rafmacalaba/datause-encoder-data huggingface dataset:
# **_I. Introduction_**

The Singapore economy is going through a period of major restructuring. Economic stagnation since the 1997 Asia financial crisis (except for a brief recovery in 1999) has called into question the continued relevance of many fundamental policies that had worked well in the past. In 2002, a high-level Economic Review Committee (ERC) was convened by the government to chart new directions for the economy. A common thread that ran through the committee’s various reports was a call to enhance the economy’s innovative capacity, with the aim of making Singapore an innovation hub in the region.<sup>2</sup> The call reflects an increased awareness both within and outside the government of the need to redefine Singapore’s comparative advantage through a new national innovation policy.

Traditionally, Singapore has billed itself as an “efficient” business city. The ability to provide quality infrastructure services more efficiently than the neighboring countries has long given the city-state a comparative advantage in the manufacturing sector.<sup>3</sup> Such efficiency, together with a relatively corrupt-free civil service<sup>4</sup> and a highly educated and English-speaking workforce, made Singapore a choice production base for multinational corporations (MNCs), which played a pivotal role in the success of the country’s industrialization program in the past. The “efficiency premium” also allows the country to leverage its strategic geographical location to serve as the commercial hub of the region.

Singapore is however facing mounting challenges in maintaining its “efficiency premium”. Other Asian countries are fast catching up on the provision of quality infrastructure. Even Singapore’s status as the premium air and seaport in the region – an area where the city’s leading position was previously thought to be unassailable – has come under tremendous competitive pressure.<sup>5</sup> At the same time, business operating costs, including land costs, do not

> 2  See ERC Main Report, 2003.

> 3  An oft-quoted example of such efficiency is that a foreign visitor arriving at the Changi International Airport generally takes less than 30 minutes to a downtown hotel (including customs clearing).

> 4   In the latest World Competitiveness Report (2002/2003), for example, Singapore ranks top (i.e. least negative) in areas like “favoritism in decision making of government officials”, “transparency of government policy-making”, “burden of regulation” etc.

> 5  The challenge to the seaport hub status is reflected in the relocation of operational headquarter by two major shipping companies, Evergreen and Mersk, to Tanjong Pelapas port in the neighboring Malaysian state of Johor in 2002.  The move sparked major changes in the Port of Singapore Authority (PSA).  See section V for more details.

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detailed information is available and provided in table A2 in the appendix.<sup>4</sup> Firms are distributed into 19 types of activities. Selling food or groceries (street-food sellers, restaurants) is the largest activity for these 8 economies with 22% of the informal firms involved in this activity. Second largest is manufacturing of clothes or shoes undertaken by about 13% of informal firms in the 8 countries. Of course, the distribution of activities may differ for the full sample used for this analysis. Majority of the firms live in fixed premises – about 76 percent as shown in the summary statistics in table 1. A nationally representative sample of informal firms would require a complete list of unregistered firms in an economy. By definition such a list is difficult to attain given they are not documented. To our knowledge, such a list does not exist for any country at the national or even city level. Thus, although the data are not nationally representative, some steps are taken in the data collection process to limit selection bias.

Data collection for the informal surveys is carried out as follows. For the Informal Enterprise Surveys, an urban center is typically divided into zones to yield a predetermined number of interviews. For instance, in the Kenya Informal Enterprise survey, five urban centers were broken down into 122 zones. A number of zones are then randomly selected to be interviewed. Typically more than one enumerator is allocated to each zone. Each enumerator is presented with maps identifying a predefined starting point that tends to be at opposite ends of the zone to ensure interviews are dispersed within a zone. The enumerators are instructed to follow the direction of the street and obtain a predetermined number of interviews. This process limits selection bias given the zones are randomized across the city, but the process cannot ensure a representative sample of informal firms. The enumerators identify informal firms and confirm their status using a short screener questionnaire. Once the informal status is confirmed, the interview begins with the main questionnaire. Most studies tend to follow a similar approach by relying on a random sample of informal firms taken from one or two main urban centers of the economy that are not nationally representative (Grimm et al., 2012; Harris, 2014; Middleton,2007; Rand and Torm, 2012). A considerable advantage of

> 4 The 8 economies are Angola, Argentina, Democratic Republic of Congo, Guatemala, Kenya, Myanmar, Peru, and Rwanda.

