rafmacalaba/data-use-mentions-extended huggingface dataset:
# **Executive summary**

In environmental economics, monitoring and enforcement issues have attracted relatively little research effort. Moreover, the bulk of the literature on these issues has been of a theoretical nature. Few have empirically analysed the impact of monitoring and enforcement activities on the environmental performance of polluters. Moreover, all existing studies have been performed in the context of developed countries. A purpose of the current paper is to partially fill this important gap by exploring the impact of inspections on the environmental performance of polluters in China. Our analysis also simultaneously examines the potential impact of pollution charges and citizens' complaints.

Our analysis of plant-level data from the city of Zhenjiang shows that inspections do have a statistically significant impact on the firms' environmental performance. In the current paper, our results suggest that pollution charges do not have a statistically significant impact on firms' performance. However, this result may simply be explained by the lack of variation in pollution charges within the city of Zhenjiang which therefore prevents us from effectively capturing the impact of pollution charges. Our results also demonstrate that complaints do impact inspections significantly. Given the impact of inspections on pollution, citizens' complaints therefore do have a significant impact on pollution control. These results may provide a key to China's future quality of environment.

Whether or not these results support that additional resources be devoted to monitoring activities cannot strictly be addressed with the data currently available. Indeed, in order to do so, there would be a need to compare the costs of performing additional inspections with the net benefits of reduced pollution emissions. However, given the high level of air and water pollution currently observed in Zhenjiang, given the impact that these may have solely on health and productivity losses, it is reasonable to speculate that inspections do increase social welfare in Zhenjiang. The results however suggest that citizens can also have an important impact on pollution (via inspections). Hence, this would suggest a greater role for the regulator to embark on information and education policies.

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non‐cognitive skills affect labor supply patterns. When considering specific skills, Conscientiousness and Extraversion have a large and positive effect on labor force participation in the United States and Germany (Barrick and Mount 1991, Wichert and Pohlmeier 2010). In contrast, Neuroticism and Openness have a negative effect in Germany (Wichert and Pohlmeier 2010) while Agreeableness plays a weaker role, only affecting labor force participation of married women. In Argentina and Chile, decision‐making, leadership (cognitive), and self‐efficacy (non‐cognitive) skills are highly correlated with labor force participation in both countries (Bassi et al. 2012). As summarized by Wichert and Pohlmeier (2010), ignoring the effect of personality traits will overestimate the influence of education on labor participation, especially for women.

Few studies have also considered the role of different skills in the nature of work. A mixture of traits seems to matter both for becoming and succeeding as an entrepreneur (Levine and Rubinstein 2013). Individuals with high‐order cognitive skills (learning aptitudes) and high self‐ esteem in adolescence are more likely to become successful incorporated entrepreneurs in the United States (Levine and Rubinstein 2013). In the Netherlands, lower‐order cognitive skills (language and clerical abilities) predict wage employment, whereas mathematical and technical ability as well as extraversion in early childhood are more valuable for entrepreneurs (Hartog et al. 2010).

> 2 The data used in this study are drawn from a psychological assessment for the military.  The authors define “leadership” as the ability to function in the very demanding environment of armed combat: willingness to assume responsibility, independence, outgoing character, persistence, emotional stability, teamwork and power of initiative (Lindqvist and Vestman 2011).

> 3 Self‐efficacy refers to how individuals perceive their capability to organize their work and achieve their goals (Bassi et al. 2012, <u>p.93).</u>

**3 |** P a g e
Mayer, B. 1999. “India’s Falling Sex Ratios.” _Population and Development Review_ 25: 323-43.

Mbizvo, M., and D.J. Adamchak. 1991 _._ “Family Planning Knowledge, Attitudes, and Practices of Men in Zimbabwe.” _Studies in Family Planning_ 22 (1): 31-8.

Miller, B. 1981. _The Endangered Sex: Neglect of Female Children in Rural North India_ , Ithaca, NY, Cornell Univesity Press.

Mullany, B., S. Becker, and M.J. Hindi. 2007. _The impact of including husbands in antenatal health education services on maternal health practices in urban Nepal: results from a randomized controlled trial. Health education research_ 22: 166-76.

Nasrin, S. 2011. “Crime or Custom? Motivations Behind Dowry Practice in Rural Bangladesh.” _Indian Journal of Gender Studies_ 18 (1): 27–50.

Naved, R.T., and L.A. Persson. 2005. “Factors Associated with Spousal Physical Violence Against Women in Bangladesh.” _Studies in Family Planning_ 36 (4): 289-300.

