rafmacalaba/datause-encoder-data huggingface dataset:
-8-

To address the concern that state-owned enterprises received a favorable treatment, an additional "dividend tax" on profits of state-owned enterprises was introduced at the beginning of 1992, mimicking dividend payments that private enterprises have to pay out to capital owners (OECD, 1993; the tax was abolished in May 1994). Thereby a level playing field for all enterprises was created and disincentives for state-owned enterprises to be privatized were partly removed.

Further changes were introduced in subsequent years. In 1995, a new CIT scheme was created. Profits were now subject to a basic tax rate of 18%. On distributed profits, a supplementary tax of 23% (tax-exclusive) was levied. The total tax burden on dividends, therefore, increased to - 18+ (100 18). 23/123=33 1/3 percent. Tax preferences for joint ventures and other enterprises were maintained but applied only to the basic tax payment of 18%. In late 1996, the Parliament approved another reform of corporate income taxation. The corporate income tax rate was harmonized at 18% for all company profits, no matter whether retained or distributed.

The Hungarian approach of granting very generous special incentives, especially to foreign investors, has been widely criticized. Since it is highly questionable whether the incentives granted actually were having the desired effect, in 1990, all preferences were limited to 10 years (remember that initially some of the tax reductions were granted indefinitely) and, in 1994, were completely abolished. Existing preferences remained in force, so that the last preferences granted under this scheme will expire by 2004.10

# _Withholding Tax_

Together with the CIT, the tax on personal income determine the overall tax burden on capital income. In 1988, taxation of capital income was reformed as part of the entire package to reform the personal income tax. Dividends and interest payments were subject to a 20% withholding tax on capital income. This flat-rate tax was final. No additional personal income tax was levied on capital income. At the same time, no credit was given for corporate income taxes paid on distributed profits. The Hungarian system, therefore, can be described as a system of partial integration, i.e., corporate income taxes can not be deducted from personal income tax liabilities, which, in turn, consist of a final withholding tax at a relatively low rate.

These rules were effective until the beginning of 1994 when, in a move to increase savings, the tax rate on dividends and interest payments was reduced to 10%. The other features of the system

**10** At the beginning of 1994, new incentives to retain and re-invest profits were introduced, again with an unclear impact on investment decisions of fims. See World Bank, 1995, p. 15.
<!-- Start of picture text --> .0007 .0007<br>.0006 .0006<br>.0005 .0005<br>.0004 .0004<br>.0003 .0003<br>.0002 .0002<br>0 20 40 60 80 100 0 20 40 60 80 100<br>% of Contract Period % of Contract Period<br>Hazard Hazard<br><!-- End of picture text --> _Source_ : Authors’ calculations. _Note_ : The model uses one interior knot.

One can introduce more interior knots to obtain a better fit using the flexible parametric approach. Observe that the relationship can still be improved. However, this quest may result in overfitting the sample. To this end, flexible parametric proportional hazards (PH) and proportional odds (PO) models with different degrees of freedom have been fit and the Akaike information criterion (AIC) and the Bayesian information criterion (BIC) are used to select the appropriate model. Table C.1 shows the resulting AICs and BICs. Observe that the PH(2) yields the lowest AIC and BIC, so the analysis overall uses the PH(2) model. It must be noted that choice of the model does not have substantial qualitative or quantitative effects on the estimates.

**Table C.1 AIC and BIC under different orders of flexible parametric methods**

||PH(1)|PO(1)|PH(2)|PO(2)|PH(3)|PO(3)|PH(4)|PO(4)|PH(5)|PO(5)|
|---|---|---|---|---|---|---|---|---|---|---|
|AIC|1504.0|1510.7|**1483.4**|1492.6|1485.3|1494.5|1489.8|1497.1|1490.6|1499.8|
|BIC|1578.8|1585.6|**1561.4**|1570.6|1566.3|1575.5|1580.2|1584.4|1584.1|1593.3|

Source: Authors’ calculations.

Note: AIC = Akaike information criterion. BIC = Bayesian information criterion. PH = proportional hazards. PO = proportional odds.

