rafmacalaba/datause-encoder-data huggingface dataset:
**Table 7. COVID-19 impacts on work hours and earnings, by formal/informal employment**

||F<br>|ormal<br>|In<br>|formal<br>|
|---|---|---|---|---|
||Work hours|Monthly earnings|Work hours|Monthly earnings|
||(1)|(2)|(3)|(4)|
|**Panel A: Female**|||||
|COVID|-4.725***|-0.119***|-0.604***|-0.187***|
||(0.238)|(0.010)|(0.198)|(0.016)|
||[0.000]|[0.000]|[0.002]|[0.000]|
|Sector / Occupation FE|Yes|Yes|Yes|Yes|
|Observations|264,147|244,505|524,026|176,681|
|Pre-pandemic average|||||
|**Panel B: Male**|||||
|COVID|-3.145***|-0.113***|-1.809***|-0.139***|
||(0.187)|(0.008)|(0.245)|(0.013)|
||[0.000]|[0.000]|[0.000]|[0.000]|
|Sector / Occupation FE|Yes|Yes|Yes|Yes|
|Observations|484,598|419,273|661,746|336,960|
|Pre-pandemic average|||||
|Test:βm= βf(p-value)|0.000|0.500|0.000|0.005|

Notes: ***, ** and * denote significance at 1%, 5% and 10%, respectively. Parentheses indicate standard errors, while square brackets indicate the False Discovery Rates (FDR). Work hours and monthly earnings are conditional on a respondent’s employment status (i.e., missing for non-employed respondents), and regressions for these variables include only workers aged 15-64 who have more than six months of experience in current job/occupation. Earnings regressions exclude the unpaid/family workers. Formal workers include workers who are either employee, or employers that are assisted by permanent workers. The main variable of interest in the above results is the COVID dummy, which takes on the value of 1 if the time period is August 2020. Pre-pandemic averages are the averages of the employment outcomes among employed individuals throughout 2016–2019 (both February and August rounds), and pre-pandemic monthly income average excludes the unpaid family workers. All earnings averages are reported in real 2007 rupiah. Control variables include age, squared age term, marital status, number of children under age five, education level dummies, training experience dummy, and urban/rural dummy. All specifications include year, province, month, sector and occupational fixed effects. Results are robust to excluding sector and occupational fixed effects.

36
Policy Research Working Paper 6657

# **Abstract**

What determines the quality of budget execution around the world, measured in terms of a government’s ability to accurately hit its own revenue and expenditure targets? The answers could be relevant to the topics of macroeconomic stability, national development, public service delivery, and political reputation. This paper takes a step toward finding answers through the exploration of a new database of budgets and budget outcomes and potential cross-country correlates of budget execution in levels and in composition. Few countries within the data sample execute their budgets well, in levels or in composition. Expenditure deviations are positively but rather loosely correlated with revenue deviations. Within this broad tendency, there is considerable variation in behavior not only across countries, but also across time within countries. In explaining the cross-country variations, the data confirm traditional drivers for common pool behavior while also supporting constructive roles for political institutions and the technical capacity for public financial management. This is good news for reform minded governments.

This paper is a product of the Poverty Reduction and Economic Management Unit, East Asia and the Pacific Region. 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://econ.worldbank. org. The author may be contacted at DAddison@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 for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
# **Table 10: Number of enterprises and employees in the UBI Samples by employment size group, 2002 and 2009**

