rafmacalaba/datause-encoder-data huggingface dataset:
cotton ginning and processing quality would have increased towards international standards, and this would have, in tum, benefited the domestic yarn and other textile production both in terms of quality and exports.

# _Mismatch of_ **_Cotton Varieties_**

Export restrictions on cotton have also caused the mismatch of cotton varieties in the domestic market in India. The staple length of cotton determines the right count of yarn spun from that cotton; long-staple cotton, medium-staple cotton, and short-staple cotton are most suited to the production of high-count (i.e., fine) yam, medium-count yam, and low-count (i.e., coarse) yarn, respectively.<sup>9</sup> In India, out of the total domestic consumption of cotton, 53 per cent was long-staple (including extra-long staple), 41 per cent was medium-staple, and 6 per cent was short-staple, while 14 per cent of the cotton yarn produced by the domestic mills was over 61 counts, 47 per cent was 21 to 40 counts, and 39 per cent was 1 to 20 counts in 1994/95 **(Table 8).**

**Table 8:** **_Staple-wise Cotton Consumption and Count-wise Yarn Production_**

|Cotton Staple|Staple-wise Share (A)|'Yam Count|Count-wise Share (B)|Ratio (A)/(B)|
|---|---|---|---|---|
|Long Staple|_53_%|Over 60 Counts|14 %|3.8|
|Medium Staple|41 %|' 2I to 60 Counts|47 %|0.9|
|Short Staple|6 %|lJp to 20 Counts|39 %|0.2|
|Total Cotton|100%|Total Yarn|100%|1.0|

Sources: Office of the Textile Commissioner, GOI (1995) etc.

There are two domestic factors behind this gap. On the supply side, the proportion of long-staple cotton has increased at a faster pace than shorter-staple cotton. Conversely, on the cotton demand side, the majority of India's cotton yarn production is in medium- and lower-counts, and the production of highercount yarn is still limited. This is because of the shifting preference of high income people from fine quality cotton textiles to man-made yarn textiles, technical constraints in the mill sector, and the high excise duty levied on higher counts of cotton yarn, as pointed out by Misra (1993). Thus, as a result of the excess supply of long-staple cotton in the domestic market, many spinning mills have overused higher-quality cotton. Moreover, the strength of lower counts of yarn has been sacrificed because longer staple cotton is not suitable for production.

The necessity to liberalize cotton exports is even more obvious if we consider the import of cotton, 20
Fjeldstad and Moore, 2008: 235-6, 259). Among the 67 countries with increases, 38 rose by only a half point, 18 by a full point, 8 by 1.5 points, and 3 by two full points. The correlation of ratings for 1999 and 2006 is .62 (rank correlation .61).

Despite the extensive criteria Bank staff are supposed to use in assessing ERM, one might think certain objective proxies are used as shortcuts, e.g. tax revenues as a share of national income (“tax effort”) or trade taxes as a share of revenues. These variables are in fact both significantly related to ERM ratings, but together they explain only about one-sixth of the variation in ERM. Alternatively, as is potentially the case for any subjective governance indicator, quality of tax policy and administration could be inferred merely from per capita income levels or recent growth rates. However, income (2006) and growth (1999 to 2006) together explain only 22% of the variation in ERM. These results are consistent with the supposition that staff assessments of ERM take into account the broader criteria in the questionnaire as intended.<sup>1</sup> The dependent variable used in the empirical analyses below is the 2006 ERM ratings. We test the impact of sovereign rents over the period 1999-2005, controlling for initial (1999) ERM ratings.<sup>2</sup> The key independent variables of interest are aid and natural resource revenues.

Aid is measured by "official development assistance" (ODA) as a percentage of gross national income (GNI), using data for the years 1999-2005 from the World Bank’s _World Development Indicators_ . These data were originally collected by the OECD’s Development Assistance Committee from each donor agency. Aid (ODA) includes

> 1 Internally, staff provide written justifications for all ERM ratings.  Some justifications are more comprehensive and relevant than others, but in general they show that staff take the questionnaire criteria very seriously in their assessments.

> 2 Annual variation in the data is not used, because effects of aid and resource rents may show up only with substantial lags.

