rafmacalaba/datause-encoder-data huggingface dataset:
bribery. On 15 February 1999, the Organisation for Economic Cooperation and Development (OECD) Anti-Bribery Convention came into force, requiring signatory countries to legislate measures intended to combat foreign bribery in their own jurisdictions. To date, 41 countries have signed the Convention, and hundreds of cases of foreign bribery have been investigated worldwide.<sup>6</sup> The number of observed cases, however, is not sufficient for the computation of a reliable _annual_ measure. In light of this, this paper consolidated data culled from corruption cases reported over a 15-year period or from 1998 to 2012. However, as more and more countries sign the OECD Anti-Bribery Convention, and as more cases of cross-border corruption are exposed, there will arise the possibility of computing the PACI for shorter periods of time. Increased data availability would also enable the computation of more granular measures, which pertain to specific sectors of the economy or particular segments of public administrations.

The PACI is described in the next section. Section II introduces the dataset and presents the computation of the index. Section III shows that the PACI is highly correlated with existing perception-based measures of corruption and considers the determinants of the observed differences. Section IV discusses available evidence regarding the assumptions that ensure the validity of the index, which are described in detail in Appendix A. Section V concludes **.**

# **I. The Public Administration Corruption Index**

To illustrate the mechanics of the PACI, it is necessary at the outset to distinguish cases of cross-border corruption (involving firms from the headquarters country _i_ bribing public officials in the foreign country _j_ ) based on where they were _enforced first,_ that is, the country whose judiciary was the first to take action on a particular corruption case. The vast majority of cross6 See Carr and Outhwaite (2008) and http://www.oecd.org/daf/anti-bribery/oecdantibriberyconvention.htm. 4
includes more limited socio-demographic variables than the DHS but are sufficient for this study. For Lesotho, there is only data for females because males were not asked the questions about condom use. The data is weighted using the sample weights suggested by the data provider and the standard errors are clustered at the enumeration area level.

The samples of the surveys include women ages 15 to 49. There is more variation in the ages of the men; in Burkina Faso, Cameroon, Ethiopia, Ghana, Guinea, Lesotho, Rwanda, and Senegal, men are ages 15-59, in Kenya, Malawi, and Zimbabwe, men are ages 15-54, and in Côte d’Ivoire and Tanzania, the men are ages 14-49.

Table 1 compares condom use with different categories of partners for males and females, with statistical significance indicated by the p-values from T-tests. Table 1a gives the percentages and standard errors for whether males and females used a condom during the last sexual intercourse they had, regardless of with whom it was. Table 1b shows the percentages and standard errors for males and females for condom use at the last sexual intercourse with a spouse, and table 1c is if a condom was used at the last sexual intercourse with someone other than a spouse. The p-values indicate whether the results are significantly different by gender. The analysis in table 1c includes single, divorced, separated and widowed individuals who, by definition, do not have a spouse. It also includes any condom use in extramarital sex by a married person.

We further compare condom use by married and non-married individuals. Table 1d has the percentages and standard errors for whether a condom was used at last intercourse with any person, spouse or non-spouse. In table 1e, the same comparison is made for whether the individual used a condom at the last intercourse with someone other 12
<!-- Start of picture text --> 140 Number of Destinations<br>120<br>2002-2003<br>100 2006-2007<br>2010-2011<br>80<br>60<br>40<br>20<br>0<br>AZE KAZ RUS TJK TKM UZB<br> 1.000<br>Share of Top 5 Destinations<br> 0.900<br>2002-2003<br> 0.800<br>2006-2007<br> 0.700<br>2010-2011<br> 0.600<br> 0.500<br> 0.400<br> 0.300<br> 0.200<br> 0.100<br> -<br>AZE KAZ RUS TJK TKM UZB<br>0.45<br>Herfindahl Markets<br>0.4<br>2002-2003<br>0.35<br>2006-2007<br>0.3<br>2010-2011<br>0.25<br>0.2<br>0.15<br>0.1<br>0.05<br>0<br>AZE KAZ RUS TJK TKM UZB<br><!-- End of picture text --> <!-- Start of picture text --> 140 Number of Destinations<br>120<br>2002-2003<br>100 2006-2007<br>80 2010-2011<br>60<br>40<br>20<br>0<br>ARM BLR GEO KGZ MDA UKR<br><!-- End of picture text --> <!-- Start of picture text -->
1.000<br>Share of Top 5 Destinations<br> 0.900<br>2002-<br> 0.800 2003<br> 0.700 2006-<br>2007<br> 0.600<br> 0.500<br> 0.400<br> 0.300<br> 0.200<br> 0.100<br> -<br>ARM BLR GEO KGZ MDA UKR<br>0.45<br>Herfindahl Markets<br>0.4<br>0.35<br>2002-2003<br>0.3<br>2006-2007<br>0.25<br>2010-2011<br>0.2<br>0.15<br>0.1<br>0.05<br>0<br>ARM BLR GEO KGZ MDA UKR<br><!-- End of picture text -->

Source: Authors’ calculations based on Comtrade Data.

