rafmacalaba/datause-encoder-data huggingface dataset:
<!-- Start of picture text --> The Taxonomy defines which<br>economic activities can be<br>ieegulation= sustainable”.considered. These“environmentallydefinitions are<br>used for both the SFDR and CSRD*<br>The SFDR specifies how financial The CSRD applies to all large<br>market participants. should disclose. companies and all companies listed<br>re P CSRD on regulated markets. It ensures that<br>sustainability information to end . . .<br>. . : (replacing investee companies report the<br>investors. To do so, financial market . : . i<br>. NFRD) information that financial market<br>participants need adequate - . :<br>. : . . participants need to fulfil their own<br>information from investee companies . .<br>SFDR reporting requirements<br>*The Taxonomy applies to (i) financial market participants, (ii) entities in scope of the NFRD, and (iii) Member States and the EU<br><!-- End of picture text -->
is also important for the efficiency of the policy. E-filing was not mandatory in Ukraine, however our estimates from this country show that an increase in TCC is associated with e-filing usage up to 25%. This should not be too surprising as most SMEs performed double filing in the country, due to lack of trust on the online system, although paper filing was not required. We provide a detail analysis on all of these in the following sections.

Firm level cross sectional survey data sets with quite detailed information on firm characteristics were used in this analysis. Our identification strategy and related assumptions are discussed below. We were critical about many potential sources of endogeneity and especially careful about self-selection. Nevertheless, our results should be taken suggestive rather than strict causality.

In what follows, the differences in policy implementation across countries and data coverage in each survey are provided along with a discussion on theoretical background and empirical identification. In section 2, we present a descriptive analysis of each data set from all three countries separately. Section 3 sheds further light on the hypothesis from regression analysis and Section 4 concludes with research findings.

# **1.1 Policy Implementation and Survey Coverage**

The analysis here is based on the experience of three countries: South Africa, Nepal, and Ukraine.<sup>8</sup> As each country has had different policy experiences, it is important to discuss these differences, including policy implementation and other details about the survey coverage, while doing the analysis.

In South Africa, e-filing was introduced in 2003, but initially only for value added (VAT) and employment taxes. E-filing for income taxes for companies and individuals followed in 2006. According to the policy implementation in the country, e-filing is voluntary and e-filers are not required to file paper returns once the process is completed electronically. An important consideration is that the TCC

> 8 TCC survey has been conducted for 12 developing countries although only three of these countries provide sufficient information for our analysis. See Coolidge (2012) fur further details on some of the data for excluded countries.

4
23 higher education, benefits are always skewed toward the upper classes but taxes appear to be even more skewed so higher education is still, in most cases, moderately redistributive. The Japanese public system is more redistributive than most U.S. state university systems because the state sales and property taxes which are used to finance higher education in the U.S. are less progressive than the national income tax system which is used to finance universities in Japan, However, the community college system in the U.S. is the most redistributive of all, because its students come disproportionately frcm low income groups (see James and Benjamin, 1987 and 1988).

In Selowsky's study of the distribution of health, education and other social services in Colombia, the upper income groups received larger benefits but the benefit distribution was not nearly as skewed as the distribution of income and taxes; hence the overall effect of governmental spending and taxation was mildly redistributive toward the poor (Selowsky, 1979).

In Brazil the bottom income quintile receives 7Z of total social benefits while the top quintile receives 41Z. This is certainly an incomebiased pattern of benefits. If the tax system were progressive or proportional the net impact would nevertheless be redistributive toward the poor, since income is even more skewed (see World Bank, 1988). However, the Brazilian tax system is probably regressive, because of the preponderance of payroll taxes, the flat rate structure, the poor coverage and the existence of hidden subsidized and tax credits (World Bank, 1989). Therefore, it is not at all clear that the public provision of social services increases the real welfare of the lowest income groups, on balance. At the same time, there is probably a redistribution to the poorer regions. For example, social security
influenced by lower levels of financial literacy and a market that is smaller in size relative to the economy generally. More mature markets have a wider range of products and services and a greater tendency in the population to utilize insurance services, providing opportunities for more market participants, some specialists in particular product lines, and a more readily accessible pool of operational staff.

