rafmacalaba/datause-encoder-data huggingface dataset:
<!-- Start of picture text --> 2000 - 2009 75% 25%<br>1990 -1999 69% 29%<br>1980 - 1989 75% 24%<br>Traditional<br>1970 -1979 86% 13% Non-traditional<br>1960 -1969 93% 7%<br>1950 - 1959 88% 12%<br>0% 20% 40% 60% 80% 100%<br><!-- End of picture text -->

# **Contribution of prices and volumes**

In this section, the issue of the contribution of prices and volumes in the recent high growth in Peru‟s exports is explored. Due to limitations with the data available, the empirical analysis looks at this question separately for traditional and non-traditional exports.

For the case of traditional exports, between 1994 and 1999 prices hardly varied, with an annual average growth of 0.7%, while volumes grew by 10.6%.<sup>11</sup> In contrast, between 2000 and 2009, the prices of these exports grew by an annual average of 13.7% and volumes by 5.3% (see Table 3). In the first period, the high growth of volumes reflects the growing extraction of minerals and hydrocarbons, following changes in the governing laws for both activities, introducing different types of incentives (e.g. related to taxes and exchange rates), the privatization of state mines and the access to agreements on tax stability, which have contributed to boosting the production and the supply of this type of products, despite the low price. In the second period, with the continuous price boom – except at the end of 2008 and the beginning of 2009 due to the international financial crisis -, volumes grew by 5.3%, as a result of the lower grade of the mineral extracted from existing mines and few important new mines coming on stream. This has given rise to a relative stagnation of the volumes in recent years, despite the significant price increase (see Figure 5, mobile average of 6 months on the black line).

> 11 / The analysis can only be performed with data starting in 1994, as the data from the Central Bank of Peru has disaggregated data on the prices and volumes of traditional and non-traditional exports as from that date. A study on this same topic is that of Banco Central de Peru (2008).

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The final drawback of rules-based measures refer to the major gaps between statutory laws "on the books" and their implementation in practice "on the ground". To take an extreme example, in all of the 41 countries covered by the 2006 Global Integrity Index, accepting a bribe is codified as illegal, and all but three countries have an anticorruption commission or similar agency (Brazil, Lebanon, and Liberia were the only exceptions). Yet there is enormous variation in perceptions-based measures of corruption across these countries: the same list of 41 countries covered by the Global Integrity Index includes the Democratic Republic of Congo which ranks 200th, and the United States which ranks 23rd, out of 207 countries on the WGI Control of Corruption Indicator for 2006.

Another example of the gap between rules and implementation that we have documented in more detail elsewhere compares the statutory ease of establishing a business with a survey-based measure of firms' perceptions of the ease of starting a business, across a large sample of countries.<sup>9</sup> In industrialized countries, where often _de jure_ rules are implemented as intended by law, unsurprisingly we found that these two measures corresponded quite closely. In contrast, in developing countries where too often there are gaps between _de jure_ rules and their _de facto_ implementation, we found the correlation between the two to be very weak; in such countries de jure codification of the rules and regulations required to start a business is not a good predictor of the actual constraints as reported by firms. Unsurprisingly, much of the difference between the _de jure_ and _de facto_ measures of the ease of starting a business in developing countries could be statistically explained by _de facto_ measures of corruption, which subverts the fair application of rules on the books.

These three drawbacks, namely an inevitable role of judgment even in "objective" indicators; the complexity and lack of knowledge regarding the links from rules to outcomes of interest; and the gap between rules "on the books" and their implementation "on the ground", suggest that although rules-based governance indicators provide valuable information, on their own they are insufficient for the purposes of measuring governance. Rules-based measures need to be complemented by and used in conjunction with outcome-based indicators of governance. We turn to such indicators, and their particular strengths and weaknesses, next.

> 9 Kaufmann, Kraay, and Mastruzzi (2006).

