rafmacalaba/datause-encoder-data huggingface dataset:
**_Figure 1: Share of foreign workers in the respective employed populations (percent)_**

<!-- Start of picture text --> 30 20<br>25<br>15<br>20<br>15 10<br>10<br>5<br>5<br>0 0<br>Total employment Youth employment Employed men Employed women<br><!-- End of picture text -->

# _Source_ : LFS, various years.

Note: Youth refers to those 15 to 24-years-old.

**Indonesians make up the largest share of the foreign worker population, according to MOHA data.** Forty percent of foreign workers are Indonesian, followed by Bangladeshi (28 percent) and Nepalese (16 percent) (Figure 2). Anecdotal evidence suggests that Indonesians move to, and work in, Malaysia as irregular foreign workers more than other nationalities, benefiting from the close geographical proximity and Indonesian migrant networks in Malaysia, and therefore the Indonesian foreign worker share could be even larger than indicated by the MOHA data. Corroborating anecdotal evidence is that Indonesia has seen an influx of returning irregular overseas workers from Malaysia because of job losses during the ongoing COVID-19 crisis.<sup>‡</sup> Additional evidence is that the Indonesian government sent aid packages to support Indonesian day laborers in Malaysia—who are highly likely to be foreign workers—who were adversely affected by the Movement Control Order (MCO) implemented by the Malaysian government as a COVID-19 mitigation measure.

**Foreign workers are largely concentrated in physically demanding sectors of the economy such as manufacturing, construction and plantations** (Figure 3) **.** Foreign workers pick up the ‘3D’ (dirty, difficult, and dangerous) jobs in these sectors that Malaysians stay away from. In 2019, 35 percent of foreign workers were in manufacturing, 22 percent in construction, and 15 percent in services. Studies report, for instance, that the construction sector faces difficulties with filling jobs from the domestic labor force, as local youth avoid the sector because of the low wages, long work hours, physically demanding tasks, and limited career progression. Others argue, however, that the high dependency on foreign workers in the construction sector is associated with the existence of irregular foreign workers (Abdul-Rahman, et. al,

> ‡ More than 64,000 Indonesian foreign workers had returned from Malaysia amid the country’s ongoing lockdown since March 18. Source: The Jakarta Post, April 23, 2020, from https://www.thejakartapost.com/news/2020/04/23/high-influx-of-indonesian-migrant-workers-from-malaysiadespite-call-to-stay-amid-outbreak.html.

4
12 quantitatively (SDA) .14

# 2.3 Ouantitative ARDroaches: General Equilibrium

If an analysis of different policy scenarios, such as different mixes of policy, different timing of policies, or no adjustment policies, is desired, then a model must be constructed to perform simulations. The complexity of the micromacro interrelationships would suggest that models of a general equilibrium nature be used.

# a. CGE Models

One approach to tracing macro effects to individual incomes is that of a behavioural model (such as a SAM/CGE model) which incorporates details on factor and household behaviour.1<sup>5</sup> The social accounting matrix (SAM) is a data accounting framework that immediately draws together the relevant base year information: the structure, composition and level of output, the factorial value added, the distribution of income among institutions and among socioeconomic groups, and the consumption patterns of these institutions and groups. The construction of the SAM alone will yield essential information for any type of further analysis, including a simple partial qualititative analysis of likely policy effects. To analyse alternative policy scenarios, behavioural equations "<sup>4</sup> The paper by N'Cho-Oguie (1989) lays out the sequential model building method proposed by the SDA unit. The RMSM model for Togo is currently being upgraded to include distributional measures. Policy variables are input and GDP by sectors are output. These GDP values are allocated to different socioeconomic groups by fixed coefficients using data from a household survey. The model is still largely an accounting model.