7
<!-- Start of picture text --> 2.50<br>2.235<br>2.00<br>1.75<br>1.50<br>1.25<br>1.00<br>O.Fs5<br>0.40<br>Oo.25<br>Tosa 1926 1988 1990 19923 1994 1996 1992 2000<br><!-- End of picture text -->
of female labor force participation, even when compared to other countries in the Middle East. Second, despite dramatic improvements in women’s human capital over recent decades, their labor market outcomes have been rather stagnant (Winkler & Gonzalez (2019)). Third, internet use increased dramatically during the period under analysis (from 2010 to 2016), with the share of users increasing from 5 to 61 percent of the population. The increase was even larger for mobile broadband access, going from near zero in 2010 to approximately 60 percent of the population in 2016 (Telegeography (2018)). Such large increase, together with the availability of longitudinal data, is crucial to the design of the identification strategy of this article.

This article is structured as follows. Section 2 provides a review of the literature on the impacts of information and communication technologies (ICT) on labor market outcomes, with a focus on women in developing countries. Section 3 describes the data sources and main trends in labor market indicators and internet penetration, and section 4 discusses the identification strategy. Section 5 presents the results, and section 6 concludes.

# **2 Digital technologies and women’s labor outcomes**

This article contributes to the literature on the labor market impacts of internet access. The internet can affect labor market outcomes through different channels. It could contribute to improve labor market efficiency, by increasing access to information about job vacancies, lowering the recruiting costs for employers and increasing the quality of job matching (Autor (2000)). On the other hand, since this technology increases the economies of scale of job applications for potential workers, it could also increase the screening costs of firms significantly and lower matching quality (Oyer & Schaefer (2011)).

Empirical literature finds, in general, positive impacts of internet access on labor market outcomes. In the United States, unemployed individuals who search for a job online found a job 25 percent faster than those who search offline, even after accounting for other differences 3
While Maddison's (2001) GDP estimates are not directly comparable to those of Bairoch (because of differences in regional grouping and currency measurement), there are some consistencies between the two. (See Tables H.6 through H.9 in the Historical Appendix.) Table H.6 reveals that total GDP for Asia exceeded that for Western Europe in the periods up to the late 1gth century - being two to four times greater in the periods between 1500 and 1820. This divergence is even more apparent in Table H.8, which shows Asia's share of world GDP at a remarkable 70 percent in the year 1000 versus about 9 percent for Western Europe. As Asia's share declines gradually to 59 percent in 1820 with a further drop to 38 percent over the next 50 years (to 1870), Europe's share increases at a slow, steady pace to reach 33.6 percent by that year. By 1913, however, Europe overtakes Asia and maintains that lead until the late **20t1h** century.

Maddison's estimates of per capita GDP follow a different trajectory from those of Bairoch. His estimates in Table H.9 show that from 1500 onward, Europe's per capita GDP surpassed that of Asia. In the year 1000, per capita GDP was nearly the same for both regions (I$40021 for Europe and I$449 for Asia). By 1870, that for Europe had risen fivefold, whereas that for Asia had increased only 23 percent. The gap only becomes greater throughout the 20th century with Europe's GDP per capita reaching a level five times that of Asia by the end of the century (based on Maddison's 1990 international Geary-Khamis dollars).

Maddison estimates that China's per capita GDP exceeded that of Europe from the 5h to the 14th centuries<sup>22</sup> (see Table 1.4 below) after which China (along with most of the rest of Asia) remained more or less stagnant in per capita terms until the second half of the 20th century. He credits the higher levels of income in the earlier periods to China's "technical precocity and meritocratic bureaucracy"<sup>23</sup> and attributes the stagnation in Asia initially to "indigenous institutions and policy, reinforced by colonial exploitation which derived from Western hegemony and was most marked from the eighteenth century onwards."<sup>24</sup> Table 1.4 <!-- Start of picture text --> "Guesstimated" Level of Chinese and European GDP Per Capita, 50-1700 AD<br>(1990 $)<br>Year<br>50 960 1280 1700<br>China 450 4501 600 600<br>Europe' 450 400 500 870<br>a Excluding Turkey and USSR<br>Source: Maddison (1998: Table 1.3, 25)<br><!-- End of picture text --> Based on Maddison's data, Japan was an exception as it did not experience this stagnation. Japan's per capita GDP remained lower than that of Asia as a whole until the early 19th century. Maddison believes that income levels in Japan were probably depressed in 1500 because of civil war but estimates a substantial increase in performance in certain sectors of the economy from 1600 to 1820. His estimate is that Japanese GDP per capita rose by a third from _1500_ to 1820 and, thus, caught up with and surpassed that of China and most of the rest of Asia by the early **1 9th** century. He 6
**TABLE 1 EMDE small states, by feature**

