rafmacalaba/data-use-mentions-extended huggingface dataset:
became more serious in the 1990s. Using provincial trade flow data to investigate the engagement of the PRC’s provinces in domestic and international trade, she finds that international trade barriers dropped but domestic trade barriers (between provinces) increased between 1987 to 1997. Interprovince trade flows fell between 1987 and 1997. Barriers to trade between the provinces in the PRC were as high as those between international borders within the European Union, or between Canada and the US.

However, evidence based on more refined data supports increasing regional specialization and product market integration over time. <mark>Bai et al. (2004)</mark> use a panel data set of 32 two-digit industries in 29 provinces between 1985 and 1997. They look at the patterns of regional specialization of industries, and examine how regional protectionism affected the patterns of regional specialization between 1985 and 1997. They find that in provinces with higher shares of SOEs, because benefits of local protection would be higher (i.e., jobs and direct control benefits), there was lower specialization amongst these industries. They also find that industries in provinces that have higher profit and tax margins have lower specialization. The higher profitability and tax revenue provided benefits and incentives to local governments to shield them from competition. However, contrary to Young (2000), they find that regional specialization rose over time, implying greater regional integration in the product market. Consistent with Bai et al. (2004), Holz (2009) presents evidence in support of an increasingly integrated domestic product market. Similarly, Huang, Rozelle and Chang (2004), using the rice market as an example, offer evidence that the PRC’s commodity markets are becoming more integrated.

# **E. Capital Market Integration**

The literature summarized below suggests that formal financial markets are still at their early development stage and inefficiency abounds, but informal channels of finances fill some of the gaps in inadequate formal financial intermediation. There is no strong evidence yet of increasing financial market integration
br>20 ETH 20 LSO 20 LSO<br>BFATCD LSOAGO BFA AGO BFAAGO<br>10 VNMGABEGYGINSENCOLMRTCIVGNBBGDGHA 10 VNMGABEGYGINSENCOLMCIVRTGNBBGDGHA 10 VNMGABEGYCOLMRTGINSENGHACIVGNBBGD<br>10 20 30 40 50 60 10 20 30 40 50 60 10 20 30 40 50 60<br>Urban poverty rate (%) Urban poverty rate (%) Urban poverty rate (%)<br>Official definition Official definition DOU<br>DOU DB DB<br>Urban poverty rate (%) Urban poverty rate (%) Urban poverty rate (%)<br><!-- End of picture text --> Source: International Urban Poverty Database. Note: WorldPop 250m is used for the DOU and DB methods. Urban areas include the categories “Urban center” and “Urban cluster” for the DOU method and the categories “Core” and “Suburb” for the DB method. Dashed lines are 45-degree lines. Poverty is measured using the $2.15 poverty line.

72
improves on existing data from UNCTAD-ERIA through more frequent updates, a wider variety of sources, and intensive forward and backward tracing that enables the creation of panel data. The data is hand collected through extensive regulatory checks, careful coding processes using the UNCTAD 3-digit MAST classification, and updated annually, making it one of the most up-to-date data on NTMs that exist, and ensuring only active regulations remain and inactive regulations are timely identified. As trade policy changes take place within the year, with over 13 government institutions issuing regulations and over 600 regulations in the data, this database allows for a timely assessment of policies, and changes to those policies, and more relevant in this paper, is sufficiently up to date for the analysis. While the data spans from January 2008 to December 2021, we use the 2019-2021 time span for the analysis to match with the trade data.

Figure 2 shows the monthly variation of incidences of NTMs in Indonesia both for products (a) and trade value (b) for all NTMs. While this gives some indication that there is some variation on a monthly basis and that the incidence has increased in 2021, it is too broad to draw meaningful interpretations. Most NTMs are designed to achieve public policy objectives, however, some NTMs can potentially affect trade. Even when this is not their main objective, such NTMs can hurt domestic producers by making imports more expensive, increasing business costs, and reducing productivity,

> 1Available at https://datacatalog.worldbank.org/search/dataset/0063543/indonesia_ nontariff_measures

5
The multilateral development banks also have a comparative advantage in data access— providing a public good function of collecting national data and presenting them with consistent definitions and standards across countries. Open data is a vital tool to democratize access to the information that forms the building block for economic research. The World Bank, and other multilateral development agencies, can work to facilitate knowledge generation in the south through open data, open tools and other such initiatives.

Finally, the World Bank Group and other multilateral development agencies can use their convening power to bring together researchers and policy makers from the developing world to exchange ideas and experiences. This convening power is one important tool in promoting ―south-south‖ learning among countries of the developing world.

# <u>Bibliography</u>

- Acemoglu, Daron, 2003, ―Labor- and Capital-Augmenting Technical Change,‖ _Journal of European Economic Association_ , Vol. 1, pp. 1-37.