# **4. Export Performance**

In this section we describe the export performance of the twelve ECA countries under consideration using a threefold approach. We first examine the role played by diversification in the export growth 12
56 property rights against the state is more important for financial development generally, other aspects of contract enforcement (such as institutions relating to collateral) may be more important for access (Haselmann, Pistor and Vig, 2006).

Institutional reform is a long term process and specific policy actions can help boost access sooner. There are a wide range of such measures, ranging from specific legislation to underpin nonblank intermediation including leasing and factoring; technologies based on the internet and mobile phones; development of credit registries; protection against money laundering and terrorist finance without jeopardizing household access and others.

For example, at the household level, giving each individual a national identification number and creating credit registries where lenders share information about their clients’ repayment records would help since all borrowers could then borrow using their future access to credit as collateral (Rajan, 2006). Reducing costs of registering and repossessing collateral is also crucial. In Brazil for example, inability to repossess property has contributed to the cost of the housing finance program, keeping the mortgage rates too high to be affordable for the poor. Governments can also be instrumental in facilitating innovative technologies to improve access. For example in Mexico, a program developed by Nafin, a government development bank, allows many small suppliers to use their receivables from large credit-worthy buyers to receive working capital financing (Klapper, 2006). This type of trade finance is called reverse factoring and effectively allows small firms to borrow based on the creditworthiness of their buyers, allowing them to borrow more at cheaper rates.<sup>12</sup>

> 11 Rajan (2006) argues “...let’s not kill the microfinance movement with kindness.  If we want it to become more than a fad...it has to follow the clear and unsentimental path of adding value and making money.  On that path lies the possibility of a true and large-scale escape from poverty.”

> 12 Also see Berger and Udell (2006) for a discussion of different innovative technologies that can expand access of small firms even in the absence of a strong institutional environment.  De la Torre, Gozzi, and Schmukler (2005) include other such public-private partnership examples of expanding access.
# I. INTRODUCTION

Historically Zimbabwe inherited at Independence in 1980 an educational system which had denied educational opportunities to the majority African (black) population. The most diutinguishing feature of the pre-independence educational system was its racial bias, characterized by limited provision of educational resources for the African population, especially in rural areas.

Before independence access to secondary education by African pupils was governed by strict sOlection policies not found in the European education sector. As a result of these harsh politically motivated selectLon **policies,** Grade 7/Form 1 transition rates before independence wore below 35%. (Table 1.1)

- TABLE 1.1: Grade 7/Form 1 Transition Rates (%), 1970/71 1988/89

Year: 70/1 2112 223 73/4 74_5 _75L6 7617 18_ LZL/2 L9/89 Transition Rate: 30 33 31 30 27 25 23 22 22 27 Year: fiQ/1 01/2 02/3 83/4 _84L5 85/6i_ 86/7 _82/8 8A/_ Transition Rates 86 70 74 82 82 _78_ 70 _65_ 66 Source: Calculated from Reay-O for African Educatign, and Reort2 of ehe Secret=far fr u druati2on, various year., Government Printers,Salisbury and Harare, and 0T*achers' Colleges and Schoolss Staffing and Enrolment Statistics, vArious years, Ministry of Education, mimeo.

In addition to unequal access to education, there were political, social and economic disparities under colonial rule. Swift and decisive political action by an independent Zimbabwean government was, therefore, expected by the
Moreover, large differences in employment protection between temporary and permanent employees have been shown to create a dual labor market, where permanent employees enjoy high levels of job security and training as well as better career prospects while temporary employees are used as a buffer against economic uncertainties, are given low pay and limited training opportunities, and thus are largely marginalized (Booth et al., 2000; Blanchard and Landier, 2002; Dolado et al., 2012). According to the OECD (2014b), job satisfaction among temporary workers declines as the gap between the level of employment protection for temporary employees and that for permanent employees widens. Research shows that these differences also significantly reduce the probability of temporary employees’ transitioning to permanent jobs because of the dismissal costs associated with permanent employment (OECD, 2014b).