37
<!-- Start of picture text --> 110.00<br>105.00 -<br>100.00<br>95.00<br>90.00 -<br>85.00<br>80.00<br>75.00 ~<br>70.00<br>65.00<br>650.00, ppgp<br>1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016<br>=——Primary (SIC 1-2) = Secondary (SIC 3-5) <=Tertiary (SIC 6 - 9)<br><!-- End of picture text -->
# **<u>Appendix Table 8: The Kitagawa-Oaxaca-Blinder Decomposition of Harvest Value by Age</u>**

||(1)|(2)|(3)|(4)|(5)|(6)|
|---|---|---|---|---|---|---|
|||Age 15-29|||Age 30-64||
|VARIABLES|Overall|Endow.|Coeff.|Overall|Endow.|Coeff.|
|Male|11.862***|||12.001***|||
||(0.051)|||(0.021)|||
|Female|11.001***|||11.064***|||
||(0.053)|||(0.029)|||
|Raw Difference|0.861***|||0.937***|||
||(0.074)|||(0.035)|||
|Difference due to3|0.482***|||0.545***|||
|Endowments|(0.082)|||(0.035)|||
|Difference due to|0.379***|||0.392***|||
|Coefficients|(0.097)|||(0.045)|||
|Individual Age||0.060|10.521*||-0.030*|-1.855|
|||(0.086)|(5.851)||(0.018)|(1.414)|
|Individual Age Squared||-0.047|-5.210*||0.027|0.765|
|||(0.079)|(3.107)||(0.017)|(0.699)|
|Number of Adults in HH||0.016|0.132||0.020***|0.145***|
|||(0.015)|(0.123)||(0.005)|(0.056)|
|Number of Children Aged 0-5||-0.054**|-0.115||0.032***|0.001|
|In HH||(0.025)|(0.108)||(0.007)|(0.029)|
|Individual owns a Financial||-0.006|0.001||0.014|-0.002|
|Account||(0.019)|(0.032)||(0.009)|(0.011)|
|Individual is Married||0.009|0.181||0.070*|0.357*|
|||(0.014)|(0.288)||(0.041)|(0.215)|
|Individual is Divorced/Married||-0.005|0.014||-0.062|0.123|
|/Separated||(0.012)|(0.012)||(0.044)|(0.075)|
|Individual Completed||-0.006*|-0.004||0.000|-0.002|
|Secondary Schooling||(0.003)|(0.004)||(0.001)|(0.002)|
|Individual has a Vehicle||0.035|0.270***||0.003|-0.018|
|(bicycle, motorcycle, car)||(0.027)|(0.086)||(0.017)|(0.061)|
|Household owns Mechanized||0.050***|0.066||0.049***|0.013|
|Agriculture Equipment||(0.017)|(0.049)||(0.007)|(0.025)|
|Area of Plot of Land||0.001|0.035||0.007|-0.010|
|||(0.006)|(0.110)||(0.005)|(0.012)|
|Area of Plot of Land Squared||-0.002|-0.014||-0.004|0.004|
|||(0.006)|(0.032)||(0.003)|(0.004)|
|Land Distance from House||0.000|-0.143***||0.000|-0.095***|
|||(0.001)|(0.048)||(0.000)|(0.018)|
|Crop Grown for Export||0.133***|-0.011**||0.164***|-0.003|
|||(0.021)|(0.005)||(0.010)|(0.003)|
|Manager of Farm is the Owner||0.014|0.023||-0.007|0.012|
|||(0.016)|(0.053)||(0.011)|(0.031)|

52
# **References in Appendix S3**

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Card, D., Kluve, J., and Weber, A. (2015). What works? A meta analysis of recent active labor market program evaluations. _NBER Working Paper 21431_ .

Cho, Y. and Honorati, M. (2014). Entrepreneurship programs in developing countries: A meta regression analysis. _Labour Economics_ , 28: 110–130.

DerSimonian, R. and Laird, N. (1986). Meta-analysis in clinical trials. _Controlled Clinical Trials_ , 7(3): 177–188.

Fernandes, D., Lynch, Jr., J.G., and Netemeyer, R.G. (2014). Financial literacy, financial education, and downstream financial behaviors _. Management Science_ , 60(8): 1861–1883.

