rafmacalaba/data-use-mentions-extended huggingface dataset:
2020; de Lucio et al., 2020) or sector attributes such as contract intensity, amenability to remote work, GVC intensity, intensity of durable products in output, dependence on external finance, reliance on letters of credit, product skill labor intensity and product complexity (Bas et al., 2022; Constantinescu et al., 2022; Crozet et al., 2022; Espitia et al., 2021). Among firm characteristics that matter, some are external attributes, such as size (Bricongne et al., 2012; Cirera et al., 021a), global engagement (Constantinescu et al., 2022; de Lucio et al., 2022), and intensity of GVC participation (Constantinescu et al., 2022; Borino et al., 2021; Brucal et al., 2021; de Lucio et al., 2022; Hyun et al., 2020), while others are internal traits such as management capabilities (Grover and Karplus, 2021; Hyun et al., 2020; Brucal et al., 2021; Borino et al., 2021) and pre-crisis digital readiness (Cirera et al., 2022; Constantinescu et al., 2022).

The rest of the paper is organized as follows. Section 2 describes the data. Section 3 specifies the empirical strategy. Section 4 presents the results. Section 5 concludes.

# **2. Data and Descriptive Statistics**

Our work combines data from the World Bank Business Pulse Surveys (BPS) and the COVID-19 follow-up of the World Bank Enterprise Surveys (WBES) for the (almost) two years between April 2020 and September 2021. Since the onset of the pandemic, these surveys have been monitoring the impact of the pandemic on the private sector across the world on critical dimensions of business performance, such as sales. For most countries, the sampling frame for the BPS was based on firm censuses from Statistics Agencies or business listings from Ministries of Finance or Economy and 4
=1]<br>0.88|0.45|0.42***|
|[0.33]|[0.50]|(0.02)|
|**_Panel C:_**_Labor market characteristics_|||
|Unemployed [=1]<br>0.10|0.11|-0.01|
|[0.30]|[0.31]|(0.01)|
|Self-employed [=1]<br>0.33|0.44|-0.10***|
|[0.47]|[0.50]|(0.02)|
|Informal [=1]<br>0.42|0.88|-0.46***|
|[0.49]|[0.33]|(0.02)|
|Work contract [=1]<br>0.29|0.09|0.20***|
|[0.45]|[0.28]|(0.01)|
|Observations(Allpanels)<br>2,157|1,460|3,617|

_Notes:_ Columns (1) and (2) describe the mean values for the adults born in Colombia and Venezuelan, respectively. The last column illustrates a mean difference test between both groups. Standard errors are reported in brackets. Male is a dichotomous variable [=1] if the individual is male, Age is measured in years, and the years of education are determined by identifying the highest educational level attained by each individual and associating it with the corresponding number of years, which were standardized using the guidelines provided by the Ministry of Education. Married [=1] if the respondent indicates being married or declares a consensual union couple in the survey . Sisb ́en Enrollment [=1] indicates
# <mark>CAPACITY REMUNERATION MECHANISMS</mark>

If resource adequacy and price volatility issues are paramount, and decision-makers are reluctant to use instruments of scarcity pricing and energy-only constructs, alternative market mechanisms are needed to promote resource adequacy, which in most cases take the form of some type of capacity payment. This has been the primary mechanism in several prominent markets, including the forward capacity market in PJM and administered capacity payment mechanisms in some of the cost-based pools in Latin America and the Republic of Korea.

There is significant support in the literature on the need for some form of capacity mechanism to overcome the limitations of the energy-only market. For example, (Cramton & Stoft, 2006) criticized the suitability of the “pure” energy-only approach for driving incentives for investment and operations appropriately. They argue that introducing the missing money must be restored without reintroducing the market power problems currently controlled by price suppression. With a stable functioning capacity market, adequate reliability would be ensured, market power would be reduced, and the risk premium associated with the industry would be minimal. Similar argumentation is provided by (P. L. Joskow, 2006a), where it is stated that <mark>according to data from the US and some other countries, wholesale electricity markets and operating reserves do not provide sufficient incentive to stimulate generating capacity in accordance with reliability requirements. A claim is made that the solution to this problem may be the introduction of well-designed forward capacity markets, which should e</mark> nhance the efficiency of spot wholesale markets and <mark>provides incentives for investing in generating capacity in a manner consistent with operating reliability criteria applied by system operators. The authors echoed the same argument during the</mark> _Symposium on ‘Capacity Markets’_ (P. L. Joskow, 2013) _._ (Cramton & Ockenfels, 2011) describe the forward procurement of reliability options, which refers to physical capacity bundled with the option to supply energy at a spot price above a strike price.
1561/101.00000039.

- Chen, Xi and William D. Nordhaus. 2011. “Using Luminosity Data as a Proxy for Economic Statistics.” _Proceedings of the National Academy of Sciences_ 108 (21): 8589–94. https://doi.org/10.1073/PNAS.1017031108.

