rafmacalaba/data-use-mentions-extended huggingface dataset:
MONGOLIA'S INFORMAL SECTOR Appendix B: Methodologies and Descrptive Statistics 35

# -- Appendix B Informal Sector Survey Methodologies and Descriptive Statistics

100. Seven hundred amd seventy informals were surveyed in the course of this study. About three fourths of the informals were either taxicab or kiosk proprietors, and the remainder were informals operating from one of the outdoor markets or the street. This appendix will outline the survey methodology and the issues involved in estimating value added and incomes. Copies of the survey instruments and tables of descriptive statistics follow at the end of this appendix.

## **Taxicab Sample and Population**

101. A survey of 308 taxicabs was conducted in February, 1997. The purposes of conducting the taxicab survey were many, among them, the desire to be able to aggregate upward and estimate the rough contribution of taxicabs to value added, employment, and income. The difficulties of making such estimations are the same difficulties - facing any study of an informal activity the nature of the activity itself, and its informality, makes it difficult to precisely identify the population and scope of the activity. The difficulty is accentuated with the study of taxicabs, since they are all really just vehicles that are sometimes used for personal use, sometimes for official use, and sometimes as taxicabs, aLll in varying degrees.

102. Taxicabs are mobile enterprises, able to go where there is demand for their services. As such, the sampling of taxicabs for an exploratory study such as this needn't be complicated. The researchers simply hailed down passing vehicles, and by definition anyone who stopped is a taxicab at least part-time. An attempt was made to obtain approximately equal number of observations from each of the six districts within Ulaanbaatar City,"<sup>7</sup> at varying times of the day and night.

### **Adjusting for Over-Sampling Frequently Driven Vehicles**

103. The drivers were asked how many hours they operate their vehicle as a taxicab in a week. The responses to
<!-- Start of picture text --> 0.30 0.025<br>Kakwani Coefficient Marginal Contribution<br>0.20<br>0.015<br>0.10<br>0.005<br>0.00<br>-0.005<br>-0.10<br>-0.015<br>-0.20<br>-0.30 -0.025<br>b. Indirect taxes in selected countries<br>0.05 Kakwani Index Marginal Contribution 0.015<br>0.00<br>0.005<br>-0.05<br>-0.005<br>-0.10<br>-0.015<br>-0.15<br>-0.025<br>-0.20<br>-0.25 -0.035<br>KAKWANI INDEX<br>(CHANGE IN GINI POINTS)<br>REGRESSIVE <-------------> PROGRESSIVE MARGINAL CONTRIBUTION TO EQUITY<br>All indirect taxes VAT on durables VAT on clothing VAT on individual... Petroluem excise on... SCT on durables VAT on education<br>SCT on alcohol and tobacco VAT on energy products VAT on motor vehicles VAT on alcohol and tobacco SCT on energy products SCT on motor vehicles Other Indirect Taxes VAT on food and beverages VAT on communication... SCT on communication... SCT on sports and hobbies VAT on medical products VAT on sports and hobbies VAT on entertainment and...<br>KAKWANI INDEX<br>TO EQUITY<br>(CHANGE IN GINI POINTS)<br>REGRESSIVE <-----> PROGRESSIVE MARGINAL CONTRIBUTION<br>Croatia (2014) Poland (2014) USA (2016) Russia (2014) Brazil (2009) Chile (
of regulatory practice such as Transparency and Predictability. This was unavoidable at the time but means that current and future studies should enhance the “what regulatory agencies <u>actually</u> do” aspect relative to the “what regulatory agencies are required by the law to do”.

> 22 For clarity, the scores in Table 2 above have been converted from the published A- E to 1-5, as was originally intended.

> 23

> The same is true of the results in the Stern-Holder paper which were drawn directly from the 1997 NERA survey.

15
This version: 15 Feb 2024 8 this question, and the group discussion which ensued, in the latter half of the paper. Our paper is also influenced by a growing literature that uses qualitative methods to understand living standards from the bottom up (e.g., Kanbur, 2003; Morduch and Schneider, 2017; Rao, 2023).<sup>5</sup> The rest of the paper is organized as follows. In section 2, using a host of survey data sets, we revisit the official account of the Malaysian miracle. In Section 3 we analyze the qualitative data from the focus groups, and in Section 4 we draw on our quantitative and qualitative findings and the work of Polanyi and Hirsch to draw some insights on why growth may have an underside. Section 5 concludes the paper and briefly discusses some implications for policy.