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Measures of the degree to which economic growth is inclusive are also affected by the assumption that at least some of the HHS-NAS gap originates from missing top incomes in survey data. In measuring the degree to which growth is inclusive, the World Bank’s twin goals and the UN Sustainable Development Goals (SDGs) monitor growth in income and consumption of the bottom 40 percent in each country, relative to the growth for the overall population (World Bank, 2016). For a recent set of comparable spells used to monitor these goals, 56 out of 88 countries (64 percent) that are available in the Shared Prosperity Database for 2013 to 2018, reported a positive ‘shared prosperity premium’: the growth of mean income or consumption among the bottom 40 percent exceeded that of the overall mean growth. Panel A of Figure 8 shows the growth of the bottom 40 percent on the vertical access, and of the overall mean on the horizontal axis. The majority of observations are above the 45-degree line, indicating that growth was inclusive, and inequality, by this measure, was falling. However, these estimates rely solely on survey data. If we assume that the gap between surveys and national accounts is partly due to missing top incomes in surveys, it may be justifiable to compare the growth of the bottom 40 percent from surveys with the mean of national accounts, assuming that this better reflects overall growth. Under such a comparison, only 40 countries (49 percent of the 81 countries for which we have HFCE data for the spells) had a positive shared prosperity premium where the bottom 40 percent grew faster than the mean as measured by HFCE. Panel B of Figure 8 illustrates the relationship and differences between growth in the bottom 40 percent and growth in the mean with the adjusted distributions. The population-weighted average annualized shared prosperity premium for the period falls by 0.6 percentage points, from a positive 0.5 percent growth to -0.1 percent, inverting the positive global picture of trends in inequality measured by the official spells. This further illustrates that conventional measures of development can be misleading if one assumes the HHS-NAS gap to originate from a lack of capture of consumption and income of the richest households in surveys.

# **5. Conclusion**

This paper has compiled a large new data set for assessing the correspondence between per capita monetary living standards measured in national accounts and household surveys. The data show that the gaps in measurement across the two data sources are larger than in previous assessments. Our assessment concludes that the gap does not seem to be due to survey income 27
risks), and wage workers least willing to take risks (6.2 for life risks and 5.3 for financial risks). These ranking are more in keeping with expectation. By these measures, own account workers are intermediate between wage workers and SME owners.

Each of the surveys contains questions developed by industrial psychologists to measure aspects of the entrepreneurial personality. These are shown on Table 6. The appendix shows the actual questions, grouped in the manner they are used in the literature and in this paper. Responses to all questions are coded on a scale of one to five, with one indicating “strongly disagree” and five “strongly agree.” In some cases, the question is reversed with respect to the characteristic being measured, so that strongly disagree indicates having the trait and strongly agree indicates not having the trait. These are adjusted in calculating the variables.

The first three rows measure work centrality (Mishra et al, 1990), tenacity (Baum and Locke, 2004) and achievement (McClelland 1985). Work centrality is measured by a single question related to the importance of work in life. Tenacity measures the extent to which individuals persist in difficult circumstances. Achievement is measured as the sum of five questions related to the satisfaction obtained from doing well and a feeling of competition with others.

All three of these are measures of personal motivation in work and life. The responses show a consistent pattern: Both SME owners and wage workers are more motivated than own account workers. In all three cases, the rank ordering of responses shows that SME owners are the most tenacious and work-motivated, and own account workers are least tenacious and motivated, with wage workers placed in between. These data point to motivation and determination as important determinants of firm size.

The next two measures are power motivation (McClelland 1985) and internal locus of control (Rotter, 1966). Power motivation is measured with three questions related to planning and deciding what other people should do and control over events. Internal locus of control is a measure of the willingness to take risks and put oneself in unfamiliar circumstances. With respect to power motivation, own account workers are similar to SME owners, and both have a stronger desire to be in control than wage workers do. The pattern with respect to staying in situations which are familiar is interesting. Here we find that SME owners are more willing to put themselves in
27 run, unemployment will increase in the nontradable sector if real wages are downwardly rigid. For the medium to longer run, as wages finally fall and as labor and then capital become mobile, income profiles by production sector and by factor are needed. From these income profiles, decomposable poverty measures could be calculated. The impact on poverty from income changes or relative price changes due to shifts in macropolicy could then be estimated using the elasticities described above.

Ravallion and Huppi (1989) analyze two household surveys from Indonesia that cover the period before and after an adjustment program. They use recent results from theoretical research on poverty to calculate several poverty measures and to rank these measures over a range of poverty lines. They conclude that poverty and undernutrition declined from 1984 to 1987 for a number of poverty lines and measures. Next, the causes of the poverty decline are examined. First, the change in poverty is decomposed into urban and rural poverty changes, population shifts between the two sectors, and interaction effects between population shifts and poverty changes. Rural poverty declines are found to be very important, suggesting that adjustment policies (such as devaluation) have improved returns to this sector. This sectoral decomposition could be done for other sectors as well. Second, the change in poverty is divided into changes due to movements in mean consumption and to movements in inequality. Most of the poverty reduction is due to growth in mean consumption; the contribution of improved equity is smaller.

