rafmacalaba/data-use-mentions-extended huggingface dataset:
this study is the first to provide information on poverty dynamics in Malaysia based on official micro-level survey data.

One particular feature of Malaysia’s development model concerns the preferential treatment of the Bumiputera ethnic groups, the population segment that was economically disadvantaged both before and after independence. For example, average consumption was and remains lower for Bumiputeras than for Chinese or Indian Malaysians, the other main ethnic groups.<sup>1</sup> Malaysia’s New Economic Policy (NEP), introduced in 1971, had the twin objectives of reducing overall poverty and improving the economic position of the Bumiputeras. The NEP aimed to raise the participation of Bumiputeras in the formal education system, tertiary education and professional occupations, as well as expand their ownership of and control over capital (Lee, 2017). We will elaborate on this context in the next section.

> 1 See Anand (1983) or Ikemoto (1985) for a detailed historical treatment, or Jomo and Hui (2014) for a more recent overview. The demonym _Malaysian_ refers to all citizens of Malaysia, regardless of their ethnicity. The term _Malay_ refers to the Malay ethnic group, the largest in the country. _Bumiputera_ is an ethnic label that groups Malays with other indigenous groups (such as _Orang Asli_ in Peninsular Malaysia and _Orang Asal_ in the states Sabah and Sarawak). The Bumiputeras form the majority of Malaysia’s population.

1
In fact, 7 years after passage of the Act, not a single one of these certificates has been awarded, despite considerable grassroots demand and the fact that in some areas work on systematic surveys with lowercost technologies had been initiated (Rugadya _et al._ 2004). Lack of a sustainable business model and institutional structure imply that even in traditional _mailo_ areas, land administration is challenged to live up to requirements. Finally, the government failed to widely disseminate the Act, despite the fact that no behavioral changes can be expected unless households are aware of its provisions. Only recently, in preparation for pilots to systematically demarcate land in few parishes, were systematic efforts, including preparation of leaflets in local languages and training sessions, undertaken. The fact that these activities were limited to the parishes singled out for subsequent intervention provides us with an interesting exogenous source of variation in the level of knowledge which can be utilized in econometric estimation.

# **3.3 Data and descriptive evidence**

The data for our analysis are from a survey conducted in the second half of 2004 by the World Bank in collaboration with the Ministry of Water Land and Environment (MWLE), Makerere University, and FASID to provide a baseline that could help to study the impact of systematic demarcation at a later stage. In each of six districts, chosen to capture the diversity of Uganda’s different regions, one parish that had been selected for systematic demarcation and a neighboring parish with similar characteristics were chosen.<sup>6</sup> This yielded a total sample of 970 households or 2185 parcels in 12 parishes. Within each parish, households were selected randomly. In addition to standard household characteristics, the survey contains results from administering a quiz on provisions of the new land Act to both the main male and female person in the household (usually head and spouse) to assess the extent of their legal knowledge. This is complemented by a large array of information on land ownership and transfer rights, soil quality, and
Upon observing marginal effects and/or elasticities (columns 6 and 7 in Table 2), we notice that _News_ per se has the biggest impact of all on environmental performance. It is followed by for the interaction term between ‘news’ and ‘awareness of news publication’. The next important sets of variables are local municipality and national government impacts. This ranking, with news impact as well as the interaction effect, seems to be consistent across all model specifications.

# **5. Conclusion**

This paper has attempted to quantify the impact of environmental news publication in media as well as awareness of news publication on (change in) overall environmental performance of firms in the Republic of Korea between 1990 and 2000.

Using data from a survey of 49 firms traded in the market in the Republic of Korea and a probit estimation methodology, the study was able to make two contributions. First, it clearly showed that environmental news publication in media is the most important predictor of environmental performance, at least in the present context. Second, the use of an interaction term (environmental news publication in media and firms’ awareness of news publication) has added another dimension in the literature. Indeed, not only does environmental news publication in the media matter for environmental performance, but also firm’ awareness of the environmental news publication is an important add-on which reinforces the news effect (see Shanielle and Mamingi, 2004 for a similar argument in another context).