# **2. Malaysia’s Economic Success: Miracle versus Paradox**

Many consider Malaysia’s economic performance a success story of inclusive growth with large reductions in poverty and inequality (World Bank, 1993; Stiglitz, 2007; <mark>Meerman, 2008)</mark> . At the time of independence, Malaysia was a low-income country, with GDP per capita comparable to that of other Southeast Asian nations such as the Philippines. Its economy largely depended on agriculture and the export of <mark>raw commodities such as tin and rubber. A</mark> close to double-digit GDP growth rate in the following decades helped Malaysia leave behind its regional neighbors and graduate to the lower-middle-income category in 1969 and to an upper-middleincome country in 1992. The growth surge coincided with the country’s rapid

> 5 We should note that Martin Ravallion, who was Vijayendra Rao’ manager for several years, was extremely supportive of the use of qualitative work in development economics.

8
MULTILINGUAL CHILD ASSESSMENT longitudinal study that examines the intergenerational effects of health investments. We used the translations and piloting data from that study to further adapt and expand the language and fine motor/perception subtests of the MDAT for the current study. The final adapted language test had 26 items. <mark>To further reduce the overall length of the test, we created start and stop rules for three different age groups (24–35 months; 36–59 months; 60–71 months) based on pass rates during piloting.</mark>

# **Caregiver survey**

Data were gathered on household assets, housing quality, household size and composition, and the age and education level of primary caregivers. In addition, we assessed caregiver literacy by asking caregivers to read a simple, five-word (second-grade level) sentence in each language adapted from the Early Grade Reading Assessment (EGRA; <mark>Gove & Wetterberg, 2011).</mark> Caregivers who read more than one word incorrectly in all three languages were categorized as illiterate. Working memory in caregivers was assessed using a summary score of the forward and backward digit span test (Ozier, 2018; out of 20 possible), and mental health was measured using an adapted version of the Centers for Epidemiological StudiesDepression scale (CES-D; Radloff, 1977; scores range 0-60). Household support for learning was measured with a set of items drawn from the HOME Inventory, Family Care Indicators, and UNICEF MICS4 (Bradley, Corwyn, McAdoo, & Coll, 2001; Hamadani et al., 2010; Kariger et al., 2012).

# **Statistical Analysis**

10
67|128|74|76|81|74|
|Capital|-7|-8|-7|-7|4|3|6|4|1|1|1|
|Transfers|6|23|4|7|19|16|30|17|52|37|34|
|Other Non-labor|-41|-47|-40|-44|-1|-1|-1|-1|4|2|3|
|Unexplained|8|-35|7|7|-24|-4|-91|-15|-18|-8|2|
|**Total change **|100|100|100|100|100|100|100|100|100|100|100|

<mark>Source: Own estimates based on Peru's ENAHO 2004 -2010, Thailand's SES 2000 -2009, and Bangladesh HIES 2000 -2010.</mark> Poverty rates are own estimates based on Peru's ENAHO 2004 -2010, Thailand's SES 2000 -2009, and Bangladesh's HIES 2000 -2010. International poverty lines are in US$ PPP terms. National lines are those establishes by the respective national statistical offices.

30
employment during the year of the reform. A typical reform in their sample increases real value added in the deregulated industry by about 10 percent after 5 years. Real wages increase significantly while labor productivity and employment increase, but these increases are borderline insignificant.

Some papers are concerned with heterogeneous responses to product market deregulation across sectors. Gal and Hijzen (2016) use a local projection approach and find that, on average, such deregulatory reforms raise firm capital by 4 percent, output by 3 percent, and employment by 1.5 percent after 2 years. These effects do, however, differ across sectors. Although most reforms occur in the service sector, they benefit firms’ output in retail trade and professional services at least as much as those in the service sector itself, indicating important downstream spillovers. Furthermore, the authors find evidence that within sectors, it is usually the most efficient firms that benefit from deregulation. In network industries, small firms tend to increase employment most, while larger incumbents react by downsizing. In retail trade, large businesses tend to benefit more than smaller ones. There are no significant differences across firm sizes in the professional service sector. However, the authors document an important role of credit constraints, which significantly weaken the positive impact of product market reform on firm investment.