"This is the approach that will be taken by the forthcoming Cornell study on adjustment in Africa, see Scobie (1989). This approach is well summarized and recommended by Thorbecke and Berrian (1987). Although some CGE models do not explicitly start with a SAM, such an accounting framework is implicit in the calibration of the model.
NIC industry dummies that are consistent across all census-years and restrict the data to only the manufacturing sector.<sup>14</sup> To explore industry heterogeneity, we use three different classifications of industries. First, we follow the procedure in Rajan and Zingales (1998) and estimate an industry’s dependence on external financing using data on US corporations (RZ index). The RZ index is based on the assumption that, since U.S. financial markets are developed, sophisticated, have fewer market imperfections and are relatively open, they should allow US firms to achieve their desired financial structure. Thus assuming that there are technological reasons why some industries depend more on eternal finance than others, the RZ index offers an exogenous way to identify the extent of external dependence of an industry anywhere in the world. The methodology does not require that the US markets are perfect but rather that market imperfections in the US do not distort the ranking of industries in terms of the technological dependence on external financing.

We reconstruct the RZ index for the period 1980-2012 by computing external dependence as (Capital Expenditures-Operating Cash Flow)/Capital Expenditures for each domestic US firm in Compustat. The median value across firms in each industry is a measure of that industry’s dependence on external finance. This index of external dependence is constructed at the SIC 2/3 digit level which is then manually matched to 3-digit ISIC codes that map onto the Indian NIC classification. Appendix C provides the concordance used in the paper. We construct **EFD,** a dummy variable that takes the value 1 if the industry’s dependence on external finance is ≥ the median value of dependence on external finance across industries and 0 if it was < the median across industries.

> 14 We drop recycling from the manufacturing sector since it is not included under manufacturing in the ISIC classification.

14
Act, requesting the National Academy of Sciences to assess the health consequences of exposure to wartime military herbicides. The Institute of Medicine provides updates on the scientific evidence on a bi‐annual basis.

The debate has also moved to the legal battlefield. War veterans and Vietnamese civilians filed a lawsuit against the chemical companies that manufactured the herbicides. The case was dismissed on March 10, 2005 and went to The Supreme Court, which let the dismissal stand in a March 2, 2009 decision.

# **3. Data and empirical methodology**

## **3.1. Data**

To look at the effects of herbicide spraying on cancer status in the Vietnamese population, two important sets of data are combined.

_3.1.1. The 2001‐2002 Vietnam National Health Survey_ _Self‐reported_ and _proxy‐reported_ cancer status is collected from the 2001‐2002 Vietnam National Health Survey (VNHS). VNHS is a nationally representative survey undertaken by the Ministry of Health and the General Statistics Office. A stratified random sample of 1200 communes (out of a total of 8926 communes) and 36 000 households was interviewed from November 2001 to November 2002. VNHS gathers individual data on self and proxy‐reported morbidity. More precisely, the survey instrument asks the main respondent (in most cases the household head or his/her spouse) about all household members’ health conditions. In particular, information on cancer is recorded as follows (official English translation): “May I ask, has anyone in your household been diagnosed by a doctor or PA with any of the following illnesses? 1) Blood pressure disease?, 2) Cancer?, 3) Epilepsy?”. A positive answer is marked with an X in the column corresponding to a given health condition and in the line corresponding to the individual suffering from it. The outcome variable of interest in this study is derived from answers to the second question.

Socio‐economic status is measured using elementary assets, education and food consumption information. Another survey module gathers information on individuals’ health care utilization history. Finally, households’ communes of residence are matched with the official General Statistics Office list of Vietnamese communes, which provides geographical 6
29 level from the calculation of taxable income.<sup>25</sup> Although helpful in correcting for distortions in the measurement of income, indexing does add to the complexity of an income tax. As a rough rule of thumb, indexing is probably not worth the trouble if inflation is low--say, less than ten percent per year. If inflation is over 20 percent per year, indexing is probably much more important. In between, the decision should rest on an assessment of administrative capacity.