- Adams-Kane, J. and J. J. Lim. 2011. ―Growth Poles and Multipolarity,‖ World Bank Policy Research Working Paper Number 5712.  June 2011.

- Aghion, Philippe and P. Howitt, 1992, ―A Model of Growth through Creative Destruction,‖ _Econometrica,_ 60(2): 323-351.

- Aghion, Philippe and Jean Tirole, 1994, "The Management of Innovation", _The Quarterly Journal of Economics_ , vol. 109, n. 4, pp. 1185-1209.

- Amin, Samir (1976), ―Unequal Development: An Essay on the Social Formations of Peripheral Capitalism‖, New York: Monthly Review Press.

- Antunes, António, Tiago Cavalcanti and Anne Villamil, 2007, ―The effect of financial repression and enforcement on entrepreneurship and economic development,‖ _Journal of Monetary Economics_ , Vol. 55, pp. 278-297.

- Azariadis, Costas and John Stachurski, 2005, ―Poverty Traps,‖ in Aghion, Phillipe and Steven Durlauf, eds., _The Handbook of Economic Growth_ , Elsevier.

- Bannerjee, Abhijit
reported measures provided by respondents. However, tax data may lack demographic information on individuals or households unless it is merged with other administrative or survey data. Also, it does not contain information on capital income or other key worker characteristics, such as education and occupation (only the NACE code of the company is recorded). The income of employees is reported by the employer, who has fewer incentives to misreport and is often more tightly monitored than the employees. This increases the data quality. In our data, labor income is measured at the individual level. Therefore, we cannot investigate tax evasion at the household level. Although the quality of tax data is usually high, it still may be plagued by missing variables, zero values challenging to interpret, and technical errors. Administrative tax data may also be challenging to extract from the administrative databases because they are often not integrated and not optimized to extract data (often, tax administration is interested only in checking the single taxpayer's income). Künn (2015) documents the increasing usage of linked administrative and survey data in economic research and discusses the challenges of data linking. Given the very large volume of information for approximately 7 million taxpayers, different identifiers were provided for the same individual, making the process of aggregating monthly tax data for each individual into an annual income measure difficult/quite challenging.

**In Romania, several income categories are exempt from personal income tax and, therefore, are not included in the definition of income used here.** Exemptions include social benefits other than pensions and temporary work incapacity benefits, such as allowances, indemnities, social insurance benefits, and scholarships. Invalidity pensions for the 1st degree of invalidity and benefits for war invalids are also exempt. Additionally, income from damages, insurance payouts, and punitive damages is tax-free, but there are other exempt categories.<sup>3</sup>

> 3 These encompass income from inheritance or donation, real estate transfers under specific conditions, and income from diplomatic
$1.7 billion.

Poor public health conditions take economic tolls in various ways, including reduced attraction for investors and tourists; continued expenditures on combating diseases which should have become history; and labor productivity foregone. The poor pay a high price in debility, reduced earning capacity, and death. The rich suffer little mortality from communicable diseases, but nevertheless suffer repeated episodes of morbidity which are reflected in high rates of stunting amongst their children.<sup>3</sup> It has long been accepted that the most effective approaches to improving population health are those that prevent rather than treat disease. Moreover, they account for a small fraction of the total health budget in most countries. It is the norm for public health services to be publicly funded, since the market has limited incentives to provide them. This applies even in the US, where medical services are largely privately financed. But in India public policies and programs have focused largely on the provision of curative care

> 2 Cited in Ann B. Jannetta (2001).

> 3 For example, estimates indicate that in 1998-99, 45 percent of children below the age of 3 in India were stunted — and even among the top wealth tertile over 28 percent of children were stunted (National Family Health Surveys I and II). See also Das Gupta et al. (2005).

1
important drivers of the gender gap in time use patterns (Apps and Rees, 2005; World Bank, 2011). Fewer studies, however, have studied gender differences in time use patterns across multiple countries, mainly because of the lack of comparable quality data—information that is crucial to guide both research and policy design.

This paper updates and reinforces the findings of various scholars and those reported by the 2012 World Development Report (WDR) by examining gender differences in time use patterns in 19 countries of different income levels and from various regions. We harmonize data from time use surveys and household surveys with time use modules collected between 2006 to 2014 to make them comparable. We focus on four aggregate categories: market or paid work, unpaid domestic work, personal care activities, and leisure, social and study activities. We answer four questions: what is the gender gap in time use patterns in countries across the various regions and income levels? How do time use patterns vary according to individual and family characteristics? How do time use patterns change over the lifecycle? How do they change in response to family formation? While some of these questions have been covered by previous literature, to our knowledge few studies analyze time use patterns at this level of detail and over the lifecycle for a broad sample of countries. We hypothesize that this might be explained by the lack of comparable data (Esquivel et al., 2007) and the intensive requirements of data harmonization.