Harbord, R. M., Higgins, J. P., et al. (2008). Meta-regression in Stata. _Stata Journal_ , 8(4):493– 519.

Hedges, L.V., Tipton, E., and Johnson, M. C. (2010). Robust variance estimation in metaregression with dependent effect size estimate, _Research Synthesis Methods_ 1(1): 39-65.

Knapp, G. and Hartung, J. (2003). Improved tests for a random effects meta-regression with a single covariate. _Statistics in Medicine_ , 22(17): 2693–2710.

Lipsey, M.W. and Wilson, D.B. (2001). _Practical meta-analysis._ Sage, Thousand Oaks, CA.

Miller, M., Reichelstein, J., Salas, C., and Zia, B. (2015). Can you help someone become financially capable? A meta-analysis of the literature. _World Bank Research Observer_ , 30(2): 220–246.

Stanley, T. D. (2001). Wheat from chaff: Meta-analysis as quantitative literature review. _Journal of Economic Perspectives_ , 15(3): 131–150.

Stanley, T. D. (2008). Meta-regression methods for detecting and estimating empirical effects in the presence of publication selection. _Oxford Bulletin of Economics and Statistics_ , 70(1):103–127.

Stanley, T. D. and Doucouliagos, H. (2012). _Meta-regression analysis in economics and business_ , Routledge, New York, NY.

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Tanner-Smith, E. E. and Tipton, E. (2014). Robust variance estimation with dependent effect sizes: practical considerations including a software tutorial in Stata and SPSS. _Research Synthesis Methods_ , 5(1):13–30.

51
# _Licensed oil_

2.4 In addition to all the general taxes imposed at the national and sub-national levels, oil companies pay taxes that are specific to the oil sector. These include: (1) export duties; (2) oil excises; (3) royalties; (4) bonuses; and (5) geological fees.

2.5 The _export duty_ was introduced in January 1992 as a wedge between domestic and foreign prices. The rate was initially set at ECU 26 per ton of crude oil and gradually reduced to ECU 15 per ton in mid-1996, as part of the Government's commitment to bringing domestic energy prices in line with international ones. The oil export duty was completely phased out in 1997, but then reinstated in 1999 as world prices took off. Export duties accrue to the federal government. In 2000, the governmental Commission on Foreign Trade Protection adopted a new floating tariff system, whereby the export duty is tied to the market price of oil. Table 5 shows the progressive relationship between oil prices and export duties. This scale refers to crude oil exports beyond the Customs Union of Russia, Belarus, Kazakhstan, Kyrgyzstan and Tajikistan. Though the scale does not have power of law, the government broadly follows in when it sets export duties by resolution. The duty currently in force is in the highest bracket, somewhat independently of fluctuations in the oil price.

Table 5. Oil Export Duty and Oil Prices

|Oilprice(averagepriceof<br>the Uralsblendforthe<br>precedingmonth,US$/ton)|Exportduty<br>(EUR/tonexported)|
|---|---|
|<12.5|0|
|12.5-15.0|2|
|15.0-17.5|_5_|
|17.5-20.0|9|
|20.0-22.5|14|
|22.5-25.0|20|
|25.0-27.5|27|
|27.5-30.0|34|
|30.0-32.5|41|
|>32.5|48|

Source: Brunswick Warburg (2000).

2.6 The _excise tax_ was set up in August 1992 at a rate of 18% of oil sales value _(ad valorem)._ It was then differentiated to account for variations in production costs (0% for high-cost producers, 24% for medium-cost producers, and 42% for low-cost producers). Excise rates increased as export tax rates decreased. In April 1994, it was transformed into an _ad quantum_ (specific) tax indexed to the RUBIUSD exchange rate. The range selected was RUB 0-85 per ton, with an average of RUB 55. Article 46 in the current law "On the Subsoil" clearly states that the system of mineral excises must reflect the economic and geographic conditions of each deposit, _i.e._ the differential rent (GOR 1992). Nevertheless, the Russian government has never worked out the corresponding excise rates, so this provision remains hollow. Instead, in January 2000, the range was eliminated and the excise 12
<!-- Start of picture text --> oO<br>neSa<br>Be<br>S<br>=<br>sta<br>=<br>wi<br>TM<br>o<br>1800 1850 1900 1950 2000<br>Year<br>————_ Agriculture ———— Manufacturing<br>————__ Services<br><!-- End of picture text --> FIGURE 20.1. Theshare of US employment in agriculture, manufacturing and services, 1800-2000.