Whether or not the tax base is indexed, absolute amounts fixed by the tax law--such as tax brackets, personal exemptions, and penalties for noncompliance--can quite easily be indexed through regular adjustment. Indexing of penalties is particularly important to prevent their becoming obsolete.<sup>26</sup>

# THE TAX TREATMENT OF THE FAMILY.

Personal exemptions for individuals provide a method of excluding those with low income from the income tax net. Most countries allow personal exemptions for each member of a family in order to take into account the larger expenses of larger families.27 As noted earlier, setting relatively high personal exemption levels--on the order of two 25 A simple and accurate method of indexing involves the following three steps. First, all real assets (primarily depreciable assets and inventory) are written up by the index factor, and this amount is included in profit on the income statement. Second, all real liabilities (owners' equity) are written up by the index factor, and this amount is subtracted from profit on the income statement. The net effect of these two steps is to add back into income the pure inflation element of interest deductions taken on debt used to finance purchases of real assets. Third, depreciation is calculated on the written-up value of depreciable assets (Harberger, 1982). For a discussion of indexing methods, see World Bank (1987), pp. 74-77.

26 Penalty clauses in the old Indonesian tax laws typically called for "'six months in jail or a fine of 600 rupiah [less than U.S.$1]"! 27 Exemptions for children are sometimes lower than exemptions for adults. Some countries limit the number of children for whom exemptions can be taken in order to support a trend toward smaller families.
||(1)|(2)|(3)|(4)|(5)|(6)|
|---|---|---|---|---|---|---|
||OLS|OLS|OLS|OLS|2SLS|2SLS|
||pcgdpgrowth|pcgdpgrowth|pcgdpgrowth|pcgdpgrowth|pcgdpgrowth|pcgdpgrowth|
|Constant|-0.023|-0.153|-0.022|-0.105|-0.028|-0.178|
||(0.013)*|(0.159)|(0.013)*|(0.154)|(0.013)**|(0.216)|
|pcgdp90|-0.000|-0.000|-0.000|-0.000|-0.000|-0.000|
||(0.000)*|(0.000)*|(0.000)|(0.000)|(0.000)|(0.000)|
|school_enrol_secondary|0.000|0.000|0.000|0.000|0.000|0.000|
||(0.000)*|(0.000)*|(0.000)*|(0.000)*|(0.000)|(0.000)*|
|school_enrol_primary|0.000|-0.000|0.000|-0.000|-0.000|-0.000|
||(0.000)|(0.000)|(0.000)|(0.000)|(0.000)|(0.000)|
|inv_gdp|0.149|0.213|0.149|0.223|0.210|0.217|
||(0.028)***|(0.036)***|(0.028)***|(0.036)***|(0.032)***|(0.033)***|
|pcwater|-0.000||-0.000||-0.000||
||(0.000)||(0.000)||(0.000)||
|pcwater_gr||0.118||0.072||0.140|
|||(0.150)||(0.145)||(0.212)|
|pcwater_mena|||-0.000||||
||||(0.000)||||
|pcwater_grmena||||-0.010|||
|||||(0.006)|||
|Observations|77|60|77|60|61|57|
|R-squared|0.46|0.55|0.46|0.57|0.54|0.57|
|Wu-Hausman F<br>test, p-value|||||0.27|0.89|

Robust standard errors in parentheses. * significant at 10%; ** significant at 5%; *** significant at 1%. Instruments are beginning of the period indicators for: infrastructure, agri/gdp, population density, population. Variables are in per capita terms except where variable name does not begin with ‘pc’.

Finally, we performed panel regressions using 5-year averages.<sup>12</sup> The results are disappointing: all infrastructure variables negative and not significant most of the time, with the exception of electricity generating capacity and the interaction of roads with the MENA dummy. When performing panel regressions with fixed effects and instruments, results are very similar with no influence of infrastructure variables on growth, the only exception being the MENA interactions term in regression of the electricity variables – but even in that case the coefficient, albeit significant, is negative again suggesting a lower effect than in the whole sample. As for panel regressions with instruments and random effects, again results are disappointing as none of the infrastructure variables or their MENA interactions is significant, except for the mobile phone one and the rail interaction which has a strongly negative coefficient.

> 12 The Tables with the results, omitted to save space, are available from the authors.