||**Tourism**<br>**reliant**|**Commodity**<br>**exporter**|<br>**FCS**|**Micro**<br>**states**|**Risk of overall**<br>**debt distress**|**Grant**<br>**reliant**|**World Bank**<br>**lending**<br>**category**|
|---|---|---|---|---|---|---|---|
|Antigua and Barbuda|X|||X|||IBRD|
|Bahrain|X|X||||||
|Barbados|X|||||||
|Bahamas, The|X|||||||
|Belize|X|X|||||IBRD|
|Bhutan||X|||Moderate|X|IDA|
|Brunei Darussalam||X||||||
|Cabo Verde|X|X|||High|X|Blend|
|Comoros||X|X||High|X|IDA|
|Djibouti|||||High|X|IDA|
|Dominica|X|||X|High||Blend|
|Eswatini|||||||IBRD|
|Fiji|X|X|||||Blend|
|Grenada|X|||X|In distress|X|Blend|
|Guyana||X|||Moderate||IDA|
|Kiribati|||X|X|High|X|IDA|
|Maldives|X||||High||IDA|
|Marshall Islands|X||X|X|High|X|IDA|
|Mauritius|X||||||IBRD|
|Micronesia, Fed Sts.|X||X|X|High|X|IDA|
|Montenegro|X||||||IBRD|
|Nauru||||X||X|IBRD|
|Palau|X|||X||X|IBRD|
|Samoa|X||||High|X|IDA|
|São Tomé and Príncipe||X|X||In distress|X|IDA|
|Seychelles|X|X||X|||IBRD|
|Solomon Islands||X|X||Moderate|X|IDA|
|St. Kitts and Nevis|X|||X|||IBRD|
|St. Lucia|X|||X|||Blend|
|St. Vincent and the<br>Grenadines|X|||X|High||Blend|
|Suriname||X|||||IBRD|
|Timor-Leste||X|X||Moderate|X|Blend|
|Tonga|X|||X|High|X|IDA|
|Tuvalu|||X|X|High|X|IDA|
|Vanuatu|X||||Moderate|X|IDA|

_Sources_ : GFS (database); UN World Tourism Organization; World Bank.

23
stoichiometrically per unit of fuel and there are currently no ways to actually abate emissions (absent carbon capture and storage technologies). So tax rates can be fuelspecific and tuned to the actual carbon content. This is important because the analysis shows how much lower the welfare losses are for the carbon tax instrument.

The results confirm the conventional argument that the relevant deadweight loss will generally be small for energy related taxes. Moreover, labor market distortions such as labor market segmentation or unemployment will likely dominate the welfare and equity implications of a carbon tax for South Africa. This being the case, if South Africa were able to remove some of the distortions in the labor market, the cost of carbon taxation would be negligible. With the supply mix of energy being tilted towards coal, the adoption of a cleaner technology, possibly financed in part by the revenue potential of a carbon tax, is an important medium-term policy issue. Although mitigation-related public finance issues are the focus in the paper, adaptation measures will also be important for South Africa. In addition, South Africa interacts with other countries in southern Africa and there is potential to share power resources in the region. Finally, there may be carbon leakages as South Africa imports goods from neighboring countries with lower taxes applied to energy goods. All these are areas for further research.

In sum, the discussion of whether South Africa should tax carbon emissions can now focus on other considerations than the welfare costs, which are likely to be quite low.