<!-- Start of picture text --> Agriculture and Development<br>Agriculture Share in Employment & GDP Per Capita in PPP, 2007<br>=<br>* MASIGR NOR<br>RE size<br>. ABT<br>o ISR *OXP sR * SVIGRC<br>o-<br>E *MLT* “see + ECS *PRT<br>£8 “ "RUS RY Sa HRY.MEXzy. pot‘ “TUR<br>re} * BGRANVsLAF uRY *cRI- CA «seer . IRN * ROM<br>loate>) *<br>a *PER *DOM *AZE + THA<br>*UKR<br>re) * PRY LKA * PHL MING sion’ MAR<br>*MDA<br>* PAK<br>() 10 20 30 40<br>Employment in agriculture (% of total employment)<br>Source: WDI. Income in 2005 constant USD, PPP<br><!-- End of picture text -->
In practice, however, landowners are easily able to ensure that the record-of-rights in land do not make mention of any existing tenants. During our field investigation, many instances were reported in which land rights were mis-recorded during survey and settlement operations. Tenants also have good reason to conceal tenancy, as highlighted in Box 12. In 1981-82, an estimated 36 percent of all tenancies in rural Orissa were concealed (Sawant, 1991).

# Box **13: Tenant motivations for concealing tenancy**

Consider this apocryphal tale of a conversation between a politician and a tenant in rural Orissa. The politician said to the tenant, "You have lived on this land for so many years, the land is yours. Register a case against the landlord." The tenant replied, " How can I start a case against him? I know this land is his. How can it suddenly become mine? When I have problems I go to him for help. We live in the same village and we see each other every day. You are here now, but after one hour you will be gone and it will be difficult for me to see you. How can we get their land in our name? It is not good."

# _Source: Mohanti (1990)_

# _4.4.3 Policy Implications_

# The discussion in the preceding sections highlights that:

- tenancy (whether sharecropping or fixed-rent) is as widespread as it is illegal;

- * the rent paid by the lessee is almost always in excess of the legally stipulated rent of one-fourth of the gross produce;

- most of those seeking to lease-in land are either the landless or the small and marginal farmers suggesting that lease markets are of great importance as a means for the rural poor to gain access to land; and

- both landowners and tenants have their own reasons to conceal tenancy arrangements.

# Tlhis suggests that:

- tenancy is a response to missing markets, especially for labour;

- rent is determined more by prevalent social and cultural norms of fairness than by state legislation;

- most transactions are non-exploitative as they take place often within the same class of farmers, and are an effective mechanism for the poor and the landless to increase access to land, and

- * concealing of tenancy affects the tenants adversely by denying them security of tenure and consequently limiting their access to institutional credit.

The key policy issue is to devise an effective mechanism to deregulate tenancy but at the same time legally to register and make possible the protection of tenants' rights in land. The question of deregulating tenancy has been discussed in a meeting of the Orissa Cabinet in which opinion was divided on whether or not to grant tenants new rights. Many Members feared a political backlash against any move to grant heritable and transferable rights to the tenants. In principle, at least, it is possible to specify a 'middle ground' in the hierarchy of rights in which tenants' use rights are 60
The descriptive statistics of the main LFS outcome variables are presented in Table A.1, Panel B. All statistics are presented as the means of the pre-COVID-19 period (i.e., all months in 2018 and 2019). On average, an HB individual worked for over 47 hours per week, earning approximately 5.8 million VND per month (approximately 250 USD). While average workload is mostly homogeneous across industries and firm sizes, average monthly income varies, between 5.3 million VND in the accommodation, food services, and entertainment sector (lowest) to over 7.2 million VND in transportation.