21
Finally, it has been previously found that research on the African continent tends to be skewed to a few countries. The evidence base for local policy makers in neglected countries or “research deserts” is relatively small. Porteous (2020) documents statistics on economic research in Africa and shows that 87% of all published economics journal articles account for one-third of African countries and are highly skewed towards five countries.<sup>3</sup> The distribution is uneven and accounted for only 16% of the continent’s population. It is evident that the Comoros falls within the forgotten 21 countries that have an average number of publications of 0.2 per country (Porteous, 2020). Heterogenous characteristics (socio-economic and political) can limit external validity across countries, especially in Africa. Even before the pandemic, as highlighted above, the Comoros had one of the highest poverty rates in the world. It is also vulnerable to natural disasters and climatic shocks. It is thus important to understand how the pandemic has affected a small island state like the Comoros, which is already facing several development challenges but with a narrow evidence base. Our unique data consisting of pre- and post-pandemic observations provides an opportunity to make a meaningful contribution. To the best of our knowledge, this paper will be the first to evaluate the welfare consequences of the Covid-19 lockdown in the Comoros in a robust manner.

This paper aims to quantify the impact of direct lockdown measures on household welfare in the Comoros, a poor developing country and specifically an understudied developing country. The unexpected outbreak of Covid-19 coincided with data collection for the Harmonized Survey on Living Conditions of Households (EHCVM), lending itself to a quasi-natural experiment in which households interviewed prior to the lockdown could be considered as the control group and those interviewed after the lockdown as the treated group. First, this paper presents descriptive statistics, followed by ordinary least squares and probit regression analysis to control

> 3 These five frequently researched countries are South Africa, Kenya, Ghana, Uganda and Malawi.

4
106(5): 574-580.

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_— 32 —_
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The scarce evidence available from a few Latin American countries indicates that low quality consumption goods and services constitute a large share of the informal sector exports, the principal buyers being formal sector workers. A similar view can be found in the 1990 World Development Report in which the informal sector is described as a producer of consumption goods, espe. e ty by low-income households (World Bank [1990] p.63). For example, Lopez et al [1987] found that, in Colombia, the demand for informal sector exports is closely related to the wage-bill. There is also some evidence from Latin America indicating that the income-elasticity of the demand for such goods is much higher for low-income than for high-income families (Tokman E1983)).21 Under these conditions, a reduction in the minimum wage could reduce the demand for the goods exported by the informal sector and thus reduce employment opportunities in the sector. Camargo [1987], for example, makes this argument when discussing the determination of informal sector earnings.

The final impact on the earnings of informal sector workers will depend on both the changes in the demand for their exports and the induced changes in the sector's terms 21Adelman and Taylor (1990] report, in the case of Mexico, higher values of household marginal expenditure propensities for working class families than for capitalists in the case of industry, services and commerce.

18
GEL 100,000 coincides with the threshold for paying VAT. We thus need to use a difference-in-difference analysis to estimate whether the size of the jump increased due to the reform.

<!-- Start of picture text --> Figure 16a: Number of new firms around GEL Figure 16b: Number of new firms around GEL<br>100,000 cutoff – 2011 data (post-reform) 100,000 cutoff – 2012 data (post-reform)<br>Local Avg. + Polynomial in GEL 500 Intervals from Cutoff Local Avg. + Polynomial in GEL 500 Intervals from Cutoff<br>50000 100000 150000 50000 100000 150000<br>2011 Declared Revenue 2012 Declared Revenue<br>40 25<br>20<br>30<br>15<br>20<br>10<br>10<br>Number of new firms in 2010 Number of new firms in 2011 5<br>0 0<br><!-- End of picture text --> Table 9 displays the results of the difference-in-difference regressions, using data for 2008 through 2012. Here, we add interaction terms of the reform threshold with a dummy for years 2009, 2008, 2011, and 2012. The coefficient on the variable “Revenue < 100,000 dummy” gives the size of the jump at the GEL 100,000 threshold in 2008. The interaction terms with each year show the difference in the size of the jump in that year, relative to 2008. The shaded estimates indicate that the size of the jump was greater in 2011 and in 2012 than in 2008, but only one of the coefficients is statistically significant and only at the 10-percent level. The size of the coefficients in 2011 and 2012 also varies quite a lot across specifications, implying that we do not find a robust effect of the small firm tax regime on formal firm creation.

26