Messina (2006) also highlights how PMR are connected to the sectoral employment patterns, and relates this to observed structural change dynamics across countries. Regressing countries’ service sector employment share on the degree of OECD PMR indicators suggests that a reduction of one standard deviation in entry barriers would result in a 1.6 to 2.3 percentage points increase in the service employment share for an average income country in the sample. Calculations imply that differences in regulations can account for about one-fifth of the cross-country differences in service sector employment shares after controlling for income levels. Against this background, the paper builds a model featuring non-homothetic preferences in agriculture and services, monopolistic competition in all three sectors, and differences in the rate of
Figure 5 plots the trends in informal shares of nonfarm employment by region between 2005/06 and 2016/17. We define informal employment as self-employment (including as a contributing family worker) or wage-employment without a written contract. Given this definition, the resulting informal shares should be treated as upper-bound estimates, as some (presumably small) percentage of the self-employed are likely to be formal and misclassified under our definition.

As the figure shows, most regions have observed a decline in the informal share of nonfarm employment. Whether a region shows a decline in informal share and to what extent does not appear to be related to whether the region is comparatively poor or rich.

# **III. Regional intersectoral productivity gaps**

# A. _Data, sample, and key variables_

Our main empirical analysis is based on data from Ghana’s Integrated Business Establishment Survey (IBES) 2014, administered by the GSS. The IBES 2014 is the latest census of nonhousehold establishments across all economic sectors.<sup>6</sup> In the survey, the GSS defines an establishment as “a unit of production or service engaged in a single economic activity under a single ownership at a single fixed location,” and defines nonhousehold establishment as one that “has a fixed location and operates from a structure not predominantly used for domestic activities.” The IBES was conducted in two phases, phase I and phase II. Fielded beginning in September 2014, phase I surveyed 638,480 business establishments. Data collected under phase I included location, form of organization, type of ownership, year of establishment, registration status, sector, principal and secondary activities, workforce size, skill distribution of the workforce, and type of financial accounting records maintained. The reference date for the data was August 31, 2014.

Fielded between November 2015 and April 2016, phase II surveyed 24,400 establishments (of an original intended sample of 31,152 establishments drawn from the set of establishments surveyed under phase I).<sup
- 5 -

# **2. Methodology**

Both qualitative and quantitative approaches have been used to analyze the impacts of different labor market institutions. Qualitative analysis is most common among “institutionalist” researchers who are interested in the complex interactions between institutions (especially unions) and the social and economic environment. However, regardless of perspective, quantitative analysis using various econometric techniques now dominates the field and, indeed, this review. Much of this research has been based on reduced form models that use aggregate cross-section data to explain the cross-country variation in various outcomes (such as unemployment) by differences in national labor market institutions. Increasingly, however, researchers are using longitudinal micro-data to estimate fixed effects models that isolate the variation in outcomes in a single jurisdiction over a period in which institutional change has occurred.

# **_2.1 Some methodological issues_**

Isolating the impacts of labor market institutions is inherently difficult. Without attempting to be exhaustive, this section briefly raises challenges that researchers face in terms of identification, measurement, and modelling and interpretation.

_Identification issues_ essentially result from the endogeneity of labor market institutions and the interactions between them. The endogeneity problem makes it difficult to attribute variations in outcomes to the institutions themselves, rather than other features of the societies in which they exist.<sup>4</sup> This is especially problematic when analysis is based on cross-country aggregate data and this is the major reason for scepticism about this approach. While single-country panels avoid this source of misidentification, they are not immune from endogeneity issues stemming from time-based sources—for example, certain institutional changes that are likely to be introduced at a certain point in the business cycle may be associated with outcomes that, in fact, could be due to the cyclical factors themselves.<sup>5</sup> Moreover, while single-country longitudinal studies may be useful for studying the impacts of some institutions that experience discrete changes (e.g., minimum wages), they are less suited for other institutions (
--|--|
|Tanzania(2006)|46%|11%|35%|--|--|--|27%|35%|25%|9%|
|West Africa|||||||||||
|Ghana(2010)|56%|41%|15%|64%|19%|5%|--|--|--|--|
|Nigeria (2008)**|47%|23%|24%|67%|7% (“currently<br>borrowing”)|2%|42%|36%|48%|22%|
|South Asia|||||||||||
|Pakistan (2009)***|44%|12%|32%|56%|35% (currently<br>has a loan)|2%|--|--|--|--|

* FinAccess. **Access to Finance Survey. ***Access to Finance Study (A2FS). §Estimate for use of formal product only.