Figure 6 presents the plot of insurance penetration, premium expressed as a percentage of gross domestic product, compared to Herfindahl Index values. Table 3 provides the results of the fitted regression lines that are also shown on the charts.

Overall, although the trend line is able to be generated, the explanatory power of the insurance penetration measure appears to be limited, and particularly so in the case of non life insurance market dynamics. Even when the trend line parameters are considered, it is important to remember that the actual values for insurance penetration are not large in their own right so will have only a limited range of variation on the prediction of the Herfindahl Index. As such, the pattern appears to be inconclusive suggesting that the level of development does not materially impact the observed level of market competition.

One conclusion that is more apparent is that there are no cases where insurance penetration is high and the Herfindahl Index value is high as well. This suggests that less liberalized markets are not consistent with increased utilization of insurance products.

**<u>Figure 6: Variation in Herfindahl Index to Insurance Penetration</u>**

<!-- Start of picture text --> Life Non Life<br>7100 7100<br>6100 6100<br>5100 5100<br>4100 4100<br>3100 3100<br>2100 2100<br>1100 1100<br>100 100<br>0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0<br>Insurance Penetration Insurance Penetration<br>Source: Staff Analysis<br>Herfindahl Herfindahl<br><!-- End of picture text -->

**Table 3: Statistical Summary of Results of Regression Lines Comparing Penetration to Herfindahl** **<u>Indices</u>**

|Case|Constant||Slope||_r_<sup>_2_</sup>|
|---|---|---|---|---|---|
|||Value|Upper Confidence<br>Interval|Lower Confidence<br>Interval||
|Life|2147.986|(111.471)|(71.228)|(151.714)|3.29%|
|Non Life|1492.141|(106.654)|(51.483)|(161.826)|1.48%|

Note: Confidence intervals shown are calculated on the basis of a two sided 95% probability. Source: Staff Analysis 12
environment for intense high-tech work (in Silicon Valley), exceptional outdoor recreational activities, and a vibrant urban center in downtown San Francisco (Florida 2002, Newscientistjobs.com 2003a).

It is clear that in the new knowledge economy, costs or government-influenced low costs (e.g., lower taxes) and access to natural resources are less important. To attract both creative people and firms, places need to foster a culture of innovation and provide an integrated habitat for all forms of creativity.<sup>35</sup> The winning formula in Europe appears to have been a combination of a favorable business environment and technological acumen (Kelly 2003, Simmie 2001). Particularly important are local policies designed to build an infrastructure to support small and emerging creative businesses. Such policies range from establishing industry forums to identify sectoral needs, creating publicly supported venture capital funds, investing in digital labs, supporting art and technology studios, organizing trade missions around particular products, to providing business development support and training (Tepper 2002). In the U.S., San Diego’s phenomenal rise is probably most inspiring. But this is not to suggest that San Diego’s competitive edge is locked in. In fact, it faces imminent shortages in the supply of marketing and management professionals and skilled workers.

Despite concerted development efforts and presence of leading research universities, some places remain trapped in past cultural and organizational norms and unable to adapt to new technologies. The case of Baltimore may be a good example of local inertia and an alternative model of university research. Funded in 1876 as the first research university in the U.S. and ranked today as the single largest recipient of federal R&D funding, Johns Hopkins University has given priority to basic research and scholarly publication from the very beginning.<sup>36</sup> Its dedication to the norms of “open science” also has been translated into an unwillingness to allow commercial interests to influence research (Feldman and Desrochers 2004). This academic culture has not encouraged direct involvement with industry, and instead has carried an almost persistent emphasis on fundamental inquiry. The failure of its first spin-off company or

> 35 The Creative Index developed by Florida (2002) is a useful gauge of the creative capabilities of places.  This index is a mix of four equally weighted factors: share of creative employees in the workforce, innovation measured by patents per capita, presence of high-tech industry, and diversity measured by the Gay Index. 36 On the other hand, the university ranked second to lowest among the top twenty American universities in its percentage of industry-sponsored research as a proportion of total research expenditure at the end of 1990s (Feldman and Desrochers 2004).