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# 6.5. Costs of interventions

_Table 6 Costs of different interventions, per road type (thousands of US dollars per kilometers). Source: Colombia and MTC, Peru_

||||Flood<br>Proof<br> <br>Routine<br>Mainte-|Rehabili-<br>|Construc-<br>|Upgrade<br>to<br>|||
|---|---|---|---|---|---|---|---|---|
|CLASS|Surface|Terrain|1m<br>nance|tation|tion|primary|Bridge|Tunnel|
|Primary|Paved|Flat|2,500 13|1,300|2,500|-|28,000|33,000|
|Primary|Paved|Hilly|2,804 16|1,328|3,117|-|-|-|
|Primary|Paved|Mountain|2,944 10|1,212|3,867|-|-|-|
|Primary|Paved|Steep|3,573 19|1,531|4,712|-|-|-|
|Secondary|Paved|Flat|2,137 15|850|1,563|1,650|-|-|
|Secondary|Paved|Hilly|2,357 16|775|2,000|1,970|-|-|
|Secondary|Paved|Mountain|2,647 13|844|2,617|2,236|-|-|
|Secondary|Paved|Steep|3,126 15|978|3,260|2,658|-|-|
|Secondary|Unpaved|Flat|1,646 6|243|840|3,163|-|-|
|Secondary|Unpaved|Hilly|1,974 7|301|1,057|3,598|-|-|
|Secondary|Unpaved|Mountain|2,265 9|372|1,433|4,072|-|-|
|Secondary|Unpaved|Steep|2,706 -|457|1,924|4,855|-|-|
|Tertiary|Unpaved|Flat|1,566 3|144|312|3,955|-|-|
|Tertiary|Unpaved|Hilly|1,874 4|177|621|4,398|-|-|
|Tertiary|Unpaved|Mountain|2,162 5|244|909|5,106|-|-|
|Tertiary|Unpaved|Steep|2,600 7|326|1,329|6,088|-|-|

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<!-- Start of picture text --> Equatorial Guinea: Overall Balance - Cash Basis - 2002 - 2006<br>(in billion of CFA francs)<br>1400<br>1200<br>1000<br>800<br>600 Overall Balance (cash basis)<br>400<br>200<br>0<br>2002 2003 2004 2005 2006<br>-200<br>Years<br>Billion CFA francs<br><!-- End of picture text --> Sources: Equatorial Guinean authorities Bank staff and IMF.

Another well-known issue of resource-rich economies is volatility, known as _boom and bust cycles,_ which can equally have negative impact on economic growth. This phenomenon plagues oil exporter<sup>29</sup> countries, given the importance of oil in the overall economy and in government revenues. The economic impact includes unpredictable revenue streams because widely fluctuating export revenues lead to fluctuating levels in overall government revenues (Mikesell 1997). These frequent upward or downward adjustments of fiscal expenditures are costly because they simultaneously discourage private investment and destabilize the government’s budget, therefore impeding its ability to sustain investment and social provision and service deliveries (Katz et al. 2004). In addition, once expenditures become entrenched, it is harder for governments to make budget cuts; rather than reversing their spending patterns during busts, they often opt to borrow, and hence, risk incurring huge debt burdens.

A country with large revenues derived from exploiting a nonrenewable resource such as oil, typically faces two main problems: (i) the revenue stream is uncertain and volatile because it depends on the world oil prices, and (ii) that revenue will eventually dry up. Nonrenewable Resource Funds (NRFs) are proposed to deal with both problems. First, a fund may be seen as able to stabilize budgetary revenues. When oil price is high, the fund would receive excess resources, which would then allocate to the budget when the price is low and therefore revenues. Second, a fund may be seen as a way to save some of the revenue generated by exploiting the finite stock of the resource, which can then provide income after it has been depleted. Funds may also be set up for other reasons such as to counteract the spending effect leading to the real exchange rate volatility and Dutch Disease, for liquidity and political economy purposes, and to enhance governance and transparency (Jeffrey Davis et al. 2001).