The paper .hen investigates the importance of initial conditions. Point elasticities of poverty with respect to changes in mean consumption, for fixed inequality, are calculated for 1984. The Indonesian data show that poverty reduction is elastic (with estimates ranging from -1.3 to -3.4) to changes in
This paper also focuses attention on two elements of the cost of migration. There has been considerable attention devoted recently to the costs of sending remittances and the potential gains to be had from lowering these costs.<sup>14</sup> The formal costs of migrating have received much less attention, and there is considerable scope for further research which examines the role of formal migration costs in determining migration numbers and on the impact of policy changes in these dimensions.

# **8. References:**

Gibson, John, David J. McKenzie, and Halahingano Rohorua (2005) “How Costelastic are Remittances? Evidence from Tongan Migrants in New Zealand”, Mimeo. The World Bank.

Global Commission on International Migration (2005) _Migration in an interconnected world: New directions for action_ , Report of the Global Commission on International Migration, www.gcim.org.

Kaufmann, Daniel, Aart Kraay and Massimo Mastruzzi (2005) “Governance Matters IV: Governance Indicators for 1996-2004”, Mimeo. The World Bank Parsons, Christopher R, Ronald Skeldon, Terrie L. Walmsley and L. Alan Winters (2005) “Quantifying the International Bilateral Movements of Migrants”, Mimeo. The World Bank and the Development Research Centre on Migration, Globalisation and Poverty at Sussex University.

Philander, Frederick (2005) “Shady Deals Revealed at Home Affairs”, _New Era_ October 10, 2005, http://allafrica.com/stories/200510100439.html [accessed November 1, 2005].

> 14 See Gibson, McKenzie and Rohorua (2005) for a calculation of the gains from lowering remittance costs.

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# **Figure 1: Counts of World Bank publications 1973-2006 (7-year moving averages)**

<!-- Start of picture text --> 500<br>Journal Articles<br>450 Books<br>Chapters<br>400 Conference Proceedings<br>Edited Volumes<br>350<br>Working Papers<br>300<br>250<br>200<br>150<br>100<br>50<br>0<br>1970 1975 1980 1985 1990 1995 2000 2005 2010<br>Publications<br><!-- End of picture text --> 30
- 8 -

individual bank level to capture systemic as opposed to individual bank risk (see section IV below for more details). Equation (1) is estimated by OLS with standard errors clustered by country to allow for correlated residuals within each country.

The variable of interest is _X_ 1 _j_ , the BCP compliance score. The data come from IMF and the World Bank BCP assessments conducted from 1999 to 2006.<sup>8</sup> Assessors rate compliance with each of the 25 Basel Core Principles using a four-point scale: non compliant, materially non compliant, largely compliant, and compliant. We assign numerical values to each of these ratings from 0 (non-compliant) to 3 (compliant). To obtain an overall index of compliance, we sum the numerical ratings for all the principles, and standardize the sum to obtain an index that varies between zero and one. To differentiate among the various dimensions of regulation and supervision, we also compute aggregate compliance indexes for each of the subgroups of principles following the grouping by chapters used by the Basel Committee (See Table 1). Also in this case, we sum the numerical ratings for each principle in the Chapter and average the value. Compliance for each chapter is used as an alternative variable of interest.

The first set of control variables includes various bank characteristics that might affect financial strength: size, measured by the logarithm of bank assets; cost efficiency, measured as overhead costs as a ratio of total assets; and illiquidity proxied by the ratio of bank loans to total assets. We also control for whether the bank is a commercial bank or not (see below for sample composition). Bank data come from Fitch’s Bankscope database.<sup>9</sup> A second group of control variables captures the overall quality of the institutions in the country. Combining information from a variety of available indexes, Kaufman, Kraay, and Mastruzzi (2003) create various broad measures of perception of institutional quality which have been widely used in empirical studies. In our baseline specification, we use an index capturing the extent to which the rule of law is respected. This index is strongly correlated with other

> 8 Some assessments are publicly available through the IMF and World Bank websites. A number of them, however, are kept confidential by the country’s authorities.

> 9 Summary statistics and cross-correlations for the variables used in the analysis are in the Appendix. A small number of observations with negative equity, negative overheads, overhead to assets ratios greater than one and negative net loans/assets were excluded.
quarter of respondents cited cost and distance; a similar share said that they did not have an account because a family member already had one. About 20 percent of respondents cited lack of documentation and trust in the financial system, and 6 percent cited religious concerns as the reason they did not have an account.

In ECA only 7 percent of unbanked adults reported insufficient funds as the sole reason for not having an account. Thirty percent cited lack of trust in financial institutions. These figures were particularly high in Azerbaijan (42 percent) and Ukraine (50 percent).