## **2.4 Face-to-Face Index**

The Face-to-Face Index measure (F2F) measures the importance and intensity of F2F interactions with other people for more than 900 occupations based on 4-digit International Standard of Industrial Classification (ISIC) codes (Avdiu and Nayyar, 2020). The measure utilizes the Occupational Information Network (O*Net) database for the United States, which provides scores on the importance of four work activities: (1) establishing and maintaining personal relationships; (2) assisting and caring for others; (3) performing for or working directly with the public; and (4) selling to or influencing others.<sup>17</sup> Table A.2 provides illustrative examples of F2F index scores and their closest 4-digit industry matches that appear in our data. Generally, manufacturing and wholesaling activities receive smaller F2F scores relative to accommodation or retails, reflecting the lower face-to-face intensity required to conduct business.

We calculate a commune-level baseline F2F measure by taking the average 2019 F2F index of all household businesses in a commune. Figure A.1 provides a visualization of the geographical distribution of the F2F measure. Visually, there is significant variation in the intensity distribution of the index, or equivalently, significant geographical variation in business lockdown exposure.<sup>18</sup>

# **3 Estimation Strategy**

To identify the impact of COVID-19 on Vietnamese household businesses, we estimate the following equation:

> 17Following Oldenski (2012), the score from each of the four work activities is aggregated for each firm in the O*Net database. The arithmetic average of the scores of all firms in each occupation then denotes the F2F index for that occupation.

> 18In Figure A.1, we aggregate our F2F indices to the district level for visualization purposes. There are 670 districts in the country, which comprises of over 11,000 communes.

7
The questions asked by these widely available surveys help understand different dimensions of social cohesion, including bonding, bridging, and linking. For instance, the World Values Survey asks respondents whether they feel insecure or experience racism within their own neighborhood, which attempts to capture dynamics within communities by specifying the geographical parameter for the respondent’s consideration. The Afro barometer, asks, _“generally speaking, would you say that most people can be trusted or that you must be very careful in dealing with people?”._ While the question does not explicitly ask for attitudes towards out-groups, Delhey, Newton and Welzel (2011) found that in most countries respondents interpret “most people” as outgroups and the indicator as a result is often used to capture this element of social cohesion.

In addition to existing surveys, there are also predesigned tools that facilitate primary data collection at a community level. The toolkit jointly developed by Mercy Corps and the World Bank includes a set of questions designed to capture the underlying constructs of bonding, bridging, and linking in the context of communitydriven development programs. The toolkit includes questions to understand relationships, resources, trust, collective action norms, civic engagement, identity, belonging and even specific attitudes towards out-groups.

The UNDP Social Cohesion and Resilience Index was developed to address the dearth of perception-based data in FCV contexts. Now used in countries including South Sudan, Nepal, the Maldives, Liberia, and Ukraine, it was initially developed for use in Cyprus to track trust in institutions, human security, and satisfaction with civic life. It includes data on the capacity of public institutions, perceptions of institutional corruption, negative stereotypes, anxiety about interactions with adversarial groups, social distance (weak ties) and threats, and active discrimination towards others.

# _A DVANTAGES_

Using existing indices is often appealing for purposes of analysis and diagnostics, because data is widely available across countries and collected at frequent intervals. The World Values Survey for instance, has been conducted since 1981 at regular intervals for a wide set of countries that has continued to expand – in 2020, it was conducted in 80 countries. Addressing data gaps in developing countries, the regional barometers cover many countries within their regions, capturing regionally meaningful variation and allowing for regional-level contextualization of the questions asked. For instance, the Afro barometer covered 37 countries in Africa in its sixth round in 2021, was conducted in 115 languages and represented 76 percent of the African population. Given that surveys are conducted at regular intervals, they allow for meaningful comparison over time and across countries – both useful dimensions to consider in social cohesion diagnostics.

15 | P a g e
<!-- Start of picture text --> 90<br>80<br>70<br>60<br>ov<br>w 50<br>Oo<br>wv<br>o<br>40<br><<br>ro)<br>@ 30<br>cc<br>20<br>10<br>0<br>15 25 35 45 55 65 75 95<br>-10<br>Percentile. of global .income distribution. . .<br><!-- End of picture text -->
37

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