- Correia, Sergio. 2016. “A Feasible Estimator for Linear Models with Multi-Way Fixed Effects.” _Working Paper_ . http://scorreia.com/research/hdfe.pdf.

- Del Valle, Alejandro, Robert J. R. Elliott, Eric Strobl and Meng Tong. 2018. “The Short-Term Economic Impact of Tropical Cyclones: Satellite Evidence from Guangdong Province.” _Economics of Disasters and Climate Change_ 2 (3): 225–35. https://doi.org/10.1007/S41885-018-0028-3.

- Del Valle, Alejandro, Mathilda Eriksson, Oscar A. Ishizawa and Juan Jose Miranda. 2020. “Mangroves Protect Coastal Economic Activity from Hurricanes.” _Proceedings of the National Academy of Sciences_ 117 (1): 265–70. https://doi.org/10.1073/PNAS.1911617116.

- Doll, Christopher N.H., Jan Peter Muller and Jeremy G. Morley. 2006. “Mapping Regional Economic Activity from Night-Time Light Satellite Imagery.” _Ecological Economics_ 57 (1): 75–92. https://doi.org/10.1016/J.ECOLECON.2005.03.007.

- Donato, Daniel C., J. Boone Kauffman, Daniel Murdiyarso, Sofyan Kurnianto, Melanie Stidham and Markku Kanninen. 2011. “Mangroves among the Most Carbon-Rich Forests in the Tropics.” _Nature Geoscience_ 4 (5): 293–97. https://doi.org/10.1038/ngeo1123.

- Duke, N.C., Z. S. Pinzon and M. C. T. Prada. 1997. “Large-Scale Damage to Mangrove
_Fareed M. A. Hassan, ECSPE_ 2 Tax Law enacted in March 1993 resulted in a substantial increase in tax rates and the number of tax brackets.

In late 1997 Bulgaria adopted major tax reform measures to be effective in 1998. These measures include: (i) reducing marginal tax rates on both personal and corporate incomes to 40 percent; (ii) aligning the top marginal personal tax rate with the corporate tax rate to diminish the incentive to shift income among the categories of personal income, partnership income, and corporate income; (iii) reducing tax burdens on the poor by raising the exemption level by 20 percent; and (vi) flattening personal income tax rate schedules as the number of tax brackets has been halved. However, the new personal income tax structure tax resulting from the 1997 amendment to the 1993 Personal Income Tax Law resembles, to a greater extent, the 1992 tax system'.

Given the 1992, 1993, and 1997 reform episodes, the similarity of the 1997 personal income tax schedule to the 1992 structure, and the availability of a detailed household budget survey for 1992, this paper attempts to examine the revenue adequacy and equity effects of Bulgaria's tax reform experience. In particular, the paper seeks to analyze the following two issues, which should be of broader interest in Bulgaria, and in other EMEs. First, it examines the effects of the 1992 personal income tax system on revenue and post-tax income distribution. Second, it explores if an alternative, simpler tax structure with lower tax rates could achieve at least equal revenue and distributional objectives as the 1992 system, and demonstrates tfhat a system with lower rates is superior in terms of revenues and distributional effects.

To answer the second, counterfactual question, which is of particular interest for tax policy, I examine the effects of simplifying the existing personal income tax system in three interrelated areas: (i) reducing the number of tax brackets, (ii) lowering tax rates, and (iii) 1/The 1997 system
significant at 10% level. In contrast, male refugees from Somalia are significantly less likely to participate in family farm activities (18 percentage points) compared to their hosts.

In general, the disaggregated results suggest that self-employment and agricultural employment are driving the observed differences among refugees and hosts, reflecting the limited availability of paid employment opportunities in refugee-hosting regions. Among women, we only see significant differences in Benishangul-Gumuz region where refugees are less likely to participate in self-employment and/or farm activities compared to women in hosts. This difference directly links with refugees’ lack of agricultural land, while women in hosts have greater access to land and about half participates in farm activities.

# <mark>Individual-Level Participation</mark>

We now turn to examine the determinants of wage employment for working age individuals (aged 15-65). Estimates are reported in as average (marginal) effects for women and men by refugee status.

The results from <mark>Table</mark> _<mark>5</mark>_ suggests that there are significant gender differences, at individual level, both among refugee and host community population. The gender gap is large among hosts where women are 15 percentage points less likely to participate in wage employment compared to men. Similarly, there is a 9-percentage points gender difference among refugees, in which women are significantly less likely to be employed. Overall, our results suggest that women (both refugee and hosts) are more likely to suffer from lack of employment opportunities compared to men. These results are consistent with findings in the descriptive statistics (Table 1), which show large differences in employment between women and men.