Nepomnyaschy, L., and J. Waldfogel. 2007. “Paternity Leave and Fathers’ Involvement with Their Young Children: Evidence from the ECLS-B.” _Community, Work, and Family_ 10 (4): 425-51.

Oldenburg, P. 1992. “Sex ratio, son preference and violence in India: A research note.” _Economic and Political Weekly_ 27 (49,50): 2657-62.

Oswald, A., N. and Powdthavee. 2010. “Daughters and Left-Wing Voting _._ ” _Review of Economics and Statistics_ 92 (2): 213-27.

Panda, P., and B. Agarwal. 2005. “Marital violence, human development and women’s property status in India _._ ” _World Development_ 33 (5): 823-50.

Pande, R.P., and N.M. Astone. 2007. Explaining son
those populations (SOGI Task Force 2015) and the effect that exclusion of sexual minorities can have on the economic growth of a country (Kim 2014). As highlighted in a World Bank report on LGBTI communities around the world, data on LGBTI people are scarce, even in developed countries (Koehler and Menzies, forthcoming).

Two terms often used in the LGBTI literature are _sexual orientation_ and _gender identity_ . The closest to generally accepted definitions of those terms are those provided by the Yogyakarta Principles on the Application of International Human Rights Law in relation to Sexual Orientation and Gender Identity: Sexual orientation is understood to refer to each person’s capacity for profound emotional, affectional and sexual attraction to, and intimate and sexual relations with, individuals of a different gender or the same gender or more than one gender.

Gender identity is understood to refer to each person’s deeply felt internal and individual experience of gender, which may or may not correspond to the sex assigned at birth, including the personal sense of the body (which may involve, if freely chosen, modification of bodily appearance or function by medical, surgical or other means) and other expressions of gender, including dress, speech and mannerisms. (ICJ 2007) Finally, adopting the more developed language used in the gender equality and women’s rights literature—which often talks about _gender gap_ to refer to the gender-based disparities in the economic, political, education, and health spheres<sup>7</sup> — the study refers to disparities in the same fields between ethnic, religious, and sexual minorities and the respective majorities as _the minority gap_ . The term is clearly a gross generalization of the myriad differences among the three groups and within each group; however, it is useful in highlighting the existence of the phenomenon and is used in this paper.

> their usufructuary traditions. Unfortunately, in many countries, indigenous peoples have seen their traditional lands eroded through mass deforestation. Mining and oil and mineral exploitation are notable problems in
|**Issue**|**Recommendation**|
|---|---|
||individual labor module (after the screening questions).<br>For activities which are either (i) entrepreneurial and/or (ii) communal to the<br>household (e.g. farming), separate modules are preferable. Usually this<br>means including:<br>(i) a specifically designed module to collect data on household agricultural<br>activities. Data would be collected on land and other inputs, including<br>household labor inputs, and on the value of production sold or retained at<br>the household; and<br>(ii) a specific non-farm household enterprise model.|
||Both modules could be used to measure the inputs (hours) of all household<br>members rather than ask these questions individually, but asking both<br>individual questions on hours and enterprise/plot level questionsof labor<br>inputs is preferable to make sure that all activities get covered for all<br>individuals. See Grosh and Glewwe (2000) for examples of each<br>approach.|
|_Source: Authors_||

These techniques are often not used. One excuse sometimes offered for not using these good practice techniques is that they make the questionnaire “too long”. It is certainly true that trying to collect too much data within a multi-purpose household survey can result in a long and tedious questionnaire, and a very expensive survey – which then will become imprecise exactly because of interviewer and respondent fatigue (Grosh and Glewwe, 2000). Certainly in the case of a census, for example, to keep costs down a short questionnaire is necessary for the majority of the respondents. Some compromises are inevitably made. The problem is that the tradeoffs being made with respect to the quality and consistency of labor force and employment data may not be considered at the time because the good practice
We then discuss different ways that migration and the prospect of migration can change the family. Individuals who plan on migrating may invest less in building relationships at home, or may accelerate marriages as they think longer term. Some migration occurs specifically for the purpose of getting married. Migration can affect the stability of existing marriages, and lead to migrants meeting a new pool of potential marriage partners, changing who they might marry.