15
3 But again it is Korea and Taiwan (China) that are making the fastest progress on the issue. Most systems in the region have opted for some form of universal coverage, or aspire to achieve it. Korea introduced universal health insurance (UHI) in 1989, six years ahead of Taiwan (China) despite being poorer than Taiwan (China), and despite being poorer than Japan was when it introduced UHI (1961). China, The Philippines, Thailand and Vietnam are all currently taking major steps towards universal coverage, and on present trends look set to achieve it well before they reach even the per capita income Korea had when it did so.

In short, despite the wide income differences within the Japan-Tiger grouping and between that grouping and the developing economies of East Asia, the opportunities for lessonlearning in the health sector would seem to be considerable. This paper provides an analytical overview of the health systems of Japan and the Asian Tigers, and suggests some lessons for the developing countries of the region. The focus is not on describing the five systems, but rather on linking their policies and institutional arrangements to outcomes of interest, such as health spending, unit costs, and use of services. The paper tries to pull out lessons both from looking across the systems, and from looking at the impacts of reforms within the various systems. Over the last few years, the availability of quality comparable data across the systems has improved. The efforts by OECD<sup>1</sup> and WHO<sup>2</sup> on health spending and sources of financing have helped improved comparability of data for Japan, Korea and Singapore, and Hong Kong (China)<sup>*</sup> and Taiwan (China)<sup>3</sup> have complemented this work with their own health accounts. And four of the five systems—Singapore is the exception—have also been represented in a multi-system Asian comparative study on equity in health care finance and
>and to deliver the third doses of the</sup> polio and DPT vaccines. Since the third doses add less<sup>than the average to</sup> LDS, reducing their proportions increases the average of the program. However, since measles vaccination has at least thirty times more impact<sup>on</sup> LDS per vaccination than any of the others, reducing its proportion even slightly has a large negative effect<sup>on the average LDS per vaccine.</sup>

Table 2 presents in columns (8)<sup>and (9) the raw material for developing a</sup> comparable estimate of b based on Javanese data and assumptions as developed and analyzed by a University of Michigan study (Grosse et al, 1979).(14] In e rural population of 50,000, the<sup>Michigan study estimated that</sup> an immunization program consisting of 27,000 administered doses per year would reduce mortality and morbidity to a degree which<sup>is calculated here to</sup> save 1,790 life years through averted deaths and 22,500 days of partial or total disability. Thus on average the Javanese vaccination program is estimated to save 25.0 healthy-life-days per vaccination, a figure which is of the same order of magnitude as the<sup>eatimates for Ghana from Table 1.</sup> However the Javanese immunization program considered by the Michigan study differs in three ways from the immunization program<sup>presented in Table</sup> 1. The Javanese program includes a vaccination of 2100 mothers per year for neonatal tetanus but excludes vaccinations against measles and polio. By referring to the Michigan report,<sup>it is possible to estimate the value of b that</sup> would obtain in Java if the vaccination program resembled that in Table<sup>1.</sup>
(2.3) must also be indexed by country _i_ , or It is well known that xed-eect least squares estimators of dynamic panel models (also called least squares dummy variables estimator, or LSDV) lead to inconsistent estimates when the time dimension _Ti_ is short and xed, even if the cross-section dimension _N_ increases to innity (Nickell, 1981). As _Ti_ grows large, however, the bias decreases and disappears as _Ti_ goes to innity. In practical terms, however, _Ti_ of the order of 20-30 is usually enough to make the bias small. The basic data set used in this paper includes 76 low income countries with data going back to 1971. The panel, however, is unbalanced. Thus, whether the sample is long enough is an empirical question. To cope with this issue, I implement a version of the bootstrap bias correction algorithm originally proposed by Pesaran and Zhao (1999) and recently extended by Tanizaki, Hamori, and Matsubayashi (2006), Everaert and Pozzi (2007), and Fomby, Ikeda, and Loayza (Forthcoming). The interested reader is referred to these papers for more details on the bias correction procedure.<sup>9</sup>

# 3.1 Data

The data consist of an unbalanced panel of 76 low income countries over the period 19712007 for which there is enough information to construct uninterrupted time series for the endogenous variables _Yit_ . Table 1 provides a list of the countries and the years for which there are data for the entire vector of endogenous variables. Data are obtained from the World Bank's World Development Indicators and the IMF's World Economic Outlook databases.