Norway, for example, has charted a long-run-oriented, tax-based and reasonably market friendly approach to the management of its oil resources. The oil revenue is deposited in the Norwegian Petroleum Fund, which is being built up and invested mostly in foreign securities for the benefit of the current generation of Norwegians when the reach old age as well as for the future generations, and also in order to shield the 29 Although market volatility is a problem for all exporters of primary commodities, the phenomena is acute for oil exporting countries given the importance of oil in the overall economy.

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**Table A.15. Differences by household migration status in association between social norms indices**

**and women’s paid work outcomes**

||**HH Roles**|**Public Space**|**Both themes**|
|---|---|---|---|
||**(1)**|**(2)**|**(3)**|
||**Paid work**|**Paid work**|**Paid work**|
|PNB Index_HH Roles # migrant<br>HH**(**β)|-0.08<br>(0.08)||-0.07<br>(0.08)|
|PNB Index_HH Roles**(**α)|-0.07* (0.04)||-0.06<br>(0.04)|
|SNE Index_HH Roles # migrant<br>HH**(**β)|-0.04<br>(0.09)||-0.00<br>(0.09)|
|SNE Index_HH Roles**(**α)|-0.03<br>(0.06)||-0.04<br>(0.06)|
|PNB Index_Public Space #<br>migrant HH**(**β)||0.03<br>(0.05)|0.03<br>(0.05)|
|PNB Index_ Public Space**(**α)||-0.03<br>(0.03)|-0.02<br>(0.03)|
|SNE Index_ Public Space #<br>migrant HH**(**β)||-0.13** (0.06)|-0.09<br>(0.06)|
|SNE Index_ Public Space**(**α)||0.02<br>(0.04)|0.01<br>(0.04)|
|Migrant HH|0.01<br>(0.06)|0.03<br>(0.05)|0.05<br>(0.06)|
|Obs.|2,000|2,000|2,000|
|Adjusted R2|0.03|0.02|0.03|
|Controls|YES|YES|YES|
|Regional FE|YES|YES|YES|

_Notes:_ Controls include a binary variable for belonging to a household with a current migrant male spouse, respondents’ age, years of education, having children younger than 5 years, log of household’s total income, at least one among mother-in-law or father-in-law living in the household, living in an urban area, belonging to the Madheshi ethnic group, and provinces.

Table A.16. Analysis of vignettes

|Comparison scenarios||p-values associated with|t-test|
|---|---|---|---|
||Full sample|Females onlysample|Males onlysample|
|1. Change SNE only: low-low vs high-<br>low (conservative SEE & SNE vs. liberal<br>SEE & conservative SNE)|0.62|0.48|1.00|
|2. Change both SEE and SNE:<br>low-low vs high-high (conservative SEE<br>& SNE vs. liberal SEE & SNE)|0.00|0.00|0.00|
|3. Change SNE only:<br>low-low vs low-high (conservative SEE<br>& SNE vs. conservative SEE & liberal<br>SNE)|0.05|0.08|0.32|

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the public market is doing well during the sample period. This issue is of particular concern in the literature because many papers have used data on private equity returns from the 1990s, when the public market was doing quite well. This issue is of less concern in the present paper because our sample period is 1961 to 2019.