- †In South Africa, this includes 45% who have funeral coverage, and 26% who use other products. In Lesotho, over a third of adults have funeral insurance. Funeral coverage is also common in Swaziland and Uganda.

‡Reflects access to government-sponsored medical insurance. Use of other types of insurance products is 0-1%.

8
||**Table**|**9:** **Non-US/EU**|**/EFTA IPAs**|**(Bilateral Tr**|**ade, 42 IPAs)**||||
|---|---|---|---|---|---|---|---|---|
||(1)<br>Low-IP|(2)<br>AI|(3)<br>BIO|(4)<br>CHEM|(5)<br>ICT|(6)<br>MED|(7)<br>PT|(8)<br>Other|
|**Exports**<br>log(GDPi)|0.361***<br>(0.075)||||||||
|Sector × log(GDPi)||0.433***|0.023|0.200**|0.234***|0.375***|0.332***|0.247***|
|||(0.078)|(0.093)|(0.080)|(0.086)|(0.096)|(0.114)|(0.072)|
|Sector × LI × IPAi|–0.465**|0.655***|–1.410**|–0.418|3.091***|0.328|0.685**|0.794***|
||(0.190)|(0.241)|(0.553)|(0.424)|(0.297)|(0.329)|
_The Global Information and Communications Technology Industry: Where Vietnam Fits in GVCs_ saturated nature of the market. Because of the fragmentation of the semiconductor industry into design and fabrication for hire in “foundries,” semiconductors designed in Vietnam can easily be fabricated in the few places in the world that dominate the foundry business: Chinese Taipei, Singapore, Malaysia, and the United States. In 2005, world foundry capacity for logic semiconductor fabrication surpassed capacity in “integrated device manufacturers” such as Intel, Samsung, and ST Microelectronics that produce their own designs of logic semiconductors in their own fabrication plants for the first time (Houseman et al, 2014)

# **Requirements for Upgrading the ICT Services and ICT-Enabled Services Sectors**

A number of software outsourcing and BPO firms interviewed for this study indicated a desire to grow in Vietnam and upgrade in the ICT services and ICT-enabled services segments of the value chain. Surveys including Gartner’s “Leading Global Locations for Offshore Services,” A.T. Kearney’s “Global Services Location Index” and Tholon’s “Top Outsourcing Destinations” indicate that Vietnam is emerging as “India+1” location for ICT and ICT-enabled services. However, many interviewees cited significant barriers to growth and upgrading, some of which will be highlighted here. Below we discuss how Vietnam can address training issues to support growth and upgrading into higher value industry niches. We focus specifically on language, technical and managerial training.

# _Language Skills_

The lack of foreign language skills in Vietnam is a serious impediment to growth in these segments of the GVC. As already indicated, Japan is an increasingly important software outsourcing market for Vietnam. In fact, Vietnam recently overtook India as the second largest exporter of software services to Japan.<sup>22</sup> Future growth in this market will depend in part on the availability of Vietnamese professionals with Japanese language skills. A similar problem exists with the US market, which requires English language skills. Many companies have developed strategies to overcome these
based on U.S. data for 2006 through 2008, while we use world data for 2001 through 2008.

# _6.7. Sources of data_

The various data sources are shown in Table 5. Data on production, consumption, beginning and ending stocks, imports, and exports for each region are obtained from the U.S. Department of Agriculture’s Production, Supply and Distribution database. Data on crop prices within each region are obtained from the FAO database. A key set of parameters in simulation models is the elasticities of crop supply and crop demand. Our specification of supply and demand requires information on elasticities of supply and demand with respect to own-price elasticities of supply and demand with respect to energy price and the income elasticity of demand. The range of elasticities contained in FAPRI database and in the literature cited by the USDA database is shown in Table 3.

39
of well-being that this measure cannot hope to capture, and we say nothing here about how responsive these other dimensions may be to growth.

