rafmacalaba/datause-encoder-data huggingface dataset:
**Figure 4: Economic and administrative regulation**

(a) Administrative regulation (b) Economic regulation <!-- Start of picture text --> 3.5 3.5<br>3.0 2.9 3.0 2.5 2.7 2.7 2.8<br>2.5 2.2 2.4 2.5 2.0 2.1 2.4<br>2.0 1.5 1.5 1.5 1.6 2.0 1.8 1.8 1.9<br>1.5 1.3 1.3 1.4 1.5<br>1.1<br>1.0 1.0<br>0.5 0.4 0.5<br>0.0 0.0<br>Romania Bulgaria Albania 2007 Croatia 2007 Slovak Republic EU15 Hungary OECD MICs Czech Rep. Poland Slovak Republic OECD EU15 Albania 2007 Czech Rep. MICs Bulgaria Romania Poland Hungary Croatia 2007<br><!-- End of picture text --> _Source: see Figures 3, 4 and 5. Note: Other MICs are Brazil, Mexico, Turkey. Values refer to 2007 for Croatia and Albania, 2006 for Bulgaria and Romania,2004 for Brazil, and 2003 for all other countries. For full data set see Annex_ I.

|**BOX 1: A REMINDER ON PMR METHODOLOGY**<br>**_Administrative regulation_**|<br>**_Economic regulation_**|
|---|---|
|- Licenses and permits|- Scope of the public enterprise sector|
|- Communication and simplification of rules and<br>procedures of administrative intervention|- Size of the public enterprise sector|
|- Administrative burdens on start ups: Corporations|- Direct control over business enterprises<br>(SOEs)|
|- Administrative burdens on start ups: Sole proprietors<br>- Administrative burdens on start ups: Sector specific<br>burdens|- Price controls<br>- Use of command and control regulation<br>- Legal barriers to competition<br>- Antitrust exemptions<br>- Foreign ownership barriers<br>- Discriminatory procedures against foreing<br>firms<br>- Tariffs|

**A second broad distinction can be made between inward oriented policies and outward oriented policies.** The former include policies and regulations that determine the degree of state control and barriers to entrepreneurship, while the latter reflect policies and regulations that affect barriers to trade and investment.  A detailed description of what the indicators measure follows in the next sections.

**Compliance with the** **_acquis communautaire_ in the perspective of EU accession and membership of the WTO have an important impact on both inward and outward oriented policies.** EU legislation must eventually be fully implemented in a wide range of domains as a precondition to participating in the EU-wide single market for goods and services.  Nonetheless, greater reform challenges, as well as greater cross-country variation, lie with the regulations that fall under the category of inward oriented policies.  Indeed, while implementation of the _acquis communautaire_ is certainly reflected in certain aspects of the inward regulatory framework in Croatia (e.g. competition policy), many areas are still subject to a large degree of domestic discretion.

7
entrepreneurship for economic growth. These metrics may also be additionally skewed in the Indian context given the well-known problem of the ̳missing middle‘ in the firm-size distribution, which is often associated with rigid employment laws. A large count of small firms may not represent an entrepreneurial cluster very well in an environment where labor laws are particularly binding for firm size (e.g., Besley and Burgess 2004).

Understandably, many researchers are instead drawn to metrics that are more tightly connected to the dynamic nature of entrepreneurship. The more recent micro-data have both enabled these measurements and stressed their better performance relative to small business counts (e.g., Haltiwanger et al. 2010). One approach focuses on start-ups within a single industry so that finer characterizations and case studies can be made (e.g., Saxenian 1994, Feldman 2003). Others look at new product introductions (e.g., Audretsch and Feldman 1996), venture capital placement (e.g., Samila and Sorenson 2011), or the founding of new firms (e.g., Kerr and Nanda 2009, Rosenthal and Strange 2010). These dynamic measures of entrepreneurship are less available than self-employment rates or small business statistics, but are more tightly connected to entrepreneurship that can generate job growth.

We follow this emerging strand and principally define entrepreneurship as the presence of young establishments. Haltiwanger et al. (2010) emphasize how young firms are more tightly associated with employment growth than small firms (conditioning on age) in the US. While we would also like to employ measures of entering establishments in their first year (e.g., Glaeser and Kerr 2009), the young establishment definition—less than three years old—is the most refined measure feasible for India at this time. Incumbent establishments, which are used to model existing activity in the district-industry and Marshallian spillovers, are defined as firms that are three years old or more. We principally define entry measures through employment in these new establishments. We also test robustness using an entry share measure based upon establishment counts.