||**_A. Number o_**|**_f enterprises i_**|**_n the sample_**||||||||
|---|---|---|---|---|---|---|---|---|---|---|
|||All se|ctors<br>|||Number o|f enterprises||||
|**Size Grou**|||% shar|e in|||||||
|**p**<br>**(number of**|Number of|enterprises|total||Primary sec|tor|Manufacturi|ng|Services & o|ther industries|
|**workers)**|2002|2009|2002|2009|2002|2009|2002|2009|2002|2009|
|less than 5|1,266|1,583|26.8|34.1|42|47|101|384|1,123|1,152|
|5‐20 workers|2,505|1,562|53.0|33.6|165|52|575|353|1,765|1,157|
|21‐100 workers|787|1,233|16.7|26.5|34|25|207|260|546|948|
|More than 100|164|270|3.5|5.8|16|14|73|83|75|173|
|Total|4,722|4,648|100.0|100.0|257|138|956|1,080|3,509|3,430|
||**_B. Number of_**<br>|**_workers in s_**<br>All se|**_ampled enter_**<br>ctors<br>% shar|**_prises_**<br>e in||Number o|f workers||||
|**Size Group**<br>**(number of**|Number of|workers|total||Primary sec|tor|Manufacturi|ng|Services & o|ther industries|
|**workers)**|2002|2009|2002|2009|2002|2009|2002|2009|2002|2009|
|less than 5|2,238|3,584|1.6|1.9|109|106|203|924|1,926|2,554|
|5‐20 workers|24,977|16,951|18.1|8.8|1,800|516|5,587|3,632|17,590|12,803|
|21‐100 workers|31,600|52,357|22.9|27.2|1,471|1,158|8,708|11,172|21,421|40,027|
|More than 100|76,896|117,672|55.8|61.1|11,507|6,407|29,614|55,710|35,775|55,555|
|Total|137,712|192,573|100.0|100.0|14,887|8,187|44,112|71,438|76,712|110,939|

|**Age Group**<br>|**_C. Number o_**<br>|**_f enterprises w_**<br>All<br>sectors<br>|**_ith known a_**<br>|**_ge in UBI_**<br>|**_samples :_**||Number of e<br>|nterprises<br>|||
|---|---|---|---|---|---|---|---|---|---|---|
|**(years)**|Number of|enterprises|% share of|total|Primary sect|or|Manufacturi|ng|Services & o|ther industries|
||2002|2009|2002|2009|2002|2009|2002|2009|2002|2009|
|< 5|1,583|1,836|47.7|40.4|57|28|280|392|1,246|1,416|
|5 to 10|853|1,147|34.6|25.3|32|32|225|270|596|845|
|More than 10|882|1,556|26.6|34.3|128|76|194|388|560|1,092|
|Total|3,318|4,539|100.0|100.0|217|136|699|1,050|2,402|3,353|
|**Age Group**|**D. Number o**|**f workers in e**<br>All<br>sectors|**nterprises wi**|**th known**|**age in UBI sa**|**mples**|Number of w|orkers|||
|**(years)**|Number of|workers|% share of|total|Primary sect|or|Manufacturi|ng|Services & o|ther industries|
||2002|2009|2002|2009|2002|2009|2002|2009|2002|2009|
|< 5|14,804|31,826|22.0|16.9|1,482|910|3,540|8,721|9,782|21,683|
|5 to 10|17,491|38,716|26.0|20.5|1,292|2,195|6,655|9,099|9,544|26,649|
|More than 10|34,886|118,128|51.9|62.6|10,542|5,024|7,009|51,058|17,335|60,171|
|Total|67,180|188,670|100.0|100.0|13,316|8,129|17,204|68,878|36,661|108,503|

44
**Decoupling and recoupling**

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<u>18</u>
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- 72 Emanuel _et al._ 2006 “Who should get influenza vaccine when not all can?” _Science_ **312** :854‐8555; also see _Letters_ in the same issue critiquing Emanuel _et al._ (from Frey, H., and Galvani _et al._ )

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``` 27 ```
While the global imbalance question is complex and involves other large economies such as Germany or Japan, it is useful to focus on the US and China: they are currently the two most dominant national economies in the world; China will shortly pass Japan to become the world's second largest economy behind the US and the two together accounted for almost one-half of all global growth during the four-year boom prior to the current global crisis; they are the two largest trading nations; the US is the largest deficit and debtor country while China is the largest surplus country and holder of dollar reserves; and they are the leaders of the two groups, the high-income industrialized countries and the emerging markets/developing nations, that each now account for about one-half of global output (Bergsten, 2009).