## **3.3 Other Data**

We relate the PME to a variety of country-level covariates. Real GDP per capita, inflation, and local currency depreciation are taken from the World Development Indicators (World Bank 2019a). Legal origins (i.e., English, French, or Socialist) are measured using the classification of La Porta et al. (1999). A measure of political risk comes from the PRS Group, a measure of corruption perception from Transparency International, and a measure of economic freedom from the Heritage Foundation. Financial openness is measured by the index of Chinn and Ito (2006, 2008), which is the first principal component of dummy variables codifying capital controls reported in the IMF’s _Annual Report on Exchange Arrangements and Exchange Restrictions_ . Financial development is measured by the ratio of private sector credit by deposit money banks to GDP, as reported in the Global Financial Development Database (World Bank 2019b).

# **4 Results**

## **4.1 Performance of a Diversified Emerging Market Private Equity Portfolio**

As a first look, Table 2 reports the performance of the IFC portfolio, pooling cash flows from direct investments and fund investments. The evolution of portfolio returns over time is documented in the table’s columns, which report performance calculated on subsets of investments grouped by earliest vintage year beginning with all investments since the first in 1961, then all investments since 1970, since 1980, and so forth.

Table 2, Panel A reports the performance of the complete portfolio. The bottom row of this panel reports the number of investments in each vintage year group. Relative to the S&P 500, the complete portfolio has achieved a PME = 1.15 since 1961. Over the long run, the portfolio has delivered 15 percent more than a counterfactual investment in the U.S. public equity market. Looking at indices available only in later decades, the PME, relative to the MSCI EM and World indices, is systematically higher, consistent with the superior average performance of the S&P 500 over the sample period. For instance, looking at all projects with vintage years after 1990, shortly after the initiation of the MSCI EM index, the IFC achieved a PME = 1.30 relative to MSCI EM, a PME = 1.23 relative to MSCI World, and a PME = 1.14 relative to the S&P 500.

As expected, returns are positive according to the IRR and TVPI. The long-run IRR is 13.4%, 13
**EVALUATION QUESTIONS AND STRATEGY**

to respond to five questions related to Value for Money to understand their willingness to pay for Impact, Cost, and VFM studies.

The survey had 497 respondents who answered at least one question; the analytic sample is composed of 407 individuals who answered at least one of the “willingness to pay” questions. The survey asked respondents about their role within their organizations and then mapped those roles onto three functions within the policy-making process: Advisors (composed of researchers, academics, evaluators and consultants), Decisionmakers (high level executives within government or international or local NGS), and those who Execute those decisions (government functionaries, project managers); a category for “Other” (e.g. teachers, students, or librarians).

Of the analytic sample, two-thirds were male. Respondents were well educated. Nearly onequarter had a Ph.D., almost two-thirds had a master’s degree, 1 in 10 had a bachelor’s degree, and less than 1 percent had anything below a bachelor’s degree. They also tended to be well established in their careers: 60 percent were between 35 and 55 years old; 17 percent were older than that; and 23 percent were between 25 and 34. The income levels and regions of the country they professionally work on are shown in figure 2.1. So, too are the types of institutions where they work and their roles within that institution.

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in Bangladesh. In Section 3, we introduce our survey and provide a summary description of the farmers who are currently using IPM techniques. Section 4 examines the determinants of IPM adoption, while Section 5 presents our productivity comparisons for IPM and conventional rice farming. In Sections 6 and 7, we summarize our survey results on farmers’ health status and local ecological conditions. Section 8 concludes the paper and discusses some implications of our results.

# **2.  Agriculture and Environment in Bangladesh**

# **2.1  Pesticide Use**

Like many developing countries, Bangladesh has promoted the use of pesticides to expand agricultural land and increase output per acre. Promotional activities have included extension services and significant subsidies (Rasul and Thapa, 2003; Hossain 1988). Figure 1 shows that pesticide use has more than doubled since 1992, rising from 7,350 metric tons to 16,200 metric tons in 2001. An FAO analysis of pesticide composition in Bangladesh has revealed high shares of toxic chemicals that epidemiological studies have found to cause cancer, genetic damage, fetal damage, and