25
of context-specific factors enabling or hampering mobilization. Consistent with the grievancebased approach to rebellion, we find that a decrease in subjective well-being – and particularly an increase in the percentage of self-reported _suffering_ people in a country – positively affects nonviolent uprisings, proxied by the number of demonstrations and strikes. A one-percentage point increase in suffering increases nonviolent conflict events by 2.1%. The magnitude of this effect is similar to that of a percentage point decrease in GDP growth.

We address endogeneity concerns by instrumenting our subjective well-being measure with the ratio of deaths due to infectious diseases, complemented by a lag structure in a system GMM model. We also test and confirm the robustness of our results using a more inclusive measure of nonviolent uprisings than the one based on anti-government protests and strikes. This measure includes government boycotts, sit-ins and nonviolent takeovers of buildings that involve mass mobilization. Further exploration of the ways dissatisfaction with different life domains affects nonviolent resistance reveals that changes in the perceived ability to lead a purposeful and meaningful life and changes in the perceived standards of living to a large extent explain the effect of subjective well-being on nonviolent uprisings. In addition, our results suggest that the effect of grievances on peaceful conflict does not depend on context-specific factors – a finding which provides empirical support for the grievance-based theory of peaceful protest. While we find evidence of an effect of well-being on nonviolent civil conflict, we do not find a similar effect on its violent counterpart. This result provides support to the notion that the determinants of violent and nonviolent conflict differ and that grievances in and of themselves might not necessarily legitimize the use of violence.

Our findings contribute to the political economy literature on subjective well-being and political dissent (e.g. Di Tella & MacCulloch, 2005; Flavin & Keane, 2012; Frey, 2012; Liberini, Redoano & Proto, 2017) and the literature on nonviolent conflict (Chenoweth & Ulfelder, 2017). Although economists have traditionally been reluctant to include subjective 6
Table 2: Baseline household characteristics between treatment and control groups

||Con|trol Grou|p|Treat|ment Gro|up||
|---|---|---|---|---|---|---|---|
|Variable|Mean|SD|N|Mean|SD|N|Difference|
|Household Size|5.272|2.735|4465|5.632|2.854|834|0.360|
|Male|0.733|0.443|4465|0.770|0.421|834|0.037*|
|Age|46.095|13.821|4465|45.400|13.466|834|-0.695|
|Urban|0.516|0.500|4465|0.702|0.458|834|0.186|
|Electricity|0.553|0.497|4465|0.533|0.499|834|-0.019|
|No Education|0.205|0.404|4129|0.207|0.405|760|0.002|
|Primary Education|0.154|0.361|4129|0.171|0.377|760|0.016|
|Secondary Education|0.566|0.496|4129|0.564|0.496|760|-0.002|
|Tertiary Education|0.075|0.263|4129|0.058|0.235|760|-0.016|
|HH. members in Industry|0.277|0.447|4029|0.202|0.401|747|-0.075|
|HH. members in Services|0.522|0.500|4029|0.383|0.486|747|-0.139|
|HH. members in Agriculture|0.502|0.500|4029|0.664|0.473|747|0.162|
|Numberof income earners|2.102|1.171|3647|2.070|0.910|704|-0.032|

Notes: This table reports average characteristics of households in the control and treated groups using data from GLSS 5. Standard errors of the differences in average characteristics are in parentheses *** p<0.01, ** p<0.05, * p<0.1 24
Policy ReseaRch WoRking PaPeR 4876