# **References**

- Ahmed, Hashim, Channing Arndt, Sherman Robinson, and Dirk Willenbockel, 2008. “A Country Study on the Economic Impact of Climate Change: The Case of Ethiopia.”  The World Bank, draft.

- Aldy, Josheph E., Scott Barrett, and Robert N. Stavins, 2003. “Thirteen plus One: A Comparison of Global Climate Architectures.” _Climate Policy_ 3: 273-97.

- Aldy, Josheph E., Eduardo Ley, and Ian Parry, 2008. “A Tax-Based Approach to Slowing Global Climate Change.” _National Tax Journal._ Vol. LXI, No. 3 (September), pp. 493-517.

- Beghin, J., D. Roland-Holst,  and D. van der Mensbrugghe (1994). “Trade Liberalization and the Environment in the Pacific Basin: Coordinated Approaches to Mexican Trade and Environment Policy.” Presented at the 1995 ASSA meeting, Washington, D.C.: January 7-9, 1995.

- Bovenberg, A. Lans and Lawrence H. Goulder, 2002. “Environmental Taxation and Regulation.” In A.J. Auerbach and M. Feldstein, eds., _Handbook of Public Economics,_ Vol. 3. New York: North-Holland, chapter 23, pp. 1471-1545.

28
heavily after 2004 independently of EU membership. The small increase after 2007 also reflects weaker economic ties between Germany and Romania.

## [Figure 3 about here.]

It is worth noting that the sharp increase in foreign acquisitions was not likely driven by the lift of restrictions on FDI. OECD data on FDI restrictiveness for Poland show that screening and legal restrictions on FDI in manufacturing sectors had already been greatly removed by the time of accession. Hence, the observed increase in FDI could be attributed to the removal of the uncertainty regarding the future relationship with EU members and the progressive alignment of regulations associated with EU membership.

# **5.3 Differential effects of EU accession on firm performance across sectors**

In this section, we examine how Germany’s initial specialization patterns shaped the overall effects of EU accession on firm performance. These effects capture not only the direct effects of German acquisitions on firm performance, but also horizontal and vertical spillovers from FDI, as well as broader knowledge transfers (which may be unrelated with FDI).

## **5.3.1 Main results**

Table 3 reports the point estimates yielded by estimating equation (4), using Germany’s initial export shares in the sector during 1994-2004 as measures of industrial specialization. The specification in column (1) considers the effects of accession on TFP. The one reported in column (2) considers effects on revenue. Finally, the estimates in columns (3) and (4) estimate effects on employment and exports, respectively. The point estimates reveal that Polish manufacturing firms operating in sectors in which Germany was more specialized at the moment of accession experienced significantly higher TFP growth in the post-2004 period. More specifically, a 10% increase in Germany’s export share is associated to a 0.5% increase in the productivity of Polish firms. The point estimates on revenues and exports are also positive and of slightly larger magnitude. This may reflect the fact that German acquisitions may have targeted Polish firms to exploit lower wages and produce labor-intensive inputs that then are brought to Germany. The effect on employment is positive but imprecisely estimated. In Table A.6 we provide estimates using an alternative method to estimate TFP based on Ackerberg et al. (2015). Results are very much aligned with those from our baseline specification.

13
class, on the other hand, are located in households from the 8<sup>th</sup> income class and above. We see, then, that the household income classes are highly positively correlated with the occupational wage earning classes.

# **4. The simulations**

This paper presents results for the central Doha scenario and for the full-liberalization scenario.

## **4.1 Model closure**

In choosing a model closure we aimed to mimic the GTAP model that generated the foreign price scenario. On the supply side, we fixed total national employment by occupation, with jobs moving freely between sectors and regions<sup>13</sup> . The model allows substitution between occupations, driven by relative wages. Similarly capital is fixed nationally but is mobile between sectors and regions. The Land stock (used just in the Agriculture activity) is fixed<sup>14</sup> . Since agriculture is an activity that produces 11 products, land is allocated to these competing products through relative prices, allowing the crop mix to change. On the demand side government and investment spending are fixed<sup>15</sup> , and a fixed trade balance enforces the national budget balance, 13 There is a tension between our GTAP-like closure and Brazilian reality. The microdata show substantial unemployment of less-skilled groups in all regions. For the microsimulation we assumed that jobs created (or lost) in a region were allotted to (or taken from) households in that region. An alternate scenario, where fixed real wages replaced national labour constraints, yielded results similar to those reported here.