Most of the Indian surveys described next unfortunately do not record whether new establishments belong to larger, multi-plant firms or whether they are independent enterprises. While it would be advantageous to study single-unit starts separately from multi-unit expansions, we are unable to do so consistently. Encouragingly, we are able to separate establishment types for organized manufacturing, and we find very similar results to those presented below when modeling the single-unit start-up entry rate separate from multi-unit expansions, but we are unable to ascertain this stability across all of the sectors we study. The Indian context is one in which a major limitation for development is the growth and replication of successful initial businesses. Thus, from this perspective, many policy makers are as concerned about encouraging entry of new expansion establishments as they are initial start-ups.

7
in U.S. treasury securities. As Cooper (1997) argued before the introduction of the euro, the attractiveness of the US dollar as a reserve currency is in large part derived from the existence of a deep and liquid market in U.S. treasury securities, and in particular in treasury bills: “Amounts measured in billions of dollars can be bought or sold readily, 24 hours a day, anonymously, without influencing the price of the outstanding bills. There is nothing comparable to this market on the European continent, or in Japan, and there is not likely to be for decades to come.”<sup>10</sup> The short-term government paper market has suffered from the preference of the German government for longer-term securities; France and Italy have large markets for government debt, but nothing comparable to that in the United States. No single euro-zone country establishes benchmarks for bonds across the maturity spectrum. In addition, long-term bond markets have been more liquid in the United States: at end-1997, bid-asked spreads for on-the-run 10 year government bonds in secondary markets were only 3 basis points in the United States, compared to 4, 6, and 10 basis points in Germany, Italy and France, respectively.<sup>11</sup> More recent data suggest that the bid-asked spreads on bunds are now more similar to those on US treasuries<sup>12</sup> , but volumes remain lower. The relative scarcity of short-term German government paper remains a problem, as do national differences in the treatment of collateral for the repo market (Galati and Tsatsaronis, 2003).

# **4. Prospects for Further Development of the Use of the Euro**

While the existence of a large pool of euro investors will continue to make debt issuance in euros attractive for developing countries, inertia in reserve currency use and limits on the liquidity of short-term euro instruments will continue to retard the development of the euro as an international currency for use in exchange market intervention and reserve holdings. The fragmented nature of the European markets for government bonds remains, despite the creation of the euro. It is possible to imagine innovative solutions that would increase the liquidity of European markets, for instance the creation of a single issuer of government short term paper, as proposed by Alexandre Lamfalussy.<sup>13</sup> However, the prospect for such an institution, which presumably would buy up a significant amount of the euro area governments’ issues, seems distant. As Galati and Tsatsaronis (2003) note, creating such an agency would imply shared responsibility for servicing government debt—contrary to the spirit of the Maastricht Treaty.

In considering future reserve currency use, it is important to distinguish the holding of reserves for intervention purposes from those that constitute an investment portfolio,

> 10 Cooper (1997), pp. 12-13.

> 11 “The Size and Liquidity of Government Bond Markets,” _BIS Quarterly Review_ , November 2000, p. 54. 12 I am grateful to Gabriele Galati for this information.

> 13 Speech to the symposium “Capital Markets and Financial Integration in Europe,” held at the European Central Bank on April 29-30, 2002.