> 9Fomby, Ikeda, and Loayza (Forthcoming) implement and extend a version of the bias correction method proposed by Pesaran and Zhao (1999) to Panel VARs. In this paper, instead, I use an iterative procedure similar to those proposed by Tanizaki, Hamori, and Matsubayashi (2006) and Everaert and Pozzi (2007). The
of 5%|
|_fc_|3.165|US average frm size conditional on _L ≥_10 = 118|

The top 10 percent employment share, the average employment ratio between 21–25 and 1-year-old firms, the average employment ratio between entrants and incumbents, and the average firm size conditional on _L ≥_ 10 were computed from the Business Dynamics Statistics database for the year 2007. Numbers are for the manufacturing sector. Standard deviation of employment growth rates for large firms are reported in Atkeson and Burstein [2010].

While the calibration strategy is standard, it is important to highlight the calibration of the fixed cost of production, which is set to target the average firm size in the US manufacturing sector among firms with ten or more workers. As explained in the data section, our cross-country firm-level database restricts us to studying forms above the ten-worker threshold, so we adjust 33
It should be noted that the identification of productivity differentials associated with characteristics comes from covariation across firms.<sup>9</sup> If we find evidence suggesting that, for example, women are less productive than men, the firm-level data does not enable us to determine whether the estimated lower productivity of women comes from the segregation of women into low-productivity firms, or from the lower productivity of women relative to men within firms. This should be considered when interpreting the results.

# **V. RESULTS**

The production function (1) and the wage equation (2) were estimated jointly, with the quality of labor aggregate as defined by (5) and (6) respectively, for all firms in ENESTYC 2001. Table 3 below shows the estimates for the marginal productivity differentials and relative wages, φ and λ , respectively for the characteristics which affect employee performance and/or wage negotiations: (i) gender, (ii) schooling, (iii) experience, and (iv) training.<sup>10</sup> The full results of the estimation are shown in Table A.1. The last column presents an asterisk if we reject the null hypothesis of equality between the productivity and wage differentials.

> 9 This means that all workers within a firm are associated to the same productivity level. Therefore, the estimated productivity differential is related to productivity differences between firms, not within. 10 As explained in the previous section, we include many other worker and firm characteristics for a complete identification of the model. However, the object of this paper is only gender, schooling, experience, and training. The analysis of the effect of other characteristics is the scope of another study.

12
In Table 2, we present African SWFs capitalization over the period 2007-2013, using the information given by the SWI in terms of the international capitalization of SWFs around the world. Given that the share of African SWFs is equal to 0.24 percent, this allows us to estimate the capitalization of African SWFs over the period 2007-2013. The mean capitalization of African SWFs over the period 2007-2013 is $11.21 billion, while the minimum is $8 billion, and the maximum reaches $15 billion.

Table 2: **African SWFs capitalization over the period 2007-2013 in $ billion**

|**Year**|**World capitalization**|**African SWFs capitalization**|
|---|---|---|
|2007|3,259|8|
|2008|4,149|10|
|2009|4,032|10|
|2010|4,418|11|
|2011|4,842|12|
|2012|5,198|12.5|
|2013|6,106|15|

Sources: SWF world capitalization data are taken from the Sovereign Wealth Fund Institute, and the African SWFs capitalization data are based on the authors’ calculations.