The evolution of the US current account balance in recent years (Figure 1) and the accumulation of public debt have been subject to much debate. Economists have worried about the potential implications of the change of status of the largest economy in the world, from a creditor nation to a debtor nation. The rapid erosion of the US net external asset position has also raised concerns about the status of the dollar as the preeminent world currency. Expressing desperation, McKinnon recently noted that “economists have failed dismally to construct convincing theoretical models of why the seemingly endless US current account deficits are sustained by a seemingly endless willingness of the rest of the world to acquire dollar assets.” The main issue with large current account deficits is obviously their sustainability, that is, whether they will be met by sufficient, timely and affordable inflows of foreign capital. In the case of the US for instance, it bears on the questions of (i) the size of the financial obligations that the deficit reflects, (ii) the availability of income payments and receipts that will eventually be paid out of the economy’s production—with the risk of reducing current consumption and investment, and (iii) the confidence in creditor nations or in the low probability of sudden swings in the mood of foreign investors.2 Although much of the public debate over current account deficits tend to focus on their size, the dynamics underlying the numbers are more important. After all, these deficits are simply the results of many forces at play, in other words the reflection of the general historical data as far back as 1890, Eichengreen (1987) found that current levels of U.S. deficits have no precedent.

> 2 A current account is considered ‘sustainable’ at a point in time “if neither it, nor the associated foreign capital inflows, nor the negative net international investment position are large enough to induce significant changes in economic variables, such as consumption or investment or interest rates or exchange rates. Even if the current account deficit is sustainable by this definition today, its trajectory could still be creating future risks for the US and global economy.” (Mann, 2002 : 134).

3
7 by foreigners in government securities amounted to 44 percent of the stock outstanding of all forms of securities. Portfolio investment in CETES amounted to almost 50 percent of the stock of such securities. Finally equity holdings by foreign investors now account for more than 60 percent of the value of shares outstanding which are being transacted.

**Table 2-b Foreign Investment in the Mexican Stock Exchange Amount Outstanding at Market Value (Millions of Dollars)**

|Month|ADR|'s|Free Subs|cription|Neutral|Fund|Mexico|Fund|T'ot|al|
|---|---|---|---|---|---|---|---|---|---|---|
||Amount|Shiare|Amount|Share|Amount|Share|Amount|Share|Amount|Share|
|Dec 1989|402.0|49.8|107.0|13.2|35.0|4.3|264.0|32.7|808.0|100.0|
|Dec 1990|2.086.8|51.2|i.072.7|26.3|676.0|16.6|243.9|6.0|4.079.5|100.0|
|Dec 1991|13.733.5|74.1|2.961.0|16.0|1.348.8|7.3|499.3|2.7|18.542.5|100.0|
|Dec 1992|21.154.0|73.8|5.097.0|17.8|1.798.1|6.3|619.01/|2.2|28.668.0|100.0|
|.Jun 1993|16.202.4|73.3|3.780.1|17.1|1.460.9|6.6|674.4|3.0|22.1 17.7|100.0|
|Dec 1993|21.154.0|73.8|5.097.0|17.8|1.798.1|6.3|619.01/|2.2|28.668.0|100.0|
|Annual|||||||||||
|Variations|||||||||||
|Dec-90/|419.1||902.6||1,831.5||-7.6||404.9||
|Dec-89|||||||||||
|Dec-91!|558.1||176.0||99.5||104.8||354.5||
|Dec-90|||||||||||
|Dec-92/|54.0||72.1||33.3||24.0||54.6||
|Dec-91<br>I/ Portfolio|value at Octo|ber 1992.|||||||||