Using the American Community Survey, we provide descriptive evidence about the extent to which migrants from developing countries change their marital status after moving to the United States. We first find that changing marital status after migration is the norm for most adult immigrants: only one-third of ever-married adult migrants are currently married to a spouse they wed before migration. The model of a fixed family sending off a migrant who remains part of that fixed family is thus empirically not the reality for the majority of migrants. The likelihood of such changes importantly depends on the initial marital status before migration: for initially unmarried migrants, getting married after migration is substantially more likely than the separation/divorce from one spouse for migrants initially married. When migrants get married after migration, they are significantly less likely to marry someone who is also born in the origin country, although the incidence of withingroup marriage is substantial with 66 percent marrying someone from their country of origin (in many cases still only someone they have met after migrating). By tracking cohorts, we show that migrants who were married at the time of migrating are more likely to return migrate than those who were unmarried, but that accounting for this does not affect our main findings on family structure changing for the majority of individuals after migration. The data also reveal that instances of split migration for pre-existing married couples do not last long after migration, so what the literature calls “transnational households” (see, for instance, Ashraf et al., 2015; Clemens and Tiongson, 2017; Abarcar et al., 2020) appear to be fragile and temporary living arrangements
2.0|2.1|2.7|3.3|3.6|4.9|5.9|6.9|8.1|0.8|1.6|4.5|
|All above goods|2.0|2.1|2.3|2.4|2.1|2.5|3.0|3.3|3.5|0.3|0.0|1.5|

Source: Computations based on Pan-European import data from UN COMTRADE Statistics.
93, and the minimum is 0. In terms of transparency, the average is 7.25, with a maximum of 10, and a minimum of 1. The average of SWF capitalization in $ billion is 103.95. However, we observe a high dispersion between SWFs in terms of capitalization, confirmed by the value of the standard deviation, which is equal to 184.04. The average of the rate of return is -0.81, while the average of the risk is 0.22. The average of the dummy variable political fund is 0.61. The maximum of political SWF is 1, while the minimum is 0. In terms of institutional variables, we find that the averages of the level of the corruption is -0.49. The maximum level corruption is 0.5, while the minimum is equal to -1.12. The maximum of the variable property rights takes a value equal to 3, while the minimum is 2. The averages of private credit is 30.03 percent of GDP. The minimum of the level of financial development measured by private credit is 4.40 percent of GDP, while the maximum is 108.63 percent. In terms of correlation we find that the logarithm of the share of SWF investments in Africa is negatively correlated with the Linaburg-Maduell transparency index. This suggests that transparent SWFs are less likely to invest in Africa. However, we find a positive correlation between political fund and political index with the logarithm of the investment share, suggesting that political SWFs are more likely to invest in Africa.

> 11Their dataset is publicly available at `http://mba.tuck.dartmouth.edu/pages/faculty/rafael.laporta/publications.html` and `https://www.prsgroup.com/about-us/our-two-methodologies/icrg.`

> 12The database of SWF transparency measured by the Linaburg-Maduell index and capitalization are publicly available at `http://www.swfinstitute.org/`
development and growth. Hussein (2002) used savings to GDP as a proxy for financial development where financial savings is the sum of demand, time, and savings deposits held at deposit money banks. He utilized such to assess the response of the savings rate to the liberalization of interest rates in Egypt in early 1991. The other three studies on savings in Egypt focused on gross domestic savings that include both public and private savings.<sup>10</sup> This research fills a significant gap on empirical modeling of private savings in Egypt. It employs a new time series on private savings in Egypt that was compiled by the Central Bank of Egypt (CBE) and the Central Authority for Public Mobilization and Statistics (CAPMAS) in Egypt. This series is inclusive of savings in deposits, money banking, post offices, specialized banks, investment and savings certificates issued by banks in addition to institutional private savings in pension funds and insurance companies. These were significant components that account for almost 15% of aggregate private savings during 1990-2010.

<!-- Start of picture text --> 100%<br>Structure of Aggregate Private Savings in Egypt<br>90%<br>80%<br>70%<br>60%<br>50% Institutional<br>40%<br>Banking<br>30%<br>20%<br>10%<br>0%<br>1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011<br><!-- End of picture text --> Source: CBE and CAPMAS, 2014 While the new series is available in annual frequency, the Chow-Lin’s Temporal Disaggregation Methodology (Chow and Lin 1971) is employed to disaggregate the annual data into a higher frequency quarterly series. This methodology generates the best linear unbiased interpolation, distribution, and extrapolation of time series by using a related series called the indicator variable.
countries where regional accounts are unavailable or of low quality, yet remote sensing data are available. This substantially expands the empirical basis for the inequality-development analysis since the traditional sample bias that had limited the analysis to more developed economies with official regional accounts is now removed.

# **7 Conclusion**

As policy makers move forward in their efforts to improve living conditions and economic growth across regions of a country, acknowledging and understating that the mechanisms through which regional economic growth can be achieved differ from those that lead to national growth. Researchers and policy analyses that seek to such policies must consider that assumptions of traditional neoclassical growth models pose serious constraints for the analysis of regional economies. For regions, interregional factor endowments, and differences in levels of factor productivity, may account for the advantage or constraints faced by an area compared to the rest of the country, or the world.