4
# **1. Introduction**

A large literature going back to Hernando de Soto (1989) has argued that complex entry regulation prevents informal firms from registering with the government and may also discourage new firm creation.<sup>2</sup> However, studies that have measured the impact of reforms to simplify entry regulation have found only small effects on firm formalization and creation.<sup>3</sup> These studies typically examine the implementation of one-stop shops that integrate various subnational and national registration procedures. For example, with a one-stop shop set up in Mexico, firms that previously had to register with different municipal and federal authorities can complete several steps of the process at a single agency, reducing the number of days required to register a business from 30 to 1 and the required procedures from 8 to 3 (Bruhn, 2011).

Creating a one-stop shop is one of the most popular business registration reforms, but another type of entry reform is to make registration an administrative (not judicial) process (World Bank, 2006). Business registries managed as an adjudicative rather than an administrative function are prone to discretionary powers and increased uncertainty. Even simple procedures such as reserving a name are complex due to being subject to discretionary approval of a judge. The inconsistent interpretation of processes by judges makes automation particularly complex, since it requires standardization of procedures. In the World Bank’s Doing Business report, countries in which courts operate business registries rank significantly lower than countries with administrative business registries (table 1).

|**Table 1: DB Ranking of Countries with Administrative vs. Court Business Registries**|
|---|

|**Administrative Registries**|**Ranking DB 2018**|**Court Registries**|**Ranking DB 2018**|
|---|---|---|---|
|New Zealand|1|France|25|
|Canada|2|Slovenia|
Policy Research Working Paper 10557

# **Abstract**

This paper studies the effect of Russia’s invasion of Ukraine on the performance of firms in Central Asia. It uses unique data from the Business Pulse Survey run by the World Bank in the Kyrgyz Republic, Tajikistan, and Uzbekistan, which tracks the sales and employment—along with other main characteristics—of about 1,200 to 1,800 firms in a panel structure. The survey contains two waves before and one wave after Russia’s invasion of Ukraine. Using the difference-in-differences methodology in a regression setup, the analysis finds that Central Asian firms with pre-invasion trade links to Russia suffered greater drops in sales and employment after the invasion—even though exporters to Russia may have experienced, on average, higher sales during the studied period. Considering the pre-invasion digitization of firms, the findings show that digitization helped firms increase their average employment during the studied period. However, the analysis does not find any significant mitigating effect of digitalization associated with the impact of the invasion.

This paper is a product of the Finance, Competitiveness and Innovation Global Practice. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contacted at miootty@worldbank.org; mmelecky@worldbank.org; ndalvit@worldbank.org; nsrinivasan5@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
% 36% 7% 4%<br>Currency restrictions 9% 13% 29% 33% 12% 5%<br>Delay in permits and approvals 6% 9% 38% 34% 9% 4%<br>0% 20% 40% 60% 80% 100%<br>Withdraw existing investment Cancel planned investment Delay planned investment<br>Consider delay/cancellation None Don't know<br><!-- End of picture text --> _Source_ : Computation based on the 2019 GIC Survey.

# _Heterogeneity across investor types_

Affiliates with more years of experience in a given host country are likely to be less sensitive to political risk in general. For each respondent, we recorded the most negative reaction across all hypothetical 6 For example, political risk ranks second among nine categories of possible impediments to FDI according to the MIGA-EIU Political Risk Survey 2013; political risk and uncertainty is ranked fifteenth among 69 organizational risks according to the Aon Global Risk Management Survey 2019; and political risks and regulatory uncertainty is ranked fourth among 12 risks according to the Association for Financial Professionals and Oliver Wyman Risk Survey 2019.