Again, at the individual level, education increases the probability of participation in wage employment for both women and men, both among hosts and refugees. While secondary and tertiary education are strongly associated with female employment, tertiary education has a large and strong effect on male employment.

Displacement duration also significantly increases participation in employment, with women who are displaced for at least
changes. The change is wage is a driver for labor supplies and migration flows across three different labor markets: rural, informal urban and formal urban. The other micro model, NIDS, estimates the consumer expenditure shares of the CGE model. The advantage of using a separate micro model NIDS over the standard CGE specifications for households (e.g., Cobb–Douglas or the linear expenditure specification) is that price and income elasticities are allowed to be different across household categories.

Morales et al. (2017) incorporate the informal sector in their CGE model when they analyze the impact on Bolivian wage and labor policy of decreasing international prices of its main exports. The definition of the informal sector in this study covers a wider spectrum of labor supply. It includes all non-remunerated workers, self-account workers without tax registration, and workers without long-term social security or contracts. The informal sector accounts for 80% of Bolivia’s labor force. The CGE model used in the study represents the labor mobility between the formal and the informal sectors through a labor supply function supplemented with a reservation wage curve. It allows the both-way (formal to informal and vice versa) migration of the labor force. The study assumes the unemployment elasticity of real wage is negative for the informal sector and zero for the formal sector. This means the wage curve is downward sloping in the informal labor market and horizontal in the formal labor market. The study defines four types of labor: formal, informal, private and government workers. But, the public sector does not hire informal workers. Labor supply between the formal and the informal sector is distributed through a CET functional form.

One of the biggest challenges to incorporate the informal sector into the CGE modeling is the lack of data. The social accounting matrix (SAM), the main database for CGE modeling, accounts data for the formal sector or aggregate sector, which includes both formal and informal activities without distinction. Some existing studies have illustrated how to incorporate the informal sector into the SAM
-0.104|-0.187|
|Sector contestability: Natural Monopoly|-0.131***|-0.131|
||-0.024|-0.151|
|Sector contestability: Partially Contestable|-0.031|-0.031|
||-0.031|-0.261|
|Size :100-250|0.494***|0.494***|
||-0.032|-0.121|
|Size :20-100|-0.046*|-0.046|
||-0.025|-0.111|
|Size :250+|0.432***|0.432***|
||-0.033|-0.145|
|Age :16-25 years|0.081**|0.081|
||-0.035|-0.119|
|Age :26-50 years|0.03|0.03|
||-0.036|-0.112|
|Age :50+ years|-0.298***|-0.298|
||-0.047|-0.272|
|Age :6-15 years|-0.043|-0.043|
||-0.035|-0.121|

50 Forthcoming analytical analysis is exploring these relationships in more detail including a comparison in performance between private owned companies and SOEs using ORBIS data.

32
produce extinction risk ratings for GBIF species as soon as their georeferenced occurrence data are it provides a transparent view ofthe relationship between risk ratings and the predictive indicators that we have developed in Section 2.

3.1.1 Model Estimation We focus on species in five IUCN Red List categories: Least Critical (LC), Near Threatened (NT), Vulnerable (VU), Endangered (EN) and Critically Endangered (CR) (IUCN 2022). We incorporate the IUCN categories into a model that predicts each species’ extinction threat status from the values vulnerable). Ordered probability models can employ probit or logit estimators, depending upon the distribution of model errors (normal for probit; logistic for logit). We chose ordered logit estimation because it provides a somewhat better fit to the data.

Our model estimation dataset comprises the 87,731 mapped GBIF species that have been assigned depart from machine learning convention by using an explicit model, but we allow for highly nonlinear relations among model variables with a translog specification.

translog estimation terms (the squared logs and log-interactions of risk indicators). Table 1 presents pairwise correlations for the variables in the five estimating equations. The correlations are almost all very small, indicating that collinearity of model variables is not a problem in this difficult to interpret. Table 2 provides a useful partial view by reporting results for a basic model that is restricted to the logs of the relevant risk indicator variables. In this model, the t-statistic for the estimated coefficient of each variable provides an approximate measure of its relative variable across the five estimates, with the appropriate sign and very high significance in all cases. Formal protection has the appropriate sign and consistently high significance in all three terrestrial The translog specification incorporates the logs and squared logs of all model variables, as well as all pairwise interactions among them. It is a second-order approximation to an unknown set of nonlinear relationships.
hold spent a non-zero amount on items from that category, and 0 otherwise. The items represent goods that are more likely to be dropped from (included in) a household’s consumption basket when the household is subjected to negative (positive) income shocks, thereby improving the model’s ability to capture temporal changes in economic conditions. Figure 6 in Appendix 2.1 examines the evolution of premium good consumption in CPHS overtime.