14
|Argentina|5096|198,702|38|25|0.49|24|34|30|
|---|---|---|---|---|---|---|---|---|
|Botswana|5687|10,782|1.8|52|..|15|26|0|
|Brazil|4875|917,079|188|14|1.01|21|30|9|
|Cambodia|514|6,970|13|69|..|..|..|..|
|Chile|7884|130,114|16|43|..|23|49|25|
|Egypt, Arab Rep.|1313|95,823|72|30|0.26|22|..|..|
|India|797|911,498|1,143|21|0.77|..|..|..|
|Indonesia|1324|301,594|227|31|..|19|22|6|
|Jordan|2458|13,609|5.5|54|..|20|..|..|
|Lebanon|5390|21,991|4|21|..|..|..|..|
|Macedonia, FYR|3003|6,286|2|47|0.20|33|53|15|
|Morocco|2080|64,142|30|34|0.64|20|10|9|
|Pakistan|723|116,370|160|15|..|21|12|24|
|Peru|3051|85,529|28|29|..|23|53|36|
|Philippines|1242|108,469|87|47|..|15|39|28|
|Romania|4944|106,727|21|30|0.45|31|62|13|
|Russian Federation|5799|826,293|142|34|1.07|29|41|51|
|Saudi Arabia|12831|325,545|25|63|0.04|20|..|..|
|Solomon Islands|921|442|0.48|36|..|..|..|..|
|South Asia|746|1,135,508|1,521|21|0.75|..|..|..|
|St. Kitts and Nevis|11389|567|0.05|37|..|..|..|..|
|Tonga|2564|260|0.1|14|..|..|..|..|
|United Kingdom|38873|2,355,546|60|29|1.75|22|45|31|
|United States|43228|12,898,400|298|11|2.64|21|..|..|
|Vietnam|687|57,271|83|74|..|20|..|..|
|Yemen, Rep.|837|17,284|20|41|..|..|..|..|

The selected indicators are intended to proxy the dimensions by which the sample is analyzed. ... indicates that the data were not available _Source: World Development Indicators, 2008._ 32
pooled.<sup>3031</sup> That controls do not substantially change the point estimate is unsurprising, given that they do not change significantly at the discontinuity.

When the estimation is carried out separately by gender, the discontinuity is significant for both men and women, but the F-statistic is now below the rule of thumb for weak instruments for the subsample of women (Stock and Yogo 2002)—though I cannot reject the equality of the discontinuities for men and women. However, because the model is just-identified, the weakinstruments bias towards OLS is not present (Angrist and Pischke 2009), though tests may not be correctly sized.

In the right panel of Figure 3, I show the estimated difference between the cumulative distribution functions for education of the populations on either side of the discontinuity. For each point in the right panel, I estimate a separate regression of the probability that respondents attain more than _x_ years of education on a piecewise linear control and an indicator for the discontinuity; the plot shows the coefficients and confidence intervals on the discontinuity for each of these outcomes. The KCPE discontinuity

> 30Decomposition as suggested by Gelbach (forthcoming) shows that the change in coefficient magnitude from column (7) to column (9) is mostly due to the inclusion of the covariate controls; the slightly larger standard error is brought about because of the inclusion of the piecewise quadratic in the running variable. A separate issue is that small fraction of the sample is still in school; this fraction varies slightly at the discontinuity, and as such, the completion of secondary schooling may be viewed as a censored outcome in the first stage, which could be the source of some bias. In practice, restricting the sample to respondents who are surveyed at least five years after they take the KCPE does not substantially alter the results.

31Also note that while I find a larger discontinuity for men than women, Uwaifo Oyelere (2010) found that variation in free primary education in Nigeria predicts years of education equally well for men and women. This could be because free primary school induces additional schooling at too young an age for womens’ early marriage and fertility decisions to be relevant, and would have been especially true in the period when Nigeria’s primary education system was first coming into existence, included in Uwaifo Oyelere’s (2010) analysis.

19
|Occupational income|Number of people in|Average annual income|
|---|---|---|
|(in milreisper annum)|occupation|relative to mean|
|1327|543|4.26|
|1328|2166|4.26|
|1349|741|4.33|
|1358|31|4.36|
|1365|362|4.38|
|1386|181|4.45|
|1392|2409|4.46|
|1417|1731|4.55|
|1424|1171|4.57|
|1425|26|4.57|
|1431|377|4.59|
|1436|388|4.61|
|1441|104|4.62|
|1464|22|4.70|
|1466|155|4.70|
|1477|569|4.74|
|1487|3872|4.77|
|1512|813|4.85|
|1526|75|4.89|
|1558|322|5.00|
|1560|254|5.00|
|1576|4|5.06|
|1587|13|5.09|
|1594|1204|5.11|
|1600|1984|5.13|
|1614|119|5.18|
|1631|214|5.23|
|1634|522|5.24|
|1638|3436|5.25|
|1639|335|5.26|
|1661|13|5.33|
|1662|26|5.33|
|1717|151|5.51|
|1728|1575|5.54|
|1729|69|5.55|
|1759|155|5.64|
|1771|17197|5.68|
|1772|949|5.68|
|1780|450|5.71|
|1784|630|5.72|
|1795|17|576|
|<br>1799|<br>716|.<br>5.77|
|1800|451|5.77|
|1830|5|5.87|
|1868|450|5.99|
|1890|42|6.06|
|1899|26|6.09|
|1908|604|6.12|
|1948|502|6.25|