16
# 3.3 FDI Regulations and Trade Agreements

In addition to transportation and infrastructure data, we also obtain information on FDI regulations and trade and investment agreements. To measure FDI regulations across countries, we use the Investing Across Borders data set, which compares FDI laws and regulations across 87 economies. It presents quantitative indicators on economies' laws, regulations, and practices affecting how foreign companies invest across sectors, start businesses, access industrial land, and arbitrate commercial disputes: Specifically, it includes the following indices:

- Investing Across Borders: its offers <mark>measures of statutory restrictions on foreign ownership of equity in new investment projects (greenfield FDI) and on the acquisition of shares in existing companies (mergers and acquisitions).</mark>

- Starting a Foreign Business: it <mark>quantifies the procedural burden that foreign companies face when entering a new market. It comprises 3 components measuring the time needed, procedural steps required, and regulatory regime for establishing a foreign-owned subsidiary.</mark>

- Accessing Industrial Land: it quantifies several aspects of land administration regimes important to foreign companies seeking to acquire land for their industrial investment projects, including the strength of land rights, the scope of available land information, and the process of leasing land in a country’s largest business city.

- Arbitrating Commercial Disputes: <mark>it reflects different aspects of domestic and international arbitration regimes in each country applicable to local and foreign companies, including the strength of the legal framework for alternative dispute resolution, rules for the arbitration process, and the extent to which the judiciary supports and facilitates arbitration.</mark>

Figure 12 compares BRI countries with non-BRI countries as well as high-income OECD countries in the above FDI policy indicators.<sup>15</sup> For each indicator, a higher score implies better performance and more attractiveness to foreign investors.

Figure 13 shows a comparison of FDI openness at the sector level.<sup>16</sup> A few patterns emerge from the
# **Table A5: Variables for panel logit and probit models (annual data)**

|**Variables**|**Definition**|**Source**|
|---|---|---|
|**Crisis dummy**|Sovereign debt, banking, or currency crisis|Laeven and Valencia<br>(2020)|
|**GDP growth**|Annual percentage growth rate of GDP at market prices<br>based on constant local currency|WDI|
|**Short-term**<br>**debt**|Share of short-term debt (with a maturity of 1 year or less)<br>in external debt|WDI|
|**Debt service**|Ratio of debt service on external debt to exports|WDI|
|**Reserve cover**|International reserves in months of imports|IDS|
|**Change in**<br>**government**<br>**debt**|Percentage point change in public debt to GDP ratio|WEO|
|**Change in**<br>**private debt**|Percentage point change in private debt to GDP ratio|GDD|
|**Concessional**<br>**debt**|Share of concessional debt in external debt|IDS|
|**Funding ratio**|Ratio of credit provided to private sector to total deposits|GFDD|
|**Currency**<br>**overvaluation**|Percentage deviation of real effective exchange rate from<br>HP-filtered trend|Bruegel|
|**Currency**<br>**mismatch**|Ratio of foreign liabilities to foreign assets|Lane and<br>Milesi-Ferretti (2021)|
|**FDI**|Net inflows of foreign direct investment as a share of GNI|WDI|

47
the owners have up to secondary level of education while high-educated self-employed are owners with vocational training or tertiary education.<sup>29</sup> Finally, the third group is employers, namely firms that employ at least one paid worker other than him or herself.<sup>30</sup> The owner of each firm type is assigned the corresponding employment type, namely low-educated self-employed, high-educated selfemployed, and employer.

> 26 The literature finds that very few self-employed establishments grow into microenterprises (Loening and Imru, 2009; Kinda and Loening, 2010; Grimm et al., 2012; Fajnzylber et al., 2006; Schoar, 2009; La Porta and Schleifer, 2014). Hence this category is mostly comprised of formal firms.

> 27 We find that 41 percent of employers in our sample have at least completed secondary school and 40 percent are in professional occupations, double the rate of HE-SE who are in professional occupations.

> 28 The IES of Zambia and Zimbabwe contain information on the number of workers who are family members. The correlation between the number of unpaid workers and the number of family members who work at the firms is 0.66 and 0.58 respectively.

> 29 We do not use incomplete secondary level as the threshold to define low educational level, as with the workers classification, due to data limitation.

> 30 Employers in the IES are more educated than those in the GMD. About 85 percent of IES employers have up to a secondary education, as compared to 41 percent of GMD employers.

9