**Figure 1:  Trends in Pesticide Use, 1992-2001**

<!-- Start of picture text --> Pesticide consumption (metric tons)<br>18,000<br>16,000<br>14,000<br>12,000<br>10,000<br>8,000<br>6,000<br>4,000<br>2,000<br>0<br>1992 1993 1994 1995 1996 1997 1998 1999 2000 2001<br>Year<br><!-- End of picture text --> _Source_ : Department of Agricultural Extension, Plant Protection Wing, Bangladesh 3
The real balance sheet of the central bank of Hungary shows a similar pattern. As indicated in Figure 5, there was also a decline in the real stocks of credits and net worth during the second half of the 1980s, leading to a decline in central bank profits. The situation is less dramatic than in Yugoslavia, as indicated by a less pronounced decline in the stock of credits and net worth, and the fact that the stock of credits remained above the stock of foreign liabilities. Howe 'er, the trends indicate a deteriorating situation due to the same causes, namely, underpriced credits and an unwarranted distribution of cash profits.

# V. Conclusions and Further Thoughts.

In this paper we review and discuss a number of issues related to the relevant definitions of fiscal and quasi-fiscal deficits, as well as the consolidation of the two. The major issues discussed are the distinction between nominal and real deficits, the treatment of foreign exchange losses, and the treatment of public sector loans to the private sector.

Despite their limitations, real measures of the deficit provide a less distorted indication of the actual fiscal policy stance than nominal measures. The distinction between nominal and real definitons is even more relevant in the case of the central bank's quasi-fiscal deficit, given the financial nature of the central bank's operations. Central banks rarely recognize explicitly their losses in their income statements. Moie often, these income statements show sizable nominal surpluses, even in the cases where there is actually a real deficit in the operations with the private domestic and foreign sectors.

Real quasi-fiscal deficits usually reflect losses in other sectors of the economy and the need for a resource transfer. Therefore, a correction of these deficits may require more than a simple elimination of credit subsidies through an increase in real interest 40
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# **City statistical yearbooks**

This paper compiled sectoral value-added, foreign industrial firms’ total output and output share at the city level in 1990, 2000 and 2005 from city statistical yearbooks. Foreign firms’ output share is the key variable of interest in this paper. City statistical yearbooks also contain information on GDP per capita, share of rural population, output share of state-owned enterprises (SOEs) across cities used in the robustness checks section.

# **Annual Survey of Industrial Firms (ASIF)**

The ASIF database is a nationwide mandatory survey administered annually by the National Bureau of Statistics (NBS) in China to firms in mining industries, manufacturing industries and utilities industries. NBS uses the ASIF database to compute China’s GDP, and the aggregate information is published in the official China Statistics Yearbooks. It contains many firms distributed across more than 600 four-digit industries and throughout China’s 31 provinces, autonomous regions, and municipalities. Firms in the sample account for 95 percent of total Chinese industrial output and 98 percent of total Chinese industrial exports (Eberhardt et al. 2011). The sample covers all SOEs and private companies with annual sales above 5 million RMB (about 600,000-660,000 US dollars based on exchange rate during that period). The number of firms covered in the sample increased steadily from around 165,000 in 1998 to 336,000 in 2007.

The database contains more than 100 variables covering firms’ basic information, financial and operational information. Basic information includes the unique identifier, firm name, legal representative, detailed address, year of incorporation, main product, industry affiliation, and ownership structure. Financial and operational information cover most items in firms’ balance sheet, profit and loss statement, as well as cash flow statement. We use the ASIF database in 2000 and 2005 to complement city statistical yearbooks in calculating foreign firms’ employment and output share at the industry and city level.

# **Tariff data**

We obtained China’s export and import tariff at 4-digit ISIC level for years 1992, 2000, and 2005 from the TRAINS database. Sector level tariff is based on weighted average of tariff from all import sources and export destinations. The weights are constructed using the trade flow data from three years earlier. Following Li (2018), we concord all 4-digit ISIC sectors into 3-digit Chinese Standard Industry Classification (CSIC) code, then calculate city level tariff shocks by interacting initial industry employment share with changes in import and export tariffs.

# **Summary statistics**

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