41
<!-- Start of picture text --> accounting, implies that total profits are equal to GDP excluding wage earn-<br>ings, we can use the same elasticities to estimate the output elasticity of the<br>corporate income tax. Again, we follow the formulae in Giorno et al (1995)<br>and Van den Noord (2000) in calculating this elasticity.<br>The output elasticities of personal income taxes, social security taxes,<br>corporate income taxes and sales/VAT taxes are then summarized in columns<br>F to I. Finally, the output elasticities of specific taxes are weighted by their<br>share of total tax revenue to give the output elasticity of tax revenues.<br>Table 2 shows our estimates of elasticities using annual data. Table 3<br>compares our estimates of the output elasticity of tax revenues—using annual<br>data-with those of the OECD, for the seven countries that appear in both<br>samples. As noted earlier, our estimates of the personal income tax elasticity<br>are virtually identical. Thus all differences in estimates of the final elasticities<br>are due to differences in estimates of macroeconomic elasticities, such as the<br>output elasticity of employment.<br>3. The effects of tax cuts: A panel estimate<br>We begin our analysis with a simple panel regression, which attempts to<br>determine the effects of tax changes on output. In doing so, we follow the<br>specification in Barro and Redlick (2009) who estimate the effects of a lagged<br>change in the tax rate on current output. They argue that tax changes at a<br>one-year lag are more likely to have an effect on output than contemporane-<br>ous changes and less likely to be affected by reverse causation.<br>These regressions are an illustration of the data available in the collected<br>dataset. The methodology used here does not fully control for the possibility<br>of reverse causation: tax rates, particularly average marginal ones, respond<br>endogenously to business cycle conditions. For this reason, we address iden-<br>8<br><!-- End of picture text -->
C�A; w� are available allows users to have a better understanding of regional levels and trends in statistical capacity.

# **4. Description of the SPI**

We apply the theoretical framework discussed above to develop a new Statistical Performance Indicator (and Index, or SPI). In this section, we discuss the features of the SPI, and compare it with the SCI. We also briefly discuss some data challenges with the construction of the SPI.

# **4.1. SPI and Its New Features**

As discussed earlier in Subsection 3.2.4, the SPI is built around four main dimensions: i) Methodology, Standards and Classifications, ii) Censuses and Surveys, iii) Availability of Key Indicators , and iv) Dissemination Practices and Openness. We further discuss each dimension, its indicators, and other practical implementation details in this section. More details on each indicator, its score, and its data sources are provided in Appendix 2.

Internationally accepted and recommended methodology, classifications, and standards provide the basis for NSSs to generate internationally relevant statistical indicators and facilitate data exchange and data integration. The first dimension (Methodology, Standards and Classifications) assesses whether NSSs have the necessary capacity to adopt and comply with international statistical standards. Twelve indicators are proposed for the first dimension to ensure that data from different sources can be compared, and to inform data users that the data are reliable and meet established technical standards. The setting and applying standards are usually regulated by law and typically the responsibility of the main national statistical agency.

25
absence of other work attempting such classification, we summarize their results as giving a rough outline of the relative importance of the different types of income earners in the economy.

The authors analyzed the data available from the Social Dimensions of Adjustment Survey for 1988. They listed six socio-economic groups to which the households were assigned as follows;

- i) Households producing the exportable crop, cocoa;

- ii) Households producing other agricultural goods-basically food;

- iii) Households with one or members who are retail or wholesale traders;

- iv) Households with one or more members in wage employment producing non-traded goods and services ( excluding traders and government and services);

- v) Households with one or more members in wage employment producing manufactured goods;

- vi) Households with one or more members employed in providing government services.

The extent of multiple occupations can be seen from the following Table 1.1 of incomes derived by the households in the sample from different sources which Appleton and Collier have calculated.