Our findings indicate that in all the countries included in our sample women specialize in unpaid domestic work, while men specialize in market work. This reinforces the results obtained by previous research from developed and developing countries (Benería 2003; Benería et al. 2015). However, the degree of specialization varies widely across settings. Evidence has shown that the gender gap in unpaid work is observed in all regions but is largest in Middle Eastern countries, mainly because men undertake considerably less unpaid work than in other regions, but also because women perform more unpaid work
residency program for physicians, foreign medical boards could form partnerships with medical centers in developed countries involving an exchange of medical experts, for example, as in the partnership between the Methodist Health care System of San Antonio and Mexico (see Albro and Norton, 1997).

Doctors that have passed the USMLE written and clinical skills exam, and have a sufficient number of training credits could be included in the overseas provider network

> 31 Hibbard et al. (2003) evaluate the impact of private versus public reporting on hospital performance on quality improvement.  They found that hospitals that received low scores in cardiac surgery and obstetrics initiated a higher level of quality improvement activities.  Also, quality improvement efforts in hospitals whose reports were made public appeared to be significantly greater than in hospitals given only private reports.

> 32 For example, companies such as WGA, Frontera and SMI have successfully maintained provider networks across the US-Mexico border for almost 15 years.

33 The first stage of the USMLE involves a test of medical science concepts, the second stage involves a test of clinical knowledge and skills, while the third stage assesses whether the candidate can apply medical knowledge and understanding of biomedical and clinical science essential for the unsupervised practice of medicine, with emphasis on patient management in ambulatory settings.

24
compare the impact across different districts by accounting for their population density, the share of services sector employment, outstanding credit per capita, and the average age.

We use nighttime light intensity as our main proxy of economic activity for a number of reasons. First, a number of studies have reported the high correlation of man-made nighttime light intensity with other measures of economic activity (Donaldson and Storeygard 2016). Most notably, Henderson et al. (2012) argue that for countries with poor national income accounts, the optimal estimate of growth is a composite measure with roughly equal weights on conventionally measured growth and growth predicted from nighttime lights. Nighttime lights track economic activity in India closely (Prakash et al. 2019; Beyer et al. 2020), and provide a useful approximation of economic activity at high spatial granularity (Gibson et al. 2017; Chanda and Kabiraj 2020). In a recent study, Chodorow-Reich et al. (2020) use cross-sectional differences 2
for the role played by non-tariff barriers. One way around the problem of lack of data on NTBs is to exploit the sequencing of trade reforms experienced by Argentina. Berlinski (1994; 2003) has documented that non-tariff barriers were mostly used during the debt crisis of 1982-1989. Before that, non-tariff barriers were not generally used; after that, they were eliminated prior to the tariff cuts of the liberalization of the 1990s. This suggests a way to check the robustness of our results by further breaking down the historical series. In column (4) of Table 4, for instance, we exclude the 1982-1989

> 10The historical trade data that we put together in this paper does not come electronically. Instead, we had to collect hard copies of trade data for thousands of HS items for many years and to input them manually. Non-tariff barriers are usually implemented through legislative decrees specific to the different industries. Building a historical dataset of norms legislated by decrees is practically unfeasible.

14
interpretation of the relevant variables and thus affect the predictability of our model. We find for all the variables that we include, the questions are similar across surveys. On the other hand, there are questions related to expenditure on consumer durables in both surveys that we do not include. First, there are discrepancies in relation to the wording of the questions between the NSSO72 and earlier surveys.<sup>20</sup> Second, the recording of possession and expenditures was different between the surveys. We observed the discrepancies in the manuals provided to the surveyors.<sup>21</sup> Third, we confirm that the sampling frame is similar across all surveys. Like the earlier rounds, the NSSO72 is a multi-stage stratified survey of all states/union territories in India. To more accurately represent population density, for the 72nd round the primary sampling units (PSUs) are selected from the 2011 census list of villages in the rural sector while for the earlier rounds they are drawn from the 2001 census list of villages. Also, the number of PSUs are slightly higher, 14,088, in the 72nd round. For each of the earlier surveys, 12,784 PSUs are selected.<sup>22</sup> For the urban sector, in all surveys the PSUs are sampled from the Urban Frame Survey (UFS) blocks. For all surveys, the methodology to select the PSUs, the strata, sub-strata and the ultimate stage units (USUs) or households remains the same.<sup>23</sup>

