aimed at smaller jurisdictions.

4.02 Like the Rio case, CIATA contains some technical and procedural innovations that might be applied in other countries: the use of simple identification and valuation techn*ques, and the use of computers<sup>in small</sup> jurisdictions. CIATA's more important lessons lie in the design and execution of technical assistance programs, particularly in the use of standardized packages of technical assistance to reach large numbers of jurisdictions at low cost.

4.03 The CIATA program was initiated by the Federal Government in 1973. It was largely a response to persistent low tax revenues in smaller municipalities, particularly those in the Northeast.

4.04 The Federal Government attributed these low yields to problems in municipal tax laws and weaknesses in local tax administration. The<sup>legal</sup> definition of value was inconsistent with the methodology used to derive it. Properties were missing from the tax rolls. Valuations were arbitrary. Procedures for monitoring collections were ineffective.

4.05 The Government's response was to establish a major program of technical assistance, terme4 CIATA.UI CIATA consists essentially of a standardized package of technical assistance executed over a 1-year<sup>period in</sup> a designated group of municipalities. Within each municipality,<sup>the program</sup> produces: (a) a new tax code;

- (b) a new fiscal cadastre--incorporating revised maps, new property records, a new table of unit costs and revised assessments on all properties--and

- (c) a set of billing records (the tax roll and individual tax bills) to be used in the first year following the project.

4.06 Since 1973, CIATA projects have been completed in 1,282 municipalities. As shown in Table 3, the program has averaged<sup>about 100 projects</sup> per year. Most have been small. The number of property units per project<sup>has</sup> averaged 6,440.

1/ _Convenio de Incentivo ao Aperfecicoamento Tecnico-Administrativo das Munlc.palldades._
The review summarized assessment frameworks across telemedicine and mobile health and generic conceptualizations for DHI assessment. Using the structure of the EUnetHTA core model (a methods framework developed by European national HTA agencies [22]), a list of categories was elicited to screen against and map the scope of included publications. The list included 12 categories: health problem and current use of technology; safety; clinical effectiveness; patient and social aspects; economic; legal; ethical; organizational; usability; data security; and technical aspects and stability. In total, 11 value assessment frameworks were identified. The most often discussed assessment domains were safety, clinical effectiveness, usability, economic aspects, and interoperability which were discussed in seven of the frameworks, while organizational, usability, data security, and technical considerations were discussed in six of the frameworks. The least attention was devoted to the understanding of ethical (two out of 11 frameworks) and legal aspects (one out of 11 frameworks).

The review proposed several recommendations regarding the criteria to be considered in the measurement of value of DHIs, as detailed in Table 3.

**Table 3 Summary Findings from Review of Existing DHI Analytical Frameworks**

|**FIVE RECOMMEN**|**DATIONS**|
|---|---|
|**Choice of**<br>**comparator**|The value of a DHI should be determined by the incremental advantage<br>compared to the current standard of care.|
|**Multi-stakeholder**<br>**perspective**|The value of a DHI should quantify incremental differences it delivers to all<br>beneficiaries.|
|**Organizational**<br>**impact**|The value of DHIs should be conditional on the health care system<br>preparedness to consume efficiency gains and assurance that data generated by<br>DHI will be accessible by health care professionals.|
|**Multidimensional**<br>**outcomes**|The value delivered by digital health solutions should consider multiple<br>dimensions such as clinical, organizational, behavioral, and technical.|
|**Interoperability**|Connectivity to other data sources must be considered in the evaluation of a<br>digital health solution.|
|**ONE METHODOL**|**OGICAL SUGGESTION**|
|**Value aggregation**<br>**function**|Given the multiple criteria to be considered in the pricing and reimbursement<br>process, each value attribute should be weighted in any calculations based on<br>the preferences of chosen stakeholder groups, and the aggregate value score for<br>each DHI should be estimated.|

_Source: Adapted from Kolasa et al (2020)_ .[6]
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