**Table 1.1: Percentage in per Capita Income Deciles**

||l|2|3|4|_5_|6|7|8|**9**|10|
|---|---|---|---|---|---|---|---|---|---|---|
|Govt.|3.1|6.7|8.5|10.4|8.6|10.0|10.9|13.7|15.6|12.6|
|NTG|8.4|8.5|9.7|11.8|11.7|8.8|11.1|8.9|10.9|10.2|
|Manu.|5.9|9.2|10.1|12.5|8.9|11.1|14.1|8.0|11.7|8.5|
|Traders|8.2|8.7|9.3|10.8|10.8|8.7|10.4|12.1|11.7|8.5|
|Cocoa|7.9|_5.0_|8.1|10.2|9.0|12.0|9.3|12.8|11.2|14.4|
|Food|10.5|11.2|11.0|10.3|9.8|9.7|9.2|1 0.2|9.3|8.8|

# _Source: Calculation by Appleton and Collier (1990), p._<sup>_8_</sup> _4.._

The size of the groups and their mean and median incomes per capita are given in Table 1.2. As already explained the same household may belong to more than one group depending on the diversification of activities of their eaming members. The figures are not to be confused with eamings per worker in the different sectors. The full distribution of households by per capita income deciles is given in Appendix Table Al of Appleton and Collier (1990) paper.

3
<!-- Start of picture text --> 60.0 Private Credit / GDP (%)<br>40.0 |<br>-— ——<br>0.0 PTT TL.<br>2000 2001 2002 2003 2004 2005 2006 2007 2008 2009<br>(__1 Value Observed Regional Median == Income Group Median<br>—— Expected median —— Peer Group Average<br><!-- End of picture text -->
NIGER’S INFRASTRUCTURE: A CONTINENTAL PERSPECTIVE

# **Challenges**

Niger still faces tremendous challenges in extending access to ICT. Barriers include low incomes, relatively high prices, lack of electricity,<sup>15</sup> and a large, landlocked landmass. Niger, however, has a good platform to grow the sector with a partly private incumbent operator, a second national operator, and a competitive mobile market.

**Figure 17. The efficient market gap in Niger—highest in the region**

<!-- Start of picture text --> 100%<br>90%<br>80%<br>70%<br>60%<br>50%<br>40%<br>30%<br>20%<br>10%<br>0%<br>Existing access Efficient market gap Coverage gap<br>Percent of population<br><!-- End of picture text --> _Source:_ Mayer and others (2009) using GSM coverage figures as of 2005. _Note:_ Existing access represents the percentage of the population covered by voice infrastructure as of the third quarter of 2006.

Efficient market gap represents the percentage of the population for whom voice telecommunications services are commercially viable given efficient and competitive markets. Coverage gap represents the coverage gap—the percentage of the population for whom services are not viable without a subsidy.

With a per capita income of $300 in 2008, Niger is the sixth-poorest country in the world.<sup>16</sup> Although the mobile market is competitive, prices have not dropped as sharply as expected, and around half of rural communities are still without access to telecommunications services (Adamou 2009). Prices for fixed, mobile, and Internet services are all above the regional average (table 1). Estimations suggest that to achieve universal mobile coverage, around 14 percent of the population would need to be subsidized (figure 17). Improving the administration of the universal service fund will efficiently fill coverage gaps in rural areas that are not likely to be met by commercial services.

In the regional context, Niger has the lowest mobile penetration among the ECOWAS countries, even though Guinea-Bissau, Liberia, and Sierra Leone all have lower per capita incomes (table 15).

Internet penetration is low, at just over 1 percent of the population. Nevertheless there are signs that the market is beginning to develop, including recent sharp increases in international connectivity (figure 18a) and wireless broadband service offerings, and a reduction in retail Internet prices. Meanwhile, Niger’s Internet penetration and connectivity still lags most of its ECOWAS peers (figure 18b). The price of a fixed ADSL<sup>17</sup> subscription has fallen by more than one half (in local currency) since 2008. The incumbent offers a CDMA<sup>18</sup> -based wireless service with an option of unlimited monthly Internet access at

> 15 Only around 10 percent of households with electricity.

> 16 Based on gross national income (GNI) per capita using the Atlas method. Data from the World Bank’s World Development Indicators (http://data.worldbank.org/indicator/NY.GNP.PCAP.CD). 17 Asymmetric digital subscriber line.

> 18 Code division multiple access.

32