The effect of a minimum wage on productivity and unemployment depends on its level as well as the ability to account for differences in local settings and in the characteristics of employees (OECD, 2014b). If the minimum wage is set too high, it will reduce employment opportunities for low-skilled workers and increase unemployment. If it is set too low, it will reduce the incomes of low-income workers and adversely affect their incentives and productivity (OECD, 2014b). An effective minimum wage is one that is set at a level at which it does not crowd out low-skilled employees and that accounts for regional differences in income levels as well as in the age, experience and productivity of employees.

Flexibility in hiring regulations and the minimum wage is important to an economy’s ability to respond to changing market conditions and keep unemployment low. But the effect of these features of labor market regulation on productivity and economic performance depends largely on how well their unintended negative consequences are taken into account in their design.

# **_Hiring regulations and the minimum wage in Sweden_**

The World Bank Group’s _Doing Business_ project provides annual data on the availability of fixedterm contracts, on the permitted duration of such contracts and on the minimum wage as stipulated in the labor laws of 189 economies. Using _Doing Business_ data, the _Economic Freedom of the World_ report creates an index to assess the flexibility of hiring regulations and the minimum wage in 144 economies. Values for this index for 2008 and 2011 show no change between those two years for Sweden (Figure 5). Values for 2011 show that Sweden’s hiring regulations and minimum wage are more flexible than the averages for the EU15 and other Nordic economies and more flexible than those of Greece, Spain, France, Luxembourg and Portugal. But they are less flexible than the averages for the G7 and OECD and less flexible than those of such competitors as the United States, Japan, and the United Kingdom.

A closer look at the three components of the hiring regulations and minimum wage index in 2013 reveals that Sweden allows fixed-term contracts for permanent tasks and for a maximum duration of 11
# **6. Consistency of monetary international poverty rates with non-monetary welfare dimensions**

This section considers whether the international extreme poverty rate rankings are consistent with non-monetary dimensions of welfare. Thus far, we have examined monetary metrics of individual well-being, including the national and standardized consumption aggregates. This section assesses how the ranking of monetary welfare related to other non-monetary dimensions of well-being. A country with high levels of (monetary) international poverty may perform badly in other nonmonetary welfare dimensions. Table 13 lists some indicators of non-monetary well-being for the subpopulation of poor people identified using the national consumption aggregates.

**Table 13. Summary statistics of indicators of non-monetary well-being for the extreme poor**

|**identified**|**using the na**|**tional cons**|**umption**|**aggregates**||||
|---|---|---|---|---|---|---|---|
|**Variable**|**Bangladesh**|**Bhutan**|**India**|**Maldives**|**Nepal**|**Pakistan**|**Sri Lanka**|
|_Household Composition_||||||||
|Household size|5.73|8.40|6.43|7.53|7.16|10.01|5.60|
|Dependency Ratio|0.97|0.73|0.78|0.67|1.16|1.42|0.70|
|_Education Attainment in Household_||||||||
|Household head Knows How to<br>Read/Write|0.29|0.19|0.50|1.00|0.37|0.28||
|Proportion of Household Member<br>Illiterate|0.70|0.63|0.44|0.38|0.63|0.80|0.21|
|Household Members with Primary|0.18|0.33|0.35|0.18|0.32|0.18|0.37|
|Schooling||||||||
|Ratio of Female Children in School<br>to All Children in School|0.54|0.41||0.48|0.53|0.35|0.47|
|_Employment_||||||||
|Household<br>Head<br>Engaged<br>in|0.56||0.55|0.37||0.49|0.53|
|Agriculture||||||||
|Household Head Self-Employed|0.35|0.24|0.48|0.39|0.80|0.39|0.32|
|_Household Assets/Facilities_||||||||
|Household has a land phone|0.01||0.01|0.12|0.02|0.01|0.09|
|Household has electricity|0.25|0.58|0.57||0.43|0.74|0.64|
|Household has a radio|0.05|0.36|0.16|0.69|0.41|0.02|0.45|
|Household has a television|0.10|0.12|0.29|0.97|0.16|0.19|0.49|
|Household has a fan|0.15|0.06|0.45|1.00|0.14|0.71|0.15|
|Household has a sewing machine|0.02|0.01|0.08|0.54|0.05|0.25|0.10|
|Household has a bicycle|0.15|0.02|0.66|0.34|0.28|0.26|0.36|
|Drinking Water from Hygienic<br>Source|0.96|0.96|||0.73|0.87|0.84|
|Availability of Proper Sanitation<br>Facilities|0.3|0.61|||0.1|0.28|0.74|

Source: Authors’ own estimates based on South Asia Harmonized Micro Dataset (SARMD). All reported summary statistics are population-weighted.