14 The factor market closure causes the model to generate percent changes in prices for 10 labour types, capital and land, ie, price changes are uniform across regions. Percent changes in demand for each of the 12 factors vary in addition by sector and region. Each adult in the PNAD microdata is identified by region and labour type; those employed are also identified by sector. Changes in microdata poverty levels are driven by wage changes and by the redistribution of jobs between sectors and regions (and hence between households).

15 In real terms, since the CPI is the model’s numeraire.

15
sectors in a country that has experienced a credit crunch. We expect the coefficient � to be negative, implying that high financially dependent industries (hereafter, _high FD_ ) experience larger declines in employment outcomes as credit conditions worsen.

It is important to mention some key caveats of this method. We are only able to measure the relative effect of the credit crunch on the labor market, and not the total effect of the initial shock on the economy (i.e., savings, wealth effects, etc.). Effects of the crisis that were independent of the firmfinancing channel (such as effects operating through exchange rates, government transfers or consumer credit) are not reflected in our estimates. Further, if governments responded to the crisis with policies targeted to sectors highly exposed to the credit crunch, then our estimates would provide a lower bound for the actual impacts.

# 3. Data

Following RZ1998, we assume that there is a technological reason why some industries depend more on finance than others. We define the variable FD as the share of desired investment that cannot be financed by internal cash flows. It is calculated as the difference between a firm’s capital expenditures minus cash flows, divided by capital expenditures. We then use the median of this variable at the twodigit NACE code. We estimate this variable using data from “Compustat” data for publicly listed firms in the United States from 1995 to 2005. This sample choice is motivated by the assumption that these firms are more likely to operate in a frictionless environment and are thereby able to meet their demand for external finance. We also assume that this technological dependence carries over across countries.<sup>9</sup> Unlike RZ1998, we extend the sample to include not only manufacturing firms, but also those in the

> 9 Specifically, the identification strategy requires that the ordering of industries according to inherent dependence on external financing is the same in the US and the study sample.

8
institutions and agencies that support mining at the national level (such as the Minerals Commission, Department of Mines, and Geological Survey), 30 percent to district assemblies, 10 percent to traditional stools (local chieftaincies), and 10 percent to traditional authorities.

In contrast to the Peruvian case, the participation of local communities in mining revenue is very small. Only 10 percent of mining royalties are distributed to local communities where mines are located. This limits the scope of development projects and mitigation activities that can be implemented at the local level.

Four additional issues may impact the effectiveness of this scheme. First, the amount of revenue is highly volatile. Second, there is a lack of transparency on both the amount of royalties collected and payments made to local authorities. Third, there is no clarity on the purpose of this fund, especially for traditional stools. In this case, the law establishes that the MDF should be used to maintain the stool in keeping with its status. Finally, traditional stools and authorities are not elected, do not need to prepare budgets or financial statements, and are not subject to the oversight of national auditing authorities. This greatly reduces the accountability of local politicians and may facilitate diversion of resources and rent extraction.

# **4.3.5 Australia and Canada - fiscal decentralization**

Both Australia and Canada have federal systems with a high degree of revenue and spending decentralization. Subnational governments (states and territories in Australia, provinces and territories in Canada) own mineral resources within their territory and have the power to raise mining taxes and royalties, in addition to taxes and fees collected by the federal government.

The high degree of fiscal decentralization guarantees that a large share of mining revenues remains within mining regions. This comes at the cost of the increasing complexity of mining taxation: each province or territory imposes its own mining taxes, and the systems vary significantly.

# **4.3.6 Impact-benefit agreements – direct contributions to communities**<sup>34</sup>

In the last 20 years, mining companies and Aboriginal communities in Canada and Australia have pioneered a new way to distribute mining benefits directly to communities using so-called Impact Benefit Agreements (IBAs). These agreements are legally binding contracts between

> 34 This discussion is based on BC First Nations Energy & Mining Council (2010). 43