**SOURCE: Anuario Bursatil 1992, Bolsa Mexicana de Valores, January, 1993**

**Table 2-c**

||||**Foreign I**<br>**A**|**nvestment**<br>**mount O**<br>**(Mi**|**in Mexi**<br>**utstandin**<br>**llions of**|**can Gov**<br>**g at Ma**<br>**New Pes**|**ernment S**<br>**rket Valu**<br>**os)**|**ecuritie**<br>**e**|**s**||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
|**D)atc**|CET|ES|PAGA|FES I/|BON|DES|TESOBO|NOS I/|AJUSTA|BONOS|TOT|AL|
||Amount|Share|Amount|Share|Amount|Share|Amount|Share|Amount|Share|Amount|Share|
|.lan-31-91|4.056.6|4t.1|262.1|2.7|4.634.7|47.0|53.4|_0.5_|862.2|8.7|9.868.9|100.0|
|**jutn-25-91**|6.692.4|45.3|667.8|4 5|4.008.2|27.t|23.8|0 2|3,379.1|22.9|14,771 3|100.0|
|D)cc-30X-9I|0.075.1|54.0|64.8|0.4|2.231.1|13.3|790.1|4.7|4.641.5|27.6|16.802.7|<br>100.0|
|**Jun-30-Q2**|15.039.3|58.4|0.0|0.0|1,695.4|6.6|924.3|3.6|8.078.8|31.4|25.7377|100.0|
|Dec-30-92|28.539.9|64.3|0.0|0.0|3.856.8|8.7|615.6|1.4|11,355.8|25.6|44.368.1|100.0|
|Variations|||||||||||||
|**Dcc-91.Jan.-9I**|<br>123.7||-75.3||-51.9||1.381.0||438.4||70.3||
|I)cc-92ADcc-91|<br>314.5||NA.||72.9||-22.1||144.7||164.1||
|1. For 1'AiAFE<br>**SOt**R('E Itanc|s and TESOB<br>o de Mexico|ONOS the av|erage exchang|e rate of'curre|nt month was|used.|||||||
<u>STATA code for Monte Carlo Simulation: Linear Model</u> clear all program define sim, rclass drop _all set obs 500 gen e=rnormal(0,1) gen u=rnormal(0,1) gen R=rnormal(0,1) ***set coefficients in system of equations *(1) y=bx+rR+e *(2) x=ay+u scalar a=-1 scalar b=1 scalar r=1 ***generate y and x; follows from solving eq (1) and (2) gen y=(1/(1-a*b))*(b*u+(r*R+e)) gen x=(1/(1-a*b))*(a*(r*R+e)+u) ***IV estimation of eq (2) ivreg x (y=R) ***generate instrument for eq (1) based on IV estimation of eq (2) scalar a_iv=_b[y] gen z=x-a_iv*y ***IV estimation of equation (1) ivreg y (x=z) scalar b_iv=_b[x]

***Pitfall I: instrument for eq (1) based on least squares estimation of eq (2) reg x y scalar a_ls=_b[y] gen z_ls=x-a_ls*y ***IV estimation of eq (1) based on residual generated by least squares of eq (2) ivreg y (x=z_ls) scalar b_iv_ls=_b[x] ***Pitfall II: least squares estimation of eq (1) reg y x scalar b_ls=_b[x] end

simulate b_iv b_iv_ls b_ls, reps(10000): sim 39
- 10-

Thirsk,<sup>3</sup> by Sijbren Cnossen,<sup>4</sup> and by Mukul Asher and Anne Booth for the ASEAN countries.5 One of the most complete recent studies is that for Jamaica by Michael Wayslenko.<sup>6</sup> All of these are based upon consumer expenditure studies, showing expenditures by commodities and services by income groups, and these are by no means entirely accurate, especially for alcoholic beverages. It is not possible to review these studies in detail, but summary is possible.

A portion of the Jamaica study is shown in Table 3, providing data for both excise taxes and the portion of the consumption tax applying to the same commodities, with different income brackets. The tax on cigarettes and tobacco products is clearly regressive, except in the lower income brackets. The tax on beer is progressive at the lowest brackets, then more or less proportional and regressive at higher levels. Tax on distilled spirits shows an irregular pattern, with progression at some levels but regression at higher levels. All alcoholic beverages combined show an overall progression except at the higher income levels, but in an irregular fashion; expenditures on the lower taxed item are concentrated in the lower income levels. The tax on motor fuel is proportional, slightly progressive at the higher income levels.

3Charles McLure and Wayne Thirsk, "The Inequjty of Taxing Iniquity," Economic DeveloDment and Cultural Chance 26 (April 1978), 487-503.

4Sijbren Cnossen, Excise Systems: A Global Study of the Selective Taxation of Goods and Services (Baltimore: Johns Hopkins Press, 1977).

5Mukul G. Asher and Anne Booth, Indirect Taxation in ASEAN (Singapore: Singapore University Press, 1983).

6 Michael Wayslenko, Tax Burden in Jamaica Before and After Tax Reform. Jamaica Tax Structure Examination Project, Metropolitan Studies Program, Syracuse University and Jamaica Board of Revenue (Syracuse and Kingston 1987).