This paper provides a motivation as to why different methods are needed to understand the challenges of regions. It then follows to review some of the methods available to understand and assess the challenges regions face. While this review is not comprehensive, it provides the reader a set of tools that can be used to better understand the works of regional economies. These tools can be used to better assess needs of regions and carefully determine the possible impact of policies. This paper suggests several avenues to improve our understanding of regional economies. First, a better understanding of the economic structure of local economies is key for policy design. The layout out the interindustry and inter-regional industrial structure and trade relationships play a critical role in determining the effects of various policies and program. Second, a complete description of regional economic structure begins with an inventory of employment, compensation (wages and salaries), and output by industry. Third, this will allow understanding how specialized or diversified the regional economy, what are its comparative and absolute advantages, help build behavioral models for assessing impacts of policies, and increase the understanding of interregional linkages. Regional accounting systems appear as a
dimension of consistency because, while data collection firm enumerators may offer an expert and independent perspective, such an approach is not financially sustainable for governments to implement on a periodic basis. The models also control for whether it is a public or private school, the region, and whether it is a high-poverty school (poverty rate 50% or more from the national poverty map).

From teacher and classroom observations, based on the (more detailed) diagnostic research tool data, our controls include class size, class level, having a second teacher, primary teacher age, primary teacher years teaching, primary teacher years taught at this school, and primary teacher professional status. From classroom observations, we also control for the differences between QAS tool and diagnostic research tool in the start time (in [fractional] days), to capture whether the same period is observed. From child data, our controls include, based on the (more detailed) diagnostic research tool data, child sex, child age (in months), and class level.

We estimate some models with additional controls, specifically socioeconomic status (SES) controls. For school and classroom level outcomes, we take the average asset score, the percentage of mothers (and likewise fathers) with secondary education, and similarly for higher

> 15 The dimensions do not simply average indicators within the dimension.

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difference-in-differences specification that estimates the impact of SPS and TBT provisions in PTAs on exports of a firm-HS 6-digit product before and after the entry in force of a PTA in a given destination (panel dimension) relative to exports of a firm-HS 6-digit product in destinations with no PTAs (cross-section dimension) While our empirical strategy captures the effect of the content of PTAs in terms of provisions included, we are not able to study the impact of their effective applicability, which is not observable. However, this concern is mitigated for two reasons. First, our fixed effects structure controls for any systematic under-enforcement bias in PTAs signed by Chile, Colombia, and Peru. Second, the previous version of the Deep Trade Agreements database described in Hofmann et al. (2017) reveals that the SPS and TBT chapters included in 75 and 80 percent, respectively, of the PTAs signed by Chile, Colombia and Peru are considered as legally enforceable .<sup>22</sup> The inclusion in our specifications of _τ_ , the tariff rate imposed by destination _j_ on exports of product _k_ by firms from a given origin, and of the _Depth_ variable capturing the normalized number of provisions in all 16 policy areas (other than SPS and TBT) discussed in Section 2.1 allows us to isolate the impact of SPS or TBT provisions from tariff concessions and other forms of integration provided by the PTA. Equations (1) and (2) are estimated by PPML introduced by Silva and Tenreyro (2006) with the recent command of Correia et al. (2020). Inference is based on Huber-White standard errors robust to heteroskedasticity clustered by origin-destination.

Equations (1) and (2) include destination GDP to control for time-varying destination-specific demand. A variant of our equations includes destination-year fixed effects which are a more flexible way to account for demand and macroeconomic shocks in destination markets (Appendix D.2).<sup>23</sup> Due to computational limitations, we are only able to estimate this variant using a
0%|
|Share Manufacturing Industry|1.1%|0.0109|13.2%|12.1%|
|Share Electricity, Gas , Steam, Water and Sewerage|0.2%|0.0470|1.0%|0.8%|
|Share Construction|1.5%|0.0000|9.7%|8.2%|
|Share Commerce and services|-1.3%|0.0126|23.6%|24.9%|
|Share Others|2.2%|0.0000|20.8%|18.5%|
|Registered with Any SS institution related to your|15.7%|0.0000|63.5%|47.8%|
|main job|||||
|Share of workers registered with any social security<br>|11.6%|0.0000|52.4%|40.8%|
|institution related to your main job|||||

_Notes_ : 2009 N = 21,324, 2013 N = 21, 467 _Source_ : LFS 2009 & 2013. World Bank author’s calculations.

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