# _Implementation_

The consumption model is estimated using data from the NSS and then applied to impute NSS-type consumption into the CPHS. Success of this approach is contingent on: (a) model stability (i.e., the model estimated in 2011 continues to apply in the years for which the CPHS is available), (b) sufficient predictive power of the model (i.e., the predictors are sufficiently correlated with household consumption), and that (c) the predictors are consistently measured between the two surveys. The analysis presented in section 3 confirms that the levels and trends in demographics, education and asset ownership observed in the (reweighted) CPHS are consistent with those observed in the nationally representative benchmark surveys.<sup>22</sup> The regression model, estimated separately for urban and rural India, is shown in Table 2 (the coefficients related to principal industry of occupation is suppressed for formatting purposes). The urban model fits the data better when compared to the rural model, which is consistent with consumption models estimated to data from other countries (e.g. Douidich, et al., 2016). Overall, families with higher share of dependents (members below the ages of 18 and above the age of 61) are associated with lower consumption per capita, while households with more educated members and greater ownership of assets are associated with higher per capita consumption.

|**Dependent variable:** Log consumption per capita|(1)<br>Rural|(1)<br>Urban|
|--
, 2021); 2) examine self-reported data on employment and income before and during COVID-19. Linear first difference regression with robust standard errors and chi-square tests were used to generate p-values for differences in total income, sex work income, price per client, and clients per week, food security, and place of work pre- and during COVID-19. Balanced panels were generated to compare outcomes by the study population in each wave. Total and sex work income in waves 1 and 2 were adjusted for inflation (10.4% wave 1, 3.7% wave 2).<sup>22</sup> Food security was expressed both as a binary variable and categorized by frequency.

4
effects, as is done in column 2, reduces the estimated reduction in the markets share premium on being connected to Suharto associated with regime change to 1.2 percentage points. Column 3 replicates the specification presented in column 2 but now uses time-varying explanatory variables, which allows us to use the full sample. This hardly impacts the estimated reduction in the connectedness premium, which is now more precisely estimated to fall by 1.3 percentage points.

Columns 4-7 presents results from our event study specifications, in which both the PC family dummy and other firm and industry controls are interacted with a full set of year dummies. The regressions presented in columns 4, 5 and 6 are analogous to those presented in columns 1, 2 and 3, respectively. The OLS regression presented in column 4 confirms that connected firms enjoyed a significant market share premium before his fall. After his fall, this market share premium on Suharto connections was not only much smaller, but also no longer significant (except in 2003).<sup>13</sup> Replicating this specification but including firm fixed effects, as is done in column 5, which presents our preferred specification (1), yields similar results. The coefficients on the interactions between Suharto era year dummies (i.e. 1993, 1994 and 1995) and being politically connected are typically small and not significant, attesting to the absence of pretrends. By contrast, the coefficients on the interaction between being a Suharto family firm and the postSuharto era year dummies are consistently negative, hovering between -1.7 and -0.4 percentage points. They are significant at the 5% level in 2001 and at the 10% level in 2002. These results are also depicted in Figure C4.1 in the online appendix. When we estimate the same specification using time-varying measures, as is done in column 6, we find slightly larger reductions in the connectedness premium, which, are significant at the 5% level in 2001 and 2002, and at the
domestic employers, the share of foreign sector employment in total skill-intensive employment accordingly rose from 35.3 percent in 2000 to 55.7 percent in 2007 suggesting the importance of foreign firms for upgrading Vietnam’s industrial structure. It is also noted that, unlike domestic private and state enterprises, foreign-owned skill-intensive enterprises tend to employ more females than males, becoming another factor contributing to a rise in female intensity in foreign sector employment.<sup>15</sup> Overall, high export-orientation and high female intensity in foreign firms in Vietnam are consistent with the view that expansion of exports has boosted the demand for female labor in manufacturing in developing countries (e.g., Ozler, 2000; Rama, 2003; Wood, 1991).<sup>16</sup>

# **3. Impacts of Foreign Ownership on Wages**

# **3.1. Data and Summary Statistics**

The _Vietnam Household Living Standard Survey_ 2004 (VHLSS 2004) was conducted by the GSO of Vietnam with the technical support of the World Bank and is generally recognized to be of high quality and representative of all of Vietnam. The VHLSS 2004 consists of 9,188 households of which about half were also represented in the sample for VHLSS 2002. Table 2 shows the summary statistics of individuals from 15 to 59 years of age who responded to the survey’s ownership question. The ownership information is based on an individual’s “most timeconsuming job in the last 12 months”. The ownership categories consist of “foreign”, “state”, “private”, “informal wage”, and “self-employment” sectors.<sup>17</sup> Table 2 reveals that the “formal”

> 15 This trend appears to reflect largely the employment expansion in certain export-oriented and female-intensive sectors such as electronics. For instance, in terms of the electrical machinery (VSIC 31), the female intensity among foreign firms registered at 80.5 percent in 2004 as opposed to
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