While the NSS surveys are highly comparable over time by international standards, there is a particular comparability problem in the rounds since the early 1990s. While most of the surveys have used a uniform recall period of 30 days for all consumption items, seven of the survey rounds in the post-1991 period have instead used a mixed-recall period (MRP), with longer (one year) recall for some (mainly non-food) items.<sup>27</sup> On a preliminary investigation of the data we found that the use of a mixed recall period increased the mean and reduced inequality, implying lower poverty measures. All our regressions below include a control for MRP survey rounds.

**_Poverty lines and price indices:_** We report results for two poverty lines.  Following Datt and Ravallion (2011), one line is that originally defined by the Planning Commission (1979), and endorsed by Planning Commission (1993). This poverty line is anchored on a nutritional norm of 2,400 calories per person per day in rural areas and 2,100 calories for urban areas, and corresponds to a per capita monthly expenditure of Rs. 617 and Rs. 922 (rounded to the nearest rupee) in rural and urban areas respectively at 2011-12 prices.<sup>28</sup> The second poverty line corresponds to the rupee value of the international poverty line of $1.25 per person per day at 2005 PPP dollars, and are equivalent to rural and urban per capita monthly expenditures of Rs. 732 and Rs. 1,115 at 2011-12 prices.<sup>29</sup> The second set of lines are thus about 20% higher than the first set of lines.

The nominal values of the poverty lines for different NSS rounds are evaluated using separate urban and rural price indices. Our price indices are mainly based on the
<!-- Start of picture text --> URY<br>Currency Cyclicality Index = 0.05 + 0.41*Capital Flow Cyclicality<br>(1.35) (2.91) Monetary Policy Cycl. = -0.31 + 0.51*Capital Flow Cycl.<br>KOR IDN (8.77) (4.37)<br>MEX CRI<br>URY PER<br>TURUKR CHL<br>SWEARG MYS THAPHL ISLMEXNZL PRT ISR GRC IND TURBGR<br>CAN NORMLT DNKITAGBR FINCZE ESPPRTMARAUSCHLHRVISRSVKPERZAFGRCBRA COL INDHUN FRACYPNOR AUTITAIRL FINCZE JPNESP MAR KORTHAZAFPHLBRA NZL<br>BEL FRACYP HKGDEUAUTIRLLUXCHE JPNNLD LVAUSA ESTBGRCRI BEL DEUDNKGBR SWE MYS COLUSA<br>CAN CHE NLDAUS<br>-.4 -.2 0 .2 .4 .6 -.4 -.2 0 .2 .4 .6<br>Capital Flow Cyclicality Capital Flow Cyclicality<br>1<br>.4<br>.2<br>.5<br>0<br>-.2<br>0<br>Currency Cyclicality Index<br>Monetary Policy Proyclicality -.4<br>-.6<br>-.5<br><!-- End of picture text --> Note: Procyclicality of capital flows is calculated as the correlation between the cyclical components of quarterly GDP and private net capital inflow. The currency cyclicality index is computed as the coefficient of correlation between the cyclical components of GDP and exchange rates, where the cyclical components are deviations from the trends for quarterly data for 62 countries from 1975, q1 to 2013, q1. Cyclicality of monetary policy is calculated as the correlation between the cyclical components of GDP and short-term interest rates; monetary policy stance is considered to be procyclical if the interest rates are high during the periods of low economic growth. Data on net foreign currency position is from Benetrix, Lane, and Shambaugh (2014), and refers to
br>40<br>31<br>20<br>17<br>20<br>10<br>0 0<br>Wave 1 Wave 2 Wave 1 Wave 2<br>Probability of investing in digital<br>Probability of starting/increasing use of digital<br><!-- End of picture text --> _Second_ , the extent of digitization and product innovation is contingent on the severity of the initial shock to mobility, although causality is difficult to establish. Firms are more likely to accelerate digital adoption and product-innovation when facing larger disruptions to mobility (Figure 17). These differences are especially large when it comes to the use of digital technologies compared to 26For example Watanabe and Omori (2020) find that in the first few months of the pandemic Japanese consumers familiar with online channels switched to products and services that were sold online perhaps in an attempt to avoid face-to-face interactions.

> 27Relying on the first wave data collected between April and August 2020.

22