# **Abstract**

Food policy often depends on markets and markets depend on institutions. But how good do institutions have to be before reforms can be launched? Relying on well timed surveys of agricultural prices and a joint study by the Government of Bulgaria and the World Bank on agricultural market institutions, this paper presents evidence that performance in food markets improved following significant policy reforms in Bulgaria, although public institutions remained weak. This suggests that even though strong institutions are preferred to weak ones, it can be costly and impractical to delay policy reforms until work on strengthening institutions is finished. Still, measured performance varied by place and by commodity, suggesting that markets developed at different tempos and that the distribution of benefits from improved markets was uneven. This points to the need to address the costs of adjustment as policies change. The paper introduces a new approach to measure market performance based on composite-error techniques.

This paper—a product of the Sustainable Rural and Urban Development Team, Development Research Group—is part of a larger effort in the department to understand how policies affect food markets in developing countries. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The author may be contacted at DLarson@ worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
22 results obtains because monitoring costs are asoumed to be small. Larger costs would qualify these conclusions."1 These results however also give food for thoughts if the federal government is willing to consider suboidies of the monitoring activities. Table 5 suggeots that, for a given level of sales tax revenue, as long as monitorlng costs do not offset the revenue from pollution taxes, the states will have an incentive to monitor to capture the potential pollution tax revenue. While this is not addressed explicitly in this version of the model, this implies that the federal government should compare the costs of inspecting the states against the cost of subsidizing monitoring by the states.

|Tib**l**e.5:<br>Y c<br>o.rcnce-ofrPollut<br>tiiio'n'Tes<br>f'or<br>|<br>"POAlut<br>Po<br>|ins<br>Cotr<br>llution**T**<br>(in cts|**ax**Rate<br>/lb)|
|---|---|---|---|
|2.63|0.10|1.00|10|
|Utility Maximizing Federal Inspection<br>level for low pollution aversion<br>100%|0%|0%|<br>100%|
|Net Federal Monitoring Revenuae<br>as % of<br>state revenue)<br>6.4%|0%|0%|12%|
|STATB||||
|Federally mandated State Monitoring<br>48%|100%|100%|<br>11.3%|
|MLnimum monitoring required for firms to<br>3.4%<br>invest in abatement|89.2%|8.9%|0.9%|
|NetState<br>revenue as %oforiginal VAT<br>revenue<br>135%|107%|143%|127%|
|FIRM (at the level of monitoring implied<br>by the federal attitude)||||
|Investment in Pollution Control as % of<br>total capital<br>15%|0.14%|11.88%|11.89%|
|Pollution Level as % of orLginal<br>55%|99.58%|64.37%|56.72%|
|Value added as % of original<br>94%|99.99%|96.35%|94.78%|