The non-monetary indicators in most cases are broadly consistent with the monetary poverty rates, although Pakistan and Bhutan are outliers with respect to literacy. Sri Lanka has the lowest 19
spending due to crowding out through higher wages, etc. These may be exacerbated in LDCs where the benefit of R&D spending to the private sector, as we document, is low, but the competition for very scarce resources may be more intense.

Second, do these findings imply that the massive increase in R&D spending in China and India is waste? Not necessarily. The answer to the China/India puzzle may lie in the fact that most this innovative effort may be done on imported innovation platforms that provide all the necessary complementary factors, within multinational corporations. As Branstetter et al. (2012) show in 2010 roughly 75% of patenting being done is done in or jointly with multinational corporations. This is very distinct from the pattern seen in Korea and Taiwan where the vast majority are, and have been since the 1970s, indigenous patents. To the degree that R&D maps to patents, then the puzzle is partly explained by the fact that China and India have imported the innovation infrastructure- management, networks, and corporate structure- thereby potentially offsetting the usual degradation that happens with distance from the frontier. But it also suggests that the innovation statistics may be vastly overstating the effort made by indigenous firms as well as the quality of the national innovation system. If the work is being done inside of Taiwanese or US firms, then knowledge, product and entrepreneurial spillovers may be very small. Further, this says nothing about the quality of the innovative effort going on in purely Chinese firms and whether it may be hampered by the absence of the usual complementary factors found in other emerging countries.

# **6 Conclusions**

Using a panel of country level data on R&D this paper first confirms that despite presumed gains from Schumpeterian backwardness poor countries tend to do very little R&D. We document that global returns to R&D across the whole sample are consistent with those found earlier, although they do fall with the introduction of internal and external instruments.

21
- **3 -**

rationing **(with unsatisfied** demand) **and** non-borrowing (while **supply** Is potentially avalIabl) arre **both possible. The analysis** utilizes cross-sectional household-level data from a study area in northeast China, obtained in a recent farm survey designed **by** the authors. The pian for tloe paper **is as follows:** Section **II** provides background on the farm sector and the ru al cre sit market In China, and describes the specific study area and data utilized in the analys.s. Section **liI** discusses the formal model underlying the empirical analysis (the mathematical model ts pr e(ente 8 in an annex). It is followed by a discussion of the econometric procedure and tr e e j>cal results In Section IV. The last section discusses the implications of the results.

# **II. CHINA'S FARM SECTOR AND RURAL CREDIT MARKET**

China introduced a smaliolder agricultural production system in a series Of reFcrms between the years 1979-1984. The "household responsibility system" made individua! householes, rather than the communes to which they belonged, the decision-makers and mariagers of the C'N farms. Individual families were allocated land by the communes on leases that run tycicairl fc' 15 years. The improved incentives brought about a significant increase in agricuwtura! cut_tc ac in rural income (Lin). While prior to the reforrns there was only Vimited nter3act on retbe households and financial institutions, the emergence of smalilholder ag:-!cu'tur e im;: -s t',t households now need liquidity for seasonal production and consumption, or longer-rer . e finance investment, construction and ceremoniai social events.

Most of agricultural households' transact,ons w;th the fcrma f ' sector ?are the rural crecit cooperatives (RCCs).1 The interest rates for agricuitura oans tas _ve 2-:_ - loans) made by forma! credit institutions are fixed :by the government, vith some _a- a, according to loan categories. In 1987, the rates of interest for agrcu!tural Scans between 7 and 1 **4** percent. The degree of intc, est subsidy is believed to Wave been **s'L** There is evidence that following the introduction of r-efcr-ms the voiu;Tce of . obtained from informal sources is substantial in China. Jiang asserts that ron-;rsl tutic'a,
# **Figure A20 – People’s beliefs about the number of COVID-19 related deaths in PNG disaggregated by their willingness to get vaccinated**

<!-- Start of picture text --> COVID deaths in PNG<br>Planning on being vaccinated Not planning on being vaccinated Unsure<br>Less than 10 3.7 Less than 10 5.4 Less than 10 7.1<br>10 or more 18.9 10 or more 8.9 10 or more 7.7<br>Unsure 77.4 Unsure 85.7 Unsure 85.3<br>0 20 40 60 80 0 20 40 60 80 0 20 40 60 80<br>Share of respondents that selected this answer<br><!-- End of picture text --> Note: This chart is based on answers to question 3 and 23 in Appendix B.