Other factors underlying the lack of account ownership include cost, lack of documentation, and distance. For the region as a whole, 27 percent of unbanked adults reported cost as a barrier. This figure was higher in Albania (40 percent), Azerbaijan (39 percent), Bulgaria (39 percent), Kosovo (42 percent), Moldova (35 percent), Russia (34 percent), and Ukraine (40 percent).

On average, only 14 percent of unbanked adults in ECA cited lack of documentation as a barrier. The figure was about 40 percent in Azerbaijan, Georgia, and Turkmenistan.

In the Republic of North Macedonia and Turkey, more than half of unbanked adults (54 and 65 percent, respectively) reported that they did not have an account because a member of the family already had one. This pattern may be associated with the fact that male household members are more likely to own an account than their spouses.

# Use of Accounts for Payments Is Increasing in the Region’s Developing Economies

Most people in ECA make or receive payments, pay bills, send money to relatives, or receive wages or government transfers. The 2017 Global Findex survey asked people what kinds of payments they made and received and whether they did so via an account or in cash.

## _Government Transfer Payments_

Except in the poorest economies in the world , most people who get government payments receive them into an account. In the developing economies of ECA, more than 70 percent of government transfer recipients receive the payments into an account. This share remained stable in 2014 and 2017. It is larger than in developing countries in other regions. In the euro area, 86 percent of adults getting government transfers received the money via an account in 2014. This share declined to 75 percent in 2017.

## _Wage Payments_

Globally, 28 percent of adults receive private sector wages—46 percent of adults in high‐income economies and 24 percent in developing ones. In high‐income economies, most people receive wage payments into an account. Only half of wage recipients do so in developing economies. In ECA more than 80 percent of private sector wage recipients and more than 90 percent of public sector wage recipients receive payments via an account. These shares increased moderately between 2014 and 2017.

## _Payments for Agricultural Product Sales_

About 15 percent of adults in developing economies receive payments for agricultural product sales. Almost all receive them in cash. In some African countries, such as Ghana, Kenya, and Zambia, about 40 12
# <u>Application of SSG measures</u>

Notifications of measures are summarized in Table A1.3. These numbers came from a review of national notifications available on the WTO documents website. In this review I found that a number of WTO Members who have reserved in their schedules the right to apply SSG measures have notified year-by-year that they have taken no SSG actions.<sup>67</sup> Other countries have taken limited actions. Norway is an example. A search of WTO documents identified nine SSG notifications from Norway The first seven are MA.5 notifications of no SSG actions in 1995, 1996, 1997, 1998, 1999, 2000, 2001.

The eighth is a MA.3 notification of a Volume-based action on one product, (flakes and granules of potatoes; tariff item number: 1105.20) The ninth notification, submitted 15 September 2008, reports no SSG actions in 2002, 2005 and 2007. It also reports that for flakes and granules of potatoes ‘Action commenced 5 April 2006 and ceased on 31 December 2006.’<sup>68</sup> Among developed Members, the United States, Japan, and the EC appear to be the main users of SSG system.<sup>69</sup> The Rep. of Korea and Chinese Taipei have applied a number of measures while other developing Members have been occasional appliers. The numbers of tariff lines for which major users have reported SSG application are listed in Tables A1.4 through A1.10. Because the SSG system functions as a minimum price system, the impact of the SSG system should not be judged by the number of products on which duties were levied.

The typical pattern of usage is that measures remain if force on products for several years. For example, in 1999, Costa Rica imposed price-based measures on 4 tariff items. Three of those were subject to measures through 2003; Costa Rica has imposed no other SSG measures. Other examples:

- the EC volume-based special safeguard has been operational for the same list of fruits and vegetables since the SSG mechanism was created, the pricebased special safeguard year-by-year for poultry meat and sugar.

- of the 17 products on which Chinese Taipei has applied measures, on only one have measures not been in place in consecutive years; on 6, measures have been in place each year, 2002-2007.

67 The Members whose notifications I have reviewed are the following. The year or crop year in parenthesis is the most recent year for which a notification is available on the WTO documents database as of 09 January 2009. Australia (2006); Botswana (2007/2008); Canada (2007); Colombia (2004); Ecuador (2005); El Salvador (2002/2003); Iceland (2002/2003); Indonesia (2000); Israel (2004); Malaysia (2007); Mexico (2005); Namibia (no notifications ); New Zealand (2007); South Africa (2006); Swaziland (no notifications ); Thailand (2006); Venezuela (1998) 68 G/AG/N/NOR/48 (17 September 2008) p. 2 69 Hallaert (2005), tabulated all notified actions through 2000, notes also that transition economies, particularly Poland were also significant users. The transition economies who were significant users have since become Member States in the EC.

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