19 . This will be addresed in a follow-up paper which will include a diacuaion of eltemative modes or fuuncing of thea **cos** and their incidence on the federal and stte budgets.
|local<br>ls the||95%|0.53<br>0.31|0.35|0.33<br>0.35|0.32|0.24<br>0.25|
|---|---|---|---|---|---|---|---|
|of <br>oo||er||||||
|uations <br>which p|**to 2008**|95%<br>Upp|0.44<br>0.20|0.26|0.21<br>0.23|0.23|0.16<br>0.15|
|eval<br>l 1,|**2007**|Lower||||||
|gh on <br> Mode||ˆ<br>_D_<br>|0.48<br>0.25|0.31|0.27<br>0.29|0.28|0.20<br>0.20|
|to hi<br>ns of||95%|0.34<br>0.16|0.16|0.13<br>0.13|0.11|0.07<br>0.06|
|low <br>catio||Upper||||||
|from <br>pecif|**r 2008**|95%<br>|0.28<br>0.07|0.07|0.02<br>0.03|0.04|0.02<br>0.01|
|ables <br>ree s|**Yea**|Lower||||||
|ri<br> th||ˆ<br>_D_|1<br>2|2|7<br>7|8|4<br>3|
|va<br>m|||0.3<br>0.1|0.1|0.0<br>0.0|0.0|0.0<br>0.0|
|atory<br>ed fro||95%|0.30<br>0.13|0.12|0.10<br>0.12|0.09|0.06<br>0.05|
|lan<br>lat||pper||||||
|owing exp<br> were simu|**Year 2007**|ower 95%<br>U|0.22<br>0.05|0.06|0.02<br>0.02|0.03|0.01<br>0.01|
|the foll<br>erences||ˆ<br>_D_<br>L|0.26<br>0.09|0.09|0.06<br>0.07|0.06|0.04<br>0.03|
|ws the efect of a change in <br>rustworthiness. The frst dif|||for good of community<br>ion)<br> (vs. highly unsatisfed)|. highly unsatisfed)|by government (vs. NGO/mission clinic)<br>ember (vs. didn’t register)|rking fridge (vs. no fridge)|un by government (vs. non-state actor)<br> (vs. not free)|
|le sho<br>illor t<br>a.|||money <br> corrupt<br>ucation|alth (vs|nity run<br>amily m|as a wo|munity r<br>tbooks|
|ab<br>nc<br>dat|||end<br>n or <br>h ed|h he|mu<br> a f|tal h|om<br> tex|
|his t<br> cou<br>08|||ors sp<br>te gai<br>ed wit|ed wit|in com<br>ath of|hospi|ol in c<br>es free|
|2: T<br>ment <br>nd 20||ble|councill<br>or priva<br>y satisf|y satisf|h clinic <br>tered de|h clinic/|ry scho<br>l provid|
|Table <br>govern<br>2007 a||Varia|Local <br>(vs. f<br>Highl|Highl|Healt<br>Regis|Healt|Prima<br>Schoo|

27
We show that expected earnings do predict whether or not individuals apply to migrate, and then explore several explanations for the underestimation of employment likelihoods and expected earnings. We find individuals to have lower expectations of employment in New Zealand if they live close to the houses of migrants who were unable to take up their initial job offers. This is consistent with the behavioral/psychological literature in which individuals place disproportionate emphasis on negative events (Taylor, 1991). We find that the degree of underestimation of earnings is greater when individuals have cousins, uncles and aunts in New Zealand compared with those who either have no relatives or who have immediate family in New Zealand. The anthropological literature on the Tongan diaspora (Lee, 2003), shows that the extended family can place large demands for remittances on migrants. We view the underestimation of earnings by potential emigrants with extended family abroad as suggesting that immigrants mitigate this remittance pressure by understating their earnings abroad when communicating with their extended family.<sup>4</sup> We also find the degree of underestimation to be larger for males than for females. Males and females earn similar amounts in Tonga conditional on age and education but there is a large male earnings premium in New Zealand. This male earnings premium in New Zealand appears to be unknown to potential emigrants in Tonga.

Our results show that potential emigrants can have very erroneous expectations about the incomes that can be earned abroad. We find this even in Tonga, a country where over three-quarters of households have at least one resident who has been to New Zealand, with a migrant stock in New Zealand equal to 17 percent of its population at home and with 75 percent of households receiving remittances. Thus we would expect that potential migrants in other countries, which have weaker links to destination countries and smaller migration information networks to draw upon, are also likely to have incorrect expectations about potential incomes abroad.

> 4 Tonga is very remittance-dependent. According to data are from the Tongan Household Income and Expenditure Survey (http://www.spc.int/prism/Country/TO/stats/Surveys/HIES-new/hhincom-new.htm) 21 percent of household monetary income is from remittances. Moreover, the average immigrant household in our survey in New Zealand sends remittances to Tonga of $1900 cash and $600 goods per year, from an annual income of $33,000. Hence these are significant income flows for both senders and receivers.

4
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