40
divide adolescent pregnant women in two groups, depending on their latent status: those who, after becoming pregnant, choose to give birth (latent status _B*_ ), and those who would choose to abort (latent status _A*_ ). Equation (1) will identify the effect of adolescent childbearing only if:

- (i) The sample is limited to women of latent status _B*_ , who after becoming pregnant choose to give birth. Consequently, they would have only two outcomes: live birth or miscarriage.

- (ii) Miscarriages are exogenous, or there is nothing in the error term  that is simultaneously correlated with the identifier for live birth _X_ and the outcome of interest _Y_ .

In order to ensure (i), it is necessary to exclude from the sample of women who experienced pregnancy as adolescents those who either aborted or would have aborted, had they not miscarried. Do ENADID data allow for this? At first sight the data present two problems that may hinder the seemingly simple process.

First, abortions are grossly underreported in ENADID. Table 2 shows that the number of abortions per thousand women reported in ENADID is 82 times lower than a low estimate based on hospitalization data and surveys of health professionals: 0.34 vs. 28 (Juarez et al., 2006). This is not surprising, considering that in 2006 abortion was illegal throughout the country (it became decriminalized in Mexico City in 2007). However, underreporting of abortions will not bias estimates in (1), as long as women _do not report_ pregnancies that were terminated in abortions (as opposed to reporting them as miscarriages). Provided that women do not report abortions as miscarriages, the coefficient  in equation (1) will be unbiased regardless of the extent of underreporting. A data analysis in the subsequent section will show that reporting abortions as miscarriages is highly unlikely.

The second issue is that some women who reported miscarriages may have latent status _A*_ , but miscarried before aborting. Hotz et al. (2005) use data on the actual proportion of abortions to address this problem.<sup>8</sup> Given the quality of abortion data in ENADID, this option is unavailable here. However, ENADID contains data on the length of pregnancy at the time of the miscarriage.

> pregnancy, it is recorded as a stillbirth ( _mortinato_ ). In this paper we refer to both: aborto and mortinato as miscarriages.

> 8 Hotz et al. (2005) demonstrate that they can identify the effect of having a baby on a woman of latent status _A*_ if they use indicator for abortion as an instrument for not giving birth.

7
Table 9: Deep trade agreements and trade in parts and components, PPML

||(1)|(2)|(3)|
|---|---|---|---|
|No. of provisions|0.00294**|||
||(0.00130)|||
|Core provisions||0.00589**||
|||(0.00273)||
|PCA depth|||0.0224**|
||||(0.0107)|
|BIT|0.127***|0.126***|0.127***|
||(0.0316)|(0.0316)|(0.0316)|
|PTA (in force or inactive|‐0.0492|‐0.0737|‐0.0574|
||(0.0470)|(0.0505)|(0.0489)|
|Observations|336,976|336,976|336,976|
|R‐squared|0.990|0.990|0.990|
|Country‐pair FE|Yes|Yes|Yes|
|Country‐time FE|Yes|Yes|Yes|

Clustered standard errors at the country pair level in parentheses.

*** p<0.01, ** p<0.05, * p<0.1

28
- 32 -

R<sup>2</sup> = 0.44 N = 273, where the numbers in parentheses are t-statistics. The variables as they appear in equation (A.2), with the exception of LAMBDA, are defined in Table 2. The instrument for household income in the absence of migration is given by Ye = Y j + W.

# Relative Deprivation without Migration by Person j.

Estimation of a household's relative deprivation in the absence of migration by person j (RDj) is complicated by the fact that relative deprivation is a function not only of the income of person j's household but also of the incomes of all other households in person j's village (equation (3)). We constructed an instrument for RDi by first estimating the income 0 (Y) of each household in the village sample and then using this estimated income distribution to estimate the level of a household's relative deprivation associated with nonmigration by person j.

Estimates of total household income (Y) were obtained by regressing observed 1982 total household income on household holdings of income-producing assets at the start of the year and then using the estimated equation to predict 1982 income for each household represented in the sample. The estimated income equation is