> 20The NSSO61, NSSO66 and NSSO68 ask about “expenditure for purchase and construction (including repair and maintenance) of durable goods for domestic use” and the NSSO72 asks about “expenditure on durable goods acquired during the last _365 days_ other than those used exclusively for entrepreneurial activity”. Second, the NSSO61, NSSO66 and NSSO68 (type 1 survey) has questions for a 30 day and a 365 day recall period while the question on the NSSO72 only
>rev 2 classification – 2-digit and specific description.|
|Main Economic Activity (4-digit)|NACE Rev. 2, core code (4 digits and<br>description)|Sector classification of main economic activity using NACE<br>rev 2 classification – 4-digit and specific description.|
|Country|Country|Countryfull name|
|CountryISO code|CountryISO code|ISO 2-digits code for the country|
|Employment|Number of employees|Total number of workers in the company (temporal and<br>permanent)|
|OperatingRevenues(Turnover)|Operatingrevenue(Turnover)|Operatingrevenues|
|Netprofits/losses|Profit/(loss)after tax|After taxprofit/losses|

Source: Authors’ elaboration

# 3.2 ORBIS data limitations and additional data sources

As (Kalemli-Ozcan, Sorensen, Villegas-Sanchez, Volosovych, & Yesiltas, 2015) pointed out, financial information in ORBIS for most European countries is superior to that of other countries because firms are required by law to file their financial information in Europe. In contrast, detailed financial data on SOEs are limited in the Middle East, North Africa, and Central Asia region due to weak oversight of SOEs and/or to a lack of direct access to financial statements (IMF, 2021). When information is not available in ORBIS, the Global BOS database is complemented with data from alternative sources, including official data from the Ministry of Finance, Treasury, business registries, tax authorities, local stock exchange (e.g., listed SOEs), open data sources, with a priority given to official government information in cases where a discrepancy is found (see Table A.2 in the Annex).

Key alternative data sources for the preparation of the Global BOS database include EMIS intelligence, which covers more than 5.5 million listed and unlisted firms across more than 125 emerging markets. Through EMIS intelligence, it is possible to identify a company’s main sector of operation, as well as its financial statements at the unconsolidated
With our battery of market-level measures added to the panel using country and month-year identifiers, we focus on measuring the concentration of PM2 _._ 5 around combustion power plants. Specifically, we use information on monthly mean surface PM2 _._ 5 concentrations measured in micrograms per cubic meter (μg/m<sup>3</sup> ) from the V5.GL.03 dataset detailed in Van Donkelaar et al. (2021).<sup>5</sup> This geophysicalhybrid dataset provides estimates of PM2 _._ 5 concentrations by combining data from satellites, chemical transport models, and ground-based monitors. It provides information at 0.01<sup>_◦_</sup> x0.01<sup>_◦_</sup> resolution at a monthly frequency between 1998 and 2021. Because previous literature has shown that there are considerable health effects within 50 km of a power plant (Qiu et al., 2023; Fraenkel et al., 2024; Clay et al., 2016), we compute the average PM2 _._ 5 concentrations for every plant and month at this distance and at 10 km. Figure 2 shows the distribution of the combustion plants in our sample and provides a visual example of how the PM2 _._ 5 concentrations are calculated. To run placebo exercises, we also compute these measures of PM2 _._ 5 concentrations within 50 km of non-combustion power plants (i.e., solar, wind, nuclear, geothermal).

Next, we include in the dataset variables that can help us account for factors that confound the relationship between PM2 _._ 5 concentrations and our market-level measures of drought. Wildfires, which are more prevalent during droughts and lead to higher PM2 _._ 5 concentrations (McClure and Jaffe, 2018), are a particular source of concern. To limit the influence of surface PM2 _._ 5 related to wildfires, we follow Qiu et al. (2023) and omit
**DISORGANZATION OR SELF-ORGANIZATION?**

# **Abstract**

The transition from plan to maret provides a rare oppomtunity for insight into the endogenous development of economic institutions. Economic activities during the Soviet regime were coordinated by a central authority. These coordinating mechanisms were disrupted during the transition period, leading to an increase in the transaction costs for finms. Blanchard and Kremer (1997), among others, emphasize the negative impact of this 'disorganization" on output behavior at the beginning of transition. Though this argument is conrect, we believe that this and similar works stop short of a fuller characterization of transition by concentrating only on the disruptive effects of the reform process.

This paper begins where the former works end by examining one of the key institutions that have emerged spontaneously in response to the challenges of transition: business associations. Its main contribution is to provide empirical evidence that institutions that help coordinate production and trade spontaneously emerge in an environment characterized bywidespread "disorganization". Using a largely unexplored, finn-level data set, we document the emergence of business associations at the beginning of transition and provide evidence that these new coordinating institutions mitigated the initial oUtpUt decline. Building on the growing literature on transaction costs and complexity, we interpre **t** he emergence of these infomial institutions as the firns' rational response to coordinate activities in a decentralized economy.

Keywords: Coordination Problems, Transition, Altemative Institutions JEL classificatio **n** os.: D23, LIO, 017, P21